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Sample records for nonnegative matrix families

  1. Convex nonnegative matrix factorization with manifold regularization.

    Science.gov (United States)

    Hu, Wenjun; Choi, Kup-Sze; Wang, Peiliang; Jiang, Yunliang; Wang, Shitong

    2015-03-01

    Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including computer vision, pattern recognition, text mining, and signal processing. However, nonnegative entries are usually required for the data matrix in NMF, which limits its application. Besides, while the basis and encoding vectors obtained by NMF can represent the original data in low dimension, the representations do not always reflect the intrinsic geometric structure embedded in the data. Motivated by manifold learning and Convex NMF (CNMF), we propose a novel matrix factorization method called Graph Regularized and Convex Nonnegative Matrix Factorization (GCNMF) by introducing a graph regularized term into CNMF. The proposed matrix factorization technique not only inherits the intrinsic low-dimensional manifold structure, but also allows the processing of mixed-sign data matrix. Clustering experiments on nonnegative and mixed-sign real-world data sets are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Max–min distance nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan; Gao, Xin

    2014-01-01

    Nonnegative Matrix Factorization (NMF) has been a popular representation method for pattern classification problems. It tries to decompose a nonnegative matrix of data samples as the product of a nonnegative basis matrix and a nonnegative coefficient matrix. The columns of the coefficient matrix can be used as new representations of these data samples. However, traditional NMF methods ignore class labels of the data samples. In this paper, we propose a novel supervised NMF algorithm to improve the discriminative ability of the new representation by using the class labels. Using the class labels, we separate all the data sample pairs into within-class pairs and between-class pairs. To improve the discriminative ability of the new NMF representations, we propose to minimize the maximum distance of the within-class pairs in the new NMF space, and meanwhile to maximize the minimum distance of the between-class pairs. With this criterion, we construct an objective function and optimize it with regard to basis and coefficient matrices, and slack variables alternatively, resulting in an iterative algorithm. The proposed algorithm is evaluated on three pattern classification problems and experiment results show that it outperforms the state-of-the-art supervised NMF methods.

  3. Max–min distance nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-10-26

    Nonnegative Matrix Factorization (NMF) has been a popular representation method for pattern classification problems. It tries to decompose a nonnegative matrix of data samples as the product of a nonnegative basis matrix and a nonnegative coefficient matrix. The columns of the coefficient matrix can be used as new representations of these data samples. However, traditional NMF methods ignore class labels of the data samples. In this paper, we propose a novel supervised NMF algorithm to improve the discriminative ability of the new representation by using the class labels. Using the class labels, we separate all the data sample pairs into within-class pairs and between-class pairs. To improve the discriminative ability of the new NMF representations, we propose to minimize the maximum distance of the within-class pairs in the new NMF space, and meanwhile to maximize the minimum distance of the between-class pairs. With this criterion, we construct an objective function and optimize it with regard to basis and coefficient matrices, and slack variables alternatively, resulting in an iterative algorithm. The proposed algorithm is evaluated on three pattern classification problems and experiment results show that it outperforms the state-of-the-art supervised NMF methods.

  4. On affine non-negative matrix factorization

    DEFF Research Database (Denmark)

    Laurberg, Hans; Hansen, Lars Kai

    2007-01-01

    We generalize the non-negative matrix factorization (NMF) generative model to incorporate an explicit offset. Multiplicative estimation algorithms are provided for the resulting sparse affine NMF model. We show that the affine model has improved uniqueness properties and leads to more accurate id...

  5. Enforced Sparse Non-Negative Matrix Factorization

    Science.gov (United States)

    2016-01-23

    proposals quotas opec legislation revenue england ico iraq vote passenger yen producer iranian surplus Figure 4. Example NMF with and without sparsity...preprint arXiv:1007.0380, 2010. [22] A. Cichocki and P. Anh-Huy, “Fast local algorithms for large scale nonnegative matrix and tensor factorizations

  6. Shifted Non-negative Matrix Factorization

    DEFF Research Database (Denmark)

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

    2007-01-01

    Non-negative matrix factorization (NMF) has become a widely used blind source separation technique due to its part based representation and ease of interpretability. We currently extend the NMF model to allow for delays between sources and sensors. This is a natural extension for spectrometry data...

  7. Non-negative Matrix Factorization for Binary Data

    DEFF Research Database (Denmark)

    Larsen, Jacob Søgaard; Clemmensen, Line Katrine Harder

    We propose the Logistic Non-negative Matrix Factorization for decomposition of binary data. Binary data are frequently generated in e.g. text analysis, sensory data, market basket data etc. A common method for analysing non-negative data is the Non-negative Matrix Factorization, though...... this is in theory not appropriate for binary data, and thus we propose a novel Non-negative Matrix Factorization based on the logistic link function. Furthermore we generalize the method to handle missing data. The formulation of the method is compared to a previously proposed method (Tome et al., 2015). We compare...... the performance of the Logistic Non-negative Matrix Factorization to Least Squares Non-negative Matrix Factorization and Kullback-Leibler (KL) Non-negative Matrix Factorization on sets of binary data: a synthetic dataset, a set of student comments on their professors collected in a binary term-document matrix...

  8. Nonnegative Matrix Factorizations Performing Object Detection and Localization

    Directory of Open Access Journals (Sweden)

    G. Casalino

    2012-01-01

    Full Text Available We study the problem of detecting and localizing objects in still, gray-scale images making use of the part-based representation provided by nonnegative matrix factorizations. Nonnegative matrix factorization represents an emerging example of subspace methods, which is able to extract interpretable parts from a set of template image objects and then to additively use them for describing individual objects. In this paper, we present a prototype system based on some nonnegative factorization algorithms, which differ in the additional properties added to the nonnegative representation of data, in order to investigate if any additional constraint produces better results in general object detection via nonnegative matrix factorizations.

  9. Incremental Nonnegative Matrix Factorization for Face Recognition

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    Wen-Sheng Chen

    2008-01-01

    Full Text Available Nonnegative matrix factorization (NMF is a promising approach for local feature extraction in face recognition tasks. However, there are two major drawbacks in almost all existing NMF-based methods. One shortcoming is that the computational cost is expensive for large matrix decomposition. The other is that it must conduct repetitive learning, when the training samples or classes are updated. To overcome these two limitations, this paper proposes a novel incremental nonnegative matrix factorization (INMF for face representation and recognition. The proposed INMF approach is based on a novel constraint criterion and our previous block strategy. It thus has some good properties, such as low computational complexity, sparse coefficient matrix. Also, the coefficient column vectors between different classes are orthogonal. In particular, it can be applied to incremental learning. Two face databases, namely FERET and CMU PIE face databases, are selected for evaluation. Compared with PCA and some state-of-the-art NMF-based methods, our INMF approach gives the best performance.

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

    KAUST Repository

    Alghamdi, Masheal M.

    2014-01-01

    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

  11. 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.

  12. Multiplicative algorithms for constrained non-negative matrix factorization

    KAUST Repository

    Peng, Chengbin; Wong, Kachun; Rockwood, Alyn; Zhang, Xiangliang; Jiang, Jinling; Keyes, David E.

    2012-01-01

    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

  13. Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation

    DEFF Research Database (Denmark)

    Brouwer, Thomas; Frellsen, Jes; Liò, Pietro

    2017-01-01

    In this paper, we study the trade-offs of different inference approaches for Bayesian matrix factorisation methods, which are commonly used for predicting missing values, and for finding patterns in the data. In particular, we consider Bayesian nonnegative variants of matrix factorisation and tri......-factorisation, and compare non-probabilistic inference, Gibbs sampling, variational Bayesian inference, and a maximum-a-posteriori approach. The variational approach is new for the Bayesian nonnegative models. We compare their convergence, and robustness to noise and sparsity of the data, on both synthetic and real...

  14. 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.

  15. Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan; AbdulJabbar, Mustafa Abdulmajeed

    2012-01-01

    Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

  16. 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.

  17. 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.

  18. 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.

  19. Multi-view clustering via multi-manifold regularized non-negative matrix factorization.

    Science.gov (United States)

    Zong, Linlin; Zhang, Xianchao; Zhao, Long; Yu, Hong; Zhao, Qianli

    2017-04-01

    Non-negative matrix factorization based multi-view clustering algorithms have shown their competitiveness among different multi-view clustering algorithms. However, non-negative matrix factorization fails to preserve the locally geometrical structure of the data space. In this paper, we propose a multi-manifold regularized non-negative matrix factorization framework (MMNMF) which can preserve the locally geometrical structure of the manifolds for multi-view clustering. MMNMF incorporates consensus manifold and consensus coefficient matrix with multi-manifold regularization to preserve the locally geometrical structure of the multi-view data space. We use two methods to construct the consensus manifold and two methods to find the consensus coefficient matrix, which leads to four instances of the framework. Experimental results show that the proposed algorithms outperform existing non-negative matrix factorization based algorithms for multi-view clustering. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Non-negative matrix factorization in texture feature for classification of dementia with MRI data

    Science.gov (United States)

    Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

    2017-07-01

    This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

  5. Single-channel source separation using non-negative matrix factorization

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard

    -determined and its solution relies on making appropriate assumptions concerning the sources. This dissertation is concerned with model-based probabilistic single-channel source separation based on non-negative matrix factorization, and consists of two parts: i) three introductory chapters and ii) five published...... papers. The first part introduces the single-channel source separation problem as well as non-negative matrix factorization and provides a comprehensive review of existing approaches, applications, and practical algorithms. This serves to provide context for the second part, the published papers......, in which a number of methods for single-channel source separation based on non-negative matrix factorization are presented. In the papers, the methods are applied to separating audio signals such as speech and musical instruments and separating different types of tissue in chemical shift imaging....

  6. Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent

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    Zunyi Tang

    2013-01-01

    Full Text Available Sparse representation of signals via an overcomplete dictionary has recently received much attention as it has produced promising results in various applications. Since the nonnegativities of the signals and the dictionary are required in some applications, for example, multispectral data analysis, the conventional dictionary learning methods imposed simply with nonnegativity may become inapplicable. In this paper, we propose a novel method for learning a nonnegative, overcomplete dictionary for such a case. This is accomplished by posing the sparse representation of nonnegative signals as a problem of nonnegative matrix factorization (NMF with a sparsity constraint. By employing the coordinate descent strategy for optimization and extending it to multivariable case for processing in parallel, we develop a so-called parallel coordinate descent dictionary learning (PCDDL algorithm, which is structured by iteratively solving the two optimal problems, the learning process of the dictionary and the estimating process of the coefficients for constructing the signals. Numerical experiments demonstrate that the proposed algorithm performs better than the conventional nonnegative K-SVD (NN-KSVD algorithm and several other algorithms for comparison. What is more, its computational consumption is remarkably lower than that of the compared algorithms.

  7. 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...

  8. 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....

  9. Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.

    Science.gov (United States)

    Ma, Yuanyuan; Hu, Xiaohua; He, Tingting; Jiang, Xingpeng

    2016-12-01

    Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H T ) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering. Copyright © 2016. Published by Elsevier Inc.

  10. 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

  11. 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.

  12. 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...

  13. 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....

  14. 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....

  15. Non-negative matrix factorization by maximizing correntropy for cancer clustering

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Xiaolei; Gao, Xin

    2013-01-01

    Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

  16. Non-negative matrix factorization by maximizing correntropy for cancer clustering

    KAUST Repository

    Wang, Jim Jing-Yan

    2013-03-24

    Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  5. 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...

  6. 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.

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

    Science.gov (United States)

    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

  8. 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.

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

    Science.gov (United States)

    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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  18. 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)

  19. 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

  20. 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...

  1. 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

  2. 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.

  3. 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.

  4. 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.

  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

  6. 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.

  7. 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

  8. 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

  9. 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

  10. Nonnegativity of uncertain polynomials

    Directory of Open Access Journals (Sweden)

    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.

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. On the nonnegative inverse eigenvalue problem of traditional matrices

    Directory of Open Access Journals (Sweden)

    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.

  10. 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.

  11. 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

  12. Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

    Science.gov (United States)

    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

  13. 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

  14. Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum

    Directory of Open Access Journals (Sweden)

    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.

  15. 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)

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

    Science.gov (United States)

    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.

  17. 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.

  18. 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

  19. 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.…

  20. 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).

  1. 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

  2. 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

  3. 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".

  4. 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)

  5. 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)].

  6. 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...

  7. 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.

  8. 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.

  9. 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...

  10. 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

  11. 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...

  12. 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...

  13. 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.

  14. 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.)

  15. 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

  16. 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.

  17. 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.

  18. 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...

  19. 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....

  20. 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

  1. 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)

  2. 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.

  3. 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.

  4. 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}}}...

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Positivity of Fundamental Matrix and Exponential Stability of Delay Differential System

    Directory of Open Access Journals (Sweden)

    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.

  11. 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

  12. 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.

  13. 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...

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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)

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  13. 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...

  14. 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

  15. 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.

  16. 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

  17. 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...

  18. 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

  19. 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...

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. YKL-40, a mammalian member of the chitinase family, is a matrix protein of specific granules in human neutrophils

    DEFF Research Database (Denmark)

    Volck, B; Price, P A; Johansen, J S

    1998-01-01

    YKL-40, also called human cartilage glycoprotein-39 (HC gp-39), is a member of family 18 glycosyl hydrolases. YKL-40 is secreted by chondrocytes, synovial cells, and macrophages, and recently it has been reported that YKL-40 has a role as an autoantigen in rheumatoid arthritis (RA). The function...... of patients with RA, and the cells are assumed to play a role in joint destruction in that disorder. Therefore, we examined whether neutrophils are a source of YKL-40. YKL-40 was found to colocalize and comobilize with lactoferrin (the most abundant protein of specific granules) but not with gelatinase...... YKL-40 at the myelocyte-metamyelocyte stage, the stage of maturation at which other specific granule proteins are formed. Assuming that YKL-40 has a role as an autoantigen in RA by inducing T cell-mediated autoimmune response, YKL-40 released from neutrophils in the inflamed joint could be essential...

  6. 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...

  7. 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.

  8. Analysis of acoustic cardiac signals for heart rate variability and murmur detection using nonnegative matrix factorization-based hierarchical decomposition

    DEFF Research Database (Denmark)

    Shah, Ghafoor; Koch, Peter; Papadias, Constantinos B.

    2014-01-01

    The detection of heart rate variability (HRV) via cardiac auscultation examination can be a useful and inexpensive tool which, however, is challenging in the presence of pathological signals and murmurs. The aim of this research is to analyze acoustic cardiac signals for HRV and murmur detection...

  9. 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...

  10. 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.

  11. 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.

  12. Facilitating organisational development using a group-based formative assessment and benchmarking method: design and implementation of the International Family Practice Maturity Matrix.

    Science.gov (United States)

    Elwyn, Glyn; Bekkers, Marie-Jet; Tapp, Laura; Edwards, Adrian; Newcombe, Robert; Eriksson, Tina; Braspenning, Jozé; Kuch, Christine; Adzic, Zlata Ozvacic; Ayankogbe, Olayinka; Cvetko, Tatjana; In 't Veld, Kees; Karotsis, Antonis; Kersnik, Janko; Lefebvre, Luc; Mecini, Ilir; Petricek, Goranka; Pisco, Luis; Thesen, Janecke; Turón, José María; van Rossen, Edward; Grol, Richard

    2010-12-01

    Well-organised practices deliver higher-quality care. Yet there has been very little effort so far to help primary care organisations achieve higher levels of team performance and to help them identify and prioritise areas where quality improvement efforts should be concentrated. No attempt at all has been made to achieve a method which would be capable of providing comparisons--and the stimulus for further improvement--at an international level. The development of the International Family Practice Maturity Matrix took place in three phases: (1) selection and refinement of organisational dimensions; (2) development of incremental scales based on a recognised theoretical framework; and (3) testing the feasibility of the approach on an international basis, including generation of an automated web-based benchmarking system. This work has demonstrated the feasibility of developing an organisational assessment tool for primary care organisations that is sufficiently generic to cross international borders and is applicable across a diverse range of health settings, from state-organised systems to insurer-based health economies. It proved possible to introduce this assessment method in 11 countries in Europe and one in Africa, and to generate comparison benchmarks based on the data collected. The evaluation of the assessment process was uniformly positive with the view that the approach efficiently enables the identification of priorities for organisational development and quality improvement at the same time as motivating change by virtue of the group dynamics. We are not aware of any other organisational assessment method for primary care which has been 'born international,' and that has involved attention to theory, dimension selection and item refinement. The principal aims were to achieve an organisational assessment which gains added value by using interaction, engagement comparative benchmarks: aims which have been achieved. The next step is to achieve wider

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

    Directory of Open Access Journals (Sweden)

    Omnia Gamal El-Dien

    2016-03-01

    Full Text Available The open-pollinated (OP family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure.

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Matrix inequalities

    CERN Document Server

    Zhan, Xingzhi

    2002-01-01

    The main purpose of this monograph is to report on recent developments in the field of matrix inequalities, with emphasis on useful techniques and ingenious ideas. Among other results this book contains the affirmative solutions of eight conjectures. Many theorems unify or sharpen previous inequalities. The author's aim is to streamline the ideas in the literature. The book can be read by research workers, graduate students and advanced undergraduates.

  11. Matrix analysis

    CERN Document Server

    Bhatia, Rajendra

    1997-01-01

    A good part of matrix theory is functional analytic in spirit. This statement can be turned around. There are many problems in operator theory, where most of the complexities and subtleties are present in the finite-dimensional case. My purpose in writing this book is to present a systematic treatment of methods that are useful in the study of such problems. This book is intended for use as a text for upper division and gradu­ ate courses. Courses based on parts of the material have been given by me at the Indian Statistical Institute and at the University of Toronto (in collaboration with Chandler Davis). The book should also be useful as a reference for research workers in linear algebra, operator theory, mathe­ matical physics and numerical analysis. A possible subtitle of this book could be Matrix Inequalities. A reader who works through the book should expect to become proficient in the art of deriving such inequalities. Other authors have compared this art to that of cutting diamonds. One first has to...

  12. 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.

  13. Matrix pentagons

    Science.gov (United States)

    Belitsky, A. V.

    2017-10-01

    The Operator Product Expansion for null polygonal Wilson loop in planar maximally supersymmetric Yang-Mills theory runs systematically in terms of multi-particle pentagon transitions which encode the physics of excitations propagating on the color flux tube ending on the sides of the four-dimensional contour. Their dynamics was unraveled in the past several years and culminated in a complete description of pentagons as an exact function of the 't Hooft coupling. In this paper we provide a solution for the last building block in this program, the SU(4) matrix structure arising from internal symmetry indices of scalars and fermions. This is achieved by a recursive solution of the Mirror and Watson equations obeyed by the so-called singlet pentagons and fixing the form of the twisted component in their tensor decomposition. The non-singlet, or charged, pentagons are deduced from these by a limiting procedure.

  14. Matrix pentagons

    Directory of Open Access Journals (Sweden)

    A.V. Belitsky

    2017-10-01

    Full Text Available The Operator Product Expansion for null polygonal Wilson loop in planar maximally supersymmetric Yang–Mills theory runs systematically in terms of multi-particle pentagon transitions which encode the physics of excitations propagating on the color flux tube ending on the sides of the four-dimensional contour. Their dynamics was unraveled in the past several years and culminated in a complete description of pentagons as an exact function of the 't Hooft coupling. In this paper we provide a solution for the last building block in this program, the SU(4 matrix structure arising from internal symmetry indices of scalars and fermions. This is achieved by a recursive solution of the Mirror and Watson equations obeyed by the so-called singlet pentagons and fixing the form of the twisted component in their tensor decomposition. The non-singlet, or charged, pentagons are deduced from these by a limiting procedure.

  15. 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.

  16. 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.

  17. 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

  18. 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...

  19. 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

  20. 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.

  1. 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.

  2. 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....

  3. 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.

  4. 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....

  5. 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.

  6. 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…

  7. 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 ...

  8. 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

  9. 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

  10. 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

  11. 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...

  12. 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

  13. 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.)

  14. Insights into early extracellular matrix evolution: spongin short chain collagen-related proteins are homologous to basement membrane type IV collagens and form a novel family widely distributed in invertebrates.

    Science.gov (United States)

    Aouacheria, Abdel; Geourjon, Christophe; Aghajari, Nushin; Navratil, Vincent; Deléage, Gilbert; Lethias, Claire; Exposito, Jean-Yves

    2006-12-01

    Collagens are thought to represent one of the most important molecular innovations in the metazoan line. Basement membrane type IV collagen is present in all Eumetazoa and was found in Homoscleromorpha, a sponge group with a well-organized epithelium, which may represent the first stage of tissue differentiation during animal evolution. In contrast, spongin seems to be a demosponge-specific collagenous protein, which can totally substitute an inorganic skeleton, such as in the well-known bath sponge. In the freshwater sponge Ephydatia mülleri, we previously characterized a family of short-chain collagens that are likely to be main components of spongins. Using a combination of sequence- and structure-based methods, we present evidence of remote homology between the carboxyl-terminal noncollagenous NC1 domain of spongin short-chain collagens and type IV collagen. Unexpectedly, spongin short-chain collagen-related proteins were retrieved in nonsponge animals, suggesting that a family related to spongin constitutes an evolutionary sister to the type IV collagen family. Formation of the ancestral NC1 domain and divergence of the spongin short-chain collagen-related and type IV collagen families may have occurred before the parazoan-eumetazoan split, the earliest divergence among extant animal phyla. Molecular phylogenetics based on NC1 domain sequences suggest distinct evolutionary histories for spongin short-chain collagen-related and type IV collagen families that include spongin short-chain collagen-related gene loss in the ancestors of Ecdyzosoa and of vertebrates. The fact that a majority of invertebrates encodes spongin short-chain collagen-related proteins raises the important question to the possible function of its members. Considering the importance of collagens for animal structure and substratum attachment, both families may have played crucial roles in animal diversification.

  15. 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...

  16. 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...

  17. 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.

  18. 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

  19. 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)

  20. Family Therapy

    Science.gov (United States)

    Family therapy Overview Family therapy is a type of psychological counseling (psychotherapy) that can help family members improve communication and resolve conflicts. Family therapy is usually provided by a psychologist, ...

  1. Dissolved families

    DEFF Research Database (Denmark)

    Christoffersen, Mogens

    The situation in the family preceding a family separation is studied here, to identify risk factors for family dissolution. Information registers covering prospective statistics about health aspects, demographic variables, family violence, self-destructive behaviour, unemployment, and the spousal...

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. The Matrix Organization Revisited

    DEFF Research Database (Denmark)

    Gattiker, Urs E.; Ulhøi, John Parm

    1999-01-01

    This paper gives a short overview of matrix structure and technology management. It outlines some of the characteristics and also points out that many organizations may actualy be hybrids (i.e. mix several ways of organizing to allocate resorces effectively).......This paper gives a short overview of matrix structure and technology management. It outlines some of the characteristics and also points out that many organizations may actualy be hybrids (i.e. mix several ways of organizing to allocate resorces effectively)....

  7. 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

  8. Apoio matricial em saúde mental entre CAPS e Saúde da Família: trilhando caminhos possíveis Apoyo matricial de salud mental entre CAPS y Salud de la Familia: trillando caminos posibles Matrix support in mental health between Psychosocial Attention Center (CAPS and Family Health Teams: analyzing possible paths

    Directory of Open Access Journals (Sweden)

    Ileno Izídio da Costa

    2013-04-01

    fortalecer la salud mental en atención primaria, con inversiones en la educación permanente, el establecimiento de indicadores y la integración entre los CAPS y SF.This paper discusses the experience of implementing the matrix support in mental health practice that aims to produce higher resolution and accountability for mental health situations in Family Health. The objective of the present study is to analyze the implementation of the mental health "matrix support" practice among Psychosocial Attention Centers (CAPS III and Family Health Teams. This is an action-research that had as instruments operational groups of reflection and the response to questionnaires. Groups were held with Family Health professionals, with CAPS professionals and with professionals from the two services together. Regarding the Family Health services, the result indicated difficulties in addressing mental health cases and the coexistence of sheltering and psychosocial models of care practice in their work. In relation to the CAPS, they indicated the importance of strengthening teamwork to achieve the "matrix support" practice. The results indicate the need to strengthen mental health services within the primary health care, by investing in continuing education, establishing indicators and integrating the CAPS and Family Health services.

  9. 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.  

  10. 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.

  11. 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...

  12. 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.

  13. 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....

  14. 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 ...

  15. Family Meals

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Family Meals KidsHealth / For Parents / Family Meals What's in ... even more important as kids get older. Making Family Meals Happen It can be a big challenge ...

  16. Family Arguments

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Life Listen Español Text Size Email Print Share Family Arguments Page Content Article Body We seem to ...

  17. Family History

    Science.gov (United States)

    Your family history includes health information about you and your close relatives. Families have many factors in common, including their genes, ... as heart disease, stroke, and cancer. Having a family member with a disease raises your risk, but ...

  18. Family Issues

    Science.gov (United States)

    ... Some have two parents, while others have a single parent. Sometimes there is no parent and grandparents raise grandchildren. Some children live in foster families, adoptive families, or in stepfamilies. Families are much ...

  19. Family Disruptions

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Life Listen Español Text Size Email Print Share Family Disruptions Page Content Article Body No matter how ...

  20. 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

  1. Complex matrix model duality

    International Nuclear Information System (INIS)

    Brown, T.W.

    2010-11-01

    The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)

  2. Complex matrix model duality

    Energy Technology Data Exchange (ETDEWEB)

    Brown, T.W.

    2010-11-15

    The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)

  3. Ethical Matrix Manual

    NARCIS (Netherlands)

    Mepham, B.; Kaiser, M.; Thorstensen, E.; Tomkins, S.; Millar, K.

    2006-01-01

    The ethical matrix is a conceptual tool designed to help decision-makers (as individuals or working in groups) reach sound judgements or decisions about the ethical acceptability and/or optimal regulatory controls for existing or prospective technologies in the field of food and agriculture.

  4. 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.

  5. Visualizing Matrix Multiplication

    Science.gov (United States)

    Daugulis, Peteris; Sondore, Anita

    2018-01-01

    Efficient visualizations of computational algorithms are important tools for students, educators, and researchers. In this article, we point out an innovative visualization technique for matrix multiplication. This method differs from the standard, formal approach by using block matrices to make computations more visual. We find this method a…

  6. Challenging the CSCW matrix

    DEFF Research Database (Denmark)

    Jørnø, Rasmus Leth Vergmann; Gynther, Karsten; Christensen, Ove

    2014-01-01

    useful information, we question whether the axis of time and space comprising the matrix pertains to relevant defining properties of the tools, technology or learning environments to which they are applied. Subsequently we offer an example of an Adobe Connect e-learning session as an illustration...

  7. 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

  8. Family Privilege

    Science.gov (United States)

    Seita, John R.

    2014-01-01

    Family privilege is defined as "strengths and supports gained through primary caring relationships." A generation ago, the typical family included two parents and a bevy of kids living under one roof. Now, every variation of blended caregiving qualifies as family. But over the long arc of human history, a real family was a…

  9. Paths correlation matrix.

    Science.gov (United States)

    Qian, Weixian; Zhou, Xiaojun; Lu, Yingcheng; Xu, Jiang

    2015-09-15

    Both the Jones and Mueller matrices encounter difficulties when physically modeling mixed materials or rough surfaces due to the complexity of light-matter interactions. To address these issues, we derived a matrix called the paths correlation matrix (PCM), which is a probabilistic mixture of Jones matrices of every light propagation path. Because PCM is related to actual light propagation paths, it is well suited for physical modeling. Experiments were performed, and the reflection PCM of a mixture of polypropylene and graphite was measured. The PCM of the mixed sample was accurately decomposed into pure polypropylene's single reflection, pure graphite's single reflection, and depolarization caused by multiple reflections, which is consistent with the theoretical derivation. Reflection parameters of rough surface can be calculated from PCM decomposition, and the results fit well with the theoretical calculations provided by the Fresnel equations. These theoretical and experimental analyses verify that PCM is an efficient way to physically model light-matter interactions.

  10. Partially separable t matrix

    International Nuclear Information System (INIS)

    Sasakawa, T.; Okuno, H.; Ishikawa, S.; Sawada, T.

    1982-01-01

    The off-shell t matrix is expressed as a sum of one nonseparable and one separable terms so that it is useful for applications to more-than-two body problems. All poles are involved in this one separable term. Both the nonseparable and the separable terms of the kernel G 0 t are regular at the origin. The nonseparable term of this kernel vanishes at large distances, while the separable term behaves asymptotically as the spherical Hankel function. These properties make our expression free from defects inherent in the Jost or the K-matrix expressions, and many applications are anticipated. As the application, a compact expression of the many-level formula is presented. Also the application is suggested to the breakup threebody problem based on the Faddeev equation. It is demonstrated that the breakup amplitude is expressed in a simple and physically interesting form and we can calculate it in coordinate space

  11. Exactly soluble matrix models

    International Nuclear Information System (INIS)

    Raju Viswanathan, R.

    1991-09-01

    We study examples of one dimensional matrix models whose potentials possess an energy spectrum that can be explicitly determined. This allows for an exact solution in the continuum limit. Specifically, step-like potentials and the Morse potential are considered. The step-like potentials show no scaling behaviour and the Morse potential (which corresponds to a γ = -1 model) has the interesting feature that there are no quantum corrections to the scaling behaviour in the continuum limit. (author). 5 refs

  12. Inside the NIKE matrix

    OpenAIRE

    Brenner, Barbara; Schlegelmilch, Bodo B.; Ambos, Björn

    2013-01-01

    This case describes how Nike, a consumer goods company with an ever expanding portfolio and a tremendous brand value, manages the tradeoff between local responsiveness and global integration. In particular, the case highlights Nike's organizational structure that consists of a global matrix organization that is replicated at a regional level for the European market. While this organizational structure allows Nike to respond to local consumer tastes it also ensures that the company benefits f...

  13. A matrix contraction process

    Science.gov (United States)

    Wilkinson, Michael; Grant, John

    2018-03-01

    We consider a stochastic process in which independent identically distributed random matrices are multiplied and where the Lyapunov exponent of the product is positive. We continue multiplying the random matrices as long as the norm, ɛ, of the product is less than unity. If the norm is greater than unity we reset the matrix to a multiple of the identity and then continue the multiplication. We address the problem of determining the probability density function of the norm, \

  14. Matrix String Theory

    CERN Document Server

    Dijkgraaf, R; Verlinde, Herman L

    1997-01-01

    Via compactification on a circle, the matrix model of M-theory proposed by Banks et al suggests a concrete identification between the large N limit of two-dimensional N=8 supersymmetric Yang-Mills theory and type IIA string theory. In this paper we collect evidence that supports this identification. We explicitly identify the perturbative string states and their interactions, and describe the appearance of D-particle and D-membrane states.

  15. Matrix groups for undergraduates

    CERN Document Server

    Tapp, Kristopher

    2016-01-01

    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 the basic objects of Lie theory: Lie algebras, matrix exponentiation, Lie brackets, maximal tori, homogeneous spaces, and roots. This second edition includes two new chapters that allow for an easier transition to the general theory of Lie groups. From reviews of the First Edition: This book could be used as an excellent textbook for a one semester course at university and it will prepare students for a graduate course on Lie groups, Lie algebras, etc. … The book combines an intuitive style of writing w...

  16. Family Violence and Family Physicians

    Science.gov (United States)

    Herbert, Carol P.

    1991-01-01

    The acronym IDEALS summarizes family physicians' obligations when violence is suspected: to identify family violence; document injuries; educate families and ensure safety for victims; access resources and coordinate care; co-operate in the legal process; and provide support for families. Failure to respond reflects personal and professional experience and attitudes, fear of legal involvement, and lack of knowledge. Risks of intervention include physician burnout, physician overfunctioning, escalation of violence, and family disruption. PMID:21228987

  17. 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)

  18. Matrix tool in the production of integrated care in the family health strategy Instrumento matricial en la producción del cuidado integral en la estrategia salud de la familia Ferramenta matricial na produção do cuidado integral na estratégia saúde da família

    Directory of Open Access Journals (Sweden)

    Maria Salete Bessa Jorge

    2012-01-01

    Full Text Available OBJECTIVE: To analyze how the matrix support in mental health contributes to the production of comprehensive care with an emphasis on the interrelationships between worker / user / family. METHODS: Research with a qualitative approach that used the techniques of interview, focus group and systematic observation. Data analysis was based on critical hermeneutics. RESULTS: Matrix support in mental health assumes pedagogical and technical assistance dimensions, which favor the interaction between primary care teams and specialist teams of the Center for Psychosocial Care (CAPS, ensuring territorially-based care, with interaction of different knowledge and practices. It further contributes to the redirection of the flow of users in seeking care for their health needs, articulating the levels of health care. The worker / user / family interrelationships are closer and allow better accommodation to the demands and bond of the team with the user and his family. However, difficulties such as consolidation of the matrix support, and the predominance of biomedical practice are noted. CONCLUSION: The matrix support contributes an expansion of the spaces of mental health care in the territory, opening living spaces, creation in the reaction of the worker / user / family, and thus configuring itself as a device for the production of integrated care.OBJETIVO: Analizar cómo el apoyo matricial en salud mental contribuye con la producción del cuidado integral con énfasis en las interrelaciones entre trabajador/usuario/familia. MÉTODOS: Investigación con abordaje cualitativo en el que se utilizó las técnicas de entrevista, grupo focal y observación sistemática. El análisis de los datos se fundamentó en la hermenéutica crítica. RESULTADOS: El apoyo matricial en salud mental asume dimensiones pedagógicas y técnico-asistenciales, que favorecen la interacción entre equipos de la atención básica y equipos especializados del Centro de Atenci

  19. Familial gigantism

    NARCIS (Netherlands)

    W.W. de Herder (Wouter)

    2012-01-01

    textabstractFamilial GH-secreting tumors are seen in association with three separate hereditary clinical syndromes: multiple endocrine neoplasia type 1, Carney complex, and familial isolated pituitary adenomas.

  20. Familial gigantism

    Directory of Open Access Journals (Sweden)

    Wouter W. de Herder

    2012-01-01

    Full Text Available Familial GH-secreting tumors are seen in association with three separate hereditary clinical syndromes: multiple endocrine neoplasia type 1, Carney complex, and familial isolated pituitary adenomas.

  1. The cellulose resource matrix.

    Science.gov (United States)

    Keijsers, Edwin R P; Yılmaz, Gülden; van Dam, Jan E G

    2013-03-01

    The emerging biobased economy is causing shifts from mineral fossil oil based resources towards renewable resources. Because of market mechanisms, current and new industries utilising renewable commodities, will attempt to secure their supply of resources. Cellulose is among these commodities, where large scale competition can be expected and already is observed for the traditional industries such as the paper industry. Cellulose and lignocellulosic raw materials (like wood and non-wood fibre crops) are being utilised in many industrial sectors. Due to the initiated transition towards biobased economy, these raw materials are intensively investigated also for new applications such as 2nd generation biofuels and 'green' chemicals and materials production (Clark, 2007; Lange, 2007; Petrus & Noordermeer, 2006; Ragauskas et al., 2006; Regalbuto, 2009). As lignocellulosic raw materials are available in variable quantities and qualities, unnecessary competition can be avoided via the choice of suitable raw materials for a target application. For example, utilisation of cellulose as carbohydrate source for ethanol production (Kabir Kazi et al., 2010) avoids the discussed competition with easier digestible carbohydrates (sugars, starch) deprived from the food supply chain. Also for cellulose use as a biopolymer several different competing markets can be distinguished. It is clear that these applications and markets will be influenced by large volume shifts. The world will have to reckon with the increase of competition and feedstock shortage (land use/biodiversity) (van Dam, de Klerk-Engels, Struik, & Rabbinge, 2005). It is of interest - in the context of sustainable development of the bioeconomy - to categorize the already available and emerging lignocellulosic resources in a matrix structure. When composing such "cellulose resource matrix" attention should be given to the quality aspects as well as to the available quantities and practical possibilities of processing the

  2. Family Issues

    Science.gov (United States)

    ... es Autismo? Family Issues Home / Living with Autism / Family Issues Stress Siblings A child’s autism diagnosis affects every member of the family in different ways. Parents/caregivers must now place their ... may put stress on their marriage, other children, work, finances, and ...

  3. Random matrix theory

    CERN Document Server

    Deift, Percy

    2009-01-01

    This book features a unified derivation of the mathematical theory of the three classical types of invariant random matrix ensembles-orthogonal, unitary, and symplectic. The authors follow the approach of Tracy and Widom, but the exposition here contains a substantial amount of additional material, in particular, facts from functional analysis and the theory of Pfaffians. The main result in the book is a proof of universality for orthogonal and symplectic ensembles corresponding to generalized Gaussian type weights following the authors' prior work. New, quantitative error estimates are derive

  4. Matrix vector analysis

    CERN Document Server

    Eisenman, Richard L

    2005-01-01

    This outstanding text and reference applies matrix ideas to vector methods, using physical ideas to illustrate and motivate mathematical concepts but employing a mathematical continuity of development rather than a physical approach. The author, who taught at the U.S. Air Force Academy, dispenses with the artificial barrier between vectors and matrices--and more generally, between pure and applied mathematics.Motivated examples introduce each idea, with interpretations of physical, algebraic, and geometric contexts, in addition to generalizations to theorems that reflect the essential structur

  5. Matrix Encryption Scheme

    Directory of Open Access Journals (Sweden)

    Abdelhakim Chillali

    2017-05-01

    Full Text Available In classical cryptography, the Hill cipher is a polygraphic substitution cipher based on linear algebra. In this work, we proposed a new problem applicable to the public key cryptography, based on the Matrices, called “Matrix discrete logarithm problem”, it uses certain elements formed by matrices whose coefficients are elements in a finite field. We have constructed an abelian group and, for the cryptographic part in this unreliable group, we then perform the computation corresponding to the algebraic equations, Returning the encrypted result to a receiver. Upon receipt of the result, the receiver can retrieve the sender’s clear message by performing the inverse calculation.

  6. Matrix string partition function

    CERN Document Server

    Kostov, Ivan K; Kostov, Ivan K.; Vanhove, Pierre

    1998-01-01

    We evaluate quasiclassically the Ramond partition function of Euclidean D=10 U(N) super Yang-Mills theory reduced to a two-dimensional torus. The result can be interpreted in terms of free strings wrapping the space-time torus, as expected from the point of view of Matrix string theory. We demonstrate that, when extrapolated to the ultraviolet limit (small area of the torus), the quasiclassical expressions reproduce exactly the recently obtained expression for the partition of the completely reduced SYM theory, including the overall numerical factor. This is an evidence that our quasiclassical calculation might be exact.

  7. 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....

  8. 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

  9. 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

  10. Characterization of supercapacitors matrix

    Energy Technology Data Exchange (ETDEWEB)

    Sakka, Monzer Al, E-mail: Monzer.Al.Sakka@vub.ac.b [Vrije Universiteit Brussel, pleinlaan 2, B-1050 Brussels (Belgium); FEMTO-ST Institute, ENISYS Department, FCLAB, UFC-UTBM, bat.F, 90010 Belfort (France); Gualous, Hamid, E-mail: Hamid.Gualous@unicaen.f [Laboratoire LUSAC, Universite de Caen Basse Normandie, Rue Louis Aragon - BP 78, 50130 Cherbourg-Octeville (France); Van Mierlo, Joeri [Vrije Universiteit Brussel, pleinlaan 2, B-1050 Brussels (Belgium)

    2010-10-30

    This paper treats supercapacitors matrix characterization. In order to cut off transient power peaks and to compensate for the intrinsic limitations in embedded sources, the use of supercapacitors as a storage system is quite suitable, because of their appropriate electrical characteristics (huge capacitance, small series resistance, high specific energy, high specific power), direct storage (energy ready for use), and easy control by power electronic conversion. This use requires supercapacitors modules where several cells connected in serial and/or in parallel, thus a bypass system to balance the charging or the discharging of supercapacitors is required. In the matrix of supercapacitors, six elements of three parallel BCAP0350 supercapacitors in serial connections have been considered. This topology permits to reduce the number of the bypass circuits and it can work in degraded mode. Actually, it allows the system to have more reliability by providing power continually to the load even when there are one or more cells failed. Simulation and experimental results are presented and discussed.

  11. Characterization of supercapacitors matrix

    International Nuclear Information System (INIS)

    Sakka, Monzer Al; Gualous, Hamid; Van Mierlo, Joeri

    2010-01-01

    This paper treats supercapacitors matrix characterization. In order to cut off transient power peaks and to compensate for the intrinsic limitations in embedded sources, the use of supercapacitors as a storage system is quite suitable, because of their appropriate electrical characteristics (huge capacitance, small series resistance, high specific energy, high specific power), direct storage (energy ready for use), and easy control by power electronic conversion. This use requires supercapacitors modules where several cells connected in serial and/or in parallel, thus a bypass system to balance the charging or the discharging of supercapacitors is required. In the matrix of supercapacitors, six elements of three parallel BCAP0350 supercapacitors in serial connections have been considered. This topology permits to reduce the number of the bypass circuits and it can work in degraded mode. Actually, it allows the system to have more reliability by providing power continually to the load even when there are one or more cells failed. Simulation and experimental results are presented and discussed.

  12. 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

  13. Jamaican families.

    Science.gov (United States)

    Miner, Dianne Cooney

    2003-01-01

    The study of the family in the Caribbean originated with European scholars who assumed the universality of the patriarchal nuclear family and the primacy of this structure to the healthy functioning of society. Matrifocal Caribbean families thus were seen as chaotic and disorganized and inadequate to perform the essential tasks of the social system. This article provides a more current discussion of the Jamaican family. It argues that its structure is the result of the agency and adaptation of its members and not the root cause of the increasing marginalization of peoples in the developing world. The article focuses on families living in poverty and how the family structure supports essential family functions, adaptations, and survival.

  14. 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

  15. 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.

  16. 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.

  17. A matrix big bang

    International Nuclear Information System (INIS)

    Craps, Ben; Sethi, Savdeep; Verlinde, Erik

    2005-01-01

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type-IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control

  18. A matrix big bang

    Energy Technology Data Exchange (ETDEWEB)

    Craps, Ben [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands); Sethi, Savdeep [Enrico Fermi Institute, University of Chicago, Chicago, IL 60637 (United States); Verlinde, Erik [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands)

    2005-10-15

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type-IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control.

  19. 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.

  20. 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.

  1. 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.

  2. Family Polymorphism

    DEFF Research Database (Denmark)

    Ernst, Erik

    2001-01-01

    safety and flexibility at the level of multi-object systems. We are granted the flexibility of using different families of kinds of objects, and we are guaranteed the safety of the combination. This paper highlights the inability of traditional polymorphism to handle multiple objects, and presents family...... polymorphism as a way to overcome this problem. Family polymorphism has been implemented in the programming language gbeta, a generalized version of Beta, and the source code of this implementation is available under GPL....

  3. Family literacy

    DEFF Research Database (Denmark)

    Sehested, Caroline

    2012-01-01

    I Projekt familielæsning, der er et samarbejde mellem Nationalt Videncenter for Læsning og Hillerød Bibliotek, arbejder vi med at få kontakt til de familier, som biblioteket ellers aldrig ser som brugere og dermed også de børn, der vokser op i familier, for hvem bøger og oplæsningssituationer ikk...... er en selvfølgelig del af barndommen. Det, vi vil undersøge og ønsker at være med til at udvikle hos disse familier, er det, man kan kalde family literacy....

  4. Community families

    DEFF Research Database (Denmark)

    Jensen, Lotte Groth; Lou, Stina; Aagaard, Jørgen

    2017-01-01

    : Qualitative interviews with members of volunteer families. Discussion: The families were motivated by helping a vulnerable person and to engaging in a rewarding relationship. However, the families often doubted their personal judgment and relied on mental health workers to act as safety net. Conclusion......Background: Social interventions targeted at people with severe mental illness (SMI) often include volunteers. Volunteers' perspectives are important for these interventions to work. The present paper investigates the experiences of volunteer families who befriend a person with SMI. Material...

  5. 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

  6. 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...

  7. 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

  8. 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...

  9. 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)

  10. 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.

  11. This is My Family

    OpenAIRE

    Yeğen, Hale Nur; Çetin, Merve

    2017-01-01

    Me and my family, Families poem, Mother-Father, Brother-Sister, Grandparents, Uncle-Aunt, Cousin, Family, Family handgame, My family tree, Activities (Three In a Family), Digital Games, A family poem, Quiz

  12. Clay matrix voltammetry

    International Nuclear Information System (INIS)

    Perdicakis, Michel

    2012-01-01

    Document available in extended abstract form only. In many countries, it is planned that the long life highly radioactive nuclear spent fuel will be stored in deep argillaceous rocks. The sites selected for this purpose are anoxic and satisfy several recommendations as mechanical stability, low permeability and low redox potential. Pyrite (FeS 2 ), iron(II) carbonate, iron(II) bearing clays and organic matter that are present in very small amounts (about 1% w:w) in soils play a major role in their reactivity and are considered today as responsible for the low redox potential values of these sites. In this communication, we describe an electrochemical technique derived from 'Salt matrix voltammetry' and allowing the almost in-situ voltammetric characterization of air-sensitive samples of soils after the only addition of the minimum humidity required for electrolytic conduction. Figure 1 shows the principle of the developed technique. It consists in the entrapment of the clay sample between a graphite working electrode and a silver counter/quasi-reference electrode. The sample was previously humidified by passing a water saturated inert gas through the electrochemical cell. The technique leads to well-defined voltammetric responses of the electro-active components of the clays. Figure 2 shows a typical voltammogram relative to a Callovo-Oxfordian argillite sample from Bure, the French place planned for the underground nuclear waste disposal. During the direct scan, one can clearly distinguish the anodic voltammetric signals for the oxidation of the iron (II) species associated with the clay and the oxidation of pyrite. The reverse scan displays a small cathodic signal for the reduction of iron (III) associated with the clay that demonstrates that the majority of the previously oxidized iron (II) species were transformed into iron (III) oxides reducible at lower potentials. When a second voltammetric cycle is performed, one can notice that the signal for iron (II

  13. Family problems

    International Nuclear Information System (INIS)

    Goldman, T.

    1984-01-01

    Even Grand Unified Theories may not explain the repetitive pattern of fermions in the Standard Model. The abysmal absence of dynamical information about these ''families'' is emphasized. The evidence that family quantum numbers exist, and are not conserved, is reviewed. It is argued that rare kaon decays may be the best means to obtain more information on this important question

  14. Family problems

    International Nuclear Information System (INIS)

    Goldman, T.

    1984-01-01

    Even Grand Unified Theories may not explain the repetitive pattern of fermions in the Standard Model. The abysmal absence of dynamical information about these families is emphasized. The evidence that family quantum numbers exist, and are not conserved, is reviewed. It is argued that rare kaon decays may be the best means to obtain more information on this important question

  15. Familial hypercholesterolemia

    Science.gov (United States)

    ... and Tests A physical exam may show fatty skin growths called xanthomas and cholesterol deposits in the eye (corneal arcus). The health care provider will ask questions about your personal and family medical history. There may be: A strong family history of ...

  16. FAMILY PYRGOTIDAE.

    Science.gov (United States)

    Mello, Ramon Luciano; Lamas, Carlos José Einicker

    2016-06-14

    Pyrgotidae is a family of endoparasitics flies of beetles with worldwide distribution. The Neotropical fauna is composed by 59 valid species names disposed in 13 genera. The occurrence of Pyrgota longipes Hendel is the first record of the family in Colombia.

  17. 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.

  18. 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.

  19. How to Study a Matrix

    Science.gov (United States)

    Jairam, Dharmananda; Kiewra, Kenneth A.; Kauffman, Douglas F.; Zhao, Ruomeng

    2012-01-01

    This study investigated how best to study a matrix. Fifty-three participants studied a matrix topically (1 column at a time), categorically (1 row at a time), or in a unified way (all at once). Results revealed that categorical and unified study produced higher: (a) performance on relationship and fact tests, (b) study material satisfaction, and…

  20. 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

  1. 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...

  2. 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.

  3. Family matters

    DEFF Research Database (Denmark)

    Kieffer-Kristensen, Rikke; Siersma, Volkert Dirk; Teasdale, Thomas William

    2013-01-01

    brain injury participated. Family and brain injury characteristics were reported by the ill and healthy parents. Children self-reported post-traumatic stress symptoms (PSS) using the Child Impact of Events revised (CRIES). Emotional and behavioural problems among the children were also identified...... by the parents using the Achenbach’s Child Behaviour Checklist (CBCL). RESULTS: The family stress variables relating to the healthy spouse in all six comparisons were significant (p... scores for the children. For the adjusted associations, we again found the family stress variables in the healthy spouse to be related to the risk of emotional and behavioral problems in the children. CONCLUSIONS: The present results suggest that in ABI families, the children’s emotional functioning...

  4. Small Families

    Science.gov (United States)

    ... children of larger families. The financial costs of maintaining a household are lower. It is easier for ... separated from you, hindering the development of new relationships with peers. In fact, you may have that ...

  5. Familial hypercholesterolaemia

    African Journals Online (AJOL)

    Familial hypercholesterolaemia (FH) is a monogenic disorder of low-density lipoprotein (LDL) metabolism. It is characterised .... Figure 2: Cumulative prevalence of physical signs in adult FH patients at the. GSH Lipid .... microvascular trauma.

  6. Family Life

    Science.gov (United States)

    ... family members to do your laundry, walk the dog, or update others on your progress. You may ... parenting while living with cancer . The importance of communication As demonstrated above, good communication is important in ...

  7. Familial dysautonomia

    Science.gov (United States)

    ... condition. FD occurs most often in people of Eastern European Jewish ancestry (Ashkenazi Jews). It is caused ... also be used for prenatal diagnosis. People of Eastern European Jewish background and families with a history ...

  8. Containment Code Validation Matrix

    International Nuclear Information System (INIS)

    Chin, Yu-Shan; Mathew, P.M.; Glowa, Glenn; Dickson, Ray; Liang, Zhe; Leitch, Brian; Barber, Duncan; Vasic, Aleks; Bentaib, Ahmed; Journeau, Christophe; Malet, Jeanne; Studer, Etienne; Meynet, Nicolas; Piluso, Pascal; Gelain, Thomas; Michielsen, Nathalie; Peillon, Samuel; Porcheron, Emmanuel; Albiol, Thierry; Clement, Bernard; Sonnenkalb, Martin; Klein-Hessling, Walter; Arndt, Siegfried; Weber, Gunter; Yanez, Jorge; Kotchourko, Alexei; Kuznetsov, Mike; Sangiorgi, Marco; Fontanet, Joan; Herranz, Luis; Garcia De La Rua, Carmen; Santiago, Aleza Enciso; Andreani, Michele; Paladino, Domenico; Dreier, Joerg; Lee, Richard; Amri, Abdallah

    2014-01-01

    The Committee on the Safety of Nuclear Installations (CSNI) formed the CCVM (Containment Code Validation Matrix) task group in 2002. The objective of this group was to define a basic set of available experiments for code validation, covering the range of containment (ex-vessel) phenomena expected in the course of light and heavy water reactor design basis accidents and beyond design basis accidents/severe accidents. It was to consider phenomena relevant to pressurised heavy water reactor (PHWR), pressurised water reactor (PWR) and boiling water reactor (BWR) designs of Western origin as well as of Eastern European VVER types. This work would complement the two existing CSNI validation matrices for thermal hydraulic code validation (NEA/CSNI/R(1993)14) and In-vessel core degradation (NEA/CSNI/R(2001)21). The report initially provides a brief overview of the main features of a PWR, BWR, CANDU and VVER reactors. It also provides an overview of the ex-vessel corium retention (core catcher). It then provides a general overview of the accident progression for light water and heavy water reactors. The main focus is to capture most of the phenomena and safety systems employed in these reactor types and to highlight the differences. This CCVM contains a description of 127 phenomena, broken down into 6 categories: - Containment Thermal-hydraulics Phenomena; - Hydrogen Behaviour (Combustion, Mitigation and Generation) Phenomena; - Aerosol and Fission Product Behaviour Phenomena; - Iodine Chemistry Phenomena; - Core Melt Distribution and Behaviour in Containment Phenomena; - Systems Phenomena. A synopsis is provided for each phenomenon, including a description, references for further information, significance for DBA and SA/BDBA and a list of experiments that may be used for code validation. The report identified 213 experiments, broken down into the same six categories (as done for the phenomena). An experiment synopsis is provided for each test. Along with a test description

  9. The matrix of inspiration

    Science.gov (United States)

    Oehlmann, Dietmar; Ohlmann, Odile M.; Danzebrink, Hans U.

    2005-04-01

    perform this exchange, as a matrix, understood as source, of new ideas.

  10. 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

  11. 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

  12. 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)

  13. Family welfare.

    Science.gov (United States)

    Sinha, N K

    1992-01-01

    Between 1901-1921, India gained 12.9 million people because mortality remained high. The death rate fell between 1921-1951, but birth rates remained the same. Therefore 110 million people were added--2 times the population increase between 1891-1921. Between 1951-1981, the population increased to 324 million. Socioeconomic development was responsible for most of the downward trend in the birth rate during the 20th century. Even though large families were the norm in early India, religious leaders encouraged small family size. The 1st government family planning clinics in the world opened in Mysore and Bangalore in 1930. Right before Independence, the Bhore Committee made recommendations to reduce population growth such as increasing the age of marriage for girls. Since 1951 there has been a change in measures and policies geared towards population growth with each of the 7 5-Year Plans because policy makers applied what they learned from each previous plan. The 1st 5-Year Plan emphasized the need to understand what factors contribute to population growth. It also integrated family planning services into health services of hospitals and health centers. The government was over zealous in its implementation of the sterilization program (2nd 5-Year Plan, 1956-1961), however, which hurt family planning programs for many years. As of early 1992, sterilization, especially tubectomy, remained the most popular family planning method, however. The 7th 5-Year Plan changed its target of reaching a Net Reproductive Rate of 1 by 2001 to 2006-2011. It set a goal of 100% immunization coverage by 1990 but it did not occur. In 1986, the Ministry of Health and Family Welfare planned to make free contraceptives available in urban and rural areas and to involve voluntary organizations. The government needs to instill measures to increase women's status, women's literacy, and age of marriage as well as to eliminate poverty, ensure old age security, and ensure child survival and

  14. 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.

  15. 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

  16. GoM Diet Matrix

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set was taken from CRD 08-18 at the NEFSC. Specifically, the Gulf of Maine diet matrix was developed for the EMAX exercise described in that center...

  17. 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.

  18. Electromagnetic matrix elements in baryons

    International Nuclear Information System (INIS)

    Lipkin, H.J.; Moinester, M.A.

    1992-01-01

    Some simple symmetry relations between matrix elements of electromagnetic operators are investigated. The implications are discussed for experiments to study hyperon radiative transitions and polarizabilities and form factors. (orig.)

  19. 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.

  20. Random matrix improved subspace clustering

    KAUST Repository

    Couillet, Romain; Kammoun, Abla

    2017-01-01

    This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show

  1. 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.

  2. Matrix Effects in XRF Measurements

    International Nuclear Information System (INIS)

    Kandil, A.T.; Gabr, N.A.; El-Aryan, S.M.

    2015-01-01

    This research treats the matrix effect on XRF measurements. The problem is treated by preparing general oxide program, which contains many samples that represent all materials in cement factories, then by using T rail Lachance m ethod to correct errors of matrix effect. This work compares the effect of using lithium tetraborate or sodium tetraborate as a fluxing agent in terms of accuracy and economic cost

  3. Matrix analysis of electrical machinery

    CERN Document Server

    Hancock, N N

    2013-01-01

    Matrix Analysis of Electrical Machinery, Second Edition is a 14-chapter edition that covers the systematic analysis of electrical machinery performance. This edition discusses the principles of various mathematical operations and their application to electrical machinery performance calculations. The introductory chapters deal with the matrix representation of algebraic equations and their application to static electrical networks. The following chapters describe the fundamentals of different transformers and rotating machines and present torque analysis in terms of the currents based on the p

  4. Staggered chiral random matrix theory

    International Nuclear Information System (INIS)

    Osborn, James C.

    2011-01-01

    We present a random matrix theory for the staggered lattice QCD Dirac operator. The staggered random matrix theory is equivalent to the zero-momentum limit of the staggered chiral Lagrangian and includes all taste breaking terms at their leading order. This is an extension of previous work which only included some of the taste breaking terms. We will also present some results for the taste breaking contributions to the partition function and the Dirac eigenvalues.

  5. 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.

  6. 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.

  7. 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.

  8. Familial macrocephaly

    International Nuclear Information System (INIS)

    Tatsuno, Masaru; Hayashi, Michiko; Iwamoto, Hiroko

    1984-01-01

    We reported 63 macrocephalic children with special emphasis on 16 cases with familial macrocephaly. Of the 16 children with familial macrocephaly, 13 were boys. Foureen parents (13 fathers and 1 mother) had head sizes above 98th percentile. Three of 5 brothers and 5 of 8 sisters also had large heads. The head circumference at birth was known for 14 of the children and it was above the 98th percentile in 7 patients. Subsequent evaluations have shown the head size of these children to be following a normal growth curve. Some of the children were hypotonic as infants, but their development was generally normal. CT scans usually clearly distinguished these children from those with hydorocephalus. The familial macrocephalic children had ventricular measurements which were within the normal range, but absolute measurements of the ventricular size may be misleading, because the CT appearance was of mildly dilated ventricles in half of them. (author)

  9. 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,...

  10. Super families

    International Nuclear Information System (INIS)

    Amato, N.; Maldonado, R.H.C.

    1989-01-01

    The study on phenomena in the super high energy region, Σ E j > 1000 TeV revealed events that present a big dark spot in central region with high concentration of energy and particles, called halo. Six super families with halo were analysed by Brazil-Japan Cooperation of Cosmic Rays. For each family the lateral distribution of energy density was constructed and R c Σ E (R c ) was estimated. For studying primary composition, the energy correlation with particles released separately in hadrons and gamma rays was analysed. (M.C.K.)

  11. 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 ...

  12. 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

  13. 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...

  14. Family Violence.

    Science.gov (United States)

    Emery, Robert E.

    1989-01-01

    Researchers and policymakers have begun to recognize the extent and severity of family violence, particularly its effects on children. But there is much disagreement about the definition of violence, its development, the consequences for victims, and the most effective avenues for intervention. Advances recommendations for further research.…

  15. Family arizing

    NARCIS (Netherlands)

    Croes, M.J.G.; Feijs, L.M.G.; Chen, L.; Djajadingrat, T.; Feijs, L.M.G.; Hu, J.; Kufin, S.H.M.; Rampino, L.; Rodriguez, E.; Steffen, D.

    2015-01-01

    In this demo we show the two main components of the Family Arizing system which allows parents to stay in contact with their child and, in cases of distress, provide the child with a remote comforting hug. The two components to be shown are the active necklace and the active snuggle.

  16. Family Genericity

    DEFF Research Database (Denmark)

    Ernst, Erik

    2006-01-01

    Type abstraction in object-oriented languages embody two techniques, each with its own strenghts and weaknesses. The first technique is extension, yielding abstraction mechanisms with good support for gradual specification. The prime example is inheritance. The second technique is functional abst...... the result as family genericity. The presented language design has been implemented....

  17. FAMILY ASILIDAE.

    Science.gov (United States)

    Wolff, Marta; Lamas, Carlos José Einicker

    2016-06-14

    Asilidae is one of the largest Diptera families with more than 7,000 recognized species worldwide. All their species are predators on arthropods, mainly insects. This catalogue presents 71 species distributed in 26 genera, ten tribes or generic groups and four subfamilies. For each species we present the available geographical information and relevant references.

  18. Family Hypnotherapy.

    Science.gov (United States)

    Araoz, Daniel L.; Negley-Parker, Esther

    1985-01-01

    A therapeutic model to help families activate experiential and right hemispheric functioning through hypnosis is presented in detail, together with a clinical illustration. Different situations in which this model is effective are mentioned and one such set of circumstances is described. (Author)

  19. Familial hypercholesterolaemia

    DEFF Research Database (Denmark)

    Versmissen, Jorie; Vongpromek, Ranitha; Yahya, Reyhana

    2016-01-01

    cholesterol efflux capacity between male familial hypercholesterolaemia (FH) patients with and without CHD relative to their non-FH brothers, and examined HDL constituents including sphingosine-1-phosphate (S1P) and its carrier apolipoprotein M (apoM). RESULTS: Seven FH patients were asymptomatic and six had...... in asymptomatic FH patients may play a role in their apparent protection from premature CHD....

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. Numerical methods in matrix computations

    CERN Document Server

    Björck, Åke

    2015-01-01

    Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated methods is given. Numerical Methods in Matrix Computations is suitable for use in courses on scientific computing and applied technical areas at advanced undergraduate and graduate level. A large bibliography is provided, which includes both historical and review papers as well as recent research papers. This makes the book useful also as a reference and guide to further study and research work. Åke Björck is a professor emeritus at the Department of Mathematics, Linköping University. He is a Fellow of the Society of Industrial and Applied Mathematics.

  5. Lectures on matrix field theory

    CERN Document Server

    Ydri, Badis

    2017-01-01

    These lecture notes provide a systematic introduction to matrix models of quantum field theories with non-commutative and fuzzy geometries. The book initially focuses on the matrix formulation of non-commutative and fuzzy spaces, followed by a description of the non-perturbative treatment of the corresponding field theories. As an example, the phase structure of non-commutative phi-four theory is treated in great detail, with a separate chapter on the multitrace approach. The last chapter offers a general introduction to non-commutative gauge theories, while two appendices round out the text. Primarily written as a self-study guide for postgraduate students – with the aim of pedagogically introducing them to key analytical and numerical tools, as well as useful physical models in applications – these lecture notes will also benefit experienced researchers by providing a reference guide to the fundamentals of non-commutative field theory with an emphasis on matrix models and fuzzy geometries.

  6. [Family violence].

    Science.gov (United States)

    Manoudi, F; Chagh, R; Es-soussi, M; Asri, F; Tazi, I

    2013-09-01

    Family violence is a serious public health problem, the scale of which is seriously increasing in Morocco. Although it has existed for a long time, we ignore the real characteristics of this plague in our country; our work consisted in an epidemiological approach of family violence in Marrakech during 2006. After elaborating a questionnaire, which allows the study of the demographic and social profile of the families, the study of violence exercised in the family and the evaluation of the depression in the women, we led an inquiry amongst 265 women. Analysis of the results obtained has allowed us to underline the following characteristics: 16.6% of the women in our sample had been physically beaten; the young age is a risk factor; the age range most affected by violence is in women between the ages of 30 and 40 and which represent 39% of the battered women; domestic violence touches all the social, economic and cultural classes: in our study, 63% of the women having undergone violence were housewives, 25% were managers and 3% senior executives; family problems were the most important cause of violence in our study, representing 32.32%. Requests for money was the cause in 11.3% of the cases, and imposed sexual relations were found in 6.8% of the cases; alcoholism is an aggravating factor of family violence; 27.3% of the spouses who assaulted their wives were drunk; 52% of the assaulted women were victims of violence in childhood and 36% had been witness to their father's violence; in 63.6% of the cases of violence, the children were witnesses, and in 25% of the cases the children were victims of violence at the same time as their mothers; 50% of the women victims of violence did not react, while 38.6% left home, and 9.1 filed for divorce. Thirty-two percent of the assaulted woman had been traumatised by the aggression; the association of depression and violence was very high, 343% of the battered women in our study suffered from severe depression. This work

  7. Supersymmetry in random matrix theory

    International Nuclear Information System (INIS)

    Kieburg, Mario

    2010-01-01

    I study the applications of supersymmetry in random matrix theory. I generalize the supersymmetry method and develop three new approaches to calculate eigenvalue correlation functions. These correlation functions are averages over ratios of characteristic polynomials. In the first part of this thesis, I derive a relation between integrals over anti-commuting variables (Grassmann variables) and differential operators with respect to commuting variables. With this relation I rederive Cauchy- like integral theorems. As a new application I trace the supermatrix Bessel function back to a product of two ordinary matrix Bessel functions. In the second part, I apply the generalized Hubbard-Stratonovich transformation to arbitrary rotation invariant ensembles of real symmetric and Hermitian self-dual matrices. This extends the approach for unitarily rotation invariant matrix ensembles. For the k-point correlation functions I derive supersymmetric integral expressions in a unifying way. I prove the equivalence between the generalized Hubbard-Stratonovich transformation and the superbosonization formula. Moreover, I develop an alternative mapping from ordinary space to superspace. After comparing the results of this approach with the other two supersymmetry methods, I obtain explicit functional expressions for the probability densities in superspace. If the probability density of the matrix ensemble factorizes, then the generating functions exhibit determinantal and Pfaffian structures. For some matrix ensembles this was already shown with help of other approaches. I show that these structures appear by a purely algebraic manipulation. In this new approach I use structures naturally appearing in superspace. I derive determinantal and Pfaffian structures for three types of integrals without actually mapping onto superspace. These three types of integrals are quite general and, thus, they are applicable to a broad class of matrix ensembles. (orig.)

  8. Supersymmetry in random matrix theory

    Energy Technology Data Exchange (ETDEWEB)

    Kieburg, Mario

    2010-05-04

    I study the applications of supersymmetry in random matrix theory. I generalize the supersymmetry method and develop three new approaches to calculate eigenvalue correlation functions. These correlation functions are averages over ratios of characteristic polynomials. In the first part of this thesis, I derive a relation between integrals over anti-commuting variables (Grassmann variables) and differential operators with respect to commuting variables. With this relation I rederive Cauchy- like integral theorems. As a new application I trace the supermatrix Bessel function back to a product of two ordinary matrix Bessel functions. In the second part, I apply the generalized Hubbard-Stratonovich transformation to arbitrary rotation invariant ensembles of real symmetric and Hermitian self-dual matrices. This extends the approach for unitarily rotation invariant matrix ensembles. For the k-point correlation functions I derive supersymmetric integral expressions in a unifying way. I prove the equivalence between the generalized Hubbard-Stratonovich transformation and the superbosonization formula. Moreover, I develop an alternative mapping from ordinary space to superspace. After comparing the results of this approach with the other two supersymmetry methods, I obtain explicit functional expressions for the probability densities in superspace. If the probability density of the matrix ensemble factorizes, then the generating functions exhibit determinantal and Pfaffian structures. For some matrix ensembles this was already shown with help of other approaches. I show that these structures appear by a purely algebraic manipulation. In this new approach I use structures naturally appearing in superspace. I derive determinantal and Pfaffian structures for three types of integrals without actually mapping onto superspace. These three types of integrals are quite general and, thus, they are applicable to a broad class of matrix ensembles. (orig.)

  9. 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.

  10. Towards Google matrix of brain

    Energy Technology Data Exchange (ETDEWEB)

    Shepelyansky, D.L., E-mail: dima@irsamc.ups-tlse.f [Laboratoire de Physique Theorique (IRSAMC), Universite de Toulouse, UPS, F-31062 Toulouse (France); LPT - IRSAMC, CNRS, F-31062 Toulouse (France); Zhirov, O.V. [Budker Institute of Nuclear Physics, 630090 Novosibirsk (Russian Federation)

    2010-07-12

    We apply the approach of the Google matrix, used in computer science and World Wide Web, to description of properties of neuronal networks. The Google matrix G is constructed on the basis of neuronal network of a brain model discussed in PNAS 105 (2008) 3593. We show that the spectrum of eigenvalues of G has a gapless structure with long living relaxation modes. The PageRank of the network becomes delocalized for certain values of the Google damping factor {alpha}. The properties of other eigenstates are also analyzed. We discuss further parallels and similarities between the World Wide Web and neuronal networks.

  11. Towards Google matrix of brain

    International Nuclear Information System (INIS)

    Shepelyansky, D.L.; Zhirov, O.V.

    2010-01-01

    We apply the approach of the Google matrix, used in computer science and World Wide Web, to description of properties of neuronal networks. The Google matrix G is constructed on the basis of neuronal network of a brain model discussed in PNAS 105 (2008) 3593. We show that the spectrum of eigenvalues of G has a gapless structure with long living relaxation modes. The PageRank of the network becomes delocalized for certain values of the Google damping factor α. The properties of other eigenstates are also analyzed. We discuss further parallels and similarities between the World Wide Web and neuronal networks.

  12. 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

  13. FAMILY BOMBYLIIDAE.

    Science.gov (United States)

    Lamas, Carlos José Einicker; Evenhuis, Neal L

    2016-06-14

    Bombyliidae is one of the largest Diptera families with more than 4,500 recognized species worldwide. Their species vary from robust to thin, and may be small to large (2-20mm) and looks like bees or wasps. They also present great variation in color. Adults can often be seen either resting and sunning themselves on trails, rocks or twigs or feeding on flowering plants as they are nectar feeders. All reared bee flies are predators or parasitoids of arthropods. The Colombian fauna of bombyliids comprises at the moment 22 species, and 12 genera, of which, six are endemic species. Nonetheless, this number may be much higher, as Colombia is a megadiverse country and there are not many specimens of this family deposited in collections all over the world.

  14. 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)

  15. 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.

  16. Parallel Sparse Matrix - Vector Product

    DEFF Research Database (Denmark)

    Alexandersen, Joe; Lazarov, Boyan Stefanov; Dammann, Bernd

    This technical report contains a case study of a sparse matrix-vector product routine, implemented for parallel execution on a compute cluster with both pure MPI and hybrid MPI-OpenMP solutions. C++ classes for sparse data types were developed and the report shows how these class can be used...

  17. Unravelling the nuclear matrix proteome

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Knol, Jaco C; Jimenez, Connie R

    2009-01-01

    The nuclear matrix (NM) model posits the presence of a protein/RNA scaffold that spans the mammalian nucleus. The NM proteins are involved in basic nuclear function and are a promising source of protein biomarkers for cancer. Importantly, the NM proteome is operationally defined as the proteins...

  18. Amorphous metal matrix composite ribbons

    International Nuclear Information System (INIS)

    Barczy, P.; Szigeti, F.

    1998-01-01

    Composite ribbons with amorphous matrix and ceramic (SiC, WC, MoB) particles were produced by modified planar melt flow casting methods. Weldability, abrasive wear and wood sanding examinations were carried out in order to find optimal material and technology for elevated wear resistance and sanding durability. The correlation between structure and composite properties is discussed. (author)

  19. Hyper-systolic matrix multiplication

    NARCIS (Netherlands)

    Lippert, Th.; Petkov, N.; Palazzari, P.; Schilling, K.

    A novel parallel algorithm for matrix multiplication is presented. It is based on a 1-D hyper-systolic processor abstraction. The procedure can be implemented on all types of parallel systems. (C) 2001 Elsevier Science B,V. All rights reserved.

  20. Matrix Metalloproteinases in Myasthenia Gravis

    NARCIS (Netherlands)

    Helgeland, G.; Petzold, A.F.S.; Luckman, S.P.; Gilhus, N.E.; Plant, G.T.; Romi, F.R.

    2011-01-01

    Introduction: Myasthenia gravis (MG) is an autoimmune disease with weakness in striated musculature due to anti-acetylcholine receptor (AChR) antibodies or muscle specific kinase at the neuromuscular junction. A subgroup of patients has periocular symptoms only; ocular MG (OMG). Matrix

  1. Concept for Energy Security Matrix

    International Nuclear Information System (INIS)

    Kisel, Einari; Hamburg, Arvi; Härm, Mihkel; Leppiman, Ando; Ots, Märt

    2016-01-01

    The following paper presents a discussion of short- and long-term energy security assessment methods and indicators. The aim of the current paper is to describe diversity of approaches to energy security, to structure energy security indicators used by different institutions and papers, and to discuss several indicators that also play important role in the design of energy policy of a state. Based on this analysis the paper presents a novel Energy Security Matrix that structures relevant energy security indicators from the aspects of Technical Resilience and Vulnerability, Economic Dependence and Political Affectability for electricity, heat and transport fuel sectors. Earlier publications by different authors have presented energy security assessment methodologies that use publicly available indicators from different databases. Current paper challenges viability of some of these indicators and introduces new indicators that would deliver stronger energy security policy assessments. Energy Security Matrix and its indicators are based on experiences that the authors have gathered as high-level energy policymakers in Estonia, where all different aspects of energy security can be observed. - Highlights: •Energy security should be analysed in technical, economic and political terms; •Energy Security Matrix provides a framework for energy security analyses; •Applicability of Matrix is limited due to the lack of statistical data and sensitivity of output.

  2. The COMPADRE Plant Matrix Database

    DEFF Research Database (Denmark)

    2014-01-01

    COMPADRE contains demographic information on hundreds of plant species. The data in COMPADRE are in the form of matrix population models and our goal is to make these publicly available to facilitate their use for research and teaching purposes. COMPADRE is an open-access database. We only request...

  3. A two-matrix alternative

    Czech Academy of Sciences Publication Activity Database

    Rohn, Jiří

    2013-01-01

    Roč. 26, 15 December (2013), s. 836-841 ISSN 1537-9582 Institutional support: RVO:67985807 Keywords : two-matrix alternative * solution * algorithm Subject RIV: BA - General Mathematics Impact factor: 0.514, year: 2013 http://www.math.technion.ac.il/iic/ ela / ela -articles/articles/vol26_pp836-841.pdf

  4. Regularization in Matrix Relevance Learning

    NARCIS (Netherlands)

    Schneider, Petra; Bunte, Kerstin; Stiekema, Han; Hammer, Barbara; Villmann, Thomas; Biehl, Michael

    A In this paper, we present a regularization technique to extend recently proposed matrix learning schemes in learning vector quantization (LVQ). These learning algorithms extend the concept of adaptive distance measures in LVQ to the use of relevance matrices. In general, metric learning can

  5. [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.

  6. 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...

  7. Family roles as family functioning regulators

    OpenAIRE

    STEPANYAN ARMINE

    2015-01-01

    The author examines the problems of formation and functioning of family roles. Having social roots, family roles appear on individual level by performing the social function of the formation of family as a social institute.

  8. The Role of Family in Family Firms

    OpenAIRE

    Marianne Bertrand; Antoinette Schoar

    2006-01-01

    History is replete with examples of spectacular ascents of family businesses. Yet there are also numerous accounts of family businesses brought down by bitter feuds among family members, disappointed expectations between generations, and tragic sagas of later generations unable to manage their wealth. A large fraction of businesses throughout the world are organized around families. Why are family firms so prevalent? What are the implications of family control for the governance, financing an...

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. The gravitational S-matrix

    CERN Document Server

    Giddings, Steven B

    2010-01-01

    We investigate the hypothesized existence of an S-matrix for gravity, and some of its expected general properties. We first discuss basic questions regarding existence of such a matrix, including those of infrared divergences and description of asymptotic states. Distinct scattering behavior occurs in the Born, eikonal, and strong gravity regimes, and we describe aspects of both the partial wave and momentum space amplitudes, and their analytic properties, from these regimes. Classically the strong gravity region would be dominated by formation of black holes, and we assume its unitary quantum dynamics is described by corresponding resonances. Masslessness limits some powerful methods and results that apply to massive theories, though a continuation path implying crossing symmetry plausibly still exists. Physical properties of gravity suggest nonpolynomial amplitudes, although crossing and causality constrain (with modest assumptions) this nonpolynomial behavior, particularly requiring a polynomial bound in c...

  16. Matrix metalloproteinases in lung biology

    Directory of Open Access Journals (Sweden)

    Parks William C

    2000-12-01

    Full Text Available Abstract Despite much information on their catalytic properties and gene regulation, we actually know very little of what matrix metalloproteinases (MMPs do in tissues. The catalytic activity of these enzymes has been implicated to function in normal lung biology by participating in branching morphogenesis, homeostasis, and repair, among other events. Overexpression of MMPs, however, has also been blamed for much of the tissue destruction associated with lung inflammation and disease. Beyond their role in the turnover and degradation of extracellular matrix proteins, MMPs also process, activate, and deactivate a variety of soluble factors, and seldom is it readily apparent by presence alone if a specific proteinase in an inflammatory setting is contributing to a reparative or disease process. An important goal of MMP research will be to identify the actual substrates upon which specific enzymes act. This information, in turn, will lead to a clearer understanding of how these extracellular proteinases function in lung development, repair, and disease.

  17. Structural properties of matrix metalloproteinases.

    Science.gov (United States)

    Bode, W; Fernandez-Catalan, C; Tschesche, H; Grams, F; Nagase, H; Maskos, K

    1999-04-01

    Matrix metalloproteinases (MMPs) are involved in extracellular matrix degradation. Their proteolytic activity must be precisely regulated by their endogenous protein inhibitors, the tissue inhibitors of metalloproteinases (TIMPs). Disruption of this balance results in serious diseases such as arthritis, tumour growth and metastasis. Knowledge of the tertiary structures of the proteins involved is crucial for understanding their functional properties and interference with associated dysfunctions. Within the last few years, several three-dimensional MMP and MMP-TIMP structures became available, showing the domain organization, polypeptide fold and main specificity determinants. Complexes of the catalytic MMP domains with various synthetic inhibitors enabled the structure-based design and improvement of high-affinity ligands, which might be elaborated into drugs. A multitude of reviews surveying work done on all aspects of MMPs have appeared in recent years, but none of them has focused on the three-dimensional structures. This review was written to close the gap.

  18. Roles within the Family

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Text Size Email Print Share Roles Within the Family Page Content Article Body Families are not democracies. ...

  19. Random matrix improved subspace clustering

    KAUST Repository

    Couillet, Romain

    2017-03-06

    This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

  20. Coherence matrix of plasmonic beams

    DEFF Research Database (Denmark)

    Novitsky, Andrey; Lavrinenko, Andrei

    2013-01-01

    We consider monochromatic electromagnetic beams of surface plasmon-polaritons created at interfaces between dielectric media and metals. We theoretically study non-coherent superpositions of elementary surface waves and discuss their spectral degree of polarization, Stokes parameters, and the for...... of the spectral coherence matrix. We compare the polarization properties of the surface plasmonspolaritons as three-dimensional and two-dimensional fields concluding that the latter is superior....

  1. The Biblical Matrix of Economics

    OpenAIRE

    Grigore PIROŞCĂ; Angela ROGOJANU

    2012-01-01

    The rationale of this paper is a prime pattern of history of economic thought in the previous ages of classic ancient times of Greek and Roman civilizations using a methodological matrix able to capture the mainstream ideas from social, political and religious events within the pages of Bible. The economic perspective of these events follows the evolution of the seeds of economic thinking within the Fertile Crescent, focused on the Biblical patriarchic heroes’ actions, but a...

  2. 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.

  3. 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

  4. The Euclid Statistical Matrix Tool

    Directory of Open Access Journals (Sweden)

    Curtis Tilves

    2017-06-01

    Full Text Available Stataphobia, a term used to describe the fear of statistics and research methods, can result from a lack of improper training in statistical methods. Poor statistical methods training can have an effect on health policy decision making and may play a role in the low research productivity seen in developing countries. One way to reduce Stataphobia is to intervene in the teaching of statistics in the classroom; however, such an intervention must tackle several obstacles, including student interest in the material, multiple ways of learning materials, and language barriers. We present here the Euclid Statistical Matrix, a tool for combatting Stataphobia on a global scale. This free tool is comprised of popular statistical YouTube channels and web sources that teach and demonstrate statistical concepts in a variety of presentation methods. Working with international teams in Iran, Japan, Egypt, Russia, and the United States, we have also developed the Statistical Matrix in multiple languages to address language barriers to learning statistics. By utilizing already-established large networks, we are able to disseminate our tool to thousands of Farsi-speaking university faculty and students in Iran and the United States. Future dissemination of the Euclid Statistical Matrix throughout the Central Asia and support from local universities may help to combat low research productivity in this region.

  5. Family Psychology and Family Therapy in Japan.

    Science.gov (United States)

    Kameguchi, Kenji; Murphy-Shigematsu, Stephen

    2001-01-01

    Reviews the development of family psychology and family therapy in Japan, tracing the origins of these movements, explaining how these fields were activated by the problem of school refusal, and describing an approach to family therapy that has been developed to work with families confronting this problem, as well as preventive programs of family…

  6. 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.

  7. Strengthening Family Practices for Latino Families.

    Science.gov (United States)

    Chartier, Karen G; Negroni, Lirio K; Hesselbrock, Michie N

    2010-01-01

    The study examined the effectiveness of a culturally-adapted Strengthening Families Program (SFP) for Latinos to reduce risks for alcohol and drug use in children. Latino families, predominantly Puerto Rican, with a 9-12 year old child and a parent(s) with a substance abuse problem participated in the study. Pre- and post-tests were conducted with each family. Parental stress, parent-child dysfunctional relations, and child behavior problems were reduced in the families receiving the intervention; family hardiness and family attachment were improved. Findings contribute to the validation of the SFP with Latinos, and can be used to inform social work practice with Puerto Rican families.

  8. 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.

  9. 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....

  10. A quenched c = 1 critical matrix model

    International Nuclear Information System (INIS)

    Qiu, Zongan; Rey, Soo-Jong.

    1990-12-01

    We study a variant of the Penner-Distler-Vafa model, proposed as a c = 1 quantum gravity: 'quenched' matrix model with logarithmic potential. The model is exactly soluble, and exhibits a two-cut branching as observed in multicritical unitary matrix models and multicut Hermitian matrix models. Using analytic continuation of the power in the conventional polynomial potential, we also show that both the Penner-Distler-Vafa model and our 'quenched' matrix model satisfy Virasoro algebra constraints

  11. Confocal microscopy imaging of the biofilm matrix

    DEFF Research Database (Denmark)

    Schlafer, Sebastian; Meyer, Rikke L

    2017-01-01

    The extracellular matrix is an integral part of microbial biofilms and an important field of research. Confocal laser scanning microscopy is a valuable tool for the study of biofilms, and in particular of the biofilm matrix, as it allows real-time visualization of fully hydrated, living specimens...... the concentration of solutes and the diffusive properties of the biofilm matrix....

  12. 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

  13. 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...

  14. 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.

  15. Construction of covariance matrix for experimental data

    International Nuclear Information System (INIS)

    Liu Tingjin; Zhang Jianhua

    1992-01-01

    For evaluators and experimenters, the information is complete only in the case when the covariance matrix is given. The covariance matrix of the indirectly measured data has been constructed and discussed. As an example, the covariance matrix of 23 Na(n, 2n) cross section is constructed. A reasonable result is obtained

  16. 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.

  17. 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.

  18. Family Matters

    Directory of Open Access Journals (Sweden)

    Isabel de Riquer

    2011-04-01

    Full Text Available The scene is at the court of James I of Aragon in the mid-13th c., the place is the royal palace of Barcelona or any of the crown's other possessions, and the dramatis personae include the heir to the throne, prince Peire (future king Peire the Great, and the court's most famous troubadour, Cerverí de Girona (fl. 1259-85. Author of the largest corpus of any Occitan troubadour (114 poems, Cerverì distinguishes himself by the surprises and challenges he presents to his audience: an alba (the most openly erotic genre to the Virgin Mary, the Cobla in sis lengatges (Cobla in Six Languages, the apparently nonsensical Vers estrayn. Cerverì borrows equally from the folk-inspired Galician-Portuguese poetry and from the French tradition, including the chanson de malmariée, where a young woman bemoans being sold off by her family to an old man (gilos, "Jealous" and separated from her youthful doulz amis, some even praying for the death of their husband. Both within that tradition and among Cerverì's three chansons de malmariée, the Gelosesca stands out as "especially determined" to lose her husband, using every "solution" (prayer, black magic, potion or experimenta.

  19. The COMPADRE Plant Matrix Database

    DEFF Research Database (Denmark)

    Salguero-Gomez, Roberto; Jones, Owen; Archer, C. Ruth

    2015-01-01

    growth or decline, such data furthermore help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change, and how to develop successful management tools for endangered or invasive species. 2. Matrix population models summarize the life cycle......1. Schedules of survival, growth and reproduction are key life history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population...

  20. Hexagonal response matrix using symmetries

    International Nuclear Information System (INIS)

    Gotoh, Y.

    1991-01-01

    A response matrix for use in core calculations for nuclear reactors with hexagonal fuel assemblies is presented. It is based on the incoming currents averaged over the half-surface of a hexagonal node by applying symmetry theory. The boundary conditions of the incoming currents on the half-surface of the node are expressed by a complete set of orthogonal vectors which are constructed from symmetrized functions. The expansion coefficients of the functions are determined by the boundary conditions of incoming currents. (author)

  1. Distributively generated matrix near rings

    International Nuclear Information System (INIS)

    Abbasi, S.J.

    1993-04-01

    It is known that if R is a near ring with identity then (I,+) is abelian if (I + ,+) is abelian and (I,+) is abelian if (I*,+) is abelian [S.J. Abbasi, J.D.P. Meldrum, 1991]. This paper extends these results. We show that if R is a distributively generated near ring with identity then (I,+) is included in Z(R), the center of R, if (I + ,+) is included in Z(M n (R)), the center of matrix near ring M n (R). Furthermore (I,+) is included in Z(R) if (I*,+) is included in Z(M n (R)). (author). 5 refs

  2. Geometric phase from dielectric matrix

    International Nuclear Information System (INIS)

    Banerjee, D.

    2005-10-01

    The dielectric property of the anisotropic optical medium is found by considering the polarized photon as two component spinor of spherical harmonics. The Geometric Phase of a polarized photon has been evaluated in two ways: the phase two-form of the dielectric matrix through a twist and the Pancharatnam phase (GP) by changing the angular momentum of the incident polarized photon over a closed triangular path on the extended Poincare sphere. The helicity in connection with the spin angular momentum of the chiral photon plays the key role in developing these phase holonomies. (author)

  3. Matrix regularization of 4-manifolds

    OpenAIRE

    Trzetrzelewski, M.

    2012-01-01

    We consider products of two 2-manifolds such as S^2 x S^2, embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)xSU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N^2 x N^2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S...

  4. Random Matrix Theory and Econophysics

    Science.gov (United States)

    Rosenow, Bernd

    2000-03-01

    Random Matrix Theory (RMT) [1] is used in many branches of physics as a ``zero information hypothesis''. It describes generic behavior of different classes of systems, while deviations from its universal predictions allow to identify system specific properties. We use methods of RMT to analyze the cross-correlation matrix C of stock price changes [2] of the largest 1000 US companies. In addition to its scientific interest, the study of correlations between the returns of different stocks is also of practical relevance in quantifying the risk of a given stock portfolio. We find [3,4] that the statistics of most of the eigenvalues of the spectrum of C agree with the predictions of RMT, while there are deviations for some of the largest eigenvalues. We interpret these deviations as a system specific property, e.g. containing genuine information about correlations in the stock market. We demonstrate that C shares universal properties with the Gaussian orthogonal ensemble of random matrices. Furthermore, we analyze the eigenvectors of C through their inverse participation ratio and find eigenvectors with large ratios at both edges of the eigenvalue spectrum - a situation reminiscent of localization theory results. This work was done in collaboration with V. Plerou, P. Gopikrishnan, T. Guhr, L.A.N. Amaral, and H.E Stanley and is related to recent work of Laloux et al.. 1. T. Guhr, A. Müller Groeling, and H.A. Weidenmüller, ``Random Matrix Theories in Quantum Physics: Common Concepts'', Phys. Rep. 299, 190 (1998). 2. See, e.g. R.N. Mantegna and H.E. Stanley, Econophysics: Correlations and Complexity in Finance (Cambridge University Press, Cambridge, England, 1999). 3. V. Plerou, P. Gopikrishnan, B. Rosenow, L.A.N. Amaral, and H.E. Stanley, ``Universal and Nonuniversal Properties of Cross Correlations in Financial Time Series'', Phys. Rev. Lett. 83, 1471 (1999). 4. V. Plerou, P. Gopikrishnan, T. Guhr, B. Rosenow, L.A.N. Amaral, and H.E. Stanley, ``Random Matrix Theory

  5. 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.

  6. 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.

  7. Interpolation of rational matrix functions

    CERN Document Server

    Ball, Joseph A; Rodman, Leiba

    1990-01-01

    This book aims to present the theory of interpolation for rational matrix functions as a recently matured independent mathematical subject with its own problems, methods and applications. The authors decided to start working on this book during the regional CBMS conference in Lincoln, Nebraska organized by F. Gilfeather and D. Larson. The principal lecturer, J. William Helton, presented ten lectures on operator and systems theory and the interplay between them. The conference was very stimulating and helped us to decide that the time was ripe for a book on interpolation for matrix valued functions (both rational and non-rational). When the work started and the first partial draft of the book was ready it became clear that the topic is vast and that the rational case by itself with its applications is already enough material for an interesting book. In the process of writing the book, methods for the rational case were developed and refined. As a result we are now able to present the rational case as an indepe...

  8. 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.

  9. 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)

  10. 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...

  11. Bequeathing Family Continuity.

    Science.gov (United States)

    Spanier, Graham B.

    1989-01-01

    Notes that many children who experience abuse, family disruption, or poverty reach adulthood with a strong commitment to family life. Questions whether changes in American families are indicators of pathology, deterioration, and instability; and asks how dysfunctional families transmit commitment to the concept of family to succeeding generations.…

  12. The Reconstituted Family

    OpenAIRE

    Talbot, Yves

    1981-01-01

    The reconstituted or step-family is becoming more prevalent. The physician who cares for families should be acquainted with the different aspects of such family structure and family functioning. This will enable professionals to better understand and assist their patients, by anticipating the different stresses related to the new family formation, and supporting their adaptation.

  13. 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

  14. 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.

  15. Family Capital: Implications for Interventions with Families

    Science.gov (United States)

    Belcher, John R.; Peckuonis, Edward V.; Deforge, Bruce R.

    2011-01-01

    Social capital has been extensively discussed in the literature as building blocks that individuals and communities utilize to leverage system resources. Similarly, some families also create capital, which can enable members of the family, such as children, to successfully negotiate the outside world. Families in poverty confront serious…

  16. The Biblical Matrix of Economics

    Directory of Open Access Journals (Sweden)

    Grigore PIROŞCĂ

    2012-05-01

    Full Text Available The rationale of this paper is a prime pattern of history of economic thought in the previous ages of classic ancient times of Greek and Roman civilizations using a methodological matrix able to capture the mainstream ideas from social, political and religious events within the pages of Bible. The economic perspective of these events follows the evolution of the seeds of economic thinking within the Fertile Crescent, focused on the Biblical patriarchic heroes’ actions, but also on the empires which their civilization interacted to. The paper aims to discover the path followed by the economic doctrines from the Bible in order to find a match with economic actuality of present days.

  17. Familial Pulmonary Fibrosis

    Science.gov (United States)

    ... Education & Training Home Conditions Familial Pulmonary Fibrosis Familial Pulmonary Fibrosis Make an Appointment Find a Doctor Ask a ... more members within the same family have Idiopathic Pulmonary Fibrosis (IPF) or any other form of Idiopathic Interstitial ...

  18. Family Activities for Fitness

    Science.gov (United States)

    Grosse, Susan J.

    2009-01-01

    This article discusses how families can increase family togetherness and improve physical fitness. The author provides easy ways to implement family friendly activities for improving and maintaining physical health. These activities include: walking, backyard games, and fitness challenges.

  19. Normal Functioning Family

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Español Text Size Email Print Share Normal Functioning Family Page Content Article Body Is there any way ...

  20. Improving Family Communications

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Listen Español Text Size Email Print Share Improving Family Communications Page Content Article Body How can I ...

  1. 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.

  2. 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...

  3. 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.

  4. Petz recovery versus matrix reconstruction

    Science.gov (United States)

    Holzäpfel, Milan; Cramer, Marcus; Datta, Nilanjana; Plenio, Martin B.

    2018-04-01

    The reconstruction of the state of a multipartite quantum mechanical system represents a fundamental task in quantum information science. At its most basic, it concerns a state of a bipartite quantum system whose subsystems are subjected to local operations. We compare two different methods for obtaining the original state from the state resulting from the action of these operations. The first method involves quantum operations called Petz recovery maps, acting locally on the two subsystems. The second method is called matrix (or state) reconstruction and involves local, linear maps that are not necessarily completely positive. Moreover, we compare the quantities on which the maps employed in the two methods depend. We show that any state that admits Petz recovery also admits state reconstruction. However, the latter is successful for a strictly larger set of states. We also compare these methods in the context of a finite spin chain. Here, the state of a finite spin chain is reconstructed from the reduced states of a few neighbouring spins. In this setting, state reconstruction is the same as the matrix product operator reconstruction proposed by Baumgratz et al. [Phys. Rev. Lett. 111, 020401 (2013)]. Finally, we generalize both these methods so that they employ long-range measurements instead of relying solely on short-range correlations embodied in such local reduced states. Long-range measurements enable the reconstruction of states which cannot be reconstructed from measurements of local few-body observables alone and hereby we improve existing methods for quantum state tomography of quantum many-body systems.

  5. Error bounds for nonnegative dynamic models

    Czech Academy of Sciences Publication Activity Database

    van Dijk, N. M.; Sladký, Karel

    1999-01-01

    Roč. 101, č. 2 (1999), s. 449-474 ISSN 0022-3239 R&D Projects: GA ČR GA402/96/0420 Institutional research plan: AV0Z1075907 Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.536, year: 1999

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. COMPOSITION OF FOWLPOX VIRUS AND INCLUSION MATRIX.

    Science.gov (United States)

    RANDALL, C C; GAFFORD, L G; DARLINGTON, R W; HYDE, J

    1964-04-01

    Randall, Charles C. (University of Mississippi School of Medicine, Jackson), Lanelle G. Gafford, Robert W. Darlington, and James M. Hyde. Composition of fowlpox virus and inclusion matrix. J. Bacteriol. 87:939-944. 1964.-Inclusion bodies of fowlpox virus infection are especially favorable starting material for the isolation of virus and inclusion matrix. Electron micrographs of viral particles and matrix indicated a high degree of purification. Density-gradient centrifugation of virus in cesium chloride and potassium tartrate was unsatisfactory because of inactivation, and clumping or disintegration. Chemical analyses of virus and matrix revealed significant amounts of lipid, protein, and deoxyribonucleic acid, but no ribonucleic acid or carbohydrate. Approximately 47% of the weight of the virus and 83% of the matrix were extractable in chloroform-methanol. The lipid partitions of the petroleum ether extracts were similar, except that the phospholipid content of the matrix was 2.2 times that of the virus. Viral particles were sensitive to diethyl ether and chloroform.

  13. 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

  14. Families and family therapy in Hong Kong.

    Science.gov (United States)

    Tse, Samson; Ng, Roger M K; Tonsing, Kareen N; Ran, Maosheng

    2012-04-01

    Family therapy views humans not as separate entities, but as embedded in a network of relationships, highlighting the reciprocal influences of one's behaviours on one another. This article gives an overview of family demographics and the implementation of family therapy in Hong Kong. We start with a review of the family demographics in Hong Kong and brief notes on families in mainland China. Demographics show that the landscape has changed markedly in the past decade, with more cross-border marriages, an increased divorce rate, and an ageing overall population - all of which could mean that there is increasing demand for professional family therapy interventions. However, only a limited number of professionals are practising the systems-based approach in Hong Kong. Some possible reasons as to why family therapy is not well disseminated and practised are discussed. These reasons include a lack of mental health policy to support family therapy, a lack of systematic family therapy training, and a shortage of skilled professionals. Furthermore, challenges in applying the western model in Chinese culture are also outlined. We conclude that more future research is warranted to investigate how family therapy can be adapted for Chinese families.

  15. 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.

  16. Covariance matrix estimation for stationary time series

    OpenAIRE

    Xiao, Han; Wu, Wei Biao

    2011-01-01

    We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or Fourier transforms...

  17. A companion matrix for 2-D polynomials

    International Nuclear Information System (INIS)

    Boudellioua, M.S.

    1995-08-01

    In this paper, a matrix form analogous to the companion matrix which is often encountered in the theory of one dimensional (1-D) linear systems is suggested for a class of polynomials in two indeterminates and real coefficients, here referred to as two dimensional (2-D) polynomials. These polynomials arise in the context of 2-D linear systems theory. Necessary and sufficient conditions are also presented under which a matrix is equivalent to this companion form. (author). 6 refs

  18. Fragmentation of extracellular matrix by hypochlorous acid

    DEFF Research Database (Denmark)

    Woods, Alan A; Davies, Michael Jonathan

    2003-01-01

    /chloramide decomposition, with copper and iron ions being effective catalysts, and decreased by compounds which scavenge chloramines/chloramides, or species derived from them. The effect of such matrix modifications on cellular behaviour is poorly understood, though it is known that changes in matrix materials can have...... profound effects on cell adhesion, proliferation, growth and phenotype. The observed matrix modifications reported here may therefore modulate cellular behaviour in diseases such as atherosclerosis where MPO-derived oxidants are generated....

  19. Matrix orderings and their associated skew fields

    International Nuclear Information System (INIS)

    Mahdavi-Hezavehi, M.

    1990-08-01

    Matrix orderings on rings are investigated. It is shown that in the commutative case they are essentially positive cones. This is proved by reducing it to the field case; similarly one can show that on a skew field, matrix positive cones can be reduced to positive cones by using the Dieudonne determinant. Our main result shows that there is a natural bijection between the matrix positive cones on a ring R and the ordered epic R-fields. (author). 7 refs

  20. MDL, Collineations and the Fundamental Matrix

    OpenAIRE

    Maybank , Steve; Sturm , Peter

    1999-01-01

    International audience; Scene geometry can be inferred from point correspondences between two images. The inference process includes the selection of a model. Four models are considered: background (or null), collineation, affine fundamental matrix and fundamental matrix. It is shown how Minimum Description Length (MDL) can be used to compare the different models. The main result is that there is little reason for preferring the fundamental matrix model over the collineation model, even when ...

  1. Extracellular matrix component signaling in cancer

    DEFF Research Database (Denmark)

    Multhaupt, Hinke A. B.; Leitinger, Birgit; Gullberg, Donald

    2016-01-01

    Cell responses to the extracellular matrix depend on specific signaling events. These are important from early development, through differentiation and tissue homeostasis, immune surveillance, and disease pathogenesis. Signaling not only regulates cell adhesion cytoskeletal organization and motil...... as well as matrix constitution and protein crosslinking. Here we summarize roles of the three major matrix receptor types, with emphasis on how they function in tumor progression. [on SciFinder(R)]...

  2. Matrix-assisted peptide synthesis on nanoparticles.

    Science.gov (United States)

    Khandadash, Raz; Machtey, Victoria; Weiss, Aryeh; Byk, Gerardo

    2014-09-01

    We report a new method for multistep peptide synthesis on polymeric nanoparticles of differing sizes. Polymeric nanoparticles were functionalized via their temporary embedment into a magnetic inorganic matrix that allows multistep peptide synthesis. The matrix is removed at the end of the process for obtaining nanoparticles functionalized with peptides. The matrix-assisted synthesis on nanoparticles was proved by generating various biologically relevant peptides. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.

  3. Family doctors' involvement with families in Estonia

    Directory of Open Access Journals (Sweden)

    Lember Margus

    2004-10-01

    Full Text Available Abstract Background Family doctors should care for individuals in the context of their family. Family has a powerful influence on health and illness and family interventions have been shown to improve health outcomes for a variety of health problems. The aim of the study was to investigate the Estonian family doctors' (FD attitudes to the patients' family-related issues in their work: to explore the degree of FDs involvement in family matters, their preparedness for management of family-related issues and their self-assessment of the ability to manage different family-related problems. Methods A random sample (n = 236 of all FDs in Estonia was investigated using a postal questionnaire. Altogether 151 FDs responded to the questionnaire (response rate 64%, while five of them were excluded as they did not actually work as FDs. Results Of the respondents, 90% thought that in managing the health problems of patients FDs should communicate and cooperate with family members. Although most of the family doctors agreed that modifying of the health damaging risk factors (smoking, alcohol and drug abuse of their patients and families is their task, one third of them felt that dealing with these problems is ineffective, or perceived themselves as poorly prepared or having too little time for such activities. Of the respondents, 58% (n = 83 were of the opinion that they could modify also relationship problems. Conclusions Estonian family doctors are favourably disposed to involvement in family-related problems, however, they need some additional training, especially in the field of relationship management.

  4. 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...

  5. 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.

  6. 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

  7. Titanium Matrix Composite Pressure Vessel, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — For over 15 years, FMW Composite Systems has developed Metal Matrix Composite manufacturing methodologies for fabricating silicon-carbide-fiber-reinforced titanium...

  8. 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

  9. 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....

  10. Interfaces between a fibre and its matrix

    DEFF Research Database (Denmark)

    Lilholt, Hans; Sørensen, Bent F.

    2017-01-01

    in polyester matrix. The analysis of existing experimental literature data is demonstrated for steel fibres in epoxy matrix and for tungsten wires in copper matrix. These latter incomplete analyses show that some results can be obtained even if all three experimental parameters are not recorded....... parameters (applied load, debond length and relative fibre/matrix displacement) are rather similar for these test modes. A simplified analysis allows the direct determination of the three interface parameters from two plots for the experimental data. The complete analysis is demonstrated for steel fibres...

  11. Matrix Krylov subspace methods for image restoration

    Directory of Open Access Journals (Sweden)

    khalide jbilou

    2015-09-01

    Full Text Available In the present paper, we consider some matrix Krylov subspace methods for solving ill-posed linear matrix equations and in those problems coming from the restoration of blurred and noisy images. Applying the well known Tikhonov regularization procedure leads to a Sylvester matrix equation depending the Tikhonov regularized parameter. We apply the matrix versions of the well known Krylov subspace methods, namely the Least Squared (LSQR and the conjugate gradient (CG methods to get approximate solutions representing the restored images. Some numerical tests are presented to show the effectiveness of the proposed methods.

  12. 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.

  13. 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.

  14. Competitiveness of Family Businesses

    NARCIS (Netherlands)

    M.A.A.M. Leenders (Mark); E. Waarts (Eric)

    2001-01-01

    textabstractThe purpose of this study is to systematically examine the advantages and disadvantages of different types of family businesses. We distinguish four different types of family businesses based on their family and business orientation: (1) House of Business, (2) Family Money Machine, (3)

  15. Families in Transition .

    Science.gov (United States)

    Bundy, Michael L., Ed.; Gumaer, James, Ed.

    1984-01-01

    Focuses on disrupted families and the role of the school counselor in helping children adjust. Describes characteristics of healthy families, and discusses the transition to the blended family, effects of divorce groups on children's classroom behavior, counseling children in stepfamilies, single-parent families, and parenting strengths of single…

  16. Pure γ-families

    International Nuclear Information System (INIS)

    Dunaevskii, A.M.

    1977-01-01

    The subject of this work are pure gamma families consisting of the gamma quanta produced in the early stages of cosmic cascades. The criteria of selecting these families from the all measured families are presented. The characteristics of these families are given and some conclusions about the mechanism of the nuclear-electromagnetic cascades are extracted. (S.B.)

  17. TRASYS form factor matrix normalization

    Science.gov (United States)

    Tsuyuki, Glenn T.

    1992-01-01

    A method has been developed for adjusting a TRASYS enclosure form factor matrix to unity. This approach is not limited to closed geometries, and in fact, it is primarily intended for use with open geometries. The purpose of this approach is to prevent optimistic form factors to space. In this method, nodal form factor sums are calculated within 0.05 of unity using TRASYS, although deviations as large as 0.10 may be acceptable, and then, a process is employed to distribute the difference amongst the nodes. A specific example has been analyzed with this method, and a comparison was performed with a standard approach for calculating radiation conductors. In this comparison, hot and cold case temperatures were determined. Exterior nodes exhibited temperature differences as large as 7 C and 3 C for the hot and cold cases, respectively when compared with the standard approach, while interior nodes demonstrated temperature differences from 0 C to 5 C. These results indicate that temperature predictions can be artificially biased if the form factor computation error is lumped into the individual form factors to space.

  18. Interplay between Matrix Metalloproteinase-9, Matrix Metalloproteinase-2, and Interleukins in Multiple Sclerosis Patients

    Directory of Open Access Journals (Sweden)

    Alessandro Trentini

    2016-01-01

    Full Text Available Matrix Metalloproteases (MMPs and cytokines have been involved in the pathogenesis of multiple sclerosis (MS. However, no studies have still explored the possible associations between the two families of molecules. The present study aimed to evaluate the contribution of active MMP-9, active MMP-2, interleukin- (IL- 17, IL-18, IL-23, and monocyte chemotactic proteins-3 to the pathogenesis of MS and the possible interconnections between MMPs and cytokines. The proteins were determined in the serum and cerebrospinal fluid (CSF of 89 MS patients and 92 other neurological disorders (OND controls. Serum active MMP-9 was increased in MS patients and OND controls compared to healthy subjects (p<0.001 and p<0.01, resp., whereas active MMP-2 and ILs did not change. CSF MMP-9, but not MMP-2 or ILs, was selectively elevated in MS compared to OND (p<0.01. Regarding the MMPs and cytokines intercorrelations, we found a significant association between CSF active MMP-2 and IL-18 (r=0.3, p<0.05, while MMP-9 did not show any associations with the cytokines examined. Collectively, our results suggest that active MMP-9, but not ILs, might be a surrogate marker for MS. In addition, interleukins and MMPs might synergistically cooperate in MS, indicating them as potential partners in the disease process.

  19. 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.

  20. Differential analysis of matrix convex functions II

    DEFF Research Database (Denmark)

    Hansen, Frank; Tomiyama, Jun

    2009-01-01

    We continue the analysis in [F. Hansen, and J. Tomiyama, Differential analysis of matrix convex functions. Linear Algebra Appl., 420:102--116, 2007] of matrix convex functions of a fixed order defined in a real interval by differential methods as opposed to the characterization in terms of divided...

  1. Towards Matrix Models in IIB Superstrings

    OpenAIRE

    Olesen, P.

    1997-01-01

    I review the properties of a matrix action of relevance for IIB superstrings. This model generalizes the action proposed by Ishibashi, Kawai, Kitazawa, and Tsuchiya by introducing an auxillary field Y, which is the matrix version of the auxillary field g in the Schild action.

  2. Indecomposability of polynomials via Jacobian matrix

    International Nuclear Information System (INIS)

    Cheze, G.; Najib, S.

    2007-12-01

    Uni-multivariate decomposition of polynomials is a special case of absolute factorization. Recently, thanks to the Ruppert's matrix some effective results about absolute factorization have been improved. Here we show that with a jacobian matrix we can get sharper bounds for the special case of uni-multivariate decomposition. (author)

  3. Multimedia Matrix: A Cognitive Strategy for Designers.

    Science.gov (United States)

    Sherry, Annette C.

    This instructional development project evaluates the effect of a matrix-based strategy to assist multimedia authors in acquiring and applying principles for effective multimedia design. The Multimedia Matrix, based on the Park and Hannafin "Twenty Principles and Implications for Interactive Multimedia" design, displays a condensed…

  4. Advances in HTR fuel matrix technology

    International Nuclear Information System (INIS)

    Voice, E.H.; Sturge, D.W.

    1974-02-01

    Progress in the materials and technology of matrix consolidation in recent years is summarised, noting especially the development of an improved resin and the introduction of a new graphite powder. An earlier irradiation programme, the Matrix Test Series, is recalled and the fabrication of the most recent experiment, the directly-cooled homogeneous Met. VI, is described. (author)

  5. A marketing matrix for health care organizations.

    Science.gov (United States)

    Weaver, F J; Gombeski, W R; Fay, G W; Eversman, J J; Cowan-Gascoigne, C

    1986-06-01

    Irrespective of the formal marketing structure successful marketing for health care organizations requires the input on many people. Detailed here is the Marketing Matrix used at the Cleveland Clinic Foundation in Cleveland, Ohio. This Matrix is both a philosophy and a tool for clarifying and focusing the organization's marketing activities.

  6. 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

  7. Matrix Management: An Organizational Alternative for Libraries.

    Science.gov (United States)

    Johnson, Peggy

    1990-01-01

    Describes various organizational structures and models, presents matrix management as an alternative to traditional hierarchical structures, and suggests matrix management as an appropriate organizational alternative for academic libraries. Benefits that are discussed include increased flexibility, a higher level of professional independence, and…

  8. Rovibrational matrix elements of the multipole moments

    Indian Academy of Sciences (India)

    Rovibrational matrix elements of the multipole moments ℓ up to rank 10 and of the linear polarizability of the H2 molecule in the condensed phase have been computed taking into account the effect of the intermolecular potential. Comparison with gas phase matrix elements shows that the effect of solid state interactions is ...

  9. Explicit Covariance Matrix for Particle Measurement Precision

    CERN Document Server

    Karimäki, Veikko

    1997-01-01

    We derive explicit and precise formulae for 3 by 3 error matrix of the particle transverse momentum, direction and impact parameter. The error matrix elements are expressed as functions of up to fourth order statistical moments of the measured coordinates. The formulae are valid for any curvature and track length in case of negligible multiple scattering.

  10. Modeling and Simulation of Matrix Converter

    DEFF Research Database (Denmark)

    Liu, Fu-rong; Klumpner, Christian; Blaabjerg, Frede

    2005-01-01

    This paper discusses the modeling and simulation of matrix converter. Two models of matrix converter are presented: one is based on indirect space vector modulation and the other is based on power balance equation. The basis of these two models is• given and the process on modeling is introduced...

  11. 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.

  12. Work-family harmony

    OpenAIRE

    Adhikari,Pralhad

    2018-01-01

    The phenomenon of positively thinking about work and organization during the family hours by a worker is called work-family harmony. On the fag opposite of work-family conflict is work-family harmony. The work extends/intrudes into the family life of the worker, but in a positive way. This kind of positive thinking about the organization helps person's subjective well-being grow and his mental health is also nourished.

  13. Family emotional expressiveness and family structure

    Directory of Open Access Journals (Sweden)

    Čotar-Konrad Sonja

    2016-01-01

    Full Text Available The present paper scrutinizes the relationship between family emotional expressiveness (i.e., the tendency to express dominant and/or submissive positive and negative emotions and components of family structure as proposed in Olson’s Circumplex model (i.e., cohesion and flexibility, family communication, and satisfaction in families with adolescents. The study was conducted on a sample of 514 Slovenian adolescents, who filled out two questionnaires: the Slovenian version of Family Emotional Expressiveness - FEQ and FACES IV. The results revealed that all four basic dimensions of family functioning were significantly associated with higher/more frequent expressions of positive submissive emotions, as well as with lower/less frequent expressions of negative dominant emotions. Moreover, expressions of negative submissive emotions explained a small, but significant amount of variance in three out of four family functioning variables (satisfaction, flexibility, and communication. The importance of particular aspects of emotional expressiveness for family cohesion, flexibility, communication, and satisfaction is discussed, and the relevance of present findings for family counselling is outlined.

  14. [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.

  15. 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

  16. 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.

  17. 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.

  18. Nontraditional family romance.

    Science.gov (United States)

    Corbett, K

    2001-07-01

    Family stories lie at the heart of psychoanalytic developmental theory and psychoanalytic clinical technique, but whose family? Increasingly, lesbian and gay families, multiparent families, and single-parent families are relying on modern reproductive technologies to form families. The contemplation of these nontraditional families and the vicissitudes of contemporary reproduction lead to an unknowing of what families are, including the ways in which psychoanalysts configure the family within developmental theory. This article focuses on the stories that families tell in order to account for their formation--stories that include narratives about parental union, parental sexuality, and conception. The author addresses three constructs that inform family stories and that require rethinking in light of the category crises posed by and for the nontraditional family: (1) normative logic, (2) family reverie and the construction of a family romance, and (3) the primal scene. These constructs are examined in tandem with detailed clinical material taken from the psychotherapy of a seven-year-old boy and his two mothers.

  19. Trends in family tourism

    Directory of Open Access Journals (Sweden)

    Heike A. Schänzel

    2015-03-01

    Full Text Available Purpose – Families represent a large and growing market for the tourism industry. Family tourism is driven by the increasing importance placed on promoting family togetherness, keeping family bonds alive and creating family memories. Predictions for the future of family travel are shaped by changes in demography and social structures. With global mobility families are increasingly geographically dispersed and new family markets are emerging. The purpose of this paper is to discuss the trends that shape the understanding of families and family tourism. Design/methodology/approach – This paper examines ten trends that the authors as experts in the field identify of importance and significance for the future of family tourism. Findings – What emerges is that the future of family tourism lies in capturing the increasing heterogeneity, fluidity and mobility of the family market. Originality/value – The paper contributes to the understanding about the changes taking place in family tourism and what it means to the tourism industry in the future.

  20. Strengthening Family Practices for Latino Families

    Science.gov (United States)

    Chartier, Karen G.; Negroni, Lirio K.; Hesselbrock, Michie N.

    2010-01-01

    This study examined the effectiveness of a culturally adapted Strengthening Families Program (SFP) for Latinos to reduce risks for alcohol and drug use in children. Latino families, predominantly Puerto Rican, with a 9- to 12-year-old child and a parent(s) with a substance abuse problem participated in the study. Pre- and post-tests were conducted…

  1. Intra-family messaging with family circles

    NARCIS (Netherlands)

    Schatorjé, R.J.W.; Markopoulos, P.; Neustaedter, C.; Harrison, S.; Sellen, A.

    2013-01-01

    This chapter makes the argument that intra-family communication is not an issue of connectivity anytime anywhere, but of providing communication media that are flexible and expressive allowing families to appropriate them and fit their own idiosyncratic ways of communicating with each other. We

  2. Family Therapy for the "Truncated" Nuclear Family.

    Science.gov (United States)

    Zuk, Gerald H.

    1980-01-01

    The truncated nuclear family consists of a two-generation group in which conflict has produced a polarization of values. The single-parent family is at special risk. Go-between process enables the therapist to depolarize sharply conflicted values and reduce pathogenic relating. (Author)

  3. Loosely coupled class families

    DEFF Research Database (Denmark)

    Ernst, Erik

    2001-01-01

    are expressed using virtual classes seem to be very tightly coupled internally. While clients have achieved the freedom to dynamically use one or the other family, it seems that any given family contains a xed set of classes and we will need to create an entire family of its own just in order to replace one...... of the members with another class. This paper shows how to express class families in such a manner that the classes in these families can be used in many dierent combinations, still enabling family polymorphism and ensuring type safety....

  4. Noniterative MAP reconstruction using sparse matrix representations.

    Science.gov (United States)

    Cao, Guangzhi; Bouman, Charles A; Webb, Kevin J

    2009-09-01

    We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inverse matrix required for MAP reconstruction. This approach has generally not been used in the past because the inverse matrix is typically large and fully populated (i.e., not sparse). In order to overcome this problem, we introduce two new ideas. The first idea is a novel theory for the lossy source coding of matrix transformations which we refer to as matrix source coding. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of both the measurement data and the matrix rows and columns before quantization and coding. The second idea is a method for efficiently storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an orthonormal transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired transforms. We demonstrate the potential of the noniterative MAP reconstruction with examples from optical tomography. The method requires offline computation to encode the inverse transform. However, once these offline computations are completed, the noniterative MAP algorithm is shown to reduce both storage and computation by well over two orders of magnitude, as compared to a linear iterative reconstruction methods.

  5. 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...

  6. A matrix model from string field theory

    Directory of Open Access Journals (Sweden)

    Syoji Zeze

    2016-09-01

    Full Text Available We demonstrate that a Hermitian matrix model can be derived from level truncated open string field theory with Chan-Paton factors. The Hermitian matrix is coupled with a scalar and U(N vectors which are responsible for the D-brane at the tachyon vacuum. Effective potential for the scalar is evaluated both for finite and large N. Increase of potential height is observed in both cases. The large $N$ matrix integral is identified with a system of N ZZ branes and a ghost FZZT brane.

  7. NLTE steady-state response matrix method.

    Science.gov (United States)

    Faussurier, G.; More, R. M.

    2000-05-01

    A connection between atomic kinetics and non-equilibrium thermodynamics has been recently established by using a collisional-radiative model modified to include line absorption. The calculated net emission can be expressed as a non-local thermodynamic equilibrium (NLTE) symmetric response matrix. In the paper, this connection is extended to both cases of the average-atom model and the Busquet's model (RAdiative-Dependent IOnization Model, RADIOM). The main properties of the response matrix still remain valid. The RADIOM source function found in the literature leads to a diagonal response matrix, stressing the absence of any frequency redistribution among the frequency groups at this order of calculation.

  8. A transilient matrix for moist convection

    Energy Technology Data Exchange (ETDEWEB)

    Romps, D.; Kuang, Z.

    2011-08-15

    A method is introduced for diagnosing a transilient matrix for moist convection. This transilient matrix quantifies the nonlocal transport of air by convective eddies: for every height z, it gives the distribution of starting heights z{prime} for the eddies that arrive at z. In a cloud-resolving simulation of deep convection, the transilient matrix shows that two-thirds of the subcloud air convecting into the free troposphere originates from within 100 m of the surface. This finding clarifies which initial height to use when calculating convective available potential energy from soundings of the tropical troposphere.

  9. The Matrix exponential, Dynamic Systems and Control

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad

    The matrix exponential can be found in various connections in analysis and control of dynamic systems. In this short note we are going to list a few examples. The matrix exponential usably pops up in connection to the sampling process, whatever it is in a deterministic or a stochastic setting...... or it is a tool for determining a Gramian matrix. This note is intended to be used in connection to the teaching post the course in Stochastic Adaptive Control (02421) given at Informatics and Mathematical Modelling (IMM), The Technical University of Denmark. This work is a result of a study of the litterature....

  10. Matrix-exponential description of radiative transfer

    International Nuclear Information System (INIS)

    Waterman, P.C.

    1981-01-01

    By appling the matrix-exponential operator technique to the radiative-transfer equation in discrete form, new analytical solutions are obtained for the transmission and reflection matrices in the limiting cases x >1, where x is the optical depth of the layer. Orthongonality of the eigenvectors of the matrix exponential apparently yields new conditions for determining. Chandrasekhar's characteristic roots. The exact law of reflection for the discrete eigenfunctions is also obtained. Finally, when used in conjuction with the doubling method, the matrix exponential should result in reduction in both computation time and loss of precision

  11. 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...

  12. The deviation matrix of a continuous-time Markov chain

    NARCIS (Netherlands)

    Coolen-Schrijner, P.; van Doorn, E.A.

    2001-01-01

    The deviation matrix of an ergodic, continuous-time Markov chain with transition probability matrix $P(.)$ and ergodic matrix $\\Pi$ is the matrix $D \\equiv \\int_0^{\\infty} (P(t)-\\Pi)dt$. We give conditions for $D$ to exist and discuss properties and a representation of $D$. The deviation matrix of a

  13. The deviation matrix of a continuous-time Markov chain

    NARCIS (Netherlands)

    Coolen-Schrijner, Pauline; van Doorn, Erik A.

    2002-01-01

    he deviation matrix of an ergodic, continuous-time Markov chain with transition probability matrix $P(.)$ and ergodic matrix $\\Pi$ is the matrix $D \\equiv \\int_0^{\\infty} (P(t)-\\Pi)dt$. We give conditions for $D$ to exist and discuss properties and a representation of $D$. The deviation matrix of a

  14. Residual, restarting and Richardson iteration for the matrix exponential

    NARCIS (Netherlands)

    Bochev, Mikhail A.; Grimm, Volker; Hochbruck, Marlis

    2013-01-01

    A well-known problem in computing some matrix functions iteratively is the lack of a clear, commonly accepted residual notion. An important matrix function for which this is the case is the matrix exponential. Suppose the matrix exponential of a given matrix times a given vector has to be computed.

  15. Residual, restarting and Richardson iteration for the matrix exponential

    NARCIS (Netherlands)

    Bochev, Mikhail A.

    2010-01-01

    A well-known problem in computing some matrix functions iteratively is a lack of a clear, commonly accepted residual notion. An important matrix function for which this is the case is the matrix exponential. Assume, the matrix exponential of a given matrix times a given vector has to be computed. We

  16. 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

  17. MSUD Family Support Group

    Science.gov (United States)

    ... The Treatment Of MSUD The MSUD Family Support Group has provided funds to Buck Institute for its ... of the membership of the MSUD Family Support Group, research for improved treatments and potential cure was ...

  18. National Military Family Association

    Science.gov (United States)

    ... MilitaryFamily.org © 2017 - National Military Family Association Twitter Facebook Pinterest Instagram Charity Navigator Four Star Charity GuideStar Exchange Better Business Bureau Charity Watch Independent Charity of America nonprofit ...

  19. IGSF9 Family Proteins

    DEFF Research Database (Denmark)

    Hansen, Maria; Walmod, Peter Schledermann

    2013-01-01

    The Drosophila protein Turtle and the vertebrate proteins immunoglobulin superfamily (IgSF), member 9 (IGSF9/Dasm1) and IGSF9B are members of an evolutionarily ancient protein family. A bioinformatics analysis of the protein family revealed that invertebrates contain only a single IGSF9 family gene......, the longest isoforms of the proteins have the same general organization as the neural cell adhesion molecule family of cell adhesion molecule proteins, and like this family of proteins, IGSF9 family members are expressed in the nervous system. A review of the literature revealed that Drosophila Turtle...... facilitates homophilic cell adhesion. Moreover, IGSF9 family proteins have been implicated in the outgrowth and branching of neurites, axon guidance, synapse maturation, self-avoidance, and tiling. However, despite the few published studies on IGSF9 family proteins, reports on the functions of both Turtle...

  20. Family Caregiver Alliance

    Science.gov (United States)

    ... on your schedule. Look for our launch soon! FAMILY CARE NAVIGATOR ─ Click on Your State AL AK ... AiA18 Smart Patients Caregivers Community In partnership with Family Caregiver Alliance Learn more Caregiver Research Studies show ...