Z4-symmetric factorized S-matrix in two space-time dimensions

International Nuclear Information System (INIS)

Zamolodchikov, A.B.

1979-01-01

The factorized S-matrix with internal symmetry Z 4 is constructed in two space-time dimensions. The two-particle amplitudes are obtained by means of solving the factorization, unitarity and analyticity equations. The solution of factorization equations can be expressed in terms of elliptic functions. The S-matrix cotains the resonance poles naturally. The simple formal relation between the general factorized S-matrices and the Baxter-type lattice transfer matrices is found. In the sense of this relation the Z 4 -symmetric S-matrix corresponds to the Baxter transfer matrix itself. (orig.)

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...

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.

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.

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.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

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

Matrix factorizations and homological mirror symmetry on the torus

International Nuclear Information System (INIS)

Knapp, Johanna; Omer, Harun

2007-01-01

We consider matrix factorizations and homological mirror symmetry on the torus T 2 using a Landau-Ginzburg description. We identify the basic matrix factorizations of the Landau-Ginzburg superpotential and compute the full spectrum taking into account the explicit dependence on bulk and boundary moduli. We verify homological mirror symmetry by comparing three-point functions in the A-model and the B-model

Matrix factorization on a hypercube multiprocessor

International Nuclear Information System (INIS)

Geist, G.A.; Heath, M.T.

1985-08-01

This paper is concerned with parallel algorithms for matrix factorization on distributed-memory, message-passing multiprocessors, with special emphasis on the hypercube. Both Cholesky factorization of symmetric positive definite matrices and LU factorization of nonsymmetric matrices using partial pivoting are considered. The use of the resulting triangular factors to solve systems of linear equations by forward and back substitutions is also considered. Efficiencies of various parallel computational approaches are compared in terms of empirical results obtained on an Intel iPSC hypercube. 19 refs., 6 figs., 2 tabs

Efficient multitasking of Choleski matrix factorization on CRAY supercomputers

Science.gov (United States)

Overman, Andrea L.; Poole, Eugene L.

1991-01-01

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

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....

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...

Normalization Of Thermal-Radiation Form-Factor Matrix

Science.gov (United States)

Tsuyuki, Glenn T.

1994-01-01

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

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.

Matrix factorizations, minimal models and Massey products

International Nuclear Information System (INIS)

Knapp, Johanna; Omer, Harun

2006-01-01

We present a method to compute the full non-linear deformations of matrix factorizations for ADE minimal models. This method is based on the calculation of higher products in the cohomology, called Massey products. The algorithm yields a polynomial ring whose vanishing relations encode the obstructions of the deformations of the D-branes characterized by these matrix factorizations. This coincides with the critical locus of the effective superpotential which can be computed by integrating these relations. Our results for the effective superpotential are in agreement with those obtained from solving the A-infinity relations. We point out a relation to the superpotentials of Kazama-Suzuki models. We will illustrate our findings by various examples, putting emphasis on the E 6 minimal model

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

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.

Estimating Depolarization with the Jones Matrix Quality Factor

Science.gov (United States)

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

2017-11-01

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

Ceramic matrix and resin matrix composites - A comparison

Science.gov (United States)

Hurwitz, Frances I.

1987-01-01

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

Ceramic matrix and resin matrix composites: A comparison

Science.gov (United States)

Hurwitz, Frances I.

1987-01-01

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

Extracellular matrix organization modulates fibroblast growth and growth factor responsiveness.

Science.gov (United States)

Nakagawa, S; Pawelek, P; Grinnell, F

1989-06-01

To learn more about the relationship between extracellular matrix organization, cell shape, and cell growth control, we studied DNA synthesis by fibroblasts in collagen gels that were either attached to culture dishes or floating in culture medium during gel contraction. After 4 days of contraction, the collagen density (initially 1.5 mg/ml) reached 22 mg/ml in attached gels and 55 mg/ml in floating gels. After contraction, attached collagen gels were well organized; collagen fibrils were aligned in the plane of cell spreading; and fibroblasts had an elongated, bipolar morphology. Floating collagen gels, however, were unorganized; collagen fibrils were arranged randomly; and fibroblasts had a stellate morphology. DNA synthesis by fibroblasts in contracted collagen gels was suppressed if the gels were floating in medium but not if the gels were attached, and inhibition was independent of the extent of gel contraction. Therefore, growth of fibroblasts in contracted collagen gels could be regulated by differences in extracellular matrix organization and cell shape independently of extracellular matrix density. We also compared the responses of fibroblasts in contracted collagen gels and monolayer culture to peptide growth factors including fibroblast growth factor, platelet-derived growth factor, transforming growth factor-beta, and interleukin 1. Cells in floating collagen gels were generally unresponsive to any of the growth factors. Cells in attached collagen gels and monolayer culture were affected similarly by fibroblast growth factor but not by the others. Our results indicate that extracellular matrix organization influenced not only cell growth, but also fibroblast responsiveness to peptide growth factors.

A hierarchical model for ordinal matrix factorization

DEFF Research Database (Denmark)

Paquet, Ulrich; Thomson, Blaise; Winther, Ole

2012-01-01

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

Followee recommendation in microblog using matrix factorization model with structural regularization.

Science.gov (United States)

Yu, Yan; Qiu, Robin G

2014-01-01

Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.

Parallelized preconditioned model building algorithm for matrix factorization

OpenAIRE

Kaya, Kamer; Birbil, İlker; Birbil, Ilker; Öztürk, Mehmet Kaan; Ozturk, Mehmet Kaan; Gohari, Amir

2017-01-01

Matrix factorization is a common task underlying several machine learning applications such as recommender systems, topic modeling, or compressed sensing. Given a large and possibly sparse matrix A, we seek two smaller matrices W and H such that their product is as close to A as possible. The objective is minimizing the sum of square errors in the approximation. Typically such problems involve hundreds of thousands of unknowns, so an optimizer must be exceptionally efficient. In this study, a...

Wiener-Hopf factorization of piecewise meromorphic matrix-valued functions

International Nuclear Information System (INIS)

Adukov, Victor M

2009-01-01

Let D + be a multiply connected domain bounded by a contour Γ, let D - be the complement of D + union Γ in C-bar=C union {∞}, and a(t) be a continuous invertible matrix-valued function on Γ which can be meromorphically extended into the open disconnected set D - (as a piecewise meromorphic matrix-valued function). An explicit solution of the Wiener-Hopf factorization problem for a(t) is obtained and the partial factorization indices of a(t) are calculated. Here an explicit solution of a factorization problem is meant in the sense of reducing it to the investigation of finitely many systems of linear algebraic equations with matrices expressed in closed form, that is, in quadratures. Bibliography: 15 titles.

Fast matrix factorization algorithm for DOSY based on the eigenvalue decomposition and the difference approximation focusing on the size of observed matrix

International Nuclear Information System (INIS)

Tanaka, Yuho; Uruma, Kazunori; Furukawa, Toshihiro; Nakao, Tomoki; Izumi, Kenya; Utsumi, Hiroaki

2017-01-01

This paper deals with an analysis problem for diffusion-ordered NMR spectroscopy (DOSY). DOSY is formulated as a matrix factorization problem of a given observed matrix. In order to solve this problem, a direct exponential curve resolution algorithm (DECRA) is well known. DECRA is based on singular value decomposition; the advantage of this algorithm is that the initial value is not required. However, DECRA requires a long calculating time, depending on the size of the given observed matrix due to the singular value decomposition, and this is a serious problem in practical use. Thus, this paper proposes a new analysis algorithm for DOSY to achieve a short calculating time. In order to solve matrix factorization for DOSY without using singular value decomposition, this paper focuses on the size of the given observed matrix. The observed matrix in DOSY is also a rectangular matrix with more columns than rows, due to limitation of the measuring time; thus, the proposed algorithm transforms the given observed matrix into a small observed matrix. The proposed algorithm applies the eigenvalue decomposition and the difference approximation to the small observed matrix, and the matrix factorization problem for DOSY is solved. The simulation and a data analysis show that the proposed algorithm achieves a lower calculating time than DECRA as well as similar analysis result results to DECRA. (author)

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

Form factors in quantum integrable models with GL(3)-invariant R-matrix

Energy Technology Data Exchange (ETDEWEB)

Pakuliak, S., E-mail: pakuliak@theor.jinr.ru [Laboratory of Theoretical Physics, JINR, 141980 Dubna, Moscow Reg. (Russian Federation); Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Moscow Reg. (Russian Federation); Institute of Theoretical and Experimental Physics, 117259 Moscow (Russian Federation); Ragoucy, E., E-mail: eric.ragoucy@lapth.cnrs.fr [Laboratoire de Physique Théorique LAPTH, CNRS and Université de Savoie, BP 110, 74941 Annecy-le-Vieux Cedex (France); Slavnov, N.A., E-mail: nslavnov@mi.ras.ru [Steklov Mathematical Institute, Moscow (Russian Federation)

2014-04-15

We study integrable models solvable by the nested algebraic Bethe ansatz and possessing GL(3)-invariant R-matrix. We obtain determinant representations for form factors of off-diagonal entries of the monodromy matrix. These representations can be used for the calculation of form factors and correlation functions of the XXX SU(3)-invariant Heisenberg chain.

Implicit vs. Explicit Trust in Social Matrix Factorization

NARCIS (Netherlands)

Fazeli, Soude; Loni, Babak; Bellogin, Alejandro; Drachsler, Hendrik; Sloep, Peter

2014-01-01

Incorporating social trust in Matrix Factorization (MF) methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist

General factorization relations and consistency conditions in the sudden approximation via infinite matrix inversion

International Nuclear Information System (INIS)

Chan, C.K.; Hoffman, D.K.; Evans, J.W.

1985-01-01

Local, i.e., multiplicative, operators satisfy well-known linear factorization relations wherein matrix elements (between states associated with a complete set of wave functions) can be obtained as a linear combination of those out of the ground state (the input data). Analytic derivation of factorization relations for general state input data results in singular integral expressions for the coefficients, which can, however, be regularized using consistency conditions between matrix elements out of a single (nonground) state. Similar results hold for suitable ''symmetry class'' averaged matrix elements where the symmetry class projection operators are ''complete.'' In several cases where the wave functions or projection operators incorporate orthogonal polynomial dependence, we show that the ground state factorization relations have a simplified structure allowing an alternative derivation of the general factorization relations via an infinite matrix inversion procedure. This form is shown to have some advantages over previous versions. In addition, this matrix inversion procedure obtains all consistency conditions (which is not always the case from regularization of singular integrals)

Strong factor in the SO(2,3) S matrix

International Nuclear Information System (INIS)

Amado, R.D.; Sparrow, D.A.

1986-01-01

The group theoretic S matrix of Alhassid, Iachello, and Wu is factorable into a product of Coulomb and strong factors. The strong factor is examined with a view to relating it to more fa- miliar potential and phase shift descriptions. We find simple approximate expressions for the phase shifts which are very accurate for heavy-ion-type applications. For peripheral scattering it is possible to obtain simple expressions relating the strong factor to an effective potential

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).

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

Science.gov (United States)

Schuster, Philip C.; Toro, Natalia

2009-06-01

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

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

International Nuclear Information System (INIS)

Schuster, Philip C.; Toro, Natalia

2009-01-01

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

Data fusion in metabolomics using coupled matrix and tensor factorizations

DEFF Research Database (Denmark)

Evrim, Acar Ataman; Bro, Rasmus; Smilde, Age Klaas

2015-01-01

of heterogeneous (i.e., in the form of higher order tensors and matrices) data sets with shared/unshared factors. In order to jointly analyze such heterogeneous data sets, we formulate data fusion as a coupled matrix and tensor factorization (CMTF) problem, which has already proved useful in many data mining...

High performance matrix inversion based on LU factorization for multicore architectures

KAUST Repository

Dongarra, Jack

2011-01-01

The goal of this paper is to present an efficient implementation of an explicit matrix inversion of general square matrices on multicore computer architecture. The inversion procedure is split into four steps: 1) computing the LU factorization, 2) inverting the upper triangular U factor, 3) solving a linear system, whose solution yields inverse of the original matrix and 4) applying backward column pivoting on the inverted matrix. Using a tile data layout, which represents the matrix in the system memory with an optimized cache-aware format, the computation of the four steps is decomposed into computational tasks. A directed acyclic graph is generated on the fly which represents the program data flow. Its nodes represent tasks and edges the data dependencies between them. Previous implementations of matrix inversions, available in the state-of-the-art numerical libraries, are suffer from unnecessary synchronization points, which are non-existent in our implementation in order to fully exploit the parallelism of the underlying hardware. Our algorithmic approach allows to remove these bottlenecks and to execute the tasks with loose synchronization. A runtime environment system called QUARK is necessary to dynamically schedule our numerical kernels on the available processing units. The reported results from our LU-based matrix inversion implementation significantly outperform the state-of-the-art numerical libraries such as LAPACK (5x), MKL (5x) and ScaLAPACK (2.5x) on a contemporary AMD platform with four sockets and the total of 48 cores for a matrix of size 24000. A power consumption analysis shows that our high performance implementation is also energy efficient and substantially consumes less power than its competitors. © 2011 ACM.

Extracellular matrix and growth factor engineering for controlled angiogenesis in regenerative medicine

Directory of Open Access Journals (Sweden)

Mikaël M Martino

2015-04-01

Full Text Available Blood vessel growth plays a key role in regenerative medicine, both to restore blood supply to ischemic tissues and to ensure rapid vascularization of clinical-size tissue-engineered grafts. For example, vascular endothelial growth factor (VEGF is the master regulator of physiological blood vessel growth and is one of the main molecular targets of therapeutic angiogenesis approaches. However, angiogenesis is a complex process and there is a need to develop rational therapeutic strategies based on a firm understanding of basic vascular biology principles, as evidenced by the disappointing results of initial clinical trials of angiogenic factor delivery. In particular, the spatial localization of angiogenic signals in the extracellular matrix is crucial to ensure the proper assembly and maturation of new vascular structures. Here we discuss the therapeutic implications of matrix interactions of angiogenic factors, with a special emphasis on VEGF, as well as provide an overview of current approaches, based on protein and biomaterial engineering that mimic the regulatory functions of extracellular matrix to optimize the signaling microenvironment of vascular growth factors.

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

Science.gov (United States)

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

2016-01-21

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

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

Science.gov (United States)

Chew, Peter A; Bader, Brett W

2012-10-16

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

Space Vector Modulation for an Indirect Matrix Converter with Improved Input Power Factor

Directory of Open Access Journals (Sweden)

Nguyen Dinh Tuyen

2017-04-01

Full Text Available Pulse width modulation strategies have been developed for indirect matrix converters (IMCs in order to improve their performance. In indirect matrix converters, the LC input filter is used to remove input current harmonics and electromagnetic interference problems. Unfortunately, due to the existence of the input filter, the input power factor is diminished, especially during operation at low voltage outputs. In this paper, a new space vector modulation (SVM is proposed to compensate for the input power factor of the indirect matrix converter. Both computer simulation and experimental studies through hardware implementation were performed to verify the effectiveness of the proposed modulation strategy.

Augmenting matrix factorization technique with the combination of tags and genres

Science.gov (United States)

Ma, Tinghuai; Suo, Xiafei; Zhou, Jinjuan; Tang, Meili; Guan, Donghai; Tian, Yuan; Al-Dhelaan, Abdullah; Al-Rodhaan, Mznah

2016-11-01

Recommender systems play an important role in our daily life and are becoming popular tools for users to find what they are really interested in. Matrix factorization methods, which are popular recommendation methods, have gained high attention these years. With the rapid growth of the Internet, lots of information has been created, like social network information, tags and so on. Along with these, a few matrix factorization approaches have been proposed which incorporate the personalized information of users or items. However, except for ratings, most of the matrix factorization models have utilized only one kind of information to understand users' interests. Considering the sparsity of information, in this paper, we try to investigate the combination of different information, like tags and genres, to reveal users' interests accurately. With regard to the generalization of genres, a constraint is added when genres are utilized to find users' similar ;soulmates;. In addition, item regularizer is also considered based on latent semantic indexing (LSI) method with the item tags. Our experiments are conducted on two real datasets: Movielens dataset and Douban dataset. The experimental results demonstrate that the combination of tags and genres is really helpful to reveal users' interests.

Direct comparison of phosphate uptake by adnate and loosely attached microalgae within an intact biofilm matrix

International Nuclear Information System (INIS)

Burkholder, J.M.; Wetzel, R.G.; Klomparens, K.L.

1990-01-01

We report a direct comparison of phosphate uptake by adnate and loosely attached microalgae in an intact biofilm matrix, with resolution at the level of individual cells. Track scanning electron microscope autoradiography enabled assay of [ 33 P]phosphate uptake from the overlying water by adnate algae left undisturbed on mature leaves of the macrophyte Potamogeton illinoensis or on artificial plant mimics. The epiphyte communities developed in either phosphate-poor or moderately phosphate-enriched water, and they were assayed on both natural and artificial plants. All adnate taxa examined from both natural and artificial plants in both habitats took up significantly less radiolabel when assayed beneath the overlying matrix than when they were exposed to the water upon removal of the overstory material. Track scanning electron microscope autoradiography and track light microscope autoradiography were intercalibrated to enable comparison of [ 33 P]phosphate uptake by adnate and loosely attached components of the epiphyte matrix. Loosley attached cells on substrata from both habitats took up significantly more radiolabel than did underlying adnate cells, indicating that access to phosphate supplies from the water depended on the position of microbial cells in the matrix. In this short-term assay, the adnate microalgae were relatively isolated from the water column nutrient source

Minimally invasive esthetic ridge preservation with growth-factor enhanced bone matrix.

Science.gov (United States)

Nevins, Marc L; Said, Sherif

2017-12-28

Extraction socket preservation procedures are critical to successful esthetic implant therapy. Conventional surgical approaches are technique sensitive and often result in alteration of the soft tissue architecture, which then requires additional corrective surgical procedures. This case series report presents the ability of flapless surgical techniques combined with a growth factor-enhanced bone matrix to provide esthetic ridge preservation at the time of extraction for compromised sockets. When considering esthetic dental implant therapy, preservation, or further enhancement of the available tissue support at the time of tooth extraction may provide an improved esthetic outcome with reduced postoperative sequelae and decreased treatment duration. Advances in minimally invasive surgical techniques combined with recombinant growth factor technology offer an alternative for bone reconstruction while maintaining the gingival architecture for enhanced esthetic outcome. The combination of freeze-dried bone allograft (FDBA) and rhPDGF-BB (platelet-derived growth factor-BB) provides a growth-factor enhanced matrix to induce bone and soft tissue healing. The use of a growth-factor enhanced matrix is an option for minimally invasive ridge preservation procedures for sites with advanced bone loss. Further studies including randomized clinical trials are needed to better understand the extent and limits of these procedures. The use of minimally invasive techniques with growth factors for esthetic ridge preservation reduces patient morbidity associated with more invasive approaches and increases the predictability for enhanced patient outcomes. By reducing the need for autogenous bone grafts the use of this technology is favorable for patient acceptance and ease of treatment process for esthetic dental implant therapy. © 2017 Wiley Periodicals, Inc.

An Elementary Proof of the Polynomial Matrix Spectral Factorization Theorem

OpenAIRE

Ephremidze, Lasha

2010-01-01

A very simple and short proof of the polynomial matrix spectral factorization theorem (on the unit circle as well as on the real line) is presented, which relies on elementary complex analysis and linear algebra.

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.

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

Calabi-Yau structures on categories of matrix factorizations

Science.gov (United States)

Shklyarov, Dmytro

2017-09-01

Using tools of complex geometry, we construct explicit proper Calabi-Yau structures, that is, non-degenerate cyclic cocycles on differential graded categories of matrix factorizations of regular functions with isolated critical points. The formulas involve the Kapustin-Li trace and its higher corrections. From the physics perspective, our result yields explicit 'off-shell' models for categories of topological D-branes in B-twisted Landau-Ginzburg models.

Metal matrix composites: History, status, factors and future

Science.gov (United States)

Cyriac, Ajith James

The history, status, and future of metal matrix composites are presented by evaluating the progression of available literature through time. The trends that existed and issues that still prevail are discussed and a prediction of the future for MMCs is presented. The factors that govern the performance of metal matrix composites are also discussed. In many developed countries and in several developing countries there exists continued interest in MMCs. Researchers tried numerous combinations of matrices and reinforcements since work strictly on MMCs began in the 1950s. This led to developments for aerospace and defense applications, but resultant commercial applications were limited. The introduction of ceramic whiskers as reinforcement and the development of 'in-situ' eutectics in the 1960s aided high temperature applications in aircraft engines. In the late 1970s the automobile industries started to take MMCs seriously. In the last 20 years, MMCs evolved from laboratories to a class of materials with numerous applications and commercial markets. After the collapse of the Berlin Wall, prevailing order in the world changed drastically. This effect was evident in the progression of metal matrix composites. The internet connected the world like never before and tremendous information was available for researchers around the world. Globalization and the internet resulted in the transformation of the world to a more level playing field, and this effect is evident in the nature and source of research on metal matrix composites happening around the world.

Calculation of the Cholesky factor directly from the stiffness matrix of the structural element

International Nuclear Information System (INIS)

Prates, C.L.M.; Soriano, H.L.

1978-01-01

The analysis of the structures of nuclear power plants requires the evaluation of the internal forces. This is attained by the solution of a system of equations. This solution takes most of the computing time and memory. One of the ways it can be achieved is based on the Cholesky factor. The structural matrix of the coeficients is transformed into an upper triangular matrix by the Cholesky decomposition. Cholesky factor can be obtained directly from the stiffness matrix of the structural element. The result can thus be obtained in a more precise and quick way. (Author)

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

Energy Technology Data Exchange (ETDEWEB)

Gittens, Alex; Kottalam, Jey; Yang, Jiyan; Ringenburg, Michael, F.; Chhugani, Jatin; Racah, Evan; Singh, Mohitdeep; Yao, Yushu; Fischer, Curt; Ruebel, Oliver; Bowen, Benjamin; Lewis, Norman, G.; Mahoney, Michael, W.; Krishnamurthy, Venkat; Prabhat, Mr

2017-07-27

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

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.

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.

All-at-once Optimization for Coupled Matrix and Tensor Factorizations

DEFF Research Database (Denmark)

Evrim, Acar Ataman; Kolda, Tamara G.; Dunlavy, Daniel M.

2011-01-01

.g., the person by person social network matrix or the restaurant by category matrix, and higher-order tensors, e.g., the "ratings" tensor of the form restaurant by meal by person. In this paper, we are particularly interested in fusing data sets with the goal of capturing their underlying latent structures. We...... formulate this problem as a coupled matrix and tensor factorization (CMTF) problem where heterogeneous data sets are modeled by fitting outer-product models to higher-order tensors and matrices in a coupled manner. Unlike traditional approaches solving this problem using alternating algorithms, we propose...... an all-at-once optimization approach called CMTF-OPT (CMTF-OPTimization), which is a gradient-based optimization approach for joint analysis of matrices and higher-order tensors. We also extend the algorithm to handle coupled incomplete data sets. Using numerical experiments, we demonstrate...

Multithreading for synchronization tolerance in matrix factorization

International Nuclear Information System (INIS)

Buttari, Alfredo; Dongarra, Jack; Husbands, Parry; Kurzak, Jakub; Yelick, Katherine

2007-01-01

Physical constraints such as power, leakage and pin bandwidth are currently driving the HPC industry to produce systems with unprecedented levels of concurrency. In these parallel systems, synchronization and memory operations are becoming considerably more expensive than before. In this work we study parallel matrix factorization codes and conclude that they need to be re-engineered to avoid unnecessary (and expensive) synchronization. We propose the use of multithreading combined with intelligent schedulers and implement representative algorithms in this style. Our results indicate that this strategy can significantly outperform traditional codes

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.

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

NARCIS (Netherlands)

Ahn, S.; Korattikara, A.; Liu, N.; Rajan, S.; Welling, M.

2015-01-01

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid ovrfitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir

2018-02-24

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Charara, Ali; Keyes, David E.

2018-01-01

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

An integrating factor matrix method to find first integrals

International Nuclear Information System (INIS)

Saputra, K V I; Quispel, G R W; Van Veen, L

2010-01-01

In this paper we develop an integrating factor matrix method to derive conditions for the existence of first integrals. We use this novel method to obtain first integrals, along with the conditions for their existence, for two- and three-dimensional Lotka-Volterra systems with constant terms. The results are compared to previous results obtained by other methods.

Electromagnetic Compatibility of Matrix Converter System

Directory of Open Access Journals (Sweden)

S. Fligl

2006-12-01

Full Text Available The presented paper deals with matrix converters pulse width modulation strategies design with emphasis on the electromagnetic compatibility. Matrix converters provide an all-silicon solution to the problem of converting AC power from one frequency to another, offering almost all the features required of an ideal static frequency changer. They possess many advantages compared to the conventional voltage or current source inverters. A matrix converter does not require energy storage components as a bulky capacitor or an inductance in the DC-link, and enables the bi-directional power flow between the power supply and load. The most of the contemporary modulation strategies are able to provide practically sinusoidal waveforms of the input and output currents with negligible low order harmonics, and to control the input displacement factor. The perspective of matrix converters regarding EMC in comparison with other types of converters is brightly evident because it is no need to use any equipment for power factor correction and current and voltage harmonics reduction. Such converter with proper control is properly compatible both with the supply mains and with the supplied load. A special digital control system was developed for the realized experimental test bed which makes it possible to achieve greater throughput of the digital control system and its variability.

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...

Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent

Directory of Open Access Journals (Sweden)

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.

Human aqueous humor levels of transforming growth factor-β2: Association with matrix metalloproteinases/tissue inhibitors of matrix metalloproteinases

OpenAIRE

Jia, Yan; Yue, Yu; Hu, Dan-Ning; Chen, Ji-Li; Zhou, Ji-Bo

2017-01-01

The present study aims to investigate the association of transforming growth factor-β2 (TGF-β2) and matrix metalloproteinases (MMPs), MMP-2 and MMP-3, and tissue inhibitors of matrix metalloproteinases (TIMPs), TIMP-1, TIMP-2 and TIMP-3 in the aqueous humor of patients with high myopia or cataracts. The levels of TGF-β2 and MMPs/TIMPs were measured with the Luminex xMAP Technology using commercially available Milliplex xMAP kits. The association between TGF-β2 and MMPs/TIMPs levels was analyz...

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

Science.gov (United States)

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

2018-06-05

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

Genetic Algorithm and Graph Theory Based Matrix Factorization Method for Online Friend Recommendation

Directory of Open Access Journals (Sweden)

Qu Li

2014-01-01

Full Text Available Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

A matrix of social accounting for Asturias

Directory of Open Access Journals (Sweden)

Margarita Argüelles

2003-01-01

Full Text Available A Social Accounting Matrix is an integrated system of accounts that presents in a double-entry table all the transactions made in an economy among productive sectors, production factors, institutional sectors and the rest of the world. In comparison with an Input-Output Table, it offers a greater deal of information and shows completely the circular process of income, captivating more precisely the effects of exogenous changes. One of the main profits of a Social Accounting Matrix is to serve as a database for the development and application of a computable general equilibrium model. This is, in fact, the aim pursued with the elaboration of the Social Accounting Matrix for the Asturian economy presented here. This Matrix has been constructed with data from the 1995 Regional Accounts of Asturias, and its structure has been adapted to its future use as a database for a computable general equilibrium model of this regional economy.

Regulation of proliferation of embryonic heart mesenchyme: Role of transforming growth factor-beta 1 and the interstitial matrix

International Nuclear Information System (INIS)

Choy, M.; Armstrong, M.T.; Armstrong, P.B.

1990-01-01

Proliferation of atrioventricular cushion mesenchyme of the embryonic avian heart maintained in three-dimensional aggregate culture is stimulated by interaction with the interstitial matrix. Chicken serum or transforming growth factor-beta 1, which stimulates proliferation, induces matrix deposition in regions of the aggregate showing high labeling indices with tritiated thymidine. Dispersed heart mesenchyme interstitial matrix introduced into serum-free culture is incorporated into the aggregate and stimulates cellular proliferation similar to serum or transforming growth factor-beta 1. Proliferation is reversibly inhibited by the peptide Gly-Arg-Gly-Asp-Ser-Pro. It is suggested that transforming growth factor-beta 1 stimulates the production of interstitial matrix and that a sufficient stimulus for proliferation in this system is the presence of the matrix, which acts as the adhesive support for cellular anchorage

KEY COMPARISON: CCQM-K27-Subsequent: Key Comparison (subsequent) for the determination of ethanol in aqueous matrix

Science.gov (United States)

Schantz, Michele M.; Duewer, David L.; Parris, Reenie M.; May, Willie E.; Archer, Marcellé; Mussell, Chris; Carter, David; Konopelko, Leonid A.; Kustikov, Yury A.; Krylov, Anatoli I.; Fatina, Olga V.

2005-01-01

Ethanol is important both forensically ('drunk driving' or driving while under the influence, 'DWI', regulations) and commercially (alcoholic beverages). Blood- and breath-alcohol testing can be imposed on individuals operating private vehicles such as cars, boats, or snowmobiles, or operators of commercial vehicles like trucks, planes, and ships. The various levels of blood alcohol that determine whether these operators are considered legally impaired vary depending on the circumstances and locality. Accurate calibration and validation of instrumentation is critical in areas of forensic testing where quantitative analysis directly affects the outcome of criminal prosecutions, as is the case with the determination of ethanol in blood and breath. Additionally, the accurate assessment of the alcoholic content of beverages is a commercially important commodity. In 2002, the CCQM conducted a Key Comparison (CCQM-K27) for the determination of ethanol in aqueous matrix with nine participants. A report on this project has been approved by the CCQM and can be found at the BIPM website and in this Technical Supplement. CCQM-K27 comprised three samples, one at low mass fraction of ethanol in water (nominal concentration of 0.8 mg/g), one at high level (nominal concentration of 120 mg/g), and one wine matrix (nominal concentration of 81 mg/g). Overall agreement among eight participants using gas chromatography with flame ionization detection (GC-FID), titrimetry, isotope dilution gas chromatography/mass spectrometry (GC-IDMS), and gas chromatography-combustion-isotope ratio mass spectrometry (ID-GC-C-IRMS) was good. The ninth participant used a headspace GC-FID method that had not been validated in an earlier pilot study (CCQM-P35). A follow-on Key Comparison, CCQM-K27-Subsequent, was initiated in 2003 to accommodate laboratories that had not been ready to benchmark their methods in the original CCQM-K27 study or that wished to benchmark a different method. Four levels of

An Extended-Tag-Induced Matrix Factorization Technique for Recommender Systems

Directory of Open Access Journals (Sweden)

Huirui Han

2018-06-01

Full Text Available Social tag information has been used by recommender systems to handle the problem of data sparsity. Recently, the relationships between users/items and tags are considered by most tag-induced recommendation methods. However, sparse tag information is challenging to most existing methods. In this paper, we propose an Extended-Tag-Induced Matrix Factorization technique for recommender systems, which exploits correlations among tags derived by co-occurrence of tags to improve the performance of recommender systems, even in the case of sparse tag information. The proposed method integrates coupled similarity between tags, which is calculated by the co-occurrences of tags in the same items, to extend each item’s tags. Finally, item similarity based on extended tags is utilized as an item relationship regularization term to constrain the process of matrix factorization. MovieLens dataset and Book-Crossing dataset are adopted to evaluate the performance of the proposed algorithm. The results of experiments show that the proposed method can alleviate the impact of tag sparsity and improve the performance of recommender systems.

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.

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.

Comparison of Damage Models for Predicting the Non-Linear Response of Laminates Under Matrix Dominated Loading Conditions

Science.gov (United States)

Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.

2010-01-01

Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.

BCYCLIC: A parallel block tridiagonal matrix cyclic solver

Science.gov (United States)

Hirshman, S. P.; Perumalla, K. S.; Lynch, V. E.; Sanchez, R.

2010-09-01

A block tridiagonal matrix is factored with minimal fill-in using a cyclic reduction algorithm that is easily parallelized. Storage of the factored blocks allows the application of the inverse to multiple right-hand sides which may not be known at factorization time. Scalability with the number of block rows is achieved with cyclic reduction, while scalability with the block size is achieved using multithreaded routines (OpenMP, GotoBLAS) for block matrix manipulation. This dual scalability is a noteworthy feature of this new solver, as well as its ability to efficiently handle arbitrary (non-powers-of-2) block row and processor numbers. Comparison with a state-of-the art parallel sparse solver is presented. It is expected that this new solver will allow many physical applications to optimally use the parallel resources on current supercomputers. Example usage of the solver in magneto-hydrodynamic (MHD), three-dimensional equilibrium solvers for high-temperature fusion plasmas is cited.

arXiv On Matrix Factorizations, Residue Pairings and Homological Mirror Symmetry

CERN Document Server

Lerche, Wolfgang

We argue how boundary B-type Landau-Ginzburg models based on matrix factorizations can be used to compute exact superpotentials for intersecting D-brane configurations on compact Calabi-Yau spaces. In this paper, we consider the dependence of open-string, boundary changing correlators on bulk moduli. This determines, via mirror symmetry, non-trivial disk instanton corrections in the A-model. As crucial ingredient we propose a differential equation that involves matrix analogs of Saito's higher residue pairings. As example, we compute from this for the elliptic curve certain quantum products m_2 and m_3, which reproduce genuine boundary changing, open Gromov-Witten invariants.

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.

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.

Three-body forces for electrons by the S-matrix method

International Nuclear Information System (INIS)

Margaritelli, R.

1989-01-01

A electromagnetic three-body potential between eletrons is derived by the S-matrix method. This potential can be compared up to a certain point with other electromagnetic potentials (obtained by other methods) encountered in the literature. However, since the potential derived here is far more complete than others, this turns direct comparison with the potentials found in the literature somewhat difficult. These calculations allow a better understanding of the S-matrix method as applied to problems which involve the calculations of three-body nuclear forces (these calculations are performed in order to understand the 3 He form factor). Furthermore, these results enable us to decide between two discrepant works which derive the two-pion exchange three-body potential, both by the S-matrix method. (author) [pt

Compound nucleus in Livsic open-system theory: Factorization of the S matrix

International Nuclear Information System (INIS)

Avishai, Y.

1988-01-01

The compound-nucleus system fits into a mathematical theory of open systems in physics developed by the mathematician M. Livsic [Translations of Mathematical Monographs (American Mathematical Society, Providence, Rhode Island, 1973), Vol. 34]. In this article we review some basic concepts of the above theory and apply it to study the structure of the compound-nucleus S matrix. One of the results is a factorization of the S matrix in the form S(ω) = S +iA/sub k//(tau/sub k/-ω)], where A/sub k/ are known matrices and tau/sub k/ are the complex resonance energies

Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach

Science.gov (United States)

Ding, Qiaoqiao; Zan, Yunlong; Huang, Qiu; Zhang, Xiaoqun

2015-02-01

The reconstruction of dynamic images from few projection data is a challenging problem, especially when noise is present and when the dynamic images are vary fast. In this paper, we propose a variational model, sparsity enforced matrix factorization (SEMF), based on low rank matrix factorization of unknown images and enforced sparsity constraints for representing both coefficients and bases. The proposed model is solved via an alternating iterative scheme for which each subproblem is convex and involves the efficient alternating direction method of multipliers (ADMM). The convergence of the overall alternating scheme for the nonconvex problem relies upon the Kurdyka-Łojasiewicz property, recently studied by Attouch et al (2010 Math. Oper. Res. 35 438) and Attouch et al (2013 Math. Program. 137 91). Finally our proof-of-concept simulation on 2D dynamic images shows the advantage of the proposed method compared to conventional methods.

Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

Energy Technology Data Exchange (ETDEWEB)

Gittens, Alex; Devarakonda, Aditya; Racah, Evan; Ringenburg, Michael; Gerhardt, Lisa; Kottalam, Jey; Liu, Jialin; Maschhoff, Kristyn; Canon, Shane; Chhugani, Jatin; Sharma, Pramod; Yang, Jiyan; Demmel, James; Harrell, Jim; Krishnamurthy, Venkat; Mahoney, Michael; Prabhat, Mr

2016-05-12

We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics on cluster computing platforms with access to local disks and is optimized for data-parallel tasks. We examine three widely-used and important matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquity) and CX (for data interpretability). We apply these methods to 1.6TB particle physics, 2.2TB and 16TB climate modeling and 1.1TB bioimaging data. The data matrices are tall-and-skinny which enable the algorithms to map conveniently into Spark’s data parallel model. We perform scaling experiments on up to 1600 Cray XC40 nodes, describe the sources of slowdowns, and provide tuning guidance to obtain high performance.

Thermal and mechanical behavior of metal matrix and ceramic matrix composites

Science.gov (United States)

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

1990-01-01

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

An interlaboratory comparison of methods for measuring rock matrix porosity

International Nuclear Information System (INIS)

Rasilainen, K.; Hellmuth, K.H.; Kivekaes, L.; Ruskeeniemi, T.; Melamed, A.; Siitari-Kauppi, M.

1996-09-01

An interlaboratory comparison study was conducted for the available Finnish methods of rock matrix porosity measurements. The aim was first to compare different experimental methods for future applications, and second to obtain quality assured data for the needs of matrix diffusion modelling. Three different versions of water immersion techniques, a tracer elution method, a helium gas through-diffusion method, and a C-14-PMMA method were tested. All methods selected for this study were established experimental tools in the respective laboratories, and they had already been individually tested. Rock samples for the study were obtained from a homogeneous granitic drill core section from the natural analogue site at Palmottu. The drill core section was cut into slabs that were expected to be practically identical. The subsamples were then circulated between the different laboratories using a round robin approach. The circulation was possible because all methods were non-destructive, except the C-14-PMMA method, which was always the last method to be applied. The possible effect of drying temperature on the measured porosity was also preliminarily tested. These measurements were done in the order of increasing drying temperature. Based on the study, it can be concluded that all methods are comparable in their accuracy. The selection of methods for future applications can therefore be based on practical considerations. Drying temperature seemed to have very little effect on the measured porosity, but a more detailed study is needed for definite conclusions. (author) (4 refs.)

Integral transport multiregion geometrical shadowing factor for the approximate collision probability matrix calculation of infinite closely packed lattices

International Nuclear Information System (INIS)

Jowzani-Moghaddam, A.

1981-01-01

An integral transport method of calculating the geometrical shadowing factor in multiregion annular cells for infinite closely packed lattices in cylindrical geometry is developed. This analytical method has been programmed in the TPGS code. This method is based upon a consideration of the properties of the integral transport method for a nonuniform body, which together with Bonalumi's approximations allows the determination of the approximate multiregion collision probability matrix for infinite closely packed lattices with sufficient accuracy. The multiregion geometrical shadowing factors have been calculated for variations in fuel pin annular segment rings in a geometry of annular cells. These shadowing factors can then be used in the calculation of neutron transport from one annulus to another in an infinite lattice. The result of this new geometrical shadowing and collision probability matrix are compared with the Dancoff-Ginsburg correction and the probability matrix using constant shadowing on Yankee fuel elements in an infinite lattice. In these cases the Dancoff-Ginsburg correction factor and collision probability matrix using constant shadowing are in difference by at most 6.2% and 6%, respectively

Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction.

Science.gov (United States)

Liu, Yong; Wu, Min; Miao, Chunyan; Zhao, Peilin; Li, Xiao-Li

2016-02-01

In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.

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

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin

2014-01-01

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

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

KAUST Repository

Wang, Jim Jing-Yan

2014-02-01

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

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.

A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem

DEFF Research Database (Denmark)

Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Pontil, Massimiliano

2014-01-01

We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy electroencephalographic (EEG) measurements, commonly named as the EEG inverse problem. We propose a new method to induce neurophysiological meaningful solutions, which takes into account the smoothness, structured...... sparsity, and low rank of the BES matrix. The method is based on the factorization of the BES matrix as a product of a sparse coding matrix and a dense latent source matrix. The structured sparse-low-rank structure is enforced by minimizing a regularized functional that includes the ℓ21-norm of the coding...... matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We analyze the convergence of the optimization procedure, and we compare, under different synthetic scenarios...

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-12-01

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

A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets

Science.gov (United States)

Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars

2015-01-01

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

Efficient fully 3D list-mode TOF PET image reconstruction using a factorized system matrix with an image domain resolution model

International Nuclear Information System (INIS)

Zhou, Jian; Qi, Jinyi

2014-01-01

A factorized system matrix utilizing an image domain resolution model is attractive in fully 3D time-of-flight PET image reconstruction using list-mode data. In this paper, we study a factored model based on sparse matrix factorization that is comprised primarily of a simplified geometrical projection matrix and an image blurring matrix. Beside the commonly-used Siddon’s ray-tracer, we propose another more simplified geometrical projector based on the Bresenham’s ray-tracer which further reduces the computational cost. We discuss in general how to obtain an image blurring matrix associated with a geometrical projector, and provide theoretical analysis that can be used to inspect the efficiency in model factorization. In simulation studies, we investigate the performance of the proposed sparse factorization model in terms of spatial resolution, noise properties and computational cost. The quantitative results reveal that the factorization model can be as efficient as a non-factored model, while its computational cost can be much lower. In addition we conduct Monte Carlo simulations to identify the conditions under which the image resolution model can become more efficient in terms of image contrast recovery. We verify our observations using the provided theoretical analysis. The result offers a general guide to achieve the optimal reconstruction performance based on a sparse factorization model with an image domain resolution model. (paper)

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-01-01

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

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

Science.gov (United States)

Hoy, Erik P; Mazziotti, David A

2015-08-14

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-08-14

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

Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data.

Directory of Open Access Journals (Sweden)

Yaron Orenstein

Full Text Available The new technology of protein binding microarrays (PBMs allows simultaneous measurement of the binding intensities of a transcription factor to tens of thousands of synthetic double-stranded DNA probes, covering all possible 10-mers. A key computational challenge is inferring the binding motif from these data. We present a systematic comparison of four methods developed specifically for reconstructing a binding site motif represented as a positional weight matrix from PBM data. The reconstructed motifs were evaluated in terms of three criteria: concordance with reference motifs from the literature and ability to predict in vivo and in vitro bindings. The evaluation encompassed over 200 transcription factors and some 300 assays. The results show a tradeoff between how the methods perform according to the different criteria, and a dichotomy of method types. Algorithms that construct motifs with low information content predict PBM probe ranking more faithfully, while methods that produce highly informative motifs match reference motifs better. Interestingly, in predicting high-affinity binding, all methods give far poorer results for in vivo assays compared to in vitro assays.

Factorizations of rational matrix functions with application to discrete isomonodromic transformations and difference Painleve equations

International Nuclear Information System (INIS)

Dzhamay, Anton

2009-01-01

We study factorizations of rational matrix functions with simple poles on the Riemann sphere. For the quadratic case (two poles) we show, using multiplicative representations of such matrix functions, that a good coordinate system on this space is given by a mix of residue eigenvectors of the matrix and its inverse. Our approach is motivated by the theory of discrete isomonodromic transformations and their relationship with difference Painleve equations. In particular, in these coordinates, basic isomonodromic transformations take the form of the discrete Euler-Lagrange equations. Secondly we show that dPV equations, previously obtained in this context by D Arinkin and A Borodin, can be understood as simple relationships between the residues of such matrices and their inverses.

ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation

KAUST Repository

Zhang, Chuxu

2018-01-15

Data sparsity and cold-start problems are prevalent in recommender systems. To address such problems, both the observable explicit social information (e.g., user-user trust connections) and the inferable implicit correlations (e.g., implicit neighbors computed by similarity measurement) have been introduced to complement user-item ratings data for improving the performances of traditional model-based recommendation algorithms such as matrix factorization. Although effective, (1) the utilization of the explicit user-user social relationships suffers from the weakness of unavailability in real systems such as Netflix or the issue of sparse observable content like 0.03% trust density in Epinions, thus there is no or little explicit social information that can be employed to improve baseline model in real applications; (2) the current similarity measurement approaches focus on inferring implicit correlations between a user (item) and their direct neighbors or top-k similar neighbors based on user-item ratings bipartite network, so that they fail to comprehensively unfold the indirect potential relationships among users and items. To solve these issues regarding both explicit/implicit social recommendation algorithms, we design a joint model of matrix factorization and implicit walk integrative learning, i.e., ImWalkMF, which only uses explicit ratings information yet models both direct rating feedbacks and multiple direct/indirect implicit correlations among users and items from a random walk perspective. We further propose a combined strategy for training two independent components in the proposed model based on sampling. The experimental results on two real-world sparse datasets demonstrate that ImWalkMF outperforms the traditional regularized/probabilistic matrix factorization models as well as other competitive baselines that utilize explicit/implicit social information.

Sparse Nonnegative Matrix Factorization Strategy for Cochlear Implants

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

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.

SHMF: Interest Prediction Model with Social Hub Matrix Factorization

Directory of Open Access Journals (Sweden)

Chaoyuan Cui

2017-01-01

Full Text Available With the development of social networks, microblog has become the major social communication tool. There is a lot of valuable information such as personal preference, public opinion, and marketing in microblog. Consequently, research on user interest prediction in microblog has a positive practical significance. In fact, how to extract information associated with user interest orientation from the constantly updated blog posts is not so easy. Existing prediction approaches based on probabilistic factor analysis use blog posts published by user to predict user interest. However, these methods are not very effective for the users who post less but browse more. In this paper, we propose a new prediction model, which is called SHMF, using social hub matrix factorization. SHMF constructs the interest prediction model by combining the information of blogs posts published by both user and direct neighbors in user’s social hub. Our proposed model predicts user interest by integrating user’s historical behavior and temporal factor as well as user’s friendships, thus achieving accurate forecasts of user’s future interests. The experimental results on Sina Weibo show the efficiency and effectiveness of our proposed model.

Comparison of transition-matrix sampling procedures

DEFF Research Database (Denmark)

Yevick, D.; Reimer, M.; Tromborg, Bjarne

2009-01-01

We compare the accuracy of the multicanonical procedure with that of transition-matrix models of static and dynamic communication system properties incorporating different acceptance rules. We find that for appropriate ranges of the underlying numerical parameters, algorithmically simple yet high...... accurate procedures can be employed in place of the standard multicanonical sampling algorithm....

A New EM CKM Matrix: Implications of the Nucleon Strange Quark Content, Anomalous Magnetic Moments of Nucleons and Electric and Magnetic Nucleon Form Factors

Science.gov (United States)

Ward, Thomas

2013-10-01

A new electromagnetic neutral-current quark mixing matrix, analog to the well-known Cabibbo-Kobayashi-Maskawa (CKM) weak charge-current matrix, is proposed to account for the strange quark content of the neutron and proton and part of the anomalous axial vector magnetic moments. The EM-CKM matrix is shown to be equivalent to the weak-CKM matrix following an EM to weak gauge symmetry transformation, demonstrating the universality of the Standard Model (SM) CKM quark mixing matrix. The electric and magnetic form factors are reformulated using a new QCD three quark nucleon gyromagnetic factor, Dirac and Pauli form factors and anomalous kappa factors. The old 1943 Jauch form factors which have been systematically used and developed for many years is shown to be in stark disagreement with the new global set of experimental polarized electron-proton scattering data whereas the reformulated SM parameter set of this study is shown to agree very well, lending strong support for this new EM SM approach.

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

Science.gov (United States)

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

2014-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-15

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

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.

Calculation of the fast multiplication factor by the fission matrix method

International Nuclear Information System (INIS)

Naumov, V.A.; Rozin, S.G.; Ehl'perin, T.I.

1976-01-01

A variation of the Monte Carlo method to calculate an effective breeding factor of a nuclear reactor is described. The evaluation procedure of reactivity perturbations by the Monte Carlo method in the first order perturbation theory is considered. The method consists in reducing an integral neutron transport equation to a set of linear algebraic equations. The coefficients of this set are elements of a fission matrix. The fission matrix being a Grin function of the neutron transport equation, is evaluated by the Monte Carlo method. In the program realizing the suggested algorithm, the game for initial neutron energy of a fission spectrum and then for the region of neutron birth, ΔVsub(f)sup(i)has been played in proportion to the product of Σsub(f)sup(i)ΔVsub(f)sup(i), where Σsub(f)sup(i) is a macroscopic cross section in the region numbered at the birth energy. Further iterations of a space distribution of neutrons in the system are performed by the generation method. In the adopted scheme of simulation of neutron histories the emission of secondary neutrons is controlled by weights; it occurs at every collision and not only in the end on the history. The breeding factor is calculated simultaneously with the space distribution of neutron worth in the system relative to the fission process and neutron flux. Efficiency of the described procedure has been tested on the calculation of the breeding factor for the Godiva assembly, simulating a fast reactor with a hard spectrum. A high accuracy of calculations at moderate number of zones in the core and reasonable statistics has been stated

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

Science.gov (United States)

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

2017-10-01

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

Reduction in the Number of Comparisons Required to Create Matrix of Expert Judgment in the Comet Method

Directory of Open Access Journals (Sweden)

Sałabun Wojciech

2014-09-01

Full Text Available Multi-criteria decision-making (MCDM methods are associated with the ranking of alternatives based on expert judgments made using a number of criteria. In the MCDM field, the distance-based approach is one popular method for receiving a final ranking. One of the newest MCDM method, which uses the distance-based approach, is the Characteristic Objects Method (COMET. In this method, the preferences of each alternative are obtained on the basis of the distance from the nearest characteristic ob jects and their values. For this purpose, the domain and fuzzy numbers set for all the considered criteria are determined. The characteristic objects are obtained as the combination of the crisp values of all the fuzzy numbers. The preference values of all the characteristic ob ject are determined based on the tournament method and the principle of indifference. Finally, the fuzzy model is constructed and is used to calculate preference values of the alternatives. In this way, a multi-criteria model is created and it is free of rank reversal phenomenon. In this approach, the matrix of expert judgment is necessary to create. For this purpose, an expert has to compare all the characteristic ob jects with each other. The number of necessary comparisons depends squarely to the number of ob jects. This study proposes the improvement of the COMET method by using the transitivity of pairwise comparisons. Three numerical examples are used to illustrate the efficiency of the proposed improvement with respect to results from the original approach. The proposed improvement reduces significantly the number of necessary comparisons to create the matrix of expert judgment.

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.

Factors associated with continuance commitment to FAA matrix teams.

Science.gov (United States)

1993-11-01

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

Fibroblast growth factor receptor 4 regulates tumor invasion by coupling fibroblast growth factor signaling to extracellular matrix degradation

DEFF Research Database (Denmark)

Sugiyama, Nami; Varjosalo, Markku; Meller, Pipsa

2010-01-01

/stroma border and tumor invasion front. The strongest overall coexpression was found in prostate carcinoma. Studies with cultured prostate carcinoma cell lines showed that the FGFR4-R388 variant, which has previously been associated with poor cancer prognosis, increased MT1-MMP-dependent collagen invasion......Aberrant expression and polymorphism of fibroblast growth factor receptor 4 (FGFR4) has been linked to tumor progression and anticancer drug resistance. We describe here a novel mechanism of tumor progression by matrix degradation involving epithelial-to-mesenchymal transition in response...... to membrane-type 1 matrix metalloproteinase (MT1-MMP, MMP-14) induction at the edge of tumors expressing the FGFR4-R388 risk variant. Both FGFR4 and MT1-MMP were upregulated in tissue biopsies from several human cancer types including breast adenocarcinomas, where they were partially coexpressed at the tumor...

Comparison of matrix methods for elastic wave scattering problems

International Nuclear Information System (INIS)

Tsao, S.J.; Varadan, V.K.; Varadan, V.V.

1983-01-01

This article briefly describes the T-matrix method and the MOOT (method of optimal truncation) of elastic wave scattering as they apply to A-D, SH- wave problems as well as 3-D elastic wave problems. Two methods are compared for scattering by elliptical cylinders as well as oblate spheroids of various eccentricity as a function of frequency. Convergence, and symmetry of the scattering cross section are also compared for ellipses and spheroidal cavities of different aspect ratios. Both the T-matrix approach and the MOOT were programmed on an AMDHL 470 computer using double precision arithmetic. Although the T-matrix method and MOOT are not always in agreement, it is in no way implied that any of the published results using MOOT are in error

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...

Comparison of two matrix data structures for advanced CSM testbed applications

Science.gov (United States)

Regelbrugge, M. E.; Brogan, F. A.; Nour-Omid, B.; Rankin, C. C.; Wright, M. A.

1989-01-01

The first section describes data storage schemes presently used by the Computational Structural Mechanics (CSM) testbed sparse matrix facilities and similar skyline (profile) matrix facilities. The second section contains a discussion of certain features required for the implementation of particular advanced CSM algorithms, and how these features might be incorporated into the data storage schemes described previously. The third section presents recommendations, based on the discussions of the prior sections, for directing future CSM testbed development to provide necessary matrix facilities for advanced algorithm implementation and use. The objective is to lend insight into the matrix structures discussed and to help explain the process of evaluating alternative matrix data structures and utilities for subsequent use in the CSM testbed.

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.

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

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

Science.gov (United States)

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

2017-07-27

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

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.

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.

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....

Effective Factors in Severity of Traffic Accident-Related Traumas; an Epidemiologic Study Based on the Haddon Matrix.

Science.gov (United States)

Masoumi, Kambiz; Forouzan, Arash; Barzegari, Hassan; Asgari Darian, Ali; Rahim, Fakher; Zohrevandi, Behzad; Nabi, Somayeh

2016-01-01

Traffic accidents are the 8(th) cause of mortality in different countries and are expected to rise to the 3(rd) rank by 2020. Based on the Haddon matrix numerous factors such as environment, host, and agent can affect the severity of traffic-related traumas. Therefore, the present study aimed to evaluate the effective factors in severity of these traumas based on Haddon matrix. In the present 1-month cross-sectional study, all the patients injured in traffic accidents, who were referred to the ED of Imam Khomeini and Golestan Hospitals, Ahvaz, Iran, during March 2013 were evaluated. Based on the Haddon matrix, effective factors in accident occurrence were defined in 3 groups of host, agent, and environment. Demographic data of the patients and data regarding Haddon risk factors were extracted and analyzed using SPSS version 20. 700 injured people with the mean age of 29.66 ± 12.64 years (3-82) were evaluated (92.4% male). Trauma mechanism was car-pedestrian in 308 (44%) of the cases and car-motorcycle in 175 (25%). 610 (87.1%) cases were traffic accidents and 371 (53%) occurred in the time between 2 pm and 8 pm. Violation of speed limit was the most common violation with 570 (81.4%) cases, followed by violation of right-of-way in 57 (8.1%) patients. 59.9% of the severe and critical injuries had occurred on road accidents, while 61.3% of the injuries caused by traffic accidents were mild to moderate (p accidents (p severity of traffic accident-related traumas were age over 50, not using safety tools, and undertaking among host-related factors; insufficient environment safety, road accidents and time between 2 pm and 8 pm among environmental factors; and finally, rollover, car-pedestrian, and motorcycle-pedestrian accidents among the agent factors.

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 ...

Fibroblasts and the extracellular matrix in right ventricular disease.

Science.gov (United States)

Frangogiannis, Nikolaos G

2017-10-01

Right ventricular failure predicts adverse outcome in patients with pulmonary hypertension (PH), and in subjects with left ventricular heart failure and is associated with interstitial fibrosis. This review manuscript discusses the cellular effectors and molecular mechanisms implicated in right ventricular fibrosis. The right ventricular interstitium contains vascular cells, fibroblasts, and immune cells, enmeshed in a collagen-based matrix. Right ventricular pressure overload in PH is associated with the expansion of the fibroblast population, myofibroblast activation, and secretion of extracellular matrix proteins. Mechanosensitive transduction of adrenergic signalling and stimulation of the renin-angiotensin-aldosterone cascade trigger the activation of right ventricular fibroblasts. Inflammatory cytokines and chemokines may contribute to expansion and activation of macrophages that may serve as a source of fibrogenic growth factors, such as transforming growth factor (TGF)-β. Endothelin-1, TGF-βs, and matricellular proteins co-operate to activate cardiac myofibroblasts, and promote synthesis of matrix proteins. In comparison with the left ventricle, the RV tolerates well volume overload and ischemia; whether the right ventricular interstitial cells and matrix are implicated in these favourable responses remains unknown. Expansion of fibroblasts and extracellular matrix protein deposition are prominent features of arrhythmogenic right ventricular cardiomyopathies and may be implicated in the pathogenesis of arrhythmic events. Prevailing conceptual paradigms on right ventricular remodelling are based on extrapolation of findings in models of left ventricular injury. Considering the unique embryologic, morphological, and physiologic properties of the RV and the clinical significance of right ventricular failure, there is a need further to dissect RV-specific mechanisms of fibrosis and interstitial remodelling. Published on behalf of the European Society of

Development and validation of a job exposure matrix for physical risk factors in low back pain.

Science.gov (United States)

Solovieva, Svetlana; Pehkonen, Irmeli; Kausto, Johanna; Miranda, Helena; Shiri, Rahman; Kauppinen, Timo; Heliövaara, Markku; Burdorf, Alex; Husgafvel-Pursiainen, Kirsti; Viikari-Juntura, Eira

2012-01-01

The aim was to construct and validate a gender-specific job exposure matrix (JEM) for physical exposures to be used in epidemiological studies of low back pain (LBP). We utilized two large Finnish population surveys, one to construct the JEM and another to test matrix validity. The exposure axis of the matrix included exposures relevant to LBP (heavy physical work, heavy lifting, awkward trunk posture and whole body vibration) and exposures that increase the biomechanical load on the low back (arm elevation) or those that in combination with other known risk factors could be related to LBP (kneeling or squatting). Job titles with similar work tasks and exposures were grouped. Exposure information was based on face-to-face interviews. Validity of the matrix was explored by comparing the JEM (group-based) binary measures with individual-based measures. The predictive validity of the matrix against LBP was evaluated by comparing the associations of the group-based (JEM) exposures with those of individual-based exposures. The matrix includes 348 job titles, representing 81% of all Finnish job titles in the early 2000s. The specificity of the constructed matrix was good, especially in women. The validity measured with kappa-statistic ranged from good to poor, being fair for most exposures. In men, all group-based (JEM) exposures were statistically significantly associated with one-month prevalence of LBP. In women, four out of six group-based exposures showed an association with LBP. The gender-specific JEM for physical exposures showed relatively high specificity without compromising sensitivity. The matrix can therefore be considered as a valid instrument for exposure assessment in large-scale epidemiological studies, when more precise but more labour-intensive methods are not feasible. Although the matrix was based on Finnish data we foresee that it could be applicable, with some modifications, in other countries with a similar level of technology.

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....

Factorization of J-unitary matrix polynomials on the line and a Schur algorithm for generalized Nevanlinna functions

NARCIS (Netherlands)

Alpay, D.; Dijksma, A.; Langer, H.

2004-01-01

We prove that a 2 × 2 matrix polynomial which is J-unitary on the real line can be written as a product of normalized elementary J-unitary factors and a J-unitary constant. In the second part we give an algorithm for this factorization using an analog of the Schur transformation.

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.

Matrix completion via a low rank factorization model and an Augmented Lagrangean Succesive Overrelaxation Algorithm

Directory of Open Access Journals (Sweden)

Hugo Lara

2014-12-01

Full Text Available The matrix completion problem (MC has been approximated by using the nuclear norm relaxation. Some algorithms based on this strategy require the computationally expensive singular value decomposition (SVD at each iteration. One way to avoid SVD calculations is to use alternating methods, which pursue the completion through matrix factorization with a low rank condition. In this work an augmented Lagrangean-type alternating algorithm is proposed. The new algorithm uses duality information to define the iterations, in contrast to the solely primal LMaFit algorithm, which employs a Successive Over Relaxation scheme. The convergence result is studied. Some numerical experiments are given to compare numerical performance of both proposals.

Coal Matrix Deformation and Pore Structure Change in High-Pressure Nitrogen Replacement of Methane

Directory of Open Access Journals (Sweden)

Xiaofeng Ji

2018-01-01

Full Text Available Coal matrix deformation is one of the main controlling factors for coal reservoir permeability changes in nitrogen foam fracturing. The characteristics and mechanism of coal matrix deformation during the process of adsorption/desorption were studied by isothermal adsorption/desorption experiments with methane and nitrogen. Based on the free-energy theories, the Langmuir equation, and elastic mechanics, mathematical models of coal matrix deformation were developed and the deformation characteristics in adsorption/desorption processes were examined. From the study, we deduced that the coal matrix swelling, caused by methane adsorption, was a Langmuir-type relationship with the gas pressure, and exponentially increased as the adsorption quantity increased. Then, the deformation rate and amplitude of the coal matrix decreased gradually with the increase of the pressure. At the following stage, where nitrogen replaces methane, the coal matrix swelling continued but the deformation amplitude decreased, which was only 19.60% of the methane adsorption stage. At the mixed gas desorption stage, the coal matrix shrank with the reduction of pressure and the shrinkage amount changed logarithmically with the pressure, which had the hysteresis effect when compared with the swelling in adsorption. The mechanism of coal matrix deformation was discussed through a comparison of the change of micropores, mesopores, and also part macropores in the adsorption process.

The interplay of matrix metalloproteinases, morphogens and growth factors is necessary for branching of mammary epithelial cells

OpenAIRE

Simian, Marina; Hirai, Yohei; Navre, Marc; Werb, Zena; Lochter, Andre; Bissell, Mina J.

2001-01-01

The mammary gland develops its adult form by a process referred to as branching morphogenesis. Many factors have been reported to affect this process. We have used cultured primary mammary epithelial organoids and mammary epithelial cell lines in three-dimensional collagen gels to elucidate which growth factors, matrix metalloproteinases (MMPs) and mammary morphogens interact in branching morphogenesis. Branching stimulated by stromal fibroblasts, epidermal growth factor, fibroblast growth fa...

Angiogenesis in vestibular schwannomas: expression of extracellular matrix factors MMP-2, MMP-9, and TIMP-1

DEFF Research Database (Denmark)

Møller, Martin Nue; Werther, Kim; Nalla, Amarnadh

2010-01-01

Vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) are potent mediators of tumor angiogenesis. It has been demonstrated that vestibular schwannoma VEGF expression correlates with tumor growth pattern, whereas knowledge on the expression of MMPs is lacking. This study...

Monte Carlo determination of the infinite matrix dose rate correction factors for 250 μm quartz and TLD500 chip

International Nuclear Information System (INIS)

Baly, L.; Martín, G.; Quesada, I.; Padilla, F.; Arteche, R.

2015-01-01

A new approach based on the Monte Carlo simulation is used to calculate the infinite matrix dose rate correction factors of gamma, beta and internal conversion radiations for 250 μm diameter grains of quartz and TLD500 chips. Here, the dependence of the correction factor on the radiation energy is initially calculated for each type of emitted particle and with this result the correction factors for the 232 Th and 238 U series and 40 K are determined. This analysis is made for dry soil and also for different levels of water content in it. The obtained beta correction factors for quartz are in good agreement with those previously reported. For the TLD500 chip certain differences with previously reported data are found. The analysis of the gamma water correction factor for quartz based on Zimmerman equation shows the correspondence with the similar correction factor for electrons. In the case of TLD500 chip a gamma water correction factor value of 1.0 was found. - Highlights: • A new approach based on Monte Carlo simulation is used to compute infinite matrix dose rate correction factors. • Infinite matrix models with real dimensions were analyzed within 3% uncertainties. • The dependence of grain size attenuation on particle energy is determined. • The same dependence for water correction factors is also analyzed

Investigation of occupational health and safety application using the internal and external factor assessment matrix: SWOT

Directory of Open Access Journals (Sweden)

2012-09-01

Material and Method: IIn this study, the threats, opportunities, weaknesses and strengths were evaluated by one of the tools named SWOT, in one of the assembly industries company in Iran, in order to controlling the operations in this company considering to safety and health standard (OHSAS18001. A comparison of the company’s performance in implementing the safety and health standards was done between years 1387 and 1388 contain in the Company considered, and weighted scoring weaknesses, strengths, threats and opportunities using the matrix of internal factors (strengths and weaknesses and external factors (treats and opportunities then, the importance of each factor were determined in the company’s implementation and enforcement of those standards. . Result: Focusing on the strengths and weaknesses, opportunities and threats, some strategies to improve the implementation were presented. Any points were weighted based on the most important weaknesses identified as the lack of monitoring contractors, lack of management commitment for implementation of OHSAS18001, no attempt to identify the risks of change, lack of training needs assessment, main strengths identified in the context of adequate budget health and safety, environmental efforts, identify risk for abnormal conditions, the most important threats for immediate delivery customer orders and the opportunity to support the safety and health plans, were determined. . Conclusion: Sum of the weighted scores in year 87 were obtained for the external factors (opportunities and threats, 2.16 and internal factors (strengths and weaknesses 1.66. Both of these scores were less than 2.5 (minimum amount of the acceptable rate so, the company has been poor performance in the implementation of this standard for the year 87 and a weak reaction in the use of opportunities and the minimize threats has. In case of internal factors, it was worse than external one and the situation was more bold of the weaknesses companies to

Turbo-SMT: Parallel Coupled Sparse Matrix-Tensor Factorizations and Applications

Science.gov (United States)

Papalexakis, Evangelos E.; Faloutsos, Christos; Mitchell, Tom M.; Talukdar, Partha Pratim; Sidiropoulos, Nicholas D.; Murphy, Brian

2016-01-01

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ’edible’, ’fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem. Can we enhance any CMTF solver, so that it can operate on potentially very large datasets that may not fit in main memory? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, produces sparse and interpretable solutions, and parallelizes any CMTF algorithm, producing sparse and interpretable solutions (up to 65 fold). Additionally, we improve upon ALS, the work-horse algorithm for CMTF, with respect to efficiency and robustness to missing values. We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy. Finally, we demonstrate the generality of Turbo-SMT, by applying it on a Facebook dataset (users, ’friends’, wall-postings); there, Turbo-SMT spots spammer-like anomalies. PMID:27672406

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.

Insulin-like growth factor I has independent effects on bone matrix formation and cell replication

International Nuclear Information System (INIS)

Hock, J.M.; Centrella, M.; Canalis, E.

1988-01-01

The effects of insulin-like growth factor-I (IGF-I) and insulin on bone matrix synthesis and bone cell replication were studied in cultured 21-day-old fetal rat calvariae. Histomorphometry techniques were developed to measure the incorporation of [2,3- 3 H]proline and [methyl- 3 H]thymidine into bone matrix and bone cell nuclei, respectively, using autoradiographs of sagittal sections of calvariae cultured with IGF-I, insulin, or vehicle for up to 96 h. To confirm an effect on bone formation, IGF-I was also studied for its effects on [ 3 H]proline incorporation into collagenase-digestible protein (CDP) and noncollagen protein and on [ 3 H]thymidine incorporation into acid-precipitable material (DNA). IGF-I at 10(-9)-10(-7) M significantly increased the rate of bone matrix apposition and CDP after 24 h by 45-50% and increased cell labeling by 8-fold in the osteoprogenitor cell zone, by 4-fold in the osteoblast cell zone, and by 2-fold in the periosteal fibroblast zone. Insulin at 10(-9)-10(-6) M also increased matrix apposition rate and CDP by 40-50%, but increased cell labeling by 2-fold only at a concentration of 10(-7) M or higher and then only in the osteoprogenitor cell zone. When hydroxyurea was added to IGF-I-treated bones, the effects of IGF-I on DNA synthesis were abolished, but the increase in bone matrix apposition induced by IGF-I was only partly diminished. In conclusion, IGF-I stimulates matrix synthesis in calvariae, an effect that is partly, although not completely, dependent on its stimulatory effect on DNA synthesis

A DSP controlled one-to-three phase matrix converter

Energy Technology Data Exchange (ETDEWEB)

Dubovsky, J.; Dobrucly, B; Tabacek, R.; Havrila, R. [Department of Electric Traction and Energetics Faculty of Electrical Engineering, University of Zilina (Slovakia)

1997-12-31

This paper deals with the theoretical analysis computer simulation and experimental results of IM fed by a one-to-three phase matrix converter which offers a unique solution for single phase electric traction applications. The proposed drive in comparison with currently used conventional drives reduces the number of power switching elements of the converter, which increases drives dependability and brings lower investment in power electronics used in drive. Further advantage is that the converter is controlled with nearly unity power factor which cuts down the operational expenses and offers higher overall performance of the drive. (orig.) 6 refs.

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.

Matrix dimensions bias demographic inferences: implications for comparative plant demography.

Science.gov (United States)

Salguero-Gómez, Roberto; Plotkin, Joshua B

2010-12-01

While the wealth of projection matrices in plant demography permits comparative studies, variation in matrix dimensions complicates interspecific comparisons. Collapsing matrices to a common dimension may facilitate such comparisons but may also bias the inferred demographic parameters. Here we examine how matrix dimension affects inferred demographic elasticities and how different collapsing criteria perform. We analyzed 13 x 13 matrices representing nine plant species, collapsing these matrices (i) into even 7 x 7, 5 x 5, 4 x 4, and 3 x 3 matrices and (ii) into 5 x 5 matrices using different criteria. Stasis and fecundity elasticities increased when matrix dimension was reduced, whereas those of progression and retrogression decreased. We suggest a collapsing criterion that minimizes dissimilarities between the original- and collapsed-matrix elasticities and apply it to 66 plant species to study how life span and growth form influence the relationship between matrix dimension and elasticities. Our analysis demonstrates that (i) projection matrix dimension has significant effects on inferred demographic parameters, (ii) there are better-performing methods than previously suggested for standardizing matrix dimension, and (iii) herbaceous perennial projection matrices are particularly sensitive to changes in matrix dimensionality. For comparative demographic studies, we recommend normalizing matrices to a common dimension by collapsing higher classes and leaving the first few classes unaltered.

Nonselective matrix metalloproteinase but not tumor necrosis factor-a inhibition effectively preserves the early critical colon anastomotic integrity

DEFF Research Database (Denmark)

Ågren, Magnus S.; Andersen, Thomas L.; Andersen, Line

2011-01-01

Increased matrix metalloproteinase (MMP) activity has been implicated in the pathogenesis of colorectal anastomotic leakage. Tumor necrosis factor-a (TNF-a) induces MMPs and may influence anastomosis repair....

Development and validation of a job exposure matrix for physical risk factors in low back pain.

Directory of Open Access Journals (Sweden)

Svetlana Solovieva

Full Text Available OBJECTIVES: The aim was to construct and validate a gender-specific job exposure matrix (JEM for physical exposures to be used in epidemiological studies of low back pain (LBP. MATERIALS AND METHODS: We utilized two large Finnish population surveys, one to construct the JEM and another to test matrix validity. The exposure axis of the matrix included exposures relevant to LBP (heavy physical work, heavy lifting, awkward trunk posture and whole body vibration and exposures that increase the biomechanical load on the low back (arm elevation or those that in combination with other known risk factors could be related to LBP (kneeling or squatting. Job titles with similar work tasks and exposures were grouped. Exposure information was based on face-to-face interviews. Validity of the matrix was explored by comparing the JEM (group-based binary measures with individual-based measures. The predictive validity of the matrix against LBP was evaluated by comparing the associations of the group-based (JEM exposures with those of individual-based exposures. RESULTS: The matrix includes 348 job titles, representing 81% of all Finnish job titles in the early 2000s. The specificity of the constructed matrix was good, especially in women. The validity measured with kappa-statistic ranged from good to poor, being fair for most exposures. In men, all group-based (JEM exposures were statistically significantly associated with one-month prevalence of LBP. In women, four out of six group-based exposures showed an association with LBP. CONCLUSIONS: The gender-specific JEM for physical exposures showed relatively high specificity without compromising sensitivity. The matrix can therefore be considered as a valid instrument for exposure assessment in large-scale epidemiological studies, when more precise but more labour-intensive methods are not feasible. Although the matrix was based on Finnish data we foresee that it could be applicable, with some modifications, in

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)

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)

Well screening for matrix stimulation treatments

International Nuclear Information System (INIS)

Saavedra, N; Solano, R; Gidley, J; Reyes, C.A; Rodriguez; Kondo, F; Hernandez, J

1998-01-01

Matrix acidizing is a stimulation technique only applicable to wells with surrounding damage. It is therefore very important to differentiate the real formation damage from the damage caused by flow Ni dynamic effects. The mechanical damage corresponds to flow restrictions caused by partial penetration, poor perforation as well as to reduce diameters of the production tubing. The dynamic effects are generated by inertia caused by high flow rates and high-pressure differentials. A common practice in our oil fields is to use a general formulation as acid treatment, most of the times without previous lab studies that guarantee the applicability of the treatment in the formation. Additionally, stimulation is randomly applied even treating undamaged wells with negative results and in the best of the cases, loss of the treatment. The selection of the well for matrix stimulation is an essential factor for the success of the treatment. Selection is done through the evaluation of the skin factor (S) and of the economic benefits of reducing the skin in comparison to the cost of the work. The most appropriate tool for skin evaluation is a good pressure test where the radial flow period can be identified. Nevertheless, we normally find-outdated tests most of the times taken with inaccurate tools. The interpretation problem is worsened by completions in which there is simultaneous production from several sand packages and it is difficult to individually differentiate damage factors. This works states a procedure for the selection of wells appropriate for stimulation; it also proposes a method to evaluate the skin factor when there are no accurate interpretations of the pressure tests. A new and increasingly applied methodology to treat wells with high water cuts, which are usually discarded due to the risk of stimulating water zones, is also mentioned

Global unitary fixing and matrix-valued correlations in matrix models

International Nuclear Information System (INIS)

Adler, Stephen L.; Horwitz, Lawrence P.

2003-01-01

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

Effect of cannabidiol on human gingival fibroblast extracellular matrix metabolism: MMP production and activity, and production of fibronectin and transforming growth factor β.

Science.gov (United States)

Rawal, S Y; Dabbous, M Kh; Tipton, D A

2012-06-01

Marijuana (Cannabis sativa) use may be associated with gingival enlargement, resembling that caused by phenytoin. Cannabidiol (CBD), a nonpsychotropic Cannabis derivative, is structurally similar to phenytoin. While there are many reports on effects of phenytoin on human gingival fibroblasts, there is no information on effects of Cannabis components on these cells. The objective of this study was to determine effects of CBD on human gingival fibroblast fibrogenic and matrix-degrading activities. Fibroblasts were incubated with CBD in serum-free medium for 1-6 d. The effect of CBD on cell viability was determined by measuring activity of a mitochondrial enzyme. The fibrogenic molecule transforming growth factor β and the extracellular matrix molecule fibronectin were measured by ELISA. Pro-MMP-1 and total MMP-2 were measured by ELISA. Activity of MMP-2 was determined via a colorimetric assay in which a detection enzyme is activated by active MMP-2. Data were analysed using ANOVA and Scheffe's F procedure for post hoc comparisons. Cannabidiol had little or no significant effect on cell viability. Low CBD concentrations increased transforming growth factor β production by as much as 40% (p Cannabidiol increased fibronectin production by as much as approximately 100% (p < 0.001). Lower CBD concentrations increased MMP production, but the highest concentrations decreased production of both MMPs (p < 0.05) and decreased MMP-2 activity (p < 0.02). The data suggest that the CBD may promote fibrotic gingival enlargement by increasing gingival fibroblast production of transforming growth factor β and fibronectin, while decreasing MMP production and activity. © 2011 John Wiley & Sons A/S.

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.

Interpretation of organic components from Positive Matrix Factorization of aerosol mass spectrometric data

Directory of Open Access Journals (Sweden)

I. M. Ulbrich

2009-05-01

Full Text Available The organic aerosol (OA dataset from an Aerodyne Aerosol Mass Spectrometer (Q-AMS collected at the Pittsburgh Air Quality Study (PAQS in September 2002 was analyzed with Positive Matrix Factorization (PMF. Three components – hydrocarbon-like organic aerosol OA (HOA, a highly-oxygenated OA (OOA-1 that correlates well with sulfate, and a less-oxygenated, semi-volatile OA (OOA-2 that correlates well with nitrate and chloride – are identified and interpreted as primary combustion emissions, aged SOA, and semivolatile, less aged SOA, respectively. The complexity of interpreting the PMF solutions of unit mass resolution (UMR AMS data is illustrated by a detailed analysis of the solutions as a function of number of components and rotational forcing. A public web-based database of AMS spectra has been created to aid this type of analysis. Realistic synthetic data is also used to characterize the behavior of PMF for choosing the best number of factors, and evaluating the rotations of non-unique solutions. The ambient and synthetic data indicate that the variation of the PMF quality of fit parameter (Q, a normalized chi-squared metric vs. number of factors in the solution is useful to identify the minimum number of factors, but more detailed analysis and interpretation are needed to choose the best number of factors. The maximum value of the rotational matrix is not useful for determining the best number of factors. In synthetic datasets, factors are "split" into two or more components when solving for more factors than were used in the input. Elements of the "splitting" behavior are observed in solutions of real datasets with several factors. Significant structure remains in the residual of the real dataset after physically-meaningful factors have been assigned and an unrealistic number of factors would be required to explain the remaining variance. This residual structure appears to be due to variability in the spectra of the components

Matrix Elements in Fermion Dynamical Symmetry Model

Institute of Scientific and Technical Information of China (English)

LIU Guang-Zhou; LIU Wei

2002-01-01

In a neutron-proton system, the matrix elements of the generators for SO(8) × SO(8) symmetry areconstructed explicitly, and with these matrix elements the low-lying excitation spectra obtained by diagonalization arepresented. The excitation spectra for SO(7) nuclei Pd and Ru isotopes and SO(6) r-soft rotational nuclei Xe, Ba, andCe isotopes are calculated, and comparison with the experimental results is carried out.

Matrix Elements in Fermion Dynamical Symmetry Model

Institute of Scientific and Technical Information of China (English)

LIUGuang－Zhou; LIUWei

2002-01-01

In a neutron-proton system,the matrix elements of the generators for SO(8)×SO(8) symmetry are constructed exp;icitly,and with these matrix elements the low-lying excitation spsectra obtained by diagonalization are presented.The excitation spectra for SO(7) nuclei Pd and Ru isotopes and SO(6) r-soft rotational nuclei Xe,Ba,and Ce isotopes are calculated,and comparison with the experimental results is carried out.

Effective Factors in Severity of Traffic Accident-Related Traumas; an Epidemiologic Study Based on the Haddon Matrix

Directory of Open Access Journals (Sweden)

Kambiz Masoumi

2016-04-01

Full Text Available Introduction: Traffic accidents are the 8th cause of mortality in different countries and are expected to rise to the 3rd rank by 2020. Based on the Haddon matrix numerous factors such as environment, host, and agent can affect the severity of traffic-related traumas. Therefore, the present study aimed to evaluate the effective factors in severity of these traumas based on Haddon matrix. Methods: In the present 1-month cross-sectional study, all the patients injured in traffic accidents, who were referred to the ED of Imam Khomeini and Golestan Hospitals, Ahvaz, Iran, during March 2013 were evaluated. Based on the Haddon matrix, effective factors in accident occurrence were defined in 3 groups of host, agent, and environment. Demographic data of the patients and data regarding Haddon risk factors were extracted and analyzed using SPSS version 20. Results: 700 injured people with the mean age of 29.66 ± 12.64 years (3-82 were evaluated (92.4% male. Trauma mechanism was car-pedestrian in 308 (44% of the cases and car-motorcycle in 175 (25%. 610 (87.1% cases were traffic accidents and 371 (53% occurred in the time between 2 pm and 8 pm. Violation of speed limit was the most common violation with 570 (81.4% cases, followed by violation of right-of-way in 57 (8.1% patients. 59.9% of the severe and critical injuries had occurred on road accidents, while 61.3% of the injuries caused by traffic accidents were mild to moderate (p < 0.001. The most common mechanisms of trauma for critical injuries were rollover (72.5%, motorcycle-pedestrian (23.8%, and car-motorcycle (13.14% accidents (p < 0.001. Conclusion: Based on the results of the present study, the most important effective factors in severity of traffic accident-related traumas were age over 50, not using safety tools, and undertaking among host-related factors; insufficient environment safety, road accidents and time between 2 pm and 8 pm among environmental factors; and finally, rollover, car

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...

Correlation matrix for quartet codon usage

CERN Document Server

Frappat, L; Sorba, Paul

2005-01-01

It has been argued that the sum of usage probabilities for codons, belonging to quartets, that have as third nucleotide C or A, is independent of the biological species for vertebrates. The comparison between the theoretical correlation matrix derived from these sum rules and the experimentally computed matrix for 26 species shows a satisfactory agreement. The Shannon entropy, weakly depending on the biological species, gives further support. Suppression of codons containing the dinucleotides CG or AU is put in evidence.

Variational optimization algorithms for uniform matrix product states

Science.gov (United States)

Zauner-Stauber, V.; Vanderstraeten, L.; Fishman, M. T.; Verstraete, F.; Haegeman, J.

2018-01-01

We combine the density matrix renormalization group (DMRG) with matrix product state tangent space concepts to construct a variational algorithm for finding ground states of one-dimensional quantum lattices in the thermodynamic limit. A careful comparison of this variational uniform matrix product state algorithm (VUMPS) with infinite density matrix renormalization group (IDMRG) and with infinite time evolving block decimation (ITEBD) reveals substantial gains in convergence speed and precision. We also demonstrate that VUMPS works very efficiently for Hamiltonians with long-range interactions and also for the simulation of two-dimensional models on infinite cylinders. The new algorithm can be conveniently implemented as an extension of an already existing DMRG implementation.

A Normalized Transfer Matrix Method for the Free Vibration of Stepped Beams: Comparison with Experimental and FE(3D Methods

Directory of Open Access Journals (Sweden)

Tamer Ahmed El-Sayed

2017-01-01

Full Text Available The exact solution for multistepped Timoshenko beam is derived using a set of fundamental solutions. This set of solutions is derived to normalize the solution at the origin of the coordinates. The start, end, and intermediate boundary conditions involve concentrated masses and linear and rotational elastic supports. The beam start, end, and intermediate equations are assembled using the present normalized transfer matrix (NTM. The advantage of this method is that it is quicker than the standard method because the size of the complete system coefficient matrix is 4 × 4. In addition, during the assembly of this matrix, there are no inverse matrix steps required. The validity of this method is tested by comparing the results of the current method with the literature. Then the validity of the exact stepped analysis is checked using experimental and FE(3D methods. The experimental results for stepped beams with single step and two steps, for sixteen different test samples, are in excellent agreement with those of the three-dimensional finite element FE(3D. The comparison between the NTM method and the finite element method results shows that the modal percentage deviation is increased when a beam step location coincides with a peak point in the mode shape. Meanwhile, the deviation decreases when a beam step location coincides with a straight portion in the mode shape.

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.

ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.

Science.gov (United States)

Lee, Keunbaik; Baek, Changryong; Daniels, Michael J

2017-11-01

In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.

Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

Science.gov (United States)

Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

2018-05-01

Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

Comparison of Matrix Frequency-Doubling Technology (FDT) Perimetry with the SWEDISH Interactive Thresholding Algorithm (SITA) Standard Automated Perimetry (SAP) in Mild Glaucoma.

Science.gov (United States)

Doozandeh, Azadeh; Irandoost, Farnoosh; Mirzajani, Ali; Yazdani, Shahin; Pakravan, Mohammad; Esfandiari, Hamed

2017-01-01

This study aimed to compare second-generation frequency-doubling technology (FDT) perimetry with standard automated perimetry (SAP) in mild glaucoma. Forty-seven eyes of 47 participants who had mild visual field defect by SAP were included in this study. All participants were examined using SITA 24-2 (SITA-SAP) and matrix 24-2 (Matrix-FDT). The correlations of global indices and the number of defects on pattern deviation (PD) plots were determined. Agreement between two sets regarding the stage of visual field damage was assessed. Pearson's correlation, intra-cluster comparison, paired t-test, and 95% limit of agreement were calculated. Although there was no significant difference between global indices, the agreement between the two devices regarding the global indices was weak (the limit of agreement for mean deviation was -6.08 to 6.08 and that for pattern standard deviation was -4.42 to 3.42). The agreement between SITA-SAP and Matrix-FDT regarding the Glaucoma Hemifield Test (GHT) and the number of defective points in each quadrant and staging of the visual field damage was also weak. Because the correlation between SITA-SAP and Matrix-FDT regarding global indices, GHT, number of defective points, and stage of the visual field damage in mild glaucoma is weak, Matrix-FDT cannot be used interchangeably with SITA-SAP in the early stages of glaucoma.

Estudio de factores de riesgo para la hemorragia de la matriz germinal del prematuro Risk factors for germinal matrix hemorrhage in preterm infants

Directory of Open Access Journals (Sweden)

Gladys P. Arango

1997-01-01

Full Text Available Con el propósito de facilitar el diagnóstico clínico de la hemorragia de la matriz germinal del prematuro, se diseñó un estudio de casos (n: 56 y controles (n: 66 para determinar los factores de riesgo de la madre y del niño; también se buscó asociación entre dichos factores y la gravedad del evento. No se halló relación entre los factores de riesgo maternos y la presencia o gravedad de la hemorragia. En cuanto a los niños, la edad gestacional menor de 31 semanas, el uso de ventilación mecánica y la persistencia del ductus arterioso mostraron una relación estadística con el evento (p < 0.05, mientras que la sumatoria de tres o más riesgos la tuvo con la gravedad del mismo (p < 0.05. Se concluye que los mencionados factores de riesgo pueden ser indicativos del desarrollo de la hemorragia de la matriz germinal en el prematuro. To facilitate clinical diagnosis of germinal matrix hemorrhage In preterm infants, a study of cases {n: 56 and controls {n: 66 was carried out. Association was investigated between hemorrhage and maternal and neonatal risk factors; also included was the correlation between such factors and seriousness of the hemorrhagic episode. No correlation was found between maternal risk factors and hemorrhage or its seriousness. Concerning neonatal risks, gestational age under 31 weeks, the use of mechanical ventilation and persistence of ductus arteriosus, independently, showed statistical correlation with the hemorrhage {p < 0.05, whereas the simultaneous presence of three or more risks correlated with intensity of hemorrhage {p < 0.05. We conclude that the abovementioned neonatal risk factors can be suggestive of the development of germinal matrix hemorrhage in preterm Infants.

Comparison of matrix exponential methods for fuel burnup calculations

International Nuclear Information System (INIS)

Oh, Hyung Suk; Yang, Won Sik

1999-01-01

Series expansion methods to compute the exponential of a matrix have been compared by applying them to fuel depletion calculations. Specifically, Taylor, Pade, Chebyshev, and rational Chebyshev approximations have been investigated by approximating the exponentials of bum matrices by truncated series of each method with the scaling and squaring algorithm. The accuracy and efficiency of these methods have been tested by performing various numerical tests using one thermal reactor and two fast reactor depletion problems. The results indicate that all the four series methods are accurate enough to be used for fuel depletion calculations although the rational Chebyshev approximation is relatively less accurate. They also show that the rational approximations are more efficient than the polynomial approximations. Considering the computational accuracy and efficiency, the Pade approximation appears to be better than the other methods. Its accuracy is better than the rational Chebyshev approximation, while being comparable to the polynomial approximations. On the other hand, its efficiency is better than the polynomial approximations and is similar to the rational Chebyshev approximation. In particular, for fast reactor depletion calculations, it is faster than the polynomial approximations by a factor of ∼ 1.7. (author). 11 refs., 4 figs., 2 tabs

A stromal cell-derived factor-1 releasing matrix enhances the progenitor cell response and blood vessel growth in ischaemic skeletal muscle

Directory of Open Access Journals (Sweden)

D Kuraitis

2011-09-01

Full Text Available Although many regenerative cell therapies are being developed to replace or regenerate ischaemic muscle, the lack of vasculature and poor persistence of the therapeutic cells represent major limiting factors to successful tissue restoration. In response to ischaemia, stromal cell-derived factor-1 (SDF-1 is up-regulated by the affected tissue to stimulate stem cell-mediated regenerative responses. Therefore, we encapsulated SDF-1 into alginate microspheres and further incorporated these into an injectable collagen-based matrix in order to improve local delivery. Microsphere-matrix impregnation reduced the time for matrix thermogelation, and also increased the viscosity reached. This double-incorporation prolonged the release of SDF-1, which maintained adhesive and migratory bioactivity, attributed to chemotaxis in response to SDF-1. In vivo, treatment of ischaemic hindlimb muscle with microsphere-matrix led to increased mobilisation of bone marrow-derived progenitor cells, and also improved recruitment of angiogenic cells expressing the SDF-1 receptor (CXCR4 from bone marrow and local tissues. Both matrix and SDF-1-releasing matrix were successful at restoring perfusion, but SDF-1 treatment appeared to play an earlier role, as evidenced by arterioles that are phenotypically older and by increased angiogenic cytokine production, stimulating the generation of a qualitative microenvironment for a rapid and therefore more efficient regeneration. These results support the release of implanted SDF-1 as a promising method for enhancing progenitor cell responses and restoring perfusion to ischaemic tissues via neovascularisation.

A Network and Visual Quality Aware N-Screen Content Recommender System Using Joint Matrix Factorization

Directory of Open Access Journals (Sweden)

Farman Ullah

2014-01-01

Full Text Available We propose a network and visual quality aware N-Screen content recommender system. N-Screen provides more ways than ever before to access multimedia content through multiple devices and heterogeneous access networks. The heterogeneity of devices and access networks present new questions of QoS (quality of service in the realm of user experience with content. We propose, a recommender system that ensures a better visual quality on user’s N-screen devices and the efficient utilization of available access network bandwidth with user preferences. The proposed system estimates the available bandwidth and visual quality on users N-Screen devices and integrates it with users preferences and contents genre information to personalize his N-Screen content. The objective is to recommend content that the user’s N-Screen device and access network are capable of displaying and streaming with the user preferences that have not been supported in existing systems. Furthermore, we suggest a joint matrix factorization approach to jointly factorize the users rating matrix with the users N-Screen device similarity and program genres similarity. Finally, the experimental results show that we also enhance the prediction and recommendation accuracy, sparsity, and cold start issues.

A network and visual quality aware N-screen content recommender system using joint matrix factorization.

Science.gov (United States)

Ullah, Farman; Sarwar, Ghulam; Lee, Sungchang

2014-01-01

We propose a network and visual quality aware N-Screen content recommender system. N-Screen provides more ways than ever before to access multimedia content through multiple devices and heterogeneous access networks. The heterogeneity of devices and access networks present new questions of QoS (quality of service) in the realm of user experience with content. We propose, a recommender system that ensures a better visual quality on user's N-screen devices and the efficient utilization of available access network bandwidth with user preferences. The proposed system estimates the available bandwidth and visual quality on users N-Screen devices and integrates it with users preferences and contents genre information to personalize his N-Screen content. The objective is to recommend content that the user's N-Screen device and access network are capable of displaying and streaming with the user preferences that have not been supported in existing systems. Furthermore, we suggest a joint matrix factorization approach to jointly factorize the users rating matrix with the users N-Screen device similarity and program genres similarity. Finally, the experimental results show that we also enhance the prediction and recommendation accuracy, sparsity, and cold start issues.

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.

A Recursive Formulation of Cholesky Factorization of a Matrix in Packed Storage Format

DEFF Research Database (Denmark)

Andersen, Bjarne Stig; Gustavson, Fred; Wasniewski, Jerzy

2001-01-01

. Algorithm RPC is based on level-3 BLAS and requires variants of algorithms {\\$\\backslash\\$bf TRSM} and {\\$\\backslash\\$bf SYRK} that work on RPF. We call these {\\$\\backslash\\$bf RP\\$\\backslash\\$\\_TRSM} and {\\$\\backslash\\$bf RP\\$\\backslash\\$\\_SYRK} and find that they do most of their work by calling...... matrix. Second, RPC gives a level-3 implementation of Cholesky factorization whereas standard packed implementations are only level 2. Hence, the performance of our RPC implementation is decidedly superior. Third, unlike fixed block size algorithms, RPC requires no block size tuning parameter. We present...

Identifying sources of atmospheric fine particles in Havana City using Positive Matrix Factorization technique

International Nuclear Information System (INIS)

Pinnera, I.; Perez, G.; Ramos, M.; Guibert, R.; Aldape, F.; Flores M, J.; Martinez, M.; Molina, E.; Fernandez, A.

2011-01-01

In previous study a set of samples of fine and coarse airborne particulate matter collected in a urban area of Havana City were analyzed by Particle-Induced X-ray Emission (PIXE) technique. The concentrations of 14 elements (S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br and Pb) were consistently determined in both particle sizes. The analytical database provided by PIXE was statistically analyzed in order to determine the local pollution sources. The Positive Matrix Factorization (PMF) technique was applied to fine particle data in order to identify possible pollution sources. These sources were further verified by enrichment factor (EF) calculation. A general discussion about these results is presented in this work. (Author)

Comparisons of treatment means when factors do not interact in two-factorial studies

KAUST Repository

Wei, Jiawei; Carroll, Raymond J.; Harden, Kathryn K.; Wu, Guoyao

2011-01-01

Scientists in the fields of nutrition and other biological sciences often design factorial studies to test the hypotheses of interest and importance. In the case of two-factorial studies, it is widely recognized that the analysis of factor effects is generally based on treatment means when the interaction of the factors is statistically significant, and involves multiple comparisons of treatment means. However, when the two factors do not interact, a common understanding among biologists is that comparisons among treatment means cannot or should not be made. Here, we bring this misconception into the attention of researchers. Additionally, we indicate what kind of comparisons among the treatment means can be performed when there is a nonsignificant interaction among two factors. Such information should be useful in analyzing the experimental data and drawing meaningful conclusions.

Comparisons of treatment means when factors do not interact in two-factorial studies

KAUST Repository

Wei, Jiawei

2011-05-06

Scientists in the fields of nutrition and other biological sciences often design factorial studies to test the hypotheses of interest and importance. In the case of two-factorial studies, it is widely recognized that the analysis of factor effects is generally based on treatment means when the interaction of the factors is statistically significant, and involves multiple comparisons of treatment means. However, when the two factors do not interact, a common understanding among biologists is that comparisons among treatment means cannot or should not be made. Here, we bring this misconception into the attention of researchers. Additionally, we indicate what kind of comparisons among the treatment means can be performed when there is a nonsignificant interaction among two factors. Such information should be useful in analyzing the experimental data and drawing meaningful conclusions.

Extracellular Matrix and Growth Factors Improve the Efficacy of Intramuscular Islet Transplantation.

Science.gov (United States)

Tsuchiya, Haruyuki; Sakata, Naoaki; Yoshimatsu, Gumpei; Fukase, Masahiko; Aoki, Takeshi; Ishida, Masaharu; Katayose, Yu; Egawa, Shinichi; Unno, Michiaki

2015-01-01

The efficacy of intramuscular islet transplantation is poor despite being technically simple, safe, and associated with reduced rates of severe complications. We evaluated the efficacy of combined treatment with extracellular matrix (ECM) and growth factors in intramuscular islet transplantation. Male BALB/C mice were used for the in vitro and transplantation studies. The following three groups were evaluated: islets without treatment (islets-only group), islets embedded in ECM with growth factors (Matrigel group), and islets embedded in ECM without growth factors [growth factor-reduced (GFR) Matrigel group]. The viability and insulin-releasing function of islets cultured for 96 h were significantly improved in Matrigel and GFR Matrigel groups compared with the islets-only group. Blood glucose and serum insulin levels immediately following transplantation were significantly improved in the Matrigel and GFR Matrigel groups and remained significantly improved in the Matrigel group at postoperative day (POD) 28. On histological examination, significantly decreased numbers of TdT-mediated deoxyuridine triphosphate-biotin nick end labeling-positive islet cells and significantly increased numbers of Ki67-positive cells were observed in the Matrigel and GFR Matrigel groups at POD 3. Peri-islet revascularization was most prominent in the Matrigel group at POD 14. The efficacy of intramuscular islet transplantation was improved by combination treatment with ECM and growth factors through the inhibition of apoptosis, increased proliferation of islet cells, and promotion of revascularization.

Expression of extracellular matrix components and related growth factors in human tendon and muscle after acute exercise

DEFF Research Database (Denmark)

Heinemeier, K M; Bjerrum, S S; Schjerling, P

2013-01-01

Acute kicking exercise induces collagen synthesis in both tendon and muscle in humans, but it is not known if this relates to increased collagen transcription and if other matrix genes are regulated. Young men performed 1 h of one-leg kicking at 67% of max workload. Biopsies were taken from...... the patellar tendon and vastus lateralis muscle of each leg at 2 (n = 10), 6 (n = 11), or 26 h (n = 10) after exercise. Levels of messenger ribonucleic acid mRNA for collagens, noncollagenous matrix proteins, and growth factors were measured with real-time reverse transcription polymerase chain reaction...

Performance evaluation of matrix gradient coils.

Science.gov (United States)

Jia, Feng; Schultz, Gerrit; Testud, Frederik; Welz, Anna Masako; Weber, Hans; Littin, Sebastian; Yu, Huijun; Hennig, Jürgen; Zaitsev, Maxim

2016-02-01

In this paper, we present a new performance measure of a matrix coil (also known as multi-coil) from the perspective of efficient, local, non-linear encoding without explicitly considering target encoding fields. An optimization problem based on a joint optimization for the non-linear encoding fields is formulated. Based on the derived objective function, a figure of merit of a matrix coil is defined, which is a generalization of a previously known resistive figure of merit for traditional gradient coils. A cylindrical matrix coil design with a high number of elements is used to illustrate the proposed performance measure. The results are analyzed to reveal novel features of matrix coil designs, which allowed us to optimize coil parameters, such as number of coil elements. A comparison to a scaled, existing multi-coil is also provided to demonstrate the use of the proposed performance parameter. The assessment of a matrix gradient coil profits from using a single performance parameter that takes the local encoding performance of the coil into account in relation to the dissipated power.

Transforming growth factor-beta stimulates wound healing and modulates extracellular matrix gene expression in pig skin. I. Excisional wound model.

Science.gov (United States)

Quaglino, D; Nanney, L B; Kennedy, R; Davidson, J M

1990-09-01

The effect of transforming growth factor-beta 1 (TGF-beta 1) on matrix gene expression has been investigated during the process of wound repair, where the formation of new connective tissue represents a critical step in restoring tissue integrity. Split-thickness excisional wounds in the pig were studied by in situ hybridization in order to obtain subjective findings on the activity and location of cells involved in matrix gene expression after the administration of recombinant TGF-beta 1. Data focus on the stimulatory role of this growth factor in granulation tissue formation, on the enhanced mRNA content of collagen types I and III, fibronectin, TGF-beta 1 itself, and on the reduction in stromelysin mRNA, suggesting that increased matrix formation measured after treatment with TGF-beta 1 is due to fibroplasia regulated by the abundance of mRNAs for several different structural, matrix proteins as well as inhibition of proteolytic phenomena elicited by metalloproteinases. These studies reveal elastin mRNA early in the repair process, and elastin mRNA expression is enhanced by administration of TGF-beta 1. Moreover, we show that TGF-beta 1 was auto-stimulating in wounds, accounting, at least in part, for the persistent effects of single doses of this multipotential cytokine.

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

Science.gov (United States)

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

2011-01-01

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

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....

Theoretical evaluation of matrix effects on trapped atomic levels

Energy Technology Data Exchange (ETDEWEB)

Das, G.P.; Gruen, D.M.

1986-06-01

We suggest a theoretical model for calculating the matrix perturbation on the spectra of atoms trapped in rare gas systems. The model requires the ''potential curves'' of the diatomic system consisting of the trapped atom interacting with one from the matrix and relies on the approximation that the total matrix perturbation is a scalar sum of the pairwise interactions with each of the lattice sites. Calculations are presented for the prototype systems Na in Ar. Attempts are made to obtain ab initio estimates of the Jahn-Teller effects for excited states. Comparison is made with our recent Matrix-Isolation Spectroscopic (MIS) data. 10 refs., 3 tabs.

Theoretical evaluation of matrix effects on trapped atomic levels

International Nuclear Information System (INIS)

Das, G.P.; Gruen, D.M.

1986-06-01

We suggest a theoretical model for calculating the matrix perturbation on the spectra of atoms trapped in rare gas systems. The model requires the ''potential curves'' of the diatomic system consisting of the trapped atom interacting with one from the matrix and relies on the approximation that the total matrix perturbation is a scalar sum of the pairwise interactions with each of the lattice sites. Calculations are presented for the prototype systems Na in Ar. Attempts are made to obtain ab initio estimates of the Jahn-Teller effects for excited states. Comparison is made with our recent Matrix-Isolation Spectroscopic (MIS) data. 10 refs., 3 tabs

Comparison of four decontamination treatments on porcine renal decellularized extracellular matrix structure, composition, and support of human renal cortical tubular epithelium cells.

Science.gov (United States)

Poornejad, Nafiseh; Nielsen, Jeffery J; Morris, Ryan J; Gassman, Jason R; Reynolds, Paul R; Roeder, Beverly L; Cook, Alonzo D

2016-03-01

Engineering whole organs from porcine decellularized extracellular matrix and human cells may lead to a plentiful source of implantable organs. Decontaminating the porcine decellularized extracellular matrix scaffolds is an essential step prior to introducing human cells. However, decontamination of whole porcine kidneys is a major challenge because the decontamination agent or irradiation needs to diffuse deep into the structure to eliminate all microbial contamination while minimizing damage to the structure and composition of the decellularized extracellular matrix. In this study, we compared four decontamination treatments that could be applicable to whole porcine kidneys: 70% ethanol, 0.2% peracetic acid in 1 M NaCl, 0.2% peracetic acid in 4% ethanol, and gamma (γ)-irradiation. Porcine kidneys were decellularized by perfusion of 0.5% (w/v) aqueous solution of sodium dodecyl sulfate and the four decontamination treatments were optimized using segments (n = 60) of renal tissue to ensure a consistent comparison. Although all four methods were successful in decontamination, γ-irradiation was very damaging to collagen fibers and glycosaminoglycans, leading to less proliferation of human renal cortical tubular epithelium cells within the porcine decellularized extracellular matrix. The effectiveness of the other three optimized solution treatments were then all confirmed using whole decellularized porcine kidneys (n = 3). An aqueous solution of 0.2% peracetic acid in 1 M NaCl was determined to be the best method for decontamination of porcine decellularized extracellular matrix. © The Author(s) 2015.

The impact of episodic nonequilibrium fracture-matrix flow on geological repository performance

International Nuclear Information System (INIS)

Buscheck, T.A.; Nitao, J.J.; Chestnut, D.A.

1991-01-01

Adequate representation of fracture-matrix interaction during episodic infiltration events is crucial in making valid hydrological predictions of repository performance at Yucca Mountain. Various approximations have been applied to represent fracture-matrix flow interaction, including the Equivalent Continuum Model (ECM), which assumes capillary equilibrium between fractures and matrix, and the Fracture-Matrix Model (FMM), which accounts for nonequilibrium fracture-matrix flow. We analyze the relative impact of matrix imbibition on episodic nonequilibrium fracture-matrix flow for the eight major hydrostratigraphic units in the unsaturated zone at Yucca Mountain. Comparisons are made between ECM and FMM predictions to determine the applicability of the ECM. The implications of nonequilibrium fracture-matrix flow on radionuclide transport are also discussed

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...

Extracellular Matrix and Growth Factors Improve the Efficacy of Intramuscular Islet Transplantation.

Directory of Open Access Journals (Sweden)

Haruyuki Tsuchiya

Full Text Available The efficacy of intramuscular islet transplantation is poor despite being technically simple, safe, and associated with reduced rates of severe complications. We evaluated the efficacy of combined treatment with extracellular matrix (ECM and growth factors in intramuscular islet transplantation.Male BALB/C mice were used for the in vitro and transplantation studies. The following three groups were evaluated: islets without treatment (islets-only group, islets embedded in ECM with growth factors (Matrigel group, and islets embedded in ECM without growth factors [growth factor-reduced (GFR Matrigel group]. The viability and insulin-releasing function of islets cultured for 96 h were significantly improved in Matrigel and GFR Matrigel groups compared with the islets-only group.Blood glucose and serum insulin levels immediately following transplantation were significantly improved in the Matrigel and GFR Matrigel groups and remained significantly improved in the Matrigel group at postoperative day (POD 28. On histological examination, significantly decreased numbers of TdT-mediated deoxyuridine triphosphate-biotin nick end labeling-positive islet cells and significantly increased numbers of Ki67-positive cells were observed in the Matrigel and GFR Matrigel groups at POD 3. Peri-islet revascularization was most prominent in the Matrigel group at POD 14.The efficacy of intramuscular islet transplantation was improved by combination treatment with ECM and growth factors through the inhibition of apoptosis, increased proliferation of islet cells, and promotion of revascularization.

Extracellular Matrix-Regulated Gene Expression RequiresCooperation of SWI/SNF and Transcription Factors

Energy Technology Data Exchange (ETDEWEB)

Xu, Ren; Spencer, Virginia A.; Bissell, Mina J.

2006-05-25

Extracellular cues play crucial roles in the transcriptional regulation of tissue-specific genes, but whether and how these signals lead to chromatin remodeling is not understood and subject to debate. Using chromatin immunoprecipitation (ChIP) assays and mammary-specific genes as models, we show here that extracellular matrix (ECM) molecules and prolactin cooperate to induce histone acetylation and binding of transcription factors and the SWI/SNF complex to the {beta}- and ?-casein promoters. Introduction of a dominant negative Brg1, an ATPase subunit of SWI/SNF complex, significantly reduced both {beta}- and ?-casein expression, suggesting that SWI/SNF-dependent chromatin remodeling is required for transcription of mammary-specific genes. ChIP analyses demonstrated that the ATPase activity of SWI/SNF is necessary for recruitment of RNA transcriptional machinery, but not for binding of transcription factors or for histone acetylation. Coimmunoprecipitation analyses showed that the SWI/SNF complex is associated with STAT5, C/EBP{beta}, and glucocorticoid receptor (GR). Thus, ECM- and prolactin-regulated transcription of the mammary-specific casein genes requires the concerted action of chromatin remodeling enzymes and transcription factors.

Rank-Optimized Logistic Matrix Regression toward Improved Matrix Data Classification.

Science.gov (United States)

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

While existing logistic regression suffers from overfitting and often fails in considering structural information, we propose a novel matrix-based logistic regression to overcome the weakness. In the proposed method, 2D matrices are directly used to learn two groups of parameter vectors along each dimension without vectorization, which allows the proposed method to fully exploit the underlying structural information embedded inside the 2D matrices. Further, we add a joint [Formula: see text]-norm on two parameter matrices, which are organized by aligning each group of parameter vectors in columns. This added co-regularization term has two roles-enhancing the effect of regularization and optimizing the rank during the learning process. With our proposed fast iterative solution, we carried out extensive experiments. The results show that in comparison to both the traditional tensor-based methods and the vector-based regression methods, our proposed solution achieves better performance for matrix data classifications.

ACORNS, Covariance and Correlation Matrix Diagonalization

International Nuclear Information System (INIS)

Szondi, E.J.

1990-01-01

1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT

Pro-inflammatory stimulation of meniscus cells increases production of matrix metalloproteinases and additional catabolic factors involved in osteoarthritis pathogenesis

Science.gov (United States)

Stone, Austin V.; Loeser, Richard F.; Vanderman, Kadie S.; Long, David L.; Clark, Stephanie C.; Ferguson, Cristin M.

2014-01-01

Objective Meniscus injury increases the risk of osteoarthritis; however, the biologic mechanism remains unknown. We hypothesized that pro-inflammatory stimulation of meniscus would increase production of matrix-degrading enzymes, cytokines and chemokines which cause joint tissue destruction and could contribute to osteoarthritis development. Design Meniscus and cartilage tissue from healthy tissue donors and total knee arthroplasties was cultured. Primary cell cultures were stimulated with pro-inflammatory factors [IL-1β, IL-6, or fibronectin fragments (FnF)] and cellular responses were analyzed by real-time PCR, protein arrays and immunoblots. To determine if NF-κB was required for MMP production, meniscus cultures were treated with inflammatory factors with and without the NF-κB inhibitor, hypoestoxide. Results Normal and osteoarthritic meniscus cells increased their MMP secretion in response to stimulation, but specific patterns emerged that were unique to each stimulus with the greatest number of MMPs expressed in response to FnF. Meniscus collagen and connective tissue growth factor gene expression was reduced. Expression of cytokines (IL-1α, IL-1β, IL-6), chemokines (IL-8, CXCL1, CXCL2, CSF1) and components of the NF-κB and tumor necrosis factor (TNF) family were significantly increased. Cytokine and chemokine protein production was also increased by stimulation. When primary cell cultures were treated with hypoestoxide in conjunction with pro-inflammatory stimulation, p65 activation was reduced as were MMP-1 and MMP-3 production. Conclusions Pro-inflammatory stimulation of meniscus cells increased matrix metalloproteinase production and catabolic gene expression. The meniscus could have an active biologic role in osteoarthritis development following joint injury through increased production of cytokines, chemokines, and matrix-degrading enzymes. PMID:24315792

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

Science.gov (United States)

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

2017-01-01

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

How to get the Matrix Organization to Work

DEFF Research Database (Denmark)

Burton, Richard M.; Obel, Børge; Håkonsson, Dorthe Døjbak

2015-01-01

a matrix to work, taking a multi-contingency perspective. We translate the matrix concept for designers and managers who are considering a matrix organization and argue that three factors are critical for its success: (1) Strong purpose: Only choose the matrix structure if there are strong reasons...... for doing so, (2) Alignment among contingencies: A matrix can only be successful if key contingencies are aligned with the matrix’s purpose, and (3) Management of junctions: The success of a matrix depends on how well activities at the junctions of the matrix are managed....

Characterization of O-glycosylated precursors of insulin-like growth factor II by matrix-assisted laser desorption/ionization mass spectrometry

NARCIS (Netherlands)

Jespersen, S.; Koedam, J.A.; Hoogerbrugge, C.M.; Tjaden, U.R.; Greef, J. van der; Brande, J.L. van den

1996-01-01

High molecular weight precursors of insulin-like growth factor II (IGF-II) were isolated from Cohn fraction IV of human plasma by ultrafiltration, affinity chromatography and reversed-phase high-performance liquid chromatography. Molecular weight determination by matrix-assisted laser

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.

Correlation Between Placental Matrix Metalloproteinase 9 and Tumor Necrosis Factor-α Protein Expression Throughout Gestation in Normal Human Pregnancy.

Science.gov (United States)

Basu, Jayasri; Agamasu, Enyonam; Bendek, Bolek; Salafia, Carolyn M; Mishra, Aruna; Lopez, Julia Vasquez; Kroes, Jessica; Dragich, Sharon Claire; Thakur, Ashley; Mikhail, Magdy

2018-04-01

Matrix metalloproteinases (MMPs), specifically MMP-9 plays a role in human placentation. The enzyme confers an invasive ability to cytotrophoblasts and degrades the endometrial matrix as the cells infiltrate the decidua to keep up with placental growth. Since tumor necrosis factor-α (TNF-α) can induce the synthesis of MMP-9, we investigated the patterns of changes in and correlation between placental villous MMP-9 and TNF-α expressions throughout normal human gestation. Placentas were obtained from 179 normal pregnant women who underwent elective abortion or term delivery. Chorionic villi isolated from placental samples were grouped as first, second, and third trimester (7 0/7 -13 0/7 , 13 1/7 -23 6/7 , and 37 0/7 -42 4/7 weeks, respectively). Chorionic villous TNF-α and MMP-9 proteins were assayed using enzyme immunoassay kits. There were significant differences in MMP-9 and TNF-α protein expressions among the trimester groups ( P = .001). The MMP-9 protein increased progressively with an increase in gestational age (GA), but TNF-α peaked in the second trimester. Within each trimester group, we searched for the effects of variation of GA in days on the 2 variables. A significant positive correlation between MMP-9 and GA was noted in the first trimester ( r = 0.364, P = .005). No other comparisons were significant. When GA was controlled for, partial correlation revealed a significant positive correlation between TNF-α and MMP-9 only in the second trimester ( r = 0.300, P = .018). We hypothesize that the TNF-α peak and the positive correlation between TNF-α and MMP-9 in the second trimester of normal human gestation could contribute toward a successful pregnancy outcome.

Inductive matrix completion for predicting gene-disease associations.

Science.gov (United States)

Natarajan, Nagarajan; Dhillon, Inderjit S

2014-06-15

Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has bigdata.ices.utexas.edu/project/gene-disease. © The Author 2014. Published by Oxford University Press.

Factors that impact the stability of vitamin C at intermediate temperatures in a food matrix

OpenAIRE

Herbig, Anna-Lena

2017-01-01

The study comprises a systematic and quantitative evaluation of potential intrinsic and extrinsic factors that impact vitamin C degradation in a real food matrix. The supernatant of centrifuged apple purée was fortified in vitamin C, and degradation was followed without stirring. Model discrimination indicated better fit for the zero order model than the first order model which was hence chosen for determination of rate constants. pH influenced strongly vitamin C degradation in citrate-phosph...

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.

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

Some Matrix Iterations for Computing Generalized Inverses and Balancing Chemical Equations

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Farahnaz Soleimani

2015-11-01

Full Text Available An application of iterative methods for computing the Moore–Penrose inverse in balancing chemical equations is considered. With the aim to illustrate proposed algorithms, an improved high order hyper-power matrix iterative method for computing generalized inverses is introduced and applied. The improvements of the hyper-power iterative scheme are based on its proper factorization, as well as on the possibility to accelerate the iterations in the initial phase of the convergence. Although the effectiveness of our approach is confirmed on the basis of the theoretical point of view, some numerical comparisons in balancing chemical equations, as well as on randomly-generated matrices are furnished.

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

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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

Parallel O(log n) algorithms for open- and closed-chain rigid multibody systems based on a new mass matrix factorization technique

Science.gov (United States)

Fijany, Amir

1993-01-01

In this paper, parallel O(log n) algorithms for computation of rigid multibody dynamics are developed. These parallel algorithms are derived by parallelization of new O(n) algorithms for the problem. The underlying feature of these O(n) algorithms is a drastically different strategy for decomposition of interbody force which leads to a new factorization of the mass matrix (M). Specifically, it is shown that a factorization of the inverse of the mass matrix in the form of the Schur Complement is derived as M(exp -1) = C - B(exp *)A(exp -1)B, wherein matrices C, A, and B are block tridiagonal matrices. The new O(n) algorithm is then derived as a recursive implementation of this factorization of M(exp -1). For the closed-chain systems, similar factorizations and O(n) algorithms for computation of Operational Space Mass Matrix lambda and its inverse lambda(exp -1) are also derived. It is shown that these O(n) algorithms are strictly parallel, that is, they are less efficient than other algorithms for serial computation of the problem. But, to our knowledge, they are the only known algorithms that can be parallelized and that lead to both time- and processor-optimal parallel algorithms for the problem, i.e., parallel O(log n) algorithms with O(n) processors. The developed parallel algorithms, in addition to their theoretical significance, are also practical from an implementation point of view due to their simple architectural requirements.

In-depth, high-accuracy proteomics of sea urchin tooth organic matrix

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Mann Matthias

2008-12-01

Full Text Available Abstract Background The organic matrix contained in biominerals plays an important role in regulating mineralization and in determining biomineral properties. However, most components of biomineral matrices remain unknown at present. In sea urchin tooth, which is an important model for developmental biology and biomineralization, only few matrix components have been identified. The recent publication of the Strongylocentrotus purpuratus genome sequence rendered possible not only the identification of genes potentially coding for matrix proteins, but also the direct identification of proteins contained in matrices of skeletal elements by in-depth, high-accuracy proteomic analysis. Results We identified 138 proteins in the matrix of tooth powder. Only 56 of these proteins were previously identified in the matrices of test (shell and spine. Among the novel components was an interesting group of five proteins containing alanine- and proline-rich neutral or basic motifs separated by acidic glycine-rich motifs. In addition, four of the five proteins contained either one or two predicted Kazal protease inhibitor domains. The major components of tooth matrix were however largely identical to the set of spicule matrix proteins and MSP130-related proteins identified in test (shell and spine matrix. Comparison of the matrices of crushed teeth to intact teeth revealed a marked dilution of known intracrystalline matrix proteins and a concomitant increase in some intracellular proteins. Conclusion This report presents the most comprehensive list of sea urchin tooth matrix proteins available at present. The complex mixture of proteins identified may reflect many different aspects of the mineralization process. A comparison between intact tooth matrix, presumably containing odontoblast remnants, and crushed tooth matrix served to differentiate between matrix components and possible contributions of cellular remnants. Because LC-MS/MS-based methods directly

Comparison of hemostatic matrix and standard hemostasis in patients undergoing primary TKA.

Science.gov (United States)

Comadoll, James L; Comadoll, Shea; Hutchcraft, Audrey; Krishnan, Sangeeta; Farrell, Kelly; Kreuwel, Huub T C; Bechter, Mark

2012-06-01

Bleeding after total knee arthroplasty increases the risk of pain, delayed rehabilitation, blood transfusion, and transfusion-associated complications. The authors compared pre- and postoperative decreases in hemoglobin as a surrogate for blood loss in consecutive patients treated at a single institution by the same surgeon (J.L.C.) using conventional hemostatic methods (electrocautery, suturing, or manual compression) or a gelatin and thrombin-based hemostatic matrix during total knee arthroplasty. Data were collected retrospectively by chart review. The population comprised 165 controls and 184 patients treated with hemostatic matrix. Median age was 66 years (range, 28-89 years); 66% were women. The arithmetic mean ± SD for the maximal postoperative decrease in hemoglobin was 3.18 ± 0.94 g/dL for controls and 2.19 ± 0.83 g/dL for the hemostatic matrix group. Least squares means estimates of the group difference (controls-hemostatic matrix) in the maximal decrease in hemoglobin was 0.96 g/dL (95% confidence interval, 0.77-1.14 mg/dL; Pmatrix, 84%). In both groups, overall mean tourniquet time was approximately 1 hour, and the most common length of stay was 3 to 5 days. No serious complications related to the hemostatic agent were observed. These data demonstrate that the use of a flowable hemostatic matrix results in less reduction in hemoglobin than the use of conventional hemostatic methods in patient undergoing total knee arthroplasty. Copyright 2012, SLACK Incorporated.

Source contributions to PM10 and arsenic concentrations in Central Chile using positive matrix factorization

Science.gov (United States)

Hedberg, Emma; Gidhagen, Lars; Johansson, Christer

Sampling of particles (PM10) was conducted during a one-year period at two rural sites in Central Chile, Quillota and Linares. The samples were analyzed for elemental composition. The data sets have undergone source-receptor analyses in order to estimate the sources and their abundance's in the PM10 size fraction, by using the factor analytical method positive matrix factorization (PMF). The analysis showed that PM10 was dominated by soil resuspension at both sites during the summer months, while during winter traffic dominated the particle mass at Quillota and local wood burning dominated the particle mass at Linares. Two copper smelters impacted the Quillota station, and contributed to 10% and 16% of PM10 as an average during summer and winter, respectively. One smelter impacted Linares by 8% and 19% of PM10 in the summer and winter, respectively. For arsenic the two smelters accounted for 87% of the monitored arsenic levels at Quillota and at Linares one smelter contributed with 72% of the measured mass. In comparison with PMF, the use of a dispersion model tended to overestimate the smelter contribution to arsenic levels at both sites. The robustness of the PMF model was tested by using randomly reduced data sets, where 85%, 70%, 50% and 33% of the samples were included. In this way the ability of the model to reconstruct the sources initially found by the original data set could be tested. On average for all sources the relative standard deviation increased from 7% to 25% for the variables identifying the sources, when decreasing the data set from 85% to 33% of the samples, indicating that the solution initially found was very stable to begin with. But it was also noted that sources due to industrial or combustion processes were more sensitive for the size of the data set, compared to the natural sources as local soil and sea spray sources.

TRENDS OF THE FACTORING TURNOVER IN INTERNATIONAL COMPARISONS

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Éva DARABOS

2017-05-01

Full Text Available The factoring scheme was developed by the competition between the market operators and the need for the most favourable conditions of sale. The seller is constrained to provide loans on a broad scale therefore the seller may have liquidity problems. In cases of this kind, the seller can apply to a factoring company in order to access sources, instead of a bank loan. The factoring service has a price. Decision of the financial managers can largely contribute to choosing the appropriate funding form to retain the continuous liquidity situation of an enterprise. Aim of the article is to present the main tendencies of the factoring turnover in international comparisons, highlighting the characteristics of the financial service by its direction, sectorial distribution and customer size in Hungary. It has been estimated that the factoring financing approaches 10% of the short-term loan stocks of SMEs required from banks which indicates that the factoring is now far beyond the marginal financial service but it is an essential element of the short-term financing toolkit.

Matrix diffusion studies by electrical conductivity methods. Comparison between laboratory and in-situ measurements

International Nuclear Information System (INIS)

Ohlsson, Y.; Neretnieks, I.

1998-01-01

Traditional laboratory diffusion experiments in rock material are time consuming, and quite small samples are generally used. Electrical conductivity measurements, on the other hand, provide a fast means for examining transport properties in rock and allow measurements on larger samples as well. Laboratory measurements using electrical conductivity give results that compare well to those from traditional diffusion experiments. The measurement of the electrical resistivity in the rock surrounding a borehole is a standard method for the detection of water conducting fractures. If these data could be correlated to matrix diffusion properties, in-situ diffusion data from large areas could be obtained. This would be valuable because it would make it possible to obtain data very early in future investigations of potentially suitable sites for a repository. This study compares laboratory electrical conductivity measurements with in-situ resistivity measurements from a borehole at Aespoe. The laboratory samples consist mainly of Aespoe diorite and fine-grained granite and the rock surrounding the borehole of Aespoe diorite, Smaaland granite and fine-grained granite. The comparison shows good agreement between laboratory measurements and in-situ data

Evaluation of the validity of job exposure matrix for psychosocial factors at work.

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Svetlana Solovieva

Full Text Available To study the performance of a developed job exposure matrix (JEM for the assessment of psychosocial factors at work in terms of accuracy, possible misclassification bias and predictive ability to detect known associations with depression and low back pain (LBP.We utilized two large population surveys (the Health 2000 Study and the Finnish Work and Health Surveys, one to construct the JEM and another to test matrix performance. In the first study, information on job demands, job control, monotonous work and social support at work was collected via face-to-face interviews. Job strain was operationalized based on job demands and job control using quadrant approach. In the second study, the sensitivity and specificity were estimated applying a Bayesian approach. The magnitude of misclassification error was examined by calculating the biased odds ratios as a function of the sensitivity and specificity of the JEM and fixed true prevalence and odds ratios. Finally, we adjusted for misclassification error the observed associations between JEM measures and selected health outcomes.The matrix showed a good accuracy for job control and job strain, while its performance for other exposures was relatively low. Without correction for exposure misclassification, the JEM was able to detect the association between job strain and depression in men and between monotonous work and LBP in both genders.Our results suggest that JEM more accurately identifies occupations with low control and high strain than those with high demands or low social support. Overall, the present JEM is a useful source of job-level psychosocial exposures in epidemiological studies lacking individual-level exposure information. Furthermore, we showed the applicability of a Bayesian approach in the evaluation of the performance of the JEM in a situation where, in practice, no gold standard of exposure assessment exists.

Evaluation of the validity of job exposure matrix for psychosocial factors at work.

Science.gov (United States)

Solovieva, Svetlana; Pensola, Tiina; Kausto, Johanna; Shiri, Rahman; Heliövaara, Markku; Burdorf, Alex; Husgafvel-Pursiainen, Kirsti; Viikari-Juntura, Eira

2014-01-01

To study the performance of a developed job exposure matrix (JEM) for the assessment of psychosocial factors at work in terms of accuracy, possible misclassification bias and predictive ability to detect known associations with depression and low back pain (LBP). We utilized two large population surveys (the Health 2000 Study and the Finnish Work and Health Surveys), one to construct the JEM and another to test matrix performance. In the first study, information on job demands, job control, monotonous work and social support at work was collected via face-to-face interviews. Job strain was operationalized based on job demands and job control using quadrant approach. In the second study, the sensitivity and specificity were estimated applying a Bayesian approach. The magnitude of misclassification error was examined by calculating the biased odds ratios as a function of the sensitivity and specificity of the JEM and fixed true prevalence and odds ratios. Finally, we adjusted for misclassification error the observed associations between JEM measures and selected health outcomes. The matrix showed a good accuracy for job control and job strain, while its performance for other exposures was relatively low. Without correction for exposure misclassification, the JEM was able to detect the association between job strain and depression in men and between monotonous work and LBP in both genders. Our results suggest that JEM more accurately identifies occupations with low control and high strain than those with high demands or low social support. Overall, the present JEM is a useful source of job-level psychosocial exposures in epidemiological studies lacking individual-level exposure information. Furthermore, we showed the applicability of a Bayesian approach in the evaluation of the performance of the JEM in a situation where, in practice, no gold standard of exposure assessment exists.

Comparison of Conjugate Gradient Density Matrix Search and Chebyshev Expansion Methods for Avoiding Diagonalization in Large-Scale Electronic Structure Calculations

Science.gov (United States)

Bates, Kevin R.; Daniels, Andrew D.; Scuseria, Gustavo E.

1998-01-01

We report a comparison of two linear-scaling methods which avoid the diagonalization bottleneck of traditional electronic structure algorithms. The Chebyshev expansion method (CEM) is implemented for carbon tight-binding calculations of large systems and its memory and timing requirements compared to those of our previously implemented conjugate gradient density matrix search (CG-DMS). Benchmark calculations are carried out on icosahedral fullerenes from C60 to C8640 and the linear scaling memory and CPU requirements of the CEM demonstrated. We show that the CPU requisites of the CEM and CG-DMS are similar for calculations with comparable accuracy.

Renormalon ambiguities in NRQCD operator matrix elements

International Nuclear Information System (INIS)

Bodwin, G.T.; Chen, Y.

1999-01-01

We analyze the renormalon ambiguities that appear in factorization formulas in QCD. Our analysis contains a simple argument that the ambiguities in the short-distance coefficients and operator matrix elements are artifacts of dimensional-regularization factorization schemes and are absent in cutoff schemes. We also present a method for computing the renormalon ambiguities in operator matrix elements and apply it to a computation of the ambiguities in the matrix elements that appear in the NRQCD factorization formulas for the annihilation decays of S-wave quarkonia. Our results, combined with those of Braaten and Chen for the short-distance coefficients, provide an explicit demonstration that the ambiguities cancel in the physical decay rates. In addition, we analyze the renormalon ambiguities in the Gremm-Kapustin relation and in various definitions of the heavy-quark mass. copyright 1999 The American Physical Society

Phosphorylated hepatocyte growth factor receptor/c-Met is associated with tumor growth and prognosis in patients with bladder cancer: correlation with matrix metalloproteinase-2 and -7 and E-cadherin.

Science.gov (United States)

Miyata, Yasuyoshi; Sagara, Yuji; Kanda, Shigeru; Hayashi, Tomayoshi; Kanetake, Hiroshi

2009-04-01

Hepatocyte growth factor receptor/c-Met is associated with malignant aggressiveness and survival in various cancers including bladder cancer. Although phosphorylation of hepatocyte growth factor receptor/c-Met is essential for its function, the pathologic significance of phosphorylated hepatocyte growth factor receptor/c-Met in bladder cancer remains elusive. We investigated the clinical significance of its expression, and its correlation with cancer cell progression-related molecules. The expression levels of 2 tyrosine residues of hepatocyte growth factor receptor/c-Met (pY1234/1235 and pY1349) were examined immunohistochemically in 133 specimens with nonmetastatic bladder cancer. We also investigated their correlation with matrix metalloproteinase-1, -2, -7, and -14; urokinase-type plasminogen activator; E-cadherin; CD44 standard, variant 3, and variant 6; and vascular endothelial growth factor. Expression of phosphorylated hepatocyte growth factor receptor/c-Met was detected in cancer cells, but was rare in normal urothelial cells. Although hepatocyte growth factor receptor/c-Met, pY1234/1235 hepatocyte growth factor receptor/c-Met, and pY1349 hepatocyte growth factor receptor/c-Met were associated with pT stage, multivariate analysis identified pY1349 hepatocyte growth factor receptor/c-met expression only as a significant factor for high pT stage. Expression of pY1349 hepatocyte growth factor receptor/c-Met was a marker of metastasis and (P = .001) and cause-specific survival (P = .003). Expressions of matrix metalloproteinase-2, matrix metalloproteinase-7, and E-cadherin correlated with pY1349 hepatocyte growth factor receptor/c-Met expression. Our results demonstrated that pY1349 hepatocyte growth factor receptor/c-Met plays an important role in tumor development, and its expression is a significant predictor of metastasis and survival of patients with bladder cancer. The results suggest that these activities are mediated, at least in part, by matrix

Plasmonic resonance of colloidal silver in nanoporous matrix

International Nuclear Information System (INIS)

Andreeva, O V; Saitov, S V; Andreeva, N V; Sidorov, A I

2014-01-01

The object of the study in this paper – silver nanoporous silicate matrix with pore size less than 20 nm. Colloidal silver particles with volume concentration about 10 −4 are formed within free volume of pores of silicate matrix by chemical method. Changes in the attenuation spectra of the investigated object during changing of the refractive index of free volume of pores from 1.0 to 1.5 are reviewed. Comparison of the obtained experimental data with the results of calculations was carried out

Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints

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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.

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.

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.

Development of Positive Matrix Factorization Model (PMF) to Annual Study of the PM2.5 Organic Composition in ChapinerIa

International Nuclear Information System (INIS)

Pindado, O.; Perez, R. M.; Garcia, S.

2013-01-01

The Positive Matrix Factorization (PMF) application to a set of PM2.5 data collected in a rural area of Madrid for a period of 1 year has been developed. Results has let describing the particulate faction of atmospheric aerosol collected in Chapineria according to 7 factor, among them fossil fuel combustion by traffic, wax plants, primary emissions of organic carbon, crustal material, and secondary organic aerosol. Five of these factors are related to primary particles; meanwhile only one factor has been associated to secondary particles. Finally, a factor has not been associated to any known source of particulate matter. (Author)

Investigation of plasma-related matrix effects in inductively coupled plasma-atomic emission spectrometry caused by matrices with low second ionization potentials-identification of the secondary factor

International Nuclear Information System (INIS)

Chan, George C.-Y.; Hieftje, Gary M.

2006-01-01

Plasma-related matrix effects induced by a comprehensive list of matrix elements (a total of fifty-one matrices) in inductively coupled plasma-atomic emission spectrometry were investigated and used to confirm that matrix effects caused by elements with a low second ionization potential are more severe than those from matrix elements having a low first ionization potential. Although the matrix effect is correlated unambiguously with the second ionization potential of a matrix, the correlation is not monotonic, which suggests that at least one other factor is operative. Through study of a large pool of matrix elements, it becomes possible to identify another critical parameter that defines the magnitude of the matrix effect; namely the presence of low-lying energy levels in the doubly charged matrix ion. Penning ionization by Ar excited states is proposed as the dominant mechanism for both analyte ionization/excitation and matrix effects; matrices with a low second ionization potential can effectively quench the population of Ar excited states through successive Penning ionization followed by ion-electron recombination and lead to more severe matrix effects

Response Matrix Method Development Program at Savannah River Laboratory

International Nuclear Information System (INIS)

Sicilian, J.M.

1976-01-01

The Response Matrix Method Development Program at Savannah River Laboratory (SRL) has concentrated on the development of an effective system of computer codes for the analysis of Savannah River Plant (SRP) reactors. The most significant contribution of this program to date has been the verification of the accuracy of diffusion theory codes as used for routine analysis of SRP reactor operation. This paper documents the two steps carried out in achieving this verification: confirmation of the accuracy of the response matrix technique through comparison with experiment and Monte Carlo calculations; and establishment of agreement between diffusion theory and response matrix codes in situations which realistically approximate actual operating conditions

Effect Of Neutron Activation Factor On The Physico-Chemical Properties Of Hydrophilic And Hydrophobic Polymer Formulation Of Matrix Tablets

International Nuclear Information System (INIS)

Ibrahim Ijang; Bohari Yaacob; Nordiana, N.R.

2011-01-01

This study was to investigate effect of neutron activation on the physicochemical properties and in vitro dissolution of sustained-release matrix tablets. The tablets incorporation of Samarium oxide (Sm 2 O 3 ) and were compared before and after irradiation with thermal neutron for 5 minutes at 1.2 x 10 12 neutron cm -2 s -1 . The neutron activation factor did not influence the compression properties of the tablets. The dissolution tests showed that irradiation increased the release of the model drug ketoprofen from the tablets. This effect might be explained by polymer degradation. Incorporation of Sm 2 O 3 in the matrix tablets did not influence the release. (author)

Molecular interactions between chondroitin-dermatan sulfate and growth factors/receptors/matrix proteins.

Science.gov (United States)

Mizumoto, Shuji; Yamada, Shuhei; Sugahara, Kazuyuki

2015-10-01

Recent functional studies on chondroitin sulfate-dermatan sulfate (CS-DS) demonstrated its indispensable roles in various biological events including brain development and cancer. CS-DS proteoglycans exert their physiological activity through interactions with specific proteins including growth factors, cell surface receptors, and matrix proteins. The characterization of these interactions is essential for regulating the biological functions of CS-DS proteoglycans. Although amino acid sequences on the bioactive proteins required for these interactions have already been elucidated, the specific saccharide sequences involved in the binding of CS-DS to target proteins have not yet been sufficiently identified. In this review, recent findings are described on the interaction between CS-DS and some proteins which are especially involved in the central nervous system and cancer development/metastasis. Copyright © 2015. Published by Elsevier Ltd.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

Science.gov (United States)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

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.

Different matrix micro-environments in colon cancer and diverticular disease.

Science.gov (United States)

Klinge, U; Rosch, R; Junge, K; Krones, C J; Stumpf, M; Lynen-Jansen, P; Mertens, P R; Schumpelick, V

2007-05-01

The extracellular matrix and the interactive signalling between its components are thought to play a pivotal role for tumour development and metastasis formation. An altered matrix composition as potential underlying pathology for the development of colorectal cancer was hypothesized. In a retrospective study of patients with colon cancer, the extracellular matrix in tumour-free bowel specimen was investigated in comparison with non-infected bowel specimen from patients operated on for colonic diverticulosis. The following matrix parameters with known associations to tumour formation, cell proliferation, invasion and metastasis were analysed by immunohistochemistry and quantified by a scoring system: VEGF, TGF-beta, ESDN, CD117, c-erb-2, cyclin D1, p53, p27, COX-2, YB-1, collagen I/III, MMP-13, PAI and uPAR. Expression profiles and correlations were calculated. The comparison of the two groups revealed a significantly decreased immunostaining for CD117 and TGF-beta in the cancer group (8.5+/-2.6 vs 10.3+/-2,1 and 4.9+/-1.5 vs 8.1+/-3, respectively), whereas PAI scores were significantly higher than in patients with diverticular disease (8.1+/-1.6 vs 6.2+/-0.9). Overall correlation patterns of matrix parameters indicated pronounced differences between tumour-free tissue in cancer patients compared with patients with diverticular disease. Our results indicate distinct differences in the colonic tissue architecture between cancer patients and patients with diverticulitis that support the notion of an altered matrix composition predisposing to the development of colon cancer.

Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization.

Science.gov (United States)

Ezzat, Ali; Zhao, Peilin; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-01-01

Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.

Identification and comparison of structural factors of innovation capability in ESCO with desirable status

Directory of Open Access Journals (Sweden)

Fatemeh Jalali

2014-12-01

Full Text Available The present study describes the identification and comparison of structural factors of innovation capability in Esfahan Steel Company (ESCO. Innovation is a crucial factor in growth, success, and survival of organizations. Since the innovation for organizations is not possible without the level of innovation capabilities and the need for steel products and imports of goods from developed countries has greatly increased, this study intends to investigate the factors affecting the subject that may be able to increase the production and reduce the need to import it. Evaluation of the innovation capability factors of ESCO compared with its desired status in industry can help companies develop innovative strategies and also achieve organizational goals. Statistical analysis methods and mean comparison test by examining the structure of the innovation capability in the form of a standard questionnaire was employed. The findings suggest that the innovation capability in the existing situation of ESCO in comparison with the desired situation is significantly different.

Factors that impact the stability of vitamin C at intermediate temperatures in a food matrix.

Science.gov (United States)

Herbig, Anna-Lena; Renard, Catherine M G C

2017-04-01

The study comprises a systematic and quantitative evaluation of potential intrinsic and extrinsic factors that impact vitamin C degradation in a real food matrix. The supernatant of centrifuged apple purée was fortified in vitamin C, and degradation was followed without stirring. Model discrimination indicated better fit for the zero order model than the first order model which was hence chosen for determination of rate constants. pH influenced strongly vitamin C degradation in citrate-phosphate buffer but not in the apple purée serum. To get an idea of the impact of the food matrix, stability in apple purée serum was compared with that in carrot purée. In the latter, stability was slightly higher. Vitamin C degradation rates were not influenced by its initial concentration. The temperature effect was only marked in the temperature range 40-60°C. In the range 60-80°C, filling height of tubes had the greatest impact. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Analysis of Nonlinear Dynamics by Square Matrix Method

Energy Technology Data Exchange (ETDEWEB)

Yu, Li Hua [Brookhaven National Lab. (BNL), Upton, NY (United States). Energy and Photon Sciences Directorate. National Synchrotron Light Source II

2016-07-25

The nonlinear dynamics of a system with periodic structure can be analyzed using a square matrix. In this paper, we show that because the special property of the square matrix constructed for nonlinear dynamics, we can reduce the dimension of the matrix from the original large number for high order calculation to low dimension in the first step of the analysis. Then a stable Jordan decomposition is obtained with much lower dimension. The transformation to Jordan form provides an excellent action-angle approximation to the solution of the nonlinear dynamics, in good agreement with trajectories and tune obtained from tracking. And more importantly, the deviation from constancy of the new action-angle variable provides a measure of the stability of the phase space trajectories and their tunes. Thus the square matrix provides a novel method to optimize the nonlinear dynamic system. The method is illustrated by many examples of comparison between theory and numerical simulation. Finally, in particular, we show that the square matrix method can be used for optimization to reduce the nonlinearity of a system.

ABCD Matrix Method a Case Study

CERN Document Server

Seidov, Zakir F; Yahalom, Asher

2004-01-01

In the Israeli Electrostatic Accelerator FEL, the distance between the accelerator's end and the wiggler's entrance is about 2.1 m, and 1.4 MeV electron beam is transported through this space using four similar quadrupoles (FODO-channel). The transfer matrix method (ABCD matrix method) was used for simulating the beam transport, a set of programs is written in the several programming languages (MATHEMATICA, MATLAB, MATCAD, MAPLE) and reasonable agreement is demonstrated between experimental results and simulations. Comparison of ABCD matrix method with the direct "numerical experiments" using EGUN, ELOP, and GPT programs with and without taking into account the space-charge effects showed the agreement to be good enough as well. Also the inverse problem of finding emittance of the electron beam at the S1 screen position (before FODO-channel), by using the spot image at S2 screen position (after FODO-channel) as function of quad currents, is considered. Spot and beam at both screens are described as tilted eel...

Absence of particle production and factorization of the s-matrix in 1 + 1 dimensional models

International Nuclear Information System (INIS)

Parke, S.

1980-01-01

In massive, 1 + 1 dimensional, local, quantum field theories the existence of two conserved charges is shown to be a sufficient condition for the absence of particle production and factorization of the s-matrix. These charges must commute and be integrals of local current densities. Their transformation properties under the Lorentz group must be different and also different from the transformation properties under the Lorentz group must be different and also different from the transformation properties pf a vector or a scalar. Also, they must not annihilate any single-particle momentum eigenstate. (orig.)

Combining kernel matrix optimization and regularization to improve particle size distribution retrieval

Science.gov (United States)

Ma, Qian; Xia, Houping; Xu, Qiang; Zhao, Lei

2018-05-01

A new method combining Tikhonov regularization and kernel matrix optimization by multi-wavelength incidence is proposed for retrieving particle size distribution (PSD) in an independent model with improved accuracy and stability. In comparison to individual regularization or multi-wavelength least squares, the proposed method exhibited better anti-noise capability, higher accuracy and stability. While standard regularization typically makes use of the unit matrix, it is not universal for different PSDs, particularly for Junge distributions. Thus, a suitable regularization matrix was chosen by numerical simulation, with the second-order differential matrix found to be appropriate for most PSD types.

One-nucleon removal reactions as a test of overlap functions from the one-body density matrix calculations

International Nuclear Information System (INIS)

Dimitrova, S.S.; Gaidarov, M.K.; Antonov, A.N.; Stoitsov, M.V.; Hodgson, P.E; Lukyanov, V.K.; Zemlyanaya, E.V.; Krumova, G.Z.

1997-01-01

Overlap functions and spectroscopic factors extracted from a model one-body density matrix (OBDM) accounting for short-range nucleon-nucleon correlations are used to calculate differential cross sections of (p, d) reactions and the momentum distributions of transitions to single-particle states in 16 O and 40 Ca. A comparison between the experimental (p, d) and (e, e'p) data, their DWBA and CDWIA analyses and the OBDM calculations is made. Our theoretical predictions for the spectroscopic factors are compared with the empirically extracted ones. It is shown that the overlap functions obtained within the Jastrow correlation method are applicable to the description of the quantities considered. (author)

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.

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.

Reappraisal of quantitative gel zymography for matrix metalloproteinases.

Science.gov (United States)

Prescimone, Tommaso; Tognotti, Danika; Caselli, Chiara; Cabiati, Manuela; D'Amico, Andrea; Del Ry, Silvia; Giannessi, Daniela

2014-09-01

The determination of matrix metalloproteases (MMPs) is relevant in many pathophysiological conditions, especially if associated with extracellular matrix remodeling; however, the results obtained are closely linked to the method used and are not directly comparable. The aim of this study was to perform a reappraisal of quantitative gel zymography technique for MMPs in human plasma, to use for comparison with commercially available ELISA and in those experimental conditions where the MMP active form needs to be revealed. The critical methodological parameters of zymography were checked and a comparison with a routinely used ELISA was performed. Sensitivity and reproducibility levels of zymography are suitable for detection of MMP-9 in human plasma, providing results closely related to those obtained by ELISA. Analytical parameters of zymography were suitable for detection of MMPs in human plasma. Quantitative zymography for MMPs is an alternative method for comparing the results of ELISA widely employed for MMP determination, thus reducing the discrepancies between laboratories regarding gelatinase assay. © 2014 Wiley Periodicals, Inc.

Does the performance of wet granulation and tablet hardness affect the drug dissolution profile of carvedilol in matrix tablets?

Science.gov (United States)

Košir, Darjan; Ojsteršek, Tadej; Vrečer, Franc

2018-06-14

Wet granulation is mostly used process for manufacturing matrix tablets. Compared to the direct compression method, it allows for a better flow and compressibility properties of compression mixtures. Granulation, including process parameters and tableting, can influence critical quality attributes (CQAs) of hydrophilic matrix tablets. One of the most important CQAs is the drug release profile. We studied the influence of granulation process parameters (type of nozzle and water quantity used as granulation liquid) and tablet hardness on the drug release profile. Matrix tablets contained HPMC K4M hydrophilic matrix former and carvedilol as a model drug. The influence of selected HPMC characteristics on the drug release profile was also evaluated using two additional HPMC batches. For statistical evaluation, partial least square (PLS) models were generated for each time point of the drug release profile using the same number of latent factors. In this way, it was possible to evaluate how the importance of factors influencing drug dissolution changes in dependence on time throughout the drug release profile. The results of statistical evaluation show that the granulation process parameters (granulation liquid quantity and type of nozzle) and tablet hardness significantly influence the release profile. On the other hand, the influence of HPMC characteristics is negligible in comparison to the other factors studied. Using a higher granulation liquid quantity and the standard nozzle type results in larger granules with a higher density and lower porosity, which leads to a slower drug release profile. Lower tablet hardness also slows down the release profile.

Development of Normalization Factors for Canada and the United States and Comparison with European Factors

DEFF Research Database (Denmark)

Lautier, Anne; Rosenbaum, Ralph K.; Margni, Manuele

2010-01-01

In Life Cycle Assessment (LCA), normalization calculates the magnitude of an impact (midpoint or endpoint) relative to the total effect of a given reference. The goal of this work is to calculate normalization factors for Canada and the US and to compare them with existing European normalization...... factors. The differences between geographical areas were highlighted by identifying and comparing the main contributors to a given impact category in Canada, the US and Europe. This comparison verified that the main contributors in Europe and in the US are also present in the Canadian inventory. It also...

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

Science.gov (United States)

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

2014-10-01

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

Spatially dependent burnup implementation into the nodal program based on the finite element response matrix method

International Nuclear Information System (INIS)

Yoriyaz, H.

1986-01-01

In this work a spatial burnup scheme and feedback effects has been implemented into the FERM ( 'Finite Element Response Matrix' )program. The spatially dependent neutronic parameters have been considered in three levels: zonewise calculation, assembly wise calculation and pointwise calculation. Flux and power distributions and the multiplication factor were calculated and compared with the results obtained by CITATIOn program. These comparisons showed that processing time in the Ferm code has been hundred of times shorter and no significant difference has been observed in the assembly average power distribution. (Author) [pt

Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics

NARCIS (Netherlands)

Strickert, M.; Schneider, P.; Keilwagen, J.; Villmann, T.; Biehl, M.; Hammer, B.

2008-01-01

Supervised attribute relevance detection using cross-comparisons (SARDUX), a recently proposed method for data-driven metric learning, is extended from dimension-weighted Minkowski distances to metrics induced by a data transformation matrix Ω for modeling mutual attribute dependence. Given class

Role of matrix metalloproteinases in recurrent corneal melting

Czech Academy of Sciences Publication Activity Database

Brejchová, K.; Lisková, P.; Čejková, Jitka; Jirsová, K.

2010-01-01

Roč. 90, č. 5 (2010), s. 583-590 ISSN 0014-4835 Institutional research plan: CEZ:AV0Z50390512 Keywords : corneal melting * extracellular matrix degradation * matrix metalloproteinases Subject RIV: FF - HEENT, Dentistry Impact factor: 2.817, year: 2010

Positive matrix factorization as source apportionment of soil lead and cadmium around a battery plant (Changxing County, China).

Science.gov (United States)

Xue, Jian-long; Zhi, Yu-you; Yang, Li-ping; Shi, Jia-chun; Zeng, Ling-zao; Wu, Lao-sheng

2014-06-01

Chemical compositions of soil samples are multivariate in nature and provide datasets suitable for the application of multivariate factor analytical techniques. One of the analytical techniques, the positive matrix factorization (PMF), uses a weighted least square by fitting the data matrix to determine the weights of the sources based on the error estimates of each data point. In this research, PMF was employed to apportion the sources of heavy metals in 104 soil samples taken within a 1-km radius of a lead battery plant contaminated site in Changxing County, Zhejiang Province, China. The site is heavily contaminated with high concentrations of lead (Pb) and cadmium (Cd). PMF successfully partitioned the variances into sources related to soil background, agronomic practices, and the lead battery plants combined with a geostatistical approach. It was estimated that the lead battery plants and the agronomic practices contributed 55.37 and 29.28%, respectively, for soil Pb of the total source. Soil Cd mainly came from the lead battery plants (65.92%), followed by the agronomic practices (21.65%), and soil parent materials (12.43%). This research indicates that PMF combined with geostatistics is a useful tool for source identification and apportionment.

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.)

Tumor Necrosis Factors, Interferons and Matrix Metalloproteinase-9 in Sera of Non-Hodgkin's Lymphoma Patients

International Nuclear Information System (INIS)

Abdel Malak, C.A.; Karawya, E.M.; Hammouda, G.A.; Zakhary, N.I.

2003-01-01

In the present study, the serum levels of some cytokines and the matrix metalloproteinase-9 (MMP-9) were studied in an attempt to find suitable markers for early diagnosis of non- Hodgkin's lymphoma (NHL) and to assess their role in differentiating between disseminated and non disseminated cases. The present study was conducted on 60 patients with non disseminated NHL, 14 patients with disseminated NHL, in addition to 10 healthy controls. Their sera were used to determine tumor necrosis factor-α (TNF--α), tumor necrosis factor--β (TNF-β), interferon---α), (IFN--α), interferon-γ (IFN--γ) and Matrix Metalloproteinase-9 (MMP-9) using the ELISA technique. The results showed that the serum level of TNF---α), and IFN---α), can be used to differentiate between the control group and the group of NHL patients. However, they could not differentiate between non disseminated NHL (nd- NHL) and disseminated NHL (d- NHL). On the other hand, the serum level of TNF-β) can be used to differentiate between nd- NHL and d- NHL, but not between the control group and nd-NHL. Each of [FN--γ and MMP-9 were not useful in discrimination between the control group and the diseased ones. Our data revealed no correlation between serum level of the parameters investigated and the gender of the patients. The present results revealed that TNF-α) and INF-α), can be used as diagnostic tools for NHL. On the other hand, TNF-β) is useful in the differentiation between nd-NHL and d-NHL

Assessment of nuclear power scenarios allowing for matrix behavior in radiological impact modeling of disposal scenarios

International Nuclear Information System (INIS)

Tronche, E.; Boussier, H.

2000-01-01

Under the provisions of the 1991 French radioactive waste management law, various fuel cycle scenarios will be assessed and compared in terms of feasibility, flexibility, cost, and ultimate waste radio-toxic inventory. The latter criterion may be further broken down into 'potential radio-toxic inventory' (the radio-toxic inventory of all the radionuclides produced) and 'residual radio-toxic inventory' (the radionuclide fraction reaching the biosphere after migration from the repository). The innovative scientific contribution of this study is to consider a third type of radio-toxic inventory: the potential radio-toxic inventory after conditioning, i.e. taking into account the containment capacity of the radionuclide conditioning matrices. The matrix fraction subjected to alteration over time determines the potential for radionuclide release, hence the notion of the potential radio-toxic inventory after conditioning. An initial comparison of possible scenarios is proposed by considering orders of magnitude for the radionuclide containment capacity of the disposal matrices and for their mobilization potential. All the scenarios investigated are normalized to the same annual electric power production so that a legitimate comparison can be established for the ultimate wasteform produced per year of operation. This approach reveals significant differences among the scenarios considered that do not appear when only the raw potential radio-toxic inventory is taken into account. The matrix containment performance has a decisive effect on the final impact of a given scenario or type of scenario. Pu recycling scenarios thus reduce the potential radio-toxicity by roughly a factor of 50 compared with an open cycle; the gain rises to a factor of about 300 for scenarios in which Pu and the minor actinides are recycled. Interestingly, the results obtained by the use of a dedicated containment matrix for the minor actinides in a scenario limited to Pu recycling were comparable to

Matrix regulators in neural stem cell functions.

Science.gov (United States)

Wade, Anna; McKinney, Andrew; Phillips, Joanna J

2014-08-01

Neural stem/progenitor cells (NSPCs) reside within a complex and dynamic extracellular microenvironment, or niche. This niche regulates fundamental aspects of their behavior during normal neural development and repair. Precise yet dynamic regulation of NSPC self-renewal, migration, and differentiation is critical and must persist over the life of an organism. In this review, we summarize some of the major components of the NSPC niche and provide examples of how cues from the extracellular matrix regulate NSPC behaviors. We use proteoglycans to illustrate the many diverse roles of the niche in providing temporal and spatial regulation of cellular behavior. The NSPC niche is comprised of multiple components that include; soluble ligands, such as growth factors, morphogens, chemokines, and neurotransmitters, the extracellular matrix, and cellular components. As illustrated by proteoglycans, a major component of the extracellular matrix, the NSPC, niche provides temporal and spatial regulation of NSPC behaviors. The factors that control NSPC behavior are vital to understand as we attempt to modulate normal neural development and repair. Furthermore, an improved understanding of how these factors regulate cell proliferation, migration, and differentiation, crucial for malignancy, may reveal novel anti-tumor strategies. This article is part of a Special Issue entitled Matrix-mediated cell behaviour and properties. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

A Comparison on Gas Separation between PES(polyethersulfone)/MMT (Na-montmorillonite) and PES/TiO2 Mixed Matrix Membranes

Czech Academy of Sciences Publication Activity Database

Liang, Ch.-Y.; Uchytil, Petr; Petričkovič, Roman; Lai, Y.-Ch.; Friess, K.; Šípek, M.; Reddy, M.M.; Suen, S.-Y.

2012-01-01

Roč. 92, MAY 18 (2012), s. 57-63 ISSN 1383-5866 R&D Projects: GA ČR GCP106/10/J038 Grant - others:NSCT(TW) NSC:99-2911-I-005-002; NSCT(TW) NSC:99-2923-E-005-001-MY2 Institutional research plan: CEZ:AV0Z40720504 Keywords : mixed matrix membrane * polyethersulfone membrane * sodium montmorillonite Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 2.894, year: 2012

Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China

International Nuclear Information System (INIS)

Wang Degao; Tian Fulin; Yang Meng; Liu Chenlin; Li Yifan

2009-01-01

Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil. - PMF model is a proper approach to identify potential sources of PAHs in soil based on the PAH profiles measured in the field and those published in the literature.

Matrix Metalloproteinases in Non-Neoplastic Disorders

Science.gov (United States)

Tokito, Akinori; Jougasaki, Michihisa

2016-01-01

The matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases belonging to the metzincin superfamily. There are at least 23 members of MMPs ever reported in human, and they and their substrates are widely expressed in many tissues. Recent growing evidence has established that MMP not only can degrade a variety of components of extracellular matrix, but also can cleave and activate various non-matrix proteins, including cytokines, chemokines and growth factors, contributing to both physiological and pathological processes. In normal conditions, MMP expression and activity are tightly regulated via interactions between their activators and inhibitors. Imbalance among these factors, however, results in dysregulated MMP activity, which causes tissue destruction and functional alteration or local inflammation, leading to the development of diverse diseases, such as cardiovascular disease, arthritis, neurodegenerative disease, as well as cancer. This article focuses on the accumulated evidence supporting a wide range of roles of MMPs in various non-neoplastic diseases and provides an outlook on the therapeutic potential of inhibiting MMP action. PMID:27455234

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.

Quantification of uncertainties in turbulence modeling: A comparison of physics-based and random matrix theoretic approaches

International Nuclear Information System (INIS)

Wang, Jian-Xun; Sun, Rui; Xiao, Heng

2016-01-01

Highlights: • Compared physics-based and random matrix methods to quantify RANS model uncertainty. • Demonstrated applications of both methods in channel ow over periodic hills. • Examined the amount of information introduced in the physics-based approach. • Discussed implications to modeling turbulence in both near-wall and separated regions. - Abstract: Numerical models based on Reynolds-Averaged Navier-Stokes (RANS) equations are widely used in engineering turbulence modeling. However, the RANS predictions have large model-form uncertainties for many complex flows, e.g., those with non-parallel shear layers or strong mean flow curvature. Quantification of these large uncertainties originating from the modeled Reynolds stresses has attracted attention in the turbulence modeling community. Recently, a physics-based Bayesian framework for quantifying model-form uncertainties has been proposed with successful applications to several flows. Nonetheless, how to specify proper priors without introducing unwarranted, artificial information remains challenging to the current form of the physics-based approach. Another recently proposed method based on random matrix theory provides the prior distributions with maximum entropy, which is an alternative for model-form uncertainty quantification in RANS simulations. This method has better mathematical rigorousness and provides the most non-committal prior distributions without introducing artificial constraints. On the other hand, the physics-based approach has the advantages of being more flexible to incorporate available physical insights. In this work, we compare and discuss the advantages and disadvantages of the two approaches on model-form uncertainty quantification. In addition, we utilize the random matrix theoretic approach to assess and possibly improve the specification of priors used in the physics-based approach. The comparison is conducted through a test case using a canonical flow, the flow past

Nuclear reaction matrix and nuclear forces

International Nuclear Information System (INIS)

Nagata, Sinobu; Bando, Hiroharu; Akaishi, Yoshinori.

1979-01-01

An essentially exact method of solution is presented for the reaction- matrix (G-matrix) equation defined with the orthogonalized plane-wave intermediate spectrum for high-lying two-particle states. The accuracy is examined for introduced truncations and also in comparison with the Tsai-Kuo and Sauer methods. Properties of the G-matrix are discussed with emphasis on the relation with the saturation mechanism, especially overall saturation from light to heavy nuclei. Density and starting-energy dependences of the G-matrix are separately extracted and discussed. It is demonstrated that the triplet-even tensor component of the nuclear force is principally responsible for these dependences and hence for the saturation mechanism. In this context different nuclear potentials are used in the renormalized Brueckner calculation for energies of closed-shell nuclei in the harmonic oscillator basis. A semi-phenomenological ''two-body potential'' is devised so that it can reproduce the saturation energies and densities of nuclear matter and finite nuclei in the lowest-order Brueckner treatment. It is composed of a realistic N-N potential and two additional parts; one incorporates the three-body force effect and the other is assumed to embody higher-cluster correlations in G. The tensor component in the triplet-even state of this potential is enhanced by the three-body force effect. The G-matrix is represented in the effective local form and decomposed into central, LS and tensor components. (author)

Performance and stochastic stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

Directory of Open Access Journals (Sweden)

Biçer Cenker

2016-01-01

Full Text Available In this paper, the stability of the adaptive fading extended Kalman filter with the matrix forgetting factor when applied to the state estimation problem with noise terms in the non–linear discrete–time stochastic systems has been analysed. The analysis is conducted in a similar manner to the standard extended Kalman filter’s stability analysis based on stochastic framework. The theoretical results show that under certain conditions on the initial estimation error and the noise terms, the estimation error remains bounded and the state estimation is stable.

Investigation of neutronic behavior in a CANDU reactor with different (Am, Th, {sup 235}U)O{sub 2} fuel matrixes

Energy Technology Data Exchange (ETDEWEB)

Gholamzadeh, Z. [Talca Univ. (Chile). Dept. of Physics; Feghhi, S.A.H. [Shahid Beheshti Univ., Tehran (Iran, Islamic Republic of). Dept. of Radiation Application

2014-11-15

Recently thorium-based fuel matrixes are taken into consideration for nuclear waste incineration because of thorium proliferation resistance feature moreover its breeding or convertor ability in both thermal and fast reactors. In this work, neutronic influences of adding Am to (Th-{sup 235}U)O{sub 2} on effective delayed neutron fraction, reactivity coefficients and burn up of a fed CANDU core has been studied using MCNPX 2.6.0 computational code. Different atom fractions of Am have been introduced in the fuel matrix to evaluate its effects on neutronic parameters of the modeled core. The computational data show that adding 2% atom fraction of Am to thorium-based fuel matrix won't noticeably change reactivity coefficients in comparison with the fuel matrix containing 1% atom fraction of Am. The use of 2% atom fraction of Am resulted in a higher delayed neutron fraction. According to the obtained data, 32.85 GWd burn up of the higher Americium-containing fuel matrix resulted in 55.2%, 26.5%, 41.9% and 2.14% depletion of {sup 241}Am, {sup 243}Am, {sup 235}U and {sup 232}Th respectively. 132.8 kg of {sup 233}U fissile element is produced after the burn up time and the nuclear core multiplication factor increases in rate of 2390 pcm. The less americium-containing fuel matrix resulted in higher depletion of {sup 241/243}Am, {sup 235}U and {sup 232}Th while the nuclear core effective multiplication factor increases in rate of 5630 pcm after the burn up time with 9.8 kg additional {sup 233}U production.

Classifying FM Value Positioning by Using a Product-Process Matrix

DEFF Research Database (Denmark)

Katchamart, Akarapong

with the type of facilities processes between FM organizations with their clients. Approach (Theory/Methodology): The paper develops the facilities product - process matrix to allow comparisons of different facilities products with facilities processes and illustrate its degree of value delivering. The building......, characterized by levels of information, knowledge and innovation sharing, and mutual involvement, defines four facilities process types. Positions on the matrix capture the product-process interrelationships in facilities management. Practical Implications: The paper presents propositions of relating...... blocks of matrix are a facilities product structure and a facilities process structure. Results: A facilities product structure, characterized by degrees of facilities product customization, complexity, contingencies involved, defines four facilities product categories. A facilities process structure...

Modeling cometary photopolarimetric characteristics with Sh-matrix method

Science.gov (United States)

Kolokolova, L.; Petrov, D.

2017-12-01

Cometary dust is dominated by particles of complex shape and structure, which are often considered as fractal aggregates. Rigorous modeling of light scattering by such particles, even using parallelized codes and NASA supercomputer resources, is very computer time and memory consuming. We are presenting a new approach to modeling cometary dust that is based on the Sh-matrix technique (e.g., Petrov et al., JQSRT, 112, 2012). This method is based on the T-matrix technique (e.g., Mishchenko et al., JQSRT, 55, 1996) and was developed after it had been found that the shape-dependent factors could be separated from the size- and refractive-index-dependent factors and presented as a shape matrix, or Sh-matrix. Size and refractive index dependences are incorporated through analytical operations on the Sh-matrix to produce the elements of T-matrix. Sh-matrix method keeps all advantages of the T-matrix method, including analytical averaging over particle orientation. Moreover, the surface integrals describing the Sh-matrix elements themselves can be solvable analytically for particles of any shape. This makes Sh-matrix approach an effective technique to simulate light scattering by particles of complex shape and surface structure. In this paper, we present cometary dust as an ensemble of Gaussian random particles. The shape of these particles is described by a log-normal distribution of their radius length and direction (Muinonen, EMP, 72, 1996). Changing one of the parameters of this distribution, the correlation angle, from 0 to 90 deg., we can model a variety of particles from spheres to particles of a random complex shape. We survey the angular and spectral dependencies of intensity and polarization resulted from light scattering by such particles, studying how they depend on the particle shape, size, and composition (including porous particles to simulate aggregates) to find the best fit to the cometary observations.

Joint refinement model for the spin resolved one-electron reduced density matrix of YTiO3 using magnetic structure factors and magnetic Compton profiles data.

Science.gov (United States)

Gueddida, Saber; Yan, Zeyin; Kibalin, Iurii; Voufack, Ariste Bolivard; Claiser, Nicolas; Souhassou, Mohamed; Lecomte, Claude; Gillon, Béatrice; Gillet, Jean-Michel

2018-04-28

In this paper, we propose a simple cluster model with limited basis sets to reproduce the unpaired electron distributions in a YTiO 3 ferromagnetic crystal. The spin-resolved one-electron-reduced density matrix is reconstructed simultaneously from theoretical magnetic structure factors and directional magnetic Compton profiles using our joint refinement algorithm. This algorithm is guided by the rescaling of basis functions and the adjustment of the spin population matrix. The resulting spin electron density in both position and momentum spaces from the joint refinement model is in agreement with theoretical and experimental results. Benefits brought from magnetic Compton profiles to the entire spin density matrix are illustrated. We studied the magnetic properties of the YTiO 3 crystal along the Ti-O 1 -Ti bonding. We found that the basis functions are mostly rescaled by means of magnetic Compton profiles, while the molecular occupation numbers are mainly modified by the magnetic structure factors.

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

Plutonium fuel lattice neutron behavior in inert matrix

International Nuclear Information System (INIS)

Hernandez L, H.; Lucatero, M. A.

2010-10-01

In several countries is had been researching the possibility of using plutonium, as weapon degree as reactor degree, as fuel material in commercial reactors to generate electricity. In special a great development has been in Pressure Water Reactors. However, in Mexico the reactors are Boiling Water Reactors type, reason for which the necessity to considers feasibility to use this fuel type in the reactors of nuclear power plant of Laguna Verde. For this propose a comparison of fuel lattice that compose a fuel assembly is made. The fuel assembly will propose to be used whit in the reactor present different inert matrix, as well as burnable poison. The material that compose the inert matrices used are cerium and zirconia (CeO 2 and ZrO 2 ) and as burnable poisons have gadolinium and erbium (Gd 2 O 4 and ErO 2 ). As far as the hydraulic design used is a cell 10 X 10 with two water channels. The lattice calculations are made with the Helios code a library with 35 energy groups, having determined the pin power factors, the infinite multiplication factor and the neutron flux profiles. (Author)

Mechanical properties of aluminium matrix composites reinforced with intermetallics

International Nuclear Information System (INIS)

Torres, B.; Garcia-Escorial, A.; Ibanez, J.; Lieblich, M.

2001-01-01

In this work 2124 aluminium matrix composites reinforced with Ni 3 Al, NiAl, MoSi 2 and Cr 3 Si intermetallic powder particles have been investigated. For comparison purposes, un reinforced 2124 and reinforced with SiC have also been studied. In all cases, the same powder metallurgy route was used, i. e. the 2124 alloy was obtained by rapid solidification and the intermetallic particles by self-propagating high-temperature synthesis (SHS). The matrix and the intermetallics were mechanically blended, cold compacted and finally hot extruded. Tensile tests were carried out in T1 and T4 treatments. Results indicate that mechanical properties depend strongly on the tendency to form new phases at the matrix-intermetallic interface during processing and/or further thermal treatments. The materials which present better properties are those that present less reaction between matrix and intermetallic reinforcement, i. e. MoSi 2 and SiC reinforced composites. (Author) 9 refs

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.

A comparison of companion matrix methods to find roots of a trigonometric polynomial

Science.gov (United States)

Boyd, John P.

2013-08-01

A trigonometric polynomial is a truncated Fourier series of the form fN(t)≡∑j=0Naj cos(jt)+∑j=1N bj sin(jt). It has been previously shown by the author that zeros of such a polynomial can be computed as the eigenvalues of a companion matrix with elements which are complex valued combinations of the Fourier coefficients, the "CCM" method. However, previous work provided no examples, so one goal of this new work is to experimentally test the CCM method. A second goal is introduce a new alternative, the elimination/Chebyshev algorithm, and experimentally compare it with the CCM scheme. The elimination/Chebyshev matrix (ECM) algorithm yields a companion matrix with real-valued elements, albeit at the price of usefulness only for real roots. The new elimination scheme first converts the trigonometric rootfinding problem to a pair of polynomial equations in the variables (c,s) where c≡cos(t) and s≡sin(t). The elimination method next reduces the system to a single univariate polynomial P(c). We show that this same polynomial is the resultant of the system and is also a generator of the Groebner basis with lexicographic ordering for the system. Both methods give very high numerical accuracy for real-valued roots, typically at least 11 decimal places in Matlab/IEEE 754 16 digit floating point arithmetic. The CCM algorithm is typically one or two decimal places more accurate, though these differences disappear if the roots are "Newton-polished" by a single Newton's iteration. The complex-valued matrix is accurate for complex-valued roots, too, though accuracy decreases with the magnitude of the imaginary part of the root. The cost of both methods scales as O(N3) floating point operations. In spite of intimate connections of the elimination/Chebyshev scheme to two well-established technologies for solving systems of equations, resultants and Groebner bases, and the advantages of using only real-valued arithmetic to obtain a companion matrix with real-valued elements

Source apportionment of atmospheric bulk deposition in the Belgrade urban area using Positive Matrix factorization

Science.gov (United States)

Tasić, M.; Mijić, Z.; Rajšić, S.; Stojić, A.; Radenković, M.; Joksić, J.

2009-04-01

The primary objective of the present study was to assess anthropogenic impacts of heavy metals to the environment by determination of total atmospheric deposition of heavy metals. Atmospheric depositions (wet + dry) were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade, using bulk deposition samplers. Concentrations of Fe, Al, Pb, Zn, Cu, Ni, Mn, Cr, V, As and Cd were analyzed using atomic absorption spectrometry. Based upon these results, the study attempted to examine elemental associations in atmospheric deposition and to elucidate the potential sources of heavy metal contaminants in the region by the use of multivariate receptor model Positive Matrix Factorization (PMF).

Source apportionment of atmospheric bulk deposition in the Belgrade urban area using Positive Matrix factorization

International Nuclear Information System (INIS)

Tasic, M; Mijic, Z; Rajsic, S; Stojic, A; Radenkovic, M; Joksic, J

2009-01-01

The primary objective of the present study was to assess anthropogenic impacts of heavy metals to the environment by determination of total atmospheric deposition of heavy metals. Atmospheric depositions (wet + dry) were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade, using bulk deposition samplers. Concentrations of Fe, Al, Pb, Zn, Cu, Ni, Mn, Cr, V, As and Cd were analyzed using atomic absorption spectrometry. Based upon these results, the study attempted to examine elemental associations in atmospheric deposition and to elucidate the potential sources of heavy metal contaminants in the region by the use of multivariate receptor model Positive Matrix Factorization (PMF).

Activity concentration measurements of 137Cs, 90Sr and 40K in a wild food matrix reference material (Wild Berries) CCRI(II)-S8

International Nuclear Information System (INIS)

Watjen, U.; Altzitzogloa, T.; Spasova, Y.; Ceccatelli, A.; Kis-Benedek, G.; Dikmen, H.; Gundogdu, G.; Yucel, U.; Ferreux, L.; Frechou, C.; Pierre, S.; Garcia, L.; Moreno, Y.; Oropesa, P.; La Rosa, J.; Luca, A.; Schmiedel, M.; Wershofen, H.; Szucs, L.; Vasile, M.

2014-01-01

In 2009, the CCRI approved a supplementary comparison to be organized by the IRMM as pilot laboratory for the activity concentrations of 137 Cs, 90 Sr and 40 K in a matrix material of dried bilberries. The organization of this comparison and the material and measurement methods used are described. The supplementary comparison reference values (SCRV) for each of the three radionuclides are given together with the degrees of equivalence of each participating laboratory with the SCRV for the specific radionuclide. The results of this supplementary comparison allow the participating NMIs/designated institutes to declare calibration and measurement capabilities (CMCs) for the given radionuclides in a similar type of food matrix, an important aspect given the relatively few supplementary comparisons for activity in matrix materials organized so far. (authors)

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.

Effect of pomegranate juice supplementation on matrix metalloproteinases 2 and 9 following exhaustive exercise in young healthy males

International Nuclear Information System (INIS)

Mazani, M.; Fard, A. S.; Baghi, A. N.; Nemati, A.; Mogadam, R. A.

2014-01-01

Objectives: To evaluate the efficacy of pomegranate juice supplementation on matrix metalloproteinases 2 and 9 serum levels and improving antioxidant function in young healthy males during exhaustive exercise. Methods: The study was conducted at Ardabil University of Medical Sciences, Iran, in 2010-11 and comprised 28 healthy subjects in 18-24 age bracket. They were randomly divided into control and supplemented groups. One cup of pomegranate juice and one cup of tap water were given to supplemented and control groups daily for two weeks respectively. Fasting blood samples were taken at baseline and at the end of two weeks of intervention. The subjects were given one exhaustive exercise and then fasting blood samples were taken for testing blood glutathione peroxidase and superoxide dismutase and serum levels of high sensitivity C-reactive protein, zinc, ceruloplasmin, matrix metalloproteinases 2 and 9, malondialdehyde and total antioxidant capacity. Data was analysed using descriptive statistical tests, paired and independent sample t-test. Results: The blood levels of glutathione peroxidase and superoxide dismutase and serum levels of total antioxidant capacity after exhaustive exercise in the supplemented group were significantly increased (p<0.05), while the content of matrix metalloproteinases 2 and 9, ceruloplasmin and malondialdehyde showed a significant decrease in comparison to the control group (p<0.05). Besides, there were no significant changes in other biochemical factors. Conclusion: Regular intake of pomegranate juice significantly modulates matrix metalloproteinases 2 and 9 serum levels of some inflammatory factors and thus protects against exhaustive exercise-induced oxidative injury in young healthy males. (author)

The interplay of matrix metalloproteinases, morphogens and growth factors is necessary for branching of mammary epithelial cells

International Nuclear Information System (INIS)

Simian, Marina; Hirai, Yohei; Navre, Marc; Werb, Zena; Lochter, Andre; Bissell, Mina J.

2002-01-01

The mammary gland develops its adult form by a process referred to as branching morphogenesis. Many factors have been reported to affect this process. We have used cultured primary mammary epithelial organoids and mammary epithelial cell lines in three-dimensional collagen gels to elucidate which growth factors, matrix metalloproteinases (MMPs) and mammary morphogens interact in branching morphogenesis. Branching stimulated by stromal fibroblasts, epidermal growth factor, fibroblast growth factor 7, fibroblast growth factor 2 and hepatocyte growth factor was strongly reduced by inhibitors of MMPs, indicating the requirement of MMPs for three-dimensional growth involved in morphogenesis. Recombinant stromelysin 1/MMP-3 alone was sufficient to drive branching in the absence of growth factors in the organoids. Plasmin also stimulated branching; however, plasmin-dependent branching was abolished by both inhibitors of plasmin and MMPs, suggesting that plasmin activates MMPs. To differentiate between signals for proliferation and morphogenesis, we used a cloned mammary epithelial cell line that lacks epimorphin, an essential mammary morphogen. Both epimorphin and MMPs were required for morphogenesis, but neither was required for epithelial cell proliferation. These results provide direct evidence for a critical role of MMPs in branching in mammary epithelium and suggest that, in addition to epimorphin, MMP activity is a minimum requirement for branching morphogenesis in the mammary gland

The interplay of matrix metalloproteinases, morphogens and growth factors is necessary for branching of mammary epithelial cells

Energy Technology Data Exchange (ETDEWEB)

Simian, M.; Harail, Y.; Navre, M.; Werb, Z.; Lochter, A.; Bissell, M.J.

2002-03-06

The mammary gland develops its adult form by a process referred to as branching morphogenesis. Many factors have been reported to affect this process. We have used cultured primary mammary epithelial organoids and mammary epithelial cell lines in three-dimensional collagen gels to elucidate which growth factors, matrix metalloproteinases (MMPs) and mammary morphogens interact in branching morphogenesis. Branching stimulated by stromal fibroblasts, epidermal growth factor, fibroblast growth factor 7, fibroblast growth factor 2 and hepatocyte growth factor was strongly reduced by inhibitors of MMPs, indicating the requirement of MMPs for three-dimensional growth involved in morphogenesis. Recombinant stromelysin 1/MMP-3 alone was sufficient to drive branching in the absence of growth factors in the organoids. Plasmin also stimulated branching; however, plasmin-dependent branching was abolished by both inhibitors of plasmin and MMPs, suggesting that plasmin activates MMPs. To differentiate between signals for proliferation and morphogenesis, we used a cloned mammary epithelial cell line that lacks epimorphin, an essential mammary morphogen. Both epimorphin and MMPs were required for morphogenesis, but neither was required for epithelial cell proliferation. These results provide direct evidence for a critical role of MMPs in branching in mammary epithelium and suggest that, in addition to epimorphin, MMP activity is a minimum requirement for branching morphogenesis in the mammary gland.

Interface matrix method in AFEN framework

Energy Technology Data Exchange (ETDEWEB)

Pogosbekyan, Leonid; Cho, Jin Young; Kim, Young Jin [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1998-12-31

In this study, we extend the application of the interface-matrix(IM) method for reflector modeling to Analytic Flux Expansion Nodal (AFEN) method. This include the modifications of the surface-averaged net current continuity and the net leakage balance conditions for IM method in accordance with AFEN formula. AFEN-interface matrix (AFEN-IM) method has been tested against ZION-1 benchmark problem. The numerical result of AFEN-IM method shows 1.24% of maximum error and 0.42% of root-mean square error in assembly power distribution, and 0.006% {Delta} k of neutron multiplication factor. This result proves that the interface-matrix method for reflector modeling can be useful in AFEN method. 3 refs., 4 figs. (Author)

Interface matrix method in AFEN framework

Energy Technology Data Exchange (ETDEWEB)

Pogosbekyan, Leonid; Cho, Jin Young; Kim, Young Jin [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1997-12-31

In this study, we extend the application of the interface-matrix(IM) method for reflector modeling to Analytic Flux Expansion Nodal (AFEN) method. This include the modifications of the surface-averaged net current continuity and the net leakage balance conditions for IM method in accordance with AFEN formula. AFEN-interface matrix (AFEN-IM) method has been tested against ZION-1 benchmark problem. The numerical result of AFEN-IM method shows 1.24% of maximum error and 0.42% of root-mean square error in assembly power distribution, and 0.006% {Delta} k of neutron multiplication factor. This result proves that the interface-matrix method for reflector modeling can be useful in AFEN method. 3 refs., 4 figs. (Author)

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

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

Load transfer in short fibre reinforced metal matrix composites

International Nuclear Information System (INIS)

Garces, Gerardo; Bruno, Giovanni; Wanner, Alexander

2007-01-01

The internal load transfer and the deformation behaviour of aluminium-matrix composites reinforced with 2D-random alumina (Saffil) short fibres was studied for different loading modes. The evolution of stress in the metallic matrix was measured by neutron diffraction during in situ uniaxial deformation tests. Tensile and compressive tests were performed with loading axis parallel or perpendicular to the 2D-reinforcement plane. The fibre stresses were computed based on force equilibrium considerations. The results are discussed in light of a model recently established by the co-authors for composites with visco-plastic matrix behaviour and extended to the case of plastic deformation in the present study. Based on that model, the evolution of internal stresses and the macroscopic stress-strain were simulated. Comparison between the experimental and computational results shows a qualitative agreement in all relevant aspects

Topical photodynamic therapy following excisional wounding of human skin increases production of transforming growth factor-β3 and matrix metalloproteinases 1 and 9, with associated improvement in dermal matrix organization.

Science.gov (United States)

Mills, S J; Farrar, M D; Ashcroft, G S; Griffiths, C E M; Hardman, M J; Rhodes, L E

2014-07-01

Animal studies report photodynamic therapy (PDT) to improve healing of excisional wounds; the mechanism is uncertain and equivalent human studies are lacking. To explore the impact of methyl aminolaevulinate (MAL)-PDT on clinical and microscopic parameters of human cutaneous excisional wound healing, examining potential modulation through production of transforming growth factor (TGF)-β isoforms. In 27 healthy older men (60-77 years), a 4-mm punch biopsy wound was created in skin of the upper inner arm and treated with MAL-PDT three times over 5 days. An identical control wound to the contralateral arm was untreated and both wounds left to heal by secondary intention. Wounds were re-excised during the inflammatory phase (7 days, n = 10), matrix remodelling (3 weeks, n = 8) and cosmetic outcome/dermal structure (9 months, n = 9). Production of TGF-β1, TGF-β3 and matrix metalloproteinases (MMPs) was assessed by immunohistochemistry alongside microscopic measurement of wound size/area and clinical assessment of wound appearance. MAL-PDT delayed re-epithelialization at 7 days, associated with increased inflammation. However, 3 weeks postwounding, treated wounds were smaller with higher production of MMP-1 (P = 0·01), MMP-9 (P = 0·04) and TGF-β3 (P = 0·03). TGF-β1 was lower than control at 7 days and higher at 3 weeks (both P = 0·03). At 9 months, MAL-PDT-treated wounds showed greater, more ordered deposition of collagen I, collagen III and elastin (all P < 0·05). MAL-PDT increases MMP-1, MMP-9 and TGF-β3 production during matrix remodelling, ultimately producing scars with improved dermal matrix architecture. © 2014 British Association of Dermatologists.

Practical criterion for the determination of translation factors

International Nuclear Information System (INIS)

Riera, A.

1984-01-01

Following an idea of Rankin and Thorson, a method is proposed to determine translation factors in the molecular model of atomic collisions, and for low and intermediate nuclear velocities. The method is based on the minimization of a measure of all (electrostatic and dynamical) couplings between the states included in, and those left out from, the molecular expansion. The properties of this measure are discussed. In particular, its evaluation involves the calculation of a few new matrix elements, and this can be performed analytically when Gaussian-type orbitals are used to construct the wave functions. The method also provides a comparison between all approaches that employ translation factors, and a test of the conditions that are usually enforced on these factors

Practical criterion for the determination of translation factors

Energy Technology Data Exchange (ETDEWEB)

Riera, A.

1984-11-01

Following an idea of Rankin and Thorson, a method is proposed to determine translation factors in the molecular model of atomic collisions, and for low and intermediate nuclear velocities. The method is based on the minimization of a measure of all (electrostatic and dynamical) couplings between the states included in, and those left out from, the molecular expansion. The properties of this measure are discussed. In particular, its evaluation involves the calculation of a few new matrix elements, and this can be performed analytically when Gaussian-type orbitals are used to construct the wave functions. The method also provides a comparison between all approaches that employ translation factors, and a test of the conditions that are usually enforced on these factors.

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.

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.

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.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

Energy Technology Data Exchange (ETDEWEB)

Telfeyan, Katherine Christina [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ware, Stuart Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Birdsell, Kay Hanson [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-06

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

An immunofluorescence assay for extracellular matrix components highlights the role of epithelial cells in producing a stable, fibrillar extracellular matrix

Directory of Open Access Journals (Sweden)

Omar S. Qureshi

2017-10-01

Full Text Available Activated fibroblasts are considered major drivers of fibrotic disease progression through the production of excessive extracellular matrix (ECM in response to signals from damaged epithelial and inflammatory cells. Nevertheless, epithelial cells are capable of expressing components of the ECM, cross-linking enzymes that increase its stability and are sensitive to factors involved in the early stages of fibrosis. We therefore wanted to test the hypothesis that epithelial cells can deposit ECM in response to stimulation in a comparable manner to fibroblasts. We performed immunofluorescence analysis of components of stable, mature extracellular matrix produced by primary human renal proximal tubular epithelial cells and renal fibroblasts in response to cytokine stimulation. Whilst fibroblasts produced a higher basal level of extracellular matrix components, epithelial cells were able to deposit significant levels of fibronectin, collagen I, III and IV in response to cytokine stimulation. In response to hypoxia, epithelial cells showed an increase in collagen IV deposition but not in response to the acute stress stimuli aristolochic acid or hydrogen peroxide. When epithelial cells were in co-culture with fibroblasts we observed significant increases in the level of matrix deposition which could be reduced by transforming growth factor beta (TGF-β blockade. Our results highlight the role of epithelial cells acting as efficient producers of stable extracellular matrix which could contribute to renal tubule thickening in fibrosis.

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.

Testing the usability of the Rapid Impact Assessment Matrix (RIAM) method for comparison of EIA and SEA results

International Nuclear Information System (INIS)

Kuitunen, Markku; Jalava, Kimmo; Hirvonen, Kimmo

2008-01-01

This study examines how the results of Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) could be compared using the Rapid Impact Assessment Matrix (RIAM) method. There are many tools and techniques that have been developed for use in impact assessment processes, including scoping, checklists, matrices, qualitative and quantitative models, literature reviews, and decision-support systems. While impact assessment processes have become more technically complicated, it is recognized that approaches including simpler applications of available tools and techniques are also appropriate. The Rapid Impact Assessment Matrix (RIAM) is a tool for organizing, analysing and presenting the results of a holistic EIA. RIAM was originally developed to compare the impact of alternative procedures in a single project. In this study, we used RIAM to compare the environmental and social impact of different projects, plans and programs realized within the same geographical area. RIAM scoring is based on five separate criteria. The RIAM criteria were applied to the impact that was considered to be the most significant in the evaluated cases, and scores were given both on environmental and social impact. Our results revealed that the RIAM method could be used for comparison and ranking of separate and distinct projects, plans, programs and policies, based on their negative or positive impact. Our data included 142 cases from the area of Central Finland that is covered by the Regional Council of Central Finland. This sample consisted of various types of projects, ranging from road construction to education programs that applied for EU funding

Characterization of the proteins comprising the integral matrix of Strongylocentrotus purpuratus embryonic spicules

Science.gov (United States)

Killian, C. E.; Wilt, F. H.

1996-01-01

In the present study, we enumerate and characterize the proteins that comprise the integral spicule matrix of the Strongylocentrotus purpuratus embryo. Two-dimensional gel electrophoresis of [35S]methionine radiolabeled spicule matrix proteins reveals that there are 12 strongly radiolabeled spicule matrix proteins and approximately three dozen less strongly radiolabeled spicule matrix proteins. The majority of the proteins have acidic isoelectric points; however, there are several spicule matrix proteins that have more alkaline isoelectric points. Western blotting analysis indicates that SM50 is the spicule matrix protein with the most alkaline isoelectric point. In addition, two distinct SM30 proteins are identified in embryonic spicules, and they have apparent molecular masses of approximately 43 and 46 kDa. Comparisons between embryonic spicule matrix proteins and adult spine integral matrix proteins suggest that the embryonic 43-kDa SM30 protein is an embryonic isoform of SM30. An adult 49-kDa spine matrix protein is also identified as a possible adult isoform of SM30. Analysis of the SM30 amino acid sequences indicates that a portion of SM30 proteins is very similar to the carbohydrate recognition domain of C-type lectin proteins.

Matrix Organization and Merit Factor Evaluation as a Method to Address the Challenge of Finding a Polymer Material for Roll Coated Polymer Solar Cells

DEFF Research Database (Denmark)

Bundgaard, Eva; Livi, Francesco; Hagemann, Ole

2015-01-01

The results presented demonstrate how the screening of 104 light-absorbing low band gap polymers for suitability in roll coated polymer solar cells can be accomplished through rational synthesis according to a matrix where 8 donor and 13 acceptor units are organized in rows and columns. Synthesis...... silver comb back electrode structure. The matrix organization enables fast identification of active layer materials according to a weighted merit factor that includes more than simply the power conversion efficiency and is used as a method to identify the lead candidates. Based on several characteristics...

Analysis of risk factors for hydrocephalus development in newborn infants with germinal matrix hemorrhage.

Science.gov (United States)

Romero, L; Ros, B; Arráez, M A; Ríus, F; González, L; Martín, A; Carrasco, A; Segura, M

2015-10-01

The aim of this study was to analyze risk factors for the development of hydrocephalus in newborn infants with germinal matrix (GM) hemorrhage. The study comprised 271 patients admitted to Carlos Haya University Hospital in Malaga with GM hemorrhage. The following data were recorded: gestational age, gender, twin birth, head circumference at birth, weight at birth, and Papile grade. Severe obstetrical (abruption, chorioamnionitis, pregnancy-induced hypertension, tocolytic treatment) and neonatal disorders (respiratory distress syndrome, neonatal infection, coagulation disorder, patent ductus arteriosus, necrotizing enterocolitis) were also recorded. Symptomatic hydrocephalus was diagnosed in the event of a progressive increase in head circumference and ventricular indices requiring shunting. Of the 271 patients, 139 (51%) developed posthemorrhagic ventriculomegaly; 47 patients (17%) developed symptomatic hydrocephalus and needed shunt implantation. We found a significant relationship between the development of symptomatic hydrocephalus and Papile grade, lower gestational age, lower birth weight, twin birth, and neonatal infection. Awareness of risk factors for the development of hydrocephalus in newborn infants with GM hemorrhage should be emphasized in order to enable an early diagnosis of ventriculomegaly and symptomatic hydrocephalus and thus make a correct therapeutic decision.

Age-related collagen turnover of the interstitial matrix and basement membrane: Implications of age- and sex-dependent remodeling of the extracellular matrix.

Science.gov (United States)

Kehlet, Stephanie N; Willumsen, Nicholas; Armbrecht, Gabriele; Dietzel, Roswitha; Brix, Susanne; Henriksen, Kim; Karsdal, Morten A

2018-01-01

The extracellular matrix (ECM) plays a vital role in maintaining normal tissue function. Collagens are major components of the ECM and there is a tight equilibrium between degradation and formation of these proteins ensuring tissue health and homeostasis. As a consequence of tissue turnover, small collagen fragments are released into the circulation, which act as important biomarkers in the study of certain tissue-related remodeling factors in health and disease. The aim of this study was to establish an age-related collagen turnover profile of the main collagens of the interstitial matrix (type I and III collagen) and basement membrane (type IV collagen) in healthy men and women. By using well-characterized competitive ELISA-assays, we assessed specific fragments of degraded (C1M, C3M, C4M) and formed (PINP, Pro-C3, P4NP7S) type I, III and IV collagen in serum from 617 healthy men and women ranging in ages from 22 to 86. Subjects were divided into 5-year age groups according to their sex and age. Groups were compared using Kruskal-Wallis adjusted for Dunn's multiple comparisons test and Mann-Whitney t-test. Age-specific changes in collagen turnover was most profound for type I collagen. PINP levels decreased in men with advancing age, whereas in women, the level decreased in early adulthood followed by an increase around the age of menopause (age 40-60). Sex-specific changes in type I, III and IV collagen turnover was present at the age around menopause (age 40-60) with women having an increased turnover. In summary, collagen turnover is affected by age and sex with the interstitial matrix and the basement membrane being differently regulated. The observed changes needs to be accounted for when measuring ECM related biomarkers in clinical studies.

Nonstatic, self-consistent πN t matrix in nuclear matter

International Nuclear Information System (INIS)

Van Orden, J.W.

1984-01-01

In a recent paper, a calculation of the self-consistent πN t matrix in nuclear matter was presented. In this calculation the driving term of the self-consistent equation was chosen to be a static approximation to the free πN t matrix. In the present work, the earlier calculation is extended by using a nonstatic, fully-off-shell free πN t matrix as a starting point. Right-hand pole and cut contributions to the P-wave πN amplitudes are derived using a Low expansion and include effects due to recoil of the interacting πN system as well as the transformation from the πN c.m. frame to the nuclear rest frame. The self-consistent t-matrix equation is rewritten as two integral equations which modify the pole and cut contributions to the t matrix separately. The self-consistent πN t matrix is calculated in nuclear matter and a nonlocal optical potential is constructed from it. The resonant contribution to the optical potential is found to be broadened by 20% to 50% depending on pion momentum and is shifted upward in energy by approximately 10 MeV in comparison to the first-order optical potential. Modifications to the nucleon pole contribution are found to be negligible

Extracellular matrix protein 1, a direct targeting molecule of parathyroid hormone–related peptide, negatively regulates chondrogenesis and endochondral ossification via associating with progranulin growth factor

Science.gov (United States)

Kong, Li; Zhao, Yun-Peng; Tian, Qing-Yun; Feng, Jian-Quan; Kobayashi, Tatsuya; Merregaert, Joseph; Liu, Chuan-Ju

2016-01-01

Chondrogenesis and endochondral ossification are precisely controlled by cellular interactions with surrounding matrix proteins and growth factors that mediate cellular signaling pathways. Here, we report that extracellular matrix protein 1 (ECM1) is a previously unrecognized regulator of chondrogenesis. ECM1 is induced in the course of chondrogenesis and its expression in chondrocytes strictly depends on parathyroid hormone–related peptide (PTHrP) signaling pathway. Overexpression of ECM1 suppresses, whereas suppression of ECM1 enhances, chondrocyte differentiation and hypertrophy in vitro and ex vivo. In addition, target transgene of ECM1 in chondrocytes or osteoblasts in mice leads to striking defects in cartilage development and endochondral bone formation. Of importance, ECM1 seems to be critical for PTHrP action in chondrogenesis, as blockage of ECM1 nearly abolishes PTHrP regulation of chondrocyte hypertrophy, and overexpression of ECM1 rescues disorganized growth plates of PTHrP-null mice. Furthermore, ECM1 and progranulin chondrogenic growth factor constitute an interaction network and act in concert in the regulation of chondrogenesis.—Kong, L., Zhao, Y.-P., Tian, Q.-Y., Feng, J.-Q., Kobayashi, T., Merregaert, J., Liu, C.-J. Extracellular matrix protein 1, a direct targeting molecule of parathyroid hormone–related peptide, negatively regulates chondrogenesis and endochondral ossification via associating with progranulin growth factor. PMID:27075243

Optoelectronic switch matrix as a look-up table for residue arithmetic.

Science.gov (United States)

Macdonald, R I

1987-10-01

The use of optoelectronic matrix switches to perform look-up table functions in residue arithmetic processors is proposed. In this application, switchable detector arrays give the advantage of a greatly reduced requirement for optical sources by comparison with previous optoelectronic residue processors.

Matrix Remodeling in Pulmonary Fibrosis and Emphysema

Science.gov (United States)

O’Reilly, Philip; Antony, Veena B.; Gaggar, Amit

2016-01-01

Pulmonary fibrosis and emphysema are chronic lung diseases characterized by a progressive decline in lung function, resulting in significant morbidity and mortality. A hallmark of these diseases is recurrent or persistent alveolar epithelial injury, typically caused by common environmental exposures such as cigarette smoke. We propose that critical determinants of the outcome of the injury-repair processes that result in fibrosis versus emphysema are mesenchymal cell fate and associated extracellular matrix dynamics. In this review, we explore the concept that regulation of mesenchymal cells under the influence of soluble factors, in particular transforming growth factor-β1, and the extracellular matrix determine the divergent tissue remodeling responses seen in pulmonary fibrosis and emphysema. PMID:26741177

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

Science.gov (United States)

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

2017-06-01

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

Matrix evaluation for Pseudomonas spp. immobilisation in phenol bioremediation

Directory of Open Access Journals (Sweden)

Leonel Chitiva Urbina

2003-07-01

Full Text Available Pseudomonas spp. were cultivated in a free cell suspension and also immobilised in three different matrices to observe the influence of a contaminant like phenol on degradation velocity and compare each one's results. Polyurethane polymers, alginate (Manohar et al, 2001 and a mixture of alginate and polyvinyl alcohol (Doria et al, 2002 were selected and tested as matrices; all of them proved viable as matrices for cell immobilisation. Pseudomonas were cultivated in an initial 10 cfu/ml concentration in each one of the matrices for comparison purposes and in a medium without matrix; all mediums were supplemented with a minimum salt medium and 200 ppm phenol. A removal time of 23 days was observed in the medium without matrix, 15 days in the polyurethane matrix and 7 days in the alginate matrices. Improved removal times were observed in all matrices when compared to the free cell suspension.

Universality in random matrix theory and chiral symmetry breaking in QCD

International Nuclear Information System (INIS)

Akemann, G.

2000-05-01

In this work we review the topic of random matrix model universality with particular stress on its application to the study of chiral symmetry breaking in QCD. We highlight the role of microscopic and macroscopic matrix model correlation functions played in the description of the deep infrared eigenvalue spectrum of the Dirac operator. The universal microscopic correlation functions are presented for all three chiral symmetry breaking patterns, and the corresponding random matrix universality proofs are given for massless and massive fermions in a unified way. These analytic results have been widely confirmed from QCD lattice data and we present a comparison with the most recent analytic calculations describing data for dynamical SU(2) staggered fermions. The microscopic matrix model results are then re-expressed in terms of the finite-volume partition functions of Leutwyler and Smilga, where some of these expressions have been recently obtained using field theory only. The macroscopic random matrix universality is reviewed for the most simplest examples of bosonic and supersymmetric models. We also give an example for a non-universal deformation of a random matrix model - the restricted trace ensemble. (orig.)

KEY COMPARISON: CCQM-K61: Quantitation of a linearised plasmid DNA, based on a matched standard in a matrix of non-target DNA

Science.gov (United States)

Woolford, Alison; Holden, Marcia; Salit, Marc; Burns, Malcolm; Ellison, Stephen L. R.

2009-01-01

Key comparison CCQM-K61 was performed to demonstrate and document the capability of interested national metrology institutes in the determination of the quantity of specific DNA target in an aqueous solution. The study provides support for the following measurement claim: "Quantitation of a linearised plasmid DNA, based on a matched standard in a matrix of non-target DNA". The comparison was an activity of the Bioanalysis Working Group (BAWG) of the Comité Consultatif pour la Quantité de Matière and was coordinated by NIST (Gaithersburg, USA) and LGC (Teddington, UK). The following laboratories (in alphabetical order) participated in this key comparison. DMSC (Thailand); IRMM (European Union); KRISS (Republic of Korea); LGC (UK); NIM (China); NIST (USA); NMIA (Australia); NMIJ (Japan); VNIIM (Russian Federation) Good agreement was observed between the reported results of all nine of the participants. Uncertainty estimates did not account fully for the dispersion of results even after allowance for possible inhomogeneity in calibration materials. Preliminary studies suggest that the effects of fluorescence threshold setting might contribute to the excess dispersion, and further study of this topic is suggested Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

Tetrahedron equations and the relativistic S-matrix of straight-strings in 2+1-dimensions

International Nuclear Information System (INIS)

Zamolodchikov, A.B.

1981-01-01

The quantum S-matrix theory of straight-strings (infinite one-dimensioanl objects like straight domain walls) in 2 + 1-dimensions is considered. The S-matrix is supposed to be purely elastic and factorized. The tetrahedron equations (which are the factorization conditions) are investigated for the special two-colour model. The relativistic three-string S-matrix, which apparently satisfies this tetrahedron equation, is proposed. (orig.)

Foundations of factor analysis

CERN Document Server

Mulaik, Stanley A

2009-01-01

Introduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMulti

Assessment of the influence of anthropogenic factors on elements of the ecological network in Vojvodina (Serbia using the Leopold matrix

Directory of Open Access Journals (Sweden)

Kicošev Vesna

2015-01-01

Full Text Available Salt steppes and marshes represent the most valuable ecosystems in the world, providing numerous ecosystem services that are extremely vulnerable to anthropogenic influences. These types of habitat in the territory of Serbia are most dominant in Banat and a significant portion of them is under protection or in the process of becoming protected. The section surrounding the protected areas of Slano Kopovo Special Nature Reserve, Rusanda Nature Park and Okanj Bara Special Nature Reserve with the non-building area of Novi Bečej, Kumane, Melenci, Elemir and Taraš cadastral municipalities, has been chosen for the analysis. The aim of this paper was to assess the influence of specific anthropogenic factors on the elements of an ecological network using the analytical method that can generate the required results in a manner suitable for presentation to various stakeholders. To achieve this aim, the Leopold matrix model, used for assessing anthropogenic influence on the environment, has been chosen. The specificity of this issue of protecting and preserving elements of an ecological network resulted in the need to isolate and evaluate the factors affecting the preservation of habitats and functionality of ecosystems, unlike the concept of Leopold matrix, which treats all factors as equally important in the process of evaluation. Evaluation results indicate significant effects of historical, perennial manner of using the area and other resources in the non-building area.

Solving symmetric-definite quadratic lambda-matrix problems without factorization

International Nuclear Information System (INIS)

Scott, D.S.; Ward, R.C.

1982-01-01

Algorithms are presented for computing some of the eigenvalues and their associated eigenvectors of the quadratic lambda-matrix M lambda 2 C lambda + K. M, C, and K are assumed to have special symmetry-type properties which insure that theory analogous to the standard symmetric eigenproblem exists. The algorithms are based on a generalization of the Rayleigh quotient and the Lanczos method for computing eigenpairs of standard symmetric eigenproblems. Monotone quadratic convergence of the basic method is proved. Test examples are presented

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

Science.gov (United States)

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

2015-01-30

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

Clinicopathological correlation of keratinocyte growth factor and matrix metalloproteinase-9 expression in human gastric cancer.

Science.gov (United States)

Zhang, Qing; Wang, Ping; Shao, Ming; Chen, Shi-Wen; Xu, Zhi-Feng; Xu, Feng; Yang, Zhong-Yin; Liu, Bing-Ya; Gu, Qin-Long; Zhang, Wen-Jian; Li, Yong

2015-01-01

Keratinocyte growth factor (KGF) is reported to be implicated in the growth of some cancer cells. Matrix metalloproteinase 9 (MMP-9) is thought to enhance the tumor invasion and metastasis ability. This study was aimed at analyzing the relationship between KGF and MMP-9 expression and patients' clinicopathological characteristics to clarify the clinical significance of the expression of KGF and MMP-9 in gastric cancer. Tissue samples from 161 patients with primary gastric cancer were investigated using immunohistochemistry. The relationship between KGF and/or MMP-9 expression and clinicopathological characteristics was analyzed. KGF expression and MMP-9 expression in gastric cancer tissue were observed in 62 cases (38.5%) and 97 cases (60.2%), respectively. MMP-9 was significantly associated with depth of invasion, lymph node metastasis and TNM stage. The prognosis of MMP-9-positive patients was significantly poorer than that of MMP-9-negative patients (p = 0.009). KGF expression was positively correlated with MMP-9 expression in gastric cancer, and the prognosis of patients with both KGF- and MMP-9-positive tumors was significantly worse than that of patients with negative tumors for either factor (p = 0.045). Expression of MMP-9 was revealed to be an independent prognostic factor (p = 0.026). Coexpression of KGF and MMP-9 in gastric cancer could be a useful prognostic factor, and MMP-9 might also serve as a novel target for both prognostic prediction and therapeutics.

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

Science.gov (United States)

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

2014-01-01

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

Experimental comparison between total calibration factors and components calibration factors of reference dosemeters used in secondary standard laboratory dosemeters

International Nuclear Information System (INIS)

Silva, T.A. da.

1981-06-01

A quantitative comparison of component calibration factors with the corresponding overall calibration factor was used to evaluate the adopted component calibration procedure in regard to parasitic elements. Judgement of significance is based upon the experimental uncertainty of a well established procedure for determination of the overall calibration factor. The experimental results obtained for different ionization chambers and different electrometers demonstrate that for one type of electrometer the parasitic elements have no influence on its sensitivity considering the experimental uncertainty of the calibration procedures. In this case the adopted procedure for determination of component calibration factors is considered to be equivalent to the procedure of determination of the overall calibration factor and thus might be used as a strong quality control measure in routine calibration. (Author) [pt

Google matrix and Ulam networks of intermittency maps.

Science.gov (United States)

Ermann, L; Shepelyansky, D L

2010-03-01

We study the properties of the Google matrix of an Ulam network generated by intermittency maps. This network is created by the Ulam method which gives a matrix approximant for the Perron-Frobenius operator of dynamical map. The spectral properties of eigenvalues and eigenvectors of this matrix are analyzed. We show that the PageRank of the system is characterized by a power law decay with the exponent beta dependent on map parameters and the Google damping factor alpha . Under certain conditions the PageRank is completely delocalized so that the Google search in such a situation becomes inefficient.

Closed-Form Expressions for the Matrix Exponential

Directory of Open Access Journals (Sweden)

F. De Zela

2014-04-01

Full Text Available We discuss a method to obtain closed-form expressions of f(A, where f is an analytic function and A a square, diagonalizable matrix. The method exploits the Cayley–Hamilton theorem and has been previously reported using tools that are perhaps not sufficiently appealing to physicists. Here, we derive the results on which the method is based by using tools most commonly employed by physicists. We show the advantages of the method in comparison with standard approaches, especially when dealing with the exponential of low-dimensional matrices. In contrast to other approaches that require, e.g., solving differential equations, the present method only requires the construction of the inverse of the Vandermonde matrix. We show the advantages of the method by applying it to different cases, mostly restricting the calculational effort to the handling of two-by-two matrices.

Matrix form of Legendre polynomials for solving linear integro-differential equations of high order

Science.gov (United States)

Kammuji, M.; Eshkuvatov, Z. K.; Yunus, Arif A. M.

2017-04-01

This paper presents an effective approximate solution of high order of Fredholm-Volterra integro-differential equations (FVIDEs) with boundary condition. Legendre truncated series is used as a basis functions to estimate the unknown function. Matrix operation of Legendre polynomials is used to transform FVIDEs with boundary conditions into matrix equation of Fredholm-Volterra type. Gauss Legendre quadrature formula and collocation method are applied to transfer the matrix equation into system of linear algebraic equations. The latter equation is solved by Gauss elimination method. The accuracy and validity of this method are discussed by solving two numerical examples and comparisons with wavelet and methods.

Porous structure analysis of radioactive spent resin cementation matrix

International Nuclear Information System (INIS)

Zhou Yaozhong; Yun Guichun

2004-01-01

According to a cement product microstructure, a radioactive spent resin cementation matrix has the properties of porous matters. The distributing of the pore size and the pore microstructure stability are closely related to many crucial macro properties, including strength and permeability of the matrixes. By using a new computer-controlled Hg pressure test, a experiment methods of the matrix micro-properties was studied. By using porous structure analyses, it was found that the experimental method is useful for the future cementation research. In this test, it was also found that ASC cement matrixes of spent resin have superior microstructure to the OPC's. They have better pore size distribution, more stable structure and higher ability to hold the Hg in the matrixes than OPC's, and these properties are the important factors that make ASC cement matrixes have more stable macro-structure and lower leaching of nuclides. (authors)

Mechanical and corrosion behaviors of developed copper-based metal matrix composites

Science.gov (United States)

Singh, Manvandra Kumar; Gautam, Rakesh Kumar; Prakash, Rajiv; Ji, Gopal

2018-03-01

This work investigates mechanical properties and corrosion resistances of cast copper-tungsten carbide (WC) metal matrix composites (MMCs). Copper matrix composites have been developed by stir casting technique. Different sizes of micro and nano particles of WC particles are utilized as reinforcement to prepare two copper-based composites, however, nano size of WC particles are prepared by high-energy ball milling. XRD (X-rays diffraction) characterize the materials for involvement of different phases. The mechanical behavior of composites has been studied by Vickers hardness test and compression test; while the corrosion behavior of developed composites is investigated by electrochemical impedance spectroscopy in 0.5 M H2SO4 solutions. The results show that hardness, compressive strength and corrosion resistance of copper matrix composites are very high in comparison to that of copper matrix, which attributed to the microstructural changes occurred during composite formation. SEM (Scanning electron microscopy) reveals the morphology of the corroded surfaces.

Enhancer of rudimentary homologue interacts with scaffold attachment factor B at the nuclear matrix to regulate SR protein phosphorylation.

Science.gov (United States)

Drakouli, Sotiria; Lyberopoulou, Aggeliki; Papathanassiou, Maria; Mylonis, Ilias; Georgatsou, Eleni

2017-08-01

Scaffold attachment factor B1 (SAFB1) is an integral component of the nuclear matrix of vertebrate cells. It binds to DNA on scaffold/matrix attachment region elements, as well as to RNA and a multitude of different proteins, affecting basic cellular activities such as transcription, splicing and DNA damage repair. In the present study, we show that enhancer of rudimentary homologue (ERH) is a new molecular partner of SAFB1 and its 70% homologous paralogue, scaffold attachment factor B2 (SAFB2). ERH interacts directly in the nucleus with the C-terminal Arg-Gly-rich region of SAFB1/2 and co-localizes with it in the insoluble nuclear fraction. ERH, a small ubiquitous protein with striking homology among species and a unique structure, has also been implicated in fundamental cellular mechanisms. Our functional analyses suggest that the SAFB/ERH interaction does not affect SAFB1/2 function in transcription (e.g. as oestrogen receptor α co-repressors), although it reverses the inhibition exerted by SAFB1/2 on the splicing kinase SR protein kinase 1 (SRPK1), which also binds on the C-terminus of SAFB1/2. Accordingly, ERH silencing decreases lamin B receptor and SR protein phosphorylation, which are major SRPK1 substrates, further substantiating the role of SAFB1 and SAFB2 in the co-ordination of nuclear function. © 2017 Federation of European Biochemical Societies.

Parametric level correlations in random-matrix models

International Nuclear Information System (INIS)

Weidenmueller, Hans A

2005-01-01

We show that parametric level correlations in random-matrix theories are closely related to a breaking of the symmetry between the advanced and the retarded Green functions. The form of the parametric level correlation function is the same as for the disordered case considered earlier by Simons and Altshuler and is given by the graded trace of the commutator of the saddle-point solution with the particular matrix that describes the symmetry breaking in the actual case of interest. The strength factor differs from the case of disorder. It is determined solely by the Goldstone mode. It is essentially given by the number of levels that are strongly mixed as the external parameter changes. The factor can easily be estimated in applications

Monitoring organic loading to swimming pools by fluorescence excitation–emission matrix with parallel factor analysis (PARAFAC)

DEFF Research Database (Denmark)

Seredynska-Sobecka, Bozena; Stedmon, Colin; Boe-Hansen, Rasmus

2011-01-01

Fluorescence Excitation–Emission Matrix spectroscopy combined with parallel factor analysis was employed to monitor water quality and organic contamination in swimming pools. The fluorescence signal of the swimming pool organic matter was low but increased slightly through the day. The analysis...... revealed that the organic matter fluorescence was characterised by five different components, one of which was unique to swimming pool organic matter and one which was specific to organic contamination. The latter component had emission peaks at 420nm and was found to be a sensitive indicator of organic...... loading in swimming pool water. The fluorescence at 420nm gradually increased during opening hours and represented material accumulating through the day....

Quantitative proteomics reveals altered expression of extracellular matrix related proteins of human primary dermal fibroblasts in response to sulfated hyaluronan and collagen applied as artificial extracellular matrix.

Science.gov (United States)

Müller, Stephan A; van der Smissen, Anja; von Feilitzsch, Margarete; Anderegg, Ulf; Kalkhof, Stefan; von Bergen, Martin

2012-12-01

Fibroblasts are the main matrix producing cells of the dermis and are also strongly regulated by their matrix environment which can be used to improve and guide skin wound healing processes. Here, we systematically investigated the molecular effects on primary dermal fibroblasts in response to high-sulfated hyaluronan [HA] (hsHA) by quantitative proteomics. The comparison of non- and high-sulfated HA revealed regulation of 84 of more than 1,200 quantified proteins. Based on gene enrichment we found that sulfation of HA alters extracellular matrix remodeling. The collagen degrading enzymes cathepsin K, matrix metalloproteinases-2 and -14 were found to be down-regulated on hsHA. Additionally protein expression of thrombospondin-1, decorin, collagen types I and XII were reduced, whereas the expression of trophoblast glycoprotein and collagen type VI were slightly increased. This study demonstrates that global proteomics provides a valuable tool for revealing proteins involved in molecular effects of growth substrates for further material optimization.

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

Science.gov (United States)

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

2014-12-01

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

Vascular Canals in Permanent Hyaline Cartilage: Development, Corrosion of Nonmineralized Cartilage Matrix, and Removal of Matrix Degradation Products.

Science.gov (United States)

Gabner, Simone; Häusler, Gabriele; Böck, Peter

2017-06-01

Core areas in voluminous pieces of permanent cartilage are metabolically supplied via vascular canals (VCs). We studied cartilage corrosion and removal of matrix degradation products during the development of VCs in nose and rib cartilage of piglets. Conventional staining methods were used for glycosaminoglycans, immunohistochemistry was performed to demonstrate collagens types I and II, laminin, Ki-67, von Willebrand factor, VEGF, macrophage marker MAC387, S-100 protein, MMPs -2,-9,-13,-14, and their inhibitors TIMP1 and TIMP2. VCs derived from connective tissue buds that bulged into cartilage matrix ("perichondrial papillae", PPs). Matrix was corroded at the tips of PPs or resulting VCs. Connective tissue stromata in PPs and VCs comprised an axial afferent blood vessel, peripherally located wide capillaries, fibroblasts, newly synthesized matrix, and residues of corroded cartilage matrix (collagen type II, acidic proteoglycans). Multinucleated chondroclasts were absent, and monocytes/macrophages were not seen outside the blood vessels. Vanishing acidity characterized areas of extracellular matrix degradation ("preresorptive layers"), from where the dismantled matrix components diffused out. Leached-out material stained in an identical manner to intact cartilage matrix. It was detected in the stroma and inside capillaries and associated downstream veins. We conclude that the delicate VCs are excavated by endothelial sprouts and fibroblasts, whilst chondroclasts are specialized to remove high volumes of mineralized cartilage. VCs leading into permanent cartilage can be formed by corrosion or inclusion, but most VCs comprise segments that have developed in either of these ways. Anat Rec, 300:1067-1082, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Regulation of matrix metalloproteinase-9 expression between gingival fibroblast cells from old and young rats

International Nuclear Information System (INIS)

Kim, Su-Jung; Chung, Yong-Koo; Chung, Tae-Wook; Kim, Jeong-Ran; Moon, Sung-Kwon; Kim, Cheorl-Ho; Park, Young-Guk

2009-01-01

Gingival fibroblast cells (rGF) from aged rats have an age-related decline in proliferative capacity compared with young rats. We investigated G1 phase cell cycle regulation and MMP-9 expression in both young and aged rGF. G1 cell cycle protein levels and activity were significantly reduced in response to interleukin-1β (IL-1β) stimulation with increasing in vitro age. Tumor necrosis factor-α (TNF-α)-induced matrix metalloproteinase-9 (MMP-9) expression was also decreased in aged rGF in comparison with young rGF. Mutational analysis and gel shift assays demonstrated that the lower MMP-9 expression in aged rGF is associated with lower activities of transcription factors NF-κB and AP-1. These results suggest that cell cycle dysregulation and down-regulation of MMP-9 expression in rGF may play a role in gingival remodeling during in vitro aging.

Periodontal Disease, Matrix Metalloproteinases and Chemically Modified Tetracyclines

OpenAIRE

Steinsvoll, Svein

2011-01-01

Matrix metalloproteinases (MMPs) are crucial in the degradation of the main components in the extracellular matrix and thereby play important roles in cell migration, wound healing and tissue remodelling. MMPs have pathogenic roles in arthritis, periodontitis, hepatitis, glomerulonephritis, atherosclerosis and cancer cell invasion. MMPs are activators of pro-inflammatory mediators that occur in latent forms, such as interleukin (IL)-1β, membrane-bound tumour necrosis factor (TNF) and dif...

Convex Banding of the Covariance Matrix.

Science.gov (United States)

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

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

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.

On Best Approximations of Polynomials in Matrices in the Matrix 2-Norm

Czech Academy of Sciences Publication Activity Database

Liesen, J.; Tichý, Petr

2009-01-01

Roč. 31, č. 2 (2009), s. 853-863 ISSN 0895-4798 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : matrix approximation problems * polynomials in matrices * matrix functions * matrix 2-norm * GMRES * Arnoldi's method Subject RIV: BA - General Mathematics Impact factor: 2.411, year: 2009

Adhesion properties of Lactobacillus rhamnosus mucus-binding factor to mucin and extracellular matrix proteins.

Science.gov (United States)

Nishiyama, Keita; Nakamata, Koichi; Ueno, Shintaro; Terao, Akari; Aryantini, Ni Putu Desy; Sujaya, I Nengah; Fukuda, Kenji; Urashima, Tadasu; Yamamoto, Yuji; Mukai, Takao

2015-01-01

We previously described potential probiotic Lactobacillus rhamnosus strains, isolated from fermented mare milk produced in Sumbawa Island, Indonesia, which showed high adhesion to porcine colonic mucin (PCM) and extracellular matrix (ECM) proteins. Recently, mucus-binding factor (MBF) was found in the GG strain of L. rhamnosus as a mucin-binding protein. In this study, we assessed the ability of recombinant MBF protein from the FSMM22 strain, one of the isolates of L. rhamnosus from fermented Sumbawa mare milk, to adhere to PCM and ECM proteins by overlay dot blot and Biacore assays. MBF bound to PCM, laminin, collagen IV, and fibronectin with submicromolar dissociation constants. Adhesion of the FSMM22 mbf mutant strain to PCM and ECM proteins was significantly less than that of the wild-type strain. Collectively, these results suggested that MBF contribute to L. rhamnosus host colonization via mucin and ECM protein binding.

High performance matrix inversion based on LU factorization for multicore architectures

KAUST Repository

Dongarra, Jack; Faverge, Mathieu; Ltaief, Hatem; Luszczek, Piotr R.

2011-01-01

on the available processing units. The reported results from our LU-based matrix inversion implementation significantly outperform the state-of-the-art numerical libraries such as LAPACK (5x), MKL (5x) and ScaLAPACK (2.5x) on a contemporary AMD platform with four

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.)

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.)

Matrix effect on paralytic shellfish toxins quantification and toxicity estimation in mussels exposed to Gymnodinium catenatum.

Science.gov (United States)

Botelho, M J; Vale, C; Mota, A M; Rodrigues, S M; Costa, P R; Simões Gonçalves, M L S

2010-12-01

Paralytic shellfish toxins were quantified in whole tissues of the mussel Mytilus galloprovincialis exposed to blooms of the dinoflagellate Gymnodinium catenatum in Portuguese coastal waters. A validated liquid chromatography method with fluorescence detection, involving pre-chromatographic oxidation was used to quantify carbamoyl, N-sulfocarbamoyl and decarbamoyl toxins. In order to test for any matrix effect in the quantification of those toxins, concentrations obtained from solvent and matrix matched calibration curves were compared. A suppression of the fluorescence signal was observed in mussel extract or fraction in comparison to solvent for the compounds dcGTX2 + 3, GTX2 + 3 and GTX1 + 4, while an enhancement was found for C1 + 2, dcSTX, STX, B1, dcNEO and NEO. These results showed that a matrix effect varies among compounds. The difference of concentrations between solvent and matrix matched calibration curves for C1 + 2 (median = 421 ng g⁻¹) exceeded largely the values for the other quantified compounds (0.09-58 ng g⁻¹). Those differences were converted into toxicity differences, using Oshima toxicity equivalence factors. The compounds C1 + 2 and dcNEO were the major contributors to the differences of total toxicity in the mussel samples. The differences of total toxicity were calculated in ten mussel samples collected during a 10-week blooming period in Portuguese coastal lagoon. Values varied between 53 and 218 µg STX equivalents kg⁻¹. The positive differences mean that the estimated toxicity using solvent calibration curves exceed the values taking into account the matrix. For the toxicity interval 200-800 µg STX equivalents kg⁻¹ an increase was found between 44 and 28%.

Comprehensive profiling and localisation of the matrix metalloproteinases in urothelial carcinoma

OpenAIRE

Wallard, M J; Pennington, C J; Veerakumarasivam, A; Burtt, G; Mills, I G; Warren, A; Leung, H Y; Murphy, G; Edwards, D R; Neal, D E; Kelly, J D

2006-01-01

The matrix metalloproteinases (MMPs) are endopeptidases which break down the extracellular matrix and regulate cytokine and growth factor activity. Several MMPs have been implicated in the promotion of invasion and metastasis in a broad range of tumours including urothelial carcinoma. In this study, RNA from 132 normal bladder and urothelial carcinoma specimens was profiled for each of the 24 human MMPs, the four endogenous tissue inhibitors of MMPs (TIMPs) and several key growth factors and ...

Non-Abelian integrable hierarchies: matrix biorthogonal polynomials and perturbations

Science.gov (United States)

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

2018-05-01

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

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.

Tumor necrosis factor-α-accelerated degradation of type I collagen in human skin is associated with elevated matrix metalloproteinase (MMP)-1 and MMP-3 ex vivo

DEFF Research Database (Denmark)

Ågren, Magnus S; Schnabel, Reinhild; Christensen, Lise H

2015-01-01

Tumor necrosis factor (TNF)-α induces matrix metalloproteinases (MMPs) that may disrupt skin integrity. We have investigated the effects and mechanisms of exogenous TNF-α on collagen degradation by incubating human skin explants in defined serum-free media with or without TNF-α (10ng/ml) in the a......Tumor necrosis factor (TNF)-α induces matrix metalloproteinases (MMPs) that may disrupt skin integrity. We have investigated the effects and mechanisms of exogenous TNF-α on collagen degradation by incubating human skin explants in defined serum-free media with or without TNF-α (10ng...... tissue-derived collagenolytic activity with TNF-α exposure was blocked by neutralizing MMP-1 monoclonal antibody and was not due to down-regulation of tissue inhibitor of metalloproteinase-1. TNF-α increased production (pendogenous MMP-1...

Towards Acid-Tolerated Ethanol Dehydration: Chitosan-Based Mixed Matrix Membranes Containing Cyano-Bridged Coordination Polymer Nanoparticles.

Science.gov (United States)

Wu, C-W; Kang, Chao-Hsiang; Lin, Yi-Feng; Tung, Kuo-Lun; Deng, Yu-Heng; Ahamad, Tansir; Alshehri, Saad M; Suzuki, Norihiro; Yamauchi, Yusuke

2016-04-01

Prussian blue (PB) nanoparticles, one of many cyano-bridged coordination polymers, are successfully incorporated into chitosan (CS) polymer to prepare PB/CS mixed matrix membranes (MMMs). The PB nanoparticles are uniformly distributed in the MMMs without the collapse of the original PB structure. As-prepared PB/CS MMMs are used for ethanol dehydration at 25 °C in the pervaporation process. The effect of loading PB in CS matrix on pervaporation performance is carefully investigated. The PB/CS membrane with 30 wt% PB loading shows the best performance with a permeate flux of 614 g. m-2 . h-1 and a separation factor of 1472. The pervaporation using our PB/CS membranes exhibits outstanding performance in comparison with the previously reported CS-based membranes and MMMs. Furthermore, the addition of PB allows PB/CS MMMs to be tolerant of acidic environment. The present work demonstrates good pervaporation performance of PB/CS MMMs for the separation of an ethanol/water (90:10 in wt%) solution. Our new system provides an opportunity for dehydration of bioethanol in the future.

The Lehmer Matrix and Its Recursive Analogue

Science.gov (United States)

2010-01-01

LU factorization of matrix A by considering det A = det U = ∏n i=1 2i−1 i2 . The nth Catalan number is given in terms of binomial coefficients by Cn...for failing to comply with a collection of information if it does not display a currently valid OMB control number . 1. REPORT DATE 2010 2. REPORT...TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE The Lehmer matrix and its recursive analogue 5a. CONTRACT NUMBER 5b

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

Science.gov (United States)

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

2011-07-01

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

Comparison of Material Behavior of Matrix Graphite for HTGR Fuel Elements upon Irradiation: A literature Survey

Energy Technology Data Exchange (ETDEWEB)

Lee, Young-Woo; Yeo, Seunghwan; Cho, Moon Sung [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

The fuel elements for the HTGRs (i.e., spherical fuel element in pebble-bed type core design and fuel compact in prismatic core design) consists of coated fuel particles dispersed and bonded in a closely packed array within a carbonaceous matrix. This matrix is generally made by mixing fully graphitized natural and needle- or pitchcoke originated powders admixed with a binder material (pitch or phenolic resin), The resulting resinated graphite powder mixture, when compacted, may influence a number of material properties as well as its behavior under neutron irradiation during reactor operation. In the fabrication routes of these two different fuel element forms, different consolidation methods are employed; a quasi-isostatic pressing method is generally adopted to make pebbles while fuel compacts are fabricated by uni-axial pressing mode. The result showed that the hardness values obtained from the two directions showed an anisotropic behavior: The values obtained from the perpendicular section showed much higher micro hardness (176.6±10.5MPa in average) than from the parallel section ((125.6±MPa in average). This anisotropic behavior was concluded to be related to the microstructure of the matrix graphite. This may imply that the uni-axial pressing method to make compacts influence the microstructure of the matrix and hence the material properties of the matrix graphite.

Coherent scattering and matrix correction in bone-lead measurements

International Nuclear Information System (INIS)

Todd, A.C.

2000-01-01

The technique of K-shell x-ray fluorescence of lead in bone has been used in many studies of the health effects of lead. This paper addresses one aspect of the technique, namely the coherent conversion factor (CCF) which converts between the matrix of the calibration standards and those of human bone. The CCF is conventionally considered a constant but is a function of scattering angle, energy and the elemental composition of the matrices. The aims of this study were to quantify the effect on the CCF of several assumptions which may not have been tested adequately and to compare the CCFs for plaster of Paris (the present matrix of calibration standards) and a synthetic apatite matrix. The CCF was calculated, using relativistic form factors, for published compositions of bone, both assumed and assessed compositions of plaster, and the synthetic apatite. The main findings of the study were, first, that impurities in plaster, lead in the plaster or bone matrices, coherent scatter from non-bone tissues and the individual subject's measurement geometry are all minor or negligible effects; and, second, that the synthetic apatite matrix is more representative of bone mineral than is plaster of Paris. (author)

Matrix metalloproteinase-2 is a consistent prognostic factor in gastric cancer

NARCIS (Netherlands)

Kubben, F.J.G.M.; Sier, C.F.M.; Duijn, W. van; Griffioen, G.; Hanemaaijer, R.; Velde, C.J.H. van de; Krieken, J.H.J.M. van; Lamers, C.B.H.W.; Verspaget, H.W.

2006-01-01

In a pioneer study, we showed 10 years ago that enhanced tissue levels of the matrix metalloproteinases (MMPs) MMP-2 and MMP-9 in gastric cancers, as determined by zymography, were related with worse overall survival of the patients. To corroborate these observations, we now assessed MMP-2 and MMP-9

Matrix metalloproteinase-2 is a consistent prognostic factor in gastric cancer.

NARCIS (Netherlands)

Kubben, F.J.G.M.; Sier, C.F.M.; Duijn, W. van; Griffioen, G.; Hanemaaijer, R.; Velde, C.J. van de; Krieken, J.H.J.M. van; Lamers, C.B.H.W.; Verspaget, H.W.

2006-01-01

In a pioneer study, we showed 10 years ago that enhanced tissue levels of the matrix metalloproteinases (MMPs) MMP-2 and MMP-9 in gastric cancers, as determined by zymography, were related with worse overall survival of the patients. To corroborate these observations, we now assessed MMP-2 and MMP-9

On the validity of cosmological Fisher matrix forecasts

International Nuclear Information System (INIS)

Wolz, Laura; Kilbinger, Martin; Weller, Jochen; Giannantonio, Tommaso

2012-01-01

We present a comparison of Fisher matrix forecasts for cosmological probes with Monte Carlo Markov Chain (MCMC) posterior likelihood estimation methods. We analyse the performance of future Dark Energy Task Force (DETF) stage-III and stage-IV dark-energy surveys using supernovae, baryon acoustic oscillations and weak lensing as probes. We concentrate in particular on the dark-energy equation of state parameters w 0 and w a . For purely geometrical probes, and especially when marginalising over w a , we find considerable disagreement between the two methods, since in this case the Fisher matrix can not reproduce the highly non-elliptical shape of the likelihood function. More quantitatively, the Fisher method underestimates the marginalized errors for purely geometrical probes between 30%-70%. For cases including structure formation such as weak lensing, we find that the posterior probability contours from the Fisher matrix estimation are in good agreement with the MCMC contours and the forecasted errors only changing on the 5% level. We then explore non-linear transformations resulting in physically-motivated parameters and investigate whether these parameterisations exhibit a Gaussian behaviour. We conclude that for the purely geometrical probes and, more generally, in cases where it is not known whether the likelihood is close to Gaussian, the Fisher matrix is not the appropriate tool to produce reliable forecasts

Strange mesonic transition form factor

International Nuclear Information System (INIS)

Goity, J.L.; Musolf, M.J.

1996-01-01

The strange-quark vector current ρ-to-π meson transition form factor is computed at one-loop order using strange meson intermediate states. A comparison is made with a φ-meson dominance model estimate. We find that one-loop contributions are comparable in magnitude to those predicted by φ-meson dominance. It is possible that the one-loop contribution can make the matrix element as large as those of the electromagnetic current mediating vector meson radiative decays. However, due to the quadratic dependence of the one-loop results on the hadronic form factor cutoff mass, a large uncertainty in the estimate of the loops is unavoidable. These results indicate that non-nucleonic strange quarks could contribute appreciable in moderate-parallel Q 2 parallel parity-violating electron-nucleus scattering measurements aimed at probing the strange-quark content of the nucleon. copyright 1996 The American Physical Society

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

Science.gov (United States)

Bi, Yuying; Patra, Prabir; Faezipour, Miad

2014-01-01

Glycosaminoglycan (GAG) is a chain-like disaccharide that is linked to polypeptide core to connect two collagen fibrils/fibers and provide the intermolecular force in Collagen-GAG matrix (C-G matrix). Thus, the distribution of GAG in C-G matrix contributes to the integrity and mechanical properties of the matrix and related tissue. This paper analyzes the transverse isotropic distribution of GAG in C-G matrix. The angle of GAGs related to collagen fibrils is used as parameters to qualify the GAGs isotropic characteristic in both 3D and 2D rendering. Statistical results included that over one third of GAGs were perpendicular directed to collagen fibril with symmetrical distribution for both 3D matrix and 2D plane cross through collagen fibrils. The three factors tested in this paper: collagen radius, collagen distribution, and GAGs density, were not statistically significant for the strength of Collagen-GAG matrix in 3D rendering. However in 2D rendering, a significant factor found was the radius of collagen in matrix for the GAGs directed to orthogonal plane of Collagen-GAG matrix. Between two cross-section selected from Collagen-GAG matrix model, the plane cross through collagen fibrils was symmetrically distributed but the total percentage of perpendicular directed GAG was deducted by decreasing collagen radius. There were some symmetry features of GAGs angle distribution in selected 2D plane that passed through space between collagen fibrils, but most models showed multiple peaks in GAGs angle distribution. With less GAGs directed to perpendicular of collagen fibril, strength in collagen cross-section weakened. Collagen distribution was also a factor that influences GAGs angle distribution in 2D rendering. True hexagonal collagen packaging is reported in this paper to have less strength at collagen cross-section compared to quasi-hexagonal collagen arrangement. In this work focus is on GAGs matrix within the collagen and its relevance to anisotropy.

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

Science.gov (United States)

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

2010-01-01

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

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

Rigorous constraints on the matrix elements of the energy–momentum tensor

Directory of Open Access Journals (Sweden)

Peter Lowdon

2017-11-01

Full Text Available The structure of the matrix elements of the energy–momentum tensor play an important role in determining the properties of the form factors A(q2, B(q2 and C(q2 which appear in the Lorentz covariant decomposition of the matrix elements. In this paper we apply a rigorous frame-independent distributional-matching approach to the matrix elements of the Poincaré generators in order to derive constraints on these form factors as q→0. In contrast to the literature, we explicitly demonstrate that the vanishing of the anomalous gravitomagnetic moment B(0 and the condition A(0=1 are independent of one another, and that these constraints are not related to the specific properties or conservation of the individual Poincaré generators themselves, but are in fact a consequence of the physical on-shell requirement of the states in the matrix elements and the manner in which these states transform under Poincaré transformations.

Functionalized carbon nanotubes mixed matrix membranes of polymers of intrinsic microporosity for gas separation.

Science.gov (United States)

Khan, Muntazim Munir; Filiz, Volkan; Bengtson, Gisela; Shishatskiy, Sergey; Rahman, Mushfequr; Abetz, Volker

2012-09-06

The present work reports on the gas transport behavior of mixed matrix membranes (MMM) which were prepared from multi-walled carbon nanotubes (MWCNTs) and dispersed within polymers of intrinsic microporosity (PIM-1) matrix. The MWCNTs were chemically functionalized with poly(ethylene glycol) (PEG) for a better dispersion in the polymer matrix. MMM-incorporating functionalized MWCNTs (f-MWCNTs) were fabricated by dip-coating method using microporous polyacrylonitrile membrane as a support and were characterized for gas separation performance. Gas permeation measurements show that MMM incorporated with pristine or functionalized MWCNTs exhibited improved gas separation performance compared to pure PIM-1. The f-MWCNTs MMM show better performance in terms of permeance and selectivity in comparison to pristine MWCNTs. The gas permeances of the derived MMM are increased to approximately 50% without sacrificing the selectivity at 2 wt.% of f-MWCNTs' loading. The PEG groups on the MWCNTs have strong interaction with CO2 which increases the solubility of polar gas and limit the solubility of nonpolar gas, which is advantageous for CO2/N2 selectivity. The addition of f-MWCNTs inside the polymer matrix also improved the long-term gas transport stability of MMM in comparison with PIM-1. The high permeance, selectivity, and long term stability of the fabricated MMM suggest that the reported approach can be utilized in practical gas separation technology.

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

Science.gov (United States)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Cartilage extracellular matrix as a biomaterial for cartilage regeneration.

Science.gov (United States)

Kiyotake, Emi A; Beck, Emily C; Detamore, Michael S

2016-11-01

The extracellular matrix (ECM) of various tissues possesses the model characteristics that biomaterials for tissue engineering strive to mimic; however, owing to the intricate hierarchical nature of the ECM, it has yet to be fully characterized and synthetically fabricated. Cartilage repair remains a challenge because the intrinsic properties that enable its durability and long-lasting function also impede regeneration. In the last decade, cartilage ECM has emerged as a promising biomaterial for regenerating cartilage, partly because of its potentially chondroinductive nature. As this research area of cartilage matrix-based biomaterials emerged, investigators facing similar challenges consequently developed convergent solutions in constructing robust and bioactive scaffolds. This review discusses the challenges, emerging trends, and future directions of cartilage ECM scaffolds, including a comparison between two different forms of cartilage matrix: decellularized cartilage (DCC) and devitalized cartilage (DVC). To overcome the low permeability of cartilage matrix, physical fragmentation greatly enhances decellularization, although the process itself may reduce the chondroinductivity of fabricated scaffolds. The less complex processing of a scaffold composed of DVC, which has not been decellularized, appears to have translational advantages and potential chondroinductive and mechanical advantages over DCC, without detrimental immunogenicity, to ultimately enhance cartilage repair in a clinically relevant way. © 2016 New York Academy of Sciences.

Charge form factors and alpha-cluster internal structure of 12C

International Nuclear Information System (INIS)

Luk'yanov, V.K.; Zemlyanaya, E.V.; Kadrev, D.N.; Antonov, A.N.; Spasova, K.; Anagnostatos, G.S.; Ginis, P.; Giapitzakis, J.

1999-01-01

The transition densities and form factors of 0 + , 2 + , and 3 - states in 12 C are calculated in alpha-cluster model using the triangle frame with clusters in the vertices. The wave functions of nucleons in the alpha clusters are taken as they were obtained in the framework of the models used for the description of the 4 He form factor and momentum distribution which are based on the one-body density matrix construction. They contain effects of the short-range NN correlations, as well as the d-shell admixtures in 4 He. Calculations and the comparison with the experimental data show that visible effects on the form and magnitude of the 12 C form factors take place, especially at relatively large momentum transfers

Hydraulic conductivities of fractures and matrix in Slovenian carbonate aquifers

Directory of Open Access Journals (Sweden)

Timotej Verbovšek

2008-12-01

Full Text Available Hydraulic conductivities and specific storage coefficients of fractures and matrix in Slovenian carbonate aquifers were determined by Barker’s method for pumping test analysis, based on fractional flow dimension. Values are presented for limestones and mainly for dolomites, and additionally for separate aquifers, divided by age andlithology in several groups. Data was obtained from hydrogeological reports for 397 water wells, and among these, 79 pumping tests were reinterpreted. Hydraulic conductivities of fractures are higher than the hydraulic conductivities of matrix, and the differences are highly statistically significant. Likewise, differences are significant for specific storage, and the values of these coefficients are higher in the matrix. Values of all coefficients vary in separate aquifers, and the differences can be explained by diagenetic effects, crystal size, degree of fracturing, andcarbonate purity. Comparison of the methods, used in the reports, and the Barker’s method (being more suitable for karstic and fractured aquifers, shows that the latter fits real data better.

Arabian, Asian, western: a cross-cultural comparison of aircraft accidents from human factor perspectives.

Science.gov (United States)

Al-Wardi, Yousuf

2017-09-01

Rates of aviation accident differ in different regions; and national culture has been implicated as a factor. This invites a discussion about the role of national culture in aviation accidents. This study makes a cross-cultural comparison between Oman, Taiwan and the USA. A cross-cultural comparison was acquired using data from three studies, including this study, by applying the Human Factors Analysis and Classification System (HFACS) framework. The Taiwan study presented 523 mishaps with 1762 occurrences of human error obtained from the Republic of China Air Force. The study from the USA carried out for commercial aviation had 119 accidents with 245 instances of human error. This study carried out in Oman had a total of 40 aircraft accidents with 129 incidences. Variations were found between Oman, Taiwan and the USA at the levels of organisational influence and unsafe supervision. Seven HFACS categories showed significant differences between the three countries (p culture can have an impact on aviation safety. This study revealed that national culture plays a role in aircraft accidents related to human factors that cannot be disregarded.

Evaluating the Effectiveness of Cryopreserved Acellular Dermal Matrix in Immediate Expander-Based Breast Reconstruction: A Comparison Study

Directory of Open Access Journals (Sweden)

So-Young Kim

2015-05-01

Full Text Available BackgroundCGCryoDerm was first introduced in 2010 and offers a different matrix preservation processes for freezing without drying preparation. From a theoretical perspective, CGCryoDerm has a more preserved dermal structure and more abundant growth factors for angiogenesis and recellularization. In the current study, the authors performed a retrospective study to evaluate freezing- and freeze-drying-processed acellular dermal matrix (ADM to determine whether any differences were present in an early complication profile.MethodsPatients who underwent ADM-assisted tissue expander placement for two stage breast reconstruction between January of 2013 and March of 2014 were retrospectively reviewed and divided into two groups based on the types of ADM-assisted expander reconstruction (CGDerm vs. CGCryoDerm. Complications were divided into four main categories and recorded as follows: seroma, hematoma, infection, and mastectomy skin flap necrosis.ResultsIn a total of 82 consecutive patients, the CGCryoDerm group had lower rates of seroma when compared to the CGDerm group without statistical significance (3.0% vs. 10.2%, P=0.221, respectively. Other complications were similar in both groups. Reconstructions with CGCryoDerm were found to have a significantly longer period of drainage when compared to reconstructions with CGDerm (11.91 days vs. 10.41 days, P=0.043.ConclusionsPreliminary findings indicate no significant differences in early complications between implant/expander-based reconstructions using CGCryoderm and those using CGDerm.

An algorithm for mass matrix calculation of internally constrained molecular geometries

International Nuclear Information System (INIS)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-01

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model

An algorithm for mass matrix calculation of internally constrained molecular geometries.

Science.gov (United States)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-28

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

Legendre Wavelet Operational Matrix Method for Solution of Riccati Differential Equation

Directory of Open Access Journals (Sweden)

S. Balaji

2014-01-01

Full Text Available A Legendre wavelet operational matrix method (LWM is presented for the solution of nonlinear fractional-order Riccati differential equations, having variety of applications in quantum chemistry and quantum mechanics. The fractional-order Riccati differential equations converted into a system of algebraic equations using Legendre wavelet operational matrix. Solutions given by the proposed scheme are more accurate and reliable and they are compared with recently developed numerical, analytical, and stochastic approaches. Comparison shows that the proposed LWM approach has a greater performance and less computational effort for getting accurate solutions. Further existence and uniqueness of the proposed problem are given and moreover the condition of convergence is verified.

A Matrix Splitting Method for Composite Function Minimization

KAUST Repository

Yuan, Ganzhao

2016-12-07

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

A Matrix Splitting Method for Composite Function Minimization

KAUST Repository

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

2016-01-01

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

Rules for matrix element evaluations in JWKB approximation

International Nuclear Information System (INIS)

Giler, S.

1990-01-01

Using the properties of the so-called fundamental solutions to the one-dimensional Schroedinger equation having Froeman and Froeman form the rules are formulated which allow one to evaluate matrix elements in the JWKB approximation and its generalizations. The rules apply to operators M(x, d/dx), M being polynomial functions of their arguments. The applicability of the rules depends on the properties of the so-called canonical indices introduced in this paper. The canonical indices are global characteristics of underlying Stokes graphs. If sufficiently small in comparison with unity they allow one to apply safely the JWKB approximation within the so-called ε-reduced canonical domains of a given Stokes graph. The Oth canonical index for the nth energy level Stokes graph corresponding to the harmonic oscillator potential is found to be ε CAN = 0.678/(2n+1). If the application of the rules is allowed then approximated matrix elements are obtained in an unambiguous way and with an accuracy controlled by corresponding canonical indices. Several examples of matrix elements are considered to illustrate how the rules should be used. Limitations to the rules are also discussed with the aid of suitably chosen examples. (author)

Matrix albedo for discrete ordinates infinite-medium boundary condition

International Nuclear Information System (INIS)

Mathews, K.; Dishaw, J.

2007-01-01

Discrete ordinates problems with an infinite exterior medium (reflector) can be more efficiently computed by eliminating grid cells in the exterior medium and applying a matrix albedo boundary condition. The albedo matrix is a discretized bidirectional reflection distribution function (BRDF) that accounts for the angular quadrature set, spatial quadrature method, and spatial grid that would have been used to model a portion of the exterior medium. The method is exact in slab geometry, and could be used as an approximation in multiple dimensions or curvilinear coordinates. We present an adequate method for computing albedo matrices and demonstrate their use in verifying a discrete ordinates code in slab geometry by comparison with Ganapol's infinite medium semi-analytic TIEL benchmark. With sufficient resolution in the spatial and angular grids and iteration tolerance to yield solutions converged to 6 digits, the conventional (scalar) albedo boundary condition yielded 2-digit accuracy at the boundary, but the matrix albedo solution reproduced the benchmark scalar flux at the boundary to all 6 digits. (authors)

Minimization of the effect of errors in approximate radiation view factors

International Nuclear Information System (INIS)

Clarksean, R.; Solbrig, C.

1993-01-01

The maximum temperature of irradiated fuel rods in storage containers was investigated taking credit only for radiation heat transfer. Estimating view factors is often easy but in many references the emphasis is placed on calculating the quadruple integrals exactly. Selecting different view factors in the view factor matrix as independent, yield somewhat different view factor matrices. In this study ten to twenty percent error in view factors produced small errors in the temperature which are well within the uncertainty due to the surface emissivities uncertainty. However, the enclosure and reciprocity principles must be strictly observed or large errors in the temperatures and wall heat flux were observed (up to a factor of 3). More than just being an aid for calculating the dependent view factors, satisfying these principles, particularly reciprocity, is more important than the calculation accuracy of the view factors. Comparison to experiment showed that the result of the radiation calculation was definitely conservative as desired in spite of the approximations to the view factors

Efficient Matrix Models for Relational Learning

Science.gov (United States)

2009-10-01

base learners and h1:r is the ensemble learner. For example, consider the case where h1, . . . , hr are linear discriminants. The weighted vote of...a multilinear form naturally leads one to consider tensor factorization: e.g., UAV T is a special case of Tucker decomposition [129] on a 2D- tensor , a...matrix. Our five modeling choices can also be used to differentiate tensor factorizations, but the choices may be subtler for tensors than for

Novel matrix for REEs recovery from waste disposal

International Nuclear Information System (INIS)

Hareendran, K.; Singha, Mousumi; Roy, S.B.; Pal, Sangita

2014-01-01

Sorption of lanthanides (98%-99%) onto a novel matrix (polyacrylamide-carboxylate hydroxamate-PAMCHO) not only remove REE's before effluent disposal but also reduces the chance of contamination of potable water, nuclear plant generated shut down or gadolinium containing effluent during controlled fission reaction, in pharmaceutical diagnosis (MRI) and many other useful process effluents. By using such sorbent, 88% of the lanthanides can be recovered using HCl solution less than pH 1 from the laden matrix and can be concentrated more than 5 times. However, sorption into the interlayer's and diffusion of the REE's during leaching depends on the cross-linked structure of the gel matrix and tortuous path of the porous micro-channel (using scanning electron microscope-SEM study). The sequestration of matrix with REE's has been well established by using instrument FT-IR and gadolinium (cation-lanthanide) exchange method. To understand interaction of REE with sorbent, matrix have been prepared with cross-linking amount variation, such as 85:15, 90:10, 95:05 and 98:02 (matrix: cross-linker). A detailed sorption study of cross-linked matrix with gadolinium in feed solution (184 ppm), filtrate, leached and laden sorbent establishes mass balance (using ICP-AES for quantitative determination). This optimized sorbent (PAMCHO) indicates recovery of valuable REEs with elution factor of more than 0.9 when HCl solution of pH1.5 was used. (author)

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.

HPLC-MS/MS method optimisation for matrix metalloproteinase 3 and matrix metalloproteinase 9 determination in human blood serum using target analysis.

Science.gov (United States)

Kotnik, Petra; Krajnc, Metka Koren; Pahor, Artur; Finšgar, Matjaž; Knez, Željko

2018-02-20

A quantitative analysis of zinc endopeptidases matrix metalloproteinase 9 (MMP9) and matrix metalloproteinase 3 (MMP3) from human blood serum are presented. Both matrix metalloproteinases (MMP) are present in human blood serum and can be used as biomarkers for different diseases. The analysis was performed using LC-MS/MS with a triple quadrupole mass spectrometer, based on two specific peptides of each MMP in comparison with an enzyme-linked immunosorbent assay (ELISA). While the conditions for the LC-MS/MS analysis of MMP9 peptides were previously reported for bronchoalveolar lavage fluid, the analysis of MMP3 peptides was newly quantified for human blood serum herein for the first time. For MMP3, the linear behaviour was determined in the concentration range from 1.0-200.0ng/mL (R 2 =0.997) with an LLOD of 0.5ng/mL. For MMP9, linearity was determined in the concentration range from 6.5-65.0ng/mL (R 2 =0.995) with an LLOD of 2.0ng/mL. Copyright © 2017 Elsevier B.V. All rights reserved.

Complete S-matrix of the O(2N) Gross-Neveu model

International Nuclear Information System (INIS)

Karowski, M.; Thun, H.J.

1980-11-01

We present the complete S-matrix of the O(2N) Gross-Neveu model including kinks, elementary fermions, and higher bound states. In addition to the S-matrix factorization, unitarity, and crossing conditions we make essential use of constraints which follow from the fact that particles in the spectrum are bound states of each other. A consistent solution can only be obtained if the kinks obey generalized statistics. Remarkably, some quantities related to this such as 'spins' and Klein factors show Bott periodicity. (orig.)

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.

A comparison of likelihood ratio tests and Rao's score test for three separable covariance matrix structures.

Science.gov (United States)

Filipiak, Katarzyna; Klein, Daniel; Roy, Anuradha

2017-01-01

The problem of testing the separability of a covariance matrix against an unstructured variance-covariance matrix is studied in the context of multivariate repeated measures data using Rao's score test (RST). The RST statistic is developed with the first component of the separable structure as a first-order autoregressive (AR(1)) correlation matrix or an unstructured (UN) covariance matrix under the assumption of multivariate normality. It is shown that the distribution of the RST statistic under the null hypothesis of any separability does not depend on the true values of the mean or the unstructured components of the separable structure. A significant advantage of the RST is that it can be performed for small samples, even smaller than the dimension of the data, where the likelihood ratio test (LRT) cannot be used, and it outperforms the standard LRT in a number of contexts. Monte Carlo simulations are then used to study the comparative behavior of the null distribution of the RST statistic, as well as that of the LRT statistic, in terms of sample size considerations, and for the estimation of the empirical percentiles. Our findings are compared with existing results where the first component of the separable structure is a compound symmetry (CS) correlation matrix. It is also shown by simulations that the empirical null distribution of the RST statistic converges faster than the empirical null distribution of the LRT statistic to the limiting χ 2 distribution. The tests are implemented on a real dataset from medical studies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

User's Manual for PCSMS (Parallel Complex Sparse Matrix Solver). Version 1.

Science.gov (United States)

Reddy, C. J.

2000-01-01

PCSMS (Parallel Complex Sparse Matrix Solver) is a computer code written to make use of the existing real sparse direct solvers to solve complex, sparse matrix linear equations. PCSMS converts complex matrices into real matrices and use real, sparse direct matrix solvers to factor and solve the real matrices. The solution vector is reconverted to complex numbers. Though, this utility is written for Silicon Graphics (SGI) real sparse matrix solution routines, it is general in nature and can be easily modified to work with any real sparse matrix solver. The User's Manual is written to make the user acquainted with the installation and operation of the code. Driver routines are given to aid the users to integrate PCSMS routines in their own codes.

Significance of soluble growth factors in the chondrogenic response of human umbilical cord matrix stem cells in a porous three dimensional scaffold

Directory of Open Access Journals (Sweden)

RS Nirmal

2013-11-01

Full Text Available Stem cell based tissue engineering has emerged as a promising strategy for articular cartilage regeneration. Foetal derived mesenchymal stem cells (MSCs with their ease of availability, pluripotency and high expansion potential have been demonstrated to be an attractive cell source over adult MSCs. However, there is a need for optimisation of chondrogenic signals to direct the differentiation of these multipotent MSCs to chondrogenic lineage. In this study we have demonstrated the in vitro chondrogenesis of human umbilical cord matrix MSCs in three dimensional PVA-PCL (polyvinyl alcohol-polycaprolactone scaffolds in the presence of the individual growth factors TGFβ1, TGFβ3, IGF, BMP2 and their combination with BMP2. Gene expression, histology and immunohistology were evaluated after 28 d culture. The induced cells showed the feature of chondrocytes in their morphology and expression of typical chondrogenic extracellular matrix molecules. Moreover, the real-time PCR assay has shown the expression of gene markers of chondrogenesis, SOX9, collagen type II and aggrecan. The expression of collagen type I and collagen type X was also evaluated. This study has demonstrated the successful chondrogenic induction of human umbilical cord MSCs in 3D scaffolds. Interestingly, the growth factor combination of TGF-β3 and BMP-2 was found to be more effective for chondrogenesis as shown by the real-time PCR studies. The findings of this study suggest the importance of using growth factor combinations for successful chondrogenic differentiation of umbilical cord MSCs.

Stiffness-dependent cellular internalization of matrix-bound BMP-2 and its relation to Smad and non-Smad signaling.

Science.gov (United States)

Gilde, Flora; Fourel, Laure; Guillot, Raphael; Pignot-Paintrand, Isabelle; Okada, Takaharu; Fitzpatrick, Vincent; Boudou, Thomas; Albiges-Rizo, Corinne; Picart, Catherine

2016-12-01

factors by a biomaterial will open new perspectives for regenerative medicine. However, to date, very little is known about how matrix-bound growth factors are delivered to cells, especially whether they are internalized and how they are signaling to drive key differentiation events. These initial steps are crucial as they will guide the subsequent processes leading to tissue regeneration. In this work, we investigate the uptake and processing by cells of BMP-2 ligands embedded in polyelectrolyte multilayer films in comparison to soluble BMP-2. We show that BMP-2 responsive cells can internalize matrix-bound BMP-2 and that internalization is dependent on the cross-linking level of the polyelectrolyte films. In addition, we show that internalization is mediated by both clathrin- and caveolin-dependent pathways. While inhibiting clathrin-dependent endocytosis affects only non-canonical signaling, blocking caveolin-1-dependent endocytosis reduces both canonical and non-canonical BMP signaling. The signaling pathways found for matrix-bound BMP-2 are similar to those found for soluble BMP-2. These results highlight that BMP-2 presented by a biomaterial at the ventral side of the cell can trigger major endocytic and associated signaling pathways leading to bone regeneration. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Cellular Magnesium Matrix Foam Composites for Mechanical Damping Applications

Science.gov (United States)

Shunmugasamy, Vasanth Chakravarthy; Mansoor, Bilal; Gupta, Nikhil

2016-01-01

The damping characteristics of metal alloys and metal matrix composites are relevant to the automotive, aerospace, and marine structures. Use of lightweight materials can help in increasing payload capacity and in decreasing fuel consumption. Lightweight composite materials possessing high damping capabilities that can be designed as structural members can greatly benefit in addressing these needs. In this context, the damping properties of lightweight metals such as aluminum and magnesium and their respective composites have been studied in the existing literature. This review focuses on analyzing the damping properties of aluminum and magnesium alloys and their cellular composites. The damping properties of various lightweight alloys and composites are compared on the basis of their density to understand the potential for weight saving in structural applications. Magnesium alloys are observed to possess better damping properties in comparison to aluminum. However, aluminum matrix syntactic foams reinforced with silicon carbide hollow particles possess a damping capacity and density comparable to magnesium alloy. By using the data presented in the study, composites with specific compositions and properties can be selected for a given application. In addition, the comparison of the results helps in identifying the areas where attention needs to be focused to address the future needs.

Microcausality, macrocausality and the physical region (micro)analytic S-matrix

International Nuclear Information System (INIS)

Iagolnitzer, D.

1980-01-01

Recent works on the physical region analytic structure of multiparticle collision amplitudes in relativistic quantum theory are presented. First, the structure that can be expected and which is the expression, in terms of general essential support or microanalyticity properties, of macrocausality and macrocausal factorization, is described. It is shown that, taken together, these properties are equivalent to decompositions of the S-matrix, in bounded parts of the physical region, in terms of generalized Feynman integrals. Derivations of this structure obtained recently for 3 → 3 processes below the four-particle threshold both in S-matrix theory (without recourse to the crucial ad hoc assumption of 'separation of singularities' in unitarity equations used previously) and in axiomatic field theory are then reviewed. It is finally explained how this structure applies in two-dimensional space-time and yields factorization of the multiparticle S-matrix itself for a class of models. (orig.)

Middle and long-term follow-up of intracranial aneurysms treated with Matrix detachable coils

International Nuclear Information System (INIS)

Wu Xi; Liu Jianmin; Huang Qinghai; Xu Yi

2008-01-01

Objective: This study was undertaken to evaluate the safety of the polyglycolic/polylactic acid (PGLA)-coated Matrix detachable coils (Matrix) and analyze factors which may relate to the recanalization rate of the Matrix coils in the treatment of intracranial aneurysms. Methods: 75 patients underwent 79 aneurysm treatments with Matrix coils from May 2003 to July 2005 were retrospectively investigated. Morphological changes were compared postoperatively with last-follow-up digital subtraction angiography (DSA) by using the Raymond scale. We defined incomplete recanalization or stable aneurysms as uncured, while those of progressive occlusion or complete occlusion aneurysms demonstrated on the last-follow-up imagings as cured. We also utilized Cox model for analyzing the relationships between factors including age, gender, degree of aneurysmal occlusion, stenting, aneurysm neck size, aneurysm maximum size and Matrix coils length (%) and the long-term angiographic follow-up results. Results: The correlative surgical complications rate with Matrix coils was 13.3%. The total rate of recanalization was 11.4%. Large aneurysms treated with combined stenting got 40% recanalization. No statistic relationships were shown between the factors forementioned and the recanalization rate, but progressive occlusion was observed in 11 (61%)incompletely treated aneurysms. Conclusions: Matrix detachable coil technique is safe for intracranial aneurysm and would further decrease the recurrence of large aneurysm with combination of stenting but long term efficacy needs further follow-up and large scale randomized control study. (authors)

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.

Explicit Inverse of an Interval Matrix with Unit Midpoint

Czech Academy of Sciences Publication Activity Database

Rohn, Jiří

2011-01-01

Roč. 22, - (2011), s. 138-150 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 * unit midpoint * inverse interval matrix * regularity Subject RIV: BA - General Mathematics Impact factor: 0.808, year: 2010 http://www.math.technion.ac.il/iic/ ela / ela -articles/articles/vol22_pp138-150.pdf

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

Science.gov (United States)

Tsuchiyama, Tomoyuki; Katsuhara, Miki; Nakajima, Masahiro

2017-11-17

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

Matrix metalloproteinase-3, vitamin D receptor gene polymorphisms, and occupational risk factors in lumbar disc degeneration.

Science.gov (United States)

Zawilla, N H; Darweesh, H; Mansour, N; Helal, S; Taha, F M; Awadallah, M; El Shazly, R

2014-06-01

Lumbar disc degeneration (LDD) is a process that begins early in life, contributing to the development of low back pain. LDD is a consequence of a variety of factors, and its etiology remains poorly understood. Objectives to investigate occupational and genetic risk factors inducing lumbar disc degeneration, and to evaluate the possible association of genetic polymorphisms of matrix metalloproteinase 3 (MMP-3) and vitamin D receptor (VDR) with the severity of LDD in an Egyptian population. A case control study involving 84 LDD and 60 controls was carried out. Five types of work related factors were investigated by questionnaire, complete neurological examination for all subjects and MRI for the cases. Polymerase chain reaction and restriction fragment length polymorphism methods were applied to detect polymorphisms in MMP-3 Promoter (-1,171 6A/5A) (rs 731236) and VDR-Apa (rs 35068180). We found that family history, back injury, smoking, high level of sitting, bending/twisting, physical workload, lifting, whole body vibration, mutant allele 5A of MMP-3 and mutant allele T of VDR were significantly associated with LDD (OR = 2.9, 3.1, 2.1, 11.1, 15.9, 11.7, 8.2, 12.6, 2.5 and 3.1 respectively, p < 0.05). Cases that carry allele 5A and/or allele T were associated with LDD severity. LDD is closely associated in occurrence and severity with occupational, environmental risk factors and susceptibility genes namely MMP-3, and VDR (ApaI). This study throws light on the importance of screening for early detection of susceptible individuals and disease prevention.

Trust and Product/Sellers Reviews as Factors Influencing Online Product Comparison Sites Usage by Young Consumers

OpenAIRE

Radoslaw Macik; Dorota Macik

2016-01-01

Paper describes young consumers’ behaviour connected with online product comparison sites usage as an example of online decision shopping aids. Authors’ main goal is to check whether or not such factors as: previous experience in such sites usage, personal innovativeness in domain of information technology – PIIT, and particularly cognitive trust (in several subdimensions), as well as affective trust toward online product comparison site, influence purchase intention via men...

Mimicking the extracellular matrix with functionalized, metal-assembled collagen peptide scaffolds.

Science.gov (United States)

Hernandez-Gordillo, Victor; Chmielewski, Jean

2014-08-01

Natural and synthetic three-dimensional (3-D) scaffolds that mimic the microenvironment of the extracellular matrix (ECM), with growth factor storage/release and the display of cell adhesion signals, offer numerous advantages for regenerative medicine and in vitro morphogenesis and oncogenesis modeling. Here we report the design of collagen mimetic peptides (CMPs) that assemble into a highly crosslinked 3-D matrix in response to metal ion stimuli, that may be functionalized with His-tagged cargoes, such as green fluorescent protein (GFP-His8) and human epidermal growth factor (hEGF-His6). The bound hEGF-His6 was found to gradually release from the matrix in vitro and induce cell proliferation in the EGF-dependent cell line MCF10A. The additional incorporation of a cell adhesion sequence (RGDS) at the N-terminus of the CMP creates an environment that facilitated the organization of matrix-encapsulated MCF10A cells into spheroid structures, thus mimicking the ECM environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Stress and Damage in Polymer Matrix Composite Materials Due to Material Degradation at High Temperatures

Science.gov (United States)

McManus, Hugh L.; Chamis, Christos C.

1996-01-01

This report describes analytical methods for calculating stresses and damage caused by degradation of the matrix constituent in polymer matrix composite materials. Laminate geometry, material properties, and matrix degradation states are specified as functions of position and time. Matrix shrinkage and property changes are modeled as functions of the degradation states. The model is incorporated into an existing composite mechanics computer code. Stresses, strains, and deformations at the laminate, ply, and micro levels are calculated, and from these calculations it is determined if there is failure of any kind. The rationale for the model (based on published experimental work) is presented, its integration into the laminate analysis code is outlined, and example results are given, with comparisons to existing material and structural data. The mechanisms behind the changes in properties and in surface cracking during long-term aging of polyimide matrix composites are clarified. High-temperature-material test methods are also evaluated.

The Particle Shape of WC Governing the Fracture Mechanism of Particle Reinforced Iron Matrix Composites.

Science.gov (United States)

Li, Zulai; Wang, Pengfei; Shan, Quan; Jiang, Yehua; Wei, He; Tan, Jun

2018-06-11

In this work, tungsten carbide particles (WC p , spherical and irregular particles)-reinforced iron matrix composites were manufactured utilizing a liquid sintering technique. The mechanical properties and the fracture mechanism of WC p /iron matrix composites were investigated theoretically and experimentally. The crack schematic diagram and fracture simulation diagram of WC p /iron matrix composites were summarized, indicating that the micro-crack was initiated both from the interface for spherical and irregular WC p /iron matrix composites. However, irregular WC p had a tendency to form spherical WC p . The micro-cracks then expanded to a wide macro-crack at the interface, leading to a final failure of the composites. In comparison with the spherical WC p , the irregular WC p were prone to break due to the stress concentration resulting in being prone to generating brittle cracking. The study on the fracture mechanisms of WC p /iron matrix composites might provide a theoretical guidance for the design and engineering application of particle reinforced composites.

Numerical Solution of Multiterm Fractional Differential Equations Using the Matrix Mittag–Leffler Functions

Directory of Open Access Journals (Sweden)

Marina Popolizio

2018-01-01

Full Text Available Multiterm fractional differential equations (MTFDEs nowadays represent a widely used tool to model many important processes, particularly for multirate systems. Their numerical solution is then a compelling subject that deserves great attention, not least because of the difficulties to apply general purpose methods for fractional differential equations (FDEs to this case. In this paper, we first transform the MTFDEs into equivalent systems of FDEs, as done by Diethelm and Ford; in this way, the solution can be expressed in terms of Mittag–Leffler (ML functions evaluated at matrix arguments. We then propose to compute it by resorting to the matrix approach proposed by Garrappa and Popolizio. Several numerical tests are presented that clearly show that this matrix approach is very accurate and fast, also in comparison with other numerical methods.

Diffusion bonded matrix of HGMF applied for BWR condensate water purification

International Nuclear Information System (INIS)

Soda, Fumitaka; Yukawa, Takao; Ito, Kazuyuki.

1984-01-01

High Gradient Magnetic Filter (HGMF) applied to the purification of power plant primary water has recently attracted much attention. In the application of HGMF to the water treatment of power plants, especially nuclear power plants, reliabillties of matrix (filtering medium) as well as removal performance for cruds (insoluble corrosion products) are considered to be important factors. To satisfy these factors, a new filtering medium named Diffision Bonded Matrix (DBM) has been developed and the test results are reported. Filtering efficiency and mechanical stiffness of DBM were examined using HGMF pilot test units consisting of 160 mm diameters x 240 mm length filter. The filtering velocity and the magnetic flux density used in this test were 800 m/h 5 kG, respectively. The filtering efficiencies and of 85-100% were obtained for artificial cruds for DBM. The DBM indicated slightly better filtering efficiency than for conventional wool matrix under the same filtering and matrix conditions. The DBM kept its original mechanical properties and very few pieces of fibers were broken off while the conventional wool matrix lost its volume elasticities and the considerable amount of fibers was broken off during the test operation. The results described here demonstrated the applicability of DBM for treatment of BWR primary water by High Gradient Magnetic Filter. (author)

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.

Quantitative comparison of some aesthetic factors among rivers

Science.gov (United States)

Leopold, Luna Bergere

1969-01-01

It is difficult to evaluate the factors contributing to aesthetic or nonmonetary aspects of a landscape. In contrast, aspects which lend themselves to cost-benefit comparisons are now treated in a routine way. As a result, nonmonetary values are described either in emotion-loaded words or else are mentioned and thence forgotten.The present report is a preliminary attempt to quantify some elements of aesthetic appeal while eliminating, insofar as possible, value judgments or personal preferences. If methods of recording such factors can be developed, the results promise to be a useful, new kind of basic data needed in many planning and decision-making circumstances. Such data would be especially useful when choices must be made among alternative courses of action. Such data would tend to provide a more prominent consideration of the nonmonetary aspects of a landscape.Assignment of quantitative estimates to aesthetic factors leads not so much to ratios of value as to relative rank positions. In fact, value itself tends to carry a connotation of preference, whereas ranking can more easily be used for categorization without attribution of preference and thus it tends to a void the introduction at too early a stage of differences in preference. Because the Federal Power Commission has been studying an application for a permit to construct one or more additional hydropower dams in the vicinity of Hells Canyon of the Snake River, the localities studied for the present discussion are in that region of Idaho. Hopefully, the data collected will provide some useful information on factors related to nonmonetary values in the region. The present discussion has been kept free of the preference judgments of the writer, and throughout the discussions observations are treated as facts.

Iron oxide nanomatrix facilitating metal ionization in matrix-assisted laser desorption/ionization mass spectrometry.

Science.gov (United States)

Obena, Rofeamor P; Lin, Po-Chiao; Lu, Ying-Wei; Li, I-Che; del Mundo, Florian; Arco, Susan dR; Nuesca, Guillermo M; Lin, Chung-Chen; Chen, Yu-Ju

2011-12-15

The significance and epidemiological effects of metals to life necessitate the development of direct, efficient, and rapid method of analysis. Taking advantage of its simple, fast, and high-throughput features, we present a novel approach to metal ion detection by matrix-functionalized magnetic nanoparticle (matrix@MNP)-assisted MALDI-MS. Utilizing 21 biologically and environmentally relevant metal ion solutions, the performance of core and matrix@MNP against conventional matrixes in MALDI-MS and laser desorption ionization (LDI) MS were systemically tested to evaluate the versatility of matrix@MNP as ionization element. The matrix@MNPs provided 20- to >100-fold enhancement on detection sensitivity of metal ions and unambiguous identification through characteristic isotope patterns and accurate mass (<5 ppm), which may be attributed to its multifunctional role as metal chelator, preconcentrator, absorber, and reservoir of energy. Together with the comparison on the ionization behaviors of various metals having different ionization potentials (IP), we formulated a metal ionization mechanism model, alluding to the role of exciton pooling in matrix@MNP-assisted MALDI-MS. Moreover, the detection of Cu in spiked tap water demonstrated the practicability of this new approach as an efficient and direct alternative tool for fast, sensitive, and accurate determination of trace metal ions in real samples.

Exploring possible causes of fatal burns in 2007 using Haddon's Matrix: a qualitative study

Directory of Open Access Journals (Sweden)

Homayoun Sadeghi-Bazargani

2015-01-01

Full Text Available Abstract: Background: Burns are a major factor in injury mortality. The aim of this study was to explore the possible causes of fatal burns using Haddon’s Matrix. Methods: This is a qualitative study using a phenomenological approach. We collected elicitation interview data using nine corroborators who were the most knowledgeable about the index burn event. Immediately after recording, the data was verbatim. Each event was analyzed using Haddon’s Matrix. Results: Interviewees provided detailed information about 11 burn cases. Overall, 202 burnrelated factors were extracted. Using Haddon’s Matrix, 43 risk factors were identified. The most common included the lack of basic knowledge of burn care, the use of unsafe appliances including kerosene heaters and stoves in hazardous environments such kitchens and bathrooms, poor burn care delivery system in hospitals, poor and unsafe living conditions, financial issues, and other factors detailed in the article. Conclusions: Our findings suggest burn related prevention efforts should focus on improving human living conditions, promoting the use of safe heating appliances, providing public burn-safety precautions education, and improving the quality of care in burn centers and hospitals. The use of Haddon’s Matrix in future injury research is discussed.

Comparison of eigensolvers for symmetric band matrices.

Science.gov (United States)

Moldaschl, Michael; Gansterer, Wilfried N

2014-09-15

We compare different algorithms for computing eigenvalues and eigenvectors of a symmetric band matrix across a wide range of synthetic test problems. Of particular interest is a comparison of state-of-the-art tridiagonalization-based methods as implemented in Lapack or Plasma on the one hand, and the block divide-and-conquer (BD&C) algorithm as well as the block twisted factorization (BTF) method on the other hand. The BD&C algorithm does not require tridiagonalization of the original band matrix at all, and the current version of the BTF method tridiagonalizes the original band matrix only for computing the eigenvalues. Avoiding the tridiagonalization process sidesteps the cost of backtransformation of the eigenvectors. Beyond that, we discovered another disadvantage of the backtransformation process for band matrices: In several scenarios, a lot of gradual underflow is observed in the (optional) accumulation of the transformation matrix and in the (obligatory) backtransformation step. According to the IEEE 754 standard for floating-point arithmetic, this implies many operations with subnormal (denormalized) numbers, which causes severe slowdowns compared to the other algorithms without backtransformation of the eigenvectors. We illustrate that in these cases the performance of existing methods from Lapack and Plasma reaches a competitive level only if subnormal numbers are disabled (and thus the IEEE standard is violated). Overall, our performance studies illustrate that if the problem size is large enough relative to the bandwidth, BD&C tends to achieve the highest performance of all methods if the spectrum to be computed is clustered. For test problems with well separated eigenvalues, the BTF method tends to become the fastest algorithm with growing problem size.

Impact of matrix size on observer performance in digital chest radiography

International Nuclear Information System (INIS)

Koelblinger, C.

2003-02-01

This thesis compared the observer performance in the detection of abnormalities on 2k matrix(0,2 mm pixel size) and 4k matrix (0,1 mm pixel size) digital chest radiographs. Eighty five patients who underwent CT of the thorax were prospectively reccruited into the study. A chest x-ray of each patient was acquired in 2k and 4k format and four readers analyzed the images by different criterias. On the one hand a ROC analysis was performed with the CT data as goldstandard. On the other hand each reader had to rate different anatomical structures in a direct comparison of the pictures. The results of the ratings did not show any significant difference between the 2k and the 4k format. The conclusion or this study is that the use of a 4k instead of a 2k matrix in digital chest radiography does not yield to an improved observer performance. (author)

An Ar threesome: Matrix models, 2d conformal field theories, and 4dN=2 gauge theories

International Nuclear Information System (INIS)

Schiappa, Ricardo; Wyllard, Niclas

2010-01-01

We explore the connections between three classes of theories: A r quiver matrix models, d=2 conformal A r Toda field theories, and d=4N=2 supersymmetric conformal A r quiver gauge theories. In particular, we analyze the quiver matrix models recently introduced by Dijkgraaf and Vafa (unpublished) and make detailed comparisons with the corresponding quantities in the Toda field theories and the N=2 quiver gauge theories. We also make a speculative proposal for how the matrix models should be modified in order for them to reproduce the instanton partition functions in quiver gauge theories in five dimensions.

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

Science.gov (United States)

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

2018-03-01

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

Orbifolds and Exact Solutions of Strongly-Coupled Matrix Models

Science.gov (United States)

Córdova, Clay; Heidenreich, Ben; Popolitov, Alexandr; Shakirov, Shamil

2018-02-01

We find an exact solution to strongly-coupled matrix models with a single-trace monomial potential. Our solution yields closed form expressions for the partition function as well as averages of Schur functions. The results are fully factorized into a product of terms linear in the rank of the matrix and the parameters of the model. We extend our formulas to include both logarithmic and finite-difference deformations, thereby generalizing the celebrated Selberg and Kadell integrals. We conjecture a formula for correlators of two Schur functions in these models, and explain how our results follow from a general orbifold-like procedure that can be applied to any one-matrix model with a single-trace potential.

The influence of cell-matrix attachment and matrix development on the micromechanical environment of the chondrocyte in tissue-engineered cartilage

NARCIS (Netherlands)

Khoshgoftar, M.; Ito, K.; Donkelaar, C.C. van

2014-01-01

Insufficiency of mechanical properties of tissue-engineered (TE) cartilage grafts is still a limiting factor for their clinical application. It has been shown that mechanostimulation of chondrocytes enhances synthesis of extracellular matrix (ECM) and thereby improves the mechanical properties of

Extended biorthogonal matrix polynomials

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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.

Laboratory Experiments to Evaluate Diffusion of 14C into Nevada Test Site Carbonate Aquifer Matrix

Energy Technology Data Exchange (ETDEWEB)

Ronald L. Hershey; William Howcroft; Paul W. Reimus

2003-03-01

Determination of groundwater flow velocities at the Nevada Test Site is important since groundwater is the principal transport medium of underground radionuclides. However, 14C-based groundwater velocities in the carbonate aquifers of the Nevada Test Site are several orders of magnitude slower than velocities derived from the Underground Test Area regional numerical model. This discrepancy has been attributed to the loss or retardation of 14C from groundwater into the surrounding aquifer matrix making 14C-based groundwater ages appear much older. Laboratory experiments were used to investigate the retardation of 14C in the carbonate aquifers at the Nevada Test Site. Three sets of experiments were conducted evaluating the diffusion of 14C into the carbonate aquifer matrix, adsorption and/or isotopic exchange onto the pore surfaces of the carbonate matrix, and adsorption and/or isotopic exchange onto the fracture surfaces of the carbonate aquifer. Experimental results a nd published aquifer matrix and fracture porosities from the Lower Carbonate Aquifer were applied to a 14C retardation model. The model produced an extremely wide range of retardation factors because of the wide range of published aquifer matrix and fracture porosities (over three orders of magnitude). Large retardation factors suggest that groundwater with very little measured 14C activity may actually be very young if matrix porosity is large relative to the fracture porosity. Groundwater samples collected from highly fractured aquifers with large effective fracture porosities may have relatively small correction factors, while samples from aquifers with a few widely spaced fractures may have very large correction factors. These retardation factors were then used to calculate groundwater velocities from a proposed flow path at the Nevada Test Site. The upper end of the range of 14C correction factors estimated groundwater velocities that appear to be at least an order of magnitude too high compared

Plasma membrane factor XIIIA transglutaminase activity regulates osteoblast matrix secretion and deposition by affecting microtubule dynamics.

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Hadil F Al-Jallad

2011-01-01

Full Text Available Transglutaminase activity, arising potentially from transglutaminase 2 (TG2 and Factor XIIIA (FXIIIA, has been linked to osteoblast differentiation where it is required for type I collagen and fibronectin matrix deposition. In this study we have used an irreversible TG-inhibitor to 'block -and-track' enzyme(s targeted during osteoblast differentiation. We show that the irreversible TG-inhibitor is highly potent in inhibiting osteoblast differentiation and mineralization and reduces secretion of both fibronectin and type I collagen and their release from the cell surface. Tracking of the dansyl probe by Western blotting and immunofluorescence microscopy demonstrated that the inhibitor targets plasma membrane-associated FXIIIA. TG2 appears not to contribute to crosslinking activity on the osteoblast surface. Inhibition of FXIIIA with NC9 resulted in defective secretory vesicle delivery to the plasma membrane which was attributable to a disorganized microtubule network and decreased microtubule association with the plasma membrane. NC9 inhibition of FXIIIA resulted in destabilization of microtubules as assessed by cellular Glu-tubulin levels. Furthermore, NC9 blocked modification of Glu-tubulin into 150 kDa high-molecular weight Glu-tubulin form which was specifically localized to the plasma membrane. FXIIIA enzyme and its crosslinking activity were colocalized with plasma membrane-associated tubulin, and thus, it appears that FXIIIA crosslinking activity is directed towards stabilizing the interaction of microtubules with the plasma membrane. Our work provides the first mechanistic cues as to how transglutaminase activity could affect protein secretion and matrix deposition in osteoblasts and suggests a novel function for plasma membrane FXIIIA in microtubule dynamics.

M(atrix) theory on an orbifold and twisted membrane

International Nuclear Information System (INIS)

Kim, N.

1997-01-01

M(atrix) theory on an orbifold and classical two-branes therein are studied with particular emphasis on heterotic M(atrix) theory on S 1 / Z 2 relevant to strongly coupled heterotic and dual type IA string theories. By analyzing the orbifold condition on Chan-Paton factors, we show that three choices of gauge group are possible for heterotic M(atrix) theory: SO(2N), SO(2N+1) or USp(2N). By examining the area-preserving diffeomorphism that underlies the M(atrix) theory, we find that each choice of gauge group restricts the possible topologies of two-branes. The result suggests that only the choice of SO(2N) or SO(2N+1) allows open two-branes, and hence, is relevant to heterotic M(atrix) theory. We show that the requirement of both local vacuum energy cancellation and of world-sheet anomaly cancellation of the resulting heterotic string identifies supersymmetric twisted sector spectra with sixteen fundamental representation spinors from each of the two fixed points. Twisted open and closed two-brane configurations are obtained in the large N limit. (orig.)

Random matrix analysis of human EEG data

Czech Academy of Sciences Publication Activity Database

Šeba, Petr

2003-01-01

Roč. 91, - (2003), s. 198104-1 - 198104-4 ISSN 0031-9007 R&D Projects: GA ČR GA202/02/0088 Institutional research plan: CEZ:AV0Z1010914 Keywords : random matrix theory * EEG signal Subject RIV: BE - Theoretical Physics Impact factor: 7.035, year: 2003

Interacting hadron resonance gas model in the K -matrix formalism

Science.gov (United States)

Dash, Ashutosh; Samanta, Subhasis; Mohanty, Bedangadas

2018-05-01

An extension of hadron resonance gas (HRG) model is constructed to include interactions using relativistic virial expansion of partition function. The noninteracting part of the expansion contains all the stable baryons and mesons and the interacting part contains all the higher mass resonances which decay into two stable hadrons. The virial coefficients are related to the phase shifts which are calculated using K -matrix formalism in the present work. We have calculated various thermodynamics quantities like pressure, energy density, and entropy density of the system. A comparison of thermodynamic quantities with noninteracting HRG model, calculated using the same number of hadrons, shows that the results of the above formalism are larger. A good agreement between equation of state calculated in K -matrix formalism and lattice QCD simulations is observed. Specifically, the lattice QCD calculated interaction measure is well described in our formalism. We have also calculated second-order fluctuations and correlations of conserved charges in K -matrix formalism. We observe a good agreement of second-order fluctuations and baryon-strangeness correlation with lattice data below the crossover temperature.

Response matrix of a multisphere neutron spectrometer with an 3 He proportional counter

International Nuclear Information System (INIS)

Vega C, H.R.; Manzanares A, E.; Hernandez D, V.M.; Mercado S, G.A.

2005-01-01

The response matrix of a Bonner sphere spectrometer was calculated by use of the MCNP code. As thermal neutron counter, the spectrometer has a 3.2 cm-diameter 3 He-filled proportional counter which is located at the center of a set of polyethylene spheres. The response was calculated for 0, 3, 5, 6, 8, 10, 12, and 16 inches-diameter polyethylene spheres for neutrons whose energy goes from 10 -9 to 20 MeV. The response matrix was compared with a set of responses measured with several monoenergetic neutron sources. In this comparison the calculated matrix agrees with the experimental results. The matrix was also compared with the response matrix calculated for the PTB C spectrometer. Even though that calculation was carried out using a detailed model to describe the proportional counter; both matrices do agree, but small differences are observed in the bare case because of the difference in the model used during calculations. Other differences are in some spheres for 14.8 and 20 MeV neutrons, probably due to the differences in the cross sections used during both calculations. (Author) 28 refs., 1 tab., 6 figs

Source apportionment of NMVOCs in the Kathmandu Valley during the SusKat-ABC international field campaign using positive matrix factorization

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C. Sarkar

2017-07-01

Full Text Available A positive matrix factorization model (US EPA PMF version 5.0 was applied for the source apportionment of the dataset of 37 non-methane volatile organic compounds (NMVOCs measured from 19 December 2012 to 30 January 2013 during the SusKat-ABC international air pollution measurement campaign using a proton-transfer-reaction time-of-flight mass spectrometer in the Kathmandu Valley. In all, eight source categories were identified with the PMF model using the new constrained model operation mode. Unresolved industrial emissions and traffic source factors were the major contributors to the total measured NMVOC mass loading (17.9 and 16.8 %, respectively followed by mixed industrial emissions (14.0 %, while the remainder of the source was split approximately evenly between residential biofuel use and waste disposal (10.9 %, solvent evaporation (10.8 %, biomass co-fired brick kilns (10.4 %, biogenic emissions (10.0 % and mixed daytime factor (9.2 %. Conditional probability function (CPF analyses were performed to identify the physical locations associated with different sources. Source contributions to individual NMVOCs showed that biomass co-fired brick kilns significantly contribute to the elevated concentrations of several health relevant NMVOCs such as benzene. Despite the highly polluted conditions, biogenic emissions had the largest contribution (24.2 % to the total daytime ozone production potential, even in winter, followed by solvent evaporation (20.2 %, traffic (15.0 % and unresolved industrial emissions (14.3 %. Secondary organic aerosol (SOA production had approximately equal contributions from biomass co-fired brick kilns (28.9 % and traffic (28.2 %. Comparison of PMF results based on the in situ data versus REAS v2.1 and EDGAR v4.2 emission inventories showed that both the inventories underestimate the contribution of traffic and do not take the contribution of brick kilns into account. In addition, the REAS

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

International Nuclear Information System (INIS)

Taylor, Washington

2001-01-01

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

Ceramic matrix composites by microwave assisted CVI

International Nuclear Information System (INIS)

Currier, R.P.; Devlin, D.J.

1993-01-01

Chemical vapor infiltration (CVI) processes for producing continuously reinforced ceramic composites are reviewed. Potential advantages of microwave assisted CVI are noted and numerical studies of microwave assisted CVI are reviewed. The models predict inverted thermal gradients in fibrous ceramic preforms subjected to microwave radiation and suggest processing strategies for achieving uniformly dense composites. Comparisons are made to experimental results on silicon-based composite systems. The role played by the relative ability of fiber and matrix to dissipate microwave energy is noted. Results suggest that microwave induced inverted gradients can be exploited to promote inside-out densification. 10 refs., 2 figs

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.

Extending injury prevention methodology to chemical terrorism preparedness: the Haddon Matrix and sarin.

Science.gov (United States)

Varney, Shawn; Hirshon, Jon Mark; Dischinger, Patricia; Mackenzie, Colin

2006-01-01

The Haddon Matrix offers a classic epidemiological model for studying injury prevention. This methodology places the public health concepts of agent, host, and environment within the three sequential phases of an injury-producing incident-pre-event, event, and postevent. This study uses this methodology to illustrate how it could be applied in systematically preparing for a mass casualty disaster such as an unconventional sarin attack in a major urban setting. Nineteen city, state, federal, and military agencies responded to the Haddon Matrix chemical terrorism preparedness exercise and offered feedback in the data review session. Four injury prevention strategies (education, engineering, enforcement, and economics) were applied to the individual factors and event phases of the Haddon Matrix. The majority of factors identified in all phases were modifiable, primarily through educational interventions focused on individual healthcare providers and first responders. The Haddon Matrix provides a viable means of studying an unconventional problem, allowing for the identification of modifiable factors to decrease the type and severity of injuries following a mass casualty disaster such as a sarin release. This strategy could be successfully incorporated into disaster planning for other weapons attacks that could potentially cause mass casualties.

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.

The Relationship between Self-Leadership and Personality: A Comparison of Hierarchical Factor Structures

OpenAIRE

Houghton, Jeffery D.

2000-01-01

This study examined the relationship between self-leadership and personality through an analysis and comparison of hierarchical factor structures. More specifically, this study examined the relationships between the self-leadership dimensions of behavior-focused strategies, natural reward strategies, and constructive thought strategies, and the personality dimensions of extraversion, emotional stability, and conscientiousness. The results of the study provide evidence that the self-leadershi...

Surface Modification of Indium Tin Oxide Nanoparticles to Improve Its Distribution in Epoxy-Silica Polymer Matrix

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Mostafa Jafari

2014-10-01

Full Text Available A semiconducting nanoparticle indium tin oxide (ITO was modified with silane groups and for this purpose trimethoxysilane (TMOS precursor was used under specific experimental conditions for surface modification of ITO nanoparticles. It is found that the modification of ITO nanoparticles increases the interactions between the filler and the matrix and subsequently improves the distibution of indium tin oxide nanoparticles in the polymer matrix. The epoxisilica polymer matrix was produced using trimethoxysilane and 3-glycidyloxypropyl trimethoxysilane precursors and ethylenediamine (EDA as curing agent at low temperature by sol-gel process. The sol-gel process was very useful due to its easily controllable process, solution concentration and homogeneity without using expensive and complicated equipments in comparison with other methods. Then, Fourier transform infrared (FTIR spectroscopy was employed to study the formation of Si-O-Si and Si-OH groups on ITO nanoparticles. X-Ray diffraction (XRD technique and thermal gravimetric analysis (TGA were employed to investigate the modification and weight loss of the modified ITO, respectively, as an indication of the presence of organic groups on these nanoparticles. The separation analyzer tests were performed to check the stability of the nanoparticles suspension and it revealed that due to better interaction of nanoparticles with the polymer matrix the stability of modified ITO suspention is higher than the unmodified sample. The morphology and particle distribution were determined by scanning electron microscopy (SEM. It was found that the distibution of modified indium tin oxide in epoxy-silica polymer matrix was improved in comparison with pure ITO.

Comparison of the two different standard flux-to-dose rate conversion factors

International Nuclear Information System (INIS)

Metghalchi, M.; Ashrafi, R.

1983-01-01

A very useful and simple way of obtaining the dose rate associated with neutron or photon fluxes is to multiply these fluxes by the appropriate flux-to-dose rate conversion factors. Two basic standard flux-to-dose rate conversion factors. are being used in all over the world, those recommended by the International Commission on Radiation Protection (ICRP) and the American National Standars (ANS). The purpose of this paper is to compare these two standard with each other. The comparison proved that the dose rate associated with a specific neutron flux, obtained by the ANS flux-to-dose rate conversion factors is usually higher than those calculated by the ICRP's conversion factors. Whereas in the case of the photon, in all energies, the difference between the dose rates obtained by these two standard flux-to-dose rate conversion factors are noticeable, and the ANS results are higher than the ICRP ones. So, it should be noted that for a specific neutron or photon flux the dose rate obtained by the ANS flux-to-dose rate conversion factors are more conservative than those obtained by the ICRP's. Therefore, in order to establish a more reasonable new standard flux-to-dose rate conversion factors, more work should be done. (author)

Invariant Imbedding T-Matrix Method for Axial Symmetric Hydrometeors with Extreme Aspect Ratios

Science.gov (United States)

Pelissier, C.; Clune, T.; Kuo, K. S.; Munchak, S. J.; Adams, I. S.

2017-12-01

The single-scattering properties (SSPs) of hydrometeors are the fundamental quantities for physics-based precipitation retrievals. Thus, efficient computation of their electromagnetic scattering is of great value. Whereas the semi-analytical T-Matrix methods are likely the most efficient for nonspherical hydrometeors with axial symmetry, they are not suitable for arbitrarily shaped hydrometeors absent of any significant symmetry, for which volume integral methods such as those based on Discrete Dipole Approximation (DDA) are required. Currently the two leading T-matrix methods are the Extended Boundary Condition Method (EBCM) and the Invariant Imbedding T-matrix Method incorporating Lorentz-Mie Separation of Variables (IITM+SOV). EBCM is known to outperform IITM+SOV for hydrometeors with modest aspect ratios. However, in cases when aspect ratios become extreme, such as needle-like particles with large height to diameter values, EBCM fails to converge. Such hydrometeors with extreme aspect ratios are known to be present in solid precipitation and their SSPs are required to model the radiative responses accurately. In these cases, IITM+SOV is shown to converge. An efficient, parallelized C++ implementation for both EBCM and IITM+SOV has been developed to conduct a performance comparison between EBCM, IITM+SOV, and DDSCAT (a popular implementation of DDA). We present the comparison results and discuss details. Our intent is to release the combined ECBM & IITM+SOV software to the community under an open source license.

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

Science.gov (United States)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Examining the Determinants of China’s Inward FDI Using Grey Matrix Relational Analysis Model

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Hang JIANG

2017-12-01

Full Text Available Grey relational analysis (GRA model is an important part of grey system theory, which is used to ascertain the relational grade between an influential factor and the major behavior factor. Most of GRA models are mainly applied to the field in which the behavior factor and influential factor are the cross-sectional or time series data in a given system. However, owing to the panel data contains plenty information including individual and time characteristics, the traditional GRA model cannot be applied to panel data analysis. To overcome this drawback, the grey matrix relational analysis model is applied to measure the similarity of panel data from two dimensions of individual and time on the basis of the definition of the matrix sequence of a discrete data sequence. This paper examines the determinants of inward foreign direct investment (IFDI in China using grey matrix relational analysis model. The study finds that the GDP per capita, enrollment of regular institutions of higher education, and internal expenditure on R&D are the key factors of IFDI.

Study of the validity of a job-exposure matrix for psychosocial work factors: results from the national French SUMER survey.

Science.gov (United States)

Niedhammer, Isabelle; Chastang, Jean-François; Levy, David; David, Simone; Degioanni, Stéphanie; Theorell, Töres

2008-10-01

To construct and evaluate the validity of a job-exposure matrix (JEM) for psychosocial work factors defined by Karasek's model using national representative data of the French working population. National sample of 24,486 men and women who filled in the Job Content Questionnaire (JCQ) by Karasek measuring the scores of psychological demands, decision latitude, and social support (individual scores) in 2003 (response rate 96.5%). Median values of the three scores in the total sample of men and women were used to define high demands, low latitude, and low support (individual binary exposures). Job title was defined by both occupation and economic activity that were coded using detailed national classifications (PCS and NAF/NACE). Two JEM measures were calculated from the individual scores of demands, latitude and support for each job title: JEM scores (mean of the individual score) and JEM binary exposures (JEM score dichotomized at the median). The analysis of the variance of the individual scores of demands, latitude, and support explained by occupations and economic activities, of the correlation and agreement between individual measures and JEM measures, and of the sensitivity and specificity of JEM exposures, as well as the study of the associations with self-reported health showed a low validity of JEM measures for psychological demands and social support, and a relatively higher validity for decision latitude compared with individual measures. Job-exposure matrix measure for decision latitude might be used as a complementary exposure assessment. Further research is needed to evaluate the validity of JEM for psychosocial work factors.

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.

Synthetic matrix metalloproteinase inhibitors inhibit growth of established breast cancer osteolytic lesions and prolong survival in mice

DEFF Research Database (Denmark)

Winding, Bent; NicAmhlaoibh, Róisín; Misander, Henriette

2002-01-01

Breast cancer frequently leads to incurable bone metastasis. Essential requirements for the development of bone metastasis are cell-cell and cell-matrix interactions, release of bioactive growth factors and cytokines, and removal of large amounts of bone matrix. Matrix metalloproteinases (MMPs...

An Uncertainty Structure Matrix for Models and Simulations

Science.gov (United States)

Green, Lawrence L.; Blattnig, Steve R.; Hemsch, Michael J.; Luckring, James M.; Tripathi, Ram K.

2008-01-01

Software that is used for aerospace flight control and to display information to pilots and crew is expected to be correct and credible at all times. This type of software is typically developed under strict management processes, which are intended to reduce defects in the software product. However, modeling and simulation (M&S) software may exhibit varying degrees of correctness and credibility, depending on a large and complex set of factors. These factors include its intended use, the known physics and numerical approximations within the M&S, and the referent data set against which the M&S correctness is compared. The correctness and credibility of an M&S effort is closely correlated to the uncertainty management (UM) practices that are applied to the M&S effort. This paper describes an uncertainty structure matrix for M&S, which provides a set of objective descriptions for the possible states of UM practices within a given M&S effort. The columns in the uncertainty structure matrix contain UM elements or practices that are common across most M&S efforts, and the rows describe the potential levels of achievement in each of the elements. A practitioner can quickly look at the matrix to determine where an M&S effort falls based on a common set of UM practices that are described in absolute terms that can be applied to virtually any M&S effort. The matrix can also be used to plan those steps and resources that would be needed to improve the UM practices for a given M&S effort.

Non-adiabatic quantum evolution: The S matrix as a geometrical phase factor

Energy Technology Data Exchange (ETDEWEB)

Saadi, Y., E-mail: S_yahiadz@yahoo.fr [Laboratoire de Physique Quantique et Systèmes Dynamiques, Faculté des Sciences, Université Ferhat Abbas de Sétif, Sétif 19000 (Algeria); Maamache, M. [Laboratoire de Physique Quantique et Systèmes Dynamiques, Faculté des Sciences, Université Ferhat Abbas de Sétif, Sétif 19000 (Algeria)

2012-03-19

We present a complete derivation of the exact evolution of quantum mechanics for the case when the underlying spectrum is continuous. We base our discussion on the use of the Weyl eigendifferentials. We show that a quantum system being in an eigenstate of an invariant will remain in the subspace generated by the eigenstates of the invariant, thereby acquiring a generalized non-adiabatic or Aharonov–Anandan geometric phase linked to the diagonal element of the S matrix. The modified Pöschl–Teller potential and the time-dependent linear potential are worked out as illustrations. -- Highlights: ► In this Letter we study the exact quantum evolution for continuous spectra problems. ► We base our discussion on the use of the Weyl eigendifferentials. ► We give a generalized Lewis and Riesenfeld phase for continuous spectra. ► This generalized phase or Aharonov–Anandan geometric phase is linked to the S matrix. ► The modified Pöschl–Teller and the linear potential are worked out as illustrations.

General-transformation matrix for Dirac spinors and the calculation of spinorial amplitudes

International Nuclear Information System (INIS)

Nam, K.; Moravcsik, M.J.

1983-01-01

A general transformation matrix T(p's';p,s) is constructed which transforms a Dirac spinor psi(p,s) into another Dirac spinor psi(p',s') with arbitrarily given momenta and polarization states by expoloting the so-called Stech operator as one of generators for those transformations. This transformation matrix is then used in a calculation to yield the spinorial matrix element M = anti psi(p',s')GAMMApsi(p,s) for any spin polarization state. The final expressions of these matrix elements show the explicit structure of spin dependence for the process described by these spinorial amplitudes. The kinematical limiting cases such as very low energy or high energy of the various matrix elements can also be easily displayed. Our method is superior to the existing one in the following points. Since we have a well-defined transformation operator between two Dirac spinor states, we can evaluate the necessary phase factor of the matrix elements in an unambiguous way without introducing the coordinate system. This enables us to write down the Feynman amplitudes of complicated processes in any spin basis very easily in terms of previously calculated matrix elements of anti psiGAMMApsi which are building blocks of those Feynman amplitudes. The usefulness of the results is illustrated on Compton scattering and on the elastic scattering of two identical massive leptons where the phase factor is important. It is also shown that the Stech operator as a polarization operator is simply related to the operator K = #betta#(polarized μ . polarized L + 1)/2 which is often used in bound state problems

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

The AdS5xS5 superstring worldsheet S matrix and crossing symmetry

International Nuclear Information System (INIS)

Janik, Romuald A.

2006-01-01

An S matrix satisfying the Yang-Baxter equation with symmetries relevant to the AdS 5 xS 5 superstring recently has been determined up to an unknown scalar factor. Such scalar factors are typically fixed using crossing relations; however, due to the lack of conventional relativistic invariance, in this case its determination remained an open problem. In this paper we propose an algebraic way to implement crossing relations for the AdS 5 xS 5 superstring worldsheet S matrix. We base our construction on a Hopf-algebraic formulation of crossing in terms of the antipode and introduce generalized rapidities living on the universal cover of the parameter space which is constructed through an auxillary, coupling-constant dependent, elliptic curve. We determine the crossing transformation and write functional equations for the scalar factor of the S matrix in the generalized rapidity plane

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.

Theory of the particle matrix elements for Helium atom scattering in surfaces

International Nuclear Information System (INIS)

Khater, A.; Toennies, J.P.

2000-01-01

Full text.A brief review is presented for the recent development of the theory of the particle transition matrix elements, basic to the cross section for Helium and inert particle scattering at thermal energies in solid surfaces. the Jackson and Mott matrix elements are presented and discussed for surface scattering processes, habitually classified as elastic and inelastic. Modified transition matrix elements, introduced originally to account for the cut-off effects, are presented in a direct and simple manner. the Debye-Waller factor is introduced and discussed. A recent calculation for the particle transition matrix elements is presented for the specular and inelastic transition matrix elements and the corresponding inelastic scattering cross section is compared in detail to experimental data. the specular and inelastic transition matrix elements are found to be intrinsically similar owing to the intermediate role of a proposed virtual particle squeezed state near the surface

One-point functions in AdS/dCFT from matrix product states

International Nuclear Information System (INIS)

Buhl-Mortensen, Isak; Leeuw, Marius de; Kristjansen, Charlotte; Zarembo, Konstantin

2016-01-01

One-point functions of certain non-protected scalar operators in the defect CFT dual to the D3-D5 probe brane system with k units of world volume flux can be expressed as overlaps between Bethe eigenstates of the Heisenberg spin chain and a matrix product state. We present a closed expression of determinant form for these one-point functions, valid for any value of k. The determinant formula factorizes into the k=2 result times a k-dependent pre-factor. Making use of the transfer matrix of the Heisenberg spin chain we recursively relate the matrix product state for higher even and odd k to the matrix product state for k=2 and k=3 respectively. We furthermore find evidence that the matrix product states for k=2 and k=3 are related via a ratio of Baxter’s Q-operators. The general k formula has an interesting thermodynamical limit involving a non-trivial scaling of k, which indicates that the match between string and field theory one-point functions found for chiral primaries might be tested for non-protected operators as well. We revisit the string computation for chiral primaries and discuss how it can be extended to non-protected operators.

Icotinib inhibits the invasion of Tca8113 cells via downregulation of nuclear factor κB-mediated matrix metalloproteinase expression.

Science.gov (United States)

Yang, Cailing; Yan, Jianguo; Yuan, Guoyan; Zhang, Yinghua; Lu, Derong; Ren, Mingxin; Cui, Weigang

2014-09-01

Icotinib is an epidermal growth factor receptor tyrosine kinase inhibitor, which has been revealed to inhibit proliferation in tumor cells. However, the effect of icotinib on cancer cell metastasis remains to be explained. This study examines the effect of icotinib on the migration and invasion of squamous cells of tongue carcinoma (Tca8113 cells) in vitro . The results of the Boyden chamber invasion assay demonstrated that icotinib reduced cell invasion, suppressed the protein levels of matrix metalloproteinases (MMPs), MMP-2 and MMP-9, and increased the expression of tissue inhibitor of metalloproteinase-1. In addition, icotinib was found to significantly decrease the protein levels of nuclear factor κB (NF-κB) p65, which suggested that icotinib inhibits NF-κB activity. Furthermore, treatment with the NF-κB inhibitor, pyrrolidine dithiocarbamate, suppressed cell invasion and MMP-2 expression. These results suggested that icotinib inhibits the invasion of Tca8113 cells by downregulating MMP via the inactivation of the NF-κB signaling pathways.

Age-related collagen turnover of the interstitial matrix and basement membrane: Implications of age- and sex-dependent remodeling of the extracellular matrix

DEFF Research Database (Denmark)

Kehlet, Stephanie N.; Willumsen, Nicholas; Armbrecht, Gabriele

2018-01-01

The extracellular matrix (ECM) plays a vital role in maintaining normal tissue function. Collagens are major components of the ECM and there is a tight equilibrium between degradation and formation of these proteins ensuring tissue health and homeostasis. As a consequence of tissue turnover, small...... collagen fragments are released into the circulation, which act as important biomarkers in the study of certain tissue-related remodeling factors in health and disease. The aim of this study was to establish an age-related collagen turnover profile of the main collagens of the interstitial matrix (type I...... an increased turnover. In summary, collagen turnover is affected by age and sex with the interstitial matrix and the basement membrane being differently regulated. The observed changes needs to be accounted for when measuring ECM related biomarkers in clinical studies....

High-resolution magnetic resonance angiography of the lower extremities with a dedicated 36-element matrix coil at 3 Tesla.

Science.gov (United States)

Kramer, Harald; Michaely, Henrik J; Matschl, Volker; Schmitt, Peter; Reiser, Maximilian F; Schoenberg, Stefan O

2007-06-01

Recent developments in hard- and software help to significantly increase image quality of magnetic resonance angiography (MRA). Parallel acquisition techniques (PAT) help to increase spatial resolution and to decrease acquisition time but also suffer from a decrease in signal-to-noise ratio (SNR). The movement to higher field strength and the use of dedicated angiography coils can further increase spatial resolution while decreasing acquisition times at the same SNR as it is known from contemporary exams. The goal of our study was to compare the image quality of MRA datasets acquired with a standard matrix coil in comparison to MRA datasets acquired with a dedicated peripheral angio matrix coil and higher factors of parallel imaging. Before the first volunteer examination, unaccelerated phantom measurements were performed with the different coils. After institutional review board approval, 15 healthy volunteers underwent MRA of the lower extremity on a 32 channel 3.0 Tesla MR System. In 5 of them MRA of the calves was performed with a PAT acceleration factor of 2 and a standard body-matrix surface coil placed at the legs. Ten volunteers underwent MRA of the calves with a dedicated 36-element angiography matrix coil: 5 with a PAT acceleration of 3 and 5 with a PAT acceleration factor of 4, respectively. The acquired volume and acquisition time was approximately the same in all examinations, only the spatial resolution was increased with the acceleration factor. The acquisition time per voxel was calculated. Image quality was rated independently by 2 readers in terms of vessel conspicuity, venous overlay, and occurrence of artifacts. The inter-reader agreement was calculated by the kappa-statistics. SNR and contrast-to-noise ratios from the different examinations were evaluated. All 15 volunteers completed the examination, no adverse events occurred. None of the examinations showed venous overlay; 70% of the examinations showed an excellent vessel conspicuity

Comparison of risk factors of CHD in the men and women with MI.

Science.gov (United States)

Ilali, E; Taraghi, Z

2010-04-01

The purpose of this study is comparison of risk factors of MI in hospitalized men and women patients in CCU. The CHD is the most important cause of mortality in the industry countries. Different environmental and race in each location can affect on frequency of risk factors of MI. In this cross sectional study, comparison was done between men and women who have involved in MI. The random sampling method was used Blood sugar, cholesterol and homocystein, LPa, BMI, family history, skin color, smoking and the amount of activity were assessed with variables such as age. The data was collected via questionnaire from September until March 2004-2005. Finally the data were analyzed with using t-test, Chi square and pearson correlation. In this research 169 patients who involved in MI (114 men and 55 women) have participated. The mean of age in the men was 55.4 and in the women was 61.02. All patients had risk factors. In the men, smoking (52.6%) and family history (41.1%) were the most common risk factors of MI. In the women, hyperlipidemia (66.4%), diabetes (62%) and hypertension (58.2%) were the most common risk factors of MI. The mean of BMI in the men was 25.9 +/- 4.25 and in the women was 27.6 +/- 4.71. The mean of LPa in the men was 59.2 +/- 4.21 and in the women was 50.9 +/- 4.25. the mean of homocystein in the men was 10.7 +/- 7.67 and in the women was 8.9 +/- 14.45. Diabetes, hyperlipidemia, hypertension and smoking had significant relationship with age and sex (p homocystein, LPa, job, personality type and mobility didn't have significant relationship with age and sex. In this study the most common risk factors of MI in the men were smoking and positive family history and in the women were known hyperlipidemia and diabetes.

Frequency-domain imaging algorithm for ultrasonic testing by application of matrix phased arrays

Directory of Open Access Journals (Sweden)

Dolmatov Dmitry

2017-01-01

Full Text Available Constantly increasing demand for high-performance materials and systems in aerospace industry requires advanced methods of nondestructive testing. One of the most promising methods is ultrasonic imaging by using matrix phased arrays. This technique allows to create three-dimensional ultrasonic imaging with high lateral resolution. Further progress in matrix phased array ultrasonic testing is determined by the development of fast imaging algorithms. In this article imaging algorithm based on frequency domain calculations is proposed. This approach is computationally efficient in comparison with time domain algorithms. Performance of the proposed algorithm was tested via computer simulations for planar specimen with flat bottom holes.

Fuzzy vulnerability matrix

International Nuclear Information System (INIS)

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

2000-01-01

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

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

International Nuclear Information System (INIS)

Sisman, Tahsin Cagri; Tekin, Bayram

2010-01-01

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

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

Science.gov (United States)

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

2008-10-01

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