matrix factorization model: Topics by Science.gov

Sample records for matrix factorization model

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)
Efficient system modeling for a small animal PET scanner with tapered DOI detectors.

PubMed

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

2016-01-21

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

PubMed

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

2017-03-31

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

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for
Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

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

2015-01-01

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

PubMed

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

EPA Pesticide Factsheets

Positive Matrix Factorization is a receptor model developed by EPA to provide scientific support for current ambient air quality standards and implement those standards by identifying and quantifying the relative contributions of air pollution sources.
Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

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

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

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

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

2017-01-01

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

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.
Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.
Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.
Efficient Matrix Models for Relational Learning

DTIC Science & Technology

2009-10-01

74 4.5.3 Comparison to pLSI- pHITS . . . . . . . . . . . . . . . . . . . . 76 5 Hierarchical Bayesian Collective...Behaviour of Newton vs. Stochastic Newton on a three-factor model. 4.5.3 Comparison to pLSI- pHITS Caveat: Collective Matrix Factorization makes no guarantees...leads to better results; and another where a co-clustering model, pLSI- pHITS , has the advantage. pLSI- pHITS [24] is a relational clustering technique
Genetic algorithm and graph theory based matrix factorization method for online friend recommendation.

PubMed

Li, Qu; Yao, Min; Yang, Jianhua; Xu, Ning

2014-01-01

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

NASA Technical Reports Server (NTRS)

Feng, Dan; Pulliam, Thomas H.

1994-01-01

This paper introduces a tensor-Krylov method, the tensor-GMRES method, for large sparse systems of nonlinear equations. This method is a coupling of tensor model formation and solution techniques for nonlinear equations with Krylov subspace projection techniques for unsymmetric systems of linear equations. Traditional tensor methods for nonlinear equations are based on a quadratic model of the nonlinear function, a standard linear model augmented by a simple second order term. These methods are shown to be significantly more efficient than standard methods both on nonsingular problems and on problems where the Jacobian matrix at the solution is singular. A major disadvantage of the traditional tensor methods is that the solution of the tensor model requires the factorization of the Jacobian matrix, which may not be suitable for problems where the Jacobian matrix is large and has a 'bad' sparsity structure for an efficient factorization. We overcome this difficulty by forming and solving the tensor model using an extension of a Newton-GMRES scheme. Like traditional tensor methods, we show that the new tensor method has significant computational advantages over the analogous Newton counterpart. Consistent with Krylov subspace based methods, the new tensor method does not depend on the factorization of the Jacobian matrix. As a matter of fact, the Jacobian matrix is never needed explicitly.
Considering Horn's Parallel Analysis from a Random Matrix Theory Point of View.

PubMed

Saccenti, Edoardo; Timmerman, Marieke E

2017-03-01

Horn's parallel analysis is a widely used method for assessing the number of principal components and common factors. We discuss the theoretical foundations of parallel analysis for principal components based on a covariance matrix by making use of arguments from random matrix theory. In particular, we show that (i) for the first component, parallel analysis is an inferential method equivalent to the Tracy-Widom test, (ii) its use to test high-order eigenvalues is equivalent to the use of the joint distribution of the eigenvalues, and thus should be discouraged, and (iii) a formal test for higher-order components can be obtained based on a Tracy-Widom approximation. We illustrate the performance of the two testing procedures using simulated data generated under both a principal component model and a common factors model. For the principal component model, the Tracy-Widom test performs consistently in all conditions, while parallel analysis shows unpredictable behavior for higher-order components. For the common factor model, including major and minor factors, both procedures are heuristic approaches, with variable performance. We conclude that the Tracy-Widom procedure is preferred over parallel analysis for statistically testing the number of principal components based on a covariance matrix.

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

NASA Astrophysics Data System (ADS)

Lesieur, Thibault; Krzakala, Florent; Zdeborová, Lenka

2017-07-01

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

ERIC Educational Resources Information Center

Pennell, Roger

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…
Joint refinement model for the spin resolved one-electron reduced density matrix of YTiO3 using magnetic structure factors and magnetic Compton profiles data.

PubMed

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

2018-04-28

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

NASA Technical Reports Server (NTRS)

Bakuckas, John G., Jr.; Johnson, W. Steven

1994-01-01

In this research, thermal residual stresses were incorporated in an analysis of fiber-bridged matrix cracks in unidirectional and cross-ply titanium matrix composites (TMC) containing center holes or center notches. Two TMC were investigated, namely, SCS-6/Timelal-21S laminates. Experimentally, matrix crack initiation and growth were monitored during tension-tension fatigue tests conducted at room temperature and at an elevated temperature of 200 C. Analytically, thermal residual stresses were included in a fiber bridging (FB) model. The local R-ratio and stress-intensity factor in the matrix due to thermal and mechanical loadings were calculated and used to evaluate the matrix crack growth behavior in the two materials studied. The frictional shear stress term, tau, assumed in this model was used as a curve-fitting parameter to matrix crack growth data. The scatter band in the values of tau used to fit the matrix crack growth data was significantly reduced when thermal residual stresses were included in the fiber bridging analysis. For a given material system, lay-up and temperature, a single value of tau was sufficient to analyze the crack growth data. It was revealed in this study that thermal residual stresses are an important factor overlooked in the original FB models.
THE U.S. ENVIRONMENTAL PROTECTION AGENCY VERSION OF POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

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

NASA Astrophysics Data System (ADS)

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.
Significance Testing in Confirmatory Factor Analytic Models.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Hocevar, Dennis

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…
Modeling fatigue crack growth in cross ply titanium matrix composites

NASA Technical Reports Server (NTRS)

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

1993-01-01

In this study, the fatigue crack growth behavior of fiber bridging matrix cracks in cross-ply SCS-6/Ti-15-3 and SCS-6/Timetal-21S laminates containing center holes was investigated. Experimental observations revealed that matrix cracking was far more extensive and wide spread in the SCS-6/Ti-15-3 laminates compared to that in the SCS-6/Timetal-21S laminates. In addition, the fatigue life of the SCS-6/Ti-15-3 laminates was significantly longer than that of the SCS-6/Timetal-21S laminates. The matrix cracking observed in both material systems was analyzed using a fiber bridging (FB) model which was formulated using the boundary correction factors and weight functions for center hole specimen configurations. A frictional shear stress is assumed in the FB model and was used as a curve fitting parameter to model matrix crack growth data. The higher frictional shear stresses calculated in the SCS-6/Timetal-21S laminates resulted in lower stress intensity factors in the matrix and higher axial stresses in the fibers compared to those in the SCS-6/Ti-15-3 laminates at the same applied stress levels.
RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

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

NASA Astrophysics Data System (ADS)

Hunter-Jones, Nicholas; Liu, Junyu

2018-05-01

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

PubMed

Fan, Jicong; Cheng, Jieyu

2018-02-01

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

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

Yu, Li-Wei, E-mail: NKyulw@gmail.com; Zhao, Qing, E-mail: qzhaoyuping@bit.edu.cn; Ge, Mo-Lin, E-mail: geml@nankai.edu.cn

2014-09-15

This paper investigates the physical effects of the Yang–Baxter equation (YBE) to quantum entanglements through the 3-body S-matrix in entangling parameter space. The explicit form of 3-body S-matrix Ř{sub 123}(θ,φ) based on the 2-body S-matrices is given due to the factorization condition of YBE. The corresponding chain Hamiltonian has been obtained and diagonalized, also the Berry phase for 3-body system is given. It turns out that by choosing different spectral parameters the Ř(θ,φ)-matrix gives GHZ and W states respectively. The extended 1-D Kitaev toy model has been derived. Examples of the role of the model in entanglement transfer are discussed.more » - Highlights: • We give the relation between 3-body S-matrix and 3-qubit entanglement. • The relation between 3-qubit and 2-qubit entanglements is investigated via YBE. • 1D Kitaev toy model is derived by the Type-II solution of YBE. • The condition of YBE kills the “Zero boundary mode” in our chain model.« less
Fuzzy Mathematical Models To Remove Poverty Of Gypsies In Tamilnadu

NASA Astrophysics Data System (ADS)

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

2018-04-01

In the society there are several poor people are living. One of the sympathetic poor people is gypsies. They are moving from one place to another place towards survive of life because of not having any permanent place to live. In this paper we have interviewed 895 gypsies in Tamilnadu using a linguistic questionnaire. As the problems faced by them to improve their life at large involve so much of feeling, uncertainties and unpredictabilitys. I felt that it deem fit to use fuzzy theory in general and fuzzy matrix in particular. Fuzzy matrix is the best suitable tool where the data is an unsupervised one. Further the fuzzy matrix is so powerful to identify the main development factor of gypsies.This paper has three sections. In section one the method of application of CEFD matrix. In section two, we describe the development factors of gypsies. In section three, we apply these factors to the CEFD matrix and derive our conclusions. Key words: RD matrix, AFD matrix, CEFD matrix.
Evaluating the MSCEIT V2.0 via CFA: comment on Mayer et al. (2003).

PubMed

Gignac, Gilles E

2005-06-01

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

PubMed

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.
A quasi-likelihood approach to non-negative matrix factorization

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

A unified approach to non-negative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proven using the Expectation-Maximization algorithm. In addition, a measure to evaluate the goodness-of-fit of the resulting factorization is described. The proposed methods allow modeling of non-linear effects via appropriate link functions and are illustrated using an application in biomedical signal processing. PMID:27348511
Factor Analysis by Generalized Least Squares.

ERIC Educational Resources Information Center

Joreskog, Karl G.; Goldberger, Arthur S.

Aitkin's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are scale free and asymptotically efficient. The estimates are computed by a rapidly…
Targeting extracellular matrix remodeling in disease: Could resveratrol be a potential candidate?

PubMed

Agarwal, Renu; Agarwal, Puneet

2017-02-01

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

PubMed Central

Agarwal, Puneet

2016-01-01

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

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1997-01-01

This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from the information matrix. The special correlation matrix provides information on the system-observability matrix and the state-vector correlation. A system model is then developed from the observability matrix in conjunction with other algebraic manipulations. This approach leads to several different algorithms for computing system matrices for use in representing the system model. The relationship of the new algorithms with other realization algorithms in the time and frequency domains is established with matrix factorization of the information matrix. Several examples are given to illustrate the validity and usefulness of these new algorithms.

Movement behaviour within and beyond perceptual ranges in three small mammals: effects of matrix type and body mass.

PubMed

Prevedello, Jayme Augusto; Forero-Medina, Germán; Vieira, Marcus Vinícius

2010-11-01

1. For animal species inhabiting heterogeneous landscapes, the tortuosity of the dispersal path is a key determinant of the success in locating habitat patches. Path tortuosity within and beyond perceptual range must differ, and may be differently affected by intrinsic attributes of individuals and extrinsic environmental factors. Understanding how these factors interact to determine path tortuosity allows more accurate inference of successful movements between habitat patches. 2. We experimentally determined the effects of intrinsic (body mass and species identity) and extrinsic factors (distance to nearest forest fragment and matrix type) on the tortuosity of movements of three forest-dwelling didelphid marsupials, in a fragmented landscape of the Atlantic Forest, Brazil. 3. A total of 202 individuals were captured in forest fragments and released in three unsuitable matrix types (mowed pasture, abandoned pasture and manioc plantation), carrying spool-and-line devices. 4. Twenty-four models were formulated representing a priori hypotheses of major determinants of path tortuosity, grouped in three scenarios (only intrinsic factors, only extrinsic factors and models with combinations of both), and compared using a model selection approach. Models were tested separately for individuals released within the perceptual range of the species, and for individuals released beyond the perceptual range. 5. Matrix type strongly affected path tortuosity, with more obstructed matrix types hampering displacement of animals. Body mass was more important than species identity to determine path tortuosity, with larger animals moving more linearly. Increased distance to the fragment resulted in more tortuous paths, but actually reflects a threshold in perceptual range: linear paths within perceptual range, tortuous paths beyond. 6. The variables tested explained successfully path tortuosity, but only for animals released within the perceptual range. Other factors, such as wind intensity and direction of plantation rows, may be more important for individuals beyond their perceptual range. 7. Simplistic scenarios considering only intrinsic or extrinsic factors are inadequate to predict path tortuosity, and to infer dispersal success in heterogeneous landscapes. Perceptual range represents a fundamental threshold where the effects of matrix type, body mass and individual behaviour change drastically. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.
Markov model of the loan portfolio dynamics considering influence of management and external economic factors

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana; Timofeeva, Galina

2016-12-01

Mathematical model of loan portfolio in the form of a controlled Markov chain with discrete time is considered. It is assumed that coefficients of migration matrix depend on corrective actions and external factors. Corrective actions include process of receiving applications, interaction with existing solvent and insolvent clients. External factors are macroeconomic indicators, such as inflation and unemployment rates, exchange rates, consumer price indices, etc. Changes in corrective actions adjust the intensity of transitions in the migration matrix. The mathematical model for forecasting the credit portfolio structure taking into account a cumulative impact of internal and external changes is obtained.
Monocyte activation by smooth muscle cell-derived matrices.

PubMed

Kaufmann, J; Jorgensen, R W; Martin, B M; Franzblau, C

1990-12-01

Mononuclear phagocytes adhere to and penetrate the vessel wall endothelium and contact the subendothelial space prior to the development of the atherosclerotic plaque. In an attempt to model the early events of plaque development we used an elastin-rich, multicomponent, cell-derived matrix from neonatal rat aortic smooth muscle cells as a substratum for monocytes. Using this model, we show that human monocyte morphology and metabolism are markedly altered by the matrix substratum. When a mixed mononuclear cell population is seeded on matrix or plastic, only monocytes adhere to the matrix surface. In contrast, lymphocytes as well as monocytes adhere to the plastic surface. The matrix-adherent monocytes develop large intracellular granules and form extensive clusters of individual cells. Metabolically, these cells develop sodium fluoride resistant non-specific esterase activity and their media contain more growth factor activity and PGE2. Although total protein synthesis is equivalent in both cultures, the matrix contact induces an increase in specific proteins in the media. We also show that a purified alpha-elastin substratum induces some, but not all, of the monocyte changes seen when using the matrix substratum. Using the alpha-elastin substratum, there is selective adhesion of monocytes and increased growth factor activity, however, the cells are morphologically different from the matrix-adherent cells. Thus, the use of the smooth muscle cell-derived matrix, in conjunction with purified matrix components, serves as a model that can provide insight into the mechanisms of monocyte adhesion and stimulation by the matrix environment that exists in vivo. Such mechanisms may be particularly important in atherogenesis.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2013-09-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Proposed framework for thermomechanical life modeling of metal matrix composites

NASA Technical Reports Server (NTRS)

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

1993-01-01

The framework of a mechanics of materials model is proposed for thermomechanical fatigue (TMF) life prediction of unidirectional, continuous-fiber metal matrix composites (MMC's). Axially loaded MMC test samples are analyzed as structural components whose fatigue lives are governed by local stress-strain conditions resulting from combined interactions of the matrix, interfacial layer, and fiber constituents. The metallic matrix is identified as the vehicle for tracking fatigue crack initiation and propagation. The proposed framework has three major elements. First, TMF flow and failure characteristics of in situ matrix material are approximated from tests of unreinforced matrix material, and matrix TMF life prediction equations are numerically calibrated. The macrocrack initiation fatigue life of the matrix material is divided into microcrack initiation and microcrack propagation phases. Second, the influencing factors created by the presence of fibers and interfaces are analyzed, characterized, and documented in equation form. Some of the influences act on the microcrack initiation portion of the matrix fatigue life, others on the microcrack propagation life, while some affect both. Influencing factors include coefficient of thermal expansion mismatch strains, residual (mean) stresses, multiaxial stress states, off-axis fibers, internal stress concentrations, multiple initiation sites, nonuniform fiber spacing, fiber debonding, interfacial layers and cracking, fractured fibers, fiber deflections of crack fronts, fiber bridging of matrix cracks, and internal oxidation along internal interfaces. Equations exist for some, but not all, of the currently identified influencing factors. The third element is the inclusion of overriding influences such as maximum tensile strain limits of brittle fibers that could cause local fractures and ensuing catastrophic failure of surrounding matrix material. Some experimental data exist for assessing the plausibility of the proposed framework.
SOURCE APPORTIONMENT OF PM 2.5 AND CARBON IN SEATTLE USING CHEMICAL MASS BALANCE AND POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

Three years of PM2.5 speciated data were collected and chemically analyzed using the IMPROVE protocol at the Beacon Hill site in Seattle. The data were analyzed by the Chemical Mass Balance Version 8 (CMB8) and Positive Matrix Factorization (PMF) source apportionment models. T...
Relational Learning via Collective Matrix Factorization

DTIC Science & Technology

2008-06-01

well-known example of such a schema is pLSI- pHITS [13], which models document-word counts and document-document citations: E1 = words and E2 = E3...relational co- clustering include pLSI, pLSI- pHITS , the symmetric block models of Long et. al. [23, 24, 25], and Bregman tensor clustering [5] (which can...to pLSI- pHITS In this section we provide an example where the additional flexibility of collective matrix factorization leads to better results; and
A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...
Research on the recycling industry development model for typical exterior plastic components of end-of-life passenger vehicle based on the SWOT method.

PubMed

Zhang, Hongshen; Chen, Ming

2013-11-01

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

NASA Technical Reports Server (NTRS)

Jain, A.; Rodriguez, G.

1992-01-01

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

NASA Astrophysics Data System (ADS)

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

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

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

ERIC Educational Resources Information Center

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

2010-01-01

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

PubMed

Bi, Yuying; Patra, Prabir; Faezipour, Miad

2014-01-01

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

PubMed

Wong, Monica H T; Mutch, David M; McNicholas, Paul D

2017-03-04

A family of parsimonious Gaussian mixture models for the biclustering of gene expression data is introduced. Biclustering is accommodated by adopting a mixture of factor analyzers model with a binary, row-stochastic factor loadings matrix. This particular form of factor loadings matrix results in a block-diagonal covariance matrix, which is a useful property in gene expression analyses, specifically in biomarker discovery scenarios where blood can potentially act as a surrogate tissue for other less accessible tissues. Prior knowledge of the factor loadings matrix is useful in this application and is reflected in the one-way supervised nature of the algorithm. Additionally, the factor loadings matrix can be assumed to be constant across all components because of the relationship desired between the various types of tissue samples. Parameter estimates are obtained through a variant of the expectation-maximization algorithm and the best-fitting model is selected using the Bayesian information criterion. The family of models is demonstrated using simulated data and two real microarray data sets. The first real data set is from a rat study that investigated the influence of diabetes on gene expression in different tissues. The second real data set is from a human transcriptomics study that focused on blood and immune tissues. The microarray data sets illustrate the biclustering family's performance in biomarker discovery involving peripheral blood as surrogate biopsy material. The simulation studies indicate that the algorithm identifies the correct biclusters, most optimally when the number of observation clusters is known. Moreover, the biclustering algorithm identified biclusters comprised of biologically meaningful data related to insulin resistance and immune function in the rat and human real data sets, respectively. Initial results using real data show that this biclustering technique provides a novel approach for biomarker discovery by enabling blood to be used as a surrogate for hard-to-obtain tissues.
Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach

NASA Astrophysics Data System (ADS)

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.
Cobimaximal lepton mixing from soft symmetry breaking

NASA Astrophysics Data System (ADS)

Grimus, W.; Lavoura, L.

2017-11-01

Cobimaximal lepton mixing, i.e.θ23 = 45 ° and δ = ± 90 ° in the lepton mixing matrix V, arises as a consequence of SV =V* P, where S is the permutation matrix that interchanges the second and third rows of V and P is a diagonal matrix of phase factors. We prove that any such V may be written in the form V = URP, where U is any predefined unitary matrix satisfying SU =U*, R is an orthogonal, i.e. real, matrix, and P is a diagonal matrix satisfying P2 = P. Using this theorem, we demonstrate the equivalence of two ways of constructing models for cobimaximal mixing-one way that uses a standard CP symmetry and a different way that uses a CP symmetry including μ-τ interchange. We also present two simple seesaw models to illustrate this equivalence; those models have, in addition to the CP symmetry, flavour symmetries broken softly by the Majorana mass terms of the right-handed neutrino singlets. Since each of the two models needs four scalar doublets, we investigate how to accommodate the Standard Model Higgs particle in them.
Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

PubMed Central

Wen, Xiaotong; Rangarajan, Govindan; Ding, Mingzhou

2013-01-01

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

NASA Astrophysics Data System (ADS)

Beece, Daniel Kenneth

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

Radiative-Transfer Modeling of Spectra of Densely Packed Particulate Media

NASA Astrophysics Data System (ADS)

Ito, G.; Mishchenko, M. I.; Glotch, T. D.

2017-12-01

Remote sensing measurements over a wide range of wavelengths from both ground- and space-based platforms have provided a wealth of data regarding the surfaces and atmospheres of various solar system bodies. With proper interpretations, important properties, such as composition and particle size, can be inferred. However, proper interpretation of such datasets can often be difficult, especially for densely packed particulate media with particle sizes on the order of wavelength of light being used for remote sensing. Radiative transfer theory has often been applied to the study of densely packed particulate media like planetary regoliths and snow, but with difficulty, and here we continue to investigate radiative transfer modeling of spectra of densely packed media. We use the superposition T-matrix method to compute scattering properties of clusters of particles and capture the near-field effects important for dense packing. Then, the scattering parameters from the T-matrix computations are modified with the static structure factor correction, accounting for the dense packing of the clusters themselves. Using these corrected scattering parameters, reflectance (or emissivity via Kirchhoff's Law) is computed with the method of invariance imbedding solution to the radiative transfer equation. For this work we modeled the emissivity spectrum of the 3.3 µm particle size fraction of enstatite, representing some common mineralogical and particle size components of regoliths, in the mid-infrared wavelengths (5 - 50 µm). The modeled spectrum from the T-matrix method with static structure factor correction using moderate packing densities (filling factors of 0.1 - 0.2) produced better fits to the laboratory measurement of corresponding spectrum than the spectrum modeled by the equivalent method without static structure factor correction. Future work will test the method of the superposition T-matrix and static structure factor correction combination for larger particles sizes and polydispersed clusters in search for the most effective modeling of spectra of densely packed particulate media.
Methods for Estimating Uncertainty in Factor Analytic Solutions

EPA Science Inventory

The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DI...
A penny-shaped crack in a filament reinforced matrix. 1: The filament model

NASA Technical Reports Server (NTRS)

Erdogan, F.; Pacella, A. H.

1973-01-01

The electrostatic problem of a penny-shaped crack in an elastic matrix which reinforced by filaments or fibers perpendicular to the plane of the crack was studied. The elastic filament model was developed for application to evaluation studies of the stress intensity factor along the periphery of the crack, the stresses in the filaments or fibers, and the interface shear between the matrix and the filaments or fibers. The requirements expected of the model are a sufficiently accurate representation of the filament and applicability to the interaction problems involving a cracked elastic continuum with multi-filament reinforcements. The technique for developing the model and numerical examples of it are shown.
Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

PubMed

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.
Transformation Abilities: A Reanalysis and Confirmation of SOI Theory.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; And Others

1987-01-01

Confirmatory factor analysis was used to reanalyze correlational data from selected variables in Guilford's Aptitudes Research Project. Results indicated Guilford's model reproduced the original correlation matrix more closely than other models. Most of Guilford's tests indicated high loadings on their hypothesized factors. (GDC)
A multivariate multilevel Gaussian model with a mixed effects structure in the mean and covariance part.

PubMed

Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel

2014-05-20

A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.
Interactions of cytokines, growth factors, and the extracellular matrix in the cellular biology of uterine leiomyomata.

PubMed

Sozen, Ibrahim; Arici, Aydin

2002-07-01

To review the available information regarding the role of cytokines, growth factors, and the extracellular matrix in the pathophysiology of uterine leiomyomata and to integrate this information in a suggested model of disease at the cellular level. A thorough literature and MEDLINE search was conducted to identify the relevant studies in the English literature published between January, 1966 and October, 2001. A model of disease at the cellular level was developed using the most likely cytokines to be involved in the pathogenesis of leiomyomata as determined by our assessment of the available literature. A number of cytokines and growth factors, including transforming growth factor-beta (TGF-beta), epidermal growth factor, monocyte chemotactic protein-1, insulin-like growth factors 1 and 2, prolactin, parathyroid-hormone-related peptide, basic fibroblast growth factor, platelet-derived growth factor, interleukin-8, and endothelin, have been investigated in myometrium and leiomyoma. Among these cytokines, TGF-beta appears to be the only growth factor that has been shown to be overexpressed in leiomyoma vs. myometrium, be hormonally-regulated both in vivo and in vitro, and be both mitogenic and fibrogenic in these tissues. In addition to the cytokines, extracellular matrix components such as collagen, fibronectin, proteoglycans, matrix metalloproteinases, and tissue inhibitors of metalloproteinases seem to play pivotal roles in the pathogenesis of leiomyomata. We believe that, given the extent and depth of the current research on the cellular biology of leiomyomata, the cellular mechanisms responsible in the pathogenesis of leiomyomata will be identified clearly within the foreseeable future. This will enable researchers to develop therapy directed against the molecules and mechanisms at the cellular level.
Quantum kinetic expansion in the spin-boson model: Matrix formulation and system-bath factorized initial state.

PubMed

Gong, Zhihao; Tang, Zhoufei; Wang, Haobin; Wu, Jianlan

2017-12-28

Within the framework of the hierarchy equation of motion (HEOM), the quantum kinetic expansion (QKE) method of the spin-boson model is reformulated in the matrix representation. The equivalence between the two formulations (HEOM matrices and quantum operators) is numerically verified from the calculation of the time-integrated QKE rates. The matrix formulation of the QKE is extended to the system-bath factorized initial state. Following a one-to-one mapping between HEOM matrices and quantum operators, a quantum kinetic equation is rederived. The rate kernel is modified by an extra term following a systematic expansion over the site-site coupling. This modified QKE is numerically tested for its reliability by calculating the time-integrated rate and non-Markovian population kinetics. For an intermediate-to-strong dissipation strength and a large site-site coupling, the population transfer is found to be significantly different when the initial condition is changed from the local equilibrium to system-bath factorized state.
Detection of extracellular matrix modification in cancer models with inverse spectroscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Spicer, Graham L. C.; Azarin, Samira M.; Yi, Ji; Young, Scott T.; Ellis, Ronald; Bauer, Greta M.; Shea, Lonnie D.; Backman, Vadim

2016-10-01

In cancer biology, there has been a recent effort to understand tumor formation in the context of the tissue microenvironment. In particular, recent progress has explored the mechanisms behind how changes in the cell-extracellular matrix ensemble influence progression of the disease. The extensive use of in vitro tissue culture models in simulant matrix has proven effective at studying such interactions, but modalities for non-invasively quantifying aspects of these systems are scant. We present the novel application of an imaging technique, Inverse Spectroscopic Optical Coherence Tomography, for the non-destructive measurement of in vitro biological samples during matrix remodeling. Our findings indicate that the nanoscale-sensitive mass density correlation shape factor D of cancer cells increases in response to a more crosslinked matrix. We present a facile technique for the non-invasive, quantitative study of the micro- and nano-scale structure of the extracellular matrix and its host cells.
Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

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

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Arnold, Steven M.

2000-01-01

The generalized method of cells micromechanics model is utilized to analyze the tensile stress-strain response of a representative titanium matrix composite with weak interfacial bonding. The fiber/matrix interface is modeled through application of a displacement discontinuity between the fiber and matrix once a critical debonding stress has been exceeded. Unidirectional composites with loading parallel and perpendicular to the fibers are examined, as well as a cross-ply laminate. For each of the laminates studied, analytically obtained results are compared to experimental data. The application of residual stresses through a cool-down process was found to have a significant effect on the tensile response. For the unidirectional laminate with loading applied perpendicular to the fibers, fiber packing and fiber shape were shown to have a significant effect on the predicted tensile response. Furthermore, the interface was characterized through the use of semi-emperical parameters including an interfacial compliance and a "debond stress;" defined as the stress level across the interface which activates fiber/matrix debonding. The results in this paper demonstrate that if architectural factors are correctly accounted for and the interface is appropriately characterized, the macro-level composite behavior can be correctly predicted without modifying any of the fiber or matrix constituent properties.
[Preparation of hydrophilic matrix sustained release tablets of total lactones from Andrographis paniculata and study on its in vitro release mechanism].

PubMed

Xu, Fang-Fang; Shi, Wei; Zhang, Hui; Guo, Qing-Ming; Wang Zhen-Zhong; Bi, Yu-An; Wang, Zhi-Min; Xiao, Wei

2015-01-01

In this study, hydrophilic matrix sustained release tablets of total lactones from Andrographis paniculata were prepared and the in vitro release behavior were also evaluated. The optimal prescription was achieved by studying the main factor of the type and amount of hydroxypropyl methylcellulose (HPMC) using single factor test and evaluating through cumulative release of three lactones. No burst drug release from the obtained matrix tablets was observed. Drug release sustained to 14 h. The release mechanism of three lactones from A. paniculata was accessed by zero-order, first-order, Higuchi and Peppas equation. The release behavior of total lactones from A. paniculata was better agreed with Higuchi model and the drug release from the tablets was controlled by degradation of the matrix. The preparation of hydrophilic matrix sustained release tablets of total lactones from A. paniculata with good performance of drug release was simple.
3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

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

NASA Astrophysics Data System (ADS)

Chakraborty, Bipasha; Davies, Christine; Koponen, Jonna; Lepage, G. Peter

2018-03-01

he quark flavor sector of the Standard Model is a fertile ground to look for new physics effects through a unitarity test of the Cabbibo-Kobayashi-Maskawa (CKM) matrix. We present a lattice QCD calculation of the scalar and the vector form factors (over a large q2 region including q2 = 0) associated with the D→ Klv semi-leptonic decay. This calculation will then allow us to determine the central CKM matrix element, Vcs in the Standard Model, by comparing the lattice QCD results for the form factors and the experimental decay rate. This form factor calculation has been performed on the Nf = 2 + 1 + 1 MILC HISQ ensembles with the physical light quark masses.
Rephasing invariants of the Cabibbo-Kobayashi- Maskawa matrix

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

Pérez R, H.; Kielanowski, P., E-mail: kiel@fis.cinvestav.mx; Juárez W, S. R., E-mail: rebeca@esfm.ipn.mx

2016-03-15

The paper is motivated by the importance of the rephasing invariance of the CKM (Cabibbo-Kobayashi-Maskawa) matrix observables. These observables appear in the discussion of the CP violation in the standard model (Jarlskog invariant) and also in the renormalization group equations for the quark Yukawa couplings. Our discussion is based on the general phase invariant monomials built out of the CKM matrix elements and their conjugates. We show that there exist 30 fundamental phase invariant monomials and 18 of them are a product of 4 CKM matrix elements and 12 are a product of 6 CKM matrix elements. In the mainmore » theorem we show that a general rephasing invariant monomial can be expressed as a product of at most five factors: four of them are fundamental phase invariant monomials and the fifth factor consists of powers of squares of absolute values of the CKM matrix elements. We also show that the imaginary part of any rephasing invariant monomial is proportional to the Jarlskog’s invariant J or is 0.« less
Adolescent Personality: A Five-Factor Model Construct Validation

ERIC Educational Resources Information Center

Baker, Spencer T.; Victor, James B.; Chambers, Anthony L.; Halverson, Jr., Charles F.

2004-01-01

The purpose of this study was to investigate convergent and discriminant validity of the five-factor model of adolescent personality in a school setting using three different raters (methods): self-ratings, peer ratings, and teacher ratings. The authors investigated validity through a multitrait-multimethod matrix and a confirmatory factor…
A Hybrid Algorithm for Non-negative Matrix Factorization Based on Symmetric Information Divergence

PubMed Central

Devarajan, Karthik; Ebrahimi, Nader; Soofi, Ehsan

2017-01-01

The objective of this paper is to provide a hybrid algorithm for non-negative matrix factorization based on a symmetric version of Kullback-Leibler divergence, known as intrinsic information. The convergence of the proposed algorithm is shown for several members of the exponential family such as the Gaussian, Poisson, gamma and inverse Gaussian models. The speed of this algorithm is examined and its usefulness is illustrated through some applied problems. PMID:28868206
Laplace-domain waveform modeling and inversion for the 3D acoustic-elastic coupled media

NASA Astrophysics Data System (ADS)

Shin, Jungkyun; Shin, Changsoo; Calandra, Henri

2016-06-01

Laplace-domain waveform inversion reconstructs long-wavelength subsurface models by using the zero-frequency component of damped seismic signals. Despite the computational advantages of Laplace-domain waveform inversion over conventional frequency-domain waveform inversion, an acoustic assumption and an iterative matrix solver have been used to invert 3D marine datasets to mitigate the intensive computing cost. In this study, we develop a Laplace-domain waveform modeling and inversion algorithm for 3D acoustic-elastic coupled media by using a parallel sparse direct solver library (MUltifrontal Massively Parallel Solver, MUMPS). We precisely simulate a real marine environment by coupling the 3D acoustic and elastic wave equations with the proper boundary condition at the fluid-solid interface. In addition, we can extract the elastic properties of the Earth below the sea bottom from the recorded acoustic pressure datasets. As a matrix solver, the parallel sparse direct solver is used to factorize the non-symmetric impedance matrix in a distributed memory architecture and rapidly solve the wave field for a number of shots by using the lower and upper matrix factors. Using both synthetic datasets and real datasets obtained by a 3D wide azimuth survey, the long-wavelength component of the P-wave and S-wave velocity models is reconstructed and the proposed modeling and inversion algorithm are verified. A cluster of 80 CPU cores is used for this study.
On determinant representations of scalar products and form factors in the SoV approach: the XXX case

NASA Astrophysics Data System (ADS)

Kitanine, N.; Maillet, J. M.; Niccoli, G.; Terras, V.

2016-03-01

In the present article we study the form factors of quantum integrable lattice models solvable by the separation of variables (SoVs) method. It was recently shown that these models admit universal determinant representations for the scalar products of the so-called separate states (a class which includes in particular all the eigenstates of the transfer matrix). These results permit to obtain simple expressions for the matrix elements of local operators (form factors). However, these representations have been obtained up to now only for the completely inhomogeneous versions of the lattice models considered. In this article we give a simple algebraic procedure to rewrite the scalar products (and hence the form factors) for the SoV related models as Izergin or Slavnov type determinants. This new form leads to simple expressions for the form factors in the homogeneous and thermodynamic limits. To make the presentation of our method clear, we have chosen to explain it first for the simple case of the XXX Heisenberg chain with anti-periodic boundary conditions. We would nevertheless like to stress that the approach presented in this article applies as well to a wide range of models solved in the SoV framework.
Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

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

Simultaneous tensor decomposition and completion using factor priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark

2014-03-01

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.
Development of a hybrid wave based-transfer matrix model for sound transmission analysis.

PubMed

Dijckmans, A; Vermeir, G

2013-04-01

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

PubMed

Bueno, C; Sousa, C O M; Freitas, S R

2015-11-01

We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most relevant factor to explain road-kill events. To test this hypothesis, we chose vertebrates as the studied assemblage and a highway crossing in an Atlantic Forest region in southeastern Brazil as the study site. Logistic regression models were designed using presence/absence of road-kill events as dependent variables and landscape characteristics as independent variables, which were selected by Akaike's Information Criterion. We considered a set of candidate models containing four types of simple regression models: Habitat effect model; Matrix types effect models; Highway effect model; and, Reference models (intercept and buffer distance). Almost three hundred road-kills and 70 species were recorded. River proximity and herbaceous vegetation cover, both matrix effect models, were associated to most road-killed vertebrate groups. Matrix was more relevant than habitat to predict road-kill of vertebrates. The association between river proximity and road-kill indicates that rivers may be a preferential route for most species. We discuss multi-species mitigation measures and implications to movement ecology and conservation strategies.
An empirical model for polarized and cross-polarized scattering from a vegetation layer

NASA Technical Reports Server (NTRS)

Liu, H. L.; Fung, A. K.

1988-01-01

An empirical model for scattering from a vegetation layer above an irregular ground surface is developed in terms of the first-order solution for like-polarized scattering and the second-order solution for cross-polarized scattering. The effects of multiple scattering within the layer and at the surface-volume boundary are compensated by using a correction factor based on the matrix doubling method. The major feature of this model is that all parameters in the model are physical parameters of the vegetation medium. There are no regression parameters. Comparisons of this empirical model with theoretical matrix-doubling method and radar measurements indicate good agreements in polarization, angular trends, and k sub a up to 4, where k is the wave number and a is the disk radius. The computational time is shortened by a factor of 8, relative to the theoretical model calculation.
Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM

ERIC Educational Resources Information Center

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

2012-01-01

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

NASA Astrophysics Data System (ADS)

Itoyama, H.; Mironov, A.; Morozov, A.

2017-06-01

We discuss the notion of renormalization group (RG) completion of non-Gaussian Lagrangians and its treatment within the framework of Bogoliubov-Zimmermann theory in application to the matrix and tensor models. With the example of the simplest non-trivial RGB tensor theory (Aristotelian rainbow), we introduce a few methods, which allow one to connect calculations in the tensor models to those in the matrix models. As a byproduct, we obtain some new factorization formulas and sum rules for the Gaussian correlators in the Hermitian and complex matrix theories, square and rectangular. These sum rules describe correlators as solutions to finite linear systems, which are much simpler than the bilinear Hirota equations and the infinite Virasoro recursion. Search for such relations can be a way to solving the tensor models, where an explicit integrability is still obscure.
A methodology to predict damage initiation, damage growth and residual strength in titanium matrix composites

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

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

USGS Publications Warehouse

Nimmo, John R.

2016-01-01

A model for preferential flow in macropores is based on the short-range spatial distribution of soil matrix infiltrability. It uses elementary areas at two different scales. One is the traditional representative elementary area (REA), which includes a sufficient heterogeneity to typify larger areas, as for measuring field-scale infiltrability. The other, called an elementary matrix area (EMA), is smaller, but large enough to represent the local infiltrability of soil matrix material, between macropores. When water is applied to the land surface, each EMA absorbs water up to the rate of its matrix infiltrability. Excess water flows into a macropore, becoming preferential flow. The land surface then can be represented by a mesoscale (EMA-scale) distribution of matrix infiltrabilities. Total preferential flow at a given depth is the sum of contributions from all EMAs. Applying the model, one case study with multi-year field measurements of both preferential and diffuse fluxes at a specific depth was used to obtain parameter values by inverse calculation. The results quantify the preferential–diffuse partition of flow from individual storms that differed in rainfall amount, intensity, antecedent soil water, and other factors. Another case study provided measured values of matrix infiltrability to estimate parameter values for comparison and illustrative predictions. These examples give a self-consistent picture from the combination of parameter values, directions of sensitivities, and magnitudes of differences caused by different variables. One major practical use of this model is to calculate the dependence of preferential flow on climate-related factors, such as varying soil wetness and rainfall intensity.
On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage.

PubMed

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J; Vernerey, Franck J

2013-03-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one's quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. Copyright © 2012 Elsevier Ltd. All rights reserved.
On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage

PubMed Central

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J.; Vernerey, Franck J.

2012-01-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one’s quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. PMID:23276516
Nonlinear hyperspectral unmixing based on sparse non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Li, Jing; Li, Xiaorun; Zhao, Liaoying

2016-01-01

Hyperspectral unmixing aims at extracting pure material spectra, accompanied by their corresponding proportions, from a mixed pixel. Owing to modeling more accurate distribution of real material, nonlinear mixing models (non-LMM) are usually considered to hold better performance than LMMs in complicated scenarios. In the past years, numerous nonlinear models have been successfully applied to hyperspectral unmixing. However, most non-LMMs only think of sum-to-one constraint or positivity constraint while the widespread sparsity among real materials mixing is the very factor that cannot be ignored. That is, for non-LMMs, a pixel is usually composed of a few spectral signatures of different materials from all the pure pixel set. Thus, in this paper, a smooth sparsity constraint is incorporated into the state-of-the-art Fan nonlinear model to exploit the sparsity feature in nonlinear model and use it to enhance the unmixing performance. This sparsity-constrained Fan model is solved with the non-negative matrix factorization. The algorithm was implemented on synthetic and real hyperspectral data and presented its advantage over those competing algorithms in the experiments.
A penny-shaped crack in a filament-reinforced matrix. I - The filament model. II - The crack problem

NASA Technical Reports Server (NTRS)

Erdogan, F.; Pacella, A. H.

1974-01-01

The study deals with the elastostatic problem of a penny-shaped crack in an elastic matrix which is reinforced by filaments or fibers perpendicular to the plane of the crack. An elastic filament model is first developed, followed by consideration of the application of the model to the penny-shaped crack problem in which the filaments of finite length are asymmetrically distributed around the crack. Since the primary interest is in the application of the results to studies relating to the fracture of fiber or filament-reinforced composites and reinforced concrete, the main emphasis of the study is on the evaluation of the stress intensity factor along the periphery of the crack, the stresses in the filaments or fibers, and the interface shear between the matrix and the filaments or fibers. Using the filament model developed, the elastostatic interaction problem between a penny-shaped crack and a slender inclusion or filament in an elastic matrix is formulated.
Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype method based on the quantitative genetics model towards the utilization of functional and structural genomic information for genomic prediction and estimation.
Reusable launch vehicle model uncertainties impact analysis

NASA Astrophysics Data System (ADS)

Chen, Jiaye; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

2018-03-01

Reusable launch vehicle(RLV) has the typical characteristics of complex aerodynamic shape and propulsion system coupling, and the flight environment is highly complicated and intensely changeable. So its model has large uncertainty, which makes the nominal system quite different from the real system. Therefore, studying the influences caused by the uncertainties on the stability of the control system is of great significance for the controller design. In order to improve the performance of RLV, this paper proposes the approach of analyzing the influence of the model uncertainties. According to the typical RLV, the coupling dynamic and kinematics models are built. Then different factors that cause uncertainties during building the model are analyzed and summed up. After that, the model uncertainties are expressed according to the additive uncertainty model. Choosing the uncertainties matrix's maximum singular values as the boundary model, and selecting the uncertainties matrix's norm to show t how much the uncertainty factors influence is on the stability of the control system . The simulation results illustrate that the inertial factors have the largest influence on the stability of the system, and it is necessary and important to take the model uncertainties into consideration before the designing the controller of this kind of aircraft( like RLV, etc).
Computationally efficient modeling and simulation of large scale systems

NASA Technical Reports Server (NTRS)

Jain, Jitesh (Inventor); Cauley, Stephen F. (Inventor); Li, Hong (Inventor); Koh, Cheng-Kok (Inventor); Balakrishnan, Venkataramanan (Inventor)

2010-01-01

A method of simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof. A matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure are obtained where the element values for each matrix include inductance L and inverse capacitance P. An adjacency matrix A associated with the interconnect structure is obtained. Numerical integration is used to solve first and second equations, each including as a factor the product of the inverse matrix X.sup.1 and at least one other matrix, with first equation including X.sup.1Y, X.sup.1A, and X.sup.1P, and the second equation including X.sup.1A and X.sup.1P.
Approximate method of variational Bayesian matrix factorization/completion with sparse prior

NASA Astrophysics Data System (ADS)

Kawasumi, Ryota; Takeda, Koujin

2018-05-01

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

ERIC Educational Resources Information Center

Peeters, Carel F. W.

2012-01-01

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

PubMed

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.
Optimization and critical evaluation of decellularization strategies to develop renal extracellular matrix scaffolds as biological templates for organ engineering and transplantation.

PubMed

Caralt, M; Uzarski, J S; Iacob, S; Obergfell, K P; Berg, N; Bijonowski, B M; Kiefer, K M; Ward, H H; Wandinger-Ness, A; Miller, W M; Zhang, Z J; Abecassis, M M; Wertheim, J A

2015-01-01

The ability to generate patient-specific cells through induced pluripotent stem cell (iPSC) technology has encouraged development of three-dimensional extracellular matrix (ECM) scaffolds as bioactive substrates for cell differentiation with the long-range goal of bioengineering organs for transplantation. Perfusion decellularization uses the vasculature to remove resident cells, leaving an intact ECM template wherein new cells grow; however, a rigorous evaluative framework assessing ECM structural and biochemical quality is lacking. To address this, we developed histologic scoring systems to quantify fundamental characteristics of decellularized rodent kidneys: ECM structure (tubules, vessels, glomeruli) and cell removal. We also assessed growth factor retention--indicating matrix biofunctionality. These scoring systems evaluated three strategies developed to decellularize kidneys (1% Triton X-100, 1% Triton X-100/0.1% sodium dodecyl sulfate (SDS) and 0.02% Trypsin-0.05% EGTA/1% Triton X-100). Triton and Triton/SDS preserved renal microarchitecture and retained matrix-bound basic fibroblast growth factor and vascular endothelial growth factor. Trypsin caused structural deterioration and growth factor loss. Triton/SDS-decellularized scaffolds maintained 3 h of leak-free blood flow in a rodent transplantation model and supported repopulation with human iPSC-derived endothelial cells and tubular epithelial cells ex vivo. Taken together, we identify an optimal Triton/SDS-based decellularization strategy that produces a biomatrix that may ultimately serve as a rodent model for kidney bioengineering. © Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.

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

PubMed

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

2006-01-01

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

NASA Astrophysics Data System (ADS)

Hao, Ming; Bryant, Stephen H.; Wang, Yanli

2017-01-01

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.
Inelastic deformation of metal matrix composites

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

DOE PAGES

Johnson, Calvin W.; Ormand, W. Erich; Krastev, Plamen G.

2013-08-07

One approach for solving interacting many-fermion systems is the configuration-interaction method, also sometimes called the interacting shell model, where one finds eigenvalues of the Hamiltonian in a many-body basis of Slater determinants (antisymmetrized products of single-particle wavefunctions). The resulting Hamiltonian matrix is typically very sparse, but for large systems the nonzero matrix elements can nonetheless require terabytes or more of storage. An alternate algorithm, applicable to a broad class of systems with symmetry, in our case rotational invariance, is to exactly factorize both the basis and the interaction using additive/multiplicative quantum numbers; such an algorithm recreates the many-body matrix elementsmore » on the fly and can reduce the storage requirements by an order of magnitude or more. Here, we discuss factorization in general and introduce a novel, generalized factorization method, essentially a ‘double-factorization’ which speeds up basis generation and set-up of required arrays. Although we emphasize techniques, we also place factorization in the context of a specific (unpublished) configuration-interaction code, BIGSTICK, which runs both on serial and parallel machines, and discuss the savings in memory due to factorization.« less
Mechanical Properties of Nanostructured Materials Determined Through Molecular Modeling Techniques

NASA Technical Reports Server (NTRS)

Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The potential for gains in material properties over conventional materials has motivated an effort to develop novel nanostructured materials for aerospace applications. These novel materials typically consist of a polymer matrix reinforced with particles on the nanometer length scale. In this study, molecular modeling is used to construct fully atomistic models of a carbon nanotube embedded in an epoxy polymer matrix. Functionalization of the nanotube which consists of the introduction of direct chemical bonding between the polymer matrix and the nanotube, hence providing a load transfer mechanism, is systematically varied. The relative effectiveness of functionalization in a nanostructured material may depend on a variety of factors related to the details of the chemical bonding and the polymer structure at the nanotube-polymer interface. The objective of this modeling is to determine what influence the details of functionalization of the carbon nanotube with the polymer matrix has on the resulting mechanical properties. By considering a range of degree of functionalization, the structure-property relationships of these materials is examined and mechanical properties of these models are calculated using standard techniques.
Factors that impact the stability of vitamin C at intermediate temperatures in a food matrix.

PubMed

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.
Highly parallel sparse Cholesky factorization

NASA Technical Reports Server (NTRS)

Gilbert, John R.; Schreiber, Robert

1990-01-01

Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms.
A computational model of in vitro angiogenesis based on extracellular matrix fibre orientation.

PubMed

Edgar, Lowell T; Sibole, Scott C; Underwood, Clayton J; Guilkey, James E; Weiss, Jeffrey A

2013-01-01

Recent interest in the process of vascularisation within the biomedical community has motivated numerous new research efforts focusing on the process of angiogenesis. Although the role of chemical factors during angiogenesis has been well documented, the role of mechanical factors, such as the interaction between angiogenic vessels and the extracellular matrix, remains poorly understood. In vitro methods for studying angiogenesis exist; however, measurements available using such techniques often suffer from limited spatial and temporal resolutions. For this reason, computational models have been extensively employed to investigate various aspects of angiogenesis. This paper outlines the formulation and validation of a simple and robust computational model developed to accurately simulate angiogenesis based on length, branching and orientation morphometrics collected from vascularised tissue constructs. Microvessels were represented as a series of connected line segments. The morphology of the vessels was determined by a linear combination of the collagen fibre orientation, the vessel density gradient and a random walk component. Excellent agreement was observed between computational and experimental morphometric data over time. Computational predictions of microvessel orientation within an anisotropic matrix correlated well with experimental data. The accuracy of this modelling approach makes it a valuable platform for investigating the role of mechanical interactions during angiogenesis.
Augmenting matrix factorization technique with the combination of tags and genres

NASA Astrophysics Data System (ADS)

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.
Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM.

PubMed

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

2012-07-01

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

PubMed

Xu, Jiao; Shi, Guo-Liang; Guo, Chang-Sheng; Wang, Hai-Ting; Tian, Ying-Ze; Huangfu, Yan-Qi; Zhang, Yuan; Feng, Yin-Chang; Xu, Jian

2018-01-01

A hybrid model based on the positive matrix factorization (PMF) model and the health risk assessment model for assessing risks associated with sources of perfluoroalkyl substances (PFASs) in water was established and applied at Dianchi Lake to test its applicability. The new method contains 2 stages: 1) the sources of PFASs were apportioned by the PMF model and 2) the contribution of health risks from each source was calculated by the new hybrid model. Two factors were extracted by PMF, with factor 1 identified as aqueous fire-fighting foams source and factor 2 as fluoropolymer manufacturing and processing and perfluorooctanoic acid production source. The health risk of PFASs in the water assessed by the health risk assessment model was 9.54 × 10 -7 a -1 on average, showing no obvious adverse effects to human health. The 2 sources' risks estimated by the new hybrid model ranged from 2.95 × 10 -10 to 6.60 × 10 -6 a -1 and from 1.64 × 10 -7 to 1.62 × 10 -6 a -1 , respectively. The new hybrid model can provide useful information on the health risks of PFAS sources, which is helpful for pollution control and environmental management. Environ Toxicol Chem 2018;37:107-115. © 2017 SETAC. © 2017 SETAC.
Lattice Boltzmann simulation of dissolution-induced changes in permeability and porosity in 3D CO2 reactive transport

NASA Astrophysics Data System (ADS)

Tian, Zhiwei; Wang, Junye

2018-02-01

Dissolution and precipitation of rock matrix are one of the most important processes of geological CO2 sequestration in reservoirs. They change connections of pore channels and properties of matrix, such as bulk density, microporosity and hydraulic conductivity. This study builds on a recently developed multi-layer model to account for dynamic changes of microporous matrix that can accurately predict variations in hydraulic properties and reaction rates due to dynamic changes in matrix porosity and pore connectivity. We apply the model to simulate the dissolution and precipitation processes of rock matrix in heterogeneous porous media to quantify (1) the effect of the reaction rate on dissolution and matrix porosity, (2) the effect of microporous matrix diffusion on the overall effective diffusion and (3) the effect of heterogeneity on hydraulic conductivity. The results show the CO2 storage influenced by factors including the matrix porosity change, reaction front movement, velocity and initial properties. We also simulated dissolution-induced permeability enhancement as well as effects of initial porosity heterogeneity. The matrix with very low permeability, which can be unresolved on X-ray CT, do contribute to flow patterns and dispersion. The concentration of reactant H+ increases along the main fracture paths where the flow velocity increases. The product Ca++ shows the inversed distribution pattern against the H+ concentration. This demonstrates the capability of this model to investigate the complex CO2 reactive transport in real 3D heterogeneous porous media.
An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

PubMed

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.
Endothelial cell-derived matrix promotes the metabolic functional maturation of hepatocyte via integrin-Src signalling.

PubMed

Guo, Xinyue; Li, Weihong; Ma, Minghui; Lu, Xin; Zhang, Haiyan

2017-11-01

The extracellular matrix (ECM) microenvironment is involved in the regulation of hepatocyte phenotype and function. Recently, the cell-derived extracellular matrix has been proposed to represent the bioactive and biocompatible materials of the native ECM. Here, we show that the endothelial cell-derived matrix (EC matrix) promotes the metabolic maturation of human adipose stem cell-derived hepatocyte-like cells (hASC-HLCs) through the activation of the transcription factor forkhead box protein A2 (FOXA2) and the nuclear receptors hepatocyte nuclear factor 4 alpha (HNF4α) and pregnane X receptor (PXR). Reducing the fibronectin content in the EC matrix or silencing the expression of α5 integrin in the hASC-HLCs inhibited the effect of the EC matrix on Src phosphorylation and hepatocyte maturation. The inhibition of Src phosphorylation using the inhibitor PP2 or silencing the expression of Src in hASC-HLCs also attenuated the up-regulation of the metabolic function of hASC-HLCs in a nuclear receptor-dependent manner. These data elucidate integrin-Src signalling linking the extrinsic EC matrix signals and metabolic functional maturation of hepatocyte. This study provides a model for studying the interaction between hepatocytes and non-parenchymal cell-derived matrix. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.
Optimization of matrix tablets controlled drug release using Elman dynamic neural networks and decision trees.

PubMed

Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele; Đurić, Zorica

2012-05-30

The main objective of the study was to develop artificial intelligence methods for optimization of drug release from matrix tablets regardless of the matrix type. Static and dynamic artificial neural networks of the same topology were developed to model dissolution profiles of different matrix tablets types (hydrophilic/lipid) using formulation composition, compression force used for tableting and tablets porosity and tensile strength as input data. Potential application of decision trees in discovering knowledge from experimental data was also investigated. Polyethylene oxide polymer and glyceryl palmitostearate were used as matrix forming materials for hydrophilic and lipid matrix tablets, respectively whereas selected model drugs were diclofenac sodium and caffeine. Matrix tablets were prepared by direct compression method and tested for in vitro dissolution profiles. Optimization of static and dynamic neural networks used for modeling of drug release was performed using Monte Carlo simulations or genetic algorithms optimizer. Decision trees were constructed following discretization of data. Calculated difference (f(1)) and similarity (f(2)) factors for predicted and experimentally obtained dissolution profiles of test matrix tablets formulations indicate that Elman dynamic neural networks as well as decision trees are capable of accurate predictions of both hydrophilic and lipid matrix tablets dissolution profiles. Elman neural networks were compared to most frequently used static network, Multi-layered perceptron, and superiority of Elman networks have been demonstrated. Developed methods allow simple, yet very precise way of drug release predictions for both hydrophilic and lipid matrix tablets having controlled drug release. Copyright © 2012 Elsevier B.V. All rights reserved.
A plasma-based biomatrix mixed with endothelial progenitor cells and keratinocytes promotes matrix formation, angiogenesis, and reepithelialization in full-thickness wounds.

PubMed

Vermeulen, Pieter; Dickens, Stijn; Degezelle, Karlien; Van den Berge, Stefaan; Hendrickx, Benoit; Vranckx, Jan Jeroen

2009-07-01

In search of an autologous vascularized skin substitute, we treated full-thickness wounds (FTWs) with autologous platelet-rich plasma gel (APG) in which we embedded endothelial progenitor cells (EPCs) and basal cell keratinocytes (KCs). We cultivated autologous KCs in low-serum conditions and expanded autologous EPCs from venous blood. FTWs (n = 55) were created on the backs of four pigs, covered with wound chambers, and randomly assigned to the following treatments: (1) APG, (2) APG + KCs, (3) APG + EPCs, (4) APG + KCs + EPCs, and (5) saline. All wounds were biopsied to measure neovascularization (lectin Bandeiraea Simplicifolia-1 (BS-1), alpha smooth muscle actin [alphaSMA], and membrane type 1 matrix metalloproteinase (MT1-MMP)), matrix deposition (fibronectin, collagen type I/III, and alphavbeta3), and reepithelialization. Wound fluids were analyzed for protein expression. All APG-treated wounds showed more vascular structures (p < 0.001), and the addition of EPCs further improved neovascularization, as confirmed by higher lectin, alphaSMA, and MT1-MMP. APG groups had higher collagen I/III (p < 0.05), alphavbeta3, and fibronectin content (p < 0.001), and they exhibited higher concentrations of platelet-derived growth factor subunit bb, basic fibroblast growth factor, hepatocyte growth factor, insulin growth factor-1, transforming growth factor-beta1 and -beta3, matrix metalloproteinase-1 and -z9, and tissue-inhibiting matrix metalloproteinase-1 and -2. Applying APG + KCs resulted in the highest reepithelialization rates (p < 0.001). No differences were found for wound contraction by planimetry. In this porcine FTW model, APG acts as a supportive biomatrix that, along with the embedded cells, improves extracellular matrix organization, promotes angiogenesis, and accelerates reepithelialization.
A new experimental design method to optimize formulations focusing on a lubricant for hydrophilic matrix tablets.

PubMed

Choi, Du Hyung; Shin, Sangmun; Khoa Viet Truong, Nguyen; Jeong, Seong Hoon

2012-09-01

A robust experimental design method was developed with the well-established response surface methodology and time series modeling to facilitate the formulation development process with magnesium stearate incorporated into hydrophilic matrix tablets. Two directional analyses and a time-oriented model were utilized to optimize the experimental responses. Evaluations of tablet gelation and drug release were conducted with two factors x₁ and x₂: one was a formulation factor (the amount of magnesium stearate) and the other was a processing factor (mixing time), respectively. Moreover, different batch sizes (100 and 500 tablet batches) were also evaluated to investigate an effect of batch size. The selected input control factors were arranged in a mixture simplex lattice design with 13 experimental runs. The obtained optimal settings of magnesium stearate for gelation were 0.46 g, 2.76 min (mixing time) for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The optimal settings for drug release were 0.33 g, 7.99 min for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The exact ratio and mixing time of magnesium stearate could be formulated according to the resulting hydrophilic matrix tablet properties. The newly designed experimental method provided very useful information for characterizing significant factors and hence to obtain optimum formulations allowing for a systematic and reliable experimental design method.
Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes.

PubMed

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Xu, Richard Yi Da; Luo, Xiangfeng

2018-05-01

Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.
Two-faced property of a market factor in asset pricing and diversification effect

NASA Astrophysics Data System (ADS)

Eom, Cheoljun

2017-04-01

This study empirically investigates the test hypothesis that a market factor acting as a representative common factor in the pricing models has a negative influence on constructing a well-diversified portfolio from the Markowitz mean-variance optimization function (MVOF). We use the comparative correlation matrix (C-CM) method to control a single eigenvalue among all eigenvalues included in the sample correlation matrix (S-CM), through the random matrix theory (RMT). In particular, this study observes the effect of the largest eigenvalue that has the property of the market factor. According to the results, the largest eigenvalue has the highest explanatory power on the stock return changes. The C-CM without the largest eigenvalue in the S-CM constructs a more diversified portfolio capable of improving the practical applicability of the MVOF. Moreover, the more diversified portfolio constructed from this C-CM has better out-of-sample performance in the future period. These results support the test hypothesis for the two-faced property of the market factor, defined by the largest eigenvalue.

Translucent Radiosity: Efficiently Combining Diffuse Inter-Reflection and Subsurface Scattering.

PubMed

Sheng, Yu; Shi, Yulong; Wang, Lili; Narasimhan, Srinivasa G

2014-07-01

It is hard to efficiently model the light transport in scenes with translucent objects for interactive applications. The inter-reflection between objects and their environments and the subsurface scattering through the materials intertwine to produce visual effects like color bleeding, light glows, and soft shading. Monte-Carlo based approaches have demonstrated impressive results but are computationally expensive, and faster approaches model either only inter-reflection or only subsurface scattering. In this paper, we present a simple analytic model that combines diffuse inter-reflection and isotropic subsurface scattering. Our approach extends the classical work in radiosity by including a subsurface scattering matrix that operates in conjunction with the traditional form factor matrix. This subsurface scattering matrix can be constructed using analytic, measurement-based or simulation-based models and can capture both homogeneous and heterogeneous translucencies. Using a fast iterative solution to radiosity, we demonstrate scene relighting and dynamically varying object translucencies at near interactive rates.
Stage-Structured Population Dynamics of AEDES AEGYPTI

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Budin, Harun; Ismail, Salemah

Aedes aegypti is the main vector in the transmission of dengue fever, a vector-borne disease affecting world population living in tropical and sub-tropical countries. Better understanding of the dynamics of its population growth will help in the efforts of controlling the spread of this disease. In looking at the population dynamics of Aedes aegypti, this paper explored the stage-structured modeling of the population growth of the mosquito using the matrix population model. The life cycle of the mosquito was divided into five stages: eggs, larvae, pupae, adult1 and adult2. Developmental rates were obtained for the average Malaysian temperature and these were used in constructing the transition matrix for the matrix model. The model, which was based only on temperature, projected that the population of Aedes aegypti will blow up with time, which is not realistic. For further work, other factors need to be taken into account to obtain a more realistic result.
Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach

NASA Astrophysics Data System (ADS)

Tsai, Bi-Huei; Chang, Chih-Huei

2009-08-01

Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.
Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

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

PubMed

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

PubMed

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 entities. The source code for MFLDA is available at: http://mlda.swu.edu.cn/codes.php? name = MFLDA. gxyu@swu.edu.cn. Supplementary data are available at Bioinformatics online.
Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

NASA Astrophysics Data System (ADS)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.
Multi-Scale Multi-Physics Modeling of Matrix Transport Properties in Fractured Shale Reservoirs

NASA Astrophysics Data System (ADS)

Mehmani, A.; Prodanovic, M.

2014-12-01

Understanding the shale matrix flow behavior is imperative in successful reservoir development for hydrocarbon production and carbon storage. Without a predictive model, significant uncertainties in flowback from the formation, the communication between the fracture and matrix as well as proper fracturing practice will ensue. Informed by SEM images, we develop deterministic network models that couple pores from multiple scales and their respective fluid physics. The models are used to investigate sorption hysteresis as an affordable way of inferring the nanoscale pore structure in core scale. In addition, restricted diffusion as a function of pore shape, pore-throat size ratios and network connectivity is computed to make correct interpretation of the 2D NMR maps possible. Our novel pore network models have the ability to match sorption hysteresis measurements without any tuning parameters. The results clarify a common misconception of linking type 3 nitrogen hysteresis curves to only the shale pore shape and show promising sensitivty for nanopore structre inference in core scale. The results on restricted diffusion shed light on the importance of including shape factors in 2D NMR interpretations. A priori "weighting factors" as a function of pore-throat and throat-length ratio are presented and the effect of network connectivity on diffusion is quantitatively assessed. We are currently working on verifying our models with experimental data gathered from the Eagleford formation.
SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS

EPA Science Inventory

Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...
Source apportionment of stack emissions from research and development facilities using positive matrix factorization

NASA Astrophysics Data System (ADS)

Ballinger, Marcel Y.; Larson, Timothy V.

2014-12-01

Research and development (R&D) facility emissions are difficult to characterize due to their variable processes, changing nature of research, and large number of chemicals. Positive matrix factorization (PMF) was applied to volatile organic compound (VOC) concentrations measured in the main exhaust stacks of four different R&D buildings to identify the number and composition of major contributing sources. PMF identified between 9 and 11 source-related factors contributing to stack emissions, depending on the building. Similar factors between buildings were major contributors to trichloroethylene (TCE), acetone, and ethanol emissions; other factors had similar profiles for two or more buildings but not all four. At least one factor for each building was identified that contained a broad mix of many species and constraints were used in PMF to modify the factors to resemble more closely the off-shift concentration profiles. PMF accepted the constraints with little decrease in model fit.
Relativistic, model-independent, multichannel 2 → 2 transition amplitudes in a finite volume

DOE PAGES

Briceno, Raul A.; Hansen, Maxwell T.

2016-07-13

We derive formalism for determining 2 + J → 2 infinite-volume transition amplitudes from finite-volume matrix elements. Specifically, we present a relativistic, model-independent relation between finite-volume matrix elements of external currents and the physically observable infinite-volume matrix elements involving two-particle asymptotic states. The result presented holds for states composed of two scalar bosons. These can be identical or non-identical and, in the latter case, can be either degenerate or non-degenerate. We further accommodate any number of strongly-coupled two-scalar channels. This formalism will, for example, allow future lattice QCD calculations of themore » $$\\rho$$-meson form factor, in which the unstable nature of the $$\\rho$$ is rigorously accommodated. In conclusion, we also discuss how this work will impact future extractions of nuclear parity and hadronic long-range matrix elements from lattice QCD.« less
UTOPIAN: user-driven topic modeling based on interactive nonnegative matrix factorization.

PubMed

Choo, Jaegul; Lee, Changhyun; Reddy, Chandan K; Park, Haesun

2013-12-01

Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets.
Nonconvex Model of Material Growth: Mathematical Theory

NASA Astrophysics Data System (ADS)

Ganghoffer, J. F.; Plotnikov, P. I.; Sokolowski, J.

2018-06-01

The model of volumetric material growth is introduced in the framework of finite elasticity. The new results obtained for the model are presented with complete proofs. The state variables include the deformations, temperature and the growth factor matrix function. The existence of global in time solutions for the quasistatic deformations boundary value problem coupled with the energy balance and the evolution of the growth factor is shown. The mathematical results can be applied to a wide class of growth models in mechanics and biology.
A DEIM Induced CUR Factorization

DTIC Science & Technology

2015-09-18

CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given matrix A, such a factorization provides a...CUR approximations based on leverage scores. 1 Introduction This work presents a new CUR matrix factorization based upon the Discrete Empirical...SUPPLEMENTARY NOTES 14. ABSTRACT We derive a CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given
Engineering Breast Cancer Microenvironments and 3D Bioprinting

PubMed Central

Belgodere, Jorge A.; King, Connor T.; Bursavich, Jacob B.; Burow, Matthew E.; Martin, Elizabeth C.; Jung, Jangwook P.

2018-01-01

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal–cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments. PMID:29881724
A comparison of analysis tools for predicting the inelastic cyclic response of cross-ply titanium matrix composites

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

Kroupa, J.L.; Coker, D.; Neu, R.W.

1996-12-31

Several micromechanical models that are currently being used for predicting the thermal and mechanical behavior of a cross-ply, [0/90], titanium matrix composite are evaluated. Six computer programs or methods are compared: (1) VISCOPLY; (2) METCAN; (3) FIDEP, an enhanced concentric cylinder model; (4) LISOL, a modified method of cells approach; (5) an elementary approach where the [90] ply is assumed to have the same properties as the matrix; and (6) a finite element method. Comparisons are made for the thermal residual stresses at room temperature resulting from processing, as well as for stresses and strains in two isothermal and twomore » thermomechanical fatigue test cases. For each case, the laminate response of the models is compared to experimental behavior, while the responses of the constituents are compared among the models. The capability of each model to predict frequency effects, inelastic cyclic strain (hysteresis) behavior, and strain ratchetting with cycling is shown. The basis of formulation for the micromechanical models, the constitutive relationships used for the matrix and fiber, and the modeling technique of the [90] ply are all found to be important factors for determining the accurate behavior of the [0/90] composite.« less
Application of the Backward-Smoothing Extended Kalman Filter to Attitude Estimation and Prediction using Radar Observations

DTIC Science & Technology

2009-06-01

projection, the measurement matrix is of rank 3. This is known as the rank theorem and enables the matrix Y to be factored into the product of two...Interface 270 6.5.5. Bistatic Radar Measurements 271 6.5.6. Computer Aided Image-Model Matching 273 8 6.5.7. Tomasi-Kanade Factorization Method...the vectors of an orthonormal basis satisfy the following scalar- product relations (2 p. 239): = i. ir = n (2.1) i-j = i-k j-k 0 i-i= j • j = k-k
Boundary formulations for sensitivity analysis without matrix derivatives

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

ERIC Educational Resources Information Center

Krijnen, Wim P.

2006-01-01

For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…
On the Extraction of Components and the Applicability of the Factor Model.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Harris, Chester W.

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

DEVELOPMENT AND EVALUATION OF PM 2.5 SOURCE APPORTIONMENT METHODOLOGIES

EPA Science Inventory

The receptor model called Positive Matrix Factorization (PMF) has been extensively used to apportion sources of ambient fine particulate matter (PM_2.5), but the accuracy of source apportionment results currently remains unknown. In addition, air quality forecast model...
WAIS-IV subtest covariance structure: conceptual and statistical considerations.

PubMed

Ward, L Charles; Bergman, Maria A; Hebert, Katina R

2012-06-01

D. Wechsler (2008b) reported confirmatory factor analyses (CFAs) with standardization data (ages 16-69 years) for 10 core and 5 supplemental subtests from the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). Analyses of the 15 subtests supported 4 hypothesized oblique factors (Verbal Comprehension, Working Memory, Perceptual Reasoning, and Processing Speed) but also revealed unexplained covariance between Block Design and Visual Puzzles (Perceptual Reasoning subtests). That covariance was not included in the final models. Instead, a path was added from Working Memory to Figure Weights (Perceptual Reasoning subtest) to improve fit and achieve a desired factor pattern. The present research with the same data (N = 1,800) showed that the path from Working Memory to Figure Weights increases the association between Working Memory and Matrix Reasoning. Specifying both paths improves model fit and largely eliminates unexplained covariance between Block Design and Visual Puzzles but with the undesirable consequence that Figure Weights and Matrix Reasoning are equally determined by Perceptual Reasoning and Working Memory. An alternative 4-factor model was proposed that explained theory-implied covariance between Block Design and Visual Puzzles and between Arithmetic and Figure Weights while maintaining compatibility with WAIS-IV Index structure. The proposed model compared favorably with a 5-factor model based on Cattell-Horn-Carroll theory. The present findings emphasize that covariance model comparisons should involve considerations of conceptual coherence and theoretical adherence in addition to statistical fit. (c) 2012 APA, all rights reserved
A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.
Partial Least Squares Regression Models for the Analysis of Kinase Signaling.

PubMed

Bourgeois, Danielle L; Kreeger, Pamela K

2017-01-01

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

PubMed

Rhoades, Elizabeth R; Geisel, Rachel E; Butcher, Barbara A; McDonough, Sean; Russell, David G

2005-05-01

The chronic inflammatory response to Mycobacterium generates complex granulomatous lesions that balance containment with destruction of infected tissues. To study the contributing factors from host and pathogen, we developed a model wherein defined mycobacterial components and leukocytes are delivered in a gel, eliciting a localized response that can be retrieved and analysed. We validated the model by comparing responses to the cell wall lipids from Mycobacterium bovis bacillus Calmette-Guerin (BCG) to reported activities in other models. BCG lipid-coated beads and bone marrow-derived macrophages (input macrophages) were injected intraperitoneally into BALB/c mice. Input macrophages and recruited peritoneal exudate cells took up fluorescently tagged BCG lipids, and matrix-associated macrophages and neutrophils produced tumor necrosis factor, interleukin-1alpha, and interleukin-6. Leukocyte numbers and cytokine levels were greater in BCG lipid-bearing matrices than matrices containing non-coated or phosphatidylglycerol-coated beads. Leukocytes arrived in successive waves of neutrophils, macrophages and eosinophils, followed by NK and T cells (CD4(+), CD8(+), or gammadelta) at 7 days and B cells within 12 days. BCG lipids also predisposed matrices for adherence and vascularization, enhancing cellular recruitment. We submit that the matrix model presents pertinent features of the murine granulomatous response that will prove to be an adaptable method for study of this complex response.
Arrowheaded enhanced multivariance products representation for matrices (AEMPRM): Specifically focusing on infinite matrices and converting arrowheadedness to tridiagonality

NASA Astrophysics Data System (ADS)

Özdemir, Gizem; Demiralp, Metin

2015-12-01

In this work, Enhanced Multivariance Products Representation (EMPR) approach which is a Demiralp-and-his- group extension to the Sobol's High Dimensional Model Representation (HDMR) has been used as the basic tool. Their discrete form have also been developed and used in practice by Demiralp and his group in addition to some other authors for the decomposition of the arrays like vectors, matrices, or multiway arrays. This work specifically focuses on the decomposition of infinite matrices involving denumerable infinitely many rows and columns. To this end the target matrix is first decomposed to the sum of certain outer products and then each outer product is treated by Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) which has been developed by Demiralp and his group. The result is a three-matrix- factor-product whose kernel (the middle factor) is an arrowheaded matrix while the pre and post factors are invertable matrices decomposed of the support vectors of TMEMPR. This new method is called as Arrowheaded Enhanced Multivariance Products Representation for Matrices. The general purpose is approximation of denumerably infinite matrices with the new method.
USE OF A CONVECTION-DIFFUSION MODEL TO UNDERSTAND GASTROINTESTINAL ABSORPTION OF ENVIRONMENTALLY-RELEVANT CHEMICALS

EPA Science Inventory

Understanding the factors that affect the gastrointestinal absorption of chemicals is important to predicting the delivered systemic dose of chemicals following exposure in food, water, and other media. Two factors of particular interest are the effects of a matrix to which th...
Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

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

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

Detwiler, Russell

Matrix diffusion and adsorption within a rock matrix are widely regarded as important mechanisms for retarding the transport of radionuclides and other solutes in fractured rock (e.g., Neretnieks, 1980; Tang et al., 1981; Maloszewski and Zuber, 1985; Novakowski and Lapcevic, 1994; Jardine et al., 1999; Zhou and Xie, 2003; Reimus et al., 2003a,b). When remediation options are being evaluated for old sources of contamination, where a large fraction of contaminants reside within the rock matrix, slow diffusion out of the matrix greatly increases the difficulty and timeframe of remediation. Estimating the rates of solute exchange between fractures and the adjacentmore » rock matrix is a critical factor in quantifying immobilization and/or remobilization of DOE-relevant contaminants within the subsurface. In principle, the most rigorous approach to modeling solute transport with fracture-matrix interaction would be based on local-scale coupled advection-diffusion/dispersion equations for the rock matrix and in discrete fractures that comprise the fracture network (Discrete Fracture Network and Matrix approach, hereinafter referred to as DFNM approach), fully resolving aperture variability in fractures and matrix property heterogeneity. However, such approaches are computationally demanding, and thus, many predictive models rely upon simplified models. These models typically idealize fracture rock masses as a single fracture or system of parallel fractures interacting with slabs of porous matrix or as a mobile-immobile or multi-rate mass transfer system. These idealizations provide tractable approaches for interpreting tracer tests and predicting contaminant mobility, but rely upon a fitted effective matrix diffusivity or mass-transfer coefficients. However, because these fitted parameters are based upon simplified conceptual models, their effectiveness at predicting long-term transport processes remains uncertain. Evidence of scale dependence of effective matrix diffusion coefficients obtained from tracer tests highlights this point and suggests that the underlying mechanisms and relationship between rock and fracture properties are not fully understood in large complex fracture networks. In this project, we developed a high-resolution DFN model of solute transport in fracture networks to explore and quantify the mechanisms that control transport in complex fracture networks and how these may give rise to observed scale-dependent matrix diffusion coefficients. Results demonstrate that small scale heterogeneity in the flow field caused by local aperture variability within individual fractures can lead to long-tailed breakthrough curves indicative of matrix diffusion, even in the absence of interactions with the fracture matrix. Furthermore, the temporal and spatial scale dependence of these processes highlights the inability of short-term tracer tests to estimate transport parameters that will control long-term fate and transport of contaminants in fractured aquifers.« less
Source apportionment of VOCs in the Los Angeles area using positive matrix factorization

NASA Astrophysics Data System (ADS)

Brown, Steven G.; Frankel, Anna; Hafner, Hilary R.

Eight 3-h speciated hydrocarbon measurements were collected daily by the South Coast Air Quality Management District (SCAQMD) as part of the Photochemical Assessment Monitoring Stations (PAMS) program during the summers of 2001-03 at two sites in the Los Angeles air basin, Azusa and Hawthorne. Over 30 hydrocarbons from over 500 samples at Azusa and 600 samples at Hawthorne were subsequently analyzed using the multivariate receptor model positive matrix factorization (PMF). At Azusa and Hawthorne, five and six factors were identified, respectively, with a good comparison between predicted and measured mass. At Azusa, evaporative emissions (a median of 31% of the total mass), motor vehicle exhaust (22%), liquid/unburned gasoline (27%), coatings (17%), and biogenic emissions (3%) factors were identified. Factors identified at Hawthorne were evaporative emissions (a median of 34% of the total mass), motor vehicle exhaust (24%), industrial process losses (15%), natural gas (13%), liquid/unburned gasoline (13%), and biogenic emissions (1%). Together, the median contribution from mobile source-related factors (exhaust, evaporative emissions, and liquid/unburned gasoline) was 80% and 71% at Azusa and Hawthorne, respectively, similar to previous source apportionment results using the chemical mass balance (CMB) model. There is a difference in the distribution among mobile source factors compared to the CMB work, with an increase in the contribution from evaporative emissions, though the cause (changes in emissions or differences between models) is unknown.
Oxidative changes and signalling pathways are pivotal in initiating age-related changes in articular cartilage

PubMed Central

Hui, Wang; Young, David A; Rowan, Andrew D; Xu, Xin; Cawston, Tim E; Proctor, Carole J

2016-01-01

Objective To use a computational approach to investigate the cellular and extracellular matrix changes that occur with age in the knee joints of mice. Methods Knee joints from an inbred C57/BL1/6 (ICRFa) mouse colony were harvested at 3–30 months of age. Sections were stained with H&E, Safranin-O, Picro-sirius red and antibodies to matrix metalloproteinase-13 (MMP-13), nitrotyrosine, LC-3B, Bcl-2, and cleaved type II collagen used for immunohistochemistry. Based on this and other data from the literature, a computer simulation model was built using the Systems Biology Markup Language using an iterative approach of data analysis and modelling. Individual parameters were subsequently altered to assess their effect on the model. Results A progressive loss of cartilage matrix occurred with age. Nitrotyrosine, MMP-13 and activin receptor-like kinase-1 (ALK1) staining in cartilage increased with age with a concomitant decrease in LC-3B and Bcl-2. Stochastic simulations from the computational model showed a good agreement with these data, once transforming growth factor-β signalling via ALK1/ALK5 receptors was included. Oxidative stress and the interleukin 1 pathway were identified as key factors in driving the cartilage breakdown associated with ageing. Conclusions A progressive loss of cartilage matrix and cellularity occurs with age. This is accompanied with increased levels of oxidative stress, apoptosis and MMP-13 and a decrease in chondrocyte autophagy. These changes explain the marked predisposition of joints to develop osteoarthritis with age. Computational modelling provides useful insights into the underlying mechanisms involved in age-related changes in musculoskeletal tissues. PMID:25475114
ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL

PubMed Central

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-01-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities. PMID:24086091
ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL.

PubMed

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-06-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities.
EPA Positive Matrix Factorization (PMF) 3.0 Fundamentals & User Guide

EPA Science Inventory

Positive matrix factorization (PMF) is a multivariate factor analysis tool that decomposes a matrix of ambient data into two matrices - factor contributions and factor profiles - which then need to be interpreted by an analyst as to what source types are represented using measure...
Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.
Decomposing Time Series Data by a Non-negative Matrix Factorization Algorithm with Temporally Constrained Coefficients

PubMed Central

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

2017-01-01

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

PubMed Central

Wiman, Nik G.; Walton, Vaughn M.; Dalton, Daniel T.; Anfora, Gianfranco; Burrack, Hannah J.; Chiu, Joanna C.; Daane, Kent M.; Grassi, Alberto; Miller, Betsey; Tochen, Samantha; Wang, Xingeng; Ioriatti, Claudio

2014-01-01

Temperature-dependent fecundity and survival data was integrated into a matrix population model to describe relative Drosophila suzukii Matsumura (Diptera: Drosophilidae) population increase and age structure based on environmental conditions. This novel modification of the classic Leslie matrix population model is presented as a way to examine how insect populations interact with the environment, and has application as a predictor of population density. For D. suzukii, we examined model implications for pest pressure on crops. As case studies, we examined model predictions in three small fruit production regions in the United States (US) and one in Italy. These production regions have distinctly different climates. In general, patterns of adult D. suzukii trap activity broadly mimicked seasonal population levels predicted by the model using only temperature data. Age structure of estimated populations suggest that trap and fruit infestation data are of limited value and are insufficient for model validation. Thus, we suggest alternative experiments for validation. The model is advantageous in that it provides stage-specific population estimation, which can potentially guide management strategies and provide unique opportunities to simulate stage-specific management effects such as insecticide applications or the effect of biological control on a specific life-stage. The two factors that drive initiation of the model are suitable temperatures (biofix) and availability of a suitable host medium (fruit). Although there are many factors affecting population dynamics of D. suzukii in the field, temperature-dependent survival and reproduction are believed to be the main drivers for D. suzukii populations. PMID:25192013
Development of gastro intestinal sustained release tablet formulation containing acryl-EZE and pH-dependent swelling HPMC K 15 M.

PubMed

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

2012-05-01

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

ERIC Educational Resources Information Center

Khattab, Ali-Maher; And Others

1982-01-01

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

NASA Astrophysics Data System (ADS)

Giasemidis, Georgios; Tierz, Miguel

2016-01-01

We solve, for finite N, the matrix model of supersymmetric U( N) Chern-Simons theory coupled to N f massive hypermultiplets of R-charge 1/2 , together with a Fayet-Iliopoulos term. We compute the partition function by identifying it with a determinant of a Hankel matrix, whose entries are parametric derivatives (of order N f - 1) of Mordell integrals. We obtain finite Gauss sums expressions for the partition functions. We also apply these results to obtain an exhaustive test of Giveon-Kutasov (GK) duality in the N=3 setting, by systematic computation of the matrix models involved. The phase factor that arises in the duality is then obtained explicitly. We give an expression characterized by modular arithmetic (mod 4) behavior that holds for all tested values of the parameters (checked up to N f = 12 flavours).

High-Throughput Screening of Vascular Endothelium-Destructive or Protective Microenvironments: Cooperative Actions of Extracellular Matrix Composition, Stiffness, and Structure.

PubMed

Ding, Yonghui; Floren, Michael; Tan, Wei

2017-06-01

Pathological modification of the subendothelial extracellular matrix (ECM) has closely been associated with endothelial activation and subsequent cardiovascular disease progression. To understand regulatory mechanisms of these matrix modifications, the majority of previous efforts have focused on the modulation of either chemical composition or matrix stiffness on 2D smooth surfaces without simultaneously probing their cooperative effects on endothelium function on in vivo like 3D fibrous matrices. To this end, a high-throughput, combinatorial microarray platform on 2D and 3D hydrogel settings to resemble the compositions, stiffness, and structure of healthy and diseased subendothelial ECM has been established, and further their respective and combined effects on endothelial attachment, proliferation, inflammation, and junctional integrity have been investigated. For the first time, the results demonstrate that 3D fibrous structure resembling native ECM is a critical endothelium-protective microenvironmental factor by maintaining the stable, quiescent endothelium with strong resistance to proinflammatory stimuli. It is also revealed that matrix stiffening, in concert with chemical compositions resembling diseased ECM, particularly collagen III, could aggravate activation of nuclear factor kappa B, disruption of endothelium integrity, and susceptibility to proinflammatory stimuli. This study elucidates cooperative effects of various microenvironmental factors on endothelial activation and sheds light on new in vitro model for cardiovascular diseases. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Massive data compression for parameter-dependent covariance matrices

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

PubMed

Reynolds, D A; Kueper, B H

2002-01-01

The migration of five dense nonaqueous phase liquids (DNAPLs) through a single fracture in a clay aquitard was numerically simulated with the use of a compositional simulator. The effects of fracture aperture, fracture dip, matrix porosity, and matrix organic carbon content on the migration of chlorobenzene, 1,2-dichloroethylene, trichloroethylene, tetra-chloroethylene, and 1,2-dibromoethane were examined. Boundary conditions were chosen such that DNAPL entry into the system was allowed to vary according to the stresses applied. The aperture is the most important factor of those studied controlling the migration rate of DNAPL through a single fracture embedded in a clay matrix. Loss of mass to the matrix through diffusion does not significantly retard the migration rate of the DNAPL, particularly in larger aperture fractures (e.g., 50 microm). With time, the ratio of diffusive loss to the matrix to DNAPL flux into the fracture approaches an asymptotic value lower than unity. The implication is that matrix diffusion cannot arrest the migration of DNAPL in a single fracture. The complex relationships between density, viscosity, and solubility that, to some extent, govern the migration of DNAPL through these systems prevent accurate predictions without the use of numerical models. The contamination potential of the migrating DNAPL is significantly increased through the transfer of mass to the matrix. The occurrence of opposite concentration gradients within the matrix can cause dissolved phase contamination to exist in the system for more than 1000 years after the DNAPL has been completely removed from the fracture.
Realizing three generations of the Standard Model fermions in the type IIB matrix model

NASA Astrophysics Data System (ADS)

Aoki, Hajime; Nishimura, Jun; Tsuchiya, Asato

2014-05-01

We discuss how the Standard Model particles appear from the type IIB matrix model, which is considered to be a nonperturbative formulation of superstring theory. In particular, we are concerned with a constructive definition of the theory, in which we start with finite- N matrices and take the large- N limit afterwards. In that case, it was pointed out recently that realizing chiral fermions in the model is more difficult than it had been thought from formal arguments at N = ∞ and that introduction of a matrix version of the warp factor is necessary. Based on this new insight, we show that two generations of the Standard Model fermions can be realized by considering a rather generic configuration of fuzzy S2 and fuzzy S2 × S2 in the extra dimensions. We also show that three generations can be obtained by squashing one of the S2's that appear in the configuration. Chiral fermions appear at the intersections of the fuzzy manifolds with nontrivial Yukawa couplings to the Higgs field, which can be calculated from the overlap of their wave functions.
Spin-foam models and the physical scalar product

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

Alesci, Emanuele; Centre de Physique Theorique de Luminy, Universite de la Mediterranee, F-13288 Marseille; Noui, Karim

2008-11-15

This paper aims at clarifying the link between loop quantum gravity and spin-foam models in four dimensions. Starting from the canonical framework, we construct an operator P acting on the space of cylindrical functions Cyl({gamma}), where {gamma} is the four-simplex graph, such that its matrix elements are, up to some normalization factors, the vertex amplitude of spin-foam models. The spin-foam models we are considering are the topological model, the Barrett-Crane model, and the Engle-Pereira-Rovelli model. If one of these spin-foam models provides a covariant quantization of gravity, then the associated operator P should be the so-called ''projector'' into physical statesmore » and its matrix elements should give the physical scalar product. We discuss the possibility to extend the action of P to any cylindrical functions on the space manifold.« less
Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China.

PubMed

Wang, Degao; Tian, Fulin; Yang, Meng; Liu, Chenlin; Li, Yi-Fan

2009-05-01

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

PubMed Central

Rogosin, S.

2018-01-01

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

PubMed

Mishuris, G; Rogosin, S

2018-01-01

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

PubMed

Sheets, Anthony R; Massey, Conner J; Cronk, Stephen M; Iafrati, Mark D; Herman, Ira M

2016-07-02

Non-healing wounds are a major global health concern and account for the majority of non-traumatic limb amputations worldwide. However, compared to standard care practices, few advanced therapeutics effectively resolve these injuries stemming from cardiovascular disease, aging, and diabetes-related vasculopathies. While matrix turnover is disrupted in these injuries, debriding enzymes may promote healing by releasing matrix fragments that induce cell migration, proliferation, and morphogenesis, and plasma products may also stimulate these processes. Thus, we created matrix- and plasma-derived peptides, Comb1 and UN3, which induce cellular injury responses in vitro, and accelerate healing in rodent models of non-healing wounds. However, the effects of these peptides in non-healing wounds in diabetes are not known. Here, we interrogated whether these peptides stimulate healing in a diabetic porcine model highly reminiscent of human healing impairments in type 1 and type 2-diabetes. After 3-6 weeks of streptozotocin-induced diabetes, full-thickness wounds were surgically created on the backs of adult female Yorkshire swine under general anesthesia. Comb1 and UN3 peptides or sterile saline (negative control) were administered to wounds daily for 3-7 days. Following sacrifice, wound tissues were harvested, and quantitative histological and immunohistochemical analyses were performed for wound closure, angiogenesis and granulation tissue deposition, along with quantitative molecular analyses of factors critical for angiogenesis, epithelialization, and dermal matrix remodeling. Comb1 and UN3 significantly increase re-epithelialization and angiogenesis in diabetic porcine wounds, compared to saline-treated controls. Additionally, fluorescein-conjugated Comb1 labels keratinocytes, fibroblasts, and vascular endothelial cells in porcine wounds, and Far western blotting reveals these cell populations express multiple fluorescein-Comb1-interacting proteins in vitro. Further, peptide treatment increases mRNA expression of several pro-angiogenic, epithelializing, and matrix-remodeling factors, importantly including balanced inductions in matrix metalloproteinase-2, -9, and tissue inhibitor of metalloproteinases-1, lending further insight into their mechanisms. Comb1 and UN3 stimulate wound resolution in diabetic Yorkshire swine through upregulation of multiple reparative growth factors and cytokines, especially matrix metalloproteinases and inhibitors that may aid in reversing the proteolytic imbalance characteristic of chronically inflamed non-healing wounds. Together, these peptides should have great therapeutic potential for all patients in need of healing, regardless of injury etiology.
Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…
Analysis of a disk-type piezoelectric ultrasonic motor using impedance matrices.

PubMed

Kim, Young H; Ha, Sung K

2003-12-01

The dynamic behavior and the performance characteristics of the disk-type traveling wave piezoelectric ultrasonic motors (USM) are analyzed using impedance matrices. The stator is divided into three coupled subsystems: an inner metal disk, a piezoelectric annular actuator with segmented electrodes, and an outer metal disk with teeth. The effects of both shear deformation and rotary inertia are taken into account in deriving an impedance matrix for the piezoelectric actuator. The impedance matrices for each subsystem then are combined into a global impedance matrix using continuity conditions at the interfaces. A comparison is made between the impedance matrix model and the three-dimensional finite element model of the piezoelectric stator, obtaining the resonance and antiresonance frequencies and the effective electromechanical coupling factors versus circumferential mode numbers. Using the calculated resonance frequency and the vibration modes for the stator and a brush model with the Coulomb friction for the stator and rotor contact, stall torque, and no-load speed versus excitation frequencies are calculated at different preloads. Performance characteristics such as speed-torque curve and the output efficiency of the USM also are estimated using the current impedance matrix and the contact model. The present impedance model can be shown to be very effective in the design of the USM.
Platelet-rich fibrin matrix improves wound angiogenesis via inducing endothelial cell proliferation.

PubMed

Roy, Sashwati; Driggs, Jason; Elgharably, Haytham; Biswas, Sabyasachi; Findley, Muna; Khanna, Savita; Gnyawali, Urmila; Bergdall, Valerie K; Sen, Chandan K

2011-11-01

The economic, social, and public health burden of chronic ulcers and other compromised wounds is enormous and rapidly increasing with the aging population. The growth factors derived from platelets play an important role in tissue remodeling including neovascularization. Platelet-rich plasma (PRP) has been utilized and studied for the last four decades. Platelet gel and fibrin sealant, derived from PRP mixed with thrombin and calcium chloride, have been exogenously applied to tissues to promote wound healing, bone growth, hemostasis, and tissue sealing. In this study, we first characterized recovery and viability of as well as growth factor release from platelets in a novel preparation of platelet gel and fibrin matrix, namely platelet-rich fibrin matrix (PRFM). Next, the effect of PRFM application in a delayed model of ischemic wound angiogenesis was investigated. The study, for the first time, shows the kinetics of the viability of platelet-embedded fibrin matrix. A slow and steady release of growth factors from PRFM was observed. The vascular endothelial growth factor released from PRFM was primarily responsible for endothelial mitogenic response via extracellular signal-regulated protein kinase activation pathway. Finally, this preparation of PRFM effectively induced endothelial cell proliferation and improved wound angiogenesis in chronic wounds, providing evidence of probable mechanisms of action of PRFM in healing of chronic ulcers. 2011 by the Wound Healing Society.
Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

PubMed

Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

2015-02-09

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.
Computing row and column counts for sparse QR and LU factorization

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

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

2001-01-01

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

PubMed

de Baat, P; Heijboer, M P; de Baat, C

2005-07-01

Bones are of crucial importance for the human body, providing skeletal support, serving as a home for the formation of haematopoietic cells, and reservoiring calcium and phosphate. Long bones develop by endochondral ossification. Flat bones develop by intramembranous ossification. Bone tissue contains hydroxyapatite and various extracellular proteins, producing bone matrix. Two biological mechanisms, determining the strength of bone, are modelling and remodelling. Modelling can change bone shape and size through bone formation by osteoblasts at some sites and through bone destruction by osteoclasts at other sites. Remodelling is bone turnover, also performed by osteoclasts and osteoblasts. The processes of modelling and remodelling are induced by mechanical loads, predominantly muscle loads. Osteoblasts develop from mesenchymal stem cells. Many stimulating factors are known to activate the differentiation. Mature osteoblasts synthesize bone matrix and may further differentiate into osteocytes. Osteocytes maintain structural bone integrity and allow bone to adapt to any mechanical and chemical stimulus. Osteoclasts derive from haematopoietic stem cells. A number of transcription and growth factors have been identified essential for osteoclast differentiation and function. Finally, there is a complex interaction between osteoblasts and osteoclasts. Bone destruction starts by attachment of osteoclasts to the bone surface. Following this, osteoclasts undergo specific morphological changes. The process of bone destruction starts by acid dissolution of hydroxyapatite. After that osteoclasts start to destruct the organic matrix.
Matrix metalloproteinase-9 and vascular endothelial growth factor expression change in experimental retinal neovascularization.

PubMed

Di, Yu; Nie, Qing-Zhu; Chen, Xiao-Long

2016-01-01

To investigate the signal transduction mechanism of matrix metalloproteinase-9 (MMP-9) mediated- vascular endothelial growth factor (VEGF) expression and retinal neovascularization (RNV) in oxygen-induced retinopathy (OIR) model. C57BL/6J mice were divided into four groups: control group, OIR group, OIR control group (phosphate-buffered saline by intravitreal injection) and treated group [tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) by intravitreal injection]. OIR model was established in C57BL/6J mice exposed to 75%±2% oxygen for 5d. mRNA level and protein expression of MMP-9, TIMP-1 and VEGF were measured by real-time polymerase chain reaction and Western blotting, and located by immunohistochemistry. Levels of MMP-9 and VEGF in retina were significantly increased in animals with OIR and OIR control group. Levels of TIMP-1 in retina was significantly reduced in animals with OIR and OIR control group. Furthermore, a significant correlation was found between MMP-9 and VEGF. Intravitreal injection of TIMP-1 significantly reduced MMP-9 and VEGF expression of the OIR mouse model (all P<0.05). These results demonstrate that MMP-9-mediated up-regulation of VEGF promotes RNV in retinopathy of prematurity (ROP). TIMP-1 may be a potential target for the prevention and treatment of ROP.
A novel mathematical model considering change of diffusion coefficient for predicting dissolution behavior of acetaminophen from wax matrix dosage form.

PubMed

Nitanai, Yuta; Agata, Yasuyoshi; Iwao, Yasunori; Itai, Shigeru

2012-05-30

From wax matrix dosage forms, drug and water-soluble polymer are released into the external solvent over time. As a consequence, the pore volume inside the wax matrix particles is increased and the diffusion coefficient of the drug is altered. In the present study, we attempted to derive a novel empirical mathematical model, namely, a time-dependent diffusivity (TDD) model, that assumes the change in the drug's diffusion coefficient can be used to predict the drug release from spherical wax matrix particles. Wax matrix particles were prepared by using acetaminophen (APAP), a model drug; glyceryl monostearate (GM), a wax base; and aminoalkyl methacrylate copolymer E (AMCE), a functional polymer that dissolves below pH 5.0 and swells over pH 5.0. A three-factor, three-level (3(3)) Box-Behnken design was used to evaluate the effects of several of the variables in the model formulation, and the release of APAP from wax matrix particles was evaluated by the paddle method at pH 4.0 and pH 6.5. When comparing the goodness of fit to the experimental data between the proposed TDD model and the conventional pure diffusion model, a better correspondence was observed for the TDD model in all cases. Multiple regression analysis revealed that an increase in AMCE loading enhanced the diffusion coefficient with time, and that this increase also had a significant effect on drug release behavior. Furthermore, from the results of the multiple regression analysis, a formulation with desired drug release behavior was found to satisfy the criteria of the bitter taste masking of APAP without lowering the bioavailability. That is to say, the amount of APAP released remains below 15% for 10 min at pH 6.5 and exceeds 90% within 30 min at pH 4.0. The predicted formulation was 15% APAP loading, 8.25% AMCE loading, and 400 μm mean particle diameter. When wax matrix dosage forms were prepared accordingly, the predicted drug release behavior agreed well with experimental values at each pH level. Therefore, the proposed model is feasible as a useful tool for predicting drug release behavior, as well as for designing the formulation of wax matrix dosage forms. Copyright © 2012 Elsevier B.V. All rights reserved.
Constitutive Modeling and Testing of Polymer Matrix Composites Incorporating Physical Aging at Elevated Temperatures

NASA Technical Reports Server (NTRS)

Veazie, David R.

1998-01-01

Advanced polymer matrix composites (PMC's) are desirable for structural materials in diverse applications such as aircraft, civil infrastructure and biomedical implants because of their improved strength-to-weight and stiffness-to-weight ratios. For example, the next generation military and commercial aircraft requires applications for high strength, low weight structural components subjected to elevated temperatures. A possible disadvantage of polymer-based composites is that the physical and mechanical properties of the matrix often change significantly over time due to the exposure of elevated temperatures and environmental factors. For design, long term exposure (i.e. aging) of PMC's must be accounted for through constitutive models in order to accurately assess the effects of aging on performance, crack initiation and remaining life. One particular aspect of this aging process, physical aging, is considered in this research.
A spatial operator algebra for manipulator modeling and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.; Milman, M.

1988-01-01

A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.
Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

Development of a microwave 20 x 20 switch matrix for 30/20 GHz SS-TDMA application

NASA Technical Reports Server (NTRS)

Cory, B. J.; Berkowitz, M.; Wallis, R.; Schiavone, A.; Shieh, D.; Campbell, J.

1982-01-01

The design and fabrication of a 3-8 GHz, 20 x 20 Satellite Switched-Time Division Multiple Access IF switch matrix applicable to a 30/20 GHz communications satellite are described. An assessment of switch architecture in 1980 concluded that the GaAs FET-based coupled crossbar switch matrix, incorporating high speed CMOS LSI logic for switch crosspoint addressing, would be the optimum technology available for communications satellite switching by 1982. This assessment was based on such factors as switching speed, bandwidth, off-state isolation, and reliability, over a 10-year mission life. A proof-of-concept model's construction and testing are presented.
Matrix product representation of the stationary state of the open zero range process

NASA Astrophysics Data System (ADS)

Bertin, Eric; Vanicat, Matthieu

2018-06-01

Many one-dimensional lattice particle models with open boundaries, like the paradigmatic asymmetric simple exclusion process (ASEP), have their stationary states represented in the form of a matrix product, with matrices that do not explicitly depend on the lattice site. In contrast, the stationary state of the open 1D zero-range process (ZRP) takes an inhomogeneous factorized form, with site-dependent probability weights. We show that in spite of the absence of correlations, the stationary state of the open ZRP can also be represented in a matrix product form, where the matrices are site-independent, non-commuting and determined from algebraic relations resulting from the master equation. We recover the known distribution of the open ZRP in two different ways: first, using an explicit representation of the matrices and boundary vectors; second, from the sole knowledge of the algebraic relations satisfied by these matrices and vectors. Finally, an interpretation of the relation between the matrix product form and the inhomogeneous factorized form is proposed within the framework of hidden Markov chains.
The R-matrix investigation of 8Li(α, n)11B reaction below 6 MeV

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

PubMed

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.
Insights into the mechanism of the formation of the most stable crystal polymorph of milk fat in model protein matrices.

PubMed

Ramel, P R; Marangoni, A G

2017-09-01

The effect of incorporation and presence of various ingredients in a model sodium caseinate-based imitation cheese matrix on the polymorphism of milk fat was comprehensively described using powder x-ray diffraction, differential scanning calorimetry, and microscopy. With anhydrous milk fat (AMF) in bulk used as control, the embedding of AMF as droplets in a protein matrix was found to result in a greater extent of formation of the β polymorph than AMF alone and AMF homogenized with water and salts solution. The use of other protein matrices such as soy and whey protein isolate gels revealed that the nature of the protein and other factors associated with it (i.e., hydrophobicity and molecular structure) do not seem to play a role in the formation of the β polymorph. These results indicated that the most important factor in the formation of the β polymorph is the physical constraints imposed by a solid protein matrix, which forces the triacylglycerols in milk fat to arrange themselves in the most stable crystal polymorph. Characterization of the crystal structure of milk fat or fats in general within a food matrix could provide insights into the complex thermal and rheological behavior of foods with added fats. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
General Population Job Exposure Matrix Applied to a Pooled Study of Prevalent Carpal Tunnel Syndrome

PubMed Central

Dale, Ann Marie; Zeringue, Angelique; Harris-Adamson, Carisa; Rempel, David; Bao, Stephen; Thiese, Matthew S.; Merlino, Linda; Burt, Susan; Kapellusch, Jay; Garg, Arun; Gerr, Fred; Hegmann, Kurt T.; Eisen, Ellen A.; Evanoff, Bradley

2015-01-01

A job exposure matrix may be useful for the study of biomechanical workplace risk factors when individual-level exposure data are unavailable. We used job title–based exposure data from a public data source to construct a job exposure matrix and test exposure-response relationships with prevalent carpal tunnel syndrome (CTS). Exposures of repetitive motion and force from the Occupational Information Network were assigned to 3,452 active workers from several industries, enrolled between 2001 and 2008 from 6 studies. Repetitive motion and force exposures were combined into high/high, high/low, and low/low exposure groupings in each of 4 multivariable logistic regression models, adjusted for personal factors. Although force measures alone were not independent predictors of CTS in these data, strong associations between combined physical exposures of force and repetition and CTS were observed in all models. Consistent with previous literature, this report shows that workers with high force/high repetition jobs had the highest prevalence of CTS (odds ratio = 2.14–2.95) followed by intermediate values (odds ratio = 1.09–2.27) in mixed exposed jobs relative to the lowest exposed workers. This study supports the use of a general population job exposure matrix to estimate workplace physical exposures in epidemiologic studies of musculoskeletal disorders when measures of individual exposures are unavailable. PMID:25700886
Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization

PubMed Central

Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio A.

2011-01-01

Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on three complementary strategies, first, a part-based image representation, called the bag of features, which takes advantage of the natural redundancy of histopathological images for capturing the fundamental patterns of biological structures, second, a latent topic model, based on non-negative matrix factorization, which captures the high-level visual patterns hidden in the image, and, third, a probabilistic annotation model that links visual appearance of morphological and architectural features associated to 10 histopathological image annotations. The method was evaluated using 1,604 annotated images of skin tissues, which included normal and pathological architectural and morphological features, obtaining a recall of 74% and a precision of 50%, which improved a baseline annotation method based on support vector machines in a 64% and 24%, respectively. PMID:22811960
An Uncertainty Structure Matrix for Models and Simulations

NASA Technical Reports Server (NTRS)

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.
A Note on the Factor Analysis of Partial Covariance Matrices

ERIC Educational Resources Information Center

McDonald, Roderick P.

1978-01-01

The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)
Headspace versus direct immersion solid phase microextraction in complex matrixes: investigation of analyte behavior in multicomponent mixtures.

PubMed

Gionfriddo, Emanuela; Souza-Silva, Érica A; Pawliszyn, Janusz

2015-08-18

This work aims to investigate the behavior of analytes in complex mixtures and matrixes with the use of solid-phase microextraction (SPME). Various factors that influence analyte uptake such as coating chemistry, extraction mode, the physicochemical properties of analytes, and matrix complexity were considered. At first, an aqueous system containing analytes bearing different hydrophobicities, molecular weights, and chemical functionalities was investigated by using commercially available liquid and solid porous coatings. The differences in the mass transfer mechanisms resulted in a more pronounced occurrence of coating saturation in headspace mode. Contrariwise, direct immersion extraction minimizes the occurrence of artifacts related to coating saturation and provides enhanced extraction of polar compounds. In addition, matrix-compatible PDMS-modified solid coatings, characterized by a new morphology that avoids coating fouling, were compared to their nonmodified analogues. The obtained results indicate that PDMS-modified coatings reduce artifacts associated with coating saturation, even in headspace mode. This factor, coupled to their matrix compatibility, make the use of direct SPME very practical as a quantification approach and the best choice for metabolomics studies where wide coverage is intended. To further understand the influence on analyte uptake on a system where additional interactions occur due to matrix components, ex vivo and in vivo sampling conditions were simulated using a starch matrix model, with the aim of mimicking plant-derived materials. Our results corroborate the fact that matrix handling can affect analyte/matrix equilibria, with consequent release of high concentrations of previously bound hydrophobic compounds, potentially leading to coating saturation. Direct immersion SPME limited the occurrence of the artifacts, which confirms the suitability of SPME for in vivo applications. These findings shed light into the implementation of in vivo SPME strategies in quantitative metabolomics studies of complex plant-based systems.
Phase diagram of matrix compressed sensing

NASA Astrophysics Data System (ADS)

Schülke, Christophe; Schniter, Philip; Zdeborová, Lenka

2016-12-01

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

PubMed

Yu, Shan; Su, Tiantian; Wu, Huijun; Liu, Shiheng; Wang, Di; Zhao, Tianhu; Jin, Zengjun; Du, Wenbin; Zhu, Mei-Jun; Chua, Song Lin; Yang, Liang; Zhu, Deyu; Gu, Lichuan; Ma, Luyan Z

2015-12-01

Biofilms are surface-associated communities of microorganism embedded in extracellular matrix. Exopolysaccharide is a critical component in the extracellular matrix that maintains biofilm architecture and protects resident biofilm bacteria from antimicrobials and host immune attack. However, self-produced factors that target the matrix exopolysaccharides, are still poorly understood. Here, we show that PslG, a protein involved in the synthesis of a key biofilm matrix exopolysaccharide Psl in Pseudomonas aeruginosa, prevents biofilm formation and disassembles existing biofilms within minutes at nanomolar concentrations when supplied exogenously. The crystal structure of PslG indicates the typical features of an endoglycosidase. PslG mainly disrupts the Psl matrix to disperse bacteria from biofilms. PslG treatment markedly enhances biofilm sensitivity to antibiotics and macrophage cells, resulting in improved biofilm clearance in a mouse implant infection model. Furthermore, PslG shows biofilm inhibition and disassembly activity against a wide range of Pseudomonas species, indicating its great potential in combating biofilm-related complications.
Predictors of time to relapse in amphetamine-type substance users in the matrix treatment program in Iran: a Cox proportional hazard model application.

PubMed

Moeeni, Maryam; Razaghi, Emran M; Ponnet, Koen; Torabi, Fatemeh; Shafiee, Seyed Ali; Pashaei, Tahereh

2016-07-26

The aim of this study was to determine which predictors influence the risk of relapse among a cohort of amphetamine-type substance (ATS) users in Iran. A Cox proportional hazards model was conducted to determine factors associated with the relapse time in the Matrix treatment program provided by the Iranian National Center of Addiction Studies (INCAS) between March 2010 and October 2011. Participating in more treatment sessions was associated with a lower probability of relapse. On the other hand, patients with less family support, longer dependence on ATS, and those with an experience of casual sex and a history of criminal offenses were more likely to relapse. This study broadens our understanding of factors influencing the risk of relapse in ATS use among an Iranian sample. The findings can guide practitioners during the treatment program.
Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

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

Gittens, Alex; Devarakonda, Aditya; Racah, Evan

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 scalingmore » experiments on up to 1600 Cray XC40 nodes, describe the sources of slowdowns, and provide tuning guidance to obtain high performance.« less
Combined Endoscopic/Sonographic-Based Risk Matrix Model for Predicting One-Year Risk of Surgery: A Prospective Observational Study of a Tertiary Center Severe/Refractory Crohn's Disease Cohort.

PubMed

Rispo, Antonio; Imperatore, Nicola; Testa, Anna; Bucci, Luigi; Luglio, Gaetano; De Palma, Giovanni Domenico; Rea, Matilde; Nardone, Olga Maria; Caporaso, Nicola; Castiglione, Fabiana

2018-03-08

In the management of Crohn's Disease (CD) patients, having a simple score combining clinical, endoscopic and imaging features to predict the risk of surgery could help to tailor treatment more effectively. AIMS: to prospectively evaluate the one-year risk factors for surgery in refractory/severe CD and to generate a risk matrix for predicting the probability of surgery at one year. CD patients needing a disease re-assessment at our tertiary IBD centre underwent clinical, laboratory, endoscopy and bowel sonography (BS) examinations within one week. The optimal cut-off values in predicting surgery were identified using ROC curves for Simple Endoscopic Score for CD (SES-CD), bowel wall thickness (BWT) at BS, and small bowel CD extension at BS. Binary logistic regression and Cox's regression were then carried out. Finally, the probabilities of surgery were calculated for selected baseline levels of covariates and results were arranged in a prediction matrix. Of 100 CD patients, 30 underwent surgery within one year. SES-CD©9 (OR 15.3; p<0.001), BWT©7 mm (OR 15.8; p<0.001), small bowel CD extension at BS©33 cm (OR 8.23; p<0.001) and stricturing/penetrating behavior (OR 4.3; p<0.001) were the only independent factors predictive of surgery at one-year based on binary logistic and Cox's regressions. Our matrix model combined these risk factors and the probability of surgery ranged from 0.48% to 87.5% (sixteen combinations). Our risk matrix combining clinical, endoscopic and ultrasonographic findings can accurately predict the one-year risk of surgery in patients with severe/refractory CD requiring a disease re-evaluation. This tool could be of value in clinical practice, serving as the basis for a tailored management of CD patients.
SOURCE APPORTIONMENT OF PM2.5 AT AN URBAN IMPROVE SITE IN SEATTLE, WA

EPA Science Inventory

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, Washington. A total of 289 filter samples were obtained with an IM...
The Performance of the Linear Logistic Test Model When the Q-Matrix Is Misspecified: A Simulation Study

ERIC Educational Resources Information Center

MacDonald, George T.

2014-01-01

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Source apportionment of atmospheric bulk deposition in the Belgrade urban area using Positive Matrix factorization

NASA Astrophysics Data System (ADS)

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).
Person Re-Identification via Distance Metric Learning With Latent Variables.

PubMed

Sun, Chong; Wang, Dong; Lu, Huchuan

2017-01-01

In this paper, we propose an effective person re-identification method with latent variables, which represents a pedestrian as the mixture of a holistic model and a number of flexible models. Three types of latent variables are introduced to model uncertain factors in the re-identification problem, including vertical misalignments, horizontal misalignments and leg posture variations. The distance between two pedestrians can be determined by minimizing a given distance function with respect to latent variables, and then be used to conduct the re-identification task. In addition, we develop a latent metric learning method for learning the effective metric matrix, which can be solved via an iterative manner: once latent information is specified, the metric matrix can be obtained based on some typical metric learning methods; with the computed metric matrix, the latent variables can be determined by searching the state space exhaustively. Finally, extensive experiments are conducted on seven databases to evaluate the proposed method. The experimental results demonstrate that our method achieves better performance than other competing algorithms.
GBM heterogeneity as a function of variable epidermal growth factor receptor variant III activity.

PubMed

Lindberg, Olle R; McKinney, Andrew; Engler, Jane R; Koshkakaryan, Gayane; Gong, Henry; Robinson, Aaron E; Ewald, Andrew J; Huillard, Emmanuelle; David James, C; Molinaro, Annette M; Shieh, Joseph T; Phillips, Joanna J

2016-11-29

Abnormal activation of the epidermal growth factor receptor (EGFR) due to a deletion of exons 2-7 of EGFR (EGFRvIII) is a common alteration in glioblastoma (GBM). While this alteration can drive gliomagenesis, tumors harboring EGFRvIII are heterogeneous. To investigate the role for EGFRvIII activation in tumor phenotype we used a neural progenitor cell-based murine model of GBM driven by EGFR signaling and generated tumor progenitor cells with high and low EGFRvIII activation, pEGFRHi and pEGFRLo. In vivo, ex vivo, and in vitro studies suggested a direct association between EGFRvIII activity and increased tumor cell proliferation, decreased tumor cell adhesion to the extracellular matrix, and altered progenitor cell phenotype. Time-lapse confocal imaging of tumor cells in brain slice cultures demonstrated blood vessel co-option by tumor cells and highlighted differences in invasive pattern. Inhibition of EGFR signaling in pEGFRHi promoted cell differentiation and increased cell-matrix adhesion. Conversely, increased EGFRvIII activation in pEGFRLo reduced cell-matrix adhesion. Our study using a murine model for GBM driven by a single genetic driver, suggests differences in EGFR activation contribute to tumor heterogeneity and aggressiveness.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…
MICRO-SCALE CFD MODELING OF OSCILLATING FLOW IN A REGENERATOR

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

Cheadle, M. J.; Nellis, G. F.; Klein, S. A.

2010-04-09

Regenerator models used by designers are macro-scale models that do not explicitly consider interactions between the fluid and the solid matrix. Rather, the heat transfer coefficient and pressure drop are calculated using correlations for Nusselt number and friction factor. These correlations are typically based on steady flow data. The error associated with using steady flow correlations to characterize the oscillatory flow that is actually present in the regenerator is not well understood. Oscillating flow correlations based on experimental data do exist in the literature; however, these results are often conflicting. This paper uses a micro-scale computational fluid dynamic (CFD) modelmore » of a unit-cell of a regenerator matrix to determine the conditions for which oscillating flow affects friction factor. These conditions are compared to those found in typical pulse tube regenerators to determine whether oscillatory flow is of practical importance. CFD results clearly show a transition Valensi number beyond which oscillating flow significantly increases the friction factor. This transition Valensi number increases with Reynolds number. Most practical pulse tube regenerators will operate below this Valensi transition number and therefore this study suggests that the effect of flow oscillation on pressure drop can be neglected in macro-scale regenerator models.« less
Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models

NASA Astrophysics Data System (ADS)

Heo, Jongbae; Dulger, Muaz; Olson, Michael R.; McGinnis, Jerome E.; Shelton, Brandon R.; Matsunaga, Aiko; Sioutas, Constantinos; Schauer, James J.

2013-07-01

Four hundred fine particulate matter (PM2.5) samples collected over a 1-year period at two sites in the Los Angeles Basin were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and organic molecular markers. The results were used in a Positive Matrix Factorization (PMF) receptor model to obtain daily, monthly and annual average source contributions to PM2.5 OC. Results of the PMF model showed similar source categories with comparable year-long contributions to PM2.5 OC across the sites. Five source categories providing reasonably stable profiles were identified: mobile, wood smoke, primary biogenic, and two types of secondary organic carbon (SOC) (i.e., anthropogenic and biogenic emissions). Total primary emission factors and total SOC factors contributed approximately 60% and 40%, respectively, to the annual-average OC concentrations. Primary sources showed strong seasonal patterns with high winter peaks and low summer peaks, while SOC showed a reverse pattern with highs in the spring and summer in the region. Interestingly, smoke from forest fires which occurred episodically in California during the summer and fall of 2009 was identified and combined with the primary biogenic source as one distinct factor to the OC budget. The PMF resolved factors were further investigated and compared to a chemical mass balance (CMB) model and a second multi-variant receptor model (UNMIX) using molecular markers considered in the PMF. Good agreement between the source contribution from mobile sources and biomass burning for three models were obtained, providing additional weight of evidence that these source apportionment techniques are sufficiently accurate for policy development. However, the CMB model did not quantify primary biogenic emissions, which were included in other sources with the SOC. Both multivariate receptor models, the PMF and the UNMIX, were unable to separate source contributions from diesel and gasoline engines.
Algorithms for Solvents and Spectral Factors of Matrix Polynomials

DTIC Science & Technology

1981-01-01

spectral factors of matrix polynomials LEANG S. SHIEHt, YIH T. TSAYt and NORMAN P. COLEMANt A generalized Newton method , based on the contracted gradient...of a matrix poly- nomial, is derived for solving the right (left) solvents and spectral factors of matrix polynomials. Two methods of selecting initial...estimates for rapid convergence of the newly developed numerical method are proposed. Also, new algorithms for solving complete sets of the right
Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

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

2018-01-01

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

NASA Astrophysics Data System (ADS)

Tang, Y. B.; Li, M.; Bernabe, Y.

2014-12-01

We modeled the electrical transport behavior of dual-pore carbonate rocks in this paper. Based on experimental data of a carbonate reservoir in China, we simply considered the low porosity samples equivalent to the matrix (micro-pore system) of the high porosity samples. For modeling the bimodal porous media, we considered that the matrix is homogeneous and interconnected. The connectivity and the pore size distribution of macro-pore system are varied randomly. Both pore systems are supposed to act electrically in parallel, connected at the nodes, where the fluid exchange takes place, an approach previously used by Bauer et al. (2012). Then, the effect of the properties of matrix, the pore size distribution and connectivity of macro-pore system on petrophysical properties of carbonates can be investigated. We simulated electrical current through networks in three-dimensional simple cubic (SC) and body-center cubic (BCC) with different coordination numbers and different pipe radius distributions of macro-pore system. Based on the simulation results, we found that the formation factor obeys a "universal" scaling relationship (i.e. independent of lattice type), 1/F∝eγz, where γ is a function of the normalized standard deviation of the pore radius distribution of macro-pore system and z is the coordination number of macro-pore system. This relationship is different from the classic "universal power law" in percolation theory. A formation factor model was inferred on the basis of the scaling relationship mentioned above and several scale-invariant quantities (such as hydraulic radius rH and throat length l of macro-pore). Several methods were developed to estimate corresponding parameters of the new model with conventional core analyses. It was satisfactorily tested against experimental data, including some published experimental data. Furthermore, the relationship between water saturation and resistivity in dual-pore carbonates was discussed based on the new model.
A novel experimental design method to optimize hydrophilic matrix formulations with drug release profiles and mechanical properties.

PubMed

Choi, Du Hyung; Lim, Jun Yeul; Shin, Sangmun; Choi, Won Jun; Jeong, Seong Hoon; Lee, Sangkil

2014-10-01

To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Filling gaps in large ecological databases: consequences for the study of global-scale plant functional trait patterns

NASA Astrophysics Data System (ADS)

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

2013-04-01

With the advent of remotely sensed data and coordinated efforts to create global databases, the ecological community has progressively become more data-intensive. However, in contrast to other disciplines, statistical ways of handling these large data sets, especially the gaps which are inherent to them, are lacking. Widely used theoretical approaches, for example model averaging based on Akaike's information criterion (AIC), are sensitive to missing values. Yet, the most common way of handling sparse matrices - the deletion of cases with missing data (complete case analysis) - is known to severely reduce statistical power as well as inducing biased parameter estimates. In order to address these issues, we present novel approaches to gap filling in large ecological data sets using matrix factorization techniques. Factorization based matrix completion was developed in a recommender system context and has since been widely used to impute missing data in fields outside the ecological community. Here, we evaluate the effectiveness of probabilistic matrix factorization techniques for imputing missing data in ecological matrices using two imputation techniques. Hierarchical Probabilistic Matrix Factorization (HPMF) effectively incorporates hierarchical phylogenetic information (phylogenetic group, family, genus, species and individual plant) into the trait imputation. Advanced Hierarchical Probabilistic Matrix Factorization (aHPMF) on the other hand includes climate and soil information into the matrix factorization by regressing the environmental variables against residuals of the HPMF. One unique opportunity opened up by aHPMF is out-of-sample prediction, where traits can be predicted for specific species at locations different to those sampled in the past. This has potentially far-reaching consequences for the study of global-scale plant functional trait patterns. We test the accuracy and effectiveness of HPMF and aHPMF in filling sparse matrices, using the TRY database of plant functional traits (http://www.try-db.org). TRY is one of the largest global compilations of plant trait databases (750 traits of 1 million plants), encompassing data on morphological, anatomical, biochemical, phenological and physiological features of plants. However, despite of unprecedented coverage, the TRY database is still very sparse, severely limiting joint trait analyses. Plant traits are the key to understanding how plants as primary producers adjust to changes in environmental conditions and in turn influence them. Forming the basis for Dynamic Global Vegetation Models (DGVMs), plant traits are also fundamental in global change studies for predicting future ecosystem changes. It is thus imperative that missing data is imputed in as accurate and precise a way as possible. In this study, we show the advantages and disadvantages of applying probabilistic matrix factorization techniques in incorporating hierarchical and environmental information for the prediction of missing plant traits as compared to conventional imputation techniques such as the complete case and mean approaches. We will discuss the implications of using gap-filled data for global-scale studies of plant functional trait - environment relationship as opposed to the above-mentioned conventional techniques, using examples of out-of-sample predictions of foliar Nitrogen across several species' ranges and biomes.
Multi-ray-based system matrix generation for 3D PET reconstruction

NASA Astrophysics Data System (ADS)

Moehrs, Sascha; Defrise, Michel; Belcari, Nicola; DelGuerra, Alberto; Bartoli, Antonietta; Fabbri, Serena; Zanetti, Gianluigi

2008-12-01

Iterative image reconstruction algorithms for positron emission tomography (PET) require a sophisticated system matrix (model) of the scanner. Our aim is to set up such a model offline for the YAP-(S)PET II small animal imaging tomograph in order to use it subsequently with standard ML-EM (maximum-likelihood expectation maximization) and OSEM (ordered subset expectation maximization) for fully three-dimensional image reconstruction. In general, the system model can be obtained analytically, via measurements or via Monte Carlo simulations. In this paper, we present the multi-ray method, which can be considered as a hybrid method to set up the system model offline. It incorporates accurate analytical (geometric) considerations as well as crystal depth and crystal scatter effects. At the same time, it has the potential to model seamlessly other physical aspects such as the positron range. The proposed method is based on multiple rays which are traced from/to the detector crystals through the image volume. Such a ray-tracing approach itself is not new; however, we derive a novel mathematical formulation of the approach and investigate the positioning of the integration (ray-end) points. First, we study single system matrix entries and show that the positioning and weighting of the ray-end points according to Gaussian integration give better results compared to equally spaced integration points (trapezoidal integration), especially if only a small number of integration points (rays) are used. Additionally, we show that, for a given variance of the single matrix entries, the number of rays (events) required to calculate the whole matrix is a factor of 20 larger when using a pure Monte-Carlo-based method. Finally, we analyse the quality of the model by reconstructing phantom data from the YAP-(S)PET II scanner.
Analytical development of disturbed matrix eigenvalue problem applied to mixed convection stability analysis in Darcy media

NASA Astrophysics Data System (ADS)

Hamed, Haikel Ben; Bennacer, Rachid

2008-08-01

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

ERIC Educational Resources Information Center

Palmieri, Patrick A.; Smith, Gregory C.

2007-01-01

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

NASA Technical Reports Server (NTRS)

Narayanan, T. V.; Erdogan, F.

1974-01-01

Using a slender inclusion model developed earlier, the elastostatic interaction problem between a penny-shaped crack and elastic fibers in an elastic matrix is formulated. For a single set and for multiple sets of fibers oriented perpendicularly to the plane of the crack and distributed symmetrically on concentric circles, the problem was reduced to a system of singular integral equations. Techniques for the regularization and for the numerical solution of the system are outlined. For various fiber geometries numerical examples are given, and distribution of the stress intensity factor along the crack border was obtained. Sample results showing the distribution of the fiber stress and a measure of the fiber-matrix interface shear are also included.
Penny-shaped crack in a fiber-reinforced matrix

NASA Technical Reports Server (NTRS)

Narayanan, T. V.; Erdogan, F.

1975-01-01

Using the slender inclusion model developed earlier the elastostatic interaction problem between a penny-shaped crack and elastic fibers in an elastic matrix is formulated. For a single set and for multiple sets of fibers oriented perpendicularly to the plane of the crack and distributed symmetrically on concentric circles the problem is reduced to a system of singular integral equations. Techniques for the regularization and for the numerical solution of the system are outlined. For various fiber geometries numerical examples are given and distribution of the stress intensity factor along the crack border is obtained. Sample results showing the distribution of the fiber stress and a measure of the fiber-matrix interface shear are also included.
Sources and drains: Major controls of hydrothermal fluid flow in the Kokanee Range, British Columbia, Canada

NASA Astrophysics Data System (ADS)

Beaudoin, Georges; Therrien, René

1999-10-01

Vein fields are fractured domains of the lithosphere that have been infiltrated by hydrothermal fluids, which deposited minerals in response to changing physico-chemical conditions. Because oxygen is a major component of the infiltrating fluid and the surrounding rock matrix, the oxygen isotope composition of minerals found in veins is used to decipher ancient fluid flow within the lithosphere. We use a numerical model to simulate oxygen isotope transport in the Kokanee Range silver-lead-zinc vein field. The model considers advective, dispersive, and reactive transport in a three-dimensional porous rock matrix intersected by high-permeability planes representing fracture zones. Here we show that it is the geometrical configuration of the sources and of the drains of hydrothermal fluids, combined with the fracture pattern, that exerts the main control on the oxygen isotope distribution. Other factors that affect, to a lesser extent, the values and positions of oxygen isopleths are the fluids and rock-matrix isotopic compositions, the isotopic fractionation, the reaction rate constant, and hydraulic conductivities of the rock matrix and fracture zones.
Constant Switching Frequency DTC for Matrix Converter Fed Speed Sensorless Induction Motor Drive

NASA Astrophysics Data System (ADS)

Mir, Tabish Nazir; Singh, Bhim; Bhat, Abdul Hamid

2018-05-01

The paper presents a constant switching frequency scheme for speed sensorless Direct Torque Control (DTC) of Matrix Converter fed Induction Motor Drive. The use of matrix converter facilitates improved power quality on input as well as motor side, along with Input Power Factor control, besides eliminating the need for heavy passive elements. Moreover, DTC through Space Vector Modulation helps in achieving a fast control over the torque and flux of the motor, with added benefit of constant switching frequency. A constant switching frequency aids in maintaining desired power quality of AC mains current even at low motor speeds, and simplifies input filter design of the matrix converter, as compared to conventional hysteresis based DTC. Further, stator voltage estimation from sensed input voltage, and subsequent stator (and rotor) flux estimation is done. For speed sensorless operation, a Model Reference Adaptive System is used, which emulates the speed dependent rotor flux equations of the induction motor. The error between conventionally estimated rotor flux (reference model) and the rotor flux estimated through the adaptive observer is processed through PI controller to generate the rotor speed estimate.
Angiogenic Type I Collagen Extracellular Matrix Integrated with Recombinant Bacteriophages Displaying Vascular Endothelial Growth Factors.

PubMed

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

2016-01-21

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

NASA Technical Reports Server (NTRS)

Johnson, W. S.

1992-01-01

Several layups of SCS-6/Ti-15-3 composites were investigated. Fatigue tests were conducted and analyzed for both notched and unnotched specimens at room temperature and elevated temperatures. Thermo-mechanical fatigue results were analyzed. Test results indicated that the stress in the 0 degree fibers is the controlling factor in fatigue life. The static and fatigue strength of these materials is shown to be strongly dependent on the level of residual stresses and the fiber/matrix interfacial strength. Fatigue tests of notched specimens showed that cracks can initiate and grow many fiber spacings in the matrix materials without breaking fibers. Fiber bridging models were applied to characterize the crack growth behavior. The matrix cracks are shown to significantly reduce the residual strength of notched composites. The notch strength of these composites was accurately predicted using a micromechanics based methodology.
Damage development in titanium metal-matrix composites subjected to cyclic loading

NASA Technical Reports Server (NTRS)

Johnson, W. S.

1993-01-01

Several layups of SCS-6/Ti-15-3 composites were investigated. Fatigue tests were conducted and analyzed for both notched and unnotched specimens at room temperature and elevated temperatures. Thermo-mechanical fatigue results were analyzed. Test results indicated that the stress in the 0 degree fibers is the controlling factor in fatigue life. The static and fatigue strength of these materials is shown to be strongly dependent on the level of residual stresses and the fiber/matrix interfacial strength. Fatigue tests of notched specimens showed that cracks can initiate and grow many fiber spacings in the matrix materials without breaking fibers. Fiber bridging models were applied to characterize the crack growth behavior. The matrix cracks are shown to significantly reduce the residual strength of notched composites. The notch strength of these composites was accurately predicted using a micromechanics based methodology.
Thalidomide Accelerates the Degradation of Extracellular Matrix in Rat Hepatic Cirrhosis via Down-Regulation of Transforming Growth Factor-β1

PubMed Central

Meng, Qingshun; Liu, Jie; Wang, Chuanfang

2015-01-01

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

PubMed

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

2017-06-01

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

Toda hierarchies and their applications

NASA Astrophysics Data System (ADS)

Takasaki, Kanehisa

2018-05-01

The 2D Toda hierarchy occupies a central position in the family of integrable hierarchies of the Toda type. The 1D Toda hierarchy and the Ablowitz–Ladik (aka relativistic Toda) hierarchy can be derived from the 2D Toda hierarchy as reductions. These integrable hierarchies have been applied to various problems of mathematics and mathematical physics since 1990s. A recent example is a series of studies on models of statistical mechanics called the melting crystal model. This research has revealed that the aforementioned two reductions of the 2D Toda hierarchy underlie two different melting crystal models. Technical clues are a fermionic realization of the quantum torus algebra, special algebraic relations therein called shift symmetries, and a matrix factorization problem. The two melting crystal models thus exhibit remarkable similarity with the Hermitian and unitary matrix models for which the two reductions of the 2D Toda hierarchy play the role of fundamental integrable structures.
Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers

NASA Astrophysics Data System (ADS)

Caballero Morales, Santiago Omar; Cox, Stephen J.

2009-12-01

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform poorly on dysarthric speakers. In this work, rather than adapting the acoustic models, we model the errors made by the speaker and attempt to correct them. For this task, two techniques have been developed: (1) a set of "metamodels" that incorporate a model of the speaker's phonetic confusion matrix into the ASR process; (2) a cascade of weighted finite-state transducers at the confusion matrix, word, and language levels. Both techniques attempt to correct the errors made at the phonetic level and make use of a language model to find the best estimate of the correct word sequence. Our experiments show that both techniques outperform standard adaptation techniques.
Non-negative Matrix Factorization and Co-clustering: A Promising Tool for Multi-tasks Bearing Fault Diagnosis

NASA Astrophysics Data System (ADS)

Shen, Fei; Chen, Chao; Yan, Ruqiang

2017-05-01

Classical bearing fault diagnosis methods, being designed according to one specific task, always pay attention to the effectiveness of extracted features and the final diagnostic performance. However, most of these approaches suffer from inefficiency when multiple tasks exist, especially in a real-time diagnostic scenario. A fault diagnosis method based on Non-negative Matrix Factorization (NMF) and Co-clustering strategy is proposed to overcome this limitation. Firstly, some high-dimensional matrixes are constructed using the Short-Time Fourier Transform (STFT) features, where the dimension of each matrix equals to the number of target tasks. Then, the NMF algorithm is carried out to obtain different components in each dimension direction through optimized matching, such as Euclidean distance and divergence distance. Finally, a Co-clustering technique based on information entropy is utilized to realize classification of each component. To verity the effectiveness of the proposed approach, a series of bearing data sets were analysed in this research. The tests indicated that although the diagnostic performance of single task is comparable to traditional clustering methods such as K-mean algorithm and Guassian Mixture Model, the accuracy and computational efficiency in multi-tasks fault diagnosis are improved.
A method for grounding grid corrosion rate prediction

NASA Astrophysics Data System (ADS)

Han, Juan; Du, Jingyi

2017-06-01

Involved in a variety of factors, prediction of grounding grid corrosion complex, and uncertainty in the acquisition process, we propose a combination of EAHP (extended AHP) and fuzzy nearness degree of effective grounding grid corrosion rate prediction model. EAHP is used to establish judgment matrix and calculate the weight of each factors corrosion of grounding grid; different sample classification properties have different corrosion rate of contribution, and combining the principle of close to predict corrosion rate.The application result shows, the model can better capture data variation, thus to improve the validity of the model to get higher prediction precision.
An Analytical Thermal Model for Autonomous Soaring Research

NASA Technical Reports Server (NTRS)

Allen, Michael

2006-01-01

A viewgraph presentation describing an analytical thermal model used to enable research on autonomous soaring for a small UAV aircraft is given. The topics include: 1) Purpose; 2) Approach; 3) SURFRAD Data; 4) Convective Layer Thickness; 5) Surface Heat Budget; 6) Surface Virtual Potential Temperature Flux; 7) Convective Scaling Velocity; 8) Other Calculations; 9) Yearly trends; 10) Scale Factors; 11) Scale Factor Test Matrix; 12) Statistical Model; 13) Updraft Strength Calculation; 14) Updraft Diameter; 15) Updraft Shape; 16) Smoothed Updraft Shape; 17) Updraft Spacing; 18) Environment Sink; 19) Updraft Lifespan; 20) Autonomous Soaring Research; 21) Planned Flight Test; and 22) Mixing Ratio.
Suspensions of polymer-grafted nanoparticles with added polymers-Structure and effective pair-interactions.

PubMed

Chandran, Sivasurender; Saw, Shibu; Kandar, A K; Dasgupta, C; Sprung, M; Basu, J K

2015-08-28

We present the results of combined experimental and theoretical (molecular dynamics simulations and integral equation theory) studies of the structure and effective interactions of suspensions of polymer grafted nanoparticles (PGNPs) in the presence of linear polymers. Due to the absence of systematic experimental and theoretical studies of PGNPs, it is widely believed that the structure and effective interactions in such binary mixtures would be very similar to those of an analogous soft colloidal material-star polymers. In our study, polystyrene-grafted gold nanoparticles with functionality f = 70 were mixed with linear polystyrene (PS) of two different molecular weights for obtaining two PGNP:PS size ratios, ξ = 0.14 and 2.76 (where, ξ = Mg/Mm, Mg and Mm being the molecular weights of grafting and matrix polymers, respectively). The experimental structure factor of PGNPs could be modeled with an effective potential (Model-X), which has been found to be widely applicable for star polymers. Similarly, the structure factor of the blends with ξ = 0.14 could be modeled reasonably well, while the structure of blends with ξ = 2.76 could not be captured, especially for high density of added polymers. A model (Model-Y) for effective interactions between PGNPs in a melt of matrix polymers also failed to provide good agreement with the experimental data for samples with ξ = 2.76 and high density of added polymers. We tentatively attribute this anomaly in modeling the structure factor of blends with ξ = 2.76 to the questionable assumption of Model-X in describing the added polymers as star polymers with functionality 2, which gets manifested in both polymer-polymer and polymer-PGNP interactions especially at higher fractions of added polymers. The failure of Model-Y may be due to the neglect of possible many-body interactions among PGNPs mediated by matrix polymers when the fraction of added polymers is high. These observations point to the need for a new framework to understand not only the structural behavior of PGNPs but also possibly their dynamics and thermo-mechanical properties as well.
Biomimetic Delivery of Keratinocyte Growth Factor upon Cellular Demand for Accelerated Wound Healing in Vitro and in Vivo

PubMed Central

Geer, David J.; Swartz, Daniel D.; Andreadis, Stelios T.

2005-01-01

Exogenous keratinocyte growth factor (KGF) significantly enhances wound healing, but its use is hampered by a short biological half-life and lack of tissue selectivity. We used a biomimetic approach to achieve cell-controlled delivery of KGF by covalently attaching a fluorescent matrix-binding peptide that contained two domains: one recognized by factor XIII and the other by plasmin. Modified KGF was incorporated into the fibrin matrix at high concentration in a factor XIII-dependent manner. Cell-mediated activation of plasminogen to plasmin degraded the fibrin matrix and cleaved the peptides, releasing active KGF to the local microenvironment and enhancing epithelial cell proliferation and migration. To demonstrate in vivo effectiveness, we used a hybrid model of wound healing that involved transplanting human bioengineered skin onto athymic mice. At 6 weeks after grafting, the transplanted tissues underwent full thickness wounding and treatment with fibrin gels containing bound KGF. In contrast to topical KGF, fibrin-bound KGF persisted in the wounds for several days and was released gradually, resulting in significantly enhanced wound closure. A fibrinolytic inhibitor prevented this healing, indicating the requirement for cell-mediated fibrin degradation to release KGF. In conclusion, this biomimetic approach of localized, cell-controlled delivery of growth factors may accelerate healing of large full-thickness wounds and chronic wounds that are notoriously difficult to heal. PMID:16314471
Multi-cut solutions in Chern-Simons matrix models

NASA Astrophysics Data System (ADS)

Morita, Takeshi; Sugiyama, Kento

2018-04-01

We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.
Non-negative matrix factorization in texture feature for classification of dementia with MRI data

NASA Astrophysics Data System (ADS)

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).
Study of melanoma invasion by FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Y.; Sulé-Suso, J.; Sockalingum, G. D.

2008-02-01

Compared to other forms of skin cancer, a malignant melanoma has a high risk of spreading to other parts of the body. Melanoma invasion is a complex process involving changes in cell-extracellular matrix (ECM) interaction and cell-cell interactions. To fully understand the factors which control the invasion process, a human skin model system was reconstructed. HBL (a commercially available cell line) melanoma cells were seeded on a skin model with and without the presence of keratinocytes and/or fibroblasts. After 14 days culture, the skin specimens were fixed, parafin embedded and cut into 7 Âµm sections. The de-parafinised sections were investigated by synchrotron Fourier transformed infrared (FTIR) microspectroscopy to study skin cell invasion behaviour. The advantage of using FTIR is its ability to obtain the fingerprint information of the invading cells in terms of protein secondary structure in comparison to non-invading cells and the concentration of the enzyme (matrix-metalloproteinase) which digests protein matrix, near the invading cells. With aid of the spectral mapping images, it is possible to pinpoint the cells in non-invasion and invasion area and analyse the respective spectra. It has been observed that the protein bands in cells and matrix shifted between non-invasive and invasive cells in the reconstructed skin model. We hypothesise that by careful analysis of the FTIR data and validation by other models, FTIR studies can reveal information on which type of cells and proteins are involved in melanoma invasion. Thus, it is possible to trace the cell invasion path by mapping the spectra along the interface of cell layer and matrix body by FTIR spectroscopy.
Three-dimensional prostate tumor model based on a hyaluronic acid-alginate hydrogel for evaluation of anti-cancer drug efficacy.

PubMed

Tang, Yadong; Huang, Boxin; Dong, Yuqin; Wang, Wenlong; Zheng, Xi; Zhou, Wei; Zhang, Kun; Du, Zhiyun

2017-10-01

In vitro cell-based assays are widely applied to evaluate anti-cancer drug efficacy. However, the conventional approaches are mostly based on two-dimensional (2D) culture systems, making it difficult to recapitulate the in vivo tumor scenario because of spatial limitations. Here, we develop an in vitro three-dimensional (3D) prostate tumor model based on a hyaluronic acid (HA)-alginate hybrid hydrogel to bridge the gap between in vitro and in vivo anticancer drug evaluations. In situ encapsulation of PCa cells was achieved by mixing HA and alginate aqueous solutions in the presence of cells and then crosslinking with calcium ions. Unlike in 2D culture, cells were found to aggregate into spheroids in a 3D matrix. The expression of epithelial to mesenchyme transition (EMT) biomarkers was found to be largely enhanced, indicating an increased invasion and metastasis potential in the hydrogel matrix. A significant up-regulation of proangiogenic growth factors (IL-8, VEGF) and matrix metalloproteinases (MMPs) was observed in 3D-cultured PCa cells. The results of anti-cancer drug evaluation suggested a higher drug tolerance within the 3D tumor model compared to conventional 2D-cultured cells. Finally, we found that the drug effect within the in vitro 3D cancer model based on HA-alginate matrix exhibited better predictability for in vivo drug efficacy.
Electronic coupling between Watson-Crick pairs for hole transfer and transport in desoxyribonucleic acid

NASA Astrophysics Data System (ADS)

Voityuk, Alexander A.; Jortner, Joshua; Bixon, M.; Rösch, Notker

2001-04-01

Electronic matrix elements for hole transfer between Watson-Crick pairs in desoxyribonucleic acid (DNA) of regular structure, calculated at the Hartree-Fock level, are compared with the corresponding intrastrand and interstrand matrix elements estimated for models comprised of just two nucleobases. The hole transfer matrix element of the GAG trimer duplex is calculated to be larger than that of the GTG duplex. "Through-space" interaction between two guanines in the trimer duplexes is comparable with the coupling through an intervening Watson-Crick pair. The gross features of bridge specificity and directional asymmetry of the electronic matrix elements for hole transfer between purine nucleobases in superstructures of dimer and trimer duplexes have been discussed on the basis of the quantum chemical calculations. These results have also been analyzed with a semiempirical superexchange model for the electronic coupling in DNA duplexes of donor (nuclobases)-acceptor, which incorporates adjacent base-base electronic couplings and empirical energy gaps corrected for solvation effects; this perturbation-theory-based model interpretation allows a theoretical evaluation of experimental observables, i.e., the absolute values of donor-acceptor electronic couplings, their distance dependence, and the reduction factors for the intrastrand hole hopping or trapping rates upon increasing the size of the nucleobases bridge. The quantum chemical results point towards some limitations of the perturbation-theory-based modeling.
Extracting factors for interest rate scenarios

NASA Astrophysics Data System (ADS)

Molgedey, L.; Galic, E.

2001-04-01

Factor based interest rate models are widely used for risk managing purposes, for option pricing and for identifying and capturing yield curve anomalies. The movements of a term structure of interest rates are commonly assumed to be driven by a small number of orthogonal factors such as SHIFT, TWIST and BUTTERFLY (BOW). These factors are usually obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). Although PCA diagonalizes the covariance matrix of either the interest rates or the interest rate changes, it does not use both covariance matrices simultaneously. Furthermore higher linear and nonlinear correlations are neglected. These correlations as well as the mean reverting properties of the interest rates become crucial, if one is interested in a longer time horizon (infrequent hedging or trading). We will show that Independent Component Analysis (ICA) is a more appropriate tool than PCA, since ICA uses the covariance matrix of the interest rates as well as the covariance matrix of the interest rate changes simultaneously. Additionally higher linear and nonlinear correlations may be easily incorporated. The resulting factors are uncorrelated for various time delays, approximately independent but nonorthogonal. This is in contrast to the factors obtained from the PCA, which are orthogonal and uncorrelated for identical times only. Although factors from the ICA are nonorthogonal, it is sufficient to consider only a few factors in order to explain most of the variation in the original data. Finally we will present examples that ICA based hedges outperforms PCA based hedges specifically if the portfolio is sensitive to structural changes of the yield curve.
3D frequency-domain finite-difference modeling of acoustic wave propagation

NASA Astrophysics Data System (ADS)

Operto, S.; Virieux, J.

2006-12-01

We present a 3D frequency-domain finite-difference method for acoustic wave propagation modeling. This method is developed as a tool to perform 3D frequency-domain full-waveform inversion of wide-angle seismic data. For wide-angle data, frequency-domain full-waveform inversion can be applied only to few discrete frequencies to develop reliable velocity model. Frequency-domain finite-difference (FD) modeling of wave propagation requires resolution of a huge sparse system of linear equations. If this system can be solved with a direct method, solutions for multiple sources can be computed efficiently once the underlying matrix has been factorized. The drawback of the direct method is the memory requirement resulting from the fill-in of the matrix during factorization. We assess in this study whether representative problems can be addressed in 3D geometry with such approach. We start from the velocity-stress formulation of the 3D acoustic wave equation. The spatial derivatives are discretized with second-order accurate staggered-grid stencil on different coordinate systems such that the axis span over as many directions as possible. Once the discrete equations were developed on each coordinate system, the particle velocity fields are eliminated from the first-order hyperbolic system (following the so-called parsimonious staggered-grid method) leading to second-order elliptic wave equations in pressure. The second-order wave equations discretized on each coordinate system are combined linearly to mitigate the numerical anisotropy. Secondly, grid dispersion is minimized by replacing the mass term at the collocation point by its weighted averaging over all the grid points of the stencil. Use of second-order accurate staggered- grid stencil allows to reduce the bandwidth of the matrix to be factorized. The final stencil incorporates 27 points. Absorbing conditions are PML. The system is solved using the parallel direct solver MUMPS developed for distributed-memory computers. The MUMPS solver is based on a multifrontal method for LU factorization. We used the METIS algorithm to perform re-ordering of the matrix coefficients before factorization. Four grid points per minimum wavelength is used for discretization. We applied our algorithm to the 3D SEG/EAGE synthetic onshore OVERTHRUST model of dimensions 20 x 20 x 4.65 km. The velocities range between 2 and 6 km/s. We performed the simulations using 192 processors with 2 Gbytes of RAM memory per processor. We performed simulations for the 5 Hz, 7 Hz and 10 Hz frequencies in some fractions of the OVERTHRUST model. The grid interval was 100 m, 75 m and 50 m respectively. The grid dimensions were 207x207x53, 275x218x71 and 409x109x102 respectively corresponding to 100, 80 and 25 percents of the model respectively. The time for factorization is 20 mn, 108 mn and 163 mn respectively. The time for resolution was 3.8, 9.3 and 10.3 s per source. The total memory used during factorization is 143, 384 and 449 Gbytes respectively. One can note the huge memory requirement for factorization and the efficiency of the direct method to compute solutions for a large number of sources. This highlights the respective drawback and merit of the frequency-domain approach with respect to the time- domain counterpart. These results show that 3D acoustic frequency-domain wave propagation modeling can be performed at low frequencies using direct solver on large clusters of Pcs. This forward modeling algorithm may be used in the future as a tool to image the first kilometers of the crust by frequency-domain full-waveform inversion. For larger problems, we will use the out-of-core memory during factorization that has been implemented by the authors of MUMPS.
Dynamics of a poly(ethylene oxide) tracer in a poly(methyl methacrylate) matrix: remarkable decoupling of local and global motions.

PubMed

Haley, Jeffrey C; Lodge, Timothy P

2005-06-15

The tracer diffusion coefficient of unentangled poly(ethylene oxide) (PEO, M=1000 gmol) in a matrix of poly(methyl methacrylate) (PMMA, M=10 000 gmol) has been measured over a temperature range from 125 to 220 degrees C with forced Rayleigh scattering. The dynamic viscosities of blends of two different high molecular weight PEO tracers (M=440 000 and 900 000 gmol) in the same PMMA matrix were also measured at temperatures ranging from 160 to 220 degrees C; failure of time-temperature superposition was observed for these systems. The monomeric friction factors for the PEO tracers were extracted from the diffusion coefficients and the rheological relaxation times using the Rouse model. The friction factors determined by diffusion and rheology were in good agreement, even though the molecular weights of the tracers differed by about three orders of magnitude. The PEO monomeric friction factors were compared with literature data for PEO segmental relaxation times measured directly with NMR. The monomeric friction factors of the PEO tracer in the PMMA matrix were found to be from two to six orders of magnitude greater than anticipated based on direct measurements of segmental dynamics. Additionally, the PEO tracer terminal dynamics are a much stronger function of temperature than the corresponding PEO segmental dynamics. These results indicate that the fastest PEO Rouse mode, inferred from diffusion and rheology, is completely separated from the bond reorientation of PEO detected by NMR. This result is unlike other blend systems in which global and local motions have been compared.
Effects of structurally stabilized EGF and bFGF on wound healing in type I and type II diabetic mice.

PubMed

Choi, Seong Mi; Lee, Kyoung-Mi; Kim, Hyun Jung; Park, Ik Kyu; Kang, Hwi Ju; Shin, Hang-Cheol; Baek, Dawoon; Choi, Yoorim; Park, Kwang Hwan; Lee, Jin Woo

2018-01-15

Diabetes mellitus comprises a multiple metabolic disorder that affects millions of people worldwide and consequentially poses challenges for clinical treatment. Among the various complications, diabetic ulcer constitutes the most prevalent associated disorder and leads to delayed wound healing. To enhance wound healing capacity, we developed structurally stabilized epidermal growth factor (ST-EGF) and basic fibroblast growth factor (ST-bFGF) to overcome limitations of commercially available EGF (CA-EGF) and bFGF (CA-bFGF), such as short half-life and loss of activity after loading onto a matrix. Neither ST-EGF nor ST-bFGF was toxic, and both were more stable at higher temperatures than CA-EGF and CA-bFGF. We loaded ST-EGF and ST-bFGF onto a hyaluronate-collagen dressing (HCD) matrix, a biocompatible carrier, and tested the effectiveness of this system in promoting wound healing in a mouse model of diabetes. Wounds treated with HCD matrix loaded with 0.3 μg/cm 2 ST-EGF or 1 μg/cm 2 ST-bFGF showed a more rapid rate of tissue repair as compared to the control in type I and II diabetes models. Our results indicate that an HDC matrix loaded with 0.3 μg/cm 2 ST-EGF or 1 μg/cm 2 ST-bFGF can promote wound healing in diabetic ulcers and are suitable for use in wound dressings owing to their stability for long periods at room temperature. Various types of dressing materials loaded with growth factors, such as VEGF, EGF, and bFGF, are widely used to effect wound repair. However, such growth factor-loaded materials have several limitations for use as therapeutic agents in healing-impaired diabetic wounds. To overcome these limitations, we have developed new materials containing structurally stabilized EGF (ST-EGF) and bFGF (ST-bFGF). To confirm the wound healing capacity of newly developed materials (ST-EGF and ST-bFGF-loaded hyaluronate-collagen dressing [HCD] matrix), we applied these matrices in type I and type II diabetic wounds. Notably, these matrices were able to accelerate wound healing including re-epithelialization, neovascularization, and collagen deposition. Consequentially, these ST-EGF and ST-bFGF-loaded HCD matrix may be used as future therapeutic agents in patients with diabetic foot ulcers. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Three-dimensional modelling of slope stability using the Local Factor of Safety concept

NASA Astrophysics Data System (ADS)

Moradi, Shirin; Huisman, Sander; Beck, Martin; Vereecken, Harry; Class, Holger

2017-04-01

Slope stability is governed by coupled hydrological and mechanical processes. The slope stability depends on the effective stress, which in turn depends on the weight of the soil and the matrix potential. Therefore, changes in water content and matrix potential associated with infiltration will affect slope stability. Most available models describing these coupled hydro-mechanical processes either rely on a one- or two-dimensional representation of hydrological and mechanical properties and processes, which obviously is a strong simplification in many applications. Therefore, the aim of this work is to develop a three-dimensional hydro-mechanical model that is able to capture the effect of spatial and temporal variability of both mechanical and hydrological parameters on slope stability. For this, we rely on DuMux, which is a free and open-source simulator for flow and transport processes in porous media that facilitates coupling of different model approaches and offers flexibility for model development. We use the Richards equation to model unsaturated water flow. The simulated water content and matrix potential distribution is used to calculate the effective stress. We only consider linear elasticity and solve for statically admissible fields of stress and displacement without invoking failure or the redistribution of post-failure stress or displacement. The Local Factor of Safety concept is used to evaluate slope stability in order to overcome some of the main limitations of commonly used methods based on limit equilibrium considerations. In a first step, we compared our model implementation with a 2D benchmark model that was implemented in COMSOL Multiphysics. In a second step, we present in-silico experiments with the newly developed 3D model to show the effect of slope morphology, spatial variability in hydraulic and mechanical material properties, and spatially variable soil depth on simulated slope stability. It is expected that this improved physically-based three-dimensional hydro-mechanical model is able to provide more reliable slope instability predictions in more complex situations.
Some applications of the Kronecker product in Hubbard representation

NASA Astrophysics Data System (ADS)

Enríquez, Marco; Rosas-Ortiz, Oscar

2014-10-01

The properties of the Kronecker product are revisited in terms of Hubbard operators. The simplest representation of a Hubbard operator Xi,jn is a square matrix of size n with an entry equal to 1 and zero elsewhere. This framework simplifies the calculation of the Kronecker product of arbitrary matrices no matter the size or the number of the involved factors. Some applications are presented, these include the algebra of permutation matrices, the Hadamard matrix, the XXX Heisenberg model and the interaction of an atom with radiation fields.
Intermediate Temperature Strength Degradation in SiC/SiC Composites

NASA Technical Reports Server (NTRS)

Morscher, Gregory N.; Cawley, James D.; Levine, Stanley (Technical Monitor)

2001-01-01

Woven silicon carbide fiber-reinforced, silicon carbide matrix composites are leading candidate materials for an advanced jet engine combustor liner application. Although the use temperature in the hot region for this application is expected to exceed 1200 C, a potential life-limiting concern for this composite system exists at intermediate temperatures (800 +/- 200 C), where significant time-dependent strength degradation has been observed under stress-rupture loading. A number of factors control the degree of stress-rupture strength degradation, the major factor being the nature of the interphase separating the fiber and the matrix. BN interphases are superior to carbon interphases due to the slower oxidation kinetics of BN. A model for the intermediate temperature stress-rupture of SiC/BN/SiC composites is presented based on the observed mechanistic process that leads to strength degradation for the simple case of through-thickness matrix cracks. The approach taken has much in common with that used by Curtin and coworkers, for two different composite systems. The predictions of the model are in good agreement with the rupture data for stress-rupture of both precracked and as-produced composites. Also, three approaches that dramatically improve the intermediate temperature stress-rupture properties are described: Si-doped BN, fiber spreading, and 'outside debonding'.
The use of type 1 collagen scaffold containing stromal cell-derived factor-1 to create a matrix environment conducive to partial-thickness cartilage defects repair.

PubMed

Zhang, Wei; Chen, Jialin; Tao, Jiadong; Jiang, Yangzi; Hu, Changchang; Huang, Lu; Ji, Junfeng; Ouyang, Hong Wei

2013-01-01

Despite the presence of cartilage-derived mesenchymal stem cells (C-MSCs) and synovial membrane-derived mesenchymal stem cells (SM-MSCs) populations, partial-thickness cartilage defects, in contrast to the full-thickness defects, are devoid of spontaneous repair capacity. This study aims to create an in situ matrix environment conducive to C-MSCs and SM-MSCs to promote cartilage self-repair. Spontaneous repair with MSCs migration into the defect area was observed in full-thickness defects, but not in partial-thickness defects in rabbit model. Ex vivo and in vitro studies showed that subchondral bone or type 1 collagen (col1) scaffold was more permissive for MSCs adhesion than cartilage or type 2 collagen (col2) scaffold and induced robust stromal cell-derived factors-1 (SDF-1) dependent migration of MSCs. Furthermore, creating a matrix environment with col1 scaffold containing SDF-1 enhanced in situ self-repair of partial-thickness defects in rabbit 6 weeks post-injury. Hence, the inferior self-repair capacity in partial-thickness defects is partially owing to the non-permissive matrix environment. Creating an in situ matrix environment conducive to C-MSCs and SM-MSCs migration and adhesion with col1 scaffold containing SDF-1 can be exploited to improve self-repair capacity of cartilage. Copyright © 2012 Elsevier Ltd. All rights reserved.

A new fracture mechanics model for multiple matrix cracks of SiC fiber reinforced brittle-matrix composites

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

Okabe, T.; Takeda, N.; Komotori, J.

1999-11-26

A new model is proposed for multiple matrix cracking in order to take into account the role of matrix-rich regions in the cross section in initiating crack growth. The model is used to predict the matrix cracking stress and the total number of matrix cracks. The model converts the matrix-rich regions into equivalent penny shape crack sizes and predicts the matrix cracking stress with a fracture mechanics crack-bridging model. The estimated distribution of matrix cracking stresses is used as statistical input to predict the number of matrix cracks. The results show good agreement with the experimental results by replica observations.more » Therefore, it is found that the matrix cracking behavior mainly depends on the distribution of matrix-rich regions in the composite.« less
Leveraging tagging and rating for recommendation: RMF meets weighted diffusion on tripartite graphs

NASA Astrophysics Data System (ADS)

Li, Jianguo; Tang, Yong; Chen, Jiemin

2017-10-01

Recommender systems (RSs) have been a widely exploited approach to solving the information overload problem. However, the performance is still limited due to the extreme sparsity of the rating data. With the popularity of Web 2.0, the social tagging system provides more external information to improve recommendation accuracy. Although some existing approaches combine the matrix factorization models with the tag co-occurrence and context of tags, they neglect the issue of tag sparsity that would also result in inaccurate recommendations. Consequently, in this paper, we propose a novel hybrid collaborative filtering model named WUDiff_RMF, which improves regularized matrix factorization (RMF) model by integrating Weighted User-Diffusion-based CF algorithm(WUDiff) that obtains the information of similar users from the weighted tripartite user-item-tag graph. This model aims to capture the degree correlation of the user-item-tag tripartite network to enhance the performance of recommendation. Experiments conducted on four real-world datasets demonstrate that our approach significantly performs better than already widely used methods in the accuracy of recommendation. Moreover, results show that WUDiff_RMF can alleviate the data sparsity, especially in the circumstance that users have made few ratings and few tags.
Synthetic Division and Matrix Factorization

ERIC Educational Resources Information Center

Barabe, Samuel; Dubeau, Franc

2007-01-01

Synthetic division is viewed as a change of basis for polynomials written under the Newton form. Then, the transition matrices obtained from a sequence of changes of basis are used to factorize the inverse of a bidiagonal matrix or a block bidiagonal matrix.
Spacecraft in switch matrix for wide band service applicatons in 30/20 GHz communications satellite systems

NASA Technical Reports Server (NTRS)

Cory, B. J.

1982-01-01

Bandwidth, switching speed, off-state isolation, and reliability over a ten-year mission were factors in determining the optimum available technology for satellite communications switching in 1982. A proof of concept model for a 20 x 20 coupled crossbar switch matrix designed with FET devices for microwave switching and with high speed CMOS LIS for switch crosspoint addressing was fabricated and tested. Results show the design is feasible for application in a multichannel SS-TDMA communications system. Expandibility can readily be achieved with this design. A conceptual design study for a 100 x 100 switch matrix utilizing a coupled crossbar architecture implemented with a monolithic microwave integrated circuits revealed technology needs for high capacity switch matrices.
Non-invasive dual fluorescence in vivo imaging for detection of macrophage infiltration and matrix metalloproteinase (MMP) activity in inflammatory arthritic joints

PubMed Central

Cho, Hongsik; Bhatti, Fazal-Ur-Rehman; Yoon, Tae Won; Hasty, Karen A.; Stuart, John M.; Yi, Ae-Kyung

2016-01-01

Detection and intervention at an early stage is a critical factor to impede arthritis progress. Here we present a non-invasive method to detect inflammatory changes in joints of arthritic mice. Inflammation was monitored by dual fluorescence optical imaging for near-infrared fluorescent (750F) matrix-metalloproteinase activatable agent and allophycocyanin-conjugated anti-mouse CD11b. Increased intensity of allophycocyanin (indication of macrophage accumulation) and 750F (indication of matrix-metalloproteinase activity) showed a biological relationship with the arthritis severity score and the histopathology score of arthritic joints. Our results demonstrate that this method can be used to detect early stages of arthritis with minimum intervention in small animal models. PMID:27231625
A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.

PubMed

Cao, Cheng; Akalin Acar, Zeynep; Kreutz-Delgado, Kenneth; Makeig, Scott

2012-01-01

Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.
Linearized T-Matrix and Mie Scattering Computations

NASA Technical Reports Server (NTRS)

Spurr, R.; Wang, J.; Zeng, J.; Mishchenko, M. I.

2011-01-01

We present a new linearization of T-Matrix and Mie computations for light scattering by non-spherical and spherical particles, respectively. In addition to the usual extinction and scattering cross-sections and the scattering matrix outputs, the linearized models will generate analytical derivatives of these optical properties with respect to the real and imaginary parts of the particle refractive index, and (for non-spherical scatterers) with respect to the ''shape'' parameter (the spheroid aspect ratio, cylinder diameter/height ratio, Chebyshev particle deformation factor). These derivatives are based on the essential linearity of Maxwell's theory. Analytical derivatives are also available for polydisperse particle size distribution parameters such as the mode radius. The T-matrix formulation is based on the NASA Goddard Institute for Space Studies FORTRAN 77 code developed in the 1990s. The linearized scattering codes presented here are in FORTRAN 90 and will be made publicly available.
Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.
Recommendation based on trust diffusion model.

PubMed

Yuan, Jinfeng; Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure.
Recommendation Based on Trust Diffusion Model

PubMed Central

Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure. PMID:25009827
Bulalo field, Philippines: Reservoir modeling for prediction of limits to sustainable generation

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

Strobel, Calvin J.

1993-01-28

The Bulalo geothermal field, located in Laguna province, Philippines, supplies 12% of the electricity on the island of Luzon. The first 110 MWe power plant was on line May 1979; current 330 MWe (gross) installed capacity was reached in 1984. Since then, the field has operated at an average plant factor of 76%. The National Power Corporation plans to add 40 MWe base load and 40 MWe standby in 1995. A numerical simulation model for the Bulalo field has been created that matches historic pressure changes, enthalpy and steam flash trends and cumulative steam production. Gravity modeling provided independent verificationmore » of mass balances and time rate of change of liquid desaturation in the rock matrix. Gravity modeling, in conjunction with reservoir simulation provides a means of predicting matrix dry out and the time to limiting conditions for sustainable levelized steam deliverability and power generation.« less
A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary

NASA Astrophysics Data System (ADS)

Gillis, Nicolas; Luce, Robert

2018-01-01

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

NASA Astrophysics Data System (ADS)

Wu, Ning

2018-01-01

For the one-dimensional spin-1/2 XX model with either periodic or open boundary conditions, it is shown by using a fermionic approach that the matrix element of the spin operator Sj- (Sj-Sj'+ ) between two eigenstates with numbers of excitations n and n +1 (n and n ) can be expressed as the determinant of an appropriate (n +1 )×(n +1 ) matrix whose entries involve the coefficients of the canonical transformations diagonalizing the model. In the special case of a homogeneous periodic XX chain, the matrix element of Sj- reduces to a variant of the Cauchy determinant that can be evaluated analytically to yield a factorized expression. The obtained compact representations of these matrix elements are then applied to two physical scenarios: (i) Nonlinear optical response of molecular aggregates, for which the determinant representation of the transition dipole matrix elements between eigenstates provides a convenient way to calculate the third-order nonlinear responses for aggregates from small to large sizes compared with the optical wavelength; and (ii) real-time dynamics of an interacting Dicke model consisting of a single bosonic mode coupled to a one-dimensional XX spin bath. In this setup, full quantum calculation up to N ≤16 spins for vanishing intrabath coupling shows that the decay of the reduced bosonic occupation number approaches a finite plateau value (in the long-time limit) that depends on the ratio between the number of excitations and the total number of spins. Our results can find useful applications in various "system-bath" systems, with the system part inhomogeneously coupled to an interacting XX chain.
Paracrine regulation of matrix metalloproteinase expression in the normal human endometrium.

PubMed

Osteen, K G; Keller, N R; Feltus, F A; Melner, M H

1999-01-01

Endometrial expression of matrix metalloproteinase (MMP)-3, MMP-7 and MMP-11 occurs during menstrual breakdown and subsequent estrogen-mediated growth, but not during the secretory phase. These enzymes are suppressed by progesterone treatment. Paracrine factors, including transforming growth factor-beta (TGF-beta) and retinoic acid, are also critical for MMP regulation in the endometrium. In contrast, inflammatory cytokines such as interleukin-1alpha may block or interfere with steroid-mediated MMP regulation at ectopic sites of growth. Using in vitro models, our laboratory has investigated the complex interactions between progesterone and locally produced cytokines that may affect MMP expression during the development of endometriosis. Our results indicate that targeting the regulation of MMPs may represent an appropriate therapeutic strategy for the treatment of endometriosis. Copyrightz1999S. KargerAG,Basel
Coupling chemical transport model source attributions with positive matrix factorization: application to two IMPROVE sites impacted by wildfires.

PubMed

Sturtz, Timothy M; Schichtel, Bret A; Larson, Timothy V

2014-10-07

Source contributions to total fine particle carbon predicted by a chemical transport model (CTM) were incorporated into the positive matrix factorization (PMF) receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in the Multilinear Engine (ME-2). The methodology provides the ability to separate features that would not be identified using PMF alone, without sacrificing fit to observations. The hybrid model was applied to IMPROVE data taken from 2006 through 2008 at Monture and Sula Peak, Montana. It was able to separately identify major contributions of total carbon (TC) from wildfires and minor contributions from biogenic sources. The predictions of TC had a lower cross-validated RMSE than those from either PMF or CTM alone. Two unconstrained, minor features were identified at each site, a soil derived feature with elevated summer impacts and a feature enriched in sulfate and nitrate with significant, but sporadic contributions across the sampling period. The respective mean TC contributions from wildfires, biogenic emissions, and other sources were 1.18, 0.12, and 0.12 ugC/m(3) at Monture and 1.60, 0.44, and 0.06 ugC/m(3) at Sula Peak.
A Comparative Study of Collagen Matrix Density Effect on Endothelial Sprout Formation Using Experimental and Computational Approaches.

PubMed

Shamloo, Amir; Mohammadaliha, Negar; Heilshorn, Sarah C; Bauer, Amy L

2016-04-01

A thorough understanding of determining factors in angiogenesis is a necessary step to control the development of new blood vessels. Extracellular matrix density is known to have a significant influence on cellular behaviors and consequently can regulate vessel formation. The utilization of experimental platforms in combination with numerical models can be a powerful method to explore the mechanisms of new capillary sprout formation. In this study, using an integrative method, the interplay between the matrix density and angiogenesis was investigated. Owing the fact that the extracellular matrix density is a global parameter that can affect other parameters such as pore size, stiffness, cell-matrix adhesion and cross-linking, deeper understanding of the most important biomechanical or biochemical properties of the ECM causing changes in sprout morphogenesis is crucial. Here, we implemented both computational and experimental methods to analyze the mechanisms responsible for the influence of ECM density on the sprout formation that is difficult to be investigated comprehensively using each of these single methods. For this purpose, we first utilized an innovative approach to quantify the correspondence of the simulated collagen fibril density to the collagen density in the experimental part. Comparing the results of the experimental study and computational model led to some considerable achievements. First, we verified the results of the computational model using the experimental results. Then, we reported parameters such as the ratio of proliferating cells to migrating cells that was difficult to obtain from experimental study. Finally, this integrative system led to gain an understanding of the possible mechanisms responsible for the effect of ECM density on angiogenesis. The results showed that stable and long sprouts were observed at an intermediate collagen matrix density of 1.2 and 1.9 mg/ml due to a balance between the number of migrating and proliferating cells. As a result of weaker connections between the cells and matrix, a lower collagen matrix density (0.7 mg/ml) led to unstable and broken sprouts. However, higher matrix density (2.7 mg/ml) suppressed sprout formation due to the high level of matrix entanglement, which inhibited cell migration. This study also showed that extracellular matrix density can influence sprout branching. Our experimental results support this finding.
Low-dimensional Representation of Error Covariance

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

NASA Astrophysics Data System (ADS)

Cheng, Jian

2009-07-01

Robust infrared target tracking is an important and challenging research topic in many military and security applications, such as infrared imaging guidance, infrared reconnaissance, scene surveillance, etc. To effectively tackle the nonlinear and non-Gaussian state estimation problems, particle filtering is introduced to construct the theory framework of infrared target tracking. Under this framework, the observation probabilistic model is one of main factors for infrared targets tracking performance. In order to improve the tracking performance, covariance matrices are introduced to represent infrared targets with the multi-features. The observation probabilistic model can be constructed by computing the distance between the reference target's and the target samples' covariance matrix. Because the covariance matrix provides a natural tool for integrating multiple features, and is scale and illumination independent, target representation with covariance matrices can hold strong discriminating ability and robustness. Two experimental results demonstrate the proposed method is effective and robust for different infrared target tracking, such as the sensor ego-motion scene, and the sea-clutter scene.
Semileptonic decays of B and D mesons in the light-front formalism

NASA Astrophysics Data System (ADS)

Jaus, W.

1990-06-01

The light-front formalism is used to present a relativistic calculation of form factors for semileptonic D and B decays in the constituent quark model. The quark-antiquark wave functions of the mesons can be obtained, in principle, from an analysis of the meson spectrum, but are approximated in this work by harmonic-oscillator wave functions. The predictions of the model are consistent with the experimental data for B decays. The Kobayashi-Maskawa (KM) matrix element ||Vcs|| is determined by a comparison of the experimental and theoretical rates for D0-->K-e+ν, and is consistent with a unitary KM matrix for three families. The predictions for D-->K* transitions are in conflict with the data.
Composition of fibrin glues significantly influences axial vascularization and degradation in isolation chamber model.

PubMed

Arkudas, Andreas; Pryymachuk, Galyna; Hoereth, Tobias; Beier, Justus P; Polykandriotis, Elias; Bleiziffer, Oliver; Gulle, Heinz; Horch, Raymund E; Kneser, Ulrich

2012-07-01

In this study, different fibrin sealants with varying concentrations of the fibrin components were evaluated in terms of matrix degradation and vascularization in the arteriovenous loop (AVL) model of the rat. An AVL was placed in a Teflon isolation chamber filled with 500 μl fibrin gel. The matrix was composed of commercially available fibrin gels, namely Beriplast (Behring GmbH, Marburg, Germany) (group A), Evicel (Omrix Biopharmaceuticals S.A., Somerville, New Jersey, USA) (group B), Tisseel VH S/D (Baxter, Vienna, Austria) with a thrombin concentration of 4 IU/ml and a fibrinogen concentration of 80 mg/ml [Tisseel S F80 (Baxter), group C] and with an fibrinogen concentration of 20 mg/ml [Tisseel S F20 (Baxter), group D]. After 2 and 4 weeks, five constructs per group and time point were investigated using micro-computed tomography, and histological and morphometrical analysis techniques. The aprotinin, factor XIII and thrombin concentration did not affect the degree of clot degradation. An inverse relationship was found between fibrin matrix degradation and sprouting of blood vessels. By reducing the fibrinogen concentration in group D, a significantly decreased construct weight and an increased generation of vascularized connective tissue were detected. There was an inverse relationship between matrix degradation and vascularization detectable. Fibrinogen as the major matrix component showed a significant impact on the matrix properties. Alteration of fibrin gel properties might optimize formation of blood vessels.

Ward Identity and Scattering Amplitudes for Nonlinear Sigma Models

NASA Astrophysics Data System (ADS)

Low, Ian; Yin, Zhewei

2018-02-01

We present a Ward identity for nonlinear sigma models using generalized nonlinear shift symmetries, without introducing current algebra or coset space. The Ward identity constrains correlation functions of the sigma model such that the Adler's zero is guaranteed for S -matrix elements, and gives rise to a subleading single soft theorem that is valid at the quantum level and to all orders in the Goldstone decay constant. For tree amplitudes, the Ward identity leads to a novel Berends-Giele recursion relation as well as an explicit form of the subleading single soft factor. Furthermore, interactions of the cubic biadjoint scalar theory associated with the single soft limit, which was previously discovered using the Cachazo-He-Yuan representation of tree amplitudes, can be seen to emerge from matrix elements of conserved currents corresponding to the generalized shift symmetry.
Fracture healing in osteoporotic bone.

PubMed

Cheung, Wing Hoi; Miclau, Theodore; Chow, Simon Kwoon-Ho; Yang, Frank F; Alt, Volker

2016-06-01

As the world population rises, osteoporotic fracture is an emerging global threat to the well-being of elderly patients. The process of fracture healing by intramembranous ossification or/and endochondral ossification involve many well-orchestrated events including the signaling, recruitment and differentiation of mesenchymal stem cells (MSCs) during the early phase; formation of a hard callus and extracellular matrix, angiogenesis and revascularization during the mid-phase; and finally callus remodeling at the late phase of fracture healing. Through clinical and animal research, many of these factors are shown to be impaired in osteoporotic bone. Animal studies related to post-menopausal estrogen deficient osteoporosis (type I) have shown healing to be prolonged with decreased levels of MSCs and decreased levels of angiogenesis. Moreover, the expression of estrogen receptor (ER) was shown to be delayed in ovariectomy-induced osteoporotic fracture. This might be related to the observed difference in mechanical sensitivity between normal and osteoporotic bones, which requires further experiments to elucidate. In mice fracture models related to senile osteoporosis (type II), it was observed that chondrocyte and osteoblast differentiation were impaired; and that transplantation of juvenile bone marrow would result in enhanced callus formation. Other factors related to angiogenesis and vasculogenesis have also been noted to be impaired in aged models, affecting the degradation of cartilaginous matrixes and vascular invasion; the result is changes in matrix composition and growth factors concentrations that ultimately impairs healing during age-related osteoporosis. Most osteoporotic related fractures occur at metaphyseal sites clinically, and reports have indicated that differences exist between diaphyseal and metaphyseal fractures. An animal model that satisfies three main criteria (metaphyseal region, plate fixation, osteoporosis) is suggested for future research for more comprehensive understanding of the impairment in osteoporotic fractures. Therefore, a metaphyseal fracture or osteotomy that achieves complete discontinuity fixed with metal implants is suggested on ovariectomized aged rodent models. © 2016 Elsevier Ltd. All rights reserved.
Human uterus myoma and gene expression profiling: A novel in vitro model for studying secretory leukocyte protease inhibitor-mediated tumor invasion.

PubMed

Mikami, Yoshikazu; Fukushima, Atsushi; Komiyama, Yusuke; Iwase, Takashi; Tsuda, Hiromasa; Higuchi, Yasuhiko; Hayakawa, Satoshi; Kuyama, Kayo; Komiyama, Kazuo

2016-08-28

Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor that diminishes tissue destruction during inflammation. A recent report revealed high levels of SLPI expression in the oral carcinoma cell. In addition, overexpression of SLPI up-regulates metastasis in lung carcinoma cells. On the other hand, matrix metalloproteinases (MMPs) are proteinases that participate in extracellular matrix degradation. SLPI and MMPs are involved as accelerators of the tumor invasion process; however, their exact roles are not fully understood. Understanding the mechanism of tumor invasion requires models that take the effect of microenvironmental factors into account. In one such in vitro model, different carcinoma cells have been shown to invade myoma tissue in highly distinct patterns. We have used this myoma model, as it provides a more natural stroma-like environment, to investigate the role of SLPI in tumor invasion. Our results indicate that the model provides a relevant matrix for tumor invasion studies, and that SLPI is important for the invasion of oral carcinoma Ca9-22 cells in conjunction with MMPs. Furthermore, using bioinformatics analysis, we have identified candidates as key molecules involved in SLPI-mediated tumor invasion. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Development and application of a density dependent matrix ...

EPA Pesticide Factsheets

Ranging along the Atlantic coast from US Florida to the Maritime Provinces of Canada, the Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Matrix population models are useful tools for ecological risk assessment because they integrate effects across the life cycle, provide a linkage between endpoints observed in the individual and ecological risk to the population as a whole, and project outcomes for many generations in the future. We developed a density dependent matrix population model for Atlantic killifish by modifying a model developed for fathead minnow (Pimephales promelas) that has proved to be extremely useful, e.g. to incorporate data from laboratory studies and project effects of endocrine disrupting chemicals. We developed a size-structured model (as opposed to one that is based upon developmental stages or age class structure) so that we could readily incorporate output from a Dynamic Energy Budget (DEB) model, currently under development. Due to a lack of sufficient data to accurately define killifish responses to density dependence, we tested a number of scenarios realistic for other fish species in order to demonstrate the outcome of including this ecologically important factor. We applied the model using published data for killifish exposed to dioxin-like compounds, and compared our results to those using
Spatial operator factorization and inversion of the manipulator mass matrix

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo; Kreutz-Delgado, Kenneth

1992-01-01

This paper advances two linear operator factorizations of the manipulator mass matrix. Embedded in the factorizations are many of the techniques that are regarded as very efficient computational solutions to inverse and forward dynamics problems. The operator factorizations provide a high-level architectural understanding of the mass matrix and its inverse, which is not visible in the detailed algorithms. They also lead to a new approach to the development of computer programs or organize complexity in robot dynamics.
EPA Positive Matrix Factorization (PMF) 5.0 Fundamentals and User Guide

EPA Science Inventory

PMF is a multivariate factor analysis tool that decomposes a matrix of speciated sample data into two matrices: factor contributions (G) and factor profiles (F). These factor profiles need to be interpreted by the user to identify the source types that may be contributing to the ...
Enforced Sparse Non-Negative Matrix Factorization

DTIC Science & Technology

2016-01-23

documents to find interesting pieces of information. With limited resources, analysts often employ automated text - mining tools that highlight common...represented as an undirected bipartite graph. It has become a common method for generating topic models of text data because it is known to produce good results...model and the convergence rate of the underlying algorithm. I. Introduction A common analyst challenge is searching through large quantities of text
How to Get Really Smart: Modeling Retest and Training Effects in Ability Testing using Computer-Generated Figural Matrix Items

ERIC Educational Resources Information Center

Freund, Philipp Alexander; Holling, Heinz

2011-01-01

The interpretation of retest scores is problematic because they are potentially affected by measurement and predictive bias, which impact construct validity, and because their size differs as a function of various factors. This paper investigates the construct stability of scores on a figural matrices test and models retest effects at the level of…
A Study of the Critical Factors Controlling the Synthesis of Ceramic Matrix Composites from Preceramic Polymers.

DTIC Science & Technology

1988-04-15

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

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

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

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

DOE PAGES

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

2017-10-30

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms thatmore » iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.« less
A new state space model for the NASA/JPL 70-meter antenna servo controls

NASA Technical Reports Server (NTRS)

Hill, R. E.

1987-01-01

A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.
Estimation of variance in Cox's regression model with shared gamma frailties.

PubMed

Andersen, P K; Klein, J P; Knudsen, K M; Tabanera y Palacios, R

1997-12-01

The Cox regression model with a shared frailty factor allows for unobserved heterogeneity or for statistical dependence between the observed survival times. Estimation in this model when the frailties are assumed to follow a gamma distribution is reviewed, and we address the problem of obtaining variance estimates for regression coefficients, frailty parameter, and cumulative baseline hazards using the observed nonparametric information matrix. A number of examples are given comparing this approach with fully parametric inference in models with piecewise constant baseline hazards.
Tetragonal deformation of the hexagonal myofilament matrix in single skinned skeletal muscle fibres owing to change in sarcomere length.

PubMed

Schiereck, P; de Beer, E L; Grundeman, R L; Manussen, T; Kylstra, N; Bras, W

1992-10-01

Single skinned skeletal muscle fibres were immersed in solutions containing two different levels of activator calcium (pCa: 4.4; 6.0). Sarcomere length was varied from 1.6 to 3.5 microns and recorded by laser diffraction. Slack length was 2.0 microns. Small-angle equatorial X-ray diffraction patterns of relaxed and activated fibres at different sarcomere lengths were recorded using synchrotron radiation. The position and amplitude of the diffraction peaks were calculated from the spectra based on the hexagonal arrangement of the myofilament matrix, relating the position of the (1.0)- and (1.1)-diffraction peaks in this model by square root of 3. The diffraction peaks were fitted by five Gaussian functions (1.0, 1.1, 2.0, 2.1 and Z-line) and residual background was corrected by means of a hyperbola. The coupling of the position of the (1.0)- and (1.1)-peak was expressed as a factor: FAC = [d(1.0)/d(1.1)]/square root 3. In the relaxed state this coupling factor decreased at increasing sarcomere length (0.9880 +/- 0.002 at 2.0 microns; 0.900 +/- 0.01 at 3.5 microns). The coupling factor tends toward the one that will be obtained from the squared structure of actin filaments near the Z-discs. At shorter sarcomere lengths a decrease of the coupling factor has also been seen (0.9600 +/- 0.005 at 1.6 microns), giving rise to an increased uniform deformation of the hexagonal matrix, when sarcomere length is changed from slack length. From these experiments we conclude that a change in sarcomere length (from slack length) increases the deformation of the actin-myosin matrix to a tetragonal lattice.
Mathematical modelling of anisotropy of illite-rich shale

USGS Publications Warehouse

Chesnokov, E.M.; Tiwary, D.K.; Bayuk, I.O.; Sparkman, M.A.; Brown, R.L.

2009-01-01

The estimation of illite-rich shale anisotropy to account for the alignment of clays and gas- or brine-filled cracks is presented via mathematical modelling. Such estimation requires analysis to interpret the dominance of one effect over another. This knowledge can help to evaluate the permeability in the unconventional reservoir, stress orientation, and the seal capacity for the conventional reservoir. Effective media modelling is used to predict the elastic properties of the illite-rich shale and to identify the dominant contributions to the shale anisotropy. We consider two principal reasons of the shale anisotropy: orientation of clay platelets and orientation of fluid-filled cracks. In reality, both of these two factors affect the shale anisotropy. The goal of this study is, first, to separately analyse the effect of these two factors to reveal the specific features in P- and S-wave velocity behaviour typical of each of the factors, and, then, consider a combined effect of the factors when the cracks are horizontally or vertically aligned. To do this, we construct four models of shale. The behaviour of P- and S-wave velocities is analysed when gas- and water-filled cracks embedded in a host matrix are randomly oriented, or horizontally or vertically aligned. The host matrix can be either isotropic or anisotropic (of VTI symmetry). In such a modelling, we use published data on mineralogy and clay platelet alignment along with other micromechanical measurements. In the model, where the host matrix is isotropic, the presence of a singularity point (when the difference VS1 - VS2 changes its sign) in shear wave velocities is an indicator of brine-filled aligned cracks. In the model with the VTI host matrix and horizontally aligned cracks filled with gas, an increase in their volume concentration leads to that the azimuth at which the singularity is observed moves toward the symmetry axis. In this case, if the clay content is small (around 20 per cent), the singularity point may even vanish. The Thomsen parameters are helpful in fluid type indication in shale. An indicator of gas-filled aligned cracks is ?? > ??. If aligned cracks in illite-rich shale are brine-filled, ?? < ??. Negative value of ?? indicates brine-filled cracks in illite-rich shale. A shale with brine-filled cracks exhibits higher Vp/Vs ratio in the vertical direction as compared to the gas-filled shale. A disorientation of clay platelets and brine-filled cracks may lead to that the singularity point is absent for brine-saturated shale as well. In this case one can also observe ?? > ?? and decreased values of Vp/Vs in the vertical direction as in the case of gas-filled cracks. In the presence of vertically aligned cracks, shales exhibit distinctly revealed features of orthorhombic symmetry. The results have important applications where seismic measurements are applied to predict the maturity state of the shale. ?? 2009 The Authors Journal compilation ?? 2009 RAS.
SparRec: An effective matrix completion framework of missing data imputation for GWAS

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

PubMed

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.
On non-negative matrix factorization algorithms for signal-dependent noise with application to electromyography data

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

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

PubMed Central

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

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

PubMed

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

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

Structure-preserving and rank-revealing QR-factorizations

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

Bischof, C.H.; Hansen, P.C.

1991-11-01

The rank-revealing QR-factorization (RRQR-factorization) is a special QR-factorization that is guaranteed to reveal the numerical rank of the matrix under consideration. This makes the RRQR-factorization a useful tool in the numerical treatment of many rank-deficient problems in numerical linear algebra. In this paper, a framework is presented for the efficient implementation of RRQR algorithms, in particular, for sparse matrices. A sparse RRQR-algorithm should seek to preserve the structure and sparsity of the matrix as much as possible while retaining the ability to capture safely the numerical rank. To this end, the paper proposes to compute an initial QR-factorization using amore » restricted pivoting strategy guarded by incremental condition estimation (ICE), and then applies the algorithm suggested by Chan and Foster to this QR-factorization. The column exchange strategy used in the initial QR factorization will exploit the fact that certain column exchanges do not change the sparsity structure, and compute a sparse QR-factorization that is a good approximation of the sought-after RRQR-factorization. Due to quantities produced by ICE, the Chan/Foster RRQR algorithm can be implemented very cheaply, thus verifying that the sought-after RRQR-factorization has indeed been computed. Experimental results on a model problem show that the initial QR-factorization is indeed very likely to produce RRQR-factorization.« less
Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices

NASA Astrophysics Data System (ADS)

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices.

PubMed

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Study of the validity of a job-exposure matrix for the job strain model factors: an update and a study of changes over time.

PubMed

Niedhammer, Isabelle; Milner, Allison; LaMontagne, Anthony D; Chastang, Jean-François

2018-03-08

The objectives of the study were to construct a job-exposure matrix (JEM) for psychosocial work factors of the job strain model, to evaluate its validity, and to compare the results over time. The study was based on national representative data of the French working population with samples of 46,962 employees (2010 SUMER survey) and 24,486 employees (2003 SUMER survey). Psychosocial work factors included the job strain model factors (Job Content Questionnaire): psychological demands, decision latitude, social support, job strain and iso-strain. Job title was defined by three variables: occupation and economic activity coded using standard classifications, and company size. A JEM was constructed using a segmentation method (Classification and Regression Tree-CART) and cross-validation. The best quality JEM was found using occupation and company size for social support. For decision latitude and psychological demands, there was not much difference using occupation and company size with or without economic activity. The validity of the JEM estimates was higher for decision latitude, job strain and iso-strain, and lower for social support and psychological demands. Differential changes over time were observed for psychosocial work factors according to occupation, economic activity and company size. This study demonstrated that company size in addition to occupation may improve the validity of JEMs for psychosocial work factors. These matrices may be time-dependent and may need to be updated over time. More research is needed to assess the validity of JEMs given that these matrices may be able to provide exposure assessments to study a range of health outcomes.
Polymer-mediated nanorod self-assembly predicted by dissipative particle dynamics simulations.

PubMed

Khani, Shaghayegh; Jamali, Safa; Boromand, Arman; Hore, Michael J A; Maia, Joao

2015-09-14

Self-assembly of nanoparticles in polymer matrices is an interesting and growing subject in the field of nanoscience and technology. We report herein on modelling studies of the self-assembly and phase behavior of nanorods in a homopolymer matrix, with the specific goal of evaluating the role of deterministic entropic and enthalpic factors that control the aggregation/dispersion in such systems. Grafting polymer brushes from the nanorods is one approach to control/impact their self-assembly capabilities within a polymer matrix. From an energetic point of view, miscible interactions between the brush and the matrix are required for achieving a better dispersibility; however, grafting density and brush length are the two important parameters in dictating the morphology. Unlike in previous computational studies, the present Dissipative Particle Dynamics (DPD) simulation framework is able to both predict dispersion or aggregation of nanorods and determine the self-assembled structure, allowing for the determination of a phase diagram, which takes all of these factors into account. Three types of morphologies are predicted: dispersion, aggregation and partial aggregation. Moreover, favorable enthalpic interactions between the brush and the matrix are found to be essential for expanding the window for achieving a well-dispersed morphology. A three-dimensional phase diagram is mapped on which all the afore-mentioned parameters are taken into account. Additionally, in the case of immiscibility between brushes and the matrix, simulations predict the formation of some new and tunable structures.
Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM2.5

PubMed Central

Dutton, Steven J.; Vedal, Sverre; Piedrahita, Ricardo; Milford, Jana B.; Miller, Shelly L.; Hannigan, Michael P.

2012-01-01

Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements. In this study, PM2.5 source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM2.5 measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF. Sensitivity of the PMF2 and ME2 models to the selection of speciated PM2.5 components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM2.5 emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers. PMID:22768005
Structured and Collaborative Signal Models: Theory and Applications in Image, Video, and Audio Analysis

DTIC Science & Technology

2013-01-01

Received Paper 01/22/2013 12.00 E. Esser, M. Moller, S. Osher, G. Sapiro, and J . Xin. A convex modelfor non-negative matrix factorization and...Ernie Esser, Michael M¨ oller , Stanley Osher, Guillermo Sapiro, Jack Xin. A convex model for non-negative matrixfactorization and dimensionality...still have one patent pending (with Adobe): X. Bai, J . Wang, and G. Sapiro, Methods and apparatus for dynamic color modeling. Patents Awarded Awards
Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

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

2013-01-01

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

PubMed Central

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

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016
Elastic-plastic finite element analyses of an unidirectional, 9 vol percent tungsten fiber reinforced copper matrix composite

NASA Technical Reports Server (NTRS)

Sanfeliz, Jose G.

1993-01-01

Micromechanical modeling via elastic-plastic finite element analyses were performed to investigate the effects that the residual stresses and the degree of matrix work hardening (i.e., cold-worked, annealed) have upon the behavior of a 9 vol percent, unidirectional W/Cu composite, undergoing tensile loading. The inclusion of the residual stress-containing state as well as the simulated matrix material conditions proved to be significant since the Cu matrix material exhibited plastic deformation, which affected the subsequent tensile response of the composite system. The stresses generated during cooldown to room temperature from the manufacturing temperature were more of a factor on the annealed-matrix composite, since they induced the softened matrix to plastically flow. This event limited the total load-carrying capacity of this matrix-dominated, ductile-ductile type material system. Plastic deformation of the hardened-matrix composite during the thermal cooldown stage was not considerable, therefore, the composite was able to sustain a higher stress before showing any appreciable matrix plasticity. The predicted room temperature, stress-strain response, and deformation stages under both material conditions represented upper and lower bounds characteristic of the composite's tensile behavior. The initial deformation stage for the hardened material condition showed negligible matrix plastic deformation while for the annealed state, its initial deformation stage showed extensive matrix plasticity. Both material conditions exhibited a final deformation stage where the fiber and matrix were straining plastically. The predicted stress-strain results were compared to the experimental, room temperature, tensile stress-strain curve generated from this particular composite system. The analyses indicated that the actual thermal-mechanical state of the composite's Cu matrix, represented by the experimental data, followed the annealed material condition.
The matrix peptide exporter HAF-1 signals a mitochondrial unfolded protein response by activating the transcription factor ZC376.7 in C. elegans

PubMed Central

Haynes, Cole M.; Yang, Yun; Blais, Steven P.; Neubert, Thomas A.; Ron, David

2010-01-01

Summary Genetic analyses previously implicated the matrix-localized protease ClpP in signaling the stress of protein misfolding in the mitochondrial matrix to activate nuclear encoded mitochondrial chaperone genes in C. elegans (UPRmt). Here we report that haf-1, a gene encoding a mitochondria-localized ATP-binding cassette protein, is required for signaling within the UPRmt and for coping with misfolded protein stress. Peptide efflux from isolated mitochondria was ATP-dependent and required HAF-1 and the protease ClpP. Defective UPRmt signaling in the haf-1 deleted worms was associated with failure of the bZIP protein, ZC376.7, to localize to nuclei in worms with perturbed mitochondrial protein folding, whereas zc376.7(RNAi) strongly inhibited the UPRmt. These observations suggest a simple model whereby perturbation of the protein-folding environment in the mitochondrial matrix promotes ClpP-mediated generation of peptides whose haf-1-dependent export from the matrix contributes to UPRmt signaling across the mitochondrial inner membrane. PMID:20188671
Neutrinoless ββ decay mediated by the exchange of light and heavy neutrinos: the role of nuclear structure correlations

NASA Astrophysics Data System (ADS)

Menéndez, J.

2018-01-01

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

NASA Astrophysics Data System (ADS)

Aoki, Yasumichi; Izubuchi, Taku; Shintani, Eigo; Soni, Amarjit

2017-07-01

We present an improved result for the lattice computation of the proton decay matrix elements in Nf=2 +1 QCD. In this study, by adopting the error reduction technique of all-mode-averaging, a significant improvement of the statistical accuracy is achieved for the relevant form factor of proton (and also neutron) decay on the gauge ensemble of Nf=2 +1 domain-wall fermions with mπ=0.34 - 0.69 GeV on a 2.7 fm3 lattice, as used in our previous work [1]. We improve the total accuracy of matrix elements to 10-15% from 30-40% for p →π e+ or from 20-40% for p →K ν ¯. The accuracy of the low-energy constants α and β in the leading-order baryon chiral perturbation theory (BChPT) of proton decay are also improved. The relevant form factors of p →π estimated through the "direct" lattice calculation from the three-point function appear to be 1.4 times smaller than those from the "indirect" method using BChPT with α and β . It turns out that the utilization of our result will provide a factor 2-3 larger proton partial lifetime than that obtained using BChPT. We also discuss the use of these parameters in a dark matter model.
Elastase and matrix metalloproteinase activities are associated with pulmonary vascular disease in the nitrofen rat model of congenital diaphragmatic hernia.

PubMed

Wild, Benjamin; St-Pierre, Marie-Eve; Langlois, Stéphanie; Cowan, Kyle N

2017-05-01

Pulmonary vascular disease (PVD) is a leading cause of congenital diaphragmatic hernia (CDH) mortality. Progression of PVD involves extracellular matrix remodeling by elastases and matrix metalloproteinases (MMP), concomitant with proliferation of smooth muscle cells in a growth factor-enriched environment. Blockade of this pathway reversed primary pulmonary hypertension and improved survival. This study was designed to determine whether a similar pathway is induced in PVD secondary to CDH. Fetal rats exposed to nitrofen at gestational day 9 developed left-sided CDH and were compared at term to their non-CDH littermates by assessing histologic and biochemical features of PVD. Rats with CDH displayed right ventricle hypertrophy, increased pulmonary artery medial wall thickness and muscularization, and decreased lumen size. As revealed by in situ zymography and immunohistochemistry, this was associated with an induction of elastolytic and MMP activities as well as an elevation of epidermal growth factor and osteopontin levels in the diseased lung vasculature. CDH-associated PVD involves an induction of elastase and MMP activities and increased osteopontin deposition in an epidermal growth factor-rich environment. Inhibition of this pathway may thus represent a novel therapeutic approach for the treatment of CDH-associated PVD. Level I (Basic Science Study). Copyright © 2017 Elsevier Inc. All rights reserved.
An Efficient Scheme for Updating Sparse Cholesky Factors

NASA Technical Reports Server (NTRS)

Raghavan, Padma

2002-01-01

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

NASA Astrophysics Data System (ADS)

Loot, A.; Hizhnyakov, V.

2018-05-01

A numerical study of the enhancement of the spontaneous parametric down-conversion in plasmonic and dielectric structures is considered. The modeling is done using a nonlinear transfer-matrix method which is extended to include vacuum fluctuations and realistic waves (e.g. Gaussian beam). The results indicate that in the case of short-range surface plasmon polaritons, the main limiting factor of the enhancement is the short length of the coherent buildup. In the case of long-range surface plasmon polaritons or dielectric guided waves, the very narrow resonances are the main limiting factor instead.
Dual permeability flow behavior for modeling horizontal well production in fractured-vuggy carbonate reservoirs

NASA Astrophysics Data System (ADS)

Guo, Jian-Chun; Nie, Ren-Shi; Jia, Yong-Lu

2012-09-01

SummaryFractured-vuggy carbonate reservoirs are composed of by matrix, fracture, and vug systems. This paper is the first investigation into the dual permeability flow issue for horizontal well production in a fractured-vuggy carbonate reservoir. Considering dispersed vugs in carbonate reservoirs and treating media directly connected with horizontal wellbore as the matrix and fracture systems, a test analysis model of a horizontal well was created, and triple porosity and dual permeability flow behavior were modeled. Standard log-log type curves were drawn up by numerical simulation and flow behavior characteristics were thoroughly analyzed. Numerical simulations showed that type curves are dominated by external boundary conditions as well as the permeability ratio of the fracture system to the sum of fracture and matrix systems. The parameter κ is only relevant to the dual permeability model, and if κ is one, then the dual permeability model is equivalent to the single permeability model. There are seven main flow regimes with constant rate of horizontal well production and five flow regimes with constant wellbore pressure of horizontal well production; different flow regimes have different flow behavior characteristics. Early radial flow and linear flow regimes are typical characteristics of horizontal well production; duration of early radial flow regime is usually short because formation thickness is generally less than 100 m. Derivative curves are W-shaped, which is a reflection of inter-porosity flows between matrix, fracture, and vug systems. A distorted W-shape, which could be produced in certain situations, such as one involving an erroneously low time of inter-porosity flows, would handicap the recognition of a linear flow regime. A real case application was successfully implemented, and some useful reservoir parameters (e.g., permeability and inter-porosity flow factor) were obtained from well testing interpretation.
Strategies to Enhance the Model Update in Regions of Weak Sensitivities for Use in Full Waveform Inversion

NASA Astrophysics Data System (ADS)

Nuber, André; Manukyan, Edgar; Maurer, Hansruedi

2014-05-01

Conventional methods of interpreting seismic data rely on filtering and processing limited portions of the recorded wavefield. Typically, either reflections, refractions or surface waves are considered in isolation. Particularly in near-surface engineering and environmental investigations (depths less than, say 100 m), these wave types often overlap in time and are difficult to separate. Full waveform inversion is a technique that seeks to exploit and interpret the full information content of the seismic records without the need for separating events first; it yields models of the subsurface at sub-wavelength resolution. We use a finite element modelling code to solve the 2D elastic isotropic wave equation in the frequency domain. This code is part of a Gauss-Newton inversion scheme which we employ to invert for the P- and S-wave velocities as well as for density in the subsurface. For shallow surface data the use of an elastic forward solver is essential because surface waves often dominate the seismograms. This leads to high sensitivities (partial derivatives contained in the Jacobian matrix of the Gauss-Newton inversion scheme) and thus large model updates close to the surface. Reflections from deeper structures may also include useful information, but the large sensitivities of the surface waves often preclude this information from being fully exploited. We have developed two methods that balance the sensitivity distributions and thus may help resolve the deeper structures. The first method includes equilibrating the columns of the Jacobian matrix prior to every inversion step by multiplying them with individual scaling factors. This is expected to also balance the model updates throughout the entire subsurface model. It can be shown that this procedure is mathematically equivalent to balancing the regularization weights of the individual model parameters. A proper choice of the scaling factors required to balance the Jacobian matrix is critical. We decided to normalise the columns of the Jacobian based on their absolute column sum, but defining an upper threshold for the scaling factors. This avoids particularly small and therefore insignificant sensitivities being over-boosted, which would produce unstable results. The second method proposed includes adjusting the inversion cell size with depth. Multiple cells of the forward modelling grid are merged to form larger inversion cells (typical ratios between forward and inversion cells are in the order of 1:100). The irregular inversion grid is adapted to the expected resolution power of full waveform inversion. Besides stabilizing the inversion, this approach also reduces the number of model parameters to be recovered. Consequently, the computational costs and the memory consumption are reduced significantly. This is particularly critical when Gauss-Newton type inversion schemes are employed. Extensive tests with synthetic data demonstrated that both methods stabilise the inversion and improve the inversion results. The two methods have some redundancy, which can be seen when both are applied simultaneously, that is, when scaling of the Jacobian matrix is applied to an irregular inversion grid. The calculated scaling factors are quite balanced and span a much smaller range than in the case of a regular inversion grid.
A novel in vitro bovine cartilage punch model for assessing the regeneration of focal cartilage defects with biocompatible bacterial nanocellulose.

PubMed

Pretzel, David; Linss, Stefanie; Ahrem, Hannes; Endres, Michaela; Kaps, Christian; Klemm, Dieter; Kinne, Raimund W

2013-01-01

Current therapies for articular cartilage defects fail to achieve qualitatively sufficient tissue regeneration, possibly because of a mismatch between the speed of cartilage rebuilding and the resorption of degradable implant polymers. The present study focused on the self-healing capacity of resident cartilage cells in conjunction with cell-free and biocompatible (but non-resorbable) bacterial nanocellulose (BNC). This was tested in a novel in vitro bovine cartilage punch model. Standardized bovine cartilage discs with a central defect filled with BNC were cultured for up to eight weeks with/without stimulation with transforming growth factor-β1 (TGF-β1. Cartilage formation and integrity were analyzed by histology, immunohistochemistry and electron microscopy. Content, release and neosynthesis of the matrix molecules proteoglycan/aggrecan, collagen II and collagen I were also quantified. Finally, gene expression of these molecules was profiled in resident chondrocytes and chondrocytes migrated onto the cartilage surface or the implant material. Non-stimulated and especially TGF-β1-stimulated cartilage discs displayed a preserved structural and functional integrity of the chondrocytes and surrounding matrix, remained vital in long-term culture (eight weeks) without signs of degeneration and showed substantial synthesis of cartilage-specific molecules at the protein and mRNA level. Whereas mobilization of chondrocytes from the matrix onto the surface of cartilage and implant was pivotal for successful seeding of cell-free BNC, chondrocytes did not immigrate into the central BNC area, possibly due to the relatively small diameter of its pores (2 to 5 μm). Chondrocytes on the BNC surface showed signs of successful redifferentiation over time, including increase of aggrecan/collagen type II mRNA, decrease of collagen type I mRNA and initial deposition of proteoglycan and collagen type II in long-term high-density pellet cultures. Although TGF-β1 stimulation showed protective effects on matrix integrity, effects on other parameters were limited. The present bovine cartilage punch model represents a robust, reproducible and highly suitable tool for the long-term culture of cartilage, maintaining matrix integrity and homoeostasis. As an alternative to animal studies, this model may closely reflect early stages of cartilage regeneration, allowing the evaluation of promising biomaterials with/without chondrogenic factors.
A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing

PubMed Central

Wang, Guoli; Ebrahimi, Nader

2014-01-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H, such that V ∼ W H. It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H. In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data. PMID:25821345

A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing.

PubMed

Devarajan, Karthik; Wang, Guoli; Ebrahimi, Nader

2015-04-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H , such that V ∼ W H . It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H . In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data.
17 beta-estradiol and tamoxifen upregulate estrogen receptor beta expression and control podocyte signaling pathways in a model of type 2 diabetes.

PubMed

Catanuto, Paola; Doublier, Sophie; Lupia, Enrico; Fornoni, Alessia; Berho, Mariana; Karl, Michael; Striker, Gary E; Xia, Xiaomei; Elliot, Sharon

2009-06-01

Diabetic nephropathy remains one of the most important causes of end-stage renal disease. This is particularly true for women from racial/ethnic minorities. Although administration of 17beta-estradiol to diabetic animals has been shown to reduce extracellular matrix deposition in glomeruli and mesangial cells, effects on podocytes are lacking. Given that podocyte injury has been implicated as a factor leading to the progression of proteinuria and diabetic nephropathy, we treated db/db mice, a model of type 2 diabetic glomerulosclerosis, with 17beta-estradiol or tamoxifen to determine whether these treatments reduce podocyte injury and decrease glomerulosclerosis. We found that albumin excretion, glomerular volume, and extracellular matrix accumulation were decreased in these mice compared to placebo treatment. Podocytes isolated from all treatment groups were immortalized and these cell lines were found to express the podocyte markers WT-1, nephrin, and the TRPC6 cation channel. Tamoxifen and 17beta-estradiol treatment decreased podocyte transforming growth factor-beta mRNA expression but increased that of the estrogen receptor subtype beta protein. 17beta-estradiol, but not tamoxifen, treatment decreased extracellular-regulated kinase phosphorylation. These data, combined with improved albumin excretion, reduced glomerular size, and decreased matrix accumulation, suggest that both 17beta-estradiol and tamoxifen may protect podocytes against injury and therefore ameliorate diabetic nephropathy.
Information matrix estimation procedures for cognitive diagnostic models.

PubMed

Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

2018-03-06

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.
[Mobbing: a meta-analysis and integrative model of its antecedents and consequences].

PubMed

Topa Cantisano, Gabriela; Depolo, Marco; Morales Domínguez, J Francisco

2007-02-01

Although mobbing has been extensively studied, empirical research has not led to firm conclusions regarding its antecedents and consequences, both at personal and organizational levels. An extensive literature search yielded 86 empirical studies with 93 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported hypotheses regarding organizational environmental factors as main predictors of mobbing.
Experiences from the testing of a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.
Experience gained in testing a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift, and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.
Technique for information retrieval using enhanced latent semantic analysis generating rank approximation matrix by factorizing the weighted morpheme-by-document matrix

DOEpatents

Chew, Peter A; Bader, Brett W

2012-10-16

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

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

Castellote, M.; Andrade, C.

This paper presents a model for the carbonation of cementitious matrixes (UR-CORE). The model is based on the principles of the 'unreacted-core' systems, typical of chemical engineering processes, in which the reacted product remains in the solid as a layer of inert ash, adapted for the specific case of carbonation. Development of the model has been undertaken in three steps: 1) Establishment of the controlling step in the global carbonation rate, by using data of fractional conversion of different phases of the cementitious matrixes, obtained by the authors through neutron diffraction data experiments, and reported in [M. Castellote, C. Andrade,more » X. Turrillas, J. Campo, G. Cuello, Accelerated carbonation of cement pastes in situ monitored by neutron diffraction, Cem. Concr. Res. (2008), doi:10.1016/j.cemconres.2008.07.002]. 2) Then, the model has been adapted and applied to the cementitious materials using different concentrations of CO{sub 2}, with the introduction of the needed assumptions and factors. 3) Finally, the model has been validated with laboratory data at different concentrations (taken from literature) and for long term natural exposure of concretes. As a result, the model seems to be reliable enough to be applied to cementitious materials, being able to extrapolate the results from accelerated tests in any conditions to predict the rate of carbonation in natural exposure, being restricted, at present stage, to conditions with a constant relative humidity.« less
Prolonged survival of transplanted stem cells after ischaemic injury via the slow release of pro-survival peptides from a collagen matrix

PubMed Central

Lee, Andrew S.; Inayathullah, Mohammed; Lijkwan, Maarten A.; Zhao, Xin; Sun, Wenchao; Park, Sujin; Hong, Wan Xing; Parekh, Mansi B.; Malkovskiy, Andrey V.; Lau, Edward; Qin, Xulei; Pothineni, Venkata Raveendra; Sanchez-Freire, Verónica; Zhang, Wendy Y.; Kooreman, Nigel G.; Ebert, Antje D.; Chan, Charles K. F.; Nguyen, Patricia K.; Rajadas, Jayakumar; Wu, Joseph C.

2018-01-01

Stem-cell-based therapies hold considerable promise for regenerative medicine. However, acute donor-cell death within several weeks after cell delivery remains a critical hurdle for clinical translation. Co-transplantation of stem cells with pro-survival factors can improve cell engraftment, but this strategy has been hampered by the typically short half-lives of the factors and by the use of Matrigel and other scaffolds that are not chemically defined. Here, we report a collagen–dendrimer biomaterial crosslinked with pro-survival peptide analogues that adheres to the extracellular matrix and slowly releases the peptides, significantly prolonging stem cell survival in mouse models of ischaemic injury. The biomaterial can serve as a generic delivery system to improve functional outcomes in cell-replacement therapy. PMID:29721363
Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment.

PubMed

Anderson, Alexander R A; Weaver, Alissa M; Cummings, Peter T; Quaranta, Vito

2006-12-01

Emergence of invasive behavior in cancer is life-threatening, yet ill-defined due to its multifactorial nature. We present a multiscale mathematical model of cancer invasion, which considers cellular and microenvironmental factors simultaneously and interactively. Unexpectedly, the model simulations predict that harsh tumor microenvironment conditions (e.g., hypoxia, heterogenous extracellular matrix) exert a dramatic selective force on the tumor, which grows as an invasive mass with fingering margins, dominated by a few clones with aggressive traits. In contrast, mild microenvironment conditions (e.g., normoxia, homogeneous matrix) allow clones with similar aggressive traits to coexist with less aggressive phenotypes in a heterogeneous tumor mass with smooth, noninvasive margins. Thus, the genetic make-up of a cancer cell may realize its invasive potential through a clonal evolution process driven by definable microenvironmental selective forces. Our mathematical model provides a theoretical/experimental framework to quantitatively characterize this selective pressure for invasion and test ways to eliminate it.
Removing flicker based on sparse color correspondences in old film restoration

NASA Astrophysics Data System (ADS)

Huang, Xi; Ding, Youdong; Yu, Bing; Xia, Tianran

2018-04-01

In the long history of human civilization, archived film is an indispensable part of it, and using digital method to repair damaged film is also a mainstream trend nowadays. In this paper, we propose a sparse color correspondences based technique to remove fading flicker for old films. Our model, combined with multi frame images to establish a simple correction model, includes three key steps. Firstly, we recover sparse color correspondences in the input frames to build a matrix with many missing entries. Secondly, we present a low-rank matrix factorization approach to estimate the unknown parameters of this model. Finally, we adopt a two-step strategy that divide the estimated parameters into reference frame parameters for color recovery correction and other frame parameters for color consistency correction to remove flicker. Our method combined multi-frames takes continuity of the input sequence into account, and the experimental results show the method can remove fading flicker efficiently.
Could a Weak Coupling Massless SU(5) Theory Underly the Standard Model S-Matrix

NASA Astrophysics Data System (ADS)

White, Alan R.

2011-04-01

The unitary Critical Pomeron connects to a unique massless left-handed SU(5) theory that, remarkably, might provide an unconventional underlying unification for the Standard Model. Multi-regge theory suggests the existence of a bound-state high-energy S-Matrix that replicates Standard Model states and interactions via massless fermion anomaly dynamics. Configurations of anomalous wee gauge boson reggeons play a vacuum-like role. All particles, including neutrinos, are bound-states with dynamical masses (there is no Higgs field) that are formed (in part) by anomaly poles. The contributing zero-momentum chirality transitions break the SU(5) symmetry to vector SU(3)⊗U(1) in the S-Matrix. The high-energy interactions are vector reggeon exchanges accompanied by wee boson sums (odd-signature for the strong interaction and even-signature for the electroweak interaction) that strongly enhance couplings. The very small SU(5) coupling, αQUD ≲ 1/120, should be reflected in small (Majorana) neutrino masses. A color sextet quark sector, still to be discovered, produces both Dark Matter and Electroweak Symmetry Breaking. Anomaly color factors imply this sector could be produced at the LHC with large cross-sections, and would be definitively identified in double pomeron processes.
Effect of molecular anisotropy on the intensity and degree of polarization of light scattered from model atmospheres

NASA Technical Reports Server (NTRS)

Bahethi, O. P.; Fraser, R. S.

1975-01-01

Computations of the intensity, flux, degree of polarization, and the positions of neutral points are presented for models of the terrestrial gaseous and hazy atmospheres by incorporating the molecular anisotropy due to air in the Rayleigh scattering optical thickness and phase matrix. Molecular anisotropy causes significant changes in the intensity, flux and the degree of polarization of the scattered light. The positions of neutral points do not change significantly. When the Rayleigh scattering optical thickness is kept constant and the molecular anisotropy factor is included only in the Rayleigh phase matrix, the flux does not change and the intensity and positions of neutron points change by a small amount. The changes in the degree of polarization are still significant.
Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel-kerosene mixtures: a comparative study.

PubMed

Divya, O; Mishra, Ashok K

2007-05-29

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.
Visco-elastic controlled-source full waveform inversion without surface waves

NASA Astrophysics Data System (ADS)

Paschke, Marco; Krause, Martin; Bleibinhaus, Florian

2016-04-01

We developed a frequency-domain visco-elastic full waveform inversion for onshore seismic experiments with topography. The forward modeling is based on a finite-difference time-domain algorithm by Robertsson that uses the image-method to ensure a stress-free condition at the surface. The time-domain data is Fourier-transformed at every point in the model space during the forward modeling for a given set of frequencies. The motivation for this approach is the reduced amount of memory when computing kernels, and the straightforward implementation of the multiscale approach. For the inversion, we calculate the Frechet derivative matrix explicitly, and we implement a Levenberg-Marquardt scheme that allows for computing the resolution matrix. To reduce the size of the Frechet derivative matrix, and to stabilize the inversion, an adapted inverse mesh is used. The node spacing is controlled by the velocity distribution and the chosen frequencies. To focus the inversion on body waves (P, P-coda, and S) we mute the surface waves from the data. Consistent spatiotemporal weighting factors are applied to the wavefields during the Fourier transform to obtain the corresponding kernels. We test our code with a synthetic study using the Marmousi model with arbitrary topography. This study also demonstrates the importance of topography and muting surface waves in controlled-source full waveform inversion.
Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions

PubMed Central

Cai, Xiaonan; Wang, Chen; Chen, Shengdi; Lu, Jian

2016-01-01

Rainy weather conditions could result in significantly negative impacts on driving on freeways. However, due to lack of enough historical data and monitoring facilities, many regions are not able to establish reliable risk assessment models to identify such impacts. Given the situation, this paper provides an alternative solution where the procedure of risk assessment is developed based on drivers’ subjective questionnaire and its performance is validated by using actual crash data. First, an ordered logit model was developed, based on questionnaire data collected from Freeway G15 in China, to estimate the relationship between drivers’ perceived risk and factors, including vehicle type, rain intensity, traffic volume, and location. Then, weighted driving risk for different conditions was obtained by the model, and further divided into four levels of early warning (specified by colors) using a rank order cluster analysis. After that, a risk matrix was established to determine which warning color should be disseminated to drivers, given a specific condition. Finally, to validate the proposed procedure, actual crash data from Freeway G15 were compared with the safety prediction based on the risk matrix. The results show that the risk matrix obtained in the study is able to predict driving risk consistent with actual safety implications, under rainy weather conditions. PMID:26894434
Designing Feature and Data Parallel Stochastic Coordinate Descent Method forMatrix and Tensor Factorization

DTIC Science & Technology

2016-05-11

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

PubMed

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 Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.
A Green's function method for two-dimensional reactive solute transport in a parallel fracture-matrix system

NASA Astrophysics Data System (ADS)

Chen, Kewei; Zhan, Hongbin

2018-06-01

The reactive solute transport in a single fracture bounded by upper and lower matrixes is a classical problem that captures the dominant factors affecting transport behavior beyond pore scale. A parallel fracture-matrix system which considers the interaction among multiple paralleled fractures is an extension to a single fracture-matrix system. The existing analytical or semi-analytical solution for solute transport in a parallel fracture-matrix simplifies the problem to various degrees, such as neglecting the transverse dispersion in the fracture and/or the longitudinal diffusion in the matrix. The difficulty of solving the full two-dimensional (2-D) problem lies in the calculation of the mass exchange between the fracture and matrix. In this study, we propose an innovative Green's function approach to address the 2-D reactive solute transport in a parallel fracture-matrix system. The flux at the interface is calculated numerically. It is found that the transverse dispersion in the fracture can be safely neglected due to the small scale of fracture aperture. However, neglecting the longitudinal matrix diffusion would overestimate the concentration profile near the solute entrance face and underestimate the concentration profile at the far side. The error caused by neglecting the longitudinal matrix diffusion decreases with increasing Peclet number. The longitudinal matrix diffusion does not have obvious influence on the concentration profile in long-term. The developed model is applied to a non-aqueous-phase-liquid (DNAPL) contamination field case in New Haven Arkose of Connecticut in USA to estimate the Trichloroethylene (TCE) behavior over 40 years. The ratio of TCE mass stored in the matrix and the injected TCE mass increases above 90% in less than 10 years.
Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

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

Cost analysis of composite fan blade manufacturing processes

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

NASA Technical Reports Server (NTRS)

Cwik, Tom; Patterson, Jean; Scott, David

1992-01-01

During the first year's operation of the Intel Touchstone Delta system, software which solves the electric field integral equations for fields scattered from arbitrarily shaped objects has been transferred to the Delta. To fully realize the Delta's resources, an out-of-core dense matrix solution algorithm that utilizes some or all of the 90 Gbyte of concurrent file system (CFS) has been used. The largest calculation completed to date computes the fields scattered from a perfectly conducting sphere modeled by 48,672 unknown functions, resulting in a complex valued dense matrix needing 37.9 Gbyte of storage. The out-of-core LU matrix factorization algorithm was executed in 8.25 h at a rate of 10.35 Gflops. Total time to complete the calculation was 19.7 h-the additional time was used to compute the 48,672 x 48,672 matrix entries, solve the system for a given excitation, and compute observable quantities. The calculation was performed in 64-b precision.
Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.
Clonorchis sinensis excretory-secretory products regulate migration and invasion in cholangiocarcinoma cells via extracellular signal-regulated kinase 1/2/nuclear factor-κB-dependent matrix metalloproteinase-9 expression.

PubMed

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

2017-01-01

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

PubMed Central

Fischer, Christin; Deininger, Natalie; Wolf, Gunter; Loeffler, Ivonne

2018-01-01

Tubulointerstitial fibrosis (TIF) is a pivotal pathophysiological process in patients with diabetic nephropathy (DN). Multiple profibrotic factors and cell types, including transforming growth factor beta 1 (TGF-β1) and interstitial myofibroblasts, respectively, are responsible for the accumulation of extracellular matrix in the kidney. Matrix-producing myofibroblasts can originate from different sources and different mechanisms are involved in the activation process of the myofibroblasts in the fibrotic kidney. In this study, 16-week-old db/db mice, a model for type 2 DN, were treated for two weeks with continuous erythropoietin receptor activator (CERA), a synthetic erythropoietin variant with possible non-hematopoietic, tissue-protective effects. Non-diabetic and diabetic mice treated with placebo were used as controls. The effects of CERA on tubulointerstitial fibrosis (TIF) as well as on the generation of the matrix-producing myofibroblasts were evaluated by morphological, immunohistochemical, and molecular biological methods. The placebo-treated diabetic mice showed significant signs of beginning renal TIF (shown by picrosirius red staining; increased connective tissue growth factor (CTGF), fibronectin and collagen I deposition; upregulated KIM1 expression) together with an increased number of interstitial myofibroblasts (shown by different mesenchymal markers), while kidneys from diabetic mice treated with CERA revealed less TIF and fewer myofibroblasts. The mechanisms, in which CERA acts as an anti-fibrotic agent/drug, seem to be multifaceted: first, CERA inhibits the generation of matrix-producing myofibroblasts and second, CERA increases the ability for tissue repair. Many of these CERA effects can be explained by the finding that CERA inhibits the renal expression of the cytokine TGF-β1. PMID:29385703
CERA Attenuates Kidney Fibrogenesis in the db/db Mouse by Influencing the Renal Myofibroblast Generation.

PubMed

Fischer, Christin; Deininger, Natalie; Wolf, Gunter; Loeffler, Ivonne

2018-01-30

Tubulointerstitial fibrosis (TIF) is a pivotal pathophysiological process in patients with diabetic nephropathy (DN). Multiple profibrotic factors and cell types, including transforming growth factor beta 1 (TGF-β1) and interstitial myofibroblasts, respectively, are responsible for the accumulation of extracellular matrix in the kidney. Matrix-producing myofibroblasts can originate from different sources and different mechanisms are involved in the activation process of the myofibroblasts in the fibrotic kidney. In this study, 16-week-old db / db mice, a model for type 2 DN, were treated for two weeks with continuous erythropoietin receptor activator (CERA), a synthetic erythropoietin variant with possible non-hematopoietic, tissue-protective effects. Non-diabetic and diabetic mice treated with placebo were used as controls. The effects of CERA on tubulointerstitial fibrosis (TIF) as well as on the generation of the matrix-producing myofibroblasts were evaluated by morphological, immunohistochemical, and molecular biological methods. The placebo-treated diabetic mice showed significant signs of beginning renal TIF (shown by picrosirius red staining; increased connective tissue growth factor (CTGF), fibronectin and collagen I deposition; upregulated KIM1 expression) together with an increased number of interstitial myofibroblasts (shown by different mesenchymal markers), while kidneys from diabetic mice treated with CERA revealed less TIF and fewer myofibroblasts. The mechanisms, in which CERA acts as an anti-fibrotic agent/drug, seem to be multifaceted: first, CERA inhibits the generation of matrix-producing myofibroblasts and second, CERA increases the ability for tissue repair. Many of these CERA effects can be explained by the finding that CERA inhibits the renal expression of the cytokine TGF-β1.
A tight and explicit representation of Q in sparse QR factorization

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

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

1992-05-01

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

NASA Technical Reports Server (NTRS)

Tsuyuki, Glenn T.

1994-01-01

Report describes algorithm that adjusts form-factor matrix in TRASYS computer program, which calculates intraspacecraft radiative interchange among various surfaces and environmental heat loading from sources such as sun.
Quantitative evaluation of the matrix effect in bioanalytical methods based on LC-MS: A comparison of two approaches.

PubMed

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

2018-06-05

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

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting Candy; Liao, Hong-Yuan Mark

2013-08-27

Tensor completion, which is a high-order extension of matrix completion, has generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called Simultaneous Tensor Decomposition and Completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data, and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.
Table-sized matrix model in fractional learning

NASA Astrophysics Data System (ADS)

Soebagyo, J.; Wahyudin; Mulyaning, E. C.

2018-05-01

This article provides an explanation of the fractional learning model i.e. a Table-Sized Matrix model in which fractional representation and its operations are symbolized by the matrix. The Table-Sized Matrix are employed to develop problem solving capabilities as well as the area model. The Table-Sized Matrix model referred to in this article is used to develop an understanding of the fractional concept to elementary school students which can then be generalized into procedural fluency (algorithm) in solving the fractional problem and its operation.
The Impact of Select Pollutant Sources on Air Quality and the Moravian-Silesian Metropolitan Region by the Positive Matrix Factorization Model

EPA Science Inventory

The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EP...
Adipose Extracellular Matrix/Stromal Vascular Fraction Gel Secretes Angiogenic Factors and Enhances Skin Wound Healing in a Murine Model.

PubMed

Sun, Mingliang; He, Yunfan; Zhou, Tao; Zhang, Pan; Gao, Jianhua; Lu, Feng

2017-01-01

Mesenchymal stem cells are an attractive cell type for cytotherapy in wound healing. The authors recently developed a novel, adipose-tissue-derived, injectable extracellular matrix/stromal vascular fraction gel (ECM/SVF-gel) for stem cell therapy. This study was designed to assess the therapeutic effects of ECM/SVF-gel on wound healing and potential mechanisms. ECM/SVF-gel was prepared for use in nude mouse excisional wound healing model. An SVF cell suspension and phosphate-buffered saline injection served as the control. The expression levels of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), and monocyte chemotactic protein-1 (MCP-1) in ECM/SVF-gel were analyzed at different time points. Angiogenesis (tube formation) assays of ECM/SVF-gel extracts were evaluated, and vessels density in skin was determined. The ECM/SVF-gel extract promoted tube formation in vitro and increased the expression of the angiogenic factors VEGF and bFGF compared with those in the control. The expression of the inflammatory chemoattractant MCP-1 was high in ECM/SVF-gel at the early stage and decreased sharply during the late stage of wound healing. The potent angiogenic effects exerted by ECM/SVF-gel may contribute to the improvement of wound healing, and these effects could be related to the enhanced inflammatory response in ECM/SVF-gel during the early stage of wound healing.
Stochastic model of the NASA/MSFC ground facility for large space structures with uncertain parameters: The maximum entropy approach, part 2

NASA Technical Reports Server (NTRS)

Hsia, Wei Shen

1989-01-01

A validated technology data base is being developed in the areas of control/structures interaction, deployment dynamics, and system performance for Large Space Structures (LSS). A Ground Facility (GF), in which the dynamics and control systems being considered for LSS applications can be verified, was designed and built. One of the important aspects of the GF is to verify the analytical model for the control system design. The procedure is to describe the control system mathematically as well as possible, then to perform tests on the control system, and finally to factor those results into the mathematical model. The reduction of the order of a higher order control plant was addressed. The computer program was improved for the maximum entropy principle adopted in Hyland's MEOP method. The program was tested against the testing problem. It resulted in a very close match. Two methods of model reduction were examined: Wilson's model reduction method and Hyland's optimal projection (OP) method. Design of a computer program for Hyland's OP method was attempted. Due to the difficulty encountered at the stage where a special matrix factorization technique is needed in order to obtain the required projection matrix, the program was successful up to the finding of the Linear Quadratic Gaussian solution but not beyond. Numerical results along with computer programs which employed ORACLS are presented.
Joint release rate estimation and measurement-by-measurement model correction for atmospheric radionuclide emission in nuclear accidents: An application to wind tunnel experiments.

PubMed

Li, Xinpeng; Li, Hong; Liu, Yun; Xiong, Wei; Fang, Sheng

2018-03-05

The release rate of atmospheric radionuclide emissions is a critical factor in the emergency response to nuclear accidents. However, there are unavoidable biases in radionuclide transport models, leading to inaccurate estimates. In this study, a method that simultaneously corrects these biases and estimates the release rate is developed. Our approach provides a more complete measurement-by-measurement correction of the biases with a coefficient matrix that considers both deterministic and stochastic deviations. This matrix and the release rate are jointly solved by the alternating minimization algorithm. The proposed method is generic because it does not rely on specific features of transport models or scenarios. It is validated against wind tunnel experiments that simulate accidental releases in a heterogonous and densely built nuclear power plant site. The sensitivities to the position, number, and quality of measurements and extendibility of the method are also investigated. The results demonstrate that this method effectively corrects the model biases, and therefore outperforms Tikhonov's method in both release rate estimation and model prediction. The proposed approach is robust to uncertainties and extendible with various center estimators, thus providing a flexible framework for robust source inversion in real accidents, even if large uncertainties exist in multiple factors. Copyright © 2017 Elsevier B.V. All rights reserved.
Structure of four executive functioning tests in healthy older adults.

PubMed

de Frias, Cindy M; Dixon, Roger A; Strauss, Esther

2006-03-01

The authors examined the factor structure of 4 indicators of executive functioning derived from 2 new (i.e., Hayling and Brixton) and 2 traditional (i.e., Stroop and Color Trails) tests. Data were from a cross-sectional sample of 55- to 85-year-old healthy adults (N=427) from the Victoria Longitudinal Study. Confirmatory factor analysis (LISREL 8.52) tested both a 2-factor model of Inhibition (Hayling, Stroop) and Shifting (Brixton, Color Trails) and a single-factor model. The 2-factor model did not fit the data because the covariance matrix of the factors was not positive definite. The single-factor model fit the data well, chi(2)(2, N=427)=0.32, p=.85, root-mean-square error of approximation (RMSEA)=.00, comparative fit index (CFI)=1.00, goodness-of-fit index (GFI)=1.00. Moreover, the single-factor structure of executive functioning was invariant (configural and metric) across gender, and invariant (configural with limited metric) across age. Structural relations showed that poorer executive functioning performance was related to older age and lower fluid intelligence, chi(2)(11, N=418)=23.04, p=.02, RMSEA=.05, CFI=.97, GFI=.98.
Comparison of Resource Requirements for a Wind Tunnel Test Designed with Conventional vs. Modern Design of Experiments Methods

NASA Technical Reports Server (NTRS)

DeLoach, Richard; Micol, John R.

2011-01-01

The factors that determine data volume requirements in a typical wind tunnel test are identified. It is suggested that productivity in wind tunnel testing can be enhanced by managing the inference error risk associated with evaluating residuals in a response surface modeling experiment. The relationship between minimum data volume requirements and the factors upon which they depend is described and certain simplifications to this relationship are realized when specific model adequacy criteria are adopted. The question of response model residual evaluation is treated and certain practical aspects of response surface modeling are considered, including inference subspace truncation. A wind tunnel test plan developed by using the Modern Design of Experiments illustrates the advantages of an early estimate of data volume requirements. Comparisons are made with a representative One Factor At a Time (OFAT) wind tunnel test matrix developed to evaluate a surface to air missile.
Disassemblability modeling technology of configurable product based on disassembly constraint relation weighted design structure matrix(DSM)

NASA Astrophysics Data System (ADS)

Qiu, Lemiao; Liu, Xiaojian; Zhang, Shuyou; Sun, Liangfeng

2014-05-01

The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix (DSM) is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.
GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

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

2018-04-24

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

PubMed

Rahbari, Nuh N; Kedrin, Dmitriy; Incio, Joao; Liu, Hao; Ho, William W; Nia, Hadi T; Edrich, Christina M; Jung, Keehoon; Daubriac, Julien; Chen, Ivy; Heishi, Takahiro; Martin, John D; Huang, Yuhui; Maimon, Nir; Reissfelder, Christoph; Weitz, Jurgen; Boucher, Yves; Clark, Jeffrey W; Grodzinsky, Alan J; Duda, Dan G; Jain, Rakesh K; Fukumura, Dai

2016-10-12

The survival benefit of anti-vascular endothelial growth factor (VEGF) therapy in metastatic colorectal cancer (mCRC) patients is limited to a few months because of acquired resistance. We show that anti-VEGF therapy induced remodeling of the extracellular matrix with subsequent alteration of the physical properties of colorectal liver metastases. Preoperative treatment with bevacizumab in patients with colorectal liver metastases increased hyaluronic acid (HA) deposition within the tumors. Moreover, in two syngeneic mouse models of CRC metastasis in the liver, we show that anti-VEGF therapy markedly increased the expression of HA and sulfated glycosaminoglycans (sGAGs), without significantly changing collagen deposition. The density of these matrix components correlated with increased tumor stiffness after anti-VEGF therapy. Treatment-induced tumor hypoxia appeared to be the driving force for the remodeling of the extracellular matrix. In preclinical models, we show that enzymatic depletion of HA partially rescued the compromised perfusion in liver mCRCs after anti-VEGF therapy and prolonged survival in combination with anti-VEGF therapy and chemotherapy. These findings suggest that extracellular matrix components such as HA could be a potential therapeutic target for reducing physical barriers to systemic treatments in patients with mCRC who receive anti-VEGF therapy. Copyright © 2016, American Association for the Advancement of Science.

Human Umbilical Cord Mesenchymal Stem Cells Reduce Fibrosis of Bleomycin-Induced Lung Injury

PubMed Central

Moodley, Yuben; Atienza, Daniel; Manuelpillai, Ursula; Samuel, Chrishan S.; Tchongue, Jorge; Ilancheran, Sivakami; Boyd, Richard; Trounson, Alan

2009-01-01

Acute respiratory distress syndrome is characterized by loss of lung tissue as a result of inflammation and fibrosis. Augmenting tissue repair by the use of mesenchymal stem cells may be an important advance in treating this condition. We evaluated the role of term human umbilical cord cells derived from Wharton’s jelly with a phenotype consistent with mesenchymal stem cells (uMSCs) in the treatment of a bleomycin-induced mouse model of lung injury. uMSCs were administered systemically, and lungs were harvested at 7, 14, and 28 days post-bleomycin. Injected uMSCs were located in the lung 2 weeks later only in areas of inflammation and fibrosis but not in healthy lung tissue. The administration of uMSCs reduced inflammation and inhibited the expression of transforming growth factor-β, interferon-γ, and the proinflammatory cytokines macrophage migratory inhibitory factor and tumor necrosis factor-α. Collagen concentration in the lung was significantly reduced by uMSC treatment, which may have been a consequence of the simultaneous reduction in Smad2 phosphorylation (transforming growth factor-β activity). uMSCs also increased matrix metalloproteinase-2 levels and reduced their endogenous inhibitors, tissue inhibitors of matrix metalloproteinases, favoring a pro-degradative milieu following collagen deposition. Notably, injected human lung fibroblasts did not influence either collagen or matrix metalloproteinase levels in the lung. The results of this study suggest that uMSCs have antifibrotic properties and may augment lung repair if used to treat acute respiratory distress syndrome. PMID:19497992
Three-dimensional magnetotelluric inversion including topography using deformed hexahedral edge finite elements, direct solvers and data space Gauss-Newton, parallelized on SMP computers

NASA Astrophysics Data System (ADS)

Kordy, M. A.; Wannamaker, P. E.; Maris, V.; Cherkaev, E.; Hill, G. J.

2014-12-01

We have developed an algorithm for 3D simulation and inversion of magnetotelluric (MT) responses using deformable hexahedral finite elements that permits incorporation of topography. Direct solvers parallelized on symmetric multiprocessor (SMP), single-chassis workstations with large RAM are used for the forward solution, parameter jacobians, and model update. The forward simulator, jacobians calculations, as well as synthetic and real data inversion are presented. We use first-order edge elements to represent the secondary electric field (E), yielding accuracy O(h) for E and its curl (magnetic field). For very low frequency or small material admittivity, the E-field requires divergence correction. Using Hodge decomposition, correction may be applied after the forward solution is calculated. It allows accurate E-field solutions in dielectric air. The system matrix factorization is computed using the MUMPS library, which shows moderately good scalability through 12 processor cores but limited gains beyond that. The factored matrix is used to calculate the forward response as well as the jacobians of field and MT responses using the reciprocity theorem. Comparison with other codes demonstrates accuracy of our forward calculations. We consider a popular conductive/resistive double brick structure and several topographic models. In particular, the ability of finite elements to represent smooth topographic slopes permits accurate simulation of refraction of electromagnetic waves normal to the slopes at high frequencies. Run time tests indicate that for meshes as large as 150x150x60 elements, MT forward response and jacobians can be calculated in ~2.5 hours per frequency. For inversion, we implemented data space Gauss-Newton method, which offers reduction in memory requirement and a significant speedup of the parameter step versus model space approach. For dense matrix operations we use tiling approach of PLASMA library, which shows very good scalability. In synthetic inversions we examine the importance of including the topography in the inversion and we test different regularization schemes using weighted second norm of model gradient as well as inverting for a static distortion matrix following Miensopust/Avdeeva approach. We also apply our algorithm to invert MT data collected at Mt St Helens.
Micromechanism Based Modeling of Structural Life in Metal Matrix Composites

DTIC Science & Technology

1997-03-23

wWchJndttees-^anätational eigenstrain ; and the embrittlement of material at the metal-ox^ interface, in addition, the influence of various heat...of two factors: the development of a surface layer consisting primarily of stoichiometric Ti02 which induces a dilatational eigenstrain ; and the...as the dilatational eigenstrain in order to capture the life reduction mechanism. As shown in Fig. 5, for the case of monotonic loading, the model
Perceived sexual harassment at work: meta-analysis and structural model of antecedents and consequences.

PubMed

Topa Cantisano, Gabriela; Morales Domínguez, J F; Depolo, Marco

2008-05-01

Although sexual harassment has been extensively studied, empirical research has not led to firm conclusions about its antecedents and consequences, both at the personal and organizational level. An extensive literature search yielded 42 empirical studies with 60 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported the hypotheses regarding organizational environmental factors as main predictors of harassment.
ORACLS: A system for linear-quadratic-Gaussian control law design

NASA Technical Reports Server (NTRS)

Armstrong, E. S.

1978-01-01

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.
Modeling CO2 Storage in Fractured Reservoirs: Fracture-Matrix Interactions of Free-Phase and Dissolved CO2

NASA Astrophysics Data System (ADS)

Oldenburg, C. M.; Zhou, Q.; Birkholzer, J. T.

2017-12-01

The injection of supercritical CO2 (scCO2) in fractured reservoirs has been conducted at several storage sites. However, no site-specific dual-continuum modeling for fractured reservoirs has been reported and modeling studies have generally underestimated the fracture-matrix interactions. We developed a conceptual model for enhanced CO2 storage to take into account global scCO2 migration in the fracture continuum, local storage of scCO2 and dissolved CO2 (dsCO2) in the matrix continuum, and driving forces for scCO2 invasion and dsCO2 diffusion from fractures. High-resolution discrete fracture-matrix models were developed for a column of idealized matrix blocks bounded by vertical and horizontal fractures and for a km-scale fractured reservoir. The column-scale simulation results show that equilibrium storage efficiency strongly depends on matrix entry capillary pressure and matrix-matrix connectivity while the time scale to reach equilibrium is sensitive to fracture spacing and matrix flow properties. The reservoir-scale modeling results shows that the preferential migration of scCO2 through fractures is coupled with bulk storage in the rock matrix that in turn retards the fracture scCO2 plume. We also developed unified-form diffusive flux equations to account for dsCO2 storage in brine-filled matrix blocks and found solubility trapping is significant in fractured reservoirs with low-permeability matrix.
Modeling analysis on germination and seedling growth using ultrasound seed pretreatment in switchgrass.

PubMed

Wang, Quanzhen; Chen, Guo; Yersaiyiti, Hayixia; Liu, Yuan; Cui, Jian; Wu, Chunhui; Zhang, Yunwei; He, Xueqing

2012-01-01

Switchgrass is a perennial C4 plant with great potential as a bioenergy source and, thus, a high demand for establishment from seed. This research investigated the effects of ultrasound treatment on germination and seedling growth in switchgrass. Using an orthogonal matrix design, conditions for the ultrasound pretreatment in switchgrass seed, including sonication time (factor A), sonication temperature (factor B) and ultrasound output power (factor C), were optimized for germinating and stimulating seedling growth (indicated as plumular and radicular lengths) through modeling analysis. The results indicate that sonication temperature (B) was the most effective factor for germination, whereas output power (C) had the largest effect on seedling growth when ultrasound treatment was used. Combined with the analyses of range, variance and models, the final optimal ultrasonic treatment conditions were sonication for 22.5 min at 39.7°C and at an output power of 348 W, which provided the greatest germination percentage and best seedling growth. For this study, the orthogonal matrix design was an efficient method for optimizing the conditions of ultrasound seed treatment on switchgrass. The electrical conductivity of seed leachates in three experimental groups (control, soaked in water only, and ultrasound treatment) was determined to investigate the effects of ultrasound on seeds and eliminate the effect of water in the ultrasound treatments. The results showed that the electrical conductivity of seed leachates during either ultrasound treatment or water bath treatment was significantly higher than that of the control, and that the ultrasound treatment had positive effects on switchgrass seeds.
Defective Endochondral Ossification-Derived Matrix and Bone Cells Alter the Lymphopoietic Niche in Collagen X Mouse Models

PubMed Central

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

2013-01-01

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

PubMed

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

2013-10-01

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

PubMed

Oktem, Caglar; Oto, Sibel; Toru, Serap; Bakar, Coskun; Ozdemir, Handan; Akova, Yonca Aydin

2016-01-01

To evaluate the efficacy and safety of suramin, genistein and collagen matrix for the prevention of inflammation, the reduction of fibrosis and the delay in adjustment after strabismus surgery on a rabbit model. By using an adjustable suture technique, a recession of the superior rectus muscle (SRM) was made in 36 eyes of 18 rabbits. Three study groups were created using genistein, suramin and collagen matrix (n = 6 per group). Two control groups utilized dimethyl sulphoxide (DMSO) (n = 6) and balanced salt solution (n = 12). The adjustments and measurements were made on days 2, 7, 14. After enucleation was done on day 21, the degree of inflammation was evaluated quantitatively in histopathological sections and immunohistochemical investigations were performed for tissue expression of cytoplasmic vascular endothelial growth factor (VEGF), MAC 387, TGF-β and bFGF. The adhesions between conjunctiva and SRM were significantly less in the collagen matrix and suramin groups (p = 0.002) and adhesions between the sclera and SRM were considerably reduced in the genistein and DMSO groups (p = 0.006) on day 7. Force exerted for adjustment was significantly less in the collagen matrix and suramin groups on day 14 (p = 0.006). Expression of b-FGF was significantly lower in the conjunctival epithelium in the suramin and genistein groups (p = 0.0001 for both). TGF-β was significantly lower (p = 0.001) in the suramin group and VEGF expression was totally absent. MAC 387 expression was lower in the genistein and suramin groups (p = 0.0001). Suramin, genistein and collagen matrix successfully reduce adhesions, and facilitate adjustment following recession surgery. Both suramin and genistein effectively suppress growth factor expression, while collagen matrix offers the longest time interval for adjustability after strabismus surgery.
Block LU factorization

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

PubMed

Thakur, Ravi; Mishra, Durga Prasad

2016-12-01

Matricellular proteins (MCPs) are the non-structural extracellular matrix (ECM) proteins with various regulatory functions. MCPs are critical regulators of ECM homeostasis and are often found dysregulated in various malignancies. They interact with various proteins like ECM structural proteins, integrins, growth factor receptors and growth factors to modulate their availability and activity. Cancer-supporting MCPs are known to induce proliferation, migration and invasion of cancer cells. MCPs also support cancer stem (like) cell growth and induce a drug-resistant state. Apart from their direct effects on cancer cells, they play key roles in angiogenesis, immunomodulation, stromal cell infiltration, stromal proliferation and matrix remodeling. High expression of various MCPs belonging to the tenascin, CCN and SIBLING families is often associated with aggressive tumors and poor patient prognosis. Due to their differential expression and distinct functional role, these MCPs are perceived as attractive therapeutic targets in cancer. Studies on preclinical models have indicated that targeting tumor-supportive MCPs could be a potent avenue for developing anti-cancer therapies. The MCP receptors, like integrins and some associated growth factor receptors, are already being targeted using pharmacological inhibitors and neutralizing antibodies. Neutralizing antibodies against CCNs, tenascins and SIBLINGs have shown promising results in preclinical cancer models, suggesting an opportunity to develop anti-MCP therapies to target cancer. Peptides derived from anti-cancer MCPs could also serve as therapeutic entities. In the present review, in continuation with the expanding horizon of MCP functions and disease association, we focus on (i) their unique domain arrangement, (ii) their association with cancer hallmarks and (iii) available and possible therapeutic interventions. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Regulation of Osteoblast Survival by the Extracellular Matrix and Gravity

NASA Technical Reports Server (NTRS)

Globus. Ruth K.; Almeida, Eduardo A. C.; Searby, Nancy D.; Bowley, Susan M. (Technical Monitor)

2000-01-01

Spaceflight adversely affects the skeleton, posing a substantial risk to astronaut's health during long duration missions. The reduced bone mass observed in growing animals following spaceflight is due at least in part to inadequate bone formation by osteoblasts. Thus, it is of central importance to identify basic cellular mechanisms underlying normal bone formation. The fundamental ideas underlying our research are that interactions between extracellular matrix proteins, integrin adhesion receptors, cytoplasmic signaling and cytoskeletal proteins are key ingredients for the proper functioning of osteoblasts, and that gravity impacts these interactions. As an in vitro model system we used primary fetal rat calvarial cells which faithfully recapitulate osteoblast differentiation characteristically observed in vivo. We showed that specific integrin receptors ((alpha)3(beta)1), ((alpha)5(beta)1), ((alpha)8(betal)1) and extracellular matrix proteins (fibronectin, laminin) were needed for the differentiation of immature osteoblasts. In the course of maturation, cultured osteoblasts switched from depending on fibronectin and laminin for differentiation to depending on these proteins for their very survival. Furthermore, we found that manipulating the gravity vector using ground-based models resulted in activation of key intracellular survival signals generated by integrin/extracellular matrix interactions. We are currently testing the in vivo relevance of some of these observations using targeted transgenic technology. In conclusion, mechanical factors including gravity may participate in regulating survival via cellular interactions with the extracellular matrix. This leads us to speculate that microgravity adversely affects the survival of osteoblasts and contributes to spaceflight-induced osteoporosis.
Lessons on the pathogenesis of aneurysm from heritable conditions

PubMed Central

Lindsay, Mark E.; Dietz, Harry C.

2013-01-01

Aortic aneurysm is common, accounting for 1–2% of all deaths in industrialized countries. Early theories of the causes of human aneurysm mostly focused on inherited or acquired defects in components of the extracellular matrix in the aorta. Although several mutations in the genes encoding extracellular matrix proteins have been recognized, more recent discoveries have shown important perturbations in cytokine signalling cascades and intracellular components of the smooth muscle contractile apparatus. The modelling of single-gene heritable aneurysm disorders in mice has shown unexpected involvement of the transforming growth factor-β cytokine pathway in aortic aneurysm, highlighting the potential for new therapeutic strategies. PMID:21593863
Localized motion in random matrix decomposition of complex financial systems

NASA Astrophysics Data System (ADS)

Jiang, Xiong-Fei; Zheng, Bo; Ren, Fei; Qiu, Tian

2017-04-01

With the random matrix theory, we decompose the multi-dimensional time series of complex financial systems into a set of orthogonal eigenmode functions, which are classified into the market mode, sector mode, and random mode. In particular, the localized motion generated by the business sectors, plays an important role in financial systems. Both the business sectors and their impact on the stock market are identified from the localized motion. We clarify that the localized motion induces different characteristics of the time correlations for the stock-market index and individual stocks. With a variation of a two-factor model, we reproduce the return-volatility correlations of the eigenmodes.
Electrical percolation threshold of magnetostrictive inclusions in a piezoelectric matrix composite as a function of relative particle size

NASA Astrophysics Data System (ADS)

Barbero, Ever J.; Bedard, Antoine Joseph

2018-04-01

Magnetoelectric composites can be produced by embedding magnetostrictive particles in a piezoelectric matrix derived from a piezoelectric powder precursor. Ferrite magnetostrictive particles, if allowed to percolate, can short the potential difference generated in the piezoelectric phase. Modeling a magnetoelectric composite as an aggregate of bi-disperse hard shells, molecular dynamics was used to explore relationships among relative particle size, particle affinity, and electrical percolation with the goal of maximizing the percolation threshold. It is found that two factors raise the percolation threshold, namely the relative size of magnetostrictive to piezoelectric particles, and the affinity between the magnetostrictive and piezoelectric particles.
Effect of Cyclic Thermo-Mechanical Loads on Fatigue Reliability in Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Shah, A. R.; Murthy, P. L. N.; Chamis, C. C.

1996-01-01

A methodology to compute probabilistic fatigue life of polymer matrix laminated composites has been developed and demonstrated. Matrix degradation effects caused by long term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress dependent multi-factor interaction relationship developed at NASA Lewis Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability- based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/- 45/90)(sub s) graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical cyclic loads and low thermal cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical cyclic loads and high thermal cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.
Cross-linked matrix rigidity and soluble retinoids synergize in nuclear lamina regulation of stem cell differentiation.

PubMed

Ivanovska, Irena L; Swift, Joe; Spinler, Kyle; Dingal, Dave; Cho, Sangkyun; Discher, Dennis E

2017-07-07

Synergistic cues from extracellular matrix and soluble factors are often obscure in differentiation. Here the rigidity of cross-linked collagen synergizes with retinoids in the osteogenesis of human marrow mesenchymal stem cells (MSCs). Collagen nanofilms serve as a model matrix that MSCs can easily deform unless the film is enzymatically cross-linked, which promotes the spreading of cells and the stiffening of nuclei as both actomyosin assembly and nucleoskeletal lamin-A increase. Expression of lamin-A is known to be controlled by retinoic acid receptor (RAR) transcription factors, but soft matrix prevents any response to any retinoids. Rigid matrix is needed to induce rapid nuclear accumulation of the RARG isoform and for RARG-specific antagonist to increase or maintain expression of lamin-A as well as for RARG-agonist to repress expression. A progerin allele of lamin-A is regulated in the same manner in iPSC-derived MSCs. Rigid matrices are further required for eventual expression of osteogenic markers, and RARG-antagonist strongly drives lamin-A-dependent osteogenesis on rigid substrates, with pretreated xenografts calcifying in vivo to a similar extent as native bone. Proteomics-detected targets of mechanosensitive lamin-A and retinoids underscore the convergent synergy of insoluble and soluble cues in differentiation. © 2017 Ivanovska et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Calculating Path-Dependent Travel Time Prediction Variance and Covariance fro a Global Tomographic P-Velocity Model

NASA Astrophysics Data System (ADS)

Ballard, S.; Hipp, J. R.; Encarnacao, A.; Young, C. J.; Begnaud, M. L.; Phillips, W. S.

2012-12-01

Seismic event locations can be made more accurate and precise by computing predictions of seismic travel time through high fidelity 3D models of the wave speed in the Earth's interior. Given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from SALSA3D, our global, seamless 3D tomographic P-velocity model. Typical global 3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.
Synergistic Effects of Temperature and Oxidation on Matrix Cracking in Fiber-Reinforced Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-06-01

In this paper, the synergistic effects of temperatrue and oxidation on matrix cracking in fiber-reinforced ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The shear-lag model cooperated with damage models, i.e., the interface oxidation model, interface debonding model, fiber strength degradation model and fiber failure model, has been adopted to analyze microstress field in the composite. The relationships between matrix cracking stress, interface debonding and slipping, fiber fracture, oxidation temperatures and time have been established. The effects of fiber volume fraction, interface properties, fiber strength and oxidation temperatures on the evolution of matrix cracking stress versus oxidation time have been analyzed. The matrix cracking stresses of C/SiC composite with strong and weak interface bonding after unstressed oxidation at an elevated temperature of 700 °C in air condition have been predicted for different oxidation time.

Nano-sized precipitate stability and its controlling factors in a NiAl-strengthened ferritic alloy

PubMed Central

Sun, Zhiqian; Song, Gian; Ilavsky, Jan; Ghosh, Gautam; Liaw, Peter K.

2015-01-01

Coherent B2-ordered NiAl-type precipitates have been used to reinforce solid-solution body-centered-cubic iron for high-temperature application in fossil-energy power plants. In this study, we investigate the stability of nano-sized precipitates in a NiAl-strengthened ferritic alloy at 700–950 °C using ultra-small angle X-ray scattering and electron microscopies. Here we show that the coarsening kinetics of NiAl-type precipitates is in excellent agreement with the ripening model in multicomponent alloys. We further demonstrate that the interfacial energy between the matrix and NiAl-type precipitates is strongly dependent on differences in the matrix/precipitate compositions. Our results profile the ripening process in multicomponent alloys by illustrating controlling factors of interfacial energy, diffusivities, and element partitioning. The study provides guidelines to design and develop high-temperature alloys with stable microstructures for long-term service. PMID:26537060
Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.
3D CSEM inversion based on goal-oriented adaptive finite element method

NASA Astrophysics Data System (ADS)

Zhang, Y.; Key, K.

2016-12-01

We present a parallel 3D frequency domain controlled-source electromagnetic inversion code name MARE3DEM. Non-linear inversion of observed data is performed with the Occam variant of regularized Gauss-Newton optimization. The forward operator is based on the goal-oriented finite element method that efficiently calculates the responses and sensitivity kernels in parallel using a data decomposition scheme where independent modeling tasks contain different frequencies and subsets of the transmitters and receivers. To accommodate complex 3D conductivity variation with high flexibility and precision, we adopt the dual-grid approach where the forward mesh conforms to the inversion parameter grid and is adaptively refined until the forward solution converges to the desired accuracy. This dual-grid approach is memory efficient, since the inverse parameter grid remains independent from fine meshing generated around the transmitter and receivers by the adaptive finite element method. Besides, the unstructured inverse mesh efficiently handles multiple scale structures and allows for fine-scale model parameters within the region of interest. Our mesh generation engine keeps track of the refinement hierarchy so that the map of conductivity and sensitivity kernel between the forward and inverse mesh is retained. We employ the adjoint-reciprocity method to calculate the sensitivity kernels which establish a linear relationship between changes in the conductivity model and changes in the modeled responses. Our code uses a direcy solver for the linear systems, so the adjoint problem is efficiently computed by re-using the factorization from the primary problem. Further computational efficiency and scalability is obtained in the regularized Gauss-Newton portion of the inversion using parallel dense matrix-matrix multiplication and matrix factorization routines implemented with the ScaLAPACK library. We show the scalability, reliability and the potential of the algorithm to deal with complex geological scenarios by applying it to the inversion of synthetic marine controlled source EM data generated for a complex 3D offshore model with significant seafloor topography.
An approach for the assessment of the statistical aspects of the SEA coupling loss factors and the vibrational energy transmission in complex aircraft structures: Experimental investigation and methods benchmark

NASA Astrophysics Data System (ADS)

Bouhaj, M.; von Estorff, O.; Peiffer, A.

2017-09-01

In the application of Statistical Energy Analysis "SEA" to complex assembled structures, a purely predictive model often exhibits errors. These errors are mainly due to a lack of accurate modelling of the power transmission mechanism described through the Coupling Loss Factors (CLF). Experimental SEA (ESEA) is practically used by the automotive and aerospace industry to verify and update the model or to derive the CLFs for use in an SEA predictive model when analytical estimates cannot be made. This work is particularly motivated by the lack of procedures that allow an estimate to be made of the variance and confidence intervals of the statistical quantities when using the ESEA technique. The aim of this paper is to introduce procedures enabling a statistical description of measured power input, vibration energies and the derived SEA parameters. Particular emphasis is placed on the identification of structural CLFs of complex built-up structures comparing different methods. By adopting a Stochastic Energy Model (SEM), the ensemble average in ESEA is also addressed. For this purpose, expressions are obtained to randomly perturb the energy matrix elements and generate individual samples for the Monte Carlo (MC) technique applied to derive the ensemble averaged CLF. From results of ESEA tests conducted on an aircraft fuselage section, the SEM approach provides a better performance of estimated CLFs compared to classical matrix inversion methods. The expected range of CLF values and the synthesized energy are used as quality criteria of the matrix inversion, allowing to assess critical SEA subsystems, which might require a more refined statistical description of the excitation and the response fields. Moreover, the impact of the variance of the normalized vibration energy on uncertainty of the derived CLFs is outlined.
Difficulty Factors, Distribution Effects, and the Least Squares Simplex Data Matrix Solution

ERIC Educational Resources Information Center

Ten Berge, Jos M. F.

1972-01-01

In the present article it is argued that the Least Squares Simplex Data Matrix Solution does not deal adequately with difficulty factors inasmuch as the theoretical foundation is insufficient. (Author/CB)
Practical limits on muscle synergy identification by non-negative matrix factorization in systems with mechanical constraints.

PubMed

Burkholder, Thomas J; van Antwerp, Keith W

2013-02-01

Statistical decomposition, including non-negative matrix factorization (NMF), is a convenient tool for identifying patterns of structured variability within behavioral motor programs, but it is unclear how the resolved factors relate to actual neural structures. Factors can be extracted from a uniformly sampled, low-dimension command space. In practical application, the command space is limited, either to those activations that perform some task(s) successfully or to activations induced in response to specific perturbations. NMF was applied to muscle activation patterns synthesized from low dimensional, synergy-like control modules mimicking simple task performance or feedback activation from proprioceptive signals. In the task-constrained paradigm, the accuracy of control module recovery was highly dependent on the sampled volume of control space, such that sampling even 50% of control space produced a substantial degradation in factor accuracy. In the feedback paradigm, NMF was not capable of extracting more than four control modules, even in a mechanical model with seven internal degrees of freedom. Reduced access to the low-dimensional control space imposed by physical constraints may result in substantial distortion of an existing low dimensional controller, such that neither the dimensionality nor the composition of the recovered/extracted factors match the original controller.
Composite blade structural analyzer (COBSTRAN) user's manual

NASA Technical Reports Server (NTRS)

Aiello, Robert A.

1989-01-01

The installation and use of a computer code, COBSTRAN (COmposite Blade STRuctrual ANalyzer), developed for the design and analysis of composite turbofan and turboprop blades and also for composite wind turbine blades was described. This code combines composite mechanics and laminate theory with an internal data base of fiber and matrix properties. Inputs to the code are constituent fiber and matrix material properties, factors reflecting the fabrication process, composite geometry and blade geometry. COBSTRAN performs the micromechanics, macromechanics and laminate analyses of these fiber composites. COBSTRAN generates a NASTRAN model with equivalent anisotropic homogeneous material properties. Stress output from NASTRAN is used to calculate individual ply stresses, strains, interply stresses, thru-the-thickness stresses and failure margins. Curved panel structures may be modeled providing the curvature of a cross-section is defined by a single value function. COBSTRAN is written in FORTRAN 77.
Simultaneous pre-concentration and separation on simple paper-based analytical device for protein analysis.

PubMed

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

2018-02-01

In this work, fast isoelectric focusing (IEF) was successfully implemented on an open paper fluidic channel for simultaneous concentration and separation of proteins from complex matrix. With this simple device, IEF can be finished in 10 min with a resolution of 0.03 pH units and concentration factor of 10, as estimated by color model proteins by smartphone-based colorimetric detection. Fast detection of albumin from human serum and glycated hemoglobin (HBA1c) from blood cell was demonstrated. In addition, off-line identification of the model proteins from the IEF fractions with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was also shown. This PAD IEF is potentially useful either for point of care test (POCT) or biomarker analysis as a cost-effective sample pretreatment method.
High Strain Rate Deformation Modeling of a Polymer Matrix Composite. Part 1; Matrix Constitutive Equations

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Stouffer, Donald C.

1998-01-01

Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.
Synergistic interactions of blood-borne immune cells, fibroblasts and extracellular matrix drive repair in an in vitro peri-implant wound healing model

NASA Astrophysics Data System (ADS)

Burkhardt, Melanie A.; Waser, Jasmin; Milleret, Vincent; Gerber, Isabel; Emmert, Maximilian Y.; Foolen, Jasper; Hoerstrup, Simon P.; Schlottig, Falko; Vogel, Viola

2016-02-01

Low correlations of cell culture data with clinical outcomes pose major medical challenges with costly consequences. While the majority of biomaterials are tested using in vitro cell monocultures, the importance of synergistic interactions between different cell types on paracrine signalling has recently been highlighted. In this proof-of-concept study, we asked whether the first contact of surfaces with whole human blood could steer the tissue healing response. This hypothesis was tested using alkali-treatment of rough titanium (Ti) surfaces since they have clinically been shown to improve early implant integration and stability, yet blood-free in vitro cell cultures poorly correlated with in vivo tissue healing. We show that alkali-treatment, compared to native Ti surfaces, increased blood clot thickness, including platelet adhesion. Strikingly, blood clots with entrapped blood cells in synergistic interactions with fibroblasts, but not fibroblasts alone, upregulated the secretion of major factors associated with fast healing. This includes matrix metalloproteinases (MMPs) to break down extracellular matrix and the growth factor VEGF, known for its angiogenic potential. Consequently, in vitro test platforms, which consider whole blood-implant interactions, might be superior in predicting wound healing in response to biomaterial properties.
How electronic dynamics with Pauli exclusion produces Fermi-Dirac statistics.

PubMed

Nguyen, Triet S; Nanguneri, Ravindra; Parkhill, John

2015-04-07

It is important that any dynamics method approaches the correct population distribution at long times. In this paper, we derive a one-body reduced density matrix dynamics for electrons in energetic contact with a bath. We obtain a remarkable equation of motion which shows that in order to reach equilibrium properly, rates of electron transitions depend on the density matrix. Even though the bath drives the electrons towards a Boltzmann distribution, hole blocking factors in our equation of motion cause the electronic populations to relax to a Fermi-Dirac distribution. These factors are an old concept, but we show how they can be derived with a combination of time-dependent perturbation theory and the extended normal ordering of Mukherjee and Kutzelnigg for a general electronic state. The resulting non-equilibrium kinetic equations generalize the usual Redfield theory to many-electron systems, while ensuring that the orbital occupations remain between zero and one. In numerical applications of our equations, we show that relaxation rates of molecules are not constant because of the blocking effect. Other applications to model atomic chains are also presented which highlight the importance of treating both dephasing and relaxation. Finally, we show how the bath localizes the electron density matrix.
Comparative Biology of Decellularized Lung Matrix: Implications of Species Mismatch in Regenerative Medicine

PubMed Central

Balestrini, Jenna L.; Gard, Ashley L.; Gerhold, Kristin A.; Wilcox, Elise C.; Liu, Angela; Schwan, Jonas; Le, Andrew V.; Baevova, Pavlina; Dimitrievska, Sashka; Zhao, Liping; Sundaram, Sumati; Sun, Huanxing; Rittié, Laure; Dyal, Rachel; Broekelmann, Tom J.; Mecham, Robert P.; Schwartz, Martin A.; Niklason, Laura E.; White, Eric S.

2016-01-01

Lung engineering is a promising technology, relying on re-seeding of either human or xenographic decellularized matrices with patient-derived pulmonary cells. Little is known about the species-specificity of decellularization in various models of lung regeneration, or if species dependent cell-matrix interactions exist within these systems. Therefore decellularized scaffolds were produced from rat, pig, primate and human lungs, and assessed by measuring residual DNA, mechanical properties, and key matrix proteins (collagen, elastin, glycosaminoglycans). To study intrinsic matrix biologic cues, human endothelial cells were seeded onto acellular slices and analyzed for markers of cell health and inflammation. Despite similar levels of collagen after decellularization, human and primate lungs were stiffer, contained more elastin, and retained fewer glycosaminoglycans than pig or rat lung scaffolds. Human endothelial cells seeded onto human and primate lung tissue demonstrated less expression of vascular cell adhesion molecule and activation of nuclear factor-κB compared to those seeded onto rodent or porcine tissue. Adhesion of endothelial cells was markedly enhanced on human and primate tissues. Our work suggests that species-dependent biologic cues intrinsic to lung extracellular matrix could have profound effects on attempts at lung regeneration. PMID:27344365
The multifacet graphically contracted function method. I. Formulation and implementation

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

PubMed

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

2014-08-14

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

DOE PAGES

Aoki, Yasumichi; Izubuchi, Taku; Shintani, Eigo; ...

2017-07-14

In this paper, we present an improved result for the lattice computation of the proton decay matrix elements in N f = 2 + 1 QCD. In this study, by adopting the error reduction technique of all-mode-averaging, a significant improvement of the statistical accuracy is achieved for the relevant form factor of proton (and also neutron) decay on the gauge ensemble of N f= 2 + 1 domain-wall fermions with m π = 0.34 – 0.69 GeV on a 2.7 fm 3 lattice, as used in our previous work. We improve the total accuracy of matrix elements to 10–15% from 30–40% for p → πe + or from 20–40% for p → Kmore » $$\\bar{ν}$$. The accuracy of the low-energy constants α and β in the leading-order baryon chiral perturbation theory (BChPT) of proton decay are also improved. The relevant form factors of p → π estimated through the “direct” lattice calculation from the three-point function appear to be 1.4 times smaller than those from the “indirect” method using BChPT with α and β . It turns out that the utilization of our result will provide a factor 2–3 larger proton partial lifetime than that obtained using BChPT. Lastly, we also discuss the use of these parameters in a dark matter model.« less
THz spectral data analysis and components unmixing based on non-negative matrix factorization methods.

PubMed

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

2017-04-15

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

PubMed

Malviya, Rachana; Chaudhary, Rubina

2010-07-01

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

The Bottlenose Dolphin (Tursiops truncatus) as a Model to Understand Variation in Stress and Reproductive Hormone Measures in Relation to Sampling Matrix, Demographics, and Environmental Factors

DTIC Science & Technology

2011-09-30

energy metabolism, suppression of immune and inflammatory reactions and inhibition of bone and muscle growth. Studies of both captive and free- ranging...Anemia, hypothyroidism and immune suppression associated with polychlorinated biphenyl exposure in bottlenose dolphins (Tursiops truncatus). Proc R
An effective medium approach to modelling the pressure-dependent electrical properties of porous rocks

NASA Astrophysics Data System (ADS)

Han, Tongcheng

2018-07-01

Understanding the electrical properties of rocks under varying pressure is important for a variety of geophysical applications. This study proposes an approach to modelling the pressure-dependent electrical properties of porous rocks based on an effective medium model. The so-named Textural model uses the aspect ratios and pressure-dependent volume fractions of the pores and the aspect ratio and electrical conductivity of the matrix grains. The pores were represented by randomly oriented stiff and compliant spheroidal shapes with constant aspect ratios, and their pressure-dependent volume fractions were inverted from the measured variation of total porosity with differential pressure using a dual porosity model. The unknown constant stiff and compliant pore aspect ratios and the aspect ratio and electrical conductivity of the matrix grains were inverted by best fitting the modelled electrical formation factor to the measured data. Application of the approach to three sandstone samples covering a broad porosity range showed that the pressure-dependent electrical properties can be satisfactorily modelled by the proposed approach. The results demonstrate that the dual porosity concept is sufficient to explain the electrical properties of porous rocks under pressure through the effective medium model scheme.
Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

PubMed Central

Nicosia, R F

2009-01-01

The aortic ring model has become one of the most widely used methods to study angiogenesis and its mechanisms. Many factors have contributed to its popularity including reproducibility, cost effectiveness, ease of use and good correlation with in vivo studies. In this system aortic rings embedded in biomatrix gels and cultured under chemically defined conditions generate arborizing vascular outgrowths which can be stimulated or inhibited with angiogenic regulators. Originally based on the rat aorta, the aortic ring model was later adapted to the mouse for the evaluation of specific molecular alterations in genetically modified animals. Viral transduction of the aortic rings has enabled investigators to overexpress genes of interest in the aortic cultures. Experiments on angiogenic mechanisms have demonstrated that formation of neovessels in aortic cultures is regulated by macrophages, pericytes and fibroblasts through a complex molecular cascade involving growth factors, inflammatory cytokines, axonal guidance cues, extracellular matrix (ECM) molecules and matrix-degrading proteolytic enzymes. These studies have shown that endothelial sprouting can be effectively blocked by depleting the aortic explants of macrophages or by interfering with the angiogenic cascade at multiple levels including growth factor signalling, cell adhesion and proteolytic degradation of the ECM. In this paper, we review the literature in this field and retrace the journey from our first morphological descriptions of the aortic outgrowths to the latest breakthroughs in the cellular and molecular regulation of aortic vessel growth and regression. PMID:19725916
Classification and identification of molecules through factor analysis method based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Jianglou; Liu, Jinsong; Wang, Kejia; Yang, Zhengang; Liu, Xiaming

2018-06-01

By means of factor analysis approach, a method of molecule classification is built based on the measured terahertz absorption spectra of the molecules. A data matrix can be obtained by sampling the absorption spectra at different frequency points. The data matrix is then decomposed into the product of two matrices: a weight matrix and a characteristic matrix. By using the K-means clustering to deal with the weight matrix, these molecules can be classified. A group of samples (spirobenzopyran, indole, styrene derivatives and inorganic salts) has been prepared, and measured via a terahertz time-domain spectrometer. These samples are classified with 75% accuracy compared to that directly classified via their molecular formulas.
Study on the Preparation Process and Influential Factors of Large Area Environment-friendly Molten Carbonate Fuel Cell Matrix

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

NASA Technical Reports Server (NTRS)

Pan, Victor; Schrieber, Robert

1989-01-01

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

PubMed

Shang, Fanhua; Cheng, James; Liu, Yuanyuan; Luo, Zhi-Quan; Lin, Zhouchen

2017-09-04

The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-level vision have proven effective priors for many applications such as background modeling, photometric stereo and image alignment. And they can be well modeled by a hyper-Laplacian. However, the use of such distributions generally leads to challenging non-convex, non-smooth and non-Lipschitz problems, and makes existing algorithms very slow for large-scale applications. Together with the analytic solutions to Lp-norm minimization with two specific values of p, i.e., p=1/2 and p=2/3, we propose two novel bilinear factor matrix norm minimization models for robust principal component analysis. We first define the double nuclear norm and Frobenius/nuclear hybrid norm penalties, and then prove that they are in essence the Schatten-1/2 and 2/3 quasi-norms, respectively, which lead to much more tractable and scalable Lipschitz optimization problems. Our experimental analysis shows that both our methods yield more accurate solutions than original Schatten quasi-norm minimization, even when the number of observations is very limited. Finally, we apply our penalties to various low-level vision problems, e.g. moving object detection, image alignment and inpainting, and show that our methods usually outperform the state-of-the-art methods.
Convergence of Transition Probability Matrix in CLVMarkov Models

NASA Astrophysics Data System (ADS)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.
Molecular deformation mechanisms of the wood cell wall material.

PubMed

Jin, Kai; Qin, Zhao; Buehler, Markus J

2015-02-01

Wood is a biological material with outstanding mechanical properties resulting from its hierarchical structure across different scales. Although earlier work has shown that the cellular structure of wood is a key factor that renders it excellent mechanical properties at light weight, the mechanical properties of the wood cell wall material itself still needs to be understood comprehensively. The wood cell wall material features a fiber reinforced composite structure, where cellulose fibrils act as stiff fibers, and hemicellulose and lignin molecules act as soft matrix. The angle between the fiber direction and the loading direction has been found to be the key factor controlling the mechanical properties. However, how the interactions between theses constitutive molecules contribute to the overall properties is still unclear, although the shearing between fibers has been proposed as a primary deformation mechanism. Here we report a molecular model of the wood cell wall material with atomistic resolution, used to assess the mechanical behavior under shear loading in order to understand the deformation mechanisms at the molecular level. The model includes an explicit description of cellulose crystals, hemicellulose, as well as lignin molecules arranged in a layered nanocomposite. The results obtained using this model show that the wood cell wall material under shear loading deforms in an elastic and then plastic manner. The plastic regime can be divided into two parts according to the different deformation mechanisms: yielding of the matrix and sliding of matrix along the cellulose surface. Our molecular dynamics study provides insights of the mechanical behavior of wood cell wall material at the molecular level, and paves a way for the multi-scale understanding of the mechanical properties of wood. Copyright © 2014 Elsevier Ltd. All rights reserved.
Optimization of metformin HCl 500 mg sustained release matrix tablets using Artificial Neural Network (ANN) based on Multilayer Perceptrons (MLP) model.

PubMed

Mandal, Uttam; Gowda, Veeran; Ghosh, Animesh; Bose, Anirbandeep; Bhaumik, Uttam; Chatterjee, Bappaditya; Pal, Tapan Kumar

2008-02-01

The aim of the present study was to apply the simultaneous optimization method incorporating Artificial Neural Network (ANN) using Multi-layer Perceptron (MLP) model to the development of a metformin HCl 500 mg sustained release matrix tablets with an optimized in vitro release profile. The amounts of HPMC K15M and PVP K30 at three levels (-1, 0, +1) for each were selected as casual factors. In vitro dissolution time profiles at four different sampling times (1 h, 2 h, 4 h and 8 h) were chosen as output variables. 13 kinds of metformin matrix tablets were prepared according to a 2(3) factorial design (central composite) with five extra center points, and their dissolution tests were performed. Commercially available STATISTICA Neural Network software (Stat Soft, Inc., Tulsa, OK, U.S.A.) was used throughout the study. The training process of MLP was completed until a satisfactory value of root square mean (RSM) for the test data was obtained using feed forward back propagation method. The root mean square value for the trained network was 0.000097, which indicated that the optimal MLP model was reached. The optimal tablet formulation based on some predetermined release criteria predicted by MLP was 336 mg of HPMC K15M and 130 mg of PVP K30. Calculated difference (f(1) 2.19) and similarity (f(2) 89.79) factors indicated that there was no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network with MLP, to assist in development of sustained release dosage forms.
Matrix analysis and risk management to avert depression and suicide among workers

PubMed Central

2010-01-01

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

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Ballard, S.; Begnaud, M. L.; Encarnacao, A. V.; Young, C. J.; Phillips, W. S.

2015-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P- and S-velocity model (SALSA3D) that provides superior first P and first S travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from our latest tomographic model. Typical global 3D SALSA3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes a prior model covariance constraint) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.
Can positive matrix factorization help to understand patterns of organic trace gases at the continental Global Atmosphere Watch site Hohenpeissenberg?

NASA Astrophysics Data System (ADS)

Leuchner, M.; Gubo, S.; Schunk, C.; Wastl, C.; Kirchner, M.; Menzel, A.; Plass-Dülmer, C.

2015-02-01

From the rural Global Atmosphere Watch (GAW) site Hohenpeissenberg in the pre-alpine area of southern Germany, a data set of 24 C2-C8 non-methane hydrocarbons over a period of 7 years was analyzed. Receptor modeling was performed by positive matrix factorization (PMF) and the resulting factors were interpreted with respect to source profiles and photochemical aging. Differing from other studies, no direct source attribution was intended because, due to chemistry along transport, mass conservation from source to receptor is not given. However, at remote sites such as Hohenpeissenberg, the observed patterns of non-methane hydrocarbons can be derived from combinations of factors determined by PMF. A six-factor solution showed high stability and the most plausible results. In addition to a biogenic and a background factor of very stable compounds, four additional anthropogenic factors were resolved that could be divided into two short- and two long-lived patterns from evaporative sources/natural gas leakage and incomplete combustion processes. The volume or mass contribution at the site over the entire period was, in decreasing order, from the following factor categories: background, gas leakage and long-lived evaporative, residential heating and long-lived combustion, short-lived evaporative, short-lived combustion, and biogenic. The importance with respect to reactivity contribution was generally in reverse order, with the biogenic and the short-lived combustion factors contributing most. The seasonality of the factors was analyzed and compared to results of a simple box model using constant emissions and the photochemical decay calculated from the measured annual cycles of OH radicals and ozone. Two of the factors, short-lived combustion and gas leakage/long-lived evaporative, showed winter/summer ratios of about 9 and 7, respectively, as expected from constant source estimations. Contrarily, the short-lived evaporative emissions were about 3 times higher in summer than in winter, while residential heating/long-lived combustion emissions were about 2 times higher in winter than in summer.
Processing of a fiber-reinforced transparent glass matrix composite and study of micromechanics of load transfer from matrix to fiber using micro-fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Banerjee, Debangshu

The brittleness of monolithic ceramic materials can be overcome by reinforcing them with high strength, high modulus ceramic fibers. These ceramic matrix composites exhibit improved strength, toughness, and work of fracture. Successful design of a ceramic matrix composite (CMC) depends on two factors: proper choice of fiber, matrix, and interface material, and understanding the mechanics of fracture. The conventional techniques for measuring stress and strain at a local level in CMCs are based on indirect experiments and analytical models. In recent years a couple of optical techniques have been explored for non- contact and direct evaluation of the stress and strain in materials, such as laser Raman spectroscopy and fluorescence spectroscopy. In order to employ spectroscopy to study stress in a composite, a transparent matrix was needed. In this study a SiC fiber reinforced transparent glass matrix composite was developed. A tape casting, binder burnout, and sintering route was adopted to achieve the optimum transparency with proper fiber alignment and interfacial properties. Sapphire fibers were used to act as probe to generate fluorescence signals for measuring stress. A fugitive carbon coating was developed to act as a weak interface for the sapphire fiber, which otherwise, forms a strong bond with the matrix. A fixture was designed to apply stress on the composite specimen, in situ, under the microscope of the spectrometer. Using fluorescence spectroscopy, the micromechanics of load transfer from matrix to fibers were studied. Studies were conducted on both strongly and weakly bonded fibers, as well as on single fiber, and multi fiber situations. Residual stresses arising from thermal expansion mismatch have been mapped along the fiber length with resolution in microns. Residual axial stress was found to follow a shear lag profile along the fiber length. A finite residual axial stress was detected at the fiber ends. Correction of the measured stress for sample probe interaction could not eliminate this finite stress completely. Residual axial stress was also found to vary across the fiber cross section. Analytical models predicting the stress variation along the fiber length and across fiber cross section were developed. (Abstract shortened by UMI.)
Model reduction of nonsquare linear MIMO systems using multipoint matrix continued-fraction expansions

NASA Technical Reports Server (NTRS)

Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San

1994-01-01

This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.
Polymer fiber-based models of connective tissue repair and healing.

PubMed

Lee, Nancy M; Erisken, Cevat; Iskratsch, Thomas; Sheetz, Michael; Levine, William N; Lu, Helen H

2017-01-01

Physiologically relevant models of wound healing are essential for understanding the biology of connective tissue repair and healing. They can also be used to identify key cellular processes and matrix characteristics critical for the design of soft tissue grafts. Modeling the various stages of repair post tendon injury, polymer meshes of varying fiber diameter (nano-1 (390 nm) < nano-2 (740 nm) < micro (1420 nm)) were produced. Alignment was also introduced in the nano-2 group to model matrix undergoing biological healing rather than scar formation. The response of human tendon fibroblasts on these model substrates were evaluated over time as a function of fiber diameter and alignment. It was observed that the repair models of unaligned nanoscale fibers enhanced cell growth and collagen synthesis, while these outcomes were significantly reduced in the mature repair model consisting of unaligned micron-sized fibers. Organization of paxillin and actin on unaligned meshes was enhanced on micro- compared to nano-sized fibers, while the expression and activity of RhoA and Rac1 were greater on nanofibers. In contrast, aligned nanofibers promoted early cell organization, while reducing excessive cell growth and collagen production in the long term. These results show that the early-stage repair model of unaligned nanoscale fibers elicits a response characteristic of the proliferative phase of wound repair, while the more mature model consisting of unaligned micron-sized fibers is more representative of the remodeling phase by supporting cell organization while suppressing growth and biosynthesis. Interestingly, introduction of fiber alignment in the nanofiber model alters fibroblast response from repair to healing, implicating matrix alignment as a critical design factor for circumventing scar formation and promoting biological healing of soft tissue injuries. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling Vascularized Bone Regeneration Within a Porous Biodegradable CaP Scaffold Loaded with Growth Factors

PubMed Central

Sun, X; Kang, Y; Bao, J; Zhang, Y; Yang, Y; Zhou, X

2013-01-01

Osteogenetic microenvironment is a complex constitution in which extracellular matrix (ECM) molecules, stem cells and growth factors each interact to direct the coordinate regulation of bone tissue development. Importantly, angiogenesis improvement and revascularization are critical for osteogenesis during bone tissue regeneration processes. In this study, we developed a three-dimensional (3D) multi-scale system model to study cell response to growth factors released from a 3D biodegradable porous calcium phosphate (CaP) scaffold. Our model reconstructed the 3D bone regeneration system and examined the effects of pore size and porosity on bone formation and angiogenesis. The results suggested that scaffold porosity played a more dominant role in affecting bone formation and angiogenesis compared with pore size, while the pore size could be controlled to tailor the growth factor release rate and release fraction. Furthermore, a combination of gradient VEGF with BMP2 and Wnt released from the multi-layer scaffold promoted angiogenesis and bone formation more readily than single growth factors. These results demonstrated that the developed model can be potentially applied to predict vascularized bone regeneration with specific scaffold and growth factors. PMID:23566802
A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

PubMed Central

Ortega-Martorell, Sandra; Ruiz, Héctor; Vellido, Alfredo; Olier, Iván; Romero, Enrique; Julià-Sapé, Margarida; Martín, José D.; Jarman, Ian H.; Arús, Carles; Lisboa, Paulo J. G.

2013-01-01

Background The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal. Methodology/Principal Findings Non-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification. Conclusions/Significance We show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing. PMID:24376744
Field-scale effective matrix diffusion coefficient for fractured rock: results from literature survey.

PubMed

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

2007-08-15

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

Molecular surface area based predictive models for the adsorption and diffusion of disperse dyes in polylactic acid matrix.

PubMed

Xu, Suxin; Chen, Jiangang; Wang, Bijia; Yang, Yiqi

2015-11-15

Two predictive models were presented for the adsorption affinities and diffusion coefficients of disperse dyes in polylactic acid matrix. Quantitative structure-sorption behavior relationship would not only provide insights into sorption process, but also enable rational engineering for desired properties. The thermodynamic and kinetic parameters for three disperse dyes were measured. The predictive model for adsorption affinity was based on two linear relationships derived by interpreting the experimental measurements with molecular structural parameters and compensation effect: ΔH° vs. dye size and ΔS° vs. ΔH°. Similarly, the predictive model for diffusion coefficient was based on two derived linear relationships: activation energy of diffusion vs. dye size and logarithm of pre-exponential factor vs. activation energy of diffusion. The only required parameters for both models are temperature and solvent accessible surface area of the dye molecule. These two predictive models were validated by testing the adsorption and diffusion properties of new disperse dyes. The models offer fairly good predictive ability. The linkage between structural parameter of disperse dyes and sorption behaviors might be generalized and extended to other similar polymer-penetrant systems. Copyright © 2015 Elsevier Inc. All rights reserved.
HES factors regulate specific aspects of chondrogenesis and chondrocyte hypertrophy during cartilage development

PubMed Central

Rutkowski, Timothy P.; Kohn, Anat; Sharma, Deepika; Ren, Yinshi; Mirando, Anthony J.

2016-01-01

ABSTRACT RBPjκ-dependent Notch signaling regulates multiple processes during cartilage development, including chondrogenesis, chondrocyte hypertrophy and cartilage matrix catabolism. Select members of the HES- and HEY-families of transcription factors are recognized Notch signaling targets that mediate specific aspects of Notch function during development. However, whether particular HES and HEY factors play any role(s) in the processes during cartilage development is unknown. Here, for the first time, we have developed unique in vivo genetic models and in vitro approaches demonstrating that the RBPjκ-dependent Notch targets HES1 and HES5 suppress chondrogenesis and promote the onset of chondrocyte hypertrophy. HES1 and HES5 might have some overlapping function in these processes, although only HES5 directly regulates Sox9 transcription to coordinate cartilage development. HEY1 and HEYL play no discernable role in regulating chondrogenesis or chondrocyte hypertrophy, whereas none of the HES or HEY factors appear to mediate Notch regulation of cartilage matrix catabolism. This work identifies important candidates that might function as downstream mediators of Notch signaling both during normal skeletal development and in Notch-related skeletal disorders. PMID:27160681
Decreased expression of extracellular matrix proteins and trophic factors in the amygdala complex of depressed mice after chronic immobilization stress

PubMed Central

2012-01-01

Background The amygdala plays an essential role in controlling emotional behaviors and has numerous connections to other brain regions. The functional role of the amygdala has been highlighted by various studies of stress-induced behavioral changes. Here we investigated gene expression changes in the amygdala in the chronic immobilization stress (CIS)-induced depression model. Results Eight genes were decreased in the amygdala of CIS mice, including genes for neurotrophic factors and extracellular matrix proteins. Among these, osteoglycin, fibromodulin, insulin-like growth factor 2 (Igf2), and insulin-like growth factor binding protein 2 (Igfbp2) were further analyzed for histological expression changes. The expression of osteoglycin and fibromodulin simultaneously decreased in the medial, basolateral, and central amygdala regions. However, Igf2 and Igfbp2 decreased specifically in the central nucleus of the amygdala. Interestingly, this decrease was found only in the amygdala of mice showing higher immobility, but not in mice displaying lower immobility, although the CIS regimen was the same for both groups. Conclusions These results suggest that the responsiveness of the amygdala may play a role in the sensitivity of CIS-induced behavioral changes in mice. PMID:22672618
A real time spectrum to dose conversion system

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

DOT National Transportation Integrated Search

1993-11-01

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

ERIC Educational Resources Information Center

Chavda, L. K.

1978-01-01

A complete matrix formulation of the theory of small oscillations is presented. Simple analytic solutions involving matrix functions are found which clearly exhibit the transients, the damping factors, the Breit-Wigner form for resonances, etc. (BB)
Human umbilical cord blood-derived mesenchymal stromal cells and small intestinal submucosa hydrogel composite promotes combined radiation-wound healing of mice.

PubMed

Lee, Changsun; Shim, Sehwan; Jang, Hyosun; Myung, Hyunwook; Lee, Janet; Bae, Chang-Hwan; Myung, Jae Kyung; Kim, Min-Jung; Lee, Seung Bum; Jang, Won-Suk; Lee, Sun-Joo; Kim, Hwi-Yool; Lee, Seung-Sook; Park, Sunhoo

2017-09-01

Mesenchymal stromal cells (MSCs) are a promising agent for treating impaired wound healing, and their therapeutic potential may be enhanced by employing extracellular matrix scaffolds as cell culture scaffolds or transplant cell carriers. Here, we evaluated the effect of human umbilical cord blood-derived (hUCB)-MSCs and a porcine small intestinal submucosa (SIS)-derived extracellular matrix scaffold in a combined radiation-wound mouse model of impaired wound healing. hUCB-MSCs and SIS hydrogel composite was applied to the excisional wound of whole-body irradiated mice. Assessment of wound closing and histological evaluation were performed in vivo. We also cultured hUCB-MSCs on SIS gel and examined the angiogenic effect of conditioned medium on irradiated human umbilical vein endothelial cells (HUVECs) in vitro. hUCB-MSCs and SIS hydrogel composite treatment enhanced wound healing and angiogenesis in the wound site of mice. Conditioned medium from hUCB-MSCs cultured on SIS hydrogel promoted the chemotaxis of irradiated HUVECs more than their proliferation. The secretion of angiogenic growth factors hepatocyte growth factor, vascular endothelial growth factor-A and angiopoietin-1 from hUCB-MSCs was significantly increased by SIS hydrogel, with HGF being the predominant angiogenic factor of irradiated HUVECs. Our results suggest that the wound healing effect of hUCB-MSCs is enhanced by SIS hydrogel via a paracrine factor-mediated recruitment of vascular endothelial cells in a combined radiation-wound mouse model. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.
Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure.

PubMed

Hoy, Erik P; Mazziotti, David A

2015-08-14

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

NASA Astrophysics Data System (ADS)

Yang, Linxiao; Fang, Jun; Duan, Huiping; Li, Hongbin; Zeng, Bing

2018-06-01

The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We show that such a hierarchical Gaussian prior has the potential to encourage a low-rank solution. Based on the proposed hierarchical prior model, a variational Bayesian method is developed for matrix completion, where the generalized approximate massage passing (GAMP) technique is embedded into the variational Bayesian inference in order to circumvent cumbersome matrix inverse operations. Simulation results show that our proposed method demonstrates superiority over existing state-of-the-art matrix completion methods.
Sparse nonnegative matrix factorization with ℓ0-constraints

PubMed Central

Peharz, Robert; Pernkopf, Franz

2012-01-01

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

PubMed

Khuda, Sefat; Slate, Andrew; Pereira, Marion; Al-Taher, Fadwa; Jackson, Lauren; Diaz-Amigo, Carmen; Bigley, Elmer C; Whitaker, Thomas; Williams, Kristina M

2012-05-02

Among the major food allergies, peanut, egg, and milk are the most common. The immunochemical detection of food allergens depends on various factors, such as the food matrix and processing method, which can affect allergen conformation and extractability. This study aimed to (1) develop matrix-specific incurred reference materials for allergen testing, (2) determine whether multiple allergens in the same model food can be simultaneously detected, and (3) establish the effect of processing on reference material stability and allergen detection. Defatted peanut flour, whole egg powder, and spray-dried milk were added to cookie dough at seven incurred levels before baking. Allergens were measured using five commercial enzyme-linked immunosorbent assay (ELISA) kits. All kits showed decreased recovery of all allergens after baking. Analytical coefficients of variation for most kits increased with baking time, but decreased with incurred allergen level. Thus, food processing negatively affects the recovery and variability of peanut, egg, and milk detection in a sugar cookie matrix when using immunochemical methods.
0 ν β β -decay nuclear matrix element for light and heavy neutrino mass mechanisms from deformed quasiparticle random-phase approximation calculations for 76Ge, 82Se, 130Te, 136Xe, and 150Nd with isospin restoration

NASA Astrophysics Data System (ADS)

Fang, Dong-Liang; Faessler, Amand; Šimkovic, Fedor

2018-04-01

In this paper, with restored isospin symmetry, we evaluated the neutrinoless double-β -decay nuclear matrix elements for 76Ge, 82Se, 130Te, 136Xe, and 150Nd for both the light and heavy neutrino mass mechanisms using the deformed quasiparticle random-phase approximation approach with realistic forces. We give detailed decompositions of the nuclear matrix elements over different intermediate states and nucleon pairs, and discuss how these decompositions are affected by the model space truncations. Compared to the spherical calculations, our results show reductions from 30 % to about 60 % of the nuclear matrix elements for the calculated isotopes mainly due to the presence of the BCS overlap factor between the initial and final ground states. The comparison between different nucleon-nucleon (NN) forces with corresponding short-range correlations shows that the choice of the NN force gives roughly 20 % deviations for the light exchange neutrino mechanism and much larger deviations for the heavy neutrino exchange mechanism.
A Glimpse of Matrix Metalloproteinases in Diabetic Nephropathy

PubMed Central

Xu, X.; Xiao, L.; Xiao, P.; Yang, S.; Chen, G.; Liu, F.; Kanwar, Y.Y.; Sun, L.

2014-01-01

Matrix metalloproteinases (MMPs) are proteolytic enzymes belonging to the family of zinc-dependent endopeptidases that are capable of degrading almost all the proteinaceous components of the extracellular matrix (ECM). It is known that MMPs play a role in a number of renal diseases, such as, various forms of glomerulonephritis and tubular diseases, including some of the inherited kidney diseases. In this regard, ECM accumulation is considered to be a hallmark morphologic finding of diabetic nephropathy, which not only is related to the excessive synthesis of matrix proteins, but also to their decreased degradation by the MMPs. In recent years, increasing evidence suggest that there is a good correlation between the activity or expression of MMPs and progression of renal disease in patients with diabetic nephropathy in humans and in various experimental animal models. In such a diabetic milieu, the expression of MMPs is modulated by high glucose, advanced glycation end products (AGEs), TGF-β, reactive oxygen species (ROS), transcription factors and some of the microRNAs. In this review, we focused on the structure and functions of MMPs, and their role in the pathogenesis of diabetic nephropathy. PMID:25039784
Biodrying of sewage sludge: kinetics of volatile solids degradation under different initial moisture contents and air-flow rates.

PubMed

Villegas, Manuel; Huiliñir, Cesar

2014-12-01

This study focuses on the kinetics of the biodegradation of volatile solids (VS) of sewage sludge for biodrying under different initial moisture contents (Mc) and air-flow rates (AFR). For the study, a 3(2) factorial design, whose factors were AFR (1, 2 or 3L/minkgTS) and initial Mc (59%, 68% and 78% w.b.), was used. Using seven kinetic models and a nonlinear regression method, kinetic parameters were estimated and the models were analyzed with two statistical indicators. Initial Mc of around 68% increases the temperature matrix and VS consumption, with higher moisture removal at lower initial Mc values. Lower AFRs gave higher matrix temperatures and VS consumption, while higher AFRs increased water removal. The kinetic models proposed successfully simulate VS biodegradation, with root mean square error (RMSE) between 0.007929 and 0.02744, and they can be used as a tool for satisfactory prediction of VS in biodrying. Copyright © 2014 Elsevier Ltd. All rights reserved.
Real-time Visualization of Tissue Dynamics during Embryonic Development and Malignant Transformation

NASA Astrophysics Data System (ADS)

Yamada, Kenneth

Tissues undergo dramatic changes in organization during embryonic development, as well as during cancer progression and invasion. Recent advances in microscopy now allow us to visualize and track directly the dynamic movements of tissues, their constituent cells, and cellular substructures. This behavior can now be visualized not only in regular tissue culture on flat surfaces (`2D' environments), but also in a variety of 3D environments that may provide physiological cues relevant to understanding dynamics within living organisms. Acquisition of imaging data using various microscopy modalities will provide rich opportunities for determining the roles of physical factors and for computational modeling of complex processes in living tissues. Direct visualization of real-time motility is providing insight into biology spanning multiple spatio-temporal scales. Many cells in our body are known to be in contact with connective tissue and other forms of extracellular matrix. They do so through microscopic cellular adhesions that bind to matrix proteins. In particular, fluorescence microscopy has revealed that cells dynamically probe and bend the matrix at the sites of cell adhesions, and that 3D matrix architecture, stiffness, and elasticity can each regulate migration of the cells. Conversely, cells remodel their local matrix as organs form or tumors invade. Cancer cells can invade tissues using microscopic protrusions that degrade the surrounding matrix; in this case, the local matrix protein concentration is more important for inducing the micro-invasive protrusions than stiffness. On the length scales of tissues, transiently high rates of individual cell movement appear to help establish organ architecture. In fact, isolated cells can self-organize to form tissue structures. In all of these cases, in-depth real-time visualization will ultimately provide the extensive data needed for computer modeling and for testing hypotheses in which physical forces interact closely with cell signaling to form organs or promote tumor invasion.
New Factorization Techniques and Fast Serial and Parrallel Algorithms for Operational Space Control of Robot Manipulators

NASA Technical Reports Server (NTRS)

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

1997-01-01

In this paper a new factorization technique for computation of inverse of mass matrix, and the operational space mass matrix, as arising in implementation of the operational space control scheme, is presented.
Optical factors determined by the T-matrix method in turbidity measurement of absolute coagulation rate constants.

PubMed

Xu, Shenghua; Liu, Jie; Sun, Zhiwei

2006-12-01

Turbidity measurement for the absolute coagulation rate constants of suspensions has been extensively adopted because of its simplicity and easy implementation. A key factor in deriving the rate constant from experimental data is how to theoretically evaluate the so-called optical factor involved in calculating the extinction cross section of doublets formed during aggregation. In a previous paper, we have shown that compared with other theoretical approaches, the T-matrix method provides a robust solution to this problem and is effective in extending the applicability range of the turbidity methodology, as well as increasing measurement accuracy. This paper will provide a more comprehensive discussion of the physical insight for using the T-matrix method in turbidity measurement and associated technical details. In particular, the importance of ensuring the correct value for the refractive indices for colloidal particles and the surrounding medium used in the calculation is addressed, because the indices generally vary with the wavelength of the incident light. The comparison of calculated results with experiments shows that the T-matrix method can correctly calculate optical factors even for large particles, whereas other existing theories cannot. In addition, the data of the optical factor calculated by the T-matrix method for a range of particle radii and incident light wavelengths are listed.
Trust in Leadership DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

PubMed Central

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2013-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item–attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible T-matrix that relates the Q-matrix to response patterns. The flexibility of the T-matrix allows the construction of a natural criterion function as well as a computationally amenable algorithm. Simulations results are presented to demonstrate usefulness and applicability of the proposed method. Extension to handling of the Q-matrix with partial information is presented. The proposed method also provides a platform on which important statistical issues, such as hypothesis testing and model selection, may be formally addressed. PMID:23926363

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

NASA Astrophysics Data System (ADS)

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

1995-10-01

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

NASA Technical Reports Server (NTRS)

David, R. E.

1984-01-01

Very efficient algorithms for solving large sparse systems of simultaneous linear equations have been developed for serial processing computers. These involve a reordering of matrix rows and columns in order to obtain a near triangular pattern of nonzero elements. Then an LU factorization is developed to represent the matrix inverse in terms of a sequence of elementary Gaussian eliminations, or pivots. In this paper it is shown how these algorithms are adapted for efficient implementation on vector processors. Results obtained on the CYBER 200 Model 205 are presented for a series of large test problems which show the comparative advantages of the triangularization and vector processing algorithms.
An ignition key for atomic-scale engines

NASA Astrophysics Data System (ADS)

Dundas, Daniel; Cunningham, Brian; Buchanan, Claire; Terasawa, Asako; Paxton, Anthony T.; Todorov, Tchavdar N.

2012-10-01

A current-carrying resonant nanoscale device, simulated by non-adiabatic molecular dynamics, exhibits sharp activation of non-conservative current-induced forces with bias. The result, above the critical bias, is generalized rotational atomic motion with a large gain in kinetic energy. The activation exploits sharp features in the electronic structure, and constitutes, in effect, an ignition key for atomic-scale motors. A controlling factor for the effect is the non-equilibrium dynamical response matrix for small-amplitude atomic motion under current. This matrix can be found from the steady-state electronic structure by a simpler static calculation, providing a way to detect the likely appearance, or otherwise, of non-conservative dynamics, in advance of real-time modelling.
The discrete hungry Lotka Volterra system and a new algorithm for computing matrix eigenvalues

NASA Astrophysics Data System (ADS)

Fukuda, Akiko; Ishiwata, Emiko; Iwasaki, Masashi; Nakamura, Yoshimasa

2009-01-01

The discrete hungry Lotka-Volterra (dhLV) system is a generalization of the discrete Lotka-Volterra (dLV) system which stands for a prey-predator model in mathematical biology. In this paper, we show that (1) some invariants exist which are expressed by dhLV variables and are independent from the discrete time and (2) a dhLV variable converges to some positive constant or zero as the discrete time becomes sufficiently large. Some characteristic polynomial is then factorized with the help of the dhLV system. The asymptotic behaviour of the dhLV system enables us to design an algorithm for computing complex eigenvalues of a certain band matrix.
Second derivative time integration methods for discontinuous Galerkin solutions of unsteady compressible flows

NASA Astrophysics Data System (ADS)

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

2017-12-01

In this paper we investigate the possibility of using the high-order accurate A (α) -stable Second Derivative (SD) schemes proposed by Enright for the implicit time integration of the Discontinuous Galerkin (DG) space-discretized Navier-Stokes equations. These multistep schemes are A-stable up to fourth-order, but their use results in a system matrix difficult to compute. Furthermore, the evaluation of the nonlinear function is computationally very demanding. We propose here a Matrix-Free (MF) implementation of Enright schemes that allows to obtain a method without the costs of forming, storing and factorizing the system matrix, which is much less computationally expensive than its matrix-explicit counterpart, and which performs competitively with other implicit schemes, such as the Modified Extended Backward Differentiation Formulae (MEBDF). The algorithm makes use of the preconditioned GMRES algorithm for solving the linear system of equations. The preconditioner is based on the ILU(0) factorization of an approximated but computationally cheaper form of the system matrix, and it has been reused for several time steps to improve the efficiency of the MF Newton-Krylov solver. We additionally employ a polynomial extrapolation technique to compute an accurate initial guess to the implicit nonlinear system. The stability properties of SD schemes have been analyzed by solving a linear model problem. For the analysis on the Navier-Stokes equations, two-dimensional inviscid and viscous test cases, both with a known analytical solution, are solved to assess the accuracy properties of the proposed time integration method for nonlinear autonomous and non-autonomous systems, respectively. The performance of the SD algorithm is compared with the ones obtained by using an MF-MEBDF solver, in order to evaluate its effectiveness, identifying its limitations and suggesting possible further improvements.
Study on invadopodia formation for lung carcinoma invasion with a microfluidic 3D culture device.

PubMed

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

2013-01-01

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

NASA Astrophysics Data System (ADS)

Lu, Zhiyong; Qin, Futong; Jin, Yican

2017-10-01

A new algorithm is proposed for the non-consistent judgment matrix in AHP. A primary judgment matrix is generated firstly through pre-ordering the targeted factor set, and a compared matrix is built through the top integral function. Then a relative error matrix is created by comparing the compared matrix with the primary judgment matrix which is regulated under the control of the relative error matrix and the dissimilar degree of the matrix step by step. Lastly, the targeted judgment matrix is generated to satisfy the requirement of consistence and the least dissimilar degree. The feasibility and validity of the proposed method are verified by simulation results.
Liarozole inhibits transforming growth factor-β3–mediated extracellular matrix formation in human three-dimensional leiomyoma cultures

PubMed Central

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

2014-01-01

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

PubMed

Sobrinho Santos, Eliane Macedo; Guimarães, Talita Antunes; Santos, Hércules Otacílio; Cangussu, Lilian Mendes Borborema; de Jesus, Sabrina Ferreira; Fraga, Carlos Alberto de Carvalho; Cardoso, Claudio Marcelo; Santos, Sérgio Henrique Souza; de Paula, Alfredo Maurício Batista; Gomez, Ricardo Santiago; Guimarães, André Luiz Sena; Farias, Lucyana Conceição

2017-05-01

Leptin, one of the main hormones controlling energy homeostasis, has been associated with different cancer types. In oral cancer, its effect is not well understood. We investigated, through in vitro and in vivo assays, whether leptin can affect the neoplastic behavior of oral squamous cell carcinoma. Expression of genes possibly linked to the leptin pathway was assessed in leptin-treated oral squamous cell carcinoma cells and also in tissue samples of oral squamous cell carcinoma and oral mucosa, including leptin, leptin receptor, hypoxia-inducible factor 1-alpha, E-cadherin, matrix metalloproteinase-2, matrix metalloproteinase-9, Col1A1, Ki67, and mir-210. Leptin treatment favored higher rates of cell proliferation and migration, and reduced apoptosis. Accordingly, leptin-treated oral squamous cell carcinoma cells show decreased messenger RNA caspase-3 expression, and increased levels of E-cadherin, Col1A1, matrix metalloproteinase-2, matrix metalloproteinase-9, and mir-210. In tissue samples, hypoxia-inducible factor 1-alpha messenger RNA and protein expression of leptin and leptin receptor were high in oral squamous cell carcinoma cases. Serum leptin levels were increased in first clinical stages of the disease. In animal model, oral squamous cell carcinoma-induced mice show higher leptin receptor expression, and serum leptin level was increased in dysplasia group. Our findings suggest that leptin seems to exert an effect on oral squamous cell carcinoma cells behavior and also on molecular markers related to cell proliferation, migration, and tumor angiogenesis.
The nuclear matrix protein NMP-1 is the transcription factor YY1.

PubMed Central

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

1995-01-01

NMP-1 was initially identified as a nuclear matrix-associated DNA-binding factor that exhibits sequence-specific recognition for the site IV regulatory element of a histone H4 gene. This distal promoter domain is a nuclear matrix interaction site. In the present study, we show that NMP-1 is the multifunctional transcription factor YY1. Gel-shift and Western blot analyses demonstrate that NMP-1 is immunoreactive with YY1 antibody. Furthermore, purified YY1 protein specifically recognizes site IV and reconstitutes the NMP-1 complex. Western blot and gel-shift analyses indicate that YY1 is present within the nuclear matrix. In situ immunofluorescence studies show that a significant fraction of YY1 is localized in the nuclear matrix, principally but not exclusively associated with residual nucleoli. Our results confirm that NMP-1/YY1 is a ubiquitous protein that is present in both human cells and in rat osteosarcoma ROS 17/2.8 cells. The finding that NMP-1 is identical to YY1 suggests that this transcriptional regulator may mediate gene-matrix interactions. Our results are consistent with the concept that the nuclear matrix may functionally compartmentalize the eukaryotic nucleus to support regulation of gene expression. Images Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 PMID:7479833
A Regional Assessment of Marine Vessel PM2.5 Impacts in the U.S. Pacific Northwest Using a Receptor Based Source Apportionment Method

EPA Science Inventory

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

PubMed Central

Ringling, Christiane

2017-01-01

Generating bioavailability data from in vivo studies is time-consuming and expensive. In vitro simulation can help to investigate factors influencing bioavailability or facilitate quantifying the impact of such factors. For folates, an efficient deconjugation of polyglutamates to the corresponding monoglutamates is crucial for bioavailability and highly dependent on the food matrix. Therefore, the bioaccessibility of folates of different foodstuffs was examined using a simulated digestion model with respect to folate stability and the efficiency of deconjugation. For realistic simulated deconjugation, porcine brush border membrane was used during the phase of the simulated digestion in the small intestine. For a better understanding of folate behaviour during digestion, single folate monoglutamates were also investigated with this in vitro digestion model. The results for bioaccessibility were compared with data from a human bioavailability study. They support the idea that both stability and deconjugation have an influence on bioaccessibility and thus on bioavailability. Tetrahydrofolate is probably lost completely or at least to a high extent and the stability of 5-methyltetrahydrofolate depends on the food matrix. Additionally, 5-methyltetrahydrofolate can be oxidised to a pyrazino-s-triazine (MeFox), whose absorption in the human intestinal tract was shown tentatively. PMID:28862677
Simulation of Food Folate Digestion and Bioavailability of an Oxidation Product of 5-Methyltetrahydrofolate.

PubMed

Ringling, Christiane; Rychlik, Michael

2017-09-01

Generating bioavailability data from in vivo studies is time-consuming and expensive. In vitro simulation can help to investigate factors influencing bioavailability or facilitate quantifying the impact of such factors. For folates, an efficient deconjugation of polyglutamates to the corresponding monoglutamates is crucial for bioavailability and highly dependent on the food matrix. Therefore, the bioaccessibility of folates of different foodstuffs was examined using a simulated digestion model with respect to folate stability and the efficiency of deconjugation. For realistic simulated deconjugation, porcine brush border membrane was used during the phase of the simulated digestion in the small intestine. For a better understanding of folate behaviour during digestion, single folate monoglutamates were also investigated with this in vitro digestion model. The results for bioaccessibility were compared with data from a human bioavailability study. They support the idea that both stability and deconjugation have an influence on bioaccessibility and thus on bioavailability. Tetrahydrofolate is probably lost completely or at least to a high extent and the stability of 5-methyltetrahydrofolate depends on the food matrix. Additionally, 5-methyltetrahydrofolate can be oxidised to a pyrazino-s-triazine (MeFox), whose absorption in the human intestinal tract was shown tentatively.
Calculating Path-Dependent Travel Time Prediction Variance and Covariance for the SALSA3D Global Tomographic P-Velocity Model with a Distributed Parallel Multi-Core Computer

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Encarnacao, A.; Ballard, S.; Young, C. J.; Phillips, W. S.; Begnaud, M. L.

2011-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P-velocity model (SALSA3D) that provides superior first P travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we show a methodology for accomplishing this by exploiting the full model covariance matrix. Our model has on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiply methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix we solve for the travel-time covariance associated with arbitrary ray-paths by integrating the model covariance along both ray paths. Setting the paths equal gives variance for that path. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Experimental Analysis and Mathematical Modeling on Mg-Li Alloy Sheets with Three Crystal Structures during Cold Rolling and Heat Treatment.

PubMed

Tang, Yan; Le, Qichi; Wang, Tong; Chen, Xingrui

2017-10-12

The microstructural evolution, mechanical properties, and mathematical relationship of an α, α + β, and β phase Mg-Li alloy during the cold rolling and annealing process were investigated. The results showed that the increased Li element gradually transformed the Mg matrix structure from hcp to bcc. Simultaneously, the alloy plasticity was improved remarkably during cold rolling. In the annealing process, a sort of abnormal grain growth was found in Mg-11Li-3Al-2Zn-0.2Y, but was not detected in Mg-5Li-3Al-2Zn-0.2Y and Mg-8Li-3Al-2Zn-0.2Y. Moreover, the mechanical properties of alloy were evidently improved through a kind of solid solution in the β matrix. To accurately quantify this strengthening effect, the method of mathematical modeling was used to determine the relationship between strength and multiple factors.
Broken flavor 2↔3 symmetry and phenomenological approach for universal quark and lepton mass matrices

NASA Astrophysics Data System (ADS)

Matsuda, Koichi; Nishiura, Hiroyuki

2006-01-01

A phenomenological approach for the universal mass matrix model with a broken flavor 2↔3 symmetry is explored by introducing the 2↔3 antisymmetric parts of mass matrices for quarks and charged leptons. We present explicit texture components of the mass matrices, which are consistent with all the neutrino oscillation experiments and quark mixing data. The mass matrices have a common structure for quarks and leptons, while the large lepton mixings and the small quark mixings are derived with no fine-tuning due to the difference of the phase factors. The model predicts a value 2.4×10-3 for the lepton mixing matrix element square |U13|2, and also ⟨mν⟩=(0.89-1.4)×10-4eV for the averaged neutrino mass which appears in the neutrinoless double beta decay.
Off-stoichiometric defect clustering in irradiated oxides

NASA Astrophysics Data System (ADS)

Khalil, Sarah; Allen, Todd; EL-Azab, Anter

2017-04-01

A cluster dynamics model describing the formation of vacancy and interstitial clusters in irradiated oxides has been developed. The model, which tracks the composition of the oxide matrix and the defect clusters, was applied to the early stage formation of voids and dislocation loops in UO2, and the effects of irradiation temperature and dose rate on the evolution of their densities and composition was investigated. The results show that Frenkel defects dominate the nucleation process in irradiated UO2. The results also show that oxygen vacancies drive vacancy clustering while the migration energy of uranium vacancies is a rate-limiting factor for the nucleation and growth of voids. In a stoichiometric UO2 under irradiation, off-stoichiometric vacancy clusters exist with a higher concentration of hyper-stoichiometric clusters. Similarly, off-stoichiometric interstitial clusters form with a higher concentration of hyper-stoichiometric clusters. The UO2 matrix was found to be hyper-stoichiometric due to the accumulation of uranium vacancies.
Stochastic model of cell rearrangements in convergent extension of ascidian notochord

NASA Astrophysics Data System (ADS)

Lubkin, Sharon; Backes, Tracy; Latterman, Russell; Small, Stephen

2007-03-01

We present a discrete stochastic cell based model of convergent extension of the ascidian notochord. Our work derives from research that clarifies the coupling of invagination and convergent extension in ascidian notochord morphogenesis (Odell and Munro, 2002). We have tested the roles of cell-cell adhesion, cell-extracellular matrix adhesion, random motion, and extension of individual cells, as well as the presence or absence of various tissue types, and determined which factors are necessary and/or sufficient for convergent extension.
Factor models for cancer signatures

NASA Astrophysics Data System (ADS)

Kakushadze, Zura; Yu, Willie

2016-11-01

We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an ;overall; mode of somatic mutational noise. We give a prescription for factoring out this noise and source code for fixing the number of signatures. We apply nonnegative matrix factorization (NMF) to genome data aggregated by cancer subtype and filtered using our method. The resultant signatures have substantially lower variability than those from unfiltered data. Also, the computational cost of signature extraction is cut by about a factor of 10. We find 3 novel cancer signatures, including a liver cancer dominant signature (96% contribution) and a renal cell carcinoma signature (70% contribution). Our method accelerates finding new cancer signatures and improves their overall stability. Reciprocally, the methods for extracting cancer signatures could have interesting applications in quantitative finance.
QCD dirac operator at nonzero chemical potential: lattice data and matrix model.

PubMed

Akemann, Gernot; Wettig, Tilo

2004-03-12

Recently, a non-Hermitian chiral random matrix model was proposed to describe the eigenvalues of the QCD Dirac operator at nonzero chemical potential. This matrix model can be constructed from QCD by mapping it to an equivalent matrix model which has the same symmetries as QCD with chemical potential. Its microscopic spectral correlations are conjectured to be identical to those of the QCD Dirac operator. We investigate this conjecture by comparing large ensembles of Dirac eigenvalues in quenched SU(3) lattice QCD at a nonzero chemical potential to the analytical predictions of the matrix model. Excellent agreement is found in the two regimes of weak and strong non-Hermiticity, for several different lattice volumes.

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.
Representation learning via Dual-Autoencoder for recommendation.

PubMed

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

2017-06-01

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

PubMed

Xu, Tianfu; Sonnenthal, Eric; Bodvarsson, Gudmundur

2003-06-01

The percolation flux in the unsaturated zone (UZ) is an important parameter addressed in site characterization and flow and transport modeling of the potential nuclear-waste repository at Yucca Mountain, NV, USA. The US Geological Survey (USGS) has documented hydrogenic calcite abundances in fractures and lithophysal cavities at Yucca Mountain to provide constraints on percolation fluxes in the UZ. The purpose of this study was to investigate the relationship between percolation flux and measured calcite abundances using reactive transport modeling. Our model considers the following essential factors affecting calcite precipitation: (1) infiltration, (2) the ambient geothermal gradient, (3) gaseous CO(2) diffusive transport and partitioning in liquid and gas phases, (4) fracture-matrix interaction for water flow and chemical constituents, and (5) water-rock interaction. Over a bounding range of 2-20 mm/year infiltration rate, the simulated calcite distributions capture the trend in calcite abundances measured in a deep borehole (WT-24) by the USGS. The calcite is found predominantly in fractures in the welded tuffs, which is also captured by the model simulations. Simulations showed that from about 2 to 6 mm/year, the amount of calcite precipitated in the welded Topopah Spring tuff is sensitive to the infiltration rate. This dependence decreases at higher infiltration rates owing to a modification of the geothermal gradient from the increased percolation flux. The model also confirms the conceptual model for higher percolation fluxes in the fractures compared to the matrix in the welded units, and the significant contribution of Ca from water-rock interaction. This study indicates that reactive transport modeling of calcite deposition can yield important constraints on the unsaturated zone infiltration-percolation flux and provide useful insight into processes such as fracture-matrix interaction as well as conditions and parameters controlling calcite deposition.
Scaling Laws Applied to a Modal Formulation of the Aeroservoelastic Equations

NASA Technical Reports Server (NTRS)

Pototzky, Anthony S.

2002-01-01

A method of scaling is described that easily converts the aeroelastic equations of motion of a full-sized aircraft into ones of a wind-tunnel model. To implement the method, a set of rules is provided for the conversion process involving matrix operations with scale factors. In addition, a technique for analytically incorporating a spring mounting system into the aeroelastic equations is also presented. As an example problem, a finite element model of a full-sized aircraft is introduced from the High Speed Research (HSR) program to exercise the scaling method. With a set of scale factor values, a brief outline is given of a procedure to generate the first-order aeroservoelastic analytical model representing the wind-tunnel model. To verify the scaling process as applied to the example problem, the root-locus patterns from the full-sized vehicle and the wind-tunnel model are compared to see if the root magnitudes scale with the frequency scale factor value. Selected time-history results are given from a numerical simulation of an active-controlled wind-tunnel model to demonstrate the utility of the scaling process.
Postconcussive Symptoms in OEF-OIF Veterans: Factor Structure and Impact of Posttraumatic Stress

DTIC Science & Technology

2009-06-03

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

NASA Astrophysics Data System (ADS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-05-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.
Temperature dependent nonlinear metal matrix laminae behavior

NASA Technical Reports Server (NTRS)

Barrett, D. J.; Buesking, K. W.

1986-01-01

An analytical method is described for computing the nonlinear thermal and mechanical response of laminated plates. The material model focuses upon the behavior of metal matrix materials by relating the nonlinear composite response to plasticity effects in the matrix. The foundation of the analysis is the unidirectional material model which is used to compute the instantaneous properties of the lamina based upon the properties of the fibers and matrix. The unidirectional model assumes that the fibers properties are constant with temperature and assumes that the matrix can be modelled as a temperature dependent, bilinear, kinematically hardening material. An incremental approach is used to compute average stresses in the fibers and matrix caused by arbitrary mechanical and thermal loads. The layer model is incorporated in an incremental laminated plate theory to compute the nonlinear response of laminated metal matrix composites of general orientation and stacking sequence. The report includes comparisons of the method with other analytical approaches and compares theoretical calculations with measured experimental material behavior. A section is included which describes the limitations of the material model.
A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Technical Reports Server (NTRS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-01-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.
Modeling for Matrix Multicracking Evolution of Cross-ply Ceramic-Matrix Composites Using Energy Balance Approach

NASA Astrophysics Data System (ADS)

Longbiao, Li

2015-12-01

The matrix multicracking evolution of cross-ply ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The multicracking of cross-ply CMCs was classified into five modes, i.e., (1) mode 1: transverse multicracking; (2) mode 2: transverse multicracking and matrix multicracking with perfect fiber/matrix interface bonding; (3) mode 3: transverse multicracking and matrix multicracking with fiber/matrix interface debonding; (4) mode 4: matrix multicracking with perfect fiber/matrix interface bonding; and (5) mode 5: matrix multicracking with fiber/matrix interface debonding. The stress distributions of four cracking modes, i.e., mode 1, mode 2, mode 3 and mode 5, are analysed using shear-lag model. The matrix multicracking evolution of mode 1, mode 2, mode 3 and mode 5, has been determined using energy balance approach. The effects of ply thickness and fiber volume fraction on matrix multicracking evolution of cross-ply CMCs have been investigated.
Using Dispersed Modes During Model Correlation

NASA Technical Reports Server (NTRS)

Stewart, Eric; Hathcock, Megan

2017-01-01

Using model dispersions as a starting point allows us to quickly adjust a model to reflect new test data: a) The analyst does a lot of work before the test to save time post-test. b) Creating 1000s of model dispersions to provide "coarse tuning," then use Attune to provide the "fine tuning." ?Successful model tuning on three structures: a) TAURUS. b) Ares I-X C) Cart (in backup charts). ?Mode weighting factors, matrix norm method, and XOR vs. MAC all play key roles in determining the BME. The BME process will be used on future tests: a) ISPE modal test (ongoing work). b) SLS modal test (mid 2018).
Organizational Models and Mythologies of the American Research University. ASHE 1986 Annual Meeting Paper.

ERIC Educational Resources Information Center

Alpert, Daniel

Features of the matrix model of the research university and myths about the academic enterprise are described, along with serious dissonances in the U.S. university system. The linear model, from which the matrix model evolved, describes the university's structure, perceived mission, and organizational behavior. A matrix model portrays in concise,…
Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar-Fiber-Reinforced Polymer-Matrix Composites

DTIC Science & Technology

2012-08-03

is unlimited. Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar ®-Fiber-Reinforced Polymer-Matrix Composites The views, opinions...12211 Research Triangle Park, NC 27709-2211 ballistics, composites, Kevlar , material models, microstructural defects REPORT DOCUMENTATION PAGE 11... Kevlar ®-Fiber-Reinforced Polymer-Matrix Composites Report Title Fiber-reinforced polymer matrix composite materials display quite complex deformation
Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold.

PubMed

Zitnik, Marinka; Zupan, Blaž

2014-01-01

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

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.
Fatigue crack growth in unidirectional metal matrix composite

NASA Technical Reports Server (NTRS)

Ghosn, Louis J.; Telesman, Jack; Kantzos, Peter

1990-01-01

The weight function method was used to determine the effective stress intensity factor and the crack opening profile for a fatigue tested composite which exhibited fiber bridging. The bridging mechanism was modeled using two approaches; the crack closure approach and the shear lag approach. The numerically determined stress intensity factor values from both methods were compared and correlated with the experimentally obtained crack growth rates for SiC/Ti-15-3 (0)(sub 8) oriented composites. The near crack tip opening profile was also determined for both methods and compared with the experimentally obtained measurements.
Deficiency of the protein-tyrosine phosphatase DEP-1/PTPRJ promotes matrix metalloproteinase-9 expression in meningioma cells.

PubMed

Petermann, Astrid; Stampnik, Yvonn; Cui, Yan; Morrison, Helen; Pachow, Doreen; Kliese, Nadine; Mawrin, Christian; Böhmer, Frank-D

2015-05-01

Brain-invasive growth of a subset of meningiomas is associated with less favorable prognosis. The molecular mechanisms causing invasiveness are only partially understood, however, the expression of matrix metalloproteinases (MMPs) has been identified as a contributing factor. We have previously found that loss of density enhanced phosphatase-1 (DEP-1, also designated PTPRJ), a transmembrane protein-tyrosine phosphatase, promotes meningioma cell motility and invasive growth in an orthotopic xenotransplantation model. We have now analyzed potential alterations of the expression of genes involved in motility control, caused by DEP-1 loss in meningioma cell lines. DEP-1 depleted cells exhibited increased expression of mRNA encoding MMP-9, and the growth factors EGF and FGF-2. The increase of MMP-9 expression in DEP-1 depleted cells was also readily detectable at the protein level by zymography. MMP-9 upregulation was sensitive to chemical inhibitors of growth factor signal transduction. Conversely, MMP-9 mRNA levels could be stimulated with growth factors (e.g. EGF) and inflammatory cytokines (e.g. TNFα). Increase of MMP-9 expression by DEP-1 depletion, or growth factor/cytokine stimulation qualitatively correlated with increased invasiveness in vitro scored as transmigration through matrigel-coated membranes. The studies suggest induction of MMP-9 expression promoted by DEP-1 deficiency, or potentially by growth factors and inflammatory cytokines, as a mechanism contributing to meningioma brain invasiveness.
Phosphorylation of hepatocyte growth factor receptor and epidermal growth factor receptor of human hepatocytes can be maintained in a (3D) collagen sandwich culture system.

PubMed

Engl, Tobias; Boost, Kim A; Leckel, Kerstin; Beecken, Wolf-Dietrich; Jonas, Dietger; Oppermann, Elsie; Auth, Marcus K H; Schaudt, André; Bechstein, Wolf-Otto; Blaheta, Roman A

2004-08-01

In vitro culture models that employ human liver cells could be potent tools for predictive studies on drug toxicity and metabolism in the pharmaceutical industry. However, an adequate receptor responsiveness is necessary to allow intracellular signalling and metabolic activity. We tested the ability of three-dimensionally arranged human hepatocytes to respond to the growth factors hepatocyte growth factor (HGF) or epidermal growth factor (EGF). Isolated adult human hepatocytes were cultivated within a three-dimensional collagen gel (sandwich) or on a two-dimensional collagen matrix. Cells were treated with HGF or EGF and expression and phosphorylative activity of HGF receptors (HGFr, c-met) or EGF receptors (EGFr) were measured by flow cytometry and Western blot. Increasing HGFr and EGFr levels were detected in hepatocytes growing two-dimensionally. However, both receptors were not activated in presence of growth factors. In contrast, when hepatocytes were plated within a three-dimensional matrix, HGFr and EGFr levels remained constantly low. However, both receptors became strongly phosphorylated by soluble HGF or EGF. We conclude that cultivation of human hepatocytes in a three-dimensionally arranged in vitro system allows the maintenance of specific functional activities. The necessity of cell dimensionality for HGFr and EGFr function should be considered when an adequate in vitro system has to be introduced for drug testing.
The Tetrahedral Zamolodchikov Algebra and the {AdS_5× S^5} S-matrix

NASA Astrophysics Data System (ADS)

Mitev, Vladimir; Staudacher, Matthias; Tsuboi, Zengo

2017-08-01

The S-matrix of the {AdS_5× S^5} string theory is a tensor product of two centrally extended su{(2|2)\\ltimes R^2 S-matrices, each of which is related to the R-matrix of the Hubbard model. The R-matrix of the Hubbard model was first found by Shastry, who ingeniously exploited the fact that, for zero coupling, the Hubbard model can be decomposed into two XX models. In this article, we review and clarify this construction from the AdS/CFT perspective and investigate the implications this has for the {AdS_5× S^5} S-matrix.
Neuroprotection by Caffeine in Hyperoxia-Induced Neonatal Brain Injury

PubMed Central

Endesfelder, Stefanie; Weichelt, Ulrike; Strauß, Evelyn; Schlör, Anja; Sifringer, Marco; Scheuer, Till; Bührer, Christoph; Schmitz, Thomas

2017-01-01

Sequelae of prematurity triggered by oxidative stress and free radical-mediated tissue damage have coined the term “oxygen radical disease of prematurity”. Caffeine, a potent free radical scavenger and adenosine receptor antagonist, reduces rates of brain damage in preterm infants. In the present study, we investigated the effects of caffeine on oxidative stress markers, anti-oxidative response, inflammation, redox-sensitive transcription factors, apoptosis, and extracellular matrix following the induction of hyperoxia in neonatal rats. The brain of a rat pups at postnatal Day 6 (P6) corresponds to that of a human fetal brain at 28–32 weeks gestation and the neonatal rat is an ideal model in which to investigate effects of oxidative stress and neuroprotection of caffeine on the developing brain. Six-day-old Wistar rats were pre-treated with caffeine and exposed to 80% oxygen for 24 and 48 h. Caffeine reduced oxidative stress marker (heme oxygenase-1, lipid peroxidation, hydrogen peroxide, and glutamate-cysteine ligase catalytic subunit (GCLC)), promoted anti-oxidative response (superoxide dismutase, peroxiredoxin 1, and sulfiredoxin 1), down-regulated pro-inflammatory cytokines, modulated redox-sensitive transcription factor expression (Nrf2/Keap1, and NFκB), reduced pro-apoptotic effectors (poly (ADP-ribose) polymerase-1 (PARP-1), apoptosis inducing factor (AIF), and caspase-3), and diminished extracellular matrix degeneration (matrix metalloproteinases (MMP) 2, and inhibitor of metalloproteinase (TIMP) 1/2). Our study affirms that caffeine is a pleiotropic neuroprotective drug in the developing brain due to its anti-oxidant, anti-inflammatory, and anti-apoptotic properties. PMID:28106777
Neuroprotection by Caffeine in Hyperoxia-Induced Neonatal Brain Injury.

PubMed

Endesfelder, Stefanie; Weichelt, Ulrike; Strauß, Evelyn; Schlör, Anja; Sifringer, Marco; Scheuer, Till; Bührer, Christoph; Schmitz, Thomas

2017-01-18

Sequelae of prematurity triggered by oxidative stress and free radical-mediated tissue damage have coined the term "oxygen radical disease of prematurity". Caffeine, a potent free radical scavenger and adenosine receptor antagonist, reduces rates of brain damage in preterm infants. In the present study, we investigated the effects of caffeine on oxidative stress markers, anti-oxidative response, inflammation, redox-sensitive transcription factors, apoptosis, and extracellular matrix following the induction of hyperoxia in neonatal rats. The brain of a rat pups at postnatal Day 6 (P6) corresponds to that of a human fetal brain at 28-32 weeks gestation and the neonatal rat is an ideal model in which to investigate effects of oxidative stress and neuroprotection of caffeine on the developing brain. Six-day-old Wistar rats were pre-treated with caffeine and exposed to 80% oxygen for 24 and 48 h. Caffeine reduced oxidative stress marker (heme oxygenase-1, lipid peroxidation, hydrogen peroxide, and glutamate-cysteine ligase catalytic subunit (GCLC)), promoted anti-oxidative response (superoxide dismutase, peroxiredoxin 1, and sulfiredoxin 1), down-regulated pro-inflammatory cytokines, modulated redox-sensitive transcription factor expression (Nrf2/Keap1, and NFκB), reduced pro-apoptotic effectors (poly (ADP-ribose) polymerase-1 (PARP-1), apoptosis inducing factor (AIF), and caspase-3), and diminished extracellular matrix degeneration (matrix metalloproteinases (MMP) 2, and inhibitor of metalloproteinase (TIMP) 1/2). Our study affirms that caffeine is a pleiotropic neuroprotective drug in the developing brain due to its anti-oxidant, anti-inflammatory, and anti-apoptotic properties.

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

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

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

2014-08-14

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

NASA Astrophysics Data System (ADS)

Hamzah, Mohd Hamdi Irwan; Baharom, Fauziah; Mohd, Haslina

2017-10-01

Commonly, organizations adopted Service-Oriented Architecture (SOA) because it can provide a flexible reconfiguration and can reduce the development time and cost. In order to guide the SOA adoption, previous industry and academia have constructed SOA maturity model. However, there is a limited number of works on how to construct the matrix in the previous SOA maturity model. Therefore, this study is going to provide a method that can be used in order to construct the matrix in the SOA maturity model. This study adapts Kano Model to construct the cross evaluation matrix focused on SOA adoption IT and business benefits. This study found that Kano Model can provide a suitable and appropriate method for constructing the cross evaluation matrix in SOA maturity model. Kano model also can be used to plot, organize and better represent the evaluation dimension for evaluating the SOA adoption.
Lignin biosynthesis perturbations affect secondary cell wall composition and saccharification yield in Arabidopsis thaliana

PubMed Central

2013-01-01

Background Second-generation biofuels are generally produced from the polysaccharides in the lignocellulosic plant biomass, mainly cellulose. However, because cellulose is embedded in a matrix of other polysaccharides and lignin, its hydrolysis into the fermentable glucose is hampered. The senesced inflorescence stems of a set of 20 Arabidopsis thaliana mutants in 10 different genes of the lignin biosynthetic pathway were analyzed for cell wall composition and saccharification yield. Saccharification models were built to elucidate which cell wall parameters played a role in cell wall recalcitrance. Results Although lignin is a key polymer providing the strength necessary for the plant’s ability to grow upward, a reduction in lignin content down to 64% of the wild-type level in Arabidopsis was tolerated without any obvious growth penalty. In contrast to common perception, we found that a reduction in lignin was not compensated for by an increase in cellulose, but rather by an increase in matrix polysaccharides. In most lignin mutants, the saccharification yield was improved by up to 88% cellulose conversion for the cinnamoyl-coenzyme A reductase1 mutants under pretreatment conditions, whereas the wild-type cellulose conversion only reached 18%. The saccharification models and Pearson correlation matrix revealed that the lignin content was the main factor determining the saccharification yield. However, also lignin composition, matrix polysaccharide content and composition, and, especially, the xylose, galactose, and arabinose contents influenced the saccharification yield. Strikingly, cellulose content did not significantly affect saccharification yield. Conclusions Although the lignin content had the main effect on saccharification, also other cell wall factors could be engineered to potentially increase the cell wall processability, such as the galactose content. Our results contribute to a better understanding of the effect of lignin perturbations on plant cell wall composition and its influence on saccharification yield, and provide new potential targets for genetic improvement. PMID:23622268
Stage-structured matrix models for organisms with non-geometric development times

Treesearch

Andrew Birt; Richard M. Feldman; David M. Cairns; Robert N. Coulson; Maria Tchakerian; Weimin Xi; James M. Guldin

2009-01-01

Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model...
Pattern identification in time-course gene expression data with the CoGAPS matrix factorization.

PubMed

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

2014-01-01

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less
A review of failure models for unidirectional ceramic matrix composites under monotonic loads

NASA Technical Reports Server (NTRS)

Tripp, David E.; Hemann, John H.; Gyekenyesi, John P.

1989-01-01

Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by trial and error since the emphasis of feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.
The genealogical decomposition of a matrix population model with applications to the aggregation of stages.

PubMed

Bienvenu, François; Akçay, Erol; Legendre, Stéphane; McCandlish, David M

2017-06-01

Matrix projection models are a central tool in many areas of population biology. In most applications, one starts from the projection matrix to quantify the asymptotic growth rate of the population (the dominant eigenvalue), the stable stage distribution, and the reproductive values (the dominant right and left eigenvectors, respectively). Any primitive projection matrix also has an associated ergodic Markov chain that contains information about the genealogy of the population. In this paper, we show that these facts can be used to specify any matrix population model as a triple consisting of the ergodic Markov matrix, the dominant eigenvalue and one of the corresponding eigenvectors. This decomposition of the projection matrix separates properties associated with lineages from those associated with individuals. It also clarifies the relationships between many quantities commonly used to describe such models, including the relationship between eigenvalue sensitivities and elasticities. We illustrate the utility of such a decomposition by introducing a new method for aggregating classes in a matrix population model to produce a simpler model with a smaller number of classes. Unlike the standard method, our method has the advantage of preserving reproductive values and elasticities. It also has conceptually satisfying properties such as commuting with changes of units. Copyright © 2017 Elsevier Inc. All rights reserved.
Micromechanical Modeling of Woven Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Pindera, Marek-Jerzy

1997-01-01

This report presents the results of an extensive micromechanical modeling effort for woven metal matrix composites. The model is employed to predict the mechanical response of 8-harness (8H) satin weave carbon/copper (C/Cu) composites. Experimental mechanical results for this novel high thermal conductivity material were recently reported by Bednarcyk et al. along with preliminary model results. The micromechanics model developed herein is based on an embedded approach. A micromechanics model for the local (micro-scale) behavior of the woven composite, the original method of cells (Aboudi), is embedded in a global (macro-scale) micromechanics model (the three-dimensional generalized method of cells (GMC-3D) (Aboudi). This approach allows representation of true repeating unit cells for woven metal matrix composites via GMC-3D, and representation of local effects, such as matrix plasticity, yarn porosity, and imperfect fiber-matrix bonding. In addition, the equations of GMC-3D were reformulated to significantly reduce the number of unknown quantities that characterize the deformation fields at the microlevel in order to make possible the analysis of actual microstructures of woven composites. The resulting micromechanical model (WCGMC) provides an intermediate level of geometric representation, versatility, and computational efficiency with respect to previous analytical and numerical models for woven composites, but surpasses all previous modeling work by allowing the mechanical response of a woven metal matrix composite, with an elastoplastic matrix, to be examined for the first time. WCGMC is employed to examine the effects of composite microstructure, porosity, residual stresses, and imperfect fiber-matrix bonding on the predicted mechanical response of 8H satin C/Cu. The previously reported experimental results are summarized, and the model predictions are compared to monotonic and cyclic tensile and shear test data. By considering appropriate levels of porosity, residual stresses, and imperfect fiber-matrix debonding, reasonably good qualitative and quantitative correlation is achieved between model and experiment.
Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.
In vitro model to study the effects of matrix stiffening on Ca2+ handling and myofilament function in isolated adult rat cardiomyocytes

PubMed Central

Najafi, Aref; Fontoura, Dulce; Valent, Erik; Goebel, Max; Kardux, Kim; Falcão‐Pires, Inês; van der Velden, Jolanda

2017-01-01

Key points This paper describes a novel model that allows exploration of matrix‐induced cardiomyocyte adaptations independent of the passive effect of matrix rigidity on cardiomyocyte function.Detachment of adult cardiomyocytes from the matrix enables the study of matrix effects on cell shortening, Ca2+ handling and myofilament function.Cell shortening and Ca2+ handling are altered in cardiomyocytes cultured for 24 h on a stiff matrix.Matrix stiffness‐impaired cardiomyocyte contractility is reversed upon normalization of extracellular stiffness.Matrix stiffness‐induced reduction in unloaded shortening is more pronounced in cardiomyocytes isolated from obese ZSF1 rats with heart failure with preserved ejection fraction compared to lean ZSF1 rats. Abstract Extracellular matrix (ECM) stiffening is a key element of cardiac disease. Increased rigidity of the ECM passively inhibits cardiac contraction, but if and how matrix stiffening also actively alters cardiomyocyte contractility is incompletely understood. In vitro models designed to study cardiomyocyte–matrix interaction lack the possibility to separate passive inhibition by a stiff matrix from active matrix‐induced alterations of cardiomyocyte properties. Here we introduce a novel experimental model that allows exploration of cardiomyocyte functional alterations in response to matrix stiffening. Adult rat cardiomyocytes were cultured for 24 h on matrices of tuneable stiffness representing the healthy and the diseased heart and detached from their matrix before functional measurements. We demonstrate that matrix stiffening, independent of passive inhibition, reduces cell shortening and Ca2+ handling but does not alter myofilament‐generated force. Additionally, detachment of adult cultured cardiomyocytes allowed the transfer of cells from one matrix to another. This revealed that stiffness‐induced cardiomyocyte changes are reversed when matrix stiffness is normalized. These matrix stiffness‐induced changes in cardiomyocyte function could not be explained by adaptation in the microtubules. Additionally, cardiomyocytes isolated from stiff hearts of the obese ZSF1 rat model of heart failure with preserved ejection fraction show more pronounced reduction in unloaded shortening in response to matrix stiffening. Taken together, we introduce a method that allows evaluation of the influence of ECM properties on cardiomyocyte function separate from the passive inhibitory component of a stiff matrix. As such, it adds an important and physiologically relevant tool to investigate the functional consequences of cardiomyocyte–matrix interactions. PMID:28485491
Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.
Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239
Modelling and analysis of FMS productivity variables by ISM, SEM and GTMA approach

NASA Astrophysics Data System (ADS)

Jain, Vineet; Raj, Tilak

2014-09-01

Productivity has often been cited as a key factor in a flexible manufacturing system (FMS) performance, and actions to increase it are said to improve profitability and the wage earning capacity of employees. Improving productivity is seen as a key issue for survival and success in the long term of a manufacturing system. The purpose of this paper is to make a model and analysis of the productivity variables of FMS. This study was performed by different approaches viz. interpretive structural modelling (ISM), structural equation modelling (SEM), graph theory and matrix approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a model of productivity variables, and then it has been analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. CFA is carried by SEM. EFA is applied to extract the factors in FMS by the statistical package for social sciences (SPSS 20) software and confirming these factors by CFA through analysis of moment structures (AMOS 20) software. The twenty productivity variables are identified through literature and four factors extracted, which involves the productivity of FMS. The four factors are people, quality, machine and flexibility. SEM using AMOS 20 was used to perform the first order four-factor structures. GTMA is a multiple attribute decision making (MADM) methodology used to find intensity/quantification of productivity variables in an organization. The FMS productivity index has purposed to intensify the factors which affect FMS.
Growth factor transgenes interactively regulate articular chondrocytes.

PubMed

Shi, Shuiliang; Mercer, Scott; Eckert, George J; Trippel, Stephen B

2013-04-01

Adult articular chondrocytes lack an effective repair response to correct damage from injury or osteoarthritis. Polypeptide growth factors that stimulate articular chondrocyte proliferation and cartilage matrix synthesis may augment this response. Gene transfer is a promising approach to delivering such factors. Multiple growth factor genes regulate these cell functions, but multiple growth factor gene transfer remains unexplored. We tested the hypothesis that multiple growth factor gene transfer selectively modulates articular chondrocyte proliferation and matrix synthesis. We tested the hypothesis by delivering combinations of the transgenes encoding insulin-like growth factor I (IGF-I), fibroblast growth factor-2 (FGF-2), transforming growth factor beta1 (TGF-β1), bone morphogenetic protein-2 (BMP-2), and bone morphogenetic protien-7 (BMP-7) to articular chondrocytes and measured changes in the production of DNA, glycosaminoglycan, and collagen. The transgenes differentially regulated all these chondrocyte activities. In concert, the transgenes interacted to generate widely divergent responses from the cells. These interactions ranged from inhibitory to synergistic. The transgene pair encoding IGF-I and FGF-2 maximized cell proliferation. The three-transgene group encoding IGF-I, BMP-2, and BMP-7 maximized matrix production and also optimized the balance between cell proliferation and matrix production. These data demonstrate an approach to articular chondrocyte regulation that may be tailored to stimulate specific cell functions, and suggest that certain growth factor gene combinations have potential value for cell-based articular cartilage repair. Copyright © 2012 Wiley Periodicals, Inc.
Leukocyte- and platelet-rich fibrin (L-PRF) for long-term delivery of growth factor in rotator cuff repair: review, preliminary results and future directions.

PubMed

Zumstein, Matthias A; Berger, Simon; Schober, Martin; Boileau, Pascal; Nyffeler, Richard W; Horn, Michael; Dahinden, Clemens A

2012-06-01

Surgical repair of the rotator cuff repair is one of the most common procedures in orthopedic surgery. Despite it being the focus of much research, the physiological tendon-bone insertion is not recreated following repair and there is an anatomic non-healing rate of up to 94%. During the healing phase, several growth factors are upregulated that induce cellular proliferation and matrix deposition. Subsequently, this provisional matrix is replaced by the definitive matrix. Leukocyte- and platelet-rich fibrin (L-PRF) contain growth factors and has a stable dense fibrin matrix. Therefore, use of LPRF in rotator cuff repair is theoretically attractive. The aim of the present study was to determine 1) the optimal protocol to achieve the highest leukocyte content; 2) whether L-PRF releases growth factors in a sustained manner over 28 days; 3) whether standard/gelatinous or dry/compressed matrix preparation methods result in higher growth factor concentrations. 1) The standard L-PRF centrifugation protocol with 400 x g showed the highest concentration of platelets and leukocytes. 2) The L-PRF clots cultured in medium showed a continuous slow release with an increase in the absolute release of growth factors TGF-β1, VEGF and MPO in the first 7 days, and for IGF1, PDGF-AB and platelet activity (PF4=CXCL4) in the first 8 hours, followed by a decrease to close to zero at 28 days. Significantly higher levels of growth factor were expressed relative to the control values of normal blood at each culture time point. 3) Except for MPO and the TGFβ-1, there was always a tendency towards higher release of growth factors (i.e., CXCL4, IGF-1, PDGF-AB, and VEGF) in the standard/gelatinous- compared to the dry/compressed group. L-PRF in its optimal standard/gelatinous-type matrix can store and deliver locally specific healing growth factors for up to 28 days and may be a useful adjunct in rotator cuff repair.
Human performance modeling for system of systems analytics: combat performance-shaping factors.

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

Lawton, Craig R.; Miller, Dwight Peter

The US military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives. To support this goal, Sandia National Laboratories (SNL) has undertaken a program of HPM as an integral augmentation to its system-of-system (SoS) analytics capabilities. The previous effort, reported in SAND2005-6569, evaluated the effects of soldier cognitive fatigue on SoS performance. The current effort began with a very broad survey of any performance-shaping factors (PSFs) that also might affect soldiers performance in combat situations. The work included consideration of three different approaches to cognition modeling and how appropriate theymore » would be for application to SoS analytics. This bulk of this report categorizes 47 PSFs into three groups (internal, external, and task-related) and provides brief descriptions of how each affects combat performance, according to the literature. The PSFs were then assembled into a matrix with 22 representative military tasks and assigned one of four levels of estimated negative impact on task performance, based on the literature. Blank versions of the matrix were then sent to two ex-military subject-matter experts to be filled out based on their personal experiences. Data analysis was performed to identify the consensus most influential PSFs. Results indicate that combat-related injury, cognitive fatigue, inadequate training, physical fatigue, thirst, stress, poor perceptual processing, and presence of chemical agents are among the PSFs with the most negative impact on combat performance.« less
Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

NASA Astrophysics Data System (ADS)

Sofowote, Uwayemi M.; Hung, Hayley; Rastogi, Ankit K.; Westgate, John N.; Deluca, Patrick F.; Su, Yushan; McCarry, Brian E.

2011-02-01

Gas-phase and particle-phase atmospheric samples collected in a sparsely populated sub-Arctic environment in the Yukon Territory, Canada were analyzed for a wide range of organic pollutants including polycyclic aromatic hydrocarbons (PAH). Receptor modeling using positive matrix factorization (PMF) was applied to a PAH data set from samples collected between August 2007 and December 2008 to afford four factors. These factors were designated as fossil fuel combustion emissions, particle-phase wood combustion emissions, gas-phase wood combustion emissions, and unburned petroleum/petrogenic emissions. The multiple linear regression-derived average contributions of these factors to the total PAH concentrations were 14% for fossil fuel combustion, 6% for particle-phase wood combustion emissions, 46% for gas-phase wood combustion emissions and 34% for petrogenic emissions. When the total PAH concentrations (defined as the sum of twenty-two PAH) and the PMF-modeled PAH concentrations set were compared, the correlation was excellent ( R2 = 0.97). Ten-day back trajectories starting at four different heights were used in a potential source contribution function analysis (PSCF) to assess the potential source regions of these PAH factors. Mapping the computed PSCF values for the four PMF factors revealed different source regions in the northern hemisphere for each PMF factor. Atmospheric transport of PAH occurred from both relatively short and long distances with both continental (North American) and trans-oceanic (Asian) sources contributing significantly to the total PAH. This study provides evidence of the transport of fossil fuel and wood combustion emissions from Asia, continental North America and northern Europe to sub-Arctic Canada (and by extension to the Canadian Arctic) primarily during cooler (fall-winter) months. This study demonstrates for the first time that the combined PMF-PSCF methodology can be used to identify geographically-disperse PAH source contributors on a hemispherical scale.

Matrix density alters zyxin phosphorylation, which limits peripheral process formation and extension in endothelial cells invading 3D collagen matrices.

PubMed

Abbey, Colette A; Bayless, Kayla J

2014-09-01

This study was designed to determine the optimal conditions required for known pro-angiogenic stimuli to elicit successful endothelial sprouting responses. We used an established, quantifiable model of endothelial cell (EC) sprout initiation where ECs were tested for invasion in low (1 mg/mL) and high density (5 mg/mL) 3D collagen matrices. Sphingosine 1-phosphate (S1P) alone, or S1P combined with stromal derived factor-1α (SDF) and phorbol ester (TPA), elicited robust sprouting responses. The ability of these factors to stimulate sprouting was more effective in higher density collagen matrices. S1P stimulation resulted in a significant increase in invasion distance, and with the exception of treatment groups containing phorbol ester, invasion distance was longer in 1mg/mL compared to 5mg/mL collagen matrices. Closer examination of cell morphology revealed that increasing matrix density and supplementing with SDF and TPA enhanced the formation of multicellular structures more closely resembling capillaries. TPA enhanced the frequency and size of lumen formation and correlated with a robust increase in phosphorylation of p42/p44 Erk kinase, while S1P and SDF did not. Also, a higher number of significantly longer extended processes formed in 5mg/mL compared to 1mg/mL collagen matrices. Because collagen matrices at higher density have been reported to be stiffer, we tested for changes in the mechanosensitive protein, zyxin. Interestingly, zyxin phosphorylation levels inversely correlated with matrix density, while levels of total zyxin did not change significantly. Immunofluorescence and localization studies revealed that total zyxin was distributed evenly throughout invading structures, while phosphorylated zyxin was slightly more intense in extended peripheral processes. Silencing zyxin expression increased extended process length and number of processes, while increasing zyxin levels decreased extended process length. Altogether these data indicate that ECs integrate signals from multiple exogenous factors, including changes in matrix density, to accomplish successful sprouting responses. We show here for the first time that zyxin limited the formation and extension of fine peripheral processes used by ECs for matrix interrogation, providing a molecular explanation for altered EC responses to high and low density collagen matrices. Copyright © 2014 International Society of Matrix Biology. Published by Elsevier B.V. All rights reserved.
Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train.

PubMed

Bengua, Johann A; Phien, Ho N; Tuan, Hoang Duong; Do, Minh N

2017-05-01

This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via TT (SiLRTC-TT) is intimately related to minimizing a nuclear norm based on TT rank. The second one is from a multilinear matrix factorization model to approximate the TT rank of a tensor, and is called tensor completion by parallel matrix factorization via TT (TMac-TT). A tensor augmentation scheme of transforming a low-order tensor to higher orders is also proposed to enhance the effectiveness of SiLRTC-TT and TMac-TT. Simulation results for color image and video recovery show the clear advantage of our method over all other methods.
scarlet: Source separation in multi-band images by Constrained Matrix Factorization

NASA Astrophysics Data System (ADS)

Melchior, Peter; Moolekamp, Fred; Jerdee, Maximilian; Armstrong, Robert; Sun, Ai-Lei; Bosch, James; Lupton, Robert

2018-03-01

SCARLET performs source separation (aka "deblending") on multi-band images. It is geared towards optical astronomy, where scenes are composed of stars and galaxies, but it is straightforward to apply it to other imaging data. Separation is achieved through a constrained matrix factorization, which models each source with a Spectral Energy Distribution (SED) and a non-parametric morphology, or multiple such components per source. The code performs forced photometry (with PSF matching if needed) using an optimal weight function given by the signal-to-noise weighted morphology across bands. The approach works well if the sources in the scene have different colors and can be further strengthened by imposing various additional constraints/priors on each source. Because of its generic utility, this package provides a stand-alone implementation that contains the core components of the source separation algorithm. However, the development of this package is part of the LSST Science Pipeline; the meas_deblender package contains a wrapper to implement the algorithms here for the LSST stack.
Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

PubMed

Zetlaoui, Mélanie; Feinberg, Max; Verger, Philippe; Clémençon, Stephan

2011-12-01

In Western countries where food supply is satisfactory, consumers organize their diets around a large combination of foods. It is the purpose of this article to examine how recent nonnegative matrix factorization (NMF) techniques can be applied to food consumption data to understand these combinations. Such data are nonnegative by nature and of high dimension. The NMF model provides a representation of consumption data through latent vectors with nonnegative coefficients, that we call consumption systems (CS), in a small number. As the NMF approach may encourage sparsity of the data representation produced, the resulting CS are easily interpretable. Beyond the illustration of its properties we provide through a simple simulation result, the NMF method is applied to data issued from a French consumption survey. The numerical results thus obtained are displayed and thoroughly discussed. A clustering based on the k-means method is also achieved in the resulting latent consumption space, to recover food consumption patterns easily usable for nutritionists. © 2011, The International Biometric Society.
Nano-sized precipitate stability and its controlling factors in a NiAl-strengthened ferritic alloy

DOE PAGES

Sun, Zhiqian; Song, Gian; Ilavsky, Jan; ...

2015-11-05

Coherent B2-ordered NiAl-type precipitates have been used to reinforce solid-solution bodycentered- cubic iron for high-temperature application in fossil-energy power plants. In this study, the stability of nano-sized precipitates in a NiAl-strengthened ferritic alloy was investigated at 700 - 950°C using ultra-small angle X-ray scattering and electron microscopies. Here we show that the coarsening kinetics of NiAl-type precipitates is in excellent agreement with the ripening model in multicomponent alloys. We further demonstrate that the interfacial energy between the matrix and NiAl-type precipitates is strongly dependent to differences in the matrix/precipitate compositions. The results profile the ripening process in multicomponent alloys bymore » illustrating controlling factors (i.e., interfacial energy, diffusivities, and element partitioning). As a result, the study provides guidelines to design and develop high-temperature alloys with stable microstructures for long-term service.« less
Community detection enhancement using non-negative matrix factorization with graph regularization

NASA Astrophysics Data System (ADS)

Liu, Xiao; Wei, Yi-Ming; Wang, Jian; Wang, Wen-Jun; He, Dong-Xiao; Song, Zhan-Jie

2016-06-01

Community detection is a meaningful task in the analysis of complex networks, which has received great concern in various domains. A plethora of exhaustive studies has made great effort and proposed many methods on community detection. Particularly, a kind of attractive one is the two-step method which first makes a preprocessing for the network and then identifies its communities. However, not all types of methods can achieve satisfactory results by using such preprocessing strategy, such as the non-negative matrix factorization (NMF) methods. In this paper, rather than using the above two-step method as most works did, we propose a graph regularized-based model to improve, specialized, the NMF-based methods for the detection of communities, namely NMFGR. In NMFGR, we introduce the similarity metric which contains both the global and local information of networks, to reflect the relationships between two nodes, so as to improve the accuracy of community detection. Experimental results on both artificial and real-world networks demonstrate the superior performance of NMFGR to some competing methods.
The Bottlenose Dolphin (Tursiops truncatus) as a Model to Understand Variation in Stress and Reproductive Hormone Measures in Relation to Sampling Matrix, Demographics, and Environmental Factors

DTIC Science & Technology

2011-09-30

support the existence of these same stress response pathways in marine mammals. While the HPA axis and physiological processes driven by the GCs are...cortisol, aldosterone , thyroid and reproductive hormones) have been routinely measured in blood as part of the health assessment which also includes a
A Block Coordinate Descent Method for Multi-Convex Optimization with Applications to Nonnegative Tensor Factorization and Completion

DTIC Science & Technology

2012-08-01

model appears in cosmic microwave background analysis [10] which solves min A,Y λ 2 trace ( (ABY − X)>C−1(ABY − X) ) + r(Y), subject to A ∈ D (1.5...and “×n” represent outer product and tensor-matrix multiplication, respectively. (The necessary background of tensor is reviewed in Sec. 3) Most
The Impact of Goal Setting and Empowerment on Governmental Matrix Organizations

DTIC Science & Technology

1993-09-01

shared. In a study of matrix management, Eduardo Vasconcellos further describes various matrix structures in the Galbraith model. In a functional...Technology/LAR, Wright-Patterson AFB OH, 1992. Vasconcellos , Eduardo . "A Model For a Better Understanding of the Matrix Structure," IEEE Transactions on...project matrix, the project manager maintains more influence and the structure lies to the right-of center ( Vasconcellos , 1979:58). Different Types of
Experimental estimation of migration and transfer of organic substances from consumer articles to cotton wipes: Evaluation of underlying mechanisms.

PubMed

Clausen, Per Axel; Spaan, Suzanne; Brouwer, Derk H; Marquart, Hans; le Feber, Maaike; Engel, Roel; Geerts, Lieve; Jensen, Keld Alstrup; Kofoed-Sørensen, Vivi; Hansen, Brian; De Brouwere, Katleen

2016-01-01

The aim of this work was to identify the key mechanisms governing transport of organic chemical substances from consumer articles to cotton wipes. The results were used to establish a mechanistic model to improve assessment of dermal contact exposure. Four types of PVC flooring, 10 types of textiles and one type of inkjet printed paper were used to establish the mechanisms and model. Kinetic extraction studies in methanol demonstrated existence of matrix diffusion and indicated the presence of a substance surface layer on some articles. Consequently, the proposed substance transfer model considers mechanical transport from a surface film and matrix diffusion in an article with a known initial total substance concentration. The estimated chemical substance transfer values to cotton wipes were comparable to the literature data (relative transfer ∼ 2%), whereas relative transfer efficiencies from spiked substrates were high (∼ 50%). For consumer articles, high correlation (r(2)=0.92) was observed between predicted and measured transfer efficiencies, but concentrations were overpredicted by a factor of 10. Adjusting the relative transfer from about 50% used in the model to about 2.5% removed overprediction. Further studies are required to confirm the model for generic use.
EFFECT OF GROWTH FACTOR-FIBRONECTIN MATRIX INTERACTION ON RAT TYPE II CELL ADHESION AND DNA SYTHESIS

EPA Science Inventory

ABSTRACT

Type II cells attach, migrate and proliferate on a provisional fibronectin-rich matrix during alveolar wall repair after lung injury. The combination of cell-substratum interactions via integrin receptors and exposure to local growth factors are likely to initiat...
In vitro model to study the effects of matrix stiffening on Ca2+ handling and myofilament function in isolated adult rat cardiomyocytes.

PubMed

van Deel, Elza D; Najafi, Aref; Fontoura, Dulce; Valent, Erik; Goebel, Max; Kardux, Kim; Falcão-Pires, Inês; van der Velden, Jolanda

2017-07-15

This paper describes a novel model that allows exploration of matrix-induced cardiomyocyte adaptations independent of the passive effect of matrix rigidity on cardiomyocyte function. Detachment of adult cardiomyocytes from the matrix enables the study of matrix effects on cell shortening, Ca 2+ handling and myofilament function. Cell shortening and Ca 2+ handling are altered in cardiomyocytes cultured for 24 h on a stiff matrix. Matrix stiffness-impaired cardiomyocyte contractility is reversed upon normalization of extracellular stiffness. Matrix stiffness-induced reduction in unloaded shortening is more pronounced in cardiomyocytes isolated from obese ZSF1 rats with heart failure with preserved ejection fraction compared to lean ZSF1 rats. Extracellular matrix (ECM) stiffening is a key element of cardiac disease. Increased rigidity of the ECM passively inhibits cardiac contraction, but if and how matrix stiffening also actively alters cardiomyocyte contractility is incompletely understood. In vitro models designed to study cardiomyocyte-matrix interaction lack the possibility to separate passive inhibition by a stiff matrix from active matrix-induced alterations of cardiomyocyte properties. Here we introduce a novel experimental model that allows exploration of cardiomyocyte functional alterations in response to matrix stiffening. Adult rat cardiomyocytes were cultured for 24 h on matrices of tuneable stiffness representing the healthy and the diseased heart and detached from their matrix before functional measurements. We demonstrate that matrix stiffening, independent of passive inhibition, reduces cell shortening and Ca 2+ handling but does not alter myofilament-generated force. Additionally, detachment of adult cultured cardiomyocytes allowed the transfer of cells from one matrix to another. This revealed that stiffness-induced cardiomyocyte changes are reversed when matrix stiffness is normalized. These matrix stiffness-induced changes in cardiomyocyte function could not be explained by adaptation in the microtubules. Additionally, cardiomyocytes isolated from stiff hearts of the obese ZSF1 rat model of heart failure with preserved ejection fraction show more pronounced reduction in unloaded shortening in response to matrix stiffening. Taken together, we introduce a method that allows evaluation of the influence of ECM properties on cardiomyocyte function separate from the passive inhibitory component of a stiff matrix. As such, it adds an important and physiologically relevant tool to investigate the functional consequences of cardiomyocyte-matrix interactions. © 2017 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.
Matrix approach to land carbon cycle modeling: A case study with the Community Land Model.

PubMed

Huang, Yuanyuan; Lu, Xingjie; Shi, Zheng; Lawrence, David; Koven, Charles D; Xia, Jianyang; Du, Zhenggang; Kluzek, Erik; Luo, Yiqi

2018-03-01

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO 2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective. © 2017 John Wiley & Sons Ltd.
Modeling invasive breast cancer: growth factors propel progression of HER2-positive premalignant lesions

PubMed Central

Pradeep, C-R; Zeisel, A; Köstler, WJ; Lauriola, M; Jacob-Hirsch, J; Haibe-Kains, B; Amariglio, N; Ben-Chetrit, N; Emde, A; Solomonov, I; Neufeld, G; Piccart, M; Sagi, I; Sotiriou, C; Rechavi, G; Domany, E; Desmedt, C; Yarden, Y

2013-01-01

The HER2/neu oncogene encodes a receptor-like tyrosine kinase whose overexpression in breast cancer predicts poor prognosis and resistance to conventional therapies. However, the mechanisms underlying aggressiveness of HER2 (human epidermal growth factor receptor 2)-overexpressing tumors remain incompletely understood. Because it assists epidermal growth factor (EGF) and neuregulin receptors, we overexpressed HER2 in MCF10A mammary cells and applied growth factors. HER2-overexpressing cells grown in extracellular matrix formed filled spheroids, which protruded outgrowths upon growth factor stimulation. Our transcriptome analyses imply a two-hit model for invasive growth: HER2-induced proliferation and evasion from anoikis generate filled structures, which are morphologically and transcriptionally analogous to preinvasive patients’ lesions. In the second hit, EGF escalates signaling and transcriptional responses leading to invasive growth. Consistent with clinical relevance, a gene expression signature based on the HER2/EGF-activated transcriptional program can predict poorer prognosis of a subgroup of HER2-overexpressing patients. In conclusion, the integration of a three-dimensional cellular model and clinical data attributes progression of HER2-overexpressing lesions to EGF-like growth factors acting in the context of the tumor's microenvironment. PMID:22139081
B → Dℓν form factors at nonzero recoil and |V cb| from 2+1-flavor lattice QCD

DOE PAGES

Bailey, Jon A.

2015-08-10

We present the first unquenched lattice-QCD calculation of the hadronic form factors for the exclusive decay B¯→Dℓν¯ at nonzero recoil. We carry out numerical simulations on 14 ensembles of gauge-field configurations generated with 2+1 flavors of asqtad-improved staggered sea quarks. The ensembles encompass a wide range of lattice spacings (approximately 0.045 to 0.12 fm) and ratios of light (up and down) to strange sea-quark masses ranging from 0.05 to 0.4. For the b and c valence quarks we use improved Wilson fermions with the Fermilab interpretation, while for the light valence quarks we use asqtad-improved staggered fermions. We extrapolate ourmore » results to the physical point using rooted staggered heavy-light meson chiral perturbation theory. We then parametrize the form factors and extend them to the full kinematic range using model-independent functions based on analyticity and unitarity. We present our final results for f +(q 2) and f 0(q 2), including statistical and systematic errors, as coefficients of a series in the variable z and the covariance matrix between these coefficients. We then fit the lattice form-factor data jointly with the experimentally measured differential decay rate from BABAR to determine the CKM matrix element, |V cb|=(39.6 ± 1.7 QCD+exp ± 0.2 QED) × 10 –3. As a byproduct of the joint fit we obtain the form factors with improved precision at large recoil. In conclusion, we use them to update our calculation of the ratio R(D) in the Standard Model, which yields R(D)=0.299(11).« less
Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample.

PubMed

Lecerf, Thierry; Canivez, Gary L

2018-06-01

Interpretation of the French Wechsler Intelligence Scale for Children-Fifth Edition (French WISC-V; Wechsler, 2016a) is based on a 5-factor model including Verbal Comprehension (VC), Visual Spatial (VS), Fluid Reasoning (FR), Working Memory (WM), and Processing Speed (PS). Evidence for the French WISC-V factorial structure was established exclusively through confirmatory factor analyses (CFAs). However, as recommended by Carroll (1995); Reise (2012), and Brown (2015), factorial structure should derive from both exploratory factor analysis (EFA) and CFA. The first goal of this study was to examine the factorial structure of the French WISC-V using EFA. The 15 French WISC-V primary and secondary subtest scaled scores intercorrelation matrix was used and factor extraction criteria suggested from 1 to 4 factors. To disentangle the contribution of first- and second-order factors, the Schmid and Leiman (1957) orthogonalization transformation (SLT) was applied. Overall, no EFA evidence for 5 factors was found. Results indicated that the g factor accounted for about 67% of the common variance and that the contributions of the first-order factors were weak (3.6 to 11.9%). CFA was used to test numerous alternative models. Results indicated that bifactor models produced better fit to these data than higher-order models. Consistent with previous studies, findings suggested dominance of the general intelligence factor and that users should thus emphasize the Full Scale IQ (FSIQ) when interpreting the French WISC-V. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
An efficient solution of real-time data processing for multi-GNSS network

NASA Astrophysics Data System (ADS)

Gong, Xiaopeng; Gu, Shengfeng; Lou, Yidong; Zheng, Fu; Ge, Maorong; Liu, Jingnan

2017-12-01

Global navigation satellite systems (GNSS) are acting as an indispensable tool for geodetic research and global monitoring of the Earth, and they have been rapidly developed over the past few years with abundant GNSS networks, modern constellations, and significant improvement in mathematic models of data processing. However, due to the increasing number of satellites and stations, the computational efficiency becomes a key issue and it could hamper the further development of GNSS applications. In this contribution, this problem is overcome from the aspects of both dense linear algebra algorithms and GNSS processing strategy. First, in order to fully explore the power of modern microprocessors, the square root information filter solution based on the blocked QR factorization employing as many matrix-matrix operations as possible is introduced. In addition, the algorithm complexity of GNSS data processing is further decreased by centralizing the carrier-phase observations and ambiguity parameters, as well as performing the real-time ambiguity resolution and elimination. Based on the QR factorization of the simulated matrix, we can conclude that compared to unblocked QR factorization, the blocked QR factorization can greatly improve processing efficiency with a magnitude of nearly two orders on a personal computer with four 3.30 GHz cores. Then, with 82 globally distributed stations, the processing efficiency is further validated in multi-GNSS (GPS/BDS/Galileo) satellite clock estimation. The results suggest that it will take about 31.38 s per epoch for the unblocked method. While, without any loss of accuracy, it only takes 0.50 and 0.31 s for our new algorithm per epoch for float and fixed clock solutions, respectively.
Collagen-binding VEGF mimetic peptide: Structure, matrix interaction, and endothelial cell activation

NASA Astrophysics Data System (ADS)

Chan, Tania R.

Long term survival of artificial tissue constructs depends greatly on proper vascularization. In nature, differentiation of endothelial cells and formation of vasculature are directed by dynamic spatio-temporal cues in the extracellular matrix that are difficult to reproduce in vitro. In this dissertation, we present a novel bifunctional peptide that mimics matrix-bound vascular endothelial growth factor (VEGF), which can be used to encode spatially controlled angiogenic signals in collagen-based scaffolds. The peptide, QKCMP, contains a collagen mimetic domain (CMP) that binds to type I collagen by a unique triple helix hybridization mechanism and a VEGF mimetic domain (QK) with pro-angiogenic activity. We demonstrate QKCMP's ability to hybridize with native and heat denatured collagens through a series of binding studies on collagen and gelatin substrates. Circular dichroism experiments show that the peptide retains the triple helical structure vital for collagen binding, and surface plasmon resonance study confirms the molecular interaction between the peptide and collagen strands. Cell culture studies demonstrate QKCMP's ability to induce endothelial cell morphogenesis and network formation as a matrix-bound factor in 2D and 3D collagen scaffolds. We also show that the peptide can be used to spatially modify collagen-based substrates to promote localized endothelial cell activation and network formation. To probe the biological events that govern these angiogenic cellular responses, we investigated the cell signaling pathways activated by collagen-bound QKCMP and determined short and long-term endothelial cell response profiles for p38, ERK1/2, and Akt signal transduction cascades. Finally, we present our efforts to translate the peptide's in vitro bioactivity to an in vivo burn injury animal model. When implanted at the wound site, QKCMP functionalized biodegradable hydrogels induce enhanced neovascularization in the granulation tissue. The results show QKCMP's efficacy as a matrix-bound angiogenic factor that directs endothelial cell proliferation and migration. These findings suggest that QKCMP can be used to enhance microvasculature formation during wound healing as well as to promote spatially controlled microvasculature for tissue engineering applications.
UDU/T/ covariance factorization for Kalman filtering

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1980-01-01

There has been strong motivation to produce numerically stable formulations of the Kalman filter algorithms because it has long been known that the original discrete-time Kalman formulas are numerically unreliable. Numerical instability can be avoided by propagating certain factors of the estimate error covariance matrix rather than the covariance matrix itself. This paper documents filter algorithms that correspond to the covariance factorization P = UDU(T), where U is a unit upper triangular matrix and D is diagonal. Emphasis is on computational efficiency and numerical stability, since these properties are of key importance in real-time filter applications. The history of square-root and U-D covariance filters is reviewed. Simple examples are given to illustrate the numerical inadequacy of the Kalman covariance filter algorithms; these examples show how factorization techniques can give improved computational reliability.

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