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.

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

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.

Receptor control in mesenchymal stem cell engineering

NASA Astrophysics Data System (ADS)

Dalby, Matthew J.; García, Andrés J.; Salmeron-Sanchez, Manuel

2018-03-01

Materials science offers a powerful tool to control mesenchymal stem cell (MSC) growth and differentiation into functional phenotypes. A complex interplay between the extracellular matrix and growth factors guides MSC phenotypes in vivo. In this Review, we discuss materials-based bioengineering approaches to direct MSC fate in vitro and in vivo, mimicking cell-matrix-growth factor crosstalk. We first scrutinize MSC-matrix interactions and how the properties of a material can be tailored to support MSC growth and differentiation in vitro, with an emphasis on MSC self-renewal mechanisms. We then highlight important growth factor signalling pathways and investigate various materials-based strategies for growth factor presentation and delivery. Integrin-growth factor crosstalk in the context of MSC engineering is introduced, and bioinspired material designs with the potential to control the MSC niche phenotype are considered. Finally, we summarize important milestones on the road to MSC engineering for regenerative medicine.

Development and Validation of a Job Exposure Matrix for Physical Risk Factors in Low Back Pain

PubMed Central

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

2012-01-01

Objectives The aim was to construct and validate a gender-specific job exposure matrix (JEM) for physical exposures to be used in epidemiological studies of low back pain (LBP). Materials and Methods We utilized two large Finnish population surveys, one to construct the JEM and another to test matrix validity. The exposure axis of the matrix included exposures relevant to LBP (heavy physical work, heavy lifting, awkward trunk posture and whole body vibration) and exposures that increase the biomechanical load on the low back (arm elevation) or those that in combination with other known risk factors could be related to LBP (kneeling or squatting). Job titles with similar work tasks and exposures were grouped. Exposure information was based on face-to-face interviews. Validity of the matrix was explored by comparing the JEM (group-based) binary measures with individual-based measures. The predictive validity of the matrix against LBP was evaluated by comparing the associations of the group-based (JEM) exposures with those of individual-based exposures. Results The matrix includes 348 job titles, representing 81% of all Finnish job titles in the early 2000s. The specificity of the constructed matrix was good, especially in women. The validity measured with kappa-statistic ranged from good to poor, being fair for most exposures. In men, all group-based (JEM) exposures were statistically significantly associated with one-month prevalence of LBP. In women, four out of six group-based exposures showed an association with LBP. Conclusions The gender-specific JEM for physical exposures showed relatively high specificity without compromising sensitivity. The matrix can therefore be considered as a valid instrument for exposure assessment in large-scale epidemiological studies, when more precise but more labour-intensive methods are not feasible. Although the matrix was based on Finnish data we foresee that it could be applicable, with some modifications, in other countries with a similar level of technology. PMID:23152793

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.

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.

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.

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.

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.

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

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.

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

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.

Evidence-Based Practice: A Matrix for Predicting Phonological Generalization

ERIC Educational Resources Information Center

Gierut, Judith A.; Hulse, Lauren E.

2010-01-01

This paper describes a matrix for clinical use in the selection of phonological treatment targets to induce generalization, and in the identification of probe sounds to monitor during the course of intervention. The matrix appeals to a set of factors that have been shown to promote phonological generalization in the research literature, including…

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.

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

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.

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.

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.

New fast DCT algorithms based on Loeffler's factorization

NASA Astrophysics Data System (ADS)

Hong, Yoon Mi; Kim, Il-Koo; Lee, Tammy; Cheon, Min-Su; Alshina, Elena; Han, Woo-Jin; Park, Jeong-Hoon

2012-10-01

This paper proposes a new 32-point fast discrete cosine transform (DCT) algorithm based on the Loeffler's 16-point transform. Fast integer realizations of 16-point and 32-point transforms are also provided based on the proposed transform. For the recent development of High Efficiency Video Coding (HEVC), simplified quanti-zation and de-quantization process are proposed. Three different forms of implementation with the essentially same performance, namely matrix multiplication, partial butterfly, and full factorization can be chosen accord-ing to the given platform. In terms of the number of multiplications required for the realization, our proposed full-factorization is 3~4 times faster than a partial butterfly, and about 10 times faster than direct matrix multiplication.

Multichannel Compressive Sensing MRI Using Noiselet Encoding

PubMed Central

Pawar, Kamlesh; Egan, Gary; Zhang, Jingxin

2015-01-01

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

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

PubMed

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

Theoretical Bound of CRLB for Energy Efficient Technique of RSS-Based Factor Graph Geolocation

NASA Astrophysics Data System (ADS)

Kahar Aziz, Muhammad Reza; Heriansyah; Saputra, EfaMaydhona; Musa, Ardiansyah

2018-03-01

To support the increase of wireless geolocation development as the key of the technology in the future, this paper proposes theoretical bound derivation, i.e., Cramer Rao lower bound (CRLB) for energy efficient of received signal strength (RSS)-based factor graph wireless geolocation technique. The theoretical bound derivation is crucially important to evaluate whether the energy efficient technique of RSS-based factor graph wireless geolocation is effective as well as to open the opportunity to further innovation of the technique. The CRLB is derived in this paper by using the Fisher information matrix (FIM) of the main formula of the RSS-based factor graph geolocation technique, which is lied on the Jacobian matrix. The simulation result shows that the derived CRLB has the highest accuracy as a bound shown by its lowest root mean squared error (RMSE) curve compared to the RMSE curve of the RSS-based factor graph geolocation technique. Hence, the derived CRLB becomes the lower bound for the efficient technique of RSS-based factor graph wireless geolocation.

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.

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

DOE PAGES

Martino, Mikael M.; Brkic, Sime; Bovo, Emmanuela; ...

2015-04-01

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

Extracellular Matrix-Inspired Growth Factor Delivery Systems for Skin Wound Healing

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

Briquez, Priscilla S.; Hubbell, Jeffrey A.; Martino, Mikaël M.

2015-08-01

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

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

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

Martino, Mikael M.; Brkic, Sime; Bovo, Emmanuela

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

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

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

Martino, Mikael M.; Brkic, Sime; Bovo, Emmanuela

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

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

PubMed Central

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

2016-01-01

Introduction: Traffic accidents are the 8th cause of mortality in different countries and are expected to rise to the 3rd rank by 2020. Based on the Haddon matrix numerous factors such as environment, host, and agent can affect the severity of traffic-related traumas. Therefore, the present study aimed to evaluate the effective factors in severity of these traumas based on Haddon matrix. Methods: In the present 1-month cross-sectional study, all the patients injured in traffic accidents, who were referred to the ED of Imam Khomeini and Golestan Hospitals, Ahvaz, Iran, during March 2013 were evaluated. Based on the Haddon matrix, effective factors in accident occurrence were defined in 3 groups of host, agent, and environment. Demographic data of the patients and data regarding Haddon risk factors were extracted and analyzed using SPSS version 20. Results: 700 injured people with the mean age of 29.66 ± 12.64 years (3-82) were evaluated (92.4% male). Trauma mechanism was car-pedestrian in 308 (44%) of the cases and car-motorcycle in 175 (25%). 610 (87.1%) cases were traffic accidents and 371 (53%) occurred in the time between 2 pm and 8 pm. Violation of speed limit was the most common violation with 570 (81.4%) cases, followed by violation of right-of-way in 57 (8.1%) patients. 59.9% of the severe and critical injuries had occurred on road accidents, while 61.3% of the injuries caused by traffic accidents were mild to moderate (p < 0.001). The most common mechanisms of trauma for critical injuries were rollover (72.5%), motorcycle-pedestrian (23.8%), and car-motorcycle (13.14%) accidents (p < 0.001). Conclusion: Based on the results of the present study, the most important effective factors in severity of traffic accident-related traumas were age over 50, not using safety tools, and undertaking among host-related factors; insufficient environment safety, road accidents and time between 2 pm and 8 pm among environmental factors; and finally, rollover, car-pedestrian, and motorcycle-pedestrian accidents among the agent factors PMID:27274517

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.

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.

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.

Periodontal plastic surgery of gingival recessions at single and multiple teeth.

PubMed

Cairo, Francesco

2017-10-01

This manuscript aims to review periodontal plastic surgery for root coverage at single and multiple gingival recessions. Techniques are assessed based on biological principles, surgical procedures, prognosticative factors and expected clinical and esthetic outcomes. The use of coronally advanced flap, laterally sliding flap, free gingival graft, the tunnel grafting technique, barrier membranes, enamel matrix derivative, collagen matrix and acellular dermal matrix are evaluated. The clinical scenario and practical implications are analyzed according to a modern evidence-based approach. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Effects of partitioning and scheduling sparse matrix factorization on communication and load balance

NASA Technical Reports Server (NTRS)

Venugopal, Sesh; Naik, Vijay K.

1991-01-01

A block based, automatic partitioning and scheduling methodology is presented for sparse matrix factorization on distributed memory systems. Using experimental results, this technique is analyzed for communication and load imbalance overhead. To study the performance effects, these overheads were compared with those obtained from a straightforward 'wrap mapped' column assignment scheme. All experimental results were obtained using test sparse matrices from the Harwell-Boeing data set. The results show that there is a communication and load balance tradeoff. The block based method results in lower communication cost whereas the wrap mapped scheme gives better load balance.

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.

Factors affecting miniature Izod impact strength of tungsten-fiber-metal-matrix

NASA Technical Reports Server (NTRS)

Winsa, E. A.; Petrasek, D. W.

1973-01-01

The miniature Izod and Charpy impact strengths of copper, copper-nickel, and nickel-base superalloy uniaxially reinforced with continuous tungsten fibers were studied. In most cases, impact strength was increased by increasing fiber or matrix toughness, decreasing fibermatrix reaction, increasing test temperature, hot working, or heat treating. Notch sensitivity was reduced by increasing fiber content or matrix toughness. An equation relating impact strength to fiber and matrix properties and fiber content was developed. Program results imply that tungsten alloy-fiber/superalloy matrix composites can be made with adequate impact resistance for turbine blade or vane applications.

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

Clustering Tree-structured Data on Manifold

PubMed Central

Lu, Na; Miao, Hongyu

2016-01-01

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

Deep learning and non-negative matrix factorization in recognition of mammograms

NASA Astrophysics Data System (ADS)

Swiderski, Bartosz; Kurek, Jaroslaw; Osowski, Stanislaw; Kruk, Michal; Barhoumi, Walid

2017-02-01

This paper presents novel approach to the recognition of mammograms. The analyzed mammograms represent the normal and breast cancer (benign and malignant) cases. The solution applies the deep learning technique in image recognition. To obtain increased accuracy of classification the nonnegative matrix factorization and statistical self-similarity of images are applied. The images reconstructed by using these two approaches enrich the data base and thanks to this improve of quality measures of mammogram recognition (increase of accuracy, sensitivity and specificity). The results of numerical experiments performed on large DDSM data base containing more than 10000 mammograms have confirmed good accuracy of class recognition, exceeding the best results reported in the actual publications for this data base.

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.

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.

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

DTIC Science & Technology

2004-06-01

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

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.

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Mohammed, Ahmed Ali; Kadiam, Subhash

2010-01-01

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!

A one-step matrix application method for MALDI mass spectrometry imaging of bacterial colony biofilms.

PubMed

Li, Bin; Comi, Troy J; Si, Tong; Dunham, Sage J B; Sweedler, Jonathan V

2016-11-01

Matrix-assisted laser desorption/ionization imaging of biofilms cultured on agar plates is challenging because of problems related to matrix deposition onto agar. We describe a one-step, spray-based application of a 2,5-dihydroxybenzoic acid solution for direct matrix-assisted laser desorption/ionization imaging of hydrated Bacillus subtilis biofilms on agar. Using both an optimized airbrush and a home-built automatic sprayer, region-specific distributions of signaling metabolites and cannibalistic factors were visualized from B. subtilis cells cultivated on biofilm-promoting medium. The approach provides a homogeneous, relatively dry coating on hydrated samples, improving spot to spot signal repeatability compared with sieved matrix application, and is easily adapted for imaging a range of agar-based biofilms. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Coping with matrix effects in headspace solid phase microextraction gas chromatography using multivariate calibration strategies.

PubMed

Ferreira, Vicente; Herrero, Paula; Zapata, Julián; Escudero, Ana

2015-08-14

SPME is extremely sensitive to experimental parameters affecting liquid-gas and gas-solid distribution coefficients. Our aims were to measure the weights of these factors and to design a multivariate strategy based on the addition of a pool of internal standards, to minimize matrix effects. Synthetic but real-like wines containing selected analytes and variable amounts of ethanol, non-volatile constituents and major volatile compounds were prepared following a factorial design. The ANOVA study revealed that even using a strong matrix dilution, matrix effects are important and additive with non-significant interaction effects and that it is the presence of major volatile constituents the most dominant factor. A single internal standard provided a robust calibration for 15 out of 47 analytes. Then, two different multivariate calibration strategies based on Partial Least Square Regression were run in order to build calibration functions based on 13 different internal standards able to cope with matrix effects. The first one is based in the calculation of Multivariate Internal Standards (MIS), linear combinations of the normalized signals of the 13 internal standards, which provide the expected area of a given unit of analyte present in each sample. The second strategy is a direct calibration relating concentration to the 13 relative areas measured in each sample for each analyte. Overall, 47 different compounds can be reliably quantified in a single fully automated method with overall uncertainties better than 15%. Copyright © 2015 Elsevier B.V. All rights reserved.

The AdS{sub 5}xS{sup 5} superstring worldsheet S matrix and crossing symmetry

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

Janik, Romuald A.

2006-04-15

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

Metal- and intermetallic-matrix composites for aerospace propulsion and power systems

NASA Astrophysics Data System (ADS)

Doychak, J.

1992-06-01

Successful development and deployment of metal-matrix composites and intermetallic- matrix composites are critical to reaching the goals of many advanced aerospace propulsion and power development programs. The material requirements are based on the aerospace propulsion and power system requirements, economics, and other factors. Advanced military and civilian aircraft engines will require higher specific strength materials that operate at higher temperatures, and the civilian engines will also require long lifetimes. The specific space propulsion and power applications require hightemperature, high-thermal-conductivity, and high-strength materials. Metal-matrix composites and intermetallic-matrix composites either fulfill or have the potential of fulfilling these requirements.

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.

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…

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.

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…

Critical Evaluation of Risk Factors and Early Complications in 564 Consecutive Two-Stage Implant-Based Breast Reconstructions Using Acellular Dermal Matrix at a Single Center.

PubMed

Selber, Jesse C; Wren, James H; Garvey, Patrick B; Zhang, Hong; Erickson, Cameron; Clemens, Mark W; Butler, Charles E

2015-07-01

Acellular dermal matrix for implant-based breast reconstruction appears to cause higher early complication rates, but long-term outcomes are perceived to be superior. This dichotomy is the subject of considerable debate. The authors hypothesized that patient characteristics and operative variables would have a greater impact on complications than the type of acellular dermal matrix used. A retrospective cohort study was performed of consecutive patients who underwent two-stage, implant-based breast reconstruction with human cadaveric or bovine acellular dermal matrix from 2006 to 2012 at a single institution. Patient characteristics and operative variables were analyzed using logistic regression analyses to identify risk factors for complications. The authors included 564 reconstructions in the study. Radiation therapy and obesity increased the odds of all complications. Every 100-ml increase in preoperative breast volume increased the odds of any complication by 1 percent, the odds of infection by 27 percent, and the risk of explantation by 16 percent. The odds of seroma increased linearly with increasing surface area of acellular dermal matrix. Odds of infection were higher with an intraoperative expander fill volume greater than 50 percent of the total volume. Risk of explantation was twice as high when intraoperative expander fill volume was greater than 300 ml. Radiation therapy, obesity, larger breasts, higher intraoperative fill volumes, and larger acellular dermal matrices are all independent risk factors for early complications. Maximizing the initial mastectomy skin envelope fill must be balanced with the understanding that higher complication rates may result from a larger intraoperative breast mound. Risk, III.

Acausal measurement-based quantum computing

NASA Astrophysics Data System (ADS)

Morimae, Tomoyuki

2014-07-01

In measurement-based quantum computing, there is a natural "causal cone" among qubits of the resource state, since the measurement angle on a qubit has to depend on previous measurement results in order to correct the effect of by-product operators. If we respect the no-signaling principle, by-product operators cannot be avoided. Here we study the possibility of acausal measurement-based quantum computing by using the process matrix framework [Oreshkov, Costa, and Brukner, Nat. Commun. 3, 1092 (2012), 10.1038/ncomms2076]. We construct a resource process matrix for acausal measurement-based quantum computing restricting local operations to projective measurements. The resource process matrix is an analog of the resource state of the standard causal measurement-based quantum computing. We find that if we restrict local operations to projective measurements the resource process matrix is (up to a normalization factor and trivial ancilla qubits) equivalent to the decorated graph state created from the graph state of the corresponding causal measurement-based quantum computing. We also show that it is possible to consider a causal game whose causal inequality is violated by acausal measurement-based quantum computing.

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

NASA Astrophysics Data System (ADS)

Schuster, Philip C.; Toro, Natalia

2009-06-01

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

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.

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.

Using Strassen's algorithm to accelerate the solution of linear systems

NASA Technical Reports Server (NTRS)

Bailey, David H.; Lee, King; Simon, Horst D.

1990-01-01

Strassen's algorithm for fast matrix-matrix multiplication has been implemented for matrices of arbitrary shapes on the CRAY-2 and CRAY Y-MP supercomputers. Several techniques have been used to reduce the scratch space requirement for this algorithm while simultaneously preserving a high level of performance. When the resulting Strassen-based matrix multiply routine is combined with some routines from the new LAPACK library, LU decomposition can be performed with rates significantly higher than those achieved by conventional means. We succeeded in factoring a 2048 x 2048 matrix on the CRAY Y-MP at a rate equivalent to 325 MFLOPS.

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

Recursive inverse factorization.

PubMed

Rubensson, Emanuel H; Bock, Nicolas; Holmström, Erik; Niklasson, Anders M N

2008-03-14

A recursive algorithm for the inverse factorization S(-1)=ZZ(*) of Hermitian positive definite matrices S is proposed. The inverse factorization is based on iterative refinement [A.M.N. Niklasson, Phys. Rev. B 70, 193102 (2004)] combined with a recursive decomposition of S. As the computational kernel is matrix-matrix multiplication, the algorithm can be parallelized and the computational effort increases linearly with system size for systems with sufficiently sparse matrices. Recent advances in network theory are used to find appropriate recursive decompositions. We show that optimization of the so-called network modularity results in an improved partitioning compared to other approaches. In particular, when the recursive inverse factorization is applied to overlap matrices of irregularly structured three-dimensional molecules.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

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.

Access of Hydrogen-Radicals to the Peptide-Backbone as a Measure for Estimating the Flexibility of Proteins Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

PubMed Central

Takayama, Mitsuo; Nagoshi, Keishiro; Iimuro, Ryunosuke; Inatomi, Kazuma

2014-01-01

A factor for estimating the flexibility of proteins is described that uses a cleavage method of “in-source decay (ISD)” coupled with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). The MALDI-ISD spectra of bovine serum albumin (BSA), myoglobin and thioredoxin show discontinuous intense ion peaks originating from one-side preferential cleavage at the N-Cα bond of Xxx-Asp, Xxx-Asn, Xxx-Cys and Gly-Xxx residues. Consistent with these observations, Asp, Asn and Gly residues are also identified by other flexibility measures such as B-factor, turn preference, protection and fluorescence decay factors, while Asp, Asn, Cys and Gly residues are identified by turn preference factor based on X-ray crystallography. The results suggest that protein molecules embedded in/on MALDI matrix crystals partly maintain α-helix and that the reason some of the residues are more susceptible to ISD (Asp, Asn, Cys and Gly) and others less so (Ile and Val) is because of accessibility of the peptide backbone to hydrogen-radicals from matrix molecules. The hydrogen-radical accessibility in MALDI-ISD could therefore be adopted as a factor for measuring protein flexibility. PMID:24828203

Necessary and sufficient conditions for the complete controllability and observability of systems in series using the coprime factorization of a rational matrix

NASA Technical Reports Server (NTRS)

Callier, F. M.; Nahum, C. D.

1975-01-01

The series connection of two linear time-invariant systems that have minimal state space system descriptions is considered. From these descriptions, strict-system-equivalent polynomial matrix system descriptions in the manner of Rosenbrock are derived. They are based on the factorization of the transfer matrix of the subsystems as a ratio of two right or left coprime polynomial matrices. They give rise to a simple polynomial matrix system description of the tandem connection. Theorem 1 states that for the complete controllability and observability of the state space system description of the series connection, it is necessary and sufficient that certain 'denominator' and 'numerator' groups are coprime. Consequences for feedback systems are drawn in Corollary 1. The role of pole-zero cancellations is explained by Lemma 3 and Corollaires 2 and 3.

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.

Probabilistic low-rank factorization accelerates tensor network simulations of critical quantum many-body ground states.

PubMed

Kohn, Lucas; Tschirsich, Ferdinand; Keck, Maximilian; Plenio, Martin B; Tamascelli, Dario; Montangero, Simone

2018-01-01

We provide evidence that randomized low-rank factorization is a powerful tool for the determination of the ground-state properties of low-dimensional lattice Hamiltonians through tensor network techniques. In particular, we show that randomized matrix factorization outperforms truncated singular value decomposition based on state-of-the-art deterministic routines in time-evolving block decimation (TEBD)- and density matrix renormalization group (DMRG)-style simulations, even when the system under study gets close to a phase transition: We report linear speedups in the bond or local dimension of up to 24 times in quasi-two-dimensional cylindrical systems.

Probabilistic low-rank factorization accelerates tensor network simulations of critical quantum many-body ground states

NASA Astrophysics Data System (ADS)

Kohn, Lucas; Tschirsich, Ferdinand; Keck, Maximilian; Plenio, Martin B.; Tamascelli, Dario; Montangero, Simone

2018-01-01

We provide evidence that randomized low-rank factorization is a powerful tool for the determination of the ground-state properties of low-dimensional lattice Hamiltonians through tensor network techniques. In particular, we show that randomized matrix factorization outperforms truncated singular value decomposition based on state-of-the-art deterministic routines in time-evolving block decimation (TEBD)- and density matrix renormalization group (DMRG)-style simulations, even when the system under study gets close to a phase transition: We report linear speedups in the bond or local dimension of up to 24 times in quasi-two-dimensional cylindrical systems.

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.

Online blind source separation using incremental nonnegative matrix factorization with volume constraint.

PubMed

Zhou, Guoxu; Yang, Zuyuan; Xie, Shengli; Yang, Jun-Mei

2011-04-01

Online blind source separation (BSS) is proposed to overcome the high computational cost problem, which limits the practical applications of traditional batch BSS algorithms. However, the existing online BSS methods are mainly used to separate independent or uncorrelated sources. Recently, nonnegative matrix factorization (NMF) shows great potential to separate the correlative sources, where some constraints are often imposed to overcome the non-uniqueness of the factorization. In this paper, an incremental NMF with volume constraint is derived and utilized for solving online BSS. The volume constraint to the mixing matrix enhances the identifiability of the sources, while the incremental learning mode reduces the computational cost. The proposed method takes advantage of the natural gradient based multiplication updating rule, and it performs especially well in the recovery of dependent sources. Simulations in BSS for dual-energy X-ray images, online encrypted speech signals, and high correlative face images show the validity of the proposed method.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-05-18

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Factorization and fitting of molecular scattering information

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

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

1977-12-15

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

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

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

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

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

PubMed

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

2015-02-01

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

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.

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

PubMed

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

2017-09-01

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

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...

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.

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal

PubMed Central

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-01-01

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

PubMed

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-10-23

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal.

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.

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

PubMed

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

2014-01-01

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

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

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

2014-01-01

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

Continuous analogues of matrix factorizations

PubMed Central

Townsend, Alex; Trefethen, Lloyd N.

2015-01-01

Analogues of singular value decomposition (SVD), QR, LU and Cholesky factorizations are presented for problems in which the usual discrete matrix is replaced by a ‘quasimatrix’, continuous in one dimension, or a ‘cmatrix’, continuous in both dimensions. Two challenges arise: the generalization of the notions of triangular structure and row and column pivoting to continuous variables (required in all cases except the SVD, and far from obvious), and the convergence of the infinite series that define the cmatrix factorizations. Our generalizations of triangularity and pivoting are based on a new notion of a ‘triangular quasimatrix’. Concerning convergence of the series, we prove theorems asserting convergence provided the functions involved are sufficiently smooth. PMID:25568618

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.

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…

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.

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.

Hardware Implementation of a MIMO Decoder Using Matrix Factorization Based Channel Estimation

NASA Astrophysics Data System (ADS)

Islam, Mohammad Tariqul; Numan, Mostafa Wasiuddin; Misran, Norbahiah; Ali, Mohd Alauddin Mohd; Singh, Mandeep

2011-05-01

This paper presents an efficient hardware realization of multiple-input multiple-output (MIMO) wireless communication decoder that utilizes the available resources by adopting the technique of parallelism. The hardware is designed and implemented on Xilinx Virtex™-4 XC4VLX60 field programmable gate arrays (FPGA) device in a modular approach which simplifies and eases hardware update, and facilitates testing of the various modules independently. The decoder involves a proficient channel estimation module that employs matrix factorization on least squares (LS) estimation to reduce a full rank matrix into a simpler form in order to eliminate matrix inversion. This results in performance improvement and complexity reduction of the MIMO system. Performance evaluation of the proposed method is validated through MATLAB simulations which indicate 2 dB improvement in terms of SNR compared to LS estimation. Moreover complexity comparison is performed in terms of mathematical operations, which shows that the proposed approach appreciably outperforms LS estimation at a lower complexity and represents a good solution for channel estimation technique.

Kinetic factors determining conducting filament formation in solid polymer electrolyte based planar devices

NASA Astrophysics Data System (ADS)

Krishnan, Karthik; Aono, Masakazu; Tsuruoka, Tohru

2016-07-01

Resistive switching characteristics and conducting filament formation dynamics in solid polymer electrolyte (SPE) based planar-type atomic switches, with opposing active Ag and inert Pt electrodes, have been investigated by optimizing the device configuration and experimental parameters such as the gap distance between the electrodes, the salt inclusion in the polymer matrix, and the compliance current applied in current-voltage measurements. The high ionic conductivities of SPE enabled us to make scanning electron microscopy observations of the filament formation processes in the sub-micrometer to micrometer ranges. It was found that switching behaviour and filament growth morphology depend strongly on several kinetic factors, such as the redox reaction rate at the electrode-polymer interfaces, ion mobility in the polymer matrix, electric field strength, and the reduction sites for precipitation. Different filament formations, resulting from unidirectional and dendritic growth behaviours, can be controlled by tuning specified parameters, which in turn improves the stability and performance of SPE-based devices.Resistive switching characteristics and conducting filament formation dynamics in solid polymer electrolyte (SPE) based planar-type atomic switches, with opposing active Ag and inert Pt electrodes, have been investigated by optimizing the device configuration and experimental parameters such as the gap distance between the electrodes, the salt inclusion in the polymer matrix, and the compliance current applied in current-voltage measurements. The high ionic conductivities of SPE enabled us to make scanning electron microscopy observations of the filament formation processes in the sub-micrometer to micrometer ranges. It was found that switching behaviour and filament growth morphology depend strongly on several kinetic factors, such as the redox reaction rate at the electrode-polymer interfaces, ion mobility in the polymer matrix, electric field strength, and the reduction sites for precipitation. Different filament formations, resulting from unidirectional and dendritic growth behaviours, can be controlled by tuning specified parameters, which in turn improves the stability and performance of SPE-based devices. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00569a

The extracellular matrix in myocardial injury, repair, and remodeling

PubMed Central

2017-01-01

The cardiac extracellular matrix (ECM) not only provides mechanical support, but also transduces essential molecular signals in health and disease. Following myocardial infarction, dynamic ECM changes drive inflammation and repair. Early generation of bioactive matrix fragments activates proinflammatory signaling. The formation of a highly plastic provisional matrix facilitates leukocyte infiltration and activates infarct myofibroblasts. Deposition of matricellular proteins modulates growth factor signaling and contributes to the spatial and temporal regulation of the reparative response. Mechanical stress due to pressure and volume overload and metabolic dysfunction also induce profound changes in ECM composition that contribute to the pathogenesis of heart failure. This manuscript reviews the role of the ECM in cardiac repair and remodeling and discusses matrix-based therapies that may attenuate remodeling while promoting repair and regeneration. PMID:28459429

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.

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 Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising

PubMed Central

Guo, Muran; Chen, Tao; Wang, Ben

2017-01-01

Co-prime arrays can estimate the directions of arrival (DOAs) of O(MN) sources with O(M+N) sensors, and are convenient to analyze due to their closed-form expression for the locations of virtual lags. However, the number of degrees of freedom is limited due to the existence of holes in difference coarrays if subspace-based algorithms such as the spatial smoothing multiple signal classification (MUSIC) algorithm are utilized. To address this issue, techniques such as positive definite Toeplitz completion and array interpolation have been proposed in the literature. Another factor that compromises the accuracy of DOA estimation is the limitation of the number of snapshots. Coarray-based processing is particularly sensitive to the discrepancy between the sample covariance matrix and the ideal covariance matrix due to the finite number of snapshots. In this paper, coarray interpolation based on matrix completion (MC) followed by a denoising operation is proposed to detect more sources with a higher accuracy. The effectiveness of the proposed method is based on the capability of MC to fill in holes in the virtual sensors and that of MC denoising operation to reduce the perturbation in the sample covariance matrix. The results of numerical simulations verify the superiority of the proposed approach. PMID:28509886

An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising.

PubMed

Guo, Muran; Chen, Tao; Wang, Ben

2017-05-16

Co-prime arrays can estimate the directions of arrival (DOAs) of O ( M N ) sources with O ( M + N ) sensors, and are convenient to analyze due to their closed-form expression for the locations of virtual lags. However, the number of degrees of freedom is limited due to the existence of holes in difference coarrays if subspace-based algorithms such as the spatial smoothing multiple signal classification (MUSIC) algorithm are utilized. To address this issue, techniques such as positive definite Toeplitz completion and array interpolation have been proposed in the literature. Another factor that compromises the accuracy of DOA estimation is the limitation of the number of snapshots. Coarray-based processing is particularly sensitive to the discrepancy between the sample covariance matrix and the ideal covariance matrix due to the finite number of snapshots. In this paper, coarray interpolation based on matrix completion (MC) followed by a denoising operation is proposed to detect more sources with a higher accuracy. The effectiveness of the proposed method is based on the capability of MC to fill in holes in the virtual sensors and that of MC denoising operation to reduce the perturbation in the sample covariance matrix. The results of numerical simulations verify the superiority of the proposed approach.

Recurrence quantity analysis based on matrix eigenvalues

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian

2018-06-01

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

Matrix effect and recovery terminology issues in regulated drug bioanalysis.

PubMed

Huang, Yong; Shi, Robert; Gee, Winnie; Bonderud, Richard

2012-02-01

Understanding the meaning of the terms used in the bioanalytical method validation guidance is essential for practitioners to implement best practice. However, terms that have several meanings or that have different interpretations exist within bioanalysis, and this may give rise to differing practices. In this perspective we discuss an important but often confusing term - 'matrix effect (ME)' - in regulated drug bioanalysis. The ME can be interpreted as either the ionization change or the measurement bias of the method caused by the nonanalyte matrix. The ME definition dilemma makes its evaluation challenging. The matrix factor is currently used as a standard method for evaluation of ionization changes caused by the matrix in MS-based methods. Standard additions to pre-extraction samples have been suggested to evaluate the overall effects of a matrix from different sources on the analytical system, because it covers ionization variation and extraction recovery variation. We also provide our personal views on the term 'recovery'.

Factors affecting the microstructure and mechanical properties of Ti-Al3Ti core-shell-structured particle-reinforced Al matrix composites

NASA Astrophysics Data System (ADS)

Guo, Baisong; Yi, Jianhong; Ni, Song; Shen, Rujuan; Song, Min

2016-04-01

This work studied the effects of matrix powder and sintering temperature on the microstructure and mechanical properties of in situ formed Ti-Al3Ti core-shell-structured particle-reinforced pure Al-based composites. It has been shown that both factors have significant effects on the morphology of the reinforcements and densification behaviour of the composites. Due to the strong interfacial bonding and the limitation of the crack propagation in the intermetallic shell during deformation by soft Al matrix and Ti core, the composite fabricated using fine spherical-shaped Al powder and sintered at 570 °C for 5 h has the optimal combination of the overall mechanical properties. The study provides a direction for the optimum combination of high strength and ductility of the composites by adjusting the fabrication parameters.

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)

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

ERIC Educational Resources Information Center

Sawaki, Yasuyo; Stricker, Lawrence; Oranje, Andreas

2008-01-01

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

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

NASA Technical Reports Server (NTRS)

Fijany, Amir

1993-01-01

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

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

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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.

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.

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

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

Nagasaka, Y; Matsuoka, S; Azad, A

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

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.

The exponential parameterization of the neutrino mixing matrix as an SU(3) group element and an account for new experimental data

NASA Astrophysics Data System (ADS)

Zhukovsky, K. V.

2017-09-01

The exponential form of the Pontecorvo-Maki-Nakagawa-Sakata mixing matrix for neutrinos is considered in the context of the fundamental representation of the SU(3) group. The logarithm of the mixing matrix is obtained. Based on the most recent experimental data on neutrino mixing, the exact values of the entries of the exponential matrix are calculated. The exact values for its real and imaginary parts are determined, respectively, in charge of the mixing without CP violation and of the pure CP violation effect. The hypothesis of complementarity for quarks and neutrinos is confirmed. The factorization of the exponential mixing matrix, which allows the separation of the mixing and of the CP violation itself in the form of the product of rotations around the real and imaginary axes, is demonstrated.

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.

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…

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.

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.

Lanczos algorithm with matrix product states for dynamical correlation functions

NASA Astrophysics Data System (ADS)

Dargel, P. E.; Wöllert, A.; Honecker, A.; McCulloch, I. P.; Schollwöck, U.; Pruschke, T.

2012-05-01

The density-matrix renormalization group (DMRG) algorithm can be adapted to the calculation of dynamical correlation functions in various ways which all represent compromises between computational efficiency and physical accuracy. In this paper we reconsider the oldest approach based on a suitable Lanczos-generated approximate basis and implement it using matrix product states (MPS) for the representation of the basis states. The direct use of matrix product states combined with an ex post reorthogonalization method allows us to avoid several shortcomings of the original approach, namely the multitargeting and the approximate representation of the Hamiltonian inherent in earlier Lanczos-method implementations in the DMRG framework, and to deal with the ghost problem of Lanczos methods, leading to a much better convergence of the spectral weights and poles. We present results for the dynamic spin structure factor of the spin-1/2 antiferromagnetic Heisenberg chain. A comparison to Bethe ansatz results in the thermodynamic limit reveals that the MPS-based Lanczos approach is much more accurate than earlier approaches at minor additional numerical cost.

A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

PubMed

Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

2017-05-01

Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

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.

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.

Static and dynamic factors in an information-based multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Ponta, Linda; Pastore, Stefano; Cincotti, Silvano

2018-02-01

An information-based multi-asset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented. In the market, agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments and agents share their sentiments by means of interactions that are determined by sparsely connected networks. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Single stock price processes exhibit volatility clustering and fat-tailed distribution of returns whereas multivariate price process exhibits both static and dynamic stylized facts, i.e., the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation of returns of different stocks. The common trends are investigated considering the variance-covariance matrix of prices. Results point out that the probability distribution of eigenvalues of the cross-correlation matrix of returns shows the presence of sectors, similar to those observed on real empirical data. As regarding the dynamic factors, the variance-covariance matrix of prices point out a limited number of assets prices series that are independent integrated processes, in close agreement with the empirical evidence of asset price time series of real stock markets. These results remarks the crucial dependence of statistical properties of multi-assets stock market on the agents' interaction structure.

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

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.

Uncertainty in positive matrix factorization solutions for PAHs in surface sediments of the Yangtze River Estuary in different seasons.

PubMed

Liu, Ruimin; Men, Cong; Yu, Wenwen; Xu, Fei; Wang, Qingrui; Shen, Zhenyao

2018-01-01

To examine the variabilities of source contributions in the Yangtze River Estuary (YRE), the uncertainty based on the positive matrix factorization (PMF) was applied to the source apportionment of the 16 priority PAHs in 120 surface sediment samples from four seasons. Based on the signal-to-noise ratios, the PAHs categorized as "Bad" might drop out of the estimation of bootstrap. Next, the spatial variability of residuals was applied to determine which species with non-normal curves should be excluded. The median values from the bootstrapped solutions were chosen as the best estimate of the true factor contributions, and the intervals from 5th to 95th percentile represent the variability in each sample factor contribution. Based on the results, the median factor contributions of wood grass combustion and coke plant emissions were highly correlated with the variability (R 2  = 0.6797-0.9937) in every season. Meanwhile, the factor of coal and gasoline combustion had large variability with lower R 2 values in every season, especially in summer (0.4784) and winter (0.2785). The coefficient of variation (CV) values based on the Bootstrap (BS) simulations were applied to indicate the uncertainties of PAHs in every factor of each season. Acy, NaP and BgP always showed higher CV values, which suggested higher uncertainties in the BS simulations, and the PAH with the lowest concentration among all PAHs usually became the species with higher uncertainties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimated Satellite Cluster Elements in Near Circular Orbit

DTIC Science & Technology

1988-12-01

cluster is investigated. TheAon-board estimator is the U-D covariance factor’xzatiion’filter with dynamics based on the Clohessy - Wiltshire equations...Appropriate values for the velocity vector vi can be found irom the Clohessy - Wiltshire equations [9] (these equations will be explained in detail in the...explained in this text is the f matrix. The state transition matrix was developed from the Clohessy - Wiltshire equations of motion [9:page 3] as i - 2qý

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

Identification of candidate angiogenic inhibitors processed by matrix metalloproteinase 2 (MMP-2) in cell-based proteomic screens: disruption of vascular endothelial growth factor (VEGF)/heparin affin regulatory peptide (pleiotrophin) and VEGF/Connective tissue growth factor angiogenic inhibitory complexes by MMP-2 proteolysis.

PubMed

Dean, Richard A; Butler, Georgina S; Hamma-Kourbali, Yamina; Delbé, Jean; Brigstock, David R; Courty, José; Overall, Christopher M

2007-12-01

Matrix metalloproteinases (MMPs) exert both pro- and antiangiogenic functions by the release of cytokines or proteolytically generated angiogenic inhibitors from extracellular matrix and basement membrane remodeling. In the Mmp2-/- mouse neovascularization is greatly reduced, but the mechanistic aspects of this remain unclear. Using isotope-coded affinity tag labeling of proteins analyzed by multidimensional liquid chromatography and tandem mass spectrometry we explored proteome differences between Mmp2-/- cells and those rescued by MMP-2 transfection. Proteome signatures that are hallmarks of proteolysis revealed cleavage of many known MMP-2 substrates in the cellular context. Proteomic evidence of MMP-2 processing of novel substrates was found. Insulin-like growth factor binding protein 6, follistatin-like 1, and cystatin C protein cleavage by MMP-2 was biochemically confirmed, and the cleavage sites in heparin affin regulatory peptide (HARP; pleiotrophin) and connective tissue growth factor (CTGF) were sequenced by matrix-assisted laser desorption ionization-time of flight mass spectrometry. MMP-2 processing of HARP and CTGF released vascular endothelial growth factor (VEGF) from angiogenic inhibitory complexes. The cleaved HARP N-terminal domain increased HARP-induced cell proliferation, whereas the HARP C-terminal domain was antagonistic and decreased cell proliferation and migration. Hence the unmasking of cytokines, such as VEGF, by metalloproteinase processing of their binding proteins is a new mechanism in the control of cytokine activation and angiogenesis.

Identification of Candidate Angiogenic Inhibitors Processed by Matrix Metalloproteinase 2 (MMP-2) in Cell-Based Proteomic Screens: Disruption of Vascular Endothelial Growth Factor (VEGF)/Heparin Affin Regulatory Peptide (Pleiotrophin) and VEGF/Connective Tissue Growth Factor Angiogenic Inhibitory Complexes by MMP-2 Proteolysis▿ †

PubMed Central

Dean, Richard A.; Butler, Georgina S.; Hamma-Kourbali, Yamina; Delbé, Jean; Brigstock, David R.; Courty, José; Overall, Christopher M.

2007-01-01

Matrix metalloproteinases (MMPs) exert both pro- and antiangiogenic functions by the release of cytokines or proteolytically generated angiogenic inhibitors from extracellular matrix and basement membrane remodeling. In the Mmp2−/− mouse neovascularization is greatly reduced, but the mechanistic aspects of this remain unclear. Using isotope-coded affinity tag labeling of proteins analyzed by multidimensional liquid chromatography and tandem mass spectrometry we explored proteome differences between Mmp2−/− cells and those rescued by MMP-2 transfection. Proteome signatures that are hallmarks of proteolysis revealed cleavage of many known MMP-2 substrates in the cellular context. Proteomic evidence of MMP-2 processing of novel substrates was found. Insulin-like growth factor binding protein 6, follistatin-like 1, and cystatin C protein cleavage by MMP-2 was biochemically confirmed, and the cleavage sites in heparin affin regulatory peptide (HARP; pleiotrophin) and connective tissue growth factor (CTGF) were sequenced by matrix-assisted laser desorption ionization-time of flight mass spectrometry. MMP-2 processing of HARP and CTGF released vascular endothelial growth factor (VEGF) from angiogenic inhibitory complexes. The cleaved HARP N-terminal domain increased HARP-induced cell proliferation, whereas the HARP C-terminal domain was antagonistic and decreased cell proliferation and migration. Hence the unmasking of cytokines, such as VEGF, by metalloproteinase processing of their binding proteins is a new mechanism in the control of cytokine activation and angiogenesis. PMID:17908800

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).

Evaluation of the availability of bound analyte for passive sampling in the presence of mobile binding matrix.

PubMed

Xu, Jianqiao; Huang, Shuyao; Jiang, Ruifen; Cui, Shufen; Luan, Tiangang; Chen, Guosheng; Qiu, Junlang; Cao, Chenyang; Zhu, Fang; Ouyang, Gangfeng

2016-04-21

Elucidating the availability of the bound analytes for the mass transfer through the diffusion boundary layers (DBLs) adjacent to passive samplers is important for understanding the passive sampling kinetics in complex samples, in which the lability factor of the bound analyte in the DBL is an important parameter. In this study, the mathematical expression of lability factor was deduced by assuming a pseudo-steady state during passive sampling, and the equation indicated that the lability factor was equal to the ratio of normalized concentration gradients between the bound and free analytes. Through the introduction of the mathematical expression of lability factor, the modified effective average diffusion coefficient was proven to be more suitable for describing the passive sampling kinetics in the presence of mobile binding matrixes. Thereafter, the lability factors of the bound polycyclic aromatic hydrocarbons (PAHs) with sodium dodecylsulphate (SDS) micelles as the binding matrixes were figured out according to the improved theory. The lability factors were observed to decrease with larger binding ratios and smaller micelle sizes, and were successfully used to predict the mass transfer efficiencies of PAHs through DBLs. This study would promote the understanding of the availability of bound analytes for passive sampling based on the theoretical improvements and experimental assessments. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

Distance descending ordering method: An O(n) algorithm for inverting the mass matrix in simulation of macromolecules with long branches

NASA Astrophysics Data System (ADS)

Xu, Xiankun; Li, Peiwen

2017-11-01

Fixman's work in 1974 and the follow-up studies have developed a method that can factorize the inverse of mass matrix into an arithmetic combination of three sparse matrices-one of them is positive definite and needs to be further factorized by using the Cholesky decomposition or similar methods. When the molecule subjected to study is of serial chain structure, this method can achieve O (n) time complexity. However, for molecules with long branches, Cholesky decomposition about the corresponding positive definite matrix will introduce massive fill-in due to its nonzero structure. Although there are several methods can be used to reduce the number of fill-in, none of them could strictly guarantee for zero fill-in for all molecules according to our test, and thus cannot obtain O (n) time complexity by using these traditional methods. In this paper we present a new method that can guarantee for no fill-in in doing the Cholesky decomposition, which was developed based on the correlations between the mass matrix and the geometrical structure of molecules. As a result, the inverting of mass matrix will remain the O (n) time complexity, no matter the molecule structure has long branches or not.

Hypoxic Regulation of Functional Extracellular Matrix Elaboration by Nucleus Pulposus Cells in Long-Term Agarose Culture

PubMed Central

Gorth, Deborah J; Lothstein, Katherine E; Chiaro, Joseph A; Farrell, Megan J; Dodge, George R; Elliott, Dawn M; Malhotra, Neil R; Mauck, Robert L; Smith, Lachlan J

2015-01-01

Degeneration of the intervertebral discs is strongly implicated as a cause of low back pain. Since current treatments for discogenic low back pain show poor long-term efficacy, a number of new, biological strategies are being pursued. For such therapies to succeed, it is critical that they be validated in conditions that mimic the unique biochemical microenvironment of the nucleus pulposus (NP), which include low oxygen tension. Therefore, the objective of this study was to investigate the effects of oxygen tension on NP cell functional extracellular matrix elaboration in 3D culture. Bovine NP cells were encapsulated in agarose constructs and cultured for 14 or 42 days in either 20% or 2% oxygen in defined media containing transforming growth factor beta-3. At each time point, extracellular matrix composition, biomechanics and mRNA expression of key phenotypic markers were evaluated. Results showed that while bulk mechanics and composition were largely independent of oxygen level, low oxygen promoted improved restoration of the NP phenotype, higher mRNA expression of extracellular matrix and NP specific markers, and more uniform matrix elaboration. These findings indicate that culture under physiological oxygen levels is an important consideration for successful development of cell and growth factor-based regenerative strategies for the disc. PMID:25640328

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).

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Tuning the surface properties of novel ternary iron(III) fluoride-based catalysts using the template effect of the matrix.

PubMed

Guo, Ying; Lippitz, Andreas; Saftien, Paul; Unger, Wolfgang E S; Kemnitz, Erhard

2015-03-21

Sol-gel prepared ternary FeF3-MgF2 materials have become promising heterogeneous catalysts due to their porosity and surface Lewis/Brønsted acidity (bi-acidity). Despite the good catalytic performance, nanoscopic characterisations of this type of material are still missing and the key factors controlling the surface properties have not yet been identified, impeding both a better understanding and further development of ternary fluoride catalysts. In this study, we characterised the interaction between the bi-acidic component (FeF3) and the matrix (MgF2) on the nano-scale. For the first time, the formation pathway of FeF3-MgF2 was profiled and the template effect of MgF2 during the synthesis process was discovered. Based on these new insights two novel materials, FeF3-CaF2 and FeF3-SrF2, were established, revealing that with decreasing the atomic numbers (from Sr to Mg), the ternary fluorides exhibited increasing surface acidity and surface area but decreasing pore size. These systematic changes gave rise to a panel of catalysts with tuneable surface and bulk properties either by changing the matrix alkaline earth metal fluoride or by adjusting their ratios to Fe or both. The template effect of the alkaline earth metal fluoride matrix was identified as the most probable key factor determining the surface properties and further influencing the catalytic performance in ternary fluoride based catalysts, and paves the way to targeted design of next-generation catalysts with tunable properties.

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.

D-MATRIX: A web tool for constructing weight matrix of conserved DNA motifs

PubMed Central

Sen, Naresh; Mishra, Manoj; Khan, Feroz; Meena, Abha; Sharma, Ashok

2009-01-01

Despite considerable efforts to date, DNA motif prediction in whole genome remains a challenge for researchers. Currently the genome wide motif prediction tools required either direct pattern sequence (for single motif) or weight matrix (for multiple motifs). Although there are known motif pattern databases and tools for genome level prediction but no tool for weight matrix construction. Considering this, we developed a D-MATRIX tool which predicts the different types of weight matrix based on user defined aligned motif sequence set and motif width. For retrieval of known motif sequences user can access the commonly used databases such as TFD, RegulonDB, DBTBS, Transfac. D­MATRIX program uses a simple statistical approach for weight matrix construction, which can be converted into different file formats according to user requirement. It provides the possibility to identify the conserved motifs in the co­regulated genes or whole genome. As example, we successfully constructed the weight matrix of LexA transcription factor binding site with the help of known sos­box cis­regulatory elements in Deinococcus radiodurans genome. The algorithm is implemented in C-Sharp and wrapped in ASP.Net to maintain a user friendly web interface. D­MATRIX tool is accessible through the CIMAP domain network. Availability http://203.190.147.116/dmatrix/ PMID:19759861

D-MATRIX: a web tool for constructing weight matrix of conserved DNA motifs.

PubMed

Sen, Naresh; Mishra, Manoj; Khan, Feroz; Meena, Abha; Sharma, Ashok

2009-07-27

Despite considerable efforts to date, DNA motif prediction in whole genome remains a challenge for researchers. Currently the genome wide motif prediction tools required either direct pattern sequence (for single motif) or weight matrix (for multiple motifs). Although there are known motif pattern databases and tools for genome level prediction but no tool for weight matrix construction. Considering this, we developed a D-MATRIX tool which predicts the different types of weight matrix based on user defined aligned motif sequence set and motif width. For retrieval of known motif sequences user can access the commonly used databases such as TFD, RegulonDB, DBTBS, Transfac. D-MATRIX program uses a simple statistical approach for weight matrix construction, which can be converted into different file formats according to user requirement. It provides the possibility to identify the conserved motifs in the co-regulated genes or whole genome. As example, we successfully constructed the weight matrix of LexA transcription factor binding site with the help of known sos-box cis-regulatory elements in Deinococcus radiodurans genome. The algorithm is implemented in C-Sharp and wrapped in ASP.Net to maintain a user friendly web interface. D-MATRIX tool is accessible through the CIMAP domain network. http://203.190.147.116/dmatrix/

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.

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

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.

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.

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.

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.

Identification of thermodynamically stable ceramic reinforcement materials for iron aluminide matrices

NASA Technical Reports Server (NTRS)

Misra, Ajay K.

1990-01-01

Aluminide-base intermetallic matrix composites are currently being considered as potential high-temperature materials. One of the key factors in the selection of a reinforcement material is its chemical stability in the matrix. In this study, chemical interactions between iron aluminides and several potential reinforcement materials, which include carbides, oxides, borides, and nitrides, are analyzed from thermodynamic considerations. Several chemically compatible reinforcement materials are identified for the iron aluminides with Al concentrations ranging from 40 to 50 at. pct.

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.

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

PubMed

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

2017-08-01

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

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

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.

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).

Cell and matrix modulation in prenatal and postnatal equine growth cartilage, zones of Ranvier and articular cartilage

PubMed Central

Löfgren, Maria; Ekman, Stina; Svala, Emilia; Lindahl, Anders; Ley, Cecilia; Skiöldebrand, Eva

2014-01-01

Formation of synovial joints includes phenotypic changes of the chondrocytes and the organisation of their extracellular matrix is regulated by different factors and signalling pathways. Increased knowledge of the normal processes involved in joint development may be used to identify similar regulatory mechanisms during pathological conditions in the joint. Samples of the distal radius were collected from prenatal and postnatal equine growth plates, zones of Ranvier and articular cartilage with the aim of identifying Notch signalling components and cells with stem cell-like characteristics and to follow changes in matrix protein localisation during joint development. The localisation of the Notch signalling components Notch1, Delta4, Hes1, Notch dysregulating protein epidermal growth factor-like domain 7 (EGFL7), the stem cell-indicating factor Stro-1 and the matrix molecules cartilage oligomeric matrix protein (COMP), fibromodulin, matrilin-1 and chondroadherin were studied using immunohistochemistry. Spatial changes in protein localisations during cartilage maturation were observed for Notch signalling components and matrix molecules, with increased pericellular localisation indicating new synthesis and involvement of these proteins in the formation of the joint. However, it was not possible to characterise the phenotype of the chondrocytes based on their surrounding matrix during normal chondrogenesis. The zone of Ranvier was identified in all horses and characterised as an area expressing Stro-1, EGFL7 and chondroadherin with an absence of COMP and Notch signalling. Stro-1 was also present in cells close to the perichondrium, in the articular cartilage and in the fetal resting zone, indicating stem cell-like characteristics of these cells. The presence of stem cells in the articular cartilage will be of importance for the repair of damaged cartilage. Perivascular chondrocytes and hypertrophic cells of the cartilage bone interface displayed positive staining for EGFL7, which is a novel finding and suggests a role of EGFL7 in the vascular infiltration of growth cartilage. PMID:25175365

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.

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.

Human mesenchymal stem cells cultured on silk hydrogels with variable stiffness and growth factor differentiate into mature smooth muscle cell phenotype.

PubMed

Floren, Michael; Bonani, Walter; Dharmarajan, Anirudh; Motta, Antonella; Migliaresi, Claudio; Tan, Wei

2016-02-01

Cell-matrix and cell-biomolecule interactions play critical roles in a diversity of biological events including cell adhesion, growth, differentiation, and apoptosis. Evidence suggests that a concise crosstalk of these environmental factors may be required to direct stem cell differentiation toward matured cell type and function. However, the culmination of these complex interactions to direct stem cells into highly specific phenotypes in vitro is still widely unknown, particularly in the context of implantable biomaterials. In this study, we utilized tunable hydrogels based on a simple high pressure CO2 method and silk fibroin (SF) the structural protein of Bombyx mori silk fibers. Modification of SF protein starting water solution concentration results in hydrogels of variable stiffness while retaining key structural parameters such as matrix pore size and β-sheet crystallinity. To further resolve the complex crosstalk of chemical signals with matrix properties, we chose to investigate the role of 3D hydrogel stiffness and transforming growth factor (TGF-β1), with the aim of correlating the effects on the vascular commitment of human mesenchymal stem cells. Our data revealed the potential to upregulate matured vascular smooth muscle cell phenotype (myosin heavy chain expression) of hMSCs by employing appropriate matrix stiffness and growth factor (within 72h). Overall, our observations suggest that chemical and physical stimuli within the cellular microenvironment are tightly coupled systems involved in the fate decisions of hMSCs. The production of tunable scaffold materials that are biocompatible and further specialized to mimic tissue-specific niche environments will be of considerable value to future tissue engineering platforms. This article investigates the role of silk fibroin hydrogel stiffness and transforming growth factor (TGF-β1), with the aim of correlating the effects on the vascular commitment of human mesenchymal stem cells. Specifically, we demonstrate the upregulation of mature vascular smooth muscle cell phenotype (myosin heavy chain expression) of hMSCs by employing appropriate matrix stiffness and growth factor (within 72h). Moreover, we demonstrate the potential to direct specialized hMSC differentiation by modulating stiffness and growth factor using silk fibroin, a well-tolerated and -defined biomaterial with an impressive portfolio of tissue engineering applications. Altogether, our study reinforce the fact that complex differentiation protocols may be simplified by engineering the cellular microenvironment on multiple scales, i.e. matrix stiffness with growth factor. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

A Fine-Grained Pipelined Implementation for Large-Scale Matrix Inversion on FPGA

NASA Astrophysics Data System (ADS)

Zhou, Jie; Dou, Yong; Zhao, Jianxun; Xia, Fei; Lei, Yuanwu; Tang, Yuxing

Large-scale matrix inversion play an important role in many applications. However to the best of our knowledge, there is no FPGA-based implementation. In this paper, we explore the possibility of accelerating large-scale matrix inversion on FPGA. To exploit the computational potential of FPGA, we introduce a fine-grained parallel algorithm for matrix inversion. A scalable linear array processing elements (PEs), which is the core component of the FPGA accelerator, is proposed to implement this algorithm. A total of 12 PEs can be integrated into an Altera StratixII EP2S130F1020C5 FPGA on our self-designed board. Experimental results show that a factor of 2.6 speedup and the maximum power-performance of 41 can be achieved compare to Pentium Dual CPU with double SSE threads.

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.

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…

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

ERIC Educational Resources Information Center

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

2013-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Using Chebyshev polynomials and approximate inverse triangular factorizations for preconditioning the conjugate gradient method

NASA Astrophysics Data System (ADS)

Kaporin, I. E.

2012-02-01

In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.

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.

Study of extraterrestrial disposal of radioactive wastes. Part 2: Preliminary feasibility screening study of extraterrestrial disposal of radioactive wastes in concentrations, matrix materials, and containers designed for storage on earth

NASA Technical Reports Server (NTRS)

Hyland, R. E.; Wohl, M. L.; Thompson, R. L.; Finnegan, P. M.

1972-01-01

The results are reported of a preliminary feasibility screening study for providing long-term solutions to the problems of handling and managing radioactive wastes by extraterrestrial transportation of the wastes. Matrix materials and containers are discussed along with payloads, costs, and destinations for candidate space vehicles. The conclusions reached are: (1) Matrix material such as spray melt can be used without exceeding temperature limits of the matrix. (2) The cost in mills per kw hr electric, of space disposal of fission products is 4, 5, and 28 mills per kw hr for earth escape, solar orbit, and solar escape, respectively. (3) A major factor effecting cost is the earth storage time. Based on a normal operating condition design for solar escape, a storage time of more than sixty years is required to make the space disposal charge less than 10% of the bus-bar electric cost. (4) Based on a 10 year earth storage without further processing, the number of shuttle launches required would exceed one per day.

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

PubMed

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

2017-01-01

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

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)

Chrestenson transform FPGA embedded factorizations.

PubMed

Corinthios, Michael J

2016-01-01

Chrestenson generalized Walsh transform factorizations for parallel processing imbedded implementations on field programmable gate arrays are presented. This general base transform, sometimes referred to as the Discrete Chrestenson transform, has received special attention in recent years. In fact, the Discrete Fourier transform and Walsh-Hadamard transform are but special cases of the Chrestenson generalized Walsh transform. Rotations of a base-p hypercube, where p is an arbitrary integer, are shown to produce dynamic contention-free memory allocation, in processor architecture. The approach is illustrated by factorizations involving the processing of matrices of the transform which are function of four variables. Parallel operations are implemented matrix multiplications. Each matrix, of dimension N × N, where N = p (n) , n integer, has a structure that depends on a variable parameter k that denotes the iteration number in the factorization process. The level of parallelism, in the form of M = p (m) processors can be chosen arbitrarily by varying m between zero to its maximum value of n - 1. The result is an equation describing the generalised parallelism factorization as a function of the four variables n, p, k and m. Applications of the approach are shown in relation to configuring field programmable gate arrays for digital signal processing applications.

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

PubMed

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

2018-06-01

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

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

PubMed

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

2011-12-01

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

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 ...

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.

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

PubMed Central

Gray, Dean; LeVanseler, Kerri; Pan, Meide

2008-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Improving stochastic estimates with inference methods: calculating matrix diagonals.

PubMed

Selig, Marco; Oppermann, Niels; Ensslin, Torsten A

2012-02-01

Estimating the diagonal entries of a matrix, that is not directly accessible but only available as a linear operator in the form of a computer routine, is a common necessity in many computational applications, especially in image reconstruction and statistical inference. Here, methods of statistical inference are used to improve the accuracy or the computational costs of matrix probing methods to estimate matrix diagonals. In particular, the generalized Wiener filter methodology, as developed within information field theory, is shown to significantly improve estimates based on only a few sampling probes, in cases in which some form of continuity of the solution can be assumed. The strength, length scale, and precise functional form of the exploited autocorrelation function of the matrix diagonal is determined from the probes themselves. The developed algorithm is successfully applied to mock and real world problems. These performance tests show that, in situations where a matrix diagonal has to be calculated from only a small number of computationally expensive probes, a speedup by a factor of 2 to 10 is possible with the proposed method. © 2012 American Physical Society

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

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.

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

PubMed

Tsuchiyama, Tomoyuki; Katsuhara, Miki; Nakajima, Masahiro

2017-11-17

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

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

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

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

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

PubMed

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

2014-06-01

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

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

PubMed Central

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

2015-01-01

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

A self-recalibration method based on scale-invariant registration for structured light measurement systems

NASA Astrophysics Data System (ADS)

Chen, Rui; Xu, Jing; Zhang, Song; Chen, Heping; Guan, Yong; Chen, Ken

2017-01-01

The accuracy of structured light measurement depends on delicate offline calibration. However, in some practical applications, the system is supposed to be reconfigured so frequently to track the target that an online calibration is required. To this end, this paper proposes a rapid and autonomous self-recalibration method. For the proposed method, first, the rotation matrix and the normalized translation vector are attained from the fundamental matrix; second, the scale factor is acquired based on scale-invariant registration such that the actual translation vector is obtained. Experiments have been conducted to verify the effectiveness of our proposed method and the results indicate a high degree of accuracy.

Generalized sub-Schawlow-Townes laser linewidths via material dispersion

NASA Astrophysics Data System (ADS)

Pillay, Jason Cornelius; Natsume, Yuki; Stone, A. Douglas; Chong, Y. D.

2014-03-01

A recent S-matrix-based theory of the quantum-limited linewidth, which is applicable to general lasers, including spatially nonuniform laser cavities operating above threshold, is analyzed in various limits. For broadband gain, a simple interpretation of the Petermann and bad-cavity factors is presented in terms of geometric relations between the zeros and poles of the S matrix. When there is substantial dispersion, on the frequency scale of the cavity lifetime, the theory yields a generalization of the bad-cavity factor, which was previously derived for spatially uniform one-dimensional lasers. This effect can lead to sub-Schawlow-Townes linewidths in lasers with very narrow gain widths. We derive a formula for the linewidth in terms of the lasing mode functions, which has accuracy comparable to the previous formula involving the residue of the lasing pole. These results for the quantum-limited linewidth are valid even in the regime of strong line pulling and spatial hole burning, where the linewidth cannot be factorized into independent Petermann and bad-cavity factors.

Addressing matrix effects in ligand-binding assays through the use of new reagents and technology.

PubMed

Chilewski, Shannon D; Mora, Johanna R; Gleason, Carol; DeSilva, Binodh

2014-04-01

Ligand-binding assays (LBAs) used in the quantification of biotherapeutics for pharmacokinetic determinations rely on interactions between reagents (antibodies or target molecule) and the biotherapeutic. Most LBAs do not employ an analyte extraction procedure and are susceptible to matrix interference. Here, we present a case study on the development of a LBA for the quantification of a PEGylated domain antibody where matrix interference was observed. The assay used to support the single ascending dose study was a plate-based electrochemiluminescent assay with a lower limit of quantification of 80 ng/mL. To meet sensitivity requirements of future studies, new reagents and the Gyrolab™ Workstation were evaluated. Assay sensitivity improved nearly threefold in the final method utilizing new antibody reagents, a buffer containing blockers to human anti-animal antibodies, and the Gyrolab Workstation. Experimental data indicate that all factors changed played a role in overcoming matrix effects.

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

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

NASA Astrophysics Data System (ADS)

Bi, Xiaoqing; Luo, Yanbing

2017-03-01

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

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.

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.

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.

Age-related decline in the matrix contents and functional properties of human periodontal ligament stem cell sheets.

PubMed

Wu, Rui-Xin; Bi, Chun-Sheng; Yu, Yang; Zhang, Lin-Lin; Chen, Fa-Ming

2015-08-01

In this study, periodontal ligament (PDL) stem cells (PDLSCs) derived from different-aged donors were used to evaluate the effect of aging on cell sheet formation. The activity of PDLSCs was first determined based on their colony-forming ability, surface markers, proliferative/differentiative potentials, senescence-associated β-galactosidase (SA-βG) staining, and expression of pluripotency-associated transcription factors. The ability of these cells to form sheets, based on their extracellular matrix (ECM) contents and their functional properties necessary for osteogenic differentiation, was evaluated to predict the age-related changes in the regenerative capacity of the cell sheets in their further application. It was found that human PDLSCs could be isolated from the PDL tissue of different-aged subjects. However, the ability of the PDLSCs to proliferate and to undergo osteogenic differentiation and their expression of pluripotency-associated transcription factors displayed age-related decreases. In addition, these cells exhibited an age-related increase in SA-βG expression. Aged cells showed an impaired ability to form functional cell sheets, as determined by morphological observations and Ki-67 immunohistochemistry staining. Based on the production of ECM proteins, such as fibronectin, integrin β1, and collagen type I; alkaline phosphatase (ALP) activity; and the expression of osteogenic genes, such as ALP, Runt-related transcription factor 2, and osteocalcin, cell sheets formed by PDLSCs derived from older donors demonstrated a less potent osteogenic capacity compared to those formed by PDLSCs from younger donors. Our data suggest that the age-associated decline in the matrix contents and osteogenic properties of PDLSC sheets should be taken into account in cell sheet engineering research and clinical periodontal regenerative therapy. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

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

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

PubMed

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

2014-08-01

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

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.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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...

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.

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

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

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.

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

Muscle-tendon units localization and activation level analysis based on high-density surface EMG array and NMF algorithm

NASA Astrophysics Data System (ADS)

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

2016-12-01

Objective. Some skeletal muscles can be subdivided into smaller segments called muscle-tendon units (MTUs). The purpose of this paper is to propose a framework to locate the active region of the corresponding MTUs within a single skeletal muscle and to analyze the activation level varieties of different MTUs during a dynamic motion task. Approach. Biceps brachii and gastrocnemius were selected as targeted muscles and three dynamic motion tasks were designed and studied. Eight healthy male subjects participated in the data collection experiments, and 128-channel surface electromyographic (sEMG) signals were collected with a high-density sEMG electrode grid (a grid consists of 8 rows and 16 columns). Then the sEMG envelopes matrix was factorized into a matrix of weighting vectors and a matrix of time-varying coefficients by nonnegative matrix factorization algorithm. Main results. The experimental results demonstrated that the weightings vectors, which represent invariant pattern of muscle activity across all channels, could be used to estimate the location of MTUs and the time-varying coefficients could be used to depict the variation of MTUs activation level during dynamic motion task. Significance. The proposed method provides one way to analyze in-depth the functional state of MTUs during dynamic tasks and thus can be employed on multiple noteworthy sEMG-based applications such as muscle force estimation, muscle fatigue research and the control of myoelectric prostheses. This work was supported by the National Nature Science Foundation of China under Grant 61431017 and 61271138.

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.

Effect of TiC addition on fracture toughness of Al6061 alloy

NASA Astrophysics Data System (ADS)

Raviraj, M. S.; Sharanprabhu, C. M.; Mohankumar, G. C.

2018-04-01

Al 6061 matrix was reinforced with different proportions of TiC particles such as 3wt%, 5wt% and 7wt% and the effect on fracture toughness was studied. Al-TiC metal matrix composites were produced by stir casting method to ensure uniform distribution of the TiC particulates in the Al matrix. LEFM (Linear Elastic Fracture Mechanics) has been used to characterize the fracture toughness using various specimen geometries. The compact tension (CT) specimens with straight through notch were machined as per ASTM E399 specifications. All the specimens were machined to have constant a/W=0.5 and B/W was varied from 0.2 to 0.7. A sharp crack initiation was done at the end of notch by fatigue loading using servo-hydraulic controlled testing machine. Load v/s crack mouth opening displacement (CMOD) data was plotted and stress intensity factor, KQ determined. Critical stress intensity factor KIC was obtained by plotting KQ v/s thickness of specimen data. The fracture toughness of the composites varied between 16-19 MPa√m as compared to 23MPa√m for base alloy Al6061. Composites with 3wt% and 7wt% TiC showed better fracture toughness than 5wt% TiC reinforced Al metal matrix composites.

Development of a cellularly degradable PEG hydrogel to promote articular cartilage extracellular matrix deposition.

PubMed

Sridhar, Balaji V; Brock, John L; Silver, Jason S; Leight, Jennifer L; Randolph, Mark A; Anseth, Kristi S

2015-04-02

Healing articular cartilage remains a significant clinical challenge because of its limited self-healing capacity. While delivery of autologous chondrocytes to cartilage defects has received growing interest, combining cell-based therapies with scaffolds that capture aspects of native tissue and promote cell-mediated remodeling could improve outcomes. Currently, scaffold-based therapies with encapsulated chondrocytes permit matrix production; however, resorption of the scaffold does not match the rate of production by cells leading to generally low extracellular matrix outputs. Here, a poly (ethylene glycol) (PEG) norbornene hydrogel is functionalized with thiolated transforming growth factor (TGF-β1) and cross-linked by an MMP-degradable peptide. Chondrocytes are co-encapsulated with a smaller population of mesenchymal stem cells, with the goal of stimulating matrix production and increasing bulk mechanical properties of the scaffold. The co-encapsulated cells cleave the MMP-degradable target sequence more readily than either cell population alone. Relative to non-degradable gels, cellularly degraded materials show significantly increased glycosaminoglycan and collagen deposition over just 14 d of culture, while maintaining high levels of viability and producing a more widely-distributed matrix. These results indicate the potential of an enzymatically degradable, peptide-functionalized PEG hydrogel to locally influence and promote cartilage matrix production over a short period. Scaffolds that permit cell-mediated remodeling may be useful in designing treatment options for cartilage tissue engineering applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effect of transforming growth factor-beta and growth differentiation factor-5 on proliferation and matrix production by human bone marrow stromal cells cultured on braided poly lactic-co-glycolic acid scaffolds for ligament tissue engineering.

PubMed

Jenner, J M G Th; van Eijk, F; Saris, D B F; Willems, W J; Dhert, W J A; Creemers, Laura B

2007-07-01

Tissue engineering of ligaments based on biomechanically suitable biomaterials combined with autologous cells may provide a solution for the drawbacks associated with conventional graft material. The aim of the present study was to investigate the contribution of recombinant human transforming growth factor beta 1 (rhTGF-beta1) and growth differentiation factor (GDF)-5, known for their role in connective tissue regeneration, to proliferation and matrix production by human bone marrow stromal cells (BMSCs) cultured onto woven, bioabsorbable, 3-dimensional (3D) poly(lactic-co-glycolic acid) scaffolds. Cells were cultured for 12 days in the presence or absence of these growth factors at different concentrations. Human BMSCs attached to the suture material, proliferated, and synthesized extracellular matrix rich in collagen type I and collagen III. No differentiation was demonstrated toward cartilage or bone tissue. The addition of rhTGF-beta1 (1-10 ng/mL) and GDF-5 (10-100 ng/mL) increased cell content (p < 0.05), but only TGF-beta1 also increased total collagen production (p < 0.05) and collagen production per cell, which is a parameter indicating differentiation. In conclusion, stimulation with rhTGF-beta1, and to a lesser extent with GDF-5, can modulate human BMSCs toward collagenous soft tissue when applied to a 3D hybrid construct. The use of growth factors could play an important role in the improvement of ligament tissue engineering.

Kinetics and mechanism of release from glyceryl monostearate-based implants: evaluation of release in a gel simulating in vivo implantation.

PubMed

Allababidi, S; Shah, J C

1998-06-01

The overall objective of the study was to design an implantable delivery system based on glyceryl monostearate (GMS) for the site-specific delivery of antibiotics for the prevention of surgical wound infection. To design the implant, a release method had to be developed that simulate the in vivo implantation conditions to be able to predict the release characteristics from the implants when they are actually used in vivo. Also, identifying the release kinetics and mechanism and evaluating the factors that influence the release of drugs from the GMS-based matrix were necessary to allow further design of implants that could yield a desired release rate. The release of cefazolin was monitored from GMS matrixes implanted into agar gel, simulating subcutaneous tissues with respect to viscosity and water content. The gel method resulted in observation of spatial and temporal concentration profiles in the immediate vicinity of the implants, indicating the benefits of local drug delivery; however, there was no significant difference between the cumulative release profiles by the gel method or the vial release method. The release of cefazolin from the GMS-based matrix with the vial method followed Higuchi's square root of time kinetics. The release rate was found to be directly proportional to cefazolin load (A) and the surface area (SA) of the matrix as expressed by the following equation: = 0.24ASA. On the basis of this equation, one can design a variety of GMS matrixes that would result in a desired release rate or release duration. This also indicated that cefazolin release followed the release kinetics of a freely soluble drug from an insoluble matrix and hence it is a diffusion-controlled process. The effect of drug solubility on the release kinetics was determined by comparing the release kinetics of the poorly water soluble ciprofloxacin (0.16 mg/mL) to that of the highly water soluble cefazolin (325 mg/mL). The release duration of ciprofloxacin (80 h) was longer than that of cefazolin (25 h) from identical GMS matrixes. Although ciprofloxacin release was initially controlled by the matrix, agitation accelerated disintegration of the matrix and release due to its poor solubility, and ciprofloxacin release appeared to be a dissolution-controlled process following zero-order release kinetics.

Quantitative experimental determination of the solid solution hardening potential of rhenium, tungsten and molybdenum in single-crystal nickel-based superalloys

DOE PAGES

Fleischmann, Ernst; Miller, Michael K.; Affeldt, Ernst; ...

2015-01-31

Here, the solid-solution hardening potential of the refractory elements rhenium, tungsten and molybdenum in the matrix of single-crystal nickel-based superalloys was experimentally quantified. Single-phase alloys with the composition of the nickel solid-solution matrix of superalloys were cast as single crystals, and tested in creep at 980 °C and 30–75 MPa. The use of single-phase single-crystalline material ensures very clean data because no grain boundary or particle strengthening effects interfere with the solid-solution hardening. This makes it possible to quantify the amount of rhenium, tungsten and molybdenum necessary to reduce the creep rate by a factor of 10. Rhenium is moremore » than two times more effective for matrix strengthening than either tungsten or molybdenum. The existence of rhenium clusters as a possible reason for the strong strengthening effect is excluded as a result of atom probe tomography measurements. If the partitioning coefficient of rhenium, tungsten and molybdenum between the γ matrix and the γ' precipitates is taken into account, the effectiveness of the alloying elements in two-phase superalloys can be calculated and the rhenium effect can be explained.« less

Potential use of gallium-doped phosphate-based glass material for periodontitis treatment.

PubMed

Sahdev, Rohan; Ansari, Tahera I; Higham, Susan M; Valappil, Sabeel P

2015-07-01

This study aimed at evaluating the potential effect of gallium-incorporated phosphate-based glasses towards periodontitis-associated bacteria, Porphyromonas gingivalis, and matrix metalloproteinase-13. Periodontitis describes a group of inflammatory diseases of the gingiva and supporting structures of the periodontium. They are initiated by the accumulation of plaque bacteria, such as the putative periodontal pathogen Porphyromonas gingivalis, but the host immune response such as elevated matrix metalloproteinases are the major contributing factor for destruction of periodontal tissues. Antibacterial assays of gallium-incorporated phosphate-based glasses were conducted on Porphyromonas gingivalis ATCC 33277 using disc diffusion assay on fastidious anaerobe agar and liquid broth assay in a modified tryptic soy broth. In vitro study investigated the effect of gallium on purified recombinant human matrix metalloproteinase-13 activity using matrix metalloproteinase assay kit. In vivo biocompatibility of gallium-incorporated phosphate-based glass was evaluated in rats as subcutaneous implants. Antibacterial assay of gallium displayed activity against Porphyromonas gingivalis (inhibition zone of 22 ± 0.5 mm compared with 0 mm for control glass, c-PBG). Gallium in the glass contributed to growth inhibitory effect on Porphyromonas gingivalis (up to 1.30 reductions in log 10 values of the viable counts compared with control) in a modified tryptic soy broth. In vitro study showed gallium-incorporated phosphate-based glasses inhibited matrix metalloproteinase activity significantly (p ≤ 0.01) compared with c-PBG. Evaluation of in vivo biocompatibility of gallium-incorporated phosphate-based glasses in rats showed a non-toxic and foreign body response after 2 weeks of implantation. The results indicate that gallium ions might act on multiple targets of biological mechanisms underlying periodontal disease. Moreover, gallium-incorporated phosphate-based glasses are biocompatible in a rat model. The findings warrant further investigation and will have important clinical implications in the future treatment and management of periodontitis. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Improved Mechanical and Tribological Properties of Metal-Matrix Composites Dispersion-Strengthened by Nanoparticles 

PubMed Central

Levashov, Evgenii; Kurbatkina, Victoria; Alexandr, Zaytsev

2009-01-01

Co- and Fe-based alloys produced by powder technology are being widely used as a matrix for diamond-containing composites in cutting, drilling, grinding pplications, etc. The severe service conditions demand that the mechanical and tribological properties of these alloys be improved. Development of metal-matrix composites (MMCs) and alloys reinforced with nanoparticles is a promising way to resolve this problem. In this work, we have investigated the effect of nano-sized WC, ZrO2, Al2O3, and Si3N4 additives on the properties of sintered dispersion-strengthened Co- and Fe-based MMCs. The results show an increase in the hardness (up to 10 HRB), bending strength (up to 50%), wear resistance (by a factor of 2–10) and a decrease in the friction coefficient (up to 4-fold) of the dispersion-strengthened materials. The use of designed alloys as a binder of cutting diamond tools gave a 4-fold increment in the service life, without reduction in their cutting speed.

Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

PubMed

Xie, M; Barsanti, K C; Hannigan, M P; Dutton, S J; Vedal, S

2013-01-01

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources ( n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series ( r = 0.92-0.98) with their corresponding factors ( n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated ( r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (≥ 10 °C and ≤ 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations ( r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations.

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

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

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

2014-08-15

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

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.

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

PubMed

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

2018-04-15

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

Bendable Electro-Acoustic Transducer Fabricated Utilizing Frequency Dispersion of Elastic Modulus

NASA Astrophysics Data System (ADS)

Miyoshi, Tetsu; Ohga, Juro

2013-09-01

To realize the speaker diaphragm that can be united with a flexible display without deteriorating lightweight properties and flexibility, a novel bendable electro-acoustic transducer (BEAT) based on 0-3-type piezoelectric composites has been developed. To overcome the trade-off between flexibility and the transmission efficiency of vibration energy, a viscoelastic polymer that has local maximum points in the loss factor as well as large frequency dispersion in the storage modulus near room temperature was employed as the matrix of the piezoelectric composite layer. Against the comparatively slow (10 Hz or less) deformation from the outside, the viscoelastic matrix is viscous enough to prevent cracking and delamination. On the other hand, in the audible range (20 Hz to 20 kHz), the matrix is elastic enough to transmit piezoelectric vibration energy, maintaining a moderately large loss factor as well as a high sound velocity. For the first time, we successfully demonstrated a rollable speaker that can continue to generate a high-quality sound while being rolled and unrolled repeatedly onto a cylinder with a curvature radius of 4 mm.

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

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

Kim, Kyungjoo; Rajamanickam, Sivasankaran; Stelle, George Widgery

We introduce a task-parallel algorithm for sparse incomplete Cholesky factorization that utilizes a 2D sparse partitioned-block layout of a matrix. Our factorization algorithm follows the idea of algorithms-by-blocks by using the block layout. The algorithm-byblocks approach induces a task graph for the factorization. These tasks are inter-related to each other through their data dependences in the factorization algorithm. To process the tasks on various manycore architectures in a portable manner, we also present a portable tasking API that incorporates different tasking backends and device-specific features using an open-source framework for manycore platforms i.e., Kokkos. A performance evaluation is presented onmore » both Intel Sandybridge and Xeon Phi platforms for matrices from the University of Florida sparse matrix collection to illustrate merits of the proposed task-based factorization. Experimental results demonstrate that our task-parallel implementation delivers about 26.6x speedup (geometric mean) over single-threaded incomplete Choleskyby- blocks and 19.2x speedup over serial Cholesky performance which does not carry tasking overhead using 56 threads on the Intel Xeon Phi processor for sparse matrices arising from various application problems.« less

Structure and function of the interphotoreceptor matrix surrounding retinal photoreceptor cells.

PubMed

Ishikawa, Makoto; Sawada, Yu; Yoshitomi, Takeshi

2015-04-01

The interphotoreceptor matrix (IPM) is a highly organized structure with interconnected domains surrounding cone and rod photoreceptor cells and extends throughout the subretinal space. Based on known roles of the extracellular matrix in other tissues, the IPM is thought to have several prominent functions including serving as a receptor for growth factors, regulating retinoid transport, participating in cytoskeletal organization in surrounding cells, and regulation of oxygen and nutrient transport. In addition, a number of studies suggest that the IPM also may play a significant role in the etiology of retinal degenerative disorders. In this review, we describe the present knowledge concerning the structure and function of the IPM under physiological and pathological conditions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Estimation of geopotential from satellite-to-satellite range rate data: Numerical results

NASA Technical Reports Server (NTRS)

Thobe, Glenn E.; Bose, Sam C.

1987-01-01

A technique for high-resolution geopotential field estimation by recovering the harmonic coefficients from satellite-to-satellite range rate data is presented and tested against both a controlled analytical simulation of a one-day satellite mission (maximum degree and order 8) and then against a Cowell method simulation of a 32-day mission (maximum degree and order 180). Innovations include: (1) a new frequency-domain observation equation based on kinetic energy perturbations which avoids much of the complication of the usual Keplerian element perturbation approaches; (2) a new method for computing the normalized inclination functions which unlike previous methods is both efficient and numerically stable even for large harmonic degrees and orders; (3) the application of a mass storage FFT to the entire mission range rate history; (4) the exploitation of newly discovered symmetries in the block diagonal observation matrix which reduce each block to the product of (a) a real diagonal matrix factor, (b) a real trapezoidal factor with half the number of rows as before, and (c) a complex diagonal factor; (5) a block-by-block least-squares solution of the observation equation by means of a custom-designed Givens orthogonal rotation method which is both numerically stable and tailored to the trapezoidal matrix structure for fast execution.

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.

Silicone Polymer Composites for Thermal Protection System: Fiber Reinforcements and Microstructures

DTIC Science & Technology

2010-01-01

angles were tested. Detailed microstructural, mass loss, and peak erosion analyses were conducted on the phenolic -based matrix composite (control) and...silicone-based matrix composites to understand their protective mechanisms. Keywords silicone polymer matrix composites, phenolic polymer matrix...erosion analyses were conducted on the phenolic -based matrix composite (control) and silicone-based matrix composites to understand their protective

A Bonner Sphere Spectrometer based on a large 6LiI(Eu) scintillator: Calibration in reference monoenergetic fields

NASA Astrophysics Data System (ADS)

Bedogni, R.; Pola, A.; Costa, M.; Monti, V.; Thomas, D. J.

2018-07-01

A Bonner Sphere spectrometer employing a large, 11 mm diameter × 3 mm thickness, 6LiI(Eu) scintillator (LL-BSS), was assembled. The purpose was to produce a BSS similar in sensitivity to those based on 3He sensors, but using alternative sensors. With respect to the traditional BSS based on the 4 mm (diameter) × 4 mm (height) 6LiI(Eu), this new BSS is a factor of 3 more sensitive. LL-BSS response matrix, determined with MCNPX, was experimentally evaluated with monoenergetic reference neutron fields of 144 keV, 565 keV and 1.2 MeV available at NPL (Teddington, UK). The results of the experiment confirmed the correctness of the response matrix within an overall uncertainty lower than ±2%.

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

PubMed

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

2015-03-01

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

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

Martino, Mikaël M.; Briquez, Priscilla S.; Maruyama, Kenta

Growth factors are very promising molecules to enhance bone regeneration. However, their translation to clinical use has been seriously limited, facing issues related to safety and cost-effectiveness. These problems derive from the vastly supra-physiological doses of growth factor used without optimized delivery systems. Therefore, these issues have motivated the development of new delivery systems allowing better control of the spatio-temporal release and signaling of growth factors. Because the extracellular matrix (ECM) naturally plays a fundamental role in coordinating growth factor activity in vivo, a number of novel delivery systems have been inspired by the growth factor regulatory function of themore » ECM. After introducing the role of growth factors during the bone regeneration process, this review exposes different issues that growth factor-based therapies have encountered in the clinic and highlights recent delivery approaches based on the natural interaction between growth factor and the ECM.« less

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.

Numerical simulation on semi-solid die-casting of magnesium matrix composite based on orthogonal experiment

NASA Astrophysics Data System (ADS)

Liu, Huihui; He, Xiongwei; Guo, Peng

2017-04-01

Three factors (pouring temperature, injection speed and mold temperature) were selected to do three levels L9 (33)orthogonal experiment, then simulate processing of semi-solid die-casting of magnesium matrix composite by Flow-3D software. The stress distribution, temperature field and defect distribution of filling process were analyzed to find the optimized processing parameter with the help of orthogonal experiment. The results showed that semi-solid has some advantages of well-proportioned stress and temperature field, less defect concentrated in the surface. The results of simulation were the same as the experimental results.

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

NASA Technical Reports Server (NTRS)

Miles, J. H.

1981-01-01

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

The High School & Beyond Data Set: Academic Self-Concept Measures.

ERIC Educational Resources Information Center

Strein, William

A series of confirmatory factor analyses using both LISREL VI (maximum likelihood method) and LISCOMP (weighted least squares method using covariance matrix based on polychoric correlations) and including cross-validation on independent samples were applied to items from the High School and Beyond data set to explore the measurement…

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.

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.

The Bioactivity of Cartilage Extracellular Matrix in Articular Cartilage Regeneration

PubMed Central

Sutherland, Amanda J.; Converse, Gabriel L.; Hopkins, Richard A.; Detamore, Michael S.

2014-01-01

Cartilage matrix is a particularly promising acellular material for cartilage regeneration given the evidence supporting its chondroinductive character. The ‘raw materials’ of cartilage matrix can serve as building blocks and signals for enhanced tissue regeneration. These matrices can be created by chemical or physical methods: physical methods disrupt cellular membranes and nuclei but may not fully remove all cell components and DNA, whereas chemical methods when combined with physical methods are particularly effective in fully decellularizing such materials. Critical endpoints include no detectable residual DNA or immunogenic antigens. It is important to first delineate between the sources of the cartilage matrix, i.e., derived from matrix produced by cells in vitro or from native tissue, and then to further characterize the cartilage matrix based on the processing method, i.e., decellularization or devitalization. With these distinctions, four types of cartilage matrices exist: decellularized native cartilage (DCC), devitalized native cartilage (DVC), decellularized cell derived matrix (DCCM), and devitalized cell derived matrix (DVCM). Delivery of cartilage matrix may be a straightforward approach without the need for additional cells or growth factors. Without additional biological additives, cartilage matrix may be attractive from a regulatory and commercialization standpoint. Source and delivery method are important considerations for clinical translation. Only one currently marketed cartilage matrix medical device is decellularized, although trends in filed patents suggest additional decellularized products may be available in the future. To choose the most relevant source and processing for cartilage matrix, qualifying testing needs to include targeting the desired application, optimizing delivery of the material, identify relevant FDA regulations, assess availability of raw materials, and immunogenic properties of the product. PMID:25044502

Positive Matrix Factorization Model for environmental data analyses

EPA Pesticide Factsheets

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

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

ERIC Educational Resources Information Center

Ten Berge, Jos M. F.

1972-01-01

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

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

NASA Astrophysics Data System (ADS)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

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

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

Magneto-photonic crystal microcavities based on magnetic nanoparticles embedded in Silica matrix

NASA Astrophysics Data System (ADS)

Hocini, Abdesselam; Moukhtari, Riad; Khedrouche, Djamel; Kahlouche, Ahmed; Zamani, Mehdi

2017-02-01

Using the three-dimensional finite difference time domain method (3D FDTD) with perfectly matched layers (PML), optical and magneto-optical properties of two-dimensional magneto-photonic crystals micro-cavity is studied. This micro-cavity is fabricated by SiO2/ZrO2 or SiO2/TiO2 matrix doped with magnetic nanoparticles, in which the refractive index varied in the range of 1.51-1.58. We demonstrate that the Q factor for the designed cavity increases as the refractive index increases, and we find that the Q factor decreases as the volume fraction VF% due to off-diagonal elements increases. These magnetic microcavities may serve as a fundamental structure in a variety of ultra compact magneto photonic devices such as optical isolators, circulators and modulators in the future.

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.

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.

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

Mueller coherency matrix method for contrast image in tissue polarimetry

NASA Astrophysics Data System (ADS)

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

2007-07-01

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

Volatile organic compounds (VOCs) in urban air: How chemistry affects the interpretation of positive matrix factorization (PMF) analysis

NASA Astrophysics Data System (ADS)

Yuan, Bin; Shao, Min; de Gouw, Joost; Parrish, David D.; Lu, Sihua; Wang, Ming; Zeng, Limin; Zhang, Qian; Song, Yu; Zhang, Jianbo; Hu, Min

2012-12-01

Volatile organic compounds (VOCs) were measured online at an urban site in Beijing in August-September 2010. Diurnal variations of various VOC species indicate that VOCs concentrations were influenced by photochemical removal with OH radicals for reactive species and secondary formation for oxygenated VOCs (OVOCs). A photochemical age-based parameterization method was applied to characterize VOCs chemistry. A large part of the variability in concentrations of both hydrocarbons and OVOCs was explained by this method. The determined emission ratios of hydrocarbons to acetylene agreed within a factor of two between 2005 and 2010 measurements. However, large differences were found for emission ratios of some alkanes and C8 aromatics between Beijing and northeastern United States secondary formation from anthropogenic VOCs generally contributed higher percentages to concentrations of reactive aldehydes than those of inert ketones and alcohols. Anthropogenic primary emissions accounted for the majority of ketones and alcohols concentrations. Positive matrix factorization (PMF) was also used to identify emission sources from this VOCs data set. The four resolved factors were three anthropogenic factors and a biogenic factor. However, the anthropogenic factors are attributed here to a common source at different stages of photochemical processing rather than three independent sources. Anthropogenic and biogenic sources of VOCs concentrations were not separated completely in PMF. This study indicates that photochemistry of VOCs in the atmosphere complicates the information about separated sources that can be extracted from PMF and the influence of photochemical processing must be carefully considered in the interpretation of source apportionment studies based upon PMF.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Factor 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…

Chimeric recombinant antibody fragments in cardiac troponin I immunoassay.

PubMed

Hyytiä, Heidi; Heikkilä, Taina; Brockmann, Eeva-Christine; Kekki, Henna; Hedberg, Pirjo; Puolakanaho, Tarja; Lövgren, Timo; Pettersson, Kim

2015-03-01

To introduce a novel nanoparticle-based immunoassay for cardiac troponin I (cTnI) utilizing chimeric antibody fragments and to demonstrate that removal of antibody Fc-part and antibody chimerization decrease matrix related interferences. A sandwich-type immunoassay for cTnI based on recombinant chimeric (mouse variable/human constant) antigen binding (cFab) antibodies and intrinsically fluorescent nanoparticles was developed. To test whether using chimeric antibody fragments helps to avoid matrix related interferences, samples (n=39) with known amounts of triglycerides, bilirubin, rheumatoid factor (RF) or human anti-mouse antibodies (HAMAs) were measured with the novel assay, along with a previously published nanoparticle-based research assay with the same antibody epitopes. The limit of detection (LoD) was 3.30ng/L. Within-laboratory precision for 29ng/L and 2819ng/L cTnI were 13.7% and 15.9%, respectively. Regression analysis with Siemens ADVIA Centaur® yielded a slope (95% confidence intervals) of 0.18 (0.17-1.19) and a y-intercept of 1.94 (-1.28-3.91) ng/L. When compared to a previously published nanoparticle-based assay, the novel assay showed substantially reduced interference in the tested interference prone samples, 15.4 vs. 51.3%. A rheumatoid factor containing sample was decreased from 241ng/L to

Molecular signaling in live cells studied by FRET

NASA Astrophysics Data System (ADS)

Chien, Shu; Wang, Yingxiao

2011-11-01

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) enables visualization of signaling events in live cells with high spatiotemporal resolution. We have used FRET to assess temporal and spatial characteristics for signaling molecules, including tyrosine kinases Src and FAK, small GTPase Rac, calcium, and a membrane-bound matrix metalloproteinase MT1-MMP. Activations of Src and Rac by platelet derived growth factor (PDGF) led to distinct subcellular patterns during cell migration on micropatterned surface, and these two enzymes interact with each other to form a feedback loop with differential regulations at different subcellular locations. We have developed FRET biosensors to monitor FAK activities at rafts vs. non-raft regions of plasma membrane in live cells. In response to cell adhesion on matrix proteins or stimulation by PDGF, the raft-targeting FAK biosensor showed a stronger FRET response than that at non-rafts. The FAK activation at rafts induced by PDGF is mediated by Src. In contrast, the FAK activation at rafts induced by adhesion is independent of Src activity, but rather is essential for Src activation. Thus, Src is upstream to FAK in response to chemical stimulation (PDGF), but FAK is upstream to Src in response to mechanical stimulation (adhesion). A novel biosensor has been developed to dynamically visualize the activity of membrane type-1-matrix metalloproteinase (MT1-MMP), which proteolytically remodels the extracellular matrix. Epidermal growth factor (EGF) directed active MT1-MMP to the leading edge of migrating live cancer cells with local accumulation of EGF receptor via a process dependent on an intact cytoskeletal network. In summary, FRET-based biosensors enable the elucidation of molecular processes and hierarchies underlying spatiotemporal regulation of biological and pathological processes, thus advancing our knowledge on how cells perceive mechanical/chemical cues in space and time to coordinate molecular/cellular functions.

Molecular signaling in live cells studied by FRET

NASA Astrophysics Data System (ADS)

Chien, Shu; Wang, Yingxiao

2012-03-01

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) enables visualization of signaling events in live cells with high spatiotemporal resolution. We have used FRET to assess temporal and spatial characteristics for signaling molecules, including tyrosine kinases Src and FAK, small GTPase Rac, calcium, and a membrane-bound matrix metalloproteinase MT1-MMP. Activations of Src and Rac by platelet derived growth factor (PDGF) led to distinct subcellular patterns during cell migration on micropatterned surface, and these two enzymes interact with each other to form a feedback loop with differential regulations at different subcellular locations. We have developed FRET biosensors to monitor FAK activities at rafts vs. non-raft regions of plasma membrane in live cells. In response to cell adhesion on matrix proteins or stimulation by PDGF, the raft-targeting FAK biosensor showed a stronger FRET response than that at non-rafts. The FAK activation at rafts induced by PDGF is mediated by Src. In contrast, the FAK activation at rafts induced by adhesion is independent of Src activity, but rather is essential for Src activation. Thus, Src is upstream to FAK in response to chemical stimulation (PDGF), but FAK is upstream to Src in response to mechanical stimulation (adhesion). A novel biosensor has been developed to dynamically visualize the activity of membrane type-1-matrix metalloproteinase (MT1-MMP), which proteolytically remodels the extracellular matrix. Epidermal growth factor (EGF) directed active MT1-MMP to the leading edge of migrating live cancer cells with local accumulation of EGF receptor via a process dependent on an intact cytoskeletal network. In summary, FRET-based biosensors enable the elucidation of molecular processes and hierarchies underlying spatiotemporal regulation of biological and pathological processes, thus advancing our knowledge on how cells perceive mechanical/chemical cues in space and time to coordinate molecular/cellular functions.

Development and optimization of a matrix converter supplying an electronic ballast - UV lamp system for water sterilization

NASA Astrophysics Data System (ADS)

Bokhtache, Aicha Aissa; Zegaoui, Abdallah; Aillerie, Michel; Djahbar, Abdelkader; Hemici, Kheira

2018-05-01

Electronic ballasts dedicated to discharge lamps allow improving the quality of radiation by operating at high frequency. In the present work, the use of a single-phase direct converter with a matrix structure for supplying a low-pressure mercury-argon UVC lamp for water sterilization is proposed. The structure of the converter is based on two switching cells allowing the realization of a fully controllable bidirectional switches. The advantages of such a matrix topology include the delivered of a sinusoidal waveform current with a controllable power factor close to unity, variable in amplitude and frequency. In order to obtain the desired amplitude and frequency, a PWM control was associated in the current realization. Finally, a linear adjustment of the lamp arc current was warranted by using of a PI regulator.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Effects of transforming growth factor-beta1 on cell motility, collagen gel contraction, myofibroblastic differentiation, and extracellular matrix expression of human adipose-derived stem cell.

PubMed

Kakudo, Natsuko; Kushida, Satoshi; Suzuki, Kenji; Ogura, Tsunetaka; Notodihardjo, Priscilla Valentin; Hara, Tomoya; Kusumoto, Kenji

2012-12-01

Human adipose-derived stem cells (ASCs) are adult pluripotent stem cells, and their usefulness in plastic surgery has garnered attention in recent years. Although, there have been expectations that ASCs might function in wound repair and regeneration, no studies to date have examined the role of ASCs in the mechanism that promotes wound-healing. Transforming growth factor-beta1 (TGF-β1) is a strong candidate cytokine for the triggering of mesenchymal stem cell migration, construction of extracellular matrices, and differentiation of ASCs into myofibroblasts. Cell proliferation, motility, and differentiation, as well as extracellular matrix production, play an important role in wound-healing. We have evaluated the capacity of ASCs to proliferate and their potential to differentiate into phenotypic myofibroblasts, as well as their cell motility and collagen gel contraction ability, when cultured with TGF-β1. Cell motility was analyzed using a wound-healing assay. ASCs that differentiated into myofibroblasts expressed the gene for alpha-smooth muscle actin, and its protein expression was detected immunohistochemically. The extracellular matrix expression in ASCs was evaluated using real-time RT-PCR. Based on the results, we conclude that human ASCs have the potential for cell motility, extracellular matrix gene expression, gel contraction, and differentiation into myofibroblasts and, therefore, may play an important role in the wound-healing process.

Sensitivity Modulation of Upconverting Thermometry through Engineering Phonon Energy of a Matrix.

PubMed

Suo, Hao; Guo, Chongfeng; Zheng, Jiming; Zhou, Bo; Ma, Chonggeng; Zhao, Xiaoqi; Li, Ting; Guo, Ping; Goldys, Ewa M

2016-11-09

Investigation of the unclear influential factors to thermal sensing capability is the only way to achieve highly sensitive thermometry, which is greatly needed to meet the growing demand for potential sensing applications. Here, the effect from the phonon energy of a matrix on the sensitivity of upconversion (UC) microthermometers is elaborately discussed using a controllable method. Uniform truncated octahedral YF 3 :Er 3+ /Yb 3+ microcrystals were prepared by a hydrothermal approach, and phase transformation from YF 3 to YOF and Y 2 O 3 with nearly unchanged morphology and size was successfully realized by controlling the annealing temperature. The phonon energies of blank matrixes were determined by FT-IR spectra and Raman scattering. Upon 980 nm excitation, phonon energy-dependent UC emitting color was finely tuned from green to yellow for three samples, and the mechanisms were proposed. Thermal sensing behaviors based on the TCLs ( 2 H 11/2 / 4 S 3/2 ) were evaluated, and the sensitivities gradually grew with the increase in the matrix's phonon energy. According to chemical bond theory and first-principle calculations, the most intrinsic factors associated with thermometric ability were qualitatively demonstrated through analyzing the inner relation between the phonon energy and bond covalency. The exciting results provide guiding insights into employing appropriate host materials with desired thermometric ability while offering the possibility of highly accurate measurement of temperature.

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

Low-Earth orbit effects on organic composite materials flown on LDEF

NASA Technical Reports Server (NTRS)

George, Pete E.; Dursch, Harry W.

1993-01-01

Over 35 different types of organic matrix composites were flown as part of 11 different experiments onboard the NASA Long Duration Exposure Facility (LDEF) satellite. This materials and systems experiment satellite flew in low-earth orbit (LEO) for 69 months. For that period, the experiments were subjected to the LEO environment including atomic oxygen (AO), ultraviolet (UV) radiation, thermal cycling, microvacuum, meteoroid and space debris (M&D), and particle radiation. Since retrieval of the satellite in January of 1990, the principal experiment investigators have been deintegrating, examining, and testing the materials specimens flown. The most detrimental environmental effect on all organic matrix composites was material loss due to AO erosion. AO erosion of uncoated organic matrix composites (OMC) facing the satellite ram direction was responsible for significant mechanical property degradations. Also, thermal cycling-induced microcracking was observed in some nonunidirectional reinforced OMC's. Thermal cycling and outgassing caused significant but predictable dimensional changes as measured in situ on one experiment. Some metal and metal oxide-based coatings were found to be very effective at preventing AO erosion of OMC's. However, M&D impacts and coating fractures which compromised these coatings allowed AO erosion of the underlying OMC substrates. The findings for organic matrix composites flown on the LDEF are summarized and the LEO environmental factors, their effects, and the influence on space hardware design factors for LEO applications are identified.

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)

Sparsistency and Rates of Convergence in Large Covariance Matrix Estimation.

PubMed

Lam, Clifford; Fan, Jianqing

2009-01-01

This paper studies the sparsistency and rates of convergence for estimating sparse covariance and precision matrices based on penalized likelihood with nonconvex penalty functions. Here, sparsistency refers to the property that all parameters that are zero are actually estimated as zero with probability tending to one. Depending on the case of applications, sparsity priori may occur on the covariance matrix, its inverse or its Cholesky decomposition. We study these three sparsity exploration problems under a unified framework with a general penalty function. We show that the rates of convergence for these problems under the Frobenius norm are of order (s(n) log p(n)/n)(1/2), where s(n) is the number of nonzero elements, p(n) is the size of the covariance matrix and n is the sample size. This explicitly spells out the contribution of high-dimensionality is merely of a logarithmic factor. The conditions on the rate with which the tuning parameter λ(n) goes to 0 have been made explicit and compared under different penalties. As a result, for the L(1)-penalty, to guarantee the sparsistency and optimal rate of convergence, the number of nonzero elements should be small: sn'=O(pn) at most, among O(pn2) parameters, for estimating sparse covariance or correlation matrix, sparse precision or inverse correlation matrix or sparse Cholesky factor, where sn' is the number of the nonzero elements on the off-diagonal entries. On the other hand, using the SCAD or hard-thresholding penalty functions, there is no such a restriction.

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.

Proposed framework for thermomechanical life modeling of metal matrix composites

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

PubMed

Hoy, Erik P; Mazziotti, David A

2015-08-14

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

Risks of Large Portfolios

PubMed Central

Fan, Jianqing; Liao, Yuan; Shi, Xiaofeng

2014-01-01

The risk of a large portfolio is often estimated by substituting a good estimator of the volatility matrix. However, the accuracy of such a risk estimator is largely unknown. We study factor-based risk estimators under a large amount of assets, and introduce a high-confidence level upper bound (H-CLUB) to assess the estimation. The H-CLUB is constructed using the confidence interval of risk estimators with either known or unknown factors. We derive the limiting distribution of the estimated risks in high dimensionality. We find that when the dimension is large, the factor-based risk estimators have the same asymptotic variance no matter whether the factors are known or not, which is slightly smaller than that of the sample covariance-based estimator. Numerically, H-CLUB outperforms the traditional crude bounds, and provides an insightful risk assessment. In addition, our simulated results quantify the relative error in the risk estimation, which is usually negligible using 3-month daily data. PMID:26195851

Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints

NASA Astrophysics Data System (ADS)

Sembiring, Pasukat

2017-12-01

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

Nanomechanical Contribution of Collagen and von Willebrand Factor A in Marine Underwater Adhesion and Its Implication for Collagen Manipulation.

PubMed

Yoo, Hee Young; Huang, Jun; Li, Lin; Foo, Mathias; Zeng, Hongbo; Hwang, Dong Soo

2016-03-14

Recent works on mussel adhesion have identified a load bearing matrix protein (PTMP1) containing von Willebrand factor (vWF) with collagen binding capability that contributes to the mussel holdfast by manipulating mussel collagens. Using a surface forces apparatus, we investigate for the first time, the nanomechanical properties of vWF-collagen interaction using homologous proteins of mussel byssus, PTMP1 and preCollagens (preCols), as collagen. Mimicking conditions similar to mussel byssus secretion (pH < 5.0) and seawater condition (pH 8.0), PTMP1 and preCol interact weakly in the "positioning" phase based on vWF-collagen binding and strengthen in "locked" phase due to the combined effects of electrostatic attraction, metal binding, and mechanical shearing. The progressive enhancement of binding between PTMP1 with porcine collagen under the aforementioned conditions is also observed. The binding mechanisms of PTMP1-preCols provide insights into the molecular interaction of the mammalian collagen system and the development of an artificial extracellular matrix based on collagens.

Peak picking NMR spectral data using non-negative matrix factorization.

PubMed

Tikole, Suhas; Jaravine, Victor; Rogov, Vladimir; Dötsch, Volker; Güntert, Peter

2014-02-11

Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments. To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments. Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.

Many Masses on One Stroke:. Economic Computation of Quark Propagators

NASA Astrophysics Data System (ADS)

Frommer, Andreas; Nöckel, Bertold; Güsken, Stephan; Lippert, Thomas; Schilling, Klaus

The computational effort in the calculation of Wilson fermion quark propagators in Lattice Quantum Chromodynamics can be considerably reduced by exploiting the Wilson fermion matrix structure in inversion algorithms based on the non-symmetric Lanczos process. We consider two such methods: QMR (quasi minimal residual) and BCG (biconjugate gradients). Based on the decomposition M/κ = 1/κ-D of the Wilson mass matrix, using QMR, one can carry out inversions on a whole trajectory of masses simultaneously, merely at the computational expense of a single propagator computation. In other words, one has to compute the propagator corresponding to the lightest mass only, while all the heavier masses are given for free, at the price of extra storage. Moreover, the symmetry γ5M = M†γ5 can be used to cut the computational effort in QMR and BCG by a factor of two. We show that both methods then become — in the critical regime of small quark masses — competitive to BiCGStab and significantly better than the standard MR method, with optimal relaxation factor, and CG as applied to the normal equations.

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

Food processing strategies to enhance phenolic compounds bioaccessibility and bioavailability in plant-based foods.

PubMed

Ribas-Agustí, Albert; Martín-Belloso, Olga; Soliva-Fortuny, Robert; Elez-Martínez, Pedro

2017-06-13

Phenolic compounds are important constituents of plant-based foods, as their presence is related to protective effects on health. To exert their biological activity, phenolic compounds must be released from the matrix during digestion in an absorbable form (bioaccessible) and finally absorbed and transferred to the bloodstream (bioavailable). Chemical structure and matrix interactions are some food-related factors that hamper phenolic compounds bioaccessibility and bioavailability, and that can be counteracted by food processing. It has been shown that food processing can induce chemical or physical modifications in food that enhance phenolic compounds bioaccessibility and bioavailability. These changes include: (i) chemical modifications into more bioaccessible and bioavailable forms; (ii) cleavage of covalent or hydrogen bonds or hydrophobic forces that attach phenolic compounds to matrix macromolecules; (iii) damaging microstructural barriers such as cell walls that impede the release from the matrix; and (iv) create microstructures that protect phenolic compounds until they are absorbed. Indeed, food processing can produce degradation of phenolic compounds, however, it is possible to counteract it by modulating the operating conditions in favor of increased bioaccessibility and bioavailability. This review compiles the current knowledge on the effects of processing on phenolic compounds bioaccessibility or bioavailability, while suggesting new guidelines in the search of optimal processing conditions as a step forward towards the design of healthier foods.

The Evidence Value Matrix for Diagnostic Imaging.

PubMed

Seidel, David; Frank, Richard A; Schmidt, Sebastian

2016-10-01

Evidence and value are independent factors that together affect the adoption of diagnostic imaging. For example, noncoverage decisions by reimbursement authorities can be justified by a lack of evidence and/or value. To create transparency and a common understanding among various stakeholders, we have proposed a two-dimensional matrix that allows classification of imaging devices into three distinct categories based on the available evidence and value: "question marks" (low value demonstrated in studies of any evidence level), "candidates" (high value demonstrated in retrospective case-control studies and smaller case series), and "stars" (high value demonstrated in large prospective cohort studies or, preferably, randomized controlled trials). We use several examples to illustrate the application of our matrix. A major benefit of the matrix includes the development of specific strategies for evidence and value generation. High-evidence/low-value studies are expensive and unlikely to convince decision makers, given the uncertainty of the impact on patient management and outcomes. Developing question marks into candidates first and then into stars will often be quicker and less expensive ("success sequence"). Only this more sophisticated and objective approach can justify the additional funding necessary to generate the evidence base to inform reimbursement by payers and adoption by providers. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2017-09-08

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

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.

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.

Correlation of pretreatment 18F-FDG PET tumor textural features with gene expression in pharyngeal cancer and implications for radiotherapy-based treatment outcomes.

PubMed

Chen, Shang-Wen; Shen, Wei-Chih; Lin, Ying-Chun; Chen, Rui-Yun; Hsieh, Te-Chun; Yen, Kuo-Yang; Kao, Chia-Hung

2017-04-01

This study investigated the correlation of the matrix heterogeneity of tumors on 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) with gene-expression profiling in patients with pharyngeal cancer and determined the prognostic factors for radiotherapy-based treatment outcomes. We retrospectively reviewed the records of 57 patients with stage III-IV oropharyngeal or hypopharyngeal cancer who had completed definitive therapy. Four groups of the textural features as well as 31 indices were studied in addition to maximum standard uptake value, metastatic tumor volume, and total lesion glycolysis. Immunohistochemical data from pretreatment biopsy specimens (Glut1, CAIX, VEGF, HIF-1α, EGFR, Ki-67, Bcl-2, CLAUDIN-4, YAP-1, c-Met, and p16) were analyzed. The relationships between the indices and genomic expression were studied, and the robustness of various textural features relative to cause-specific survival and primary relapse-free survival was analyzed. The overexpression of VEGF was positively associated with the increased values of the matrix heterogeneity obtained using gray-level nonuniformity for zone (GLNUz) and run-length nonuniformity (RLNU). Advanced T stage (p = 0.01, hazard ratio [HR] = 3.38), a VEGF immunoreactive score of >2 (p = 0.03, HR = 2.79), and a higher GLNUz value (p = 0.04, HR = 2.51) were prognostic factors for low cause-specific survival, whereas advanced T stage, a HIF-1α staining percentage of ≥80%, and a higher GLNUz value were prognostic factors for low primary-relapse free survival. The overexpression of VEGF was associated with the increased matrix index of GLNUz and RLNU. For patients with pharyngeal cancer requiring radiotherapy, the treatment outcome can be stratified according to the textural features, T stage, and biomarkers.

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

Decision to abort after a prenatal diagnosis of sex chromosome abnormality: a systematic review of the literature.

PubMed

Jeon, Kwon Chan; Chen, Lei-Shih; Goodson, Patricia

2012-01-01

We performed a systematic review of factors affecting parental decisions to continue or terminate a pregnancy after prenatal diagnosis of a sex chromosome abnormality, as reported in published studies from 1987 to May 2011. Based on the Matrix Method for systematic reviews, 19 studies were found in five electronic databases, meeting specific inclusion/exclusion criteria. Abstracted data were organized in a matrix. Alongside the search for factors influencing parental decisions, each study was judged on its methodological quality and assigned a methodological quality score. Decisions either to terminate or to continue a sex chromosome abnormality-affected pregnancy shared five similar factors: specific type of sex chromosome abnormality, gestational week at diagnosis, parents' age, providers' genetic expertise, and number of children/desire for (more) children. Factors unique to termination decisions included parents' fear/anxiety and directive counseling. Factors uniquely associated with continuation decisions were parents' socioeconomic status and ethnicity. The studies' average methodological quality score was 10.6 (SD = 1.67; range, 8-14). Findings from this review can be useful in adapting and modifying guidelines for genetic counseling after prenatal diagnosis of a sex chromosome abnormality. Moreover, improving the quality of future studies on this topic may allow clearer understanding of the most influential factors affecting parental decisions.

A generalized leaky FxLMS algorithm for tuning the waterbed effect of feedback active noise control systems

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Guo, Yecai

2018-06-01

To tune the noise amplification in the feedback system caused by the waterbed effect effectively, an adaptive algorithm is proposed in this paper by replacing the scalar leaky factor of the leaky FxLMS algorithm with a real symmetric Toeplitz matrix. The elements in the matrix are calculated explicitly according to the noise amplification constraints, which are defined based on a simple but efficient method. Simulations in an ANC headphone application demonstrate that the proposed algorithm can adjust the frequency band of noise amplification more effectively than the FxLMS algorithm and the leaky FxLMS algorithm.

Progressive delamination in polymer matrix composite laminates: A new approach

NASA Technical Reports Server (NTRS)

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

1992-01-01

A new approach independent of stress intensity factors and fracture toughness parameters has been developed and is described for the computational simulation of progressive delamination in polymer matrix composite laminates. The damage stages are quantified based on physics via composite mechanics while the degradation of the laminate behavior is quantified via the finite element method. The approach accounts for all types of composite behavior, laminate configuration, load conditions, and delamination processes starting from damage initiation, to unstable propagation, and to laminate fracture. Results of laminate fracture in composite beams, panels, plates, and shells are presented to demonstrate the effectiveness and versatility of this new approach.

Study of Erosive Wear Behaviour on SIC/SIC Composites

NASA Astrophysics Data System (ADS)

Suh, Min-Soo

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

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.

Aberrant expression of genes and proteins in pterygium and their implications in the pathogenesis

PubMed Central

Feng, Qing-Yang; Hu, Zi-Xuan; Song, Xi-Ling; Pan, Hong-Wei

2017-01-01

Pterygium is a common ocular surface disease induced by a variety of factors. The exact pathogenesis of pterygium remains unclear. Numbers of genes and proteins are discovered in pterygium and they function differently in the occurrence and development of this disease. We searched the Web of Science and PubMed throughout history for literatures about the subject. The keywords we used contain pterygium, gene, protein, angiogenesis, fibrosis, proliferation, inflammation, pathogenesis and therapy. In this review, we summarize the aberrant expression of a range of genes and proteins in pterygium compared with normal conjunctiva or cornea, including growth factors, matrix metalloproteinases and tissue inhibitors of metalloproteinases, interleukins, tumor suppressor genes, proliferation related proteins, apoptosis related proteins, cell adhesion molecules, extracellular matrix proteins, heat shock proteins and tight junction proteins. We illustrate their possible mechanisms in the pathogenesis of pterygium as well as the related intervention based on them for pterygium therapy. PMID:28730091

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

NASA Astrophysics Data System (ADS)

Pandey, Ras; Farmer, Barry

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

The Developmental Regulator SEEDSTICK Controls Structural and Mechanical Properties of the Arabidopsis Seed Coat

PubMed Central

Beauzamy, Léna; Caporali, Elisabetta; Koroney, Abdoul-Salam

2016-01-01

Although many transcription factors involved in cell wall morphogenesis have been identified and studied, it is still unknown how genetic and molecular regulation of cell wall biosynthesis is integrated into developmental programs. We demonstrate by molecular genetic studies that SEEDSTICK (STK), a transcription factor controlling ovule and seed integument identity, directly regulates PMEI6 and other genes involved in the biogenesis of the cellulose-pectin matrix of the cell wall. Based on atomic force microscopy, immunocytochemistry, and chemical analyses, we propose that structural modifications of the cell wall matrix in the stk mutant contribute to defects in mucilage release and seed germination under water-stress conditions. Our studies reveal a molecular network controlled by STK that regulates cell wall properties of the seed coat, demonstrating that developmental regulators controlling organ identity also coordinate specific aspects of cell wall characteristics. PMID:27624758

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

PubMed

Zhang, Shu; Li, Xiang; Lv, Jinglei; Jiang, Xi; Guo, Lei; Liu, Tianming

2016-03-01

A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100% classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release.

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...

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.

Weighted augmented Jacobian matrix with a variable coefficient method for kinematics mapping of space teleoperation based on human-robot motion similarity

NASA Astrophysics Data System (ADS)

Shi, Zhong; Huang, Xuexiang; Hu, Tianjian; Tan, Qian; Hou, Yuzhuo

2016-10-01

Space teleoperation is an important space technology, and human-robot motion similarity can improve the flexibility and intuition of space teleoperation. This paper aims to obtain an appropriate kinematics mapping method of coupled Cartesian-joint space for space teleoperation. First, the coupled Cartesian-joint similarity principles concerning kinematics differences are defined. Then, a novel weighted augmented Jacobian matrix with a variable coefficient (WAJM-VC) method for kinematics mapping is proposed. The Jacobian matrix is augmented to achieve a global similarity of human-robot motion. A clamping weighted least norm scheme is introduced to achieve local optimizations, and the operating ratio coefficient is variable to pursue similarity in the elbow joint. Similarity in Cartesian space and the property of joint constraint satisfaction is analysed to determine the damping factor and clamping velocity. Finally, a teleoperation system based on human motion capture is established, and the experimental results indicate that the proposed WAJM-VC method can improve the flexibility and intuition of space teleoperation to complete complex space tasks.

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

PubMed

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

2016-04-01

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

An ultra-compact and low loss passive beam-forming network integrated on chip with off chip linear array

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

Lepkowski, Stefan Mark

2015-05-01

The work here presents a review of beam forming architectures. As an example, the author presents an 8x8 Butler Matrix passive beam forming network including the schematic, design/modeling, operation, and simulated results. The limiting factor in traditional beam formers has been the large size dictated by transmission line based couplers. By replacing these couplers with transformer-based couplers, the matrix size is reduced substantially allowing for on chip compact integration. In the example presented, the core area, including the antenna crossover, measures 0.82mm×0.39mm (0.48% the size of a branch line coupler at the same frequency). The simulated beam forming achieves amore » peak PNR of 17.1 dB and 15dB from 57 to 63GHz. At the 60GHz center frequency the average insertion loss is simulated to be 3.26dB. The 8x8 Butler Matrix feeds into an 8-element antenna array to show the array patterns with single beam and adjacent beam isolation.« less

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.

Discriminant projective non-negative matrix factorization.

PubMed

Guan, Naiyang; Zhang, Xiang; Luo, Zhigang; Tao, Dacheng; Yang, Xuejun

2013-01-01

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W(T) X as their coefficients, i.e., X≈WW(T) X. Since PNMF learns the natural parts-based representation Wof X, it has been widely used in many fields such as pattern recognition and computer vision. However, PNMF does not perform well in classification tasks because it completely ignores the label information of the dataset. This paper proposes a Discriminant PNMF method (DPNMF) to overcome this deficiency. In particular, DPNMF exploits Fisher's criterion to PNMF for utilizing the label information. Similar to PNMF, DPNMF learns a single non-negative basis matrix and needs less computational burden than NMF. In contrast to PNMF, DPNMF maximizes the distance between centers of any two classes of examples meanwhile minimizes the distance between any two examples of the same class in the lower-dimensional subspace and thus has more discriminant power. We develop a multiplicative update rule to solve DPNMF and prove its convergence. Experimental results on four popular face image datasets confirm its effectiveness comparing with the representative NMF and PNMF algorithms.

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

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

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

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

Discriminant Projective Non-Negative Matrix Factorization

PubMed Central

Guan, Naiyang; Zhang, Xiang; Luo, Zhigang; Tao, Dacheng; Yang, Xuejun

2013-01-01

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers WT X as their coefficients, i.e., X≈WWT X. Since PNMF learns the natural parts-based representation Wof X, it has been widely used in many fields such as pattern recognition and computer vision. However, PNMF does not perform well in classification tasks because it completely ignores the label information of the dataset. This paper proposes a Discriminant PNMF method (DPNMF) to overcome this deficiency. In particular, DPNMF exploits Fisher's criterion to PNMF for utilizing the label information. Similar to PNMF, DPNMF learns a single non-negative basis matrix and needs less computational burden than NMF. In contrast to PNMF, DPNMF maximizes the distance between centers of any two classes of examples meanwhile minimizes the distance between any two examples of the same class in the lower-dimensional subspace and thus has more discriminant power. We develop a multiplicative update rule to solve DPNMF and prove its convergence. Experimental results on four popular face image datasets confirm its effectiveness comparing with the representative NMF and PNMF algorithms. PMID:24376680

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

Analytic tools for investigating the structure of network reliability measures with regard to observation correlations

NASA Astrophysics Data System (ADS)

Prószyński, W.; Kwaśniak, M.

2018-03-01

A global measure of observation correlations in a network is proposed, together with the auxiliary indices related to non-diagonal elements of the correlation matrix. Based on the above global measure, a specific representation of the correlation matrix is presented, being the result of rigorously proven theorem formulated within the present research. According to the theorem, each positive definite correlation matrix can be expressed by a scale factor and a so-called internal weight matrix. Such a representation made it possible to investigate the structure of the basic reliability measures with regard to observation correlations. Numerical examples carried out for two test networks illustrate the structure of those measures that proved to be dependent on global correlation index. Also, the levels of global correlation are proposed. It is shown that one can readily find an approximate value of the global correlation index, and hence the correlation level, for the expected values of auxiliary indices being the only knowledge about a correlation matrix of interest. The paper is an extended continuation of the previous study of authors that was confined to the elementary case termed uniform correlation. The extension covers arbitrary correlation matrices and a structure of correlation effect.

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.

Supermacroporous cryogel matrix for integrated protein isolation. Immobilized metal affinity chromatographic purification of urokinase from cell culture broth of a human kidney cell line.

PubMed

Kumar, Ashok; Bansal, Vibha; Andersson, Jonatan; Roychoudhury, Pradip K; Mattiasson, Bo

2006-01-20

A new type of supermacroporous, monolithic, cryogel affinity adsorbent was developed, allowing the specific capture of urokinase from conditioned media of human fibrosarcoma cell line HT1080. The affinity adsorbent was designed with the objective of using it as a capture column in an integrated perfusion/protein separation bioreactor setup. A comparative study between the utility of this novel cryogel based matrix and the conventional Sepharose based affinity matrix for the continuous capture of urokinase in an integrated bioreactor system was performed. Cu(II)-ion was coupled to epoxy activated polyacrylamide cryogel and Sepharose using iminodiacetic acid (IDA) as the chelating ligand. About 27-fold purification of urokinase from the conditioned culture media was achieved with Cu(II)-IDA-polyacrylamide cryogel column giving specific activity of about 814 Plough units (PU)/mg protein and enzyme yields of about 80%. High yields (95%) were obtained with Cu(II)-IDA-Sepharose column by virtue of its high binding capacity. However, the adsorbent showed lower selectivity as compared to cryogel matrix giving specific activity of 161 PU/mg protein and purification factor of 5.3. The high porosity, selectivity and reasonably good binding capacity of Cu(II)-IDA-polyacrylamide cryogel column make it a promising option for use as a protein capture column in integrated perfusion/separation processes. The urokinase peak pool from Cu(II)-IDA-polyacrylamide cryogel column could be further resolved into separate fractions for high and low molecular weight forms of urokinase by gel filtration chromatography on Sephacryl S-200. The selectivity of the cryogel based IMAC matrix for urokinase was found to be higher as compared to that of Cu(II)-IDA-Sepharose column.

Growth factors and chronic wound healing: past, present, and future.

PubMed

Goldman, Robert

2004-01-01

Growth substances (cytokines and growth factors) are soluble signaling proteins affecting the process of normal wound healing. Cytokines govern the inflammatory phase that clears cellular and extracellular matrix debris. Wound repair is controlled by growth factors (platelet-derived growth factor [PDGF], keratinocyte growth factor, and transforming growth factor beta). Endogenous growth factors communicate across the dermal-epidermal interface. PDGF is important for most phases of wound healing. Becaplermin (PDGF-BB), the only growth factor approved by the Food and Drug Administration, requires daily application for neuropathic wound healing. Gene therapy is under development for more efficient growth factor delivery; a single application will induce constitutive growth factor expression for weeks. Based on dramatic preclinical animal studies, a phase 1 clinical trial planned on a PDGF genetic construct appears promising.

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

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...

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.

Recursive mass matrix factorization and inversion: An operator approach to open- and closed-chain multibody dynamics

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.

1988-01-01

This report advances a linear operator approach for analyzing the dynamics of systems of joint-connected rigid bodies.It is established that the mass matrix M for such a system can be factored as M=(I+H phi L)D(I+H phi L) sup T. This yields an immediate inversion M sup -1=(I-H psi L) sup T D sup -1 (I-H psi L), where H and phi are given by known link geometric parameters, and L, psi and D are obtained recursively by a spatial discrete-step Kalman filter and by the corresponding Riccati equation associated with this filter. The factors (I+H phi L) and (I-H psi L) are lower triangular matrices which are inverses of each other, and D is a diagonal matrix. This factorization and inversion of the mass matrix leads to recursive algortihms for forward dynamics based on spatially recursive filtering and smoothing. The primary motivation for advancing the operator approach is to provide a better means to formulate, analyze and understand spatial recursions in multibody dynamics. This is achieved because the linear operator notation allows manipulation of the equations of motion using a very high-level analytical framework (a spatial operator algebra) that is easy to understand and use. Detailed lower-level recursive algorithms can readily be obtained for inspection from the expressions involving spatial operators. The report consists of two main sections. In Part 1, the problem of serial chain manipulators is analyzed and solved. Extensions to a closed-chain system formed by multiple manipulators moving a common task object are contained in Part 2. To retain ease of exposition in the report, only these two types of multibody systems are considered. However, the same methods can be easily applied to arbitrary multibody systems formed by a collection of joint-connected regid bodies.

Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision

PubMed Central

Wang, Yaming; Tong, Lingling; Jiang, Mingfeng; Zheng, Junbao

2015-01-01

In this paper, the problem of non-rigid structure estimation in trajectory space from monocular vision is investigated. Similar to the Point Trajectory Approach (PTA), based on characteristic points’ trajectories described by a predefined Discrete Cosine Transform (DCT) basis, the structure matrix was also calculated by using a factorization method. To further optimize the non-rigid structure estimation from monocular vision, the rank minimization problem about structure matrix is proposed to implement the non-rigid structure estimation by introducing the basic low-rank condition. Moreover, the Accelerated Proximal Gradient (APG) algorithm is proposed to solve the rank minimization problem, and the initial structure matrix calculated by the PTA method is optimized. The APG algorithm can converge to efficient solutions quickly and lessen the reconstruction error obviously. The reconstruction results of real image sequences indicate that the proposed approach runs reliably, and effectively improves the accuracy of non-rigid structure estimation from monocular vision. PMID:26473863

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.

Nipah Virus C Protein Recruits Tsg101 to Promote the Efficient Release of Virus in an ESCRT-Dependent Pathway.

PubMed

Park, Arnold; Yun, Tatyana; Vigant, Frederic; Pernet, Olivier; Won, Sohui T; Dawes, Brian E; Bartkowski, Wojciech; Freiberg, Alexander N; Lee, Benhur

2016-05-01

The budding of Nipah virus, a deadly member of the Henipavirus genus within the Paramyxoviridae, has been thought to be independent of the host ESCRT pathway, which is critical for the budding of many enveloped viruses. This conclusion was based on the budding properties of the virus matrix protein in the absence of other virus components. Here, we find that the virus C protein, which was previously investigated for its role in antagonism of innate immunity, recruits the ESCRT pathway to promote efficient virus release. Inhibition of ESCRT or depletion of the ESCRT factor Tsg101 abrogates the C enhancement of matrix budding and impairs live Nipah virus release. Further, despite the low sequence homology of the C proteins of known henipaviruses, they all enhance the budding of their cognate matrix proteins, suggesting a conserved and previously unknown function for the henipavirus C proteins.

[The applications of periodontal gingival surgery. Ⅱ: alternative materials].

PubMed

Mao, Er-Jia

2018-04-01

The main purposes of periodontal graft surgery include achieving root coverage, improving the clinical attachment level and keratinized tissue, and advancing the procedure of periodontal plastic surgery. Autogenous graft, such as subepithelial connective tissue graft-based procedure, provide the best outcomes for mean and complete root coverage, as well as increase in keratinized tissue. However, a disadvantage of the procedure is in the location of the operation itself: the additional surgical site (palate). Therefore, clinicians are always looking for graft substitutes. This article will discuss the evidence supporting the use of 1) acellular dermal matrix (ADM); 2) xenogeneic collagen matrix (XCM); 3) recombinant human platelet-derived growth factor (rhPDGF); 4) enamel matrix derivative (EMD); 5) guided tissue regeneration (GTR); 6) living cellular construct (LCC), all of which are used in conjunction with coronally advanced flaps as alternatives to autogenous donor tissue. The decision tree for treatments of Miller recession-type defects are also discussed.

A neutron scintillator based on transparent nanocrystalline CaF{sub 2}:Eu glass ceramic

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

Struebing, Christian; Kang, Zhitao, E-mail: zhitao.kang@gtri.gatech.edu; School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332

2016-04-11

There are no efficient Eu{sup 2+} doped glass neutron scintillators reported due to low doping concentrations of Eu{sup 2+} and the amorphous nature of the glass matrix. In this work, an efficient CaF{sub 2}:Eu glass ceramic neutron scintillator was prepared by forming CaF{sub 2}:Eu nanocrystals in a {sup 6}Li-containing glass matrix. Through appropriate thermal treatments, the scintillation light yield of the transparent glass ceramic was increased by a factor of at least 46 compared to the as-cast amorphous glass. This improvement was attributed to more efficient energy transfer from the CaF{sub 2} crystals to the Eu{sup 2+} emitting centers. Furthermore » light yield improvement is expected if the refractive index of the glass matrix can be matched to the CaF{sub 2} crystal.« less

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.

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

Joint estimation of 2D-DOA and frequency based on space-time matrix and conformal array.

PubMed

Wan, Liang-Tian; Liu, Lu-Tao; Si, Wei-Jian; Tian, Zuo-Xi

2013-01-01

Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

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

2018-02-01

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

Tribological properties of the babbit B83-based composite materials fabricated by powder metallurgy

NASA Astrophysics Data System (ADS)

Kalashnikov, I. E.; Bolotova, L. K.; Bykov, P. A.; Kobeleva, L. I.; Katin, I. V.; Mikheev, R. S.; Kobernik, N. V.

2016-07-01

Technological processes are developed to fabricate composite materials based on B83 babbit using hot pressing of a mixture of powders in the presence of a liquid phase. As a result, the structure of the matrix B83 alloy is dispersed, the morphology of intermetallic phases is changed, and reinforcing micro- and nanosized fillers are introduced and uniformly distributed in the matrix. The tribological properties of the synthesized materials are studied. The friction of the B83 babbit + 0.5 wt % MSR + 3 wt % SiC (MSR is modified schungite rock) composite material at high loads is characterized by an increase in the stability coefficient, and the wear resistance of the material increases by a factor of 1.8 as compared to the as-cast alloy at comparable friction coefficients.

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

PubMed

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

2017-09-05

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

Market potential of nanoremediation in Europe - Market drivers and interventions identified in a deliberative scenario approach.

PubMed

Bartke, Stephan; Hagemann, Nina; Harries, Nicola; Hauck, Jennifer; Bardos, Paul

2018-04-01

A deliberate expert-based scenario approach is applied to better understand the likely determinants of the evolution of the market for nanoparticles use in remediation in Europe until 2025. An initial set of factors had been obtained from a literature review and was complemented by a workshop and key-informant interviews. In further expert engaging formats - focus groups, workshops, conferences, surveys - this initial set of factors was condensed and engaged experts scored the factors regarding their importance for being likely to influence the market development. An interaction matrix was obtained identifying the factors being most active in shaping the market development in Europe by 2025, namely "Science-Policy-Interface" and "Validated information on nanoparticle application potential". Based on these, potential scenarios were determined and development of factors discussed. Conclusions are offered on achievable interventions to enhance nanoremediation deployment. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of variable-magnification X-ray Bragg optics.

PubMed

Hirano, Keiichi; Yamashita, Yoshiki; Takahashi, Yumiko; Sugiyama, Hiroshi

2015-07-01

A novel X-ray Bragg optics is proposed for variable-magnification of an X-ray beam. This X-ray Bragg optics is composed of two magnifiers in a crossed arrangement, and the magnification factor, M, is controlled through the azimuth angle of each magnifier. The basic properties of the X-ray optics such as the magnification factor, image transformation matrix and intrinsic acceptance angle are described based on the dynamical theory of X-ray diffraction. The feasibility of the variable-magnification X-ray Bragg optics was verified at the vertical-wiggler beamline BL-14B of the Photon Factory. For X-ray Bragg magnifiers, Si(220) crystals with an asymmetric angle of 14° were used. The magnification factor was calculated to be tunable between 0.1 and 10.0 at a wavelength of 0.112 nm. At various magnification factors (M ≥ 1.0), X-ray images of a nylon mesh were observed with an air-cooled X-ray CCD camera. Image deformation caused by the optics could be corrected by using a 2 × 2 transformation matrix and bilinear interpolation method. Not only absorption-contrast but also edge-contrast due to Fresnel diffraction was observed in the magnified images.

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.

Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation.

PubMed

Christensen, Ole F

2012-12-03

Single-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1) adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2) extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets. The method derived here is a single-step method in which the marker-based relationship matrix is constructed assuming all allele frequencies equal to 0.5 and the pedigree-based relationship matrix is constructed using the unusual assumption that animals in the base population are related and inbred with a relationship coefficient γ and an inbreeding coefficient γ / 2. Taken together, this γ parameter and a parameter that scales the marker-based relationship matrix can handle the issue of compatibility between marker-based and pedigree-based relationship matrices. The full log-likelihood function used for parameter inference contains two terms. The first term is the REML-log-likelihood for the phenotypes conditional on the observed marker genotypes, whereas the second term is the log-likelihood for the observed marker genotypes. Analyses of the two simulated datasets with this new method showed that 1) the parameters involved in adjusting marker-based and pedigree-based relationship matrices can depend on both observed phenotypes and observed marker genotypes and 2) a strong association between these two parameters exists. Finally, this method performed at least as well as a method based on adjusting the marker-based relationship matrix. Using the full log-likelihood and adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix provides a new and interesting approach to handle the issue of compatibility between the two matrices in single-step genetic evaluation.

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.

Synchronized and sustained release of multiple components in silymarin from erodible glyceryl monostearate matrix system.

PubMed

Lu, Cheng; Lu, Yi; Chen, Jian; Zhang, Wentong; Wu, Wei

2007-05-01

Development of sustained delivery systems for herbal medicines was very difficult because of their complexity in composition. The concept of synchronized release from sustained release systems, which is characterized by release of multiple components in their original ratio that defines a herbal medicine, served as the basis for keeping the original pharmacological activity. In this study, erodible matrix systems based on glyceryl monostearate and polyethylene glycol 6000 or poloxamer 188 were prepared to perform strict control on synchronized release of the five active components of silymarin, i.e. taxifolin, silychrystin, silydianin, isosilybin and silybin. The matrix system was prepared by a melt fusion method. Synchronized release was achieved with high similarity factor f(2) values between each two of the five components. Erosion profiles of the matrix were in good correlation with release profiles of the five components, showing erosion-controlled release mechanisms. Through tuning some of the formulation variables, the system can be adjusted for synchronized and sustained release of silymarin for oral administration. In vitro hemolysis study indicated that the synchronized release samples showed a much better stabilizing effect on erythrocyte membrane.

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.

In-situ formation of nanoparticles within a silicon-based matrix

DOEpatents

Thoma, Steven G [Albuquerque, NM; Wilcoxon, Jess P [Albuquerque, NM; Abrams, Billie L [Albuquerque, NM

2008-06-10

A method for encapsulating nanoparticles with an encapsulating matrix that minimizes aggregation and maintains favorable properties of the nanoparticles. The matrix comprises silicon-based network-forming compounds such as ormosils and polysiloxanes. The nanoparticles are synthesized from precursors directly within the silicon-based matrix.

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…

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...

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.

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.

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.

Human umbilical cord derived matrix: A scaffold suitable for tissue engineering application.

PubMed

Dan, Pan; Velot, Émilie; Mesure, Benjamin; Groshenry, Guillaume; Bacharouche, Jalal; Decot, Véronique; Menu, Patrick

2017-01-01

Human tissue derived natural extracellular matrix (ECM) has great potential in tissue engineering. We sought to isolate extracellular matrix derived from human umbilical cord and test its potential in tissue engineering. An enzymatic method was applied to isolate and solubilized complete human umbilical cord derived matrix (hUCM). The obtained solution was analyzed for growth factors, collagen and residual DNA contents, then used to coat 2D and 3D surfaces for cell culture application. The hUCM was successfully isolated with trypsin digestion to acquire a solution containing various growth factors and collagen but no residual DNA. This hUCM solution can form a coating on 2D and 3D substrates suitable cell culture. We developed a new matrix derived from human source that can be further used in tissue engineering.

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

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.

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.

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.

Inter-class sparsity based discriminative least square regression.

PubMed

Wen, Jie; Xu, Yong; Li, Zuoyong; Ma, Zhongli; Xu, Yuanrong

2018-06-01

Least square regression is a very popular supervised classification method. However, two main issues greatly limit its performance. The first one is that it only focuses on fitting the input features to the corresponding output labels while ignoring the correlations among samples. The second one is that the used label matrix, i.e., zero-one label matrix is inappropriate for classification. To solve these problems and improve the performance, this paper presents a novel method, i.e., inter-class sparsity based discriminative least square regression (ICS_DLSR), for multi-class classification. Different from other methods, the proposed method pursues that the transformed samples have a common sparsity structure in each class. For this goal, an inter-class sparsity constraint is introduced to the least square regression model such that the margins of samples from the same class can be greatly reduced while those of samples from different classes can be enlarged. In addition, an error term with row-sparsity constraint is introduced to relax the strict zero-one label matrix, which allows the method to be more flexible in learning the discriminative transformation matrix. These factors encourage the method to learn a more compact and discriminative transformation for regression and thus has the potential to perform better than other methods. Extensive experimental results show that the proposed method achieves the best performance in comparison with other methods for multi-class classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bioengineering a highly vascularized matrix for the ectopic transplantation of islets

PubMed Central

Ellis, Cara E; Suuronen, Erik; Yeung, Telford; Seeberger, Karen; Korbutt, Gregory S

2013-01-01

Islet transplantation is a promising treatment for Type 1 diabetes; however limitations of the intra-portal site and poor revascularization of islets must be overcome. We hypothesize that engineering a highly vascularized collagen-based construct will allow islet graft survival and function in alternative sites. In this study, we developed such a collagen-based biomaterial. Neonatal porcine islets (NPIs) were embedded in collagen matrices crosslinked with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysuccinimide containing combinations of chondroitin-6-sulfate, chitosan, and laminin, and compared with controls cultured in standard media. Islets were examined for insulin secretory activity after 24 h and 4 d and for apoptotic cell death and matrix integrity after 7 d in vitro. These same NPI/collagen constructs were transplanted subcutaneously in immunoincompetent B6.Rag−/− mice and then assessed for islet survival and vascularization. At all time points assessed during in vitro culture there were no significant differences in insulin secretory activity between control islets and those embedded in the collagen constructs, indicating that the collagen matrix had no adverse effect on islet function. Less cell death was observed in the matrix with all co-polymers compared with the other matrices tested. Immunohistochemical analysis of the grafts post-transplant confirmed the presence of intact insulin-positive islets; grafts were also shown to be vascularized by von Willebrand factor staining. This study demonstrates that a collagen, chondroitin-6-sulfate, chitosan, and laminin matrix supports islet function in vitro and moreover allows islet survival and vascularization post-transplantation; therefore, this bio-engineered vascularized construct is capable of supporting islet survival. PMID:24262950

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

NASA Astrophysics Data System (ADS)

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

2008-07-01

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

Quantification of various growth factors in different demineralized bone matrix preparations.

PubMed

Wildemann, B; Kadow-Romacker, A; Haas, N P; Schmidmaier, G

2007-05-01

Besides autografts, allografts, and synthetic materials, demineralized bone matrix (DBM) is used for bone defect filling and treatment of non-unions. Different DBM formulations are introduced in clinic since years. However, little is known about the presents and quantities of growth factors in DBM. Aim of the present study was the quantification of eight growth factors important for bone healing in three different "off the shelf" DBM formulations, which are already in human use: DBX putty, Grafton DBM putty, and AlloMatrix putty. All three DBM formulations are produced from human donor tissue but they differ in the substitutes added. From each of the three products 10 different lots were analyzed. Protein was extracted from the samples with Guanidine HCL/EDTA method and human ELISA kits were used for growth factor quantification. Differences between the three different products were seen in total protein contend and the absolute growth factor values but also a large variability between the different lots was found. The order of the growth factors, however, is almost comparable between the materials. In the three investigated materials FGF basic and BMP-4 were not detectable in any analyzed sample. BMP-2 revealed the highest concentration extractable from the samples with approximately 3.6 microg/g tissue without a significant difference between the three DBM formulations. In DBX putty significantly more TGF-beta1 and FGFa were measurable compared to the two other DBMs. IGF-I revealed the significantly highest value in the AlloMatrix and PDGF in Grafton. No differences were accessed for VEGF. Due to the differences in the growth factor concentration between the individual samples, independently from the product formulation, further analyzes are required to optimize the clinical outcome of the used demineralized bone matrix. Copyright 2006 Wiley Periodicals, Inc.

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.

Mechanical regulation of chondrogenesis

PubMed Central

2013-01-01

Mechanical factors play a crucial role in the development of articular cartilage in vivo. In this regard, tissue engineers have sought to leverage native mechanotransduction pathways to enhance in vitro stem cell-based cartilage repair strategies. However, a thorough understanding of how individual mechanical factors influence stem cell fate is needed to predictably and effectively utilize this strategy of mechanically-induced chondrogenesis. This article summarizes some of the latest findings on mechanically stimulated chondrogenesis, highlighting several new areas of interest, such as the effects of mechanical stimulation on matrix maintenance and terminal differentiation, as well as the use of multifactorial bioreactors. Additionally, the roles of individual biophysical factors, such as hydrostatic or osmotic pressure, are examined in light of their potential to induce mesenchymal stem cell chondrogenesis. An improved understanding of biomechanically-driven tissue development and maturation of stem cell-based cartilage replacements will hopefully lead to the development of cell-based therapies for cartilage degeneration and disease. PMID:23809493

From Spatial Intelligence to Spatial Competences: The Results of Applied Geo-Research in Italian Schools

ERIC Educational Resources Information Center

Sarno, Emilia

2012-01-01

This contribution explains the connection between spatial intelligence and spatial competences and by indicating how the first is the cognitive matrix of abilities necessary to move in space as well as to represent it. Indeed, two are principal factors involved in the spatial intelligence: orientation and representation. Both are based on a close…

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

PubMed

Kutys, Matthew L; Yamada, Kenneth M

2014-09-01

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

Requirement of vitamin C for cartilage calcification in a differentiating chick limb-bud mesenchymal cell culture.

PubMed

Boskey, A L; Stiner, D; Doty, S B; Binderman, I

1991-01-01

Mesenchymal cells isolated from stage 21-24 chick limb-buds plated in a micro-mass culture differentiate to form chondrocytes and synthesize a calcifiable matrix. In the presence of inorganic phosphate (4 mM), hydroxyapatite mineral deposits around cartilage nodules. Ascorbic acid is, in general, an essential co-factor for extracellular matrix synthesis in culture, since it is required for collagen synthesis. In this study we demonstrate that in the absence of ascorbic acid supplementation in the mesenchymal cell cultures, mineral deposition (indicated by X-ray diffraction, measurement of Ca:hydroxyproline ratio, and 45Ca uptake) does not occur. Concentrations of 10-50 micrograms/ml ascorbate were compared to find the "optimal" concentration for cell mediated mineralization; 25 micrograms/ml was selected as optimal based on matrix appearance at the EM level and the rate of 45Ca uptake. High concentrations of ascorbic acid (greater than 75 micrograms/ml), while increasing the amount of hydroxyproline in the matrix synthesized, caused some cell death and hence less cell-mediated mineralization. This study demonstrates both the need for viable cells and a proper matrix for in vitro cell-mediated mineralization, and shows that varying the concentration of L-ascorbate (vitamin C) in the medium can have a marked effect on mineralization in vitro.

Macromolecular crowding meets oxygen tension in human mesenchymal stem cell culture - A step closer to physiologically relevant in vitro organogenesis

NASA Astrophysics Data System (ADS)

Cigognini, Daniela; Gaspar, Diana; Kumar, Pramod; Satyam, Abhigyan; Alagesan, Senthilkumar; Sanz-Nogués, Clara; Griffin, Matthew; O'Brien, Timothy; Pandit, Abhay; Zeugolis, Dimitrios I.

2016-08-01

Modular tissue engineering is based on the cells’ innate ability to create bottom-up supramolecular assemblies with efficiency and efficacy still unmatched by man-made devices. Although the regenerative potential of such tissue substitutes has been documented in preclinical and clinical setting, the prolonged culture time required to develop an implantable device is associated with phenotypic drift and/or cell senescence. Herein, we demonstrate that macromolecular crowding significantly enhances extracellular matrix deposition in human bone marrow mesenchymal stem cell culture at both 20% and 2% oxygen tension. Although hypoxia inducible factor - 1α was activated at 2% oxygen tension, increased extracellular matrix synthesis was not observed. The expression of surface markers and transcription factors was not affected as a function of oxygen tension and macromolecular crowding. The multilineage potential was also maintained, albeit adipogenic differentiation was significantly reduced in low oxygen tension cultures, chondrogenic differentiation was significantly increased in macromolecularly crowded cultures and osteogenic differentiation was not affected as a function of oxygen tension and macromolecular crowding. Collectively, these data pave the way for the development of bottom-up tissue equivalents based on physiologically relevant developmental processes.

Macromolecular crowding meets oxygen tension in human mesenchymal stem cell culture - A step closer to physiologically relevant in vitro organogenesis

PubMed Central

Cigognini, Daniela; Gaspar, Diana; Kumar, Pramod; Satyam, Abhigyan; Alagesan, Senthilkumar; Sanz-Nogués, Clara; Griffin, Matthew; O’Brien, Timothy; Pandit, Abhay; Zeugolis, Dimitrios I.

2016-01-01

Modular tissue engineering is based on the cells’ innate ability to create bottom-up supramolecular assemblies with efficiency and efficacy still unmatched by man-made devices. Although the regenerative potential of such tissue substitutes has been documented in preclinical and clinical setting, the prolonged culture time required to develop an implantable device is associated with phenotypic drift and/or cell senescence. Herein, we demonstrate that macromolecular crowding significantly enhances extracellular matrix deposition in human bone marrow mesenchymal stem cell culture at both 20% and 2% oxygen tension. Although hypoxia inducible factor - 1α was activated at 2% oxygen tension, increased extracellular matrix synthesis was not observed. The expression of surface markers and transcription factors was not affected as a function of oxygen tension and macromolecular crowding. The multilineage potential was also maintained, albeit adipogenic differentiation was significantly reduced in low oxygen tension cultures, chondrogenic differentiation was significantly increased in macromolecularly crowded cultures and osteogenic differentiation was not affected as a function of oxygen tension and macromolecular crowding. Collectively, these data pave the way for the development of bottom-up tissue equivalents based on physiologically relevant developmental processes. PMID:27478033

Peak picking NMR spectral data using non-negative matrix factorization

PubMed Central

2014-01-01

Background Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments. Results To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments. Conclusions Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap. PMID:24511909

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

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

2017-01-01

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

Cell Encapsulating Biomaterial Regulates Mesenchymal Stromal/Stem Cell Differentiation and Macrophage Immunophenotype

PubMed Central

Cantu, David Antonio; Hematti, Peiman

2012-01-01

Bone marrow mesenchymal stromal/stem cell (MSC) encapsulation within a biomatrix could improve cellular delivery and extend survival and residence time over conventional intravenous administration. Although MSCs modulate monocyte/macrophage (Mø) immunophenotypic properties, little is known about how such interactions are influenced when MSCs are entrapped within a biomaterial. Furthermore, the impact of the cell-encapsulating matrix on MSC multipotency and on Møs, which infiltrate biomaterials, remains poorly understood. Here we elucidate this three-way interaction. The Mø immunophenotype and MSC differentiation were examined with regard to established and experimental collagen-based biomaterials for MSC entrapment. Tumor necrosis factor-α secretion was acutely inhibited at 4 days. MSCs cocultured with Møs demonstrated attenuated chondrocyte differentiation, whereas osteoblast differentiation was enhanced. Adipocyte differentiation was considerably enhanced for MSCs entrapped within the gelatin/polyethylene glycol-based matrix. A better understanding of the effect of cell encapsulation on differentiation potency and immunomodulation of MSCs is essential for MSC-based, biomaterial-enabled therapies. PMID:23197666

Cell-based delivery of glucagon-like peptide-1 using encapsulated mesenchymal stem cells.

PubMed

Wallrapp, Christine; Thoenes, Eric; Thürmer, Frank; Jork, Anette; Kassem, Moustapha; Geigle, Peter

2013-01-01

Glucagon-like peptide-1 (GLP-1) CellBeads are cell-based implants for the sustained local delivery of bioactive factors. They consist of GLP-1 secreting mesenchymal stem cells encapsulated in a spherically shaped immuno-isolating alginate matrix. A highly standardized and reproducible encapsulation method is described for the manufacturing of homogeneous CellBeads. Viability and sustained secretion was shown for the recombinant GLP-1 and the cell endogenous bioactive factors like vascular endothelial growth factor, neurotrophin 3 (NT-3) and glial cell line-derived neurotrophic factor. Manufacturing and quality control is performed in compliance with good manufacturing practice and fulfils all regulatory requirements for human clinical use. GLP-1 CellBeads combine the neuro- and cardioprotective properties of both GLP-1 and mesenchymal stem cells. First promising results were obtained from preclinical studies and an ongoing safety trial in humans but further studies have to prove the overall potential of CellBead technology in cell-based regenerative medicine.

Stress-intensity factors of r-cracks in fiber-reinforced composites under thermal and mechanical loading

NASA Astrophysics Data System (ADS)

Mueller, W. H.; Schmauder, S.

1993-02-01

This paper is concerned with the problem of the calculation of stress-intensity factors at the tips of radial matrix cracks (r-cracks) in fiber-reinforced composites under thermal and/or transverse uniaxial or biaxial mechanical loading. The crack is either located in the immediate vicinity of a single fiber or it terminates at the interface between the fiber and the matrix. The problem is stated and solved numerically within the framework of linear elasticity using Erdogan's integral equation technique. It is shown that the solutions for purely thermal and purely mechanical loading can simply be superimposed in order to obtain the results of the combined loading case. Stress-intensity factors (SIFs) are calculated for various lengths and distances of the crack from the interface for each of these loading conditions. The behavior of the SIFs for cracks growing towards or away from the interface is examined. The role of the elastic mismatch between the fibers and the matrix is emphasized and studied extensively using the so-called Dundurs' parameters. It is shown that an r-crack, which is remotely located from the fiber, can either be stabilized or destabilized depending on both the elastic as well as the thermal mismatch of the fibrous composite. Furthermore, Dundurs' parameters are used to predict the exponent of the singularity of the crack tip elastic field and the behavior of the corresponding SIFs for cracks which terminate at the interface. An analytical solution for the SIFs is derived for all three loading conditions under the assumption that the elastic constants of the matrix and the fiber are equal. It is shown that the analytical solution is in good agreement with the corresponding numerical results. Moreover, another analytical solution from the literature, which is based upon Paris' equation for the calculation of stress-intensity factors, is compared with the numerical results and it is shown to be valid only for extremely short r-cracks touching the interface. The numerical results presented are valid for practical fiber composites with r-cracks close to or terminating at the interface provided the matrix material is brittle and the crack does not interact with other neighboring fibers. They may be applied to predict the transverse mechanical behavior of high strength fiber composites.

[Special application of matrix-assisted laser desorption ionization time-of-flight mass spectrometry in clinical microbiological diagnostics].

PubMed

Nagy, Erzsébet; Abrók, Marianna; Bartha, Noémi; Bereczki, László; Juhász, Emese; Kardos, Gábor; Kristóf, Katalin; Miszti, Cecilia; Urbán, Edit

2014-09-21

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry as a new possibility for rapid identification of bacteria and fungi revolutionized the clinical microbiological diagnostics. It has an extreme importance in the routine microbiological laboratories, as identification of the pathogenic species rapidly will influence antibiotic selection before the final determination of antibiotic resistance of the isolate. The classical methods for identification of bacteria or fungi, based on biochemical tests, are influenced by many environmental factors. The matrix-assisted laser desorption ionization time-of-flight mass spectrometry is a rapid method which is able to identify a great variety of the isolated bacteria and fungi based on the composition of conserved ribosomal proteins. Recently several other applications of the method have also been investigated such as direct identification of pathogens from the positive blood cultures. There are possibilities to identify bacteria from the urine samples in urinary tract infection or from other sterile body fluids. Using selective enrichment broth Salmonella sp from the stool samples can be identified more rapidly, too. The extended spectrum beta-lactamase or carbapenemase production of the isolated bacteria can be also detected by this method helping the antibiotic selection in some cases. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry based methods are suitable to investigate changes in deoxyribonucleic acid or ribonucleic acid, to carry out rapid antibiotic resistance determination or other proteomic analysis. The aim of this paper is to give an overview about present possibilities of using this technique in the clinical microbiological routine procedures.

Engineering growth factors for regenerative medicine applications.

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

Mitchell, Aaron C.; Briquez, Priscilla S.; Hubbell, Jeffrey A.

Growth factors are important morphogenetic proteins that instruct cell behavior and guide tissue repair and renewal. Although their therapeutic potential holds great promise in regenerative medicine applications, translation of growth factors into clinical treatments has been hindered by limitations including poor protein stability, low recombinant expression yield, and suboptimal efficacy. This review highlights current tools, technologies, and approaches to design integrated and effective growth factor-based therapies for regenerative medicine applications. The first section describes rational and combinatorial protein engineering approaches that have been utilized to improve growth factor stability, expression yield, biodistribution, and serum half-life, or alter their cell traffickingmore » behavior or receptor binding affinity. The second section highlights elegant biomaterial-based systems, inspired by the natural extracellular matrix milieu, that have been developed for effective spatial and temporal delivery of growth factors to cell surface receptors. Although appearing distinct, these two approaches are highly complementary and involve principles of molecular design and engineering to be considered in parallel when developing optimal materials for clinical applications.« less

An inflammation-responsive transcription factor in the pathophysiology of osteoarthritis.

PubMed

Ray, Alpana; Ray, Bimal K

2008-01-01

A number of risk factors including biomechanical stress on the articular cartilage imposed by joint overloading due to obesity, repetitive damage of the joint tissues by injury of the menisci and ligaments, and abnormal joint alignment play a significant role in the onset of osteoarthritis (OA). Genetic predisposition can also lead to the formation of defective cartilage matrix because of abnormal gene expression in the cartilage-specific cells. Another important biochemical event in OA is the consequence of inflammation. It has been shown that synovial inflammation triggers the synthesis of biological stimuli such as cytokines and growth factors which subsequently reach the chondrocyte cells of the articular cartilage activating inflammatory events in the chondrocytes leading to cartilage destruction. In addition to cartilage degradation, hypertrophy of the subchondral bone and osteophyte formation at the joint margins also takes place in OA. Both processes involve abnormal expression of a number of genes including matrix metalloproteinases (MMPs) for cartilage degradation and those associated with bone formation during osteophyte development. To address how diverse groups of genes are activated in OA chondrocyte, we have studied their induction mechanism. We present evidence for abundant expression of an inflammation-responsive transcription factor, SAF-1, in moderate to severely damaged OA cartilage tissues. In contrast, cells in normal cartilage matrix contain very low level of SAF-1 protein. SAF-1 is identified as a major regulator of increased synthesis of MMP-1 and -9 and pro-angiogenic factor, vascular endothelial growth factor (VEGF). While VEGF by stimulating angiogenesis plays a key role in new bone formation in osteophyte, increase of MMP-1 and -9 is instrumental for cartilage erosion in the pathogenesis of OA. Increased expression in degenerated cartilage matrix and in the osteophytes indicate for a key regulatory role of SAF-1 in directing catabolic matrix degrading and anabolic matrix regenerating activities.

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

PubMed Central

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

2016-01-01

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

Emulation and design of terahertz reflection-mode confocal scanning microscopy based on virtual pinhole

NASA Astrophysics Data System (ADS)

Yang, Yong-fa; Li, Qi

2014-12-01

In the practical application of terahertz reflection-mode confocal scanning microscopy, the size of detector pinhole is an important factor that determines the performance of spatial resolution characteristic of the microscopic system. However, the use of physical pinhole brings some inconvenience to the experiment and the adjustment error has a great influence on the experiment result. Through reasonably selecting the parameter of matrix detector virtual pinhole (VPH), it can efficiently approximate the physical pinhole. By using this approach, the difficulty of experimental calibration is reduced significantly. In this article, an imaging scheme of terahertz reflection-mode confocal scanning microscopy that is based on the matrix detector VPH is put forward. The influence of detector pinhole size on the axial resolution of confocal scanning microscopy is emulated and analyzed. Then, the parameter of VPH is emulated when the best axial imaging performance is reached.

Multifractal-based nuclei segmentation in fish images.

PubMed

Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

2017-09-01

The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

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.

The Asset-Based Context Matrix: A Tool for Assessing Children's Learning Opportunities and Participation in Natural Environments

ERIC Educational Resources Information Center

Wilson, Linda L.; Mott, Donald W.; Batman, Deb

2004-01-01

This article provides a description of the "Asset-Based Context Matrix" (ABC Matrix). The ABC Matrix is an assessment tool for designing interventions for children in natural learning environments. The tool is based on research evidence indicating that children's learning is enhanced in contextually meaningful learning environments. The ABC Matrix…

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'.

Contrasting recovery patterns of 2, 4-dinitrophenylhydrazones (DNPH) derivative of carbonyls between liquid and gas phase standards using HPLC-based analysis

NASA Astrophysics Data System (ADS)

Saha, Subbroto Kumar; Jo, Sang-Hee; Song, Hee-Nam; Brown, Richard J. C.; Kim, Ki-Hyun

2012-12-01

This study evaluates the relative recovery (RR) of five different carbonyls (CCs) (i.e., acetaldehyde, propionaldehyde, butyraldehyde, isovaleraldehyde, and valeraldehyde) following their reaction as 2, 4-dinitrophenylhydrazine (DNPH) derivatives when using gas phase and liquid phase standards. To this end, relative efficiency of CC-DNPH derivatization is compared between two liquid-phase standards (commercially available vs. lab made mixture) and between liquid and gas-phase standard. If the results are compared in terms of response factors (RF) derived for five carbonyls from all different standard phases, the recovery of gaseous CC standard was distinguished from that of liquid counterparts. The RR of the heavier carbonyls (propionaldehyde, butyraldehyde, isovaleraldehyde, and valeraldehyde) was approximately 60% low relative to their liquid counterparts; however, it was not the case for the lighter carbonyls (acetaldehyde) with the RR of ˜92%. This study thus suggests that the quantification of heavy carbonyls in ambient air, unless made by standards of the same matrix (i.e., gas phase) or compensated by the proper correction factor, may be subject to a large bias due to difference in derivatization reaction efficiency between matrix types. Hence, consideration of the matrix effect at the calibration stage is of particular importance to measure CC quantitatively.

[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.

Correction of photoresponse nonuniformity for matrix detectors based on prior compensation for their nonlinear behavior.

PubMed

Ferrero, Alejandro; Campos, Joaquin; Pons, Alicia

2006-04-10

What we believe to be a novel procedure to correct the nonuniformity that is inherent in all matrix detectors has been developed and experimentally validated. This correction method, unlike other nonuniformity-correction algorithms, consists of two steps that separate two of the usual problems that affect characterization of matrix detectors, i.e., nonlinearity and the relative variation of the pixels' responsivity across the array. The correction of the nonlinear behavior remains valid for any illumination wavelength employed, as long as the nonlinearity is not due to power dependence of the internal quantum efficiency. This method of correction of nonuniformity permits the immediate calculation of the correction factor for any given power level and for any illuminant that has a known spectral content once the nonuniform behavior has been characterized for a sufficient number of wavelengths. This procedure has a significant advantage compared with other traditional calibration-based methods, which require that a full characterization be carried out for each spectral distribution pattern of the incident optical radiation. The experimental application of this novel method has achieved a 20-fold increase in the uniformity of a CCD array for response levels close to saturation.

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

PubMed

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

2014-12-30

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

Transcriptomic differences between day and night in Acropora millepora provide new insights into metabolite exchange and light-enhanced calcification in corals.

PubMed

Bertucci, A; Forêt, S; Ball, E E; Miller, D J

2015-09-01

The evolutionary success of reef-building corals is often attributed to their symbiotic relationship with photosynthetic dinoflagellates of the genus Symbiodinium, but metabolic interactions between the partners and the molecular bases of light-enhanced calcification (LEC) are not well understood. Here, the metabolic bases of the interaction between the coral Acropora millepora and its dinoflagellate symbiont were investigated by comparing gene expression levels under light and dark conditions at the whole transcriptome level. Among the 497 differentially expressed genes identified, a suite of genes involved in cholesterol transport was found to be upregulated under light conditions, confirming the significance of this compound in the coral symbiosis. Although ion transporters likely to have roles in calcification were not differentially expressed in this study, expression levels of many genes associated with skeletal organic matrix composition and organization were higher in light conditions. This implies that the rate of organic matrix synthesis is one factor limiting calcification at night. Thus, LEC during the day is likely to be a consequence of increases in both matrix synthesis and the supply of precursor molecules as a result of photosynthetic activity. © 2015 John Wiley & Sons Ltd.

10Gbps 2D MGC OCDMA Code over FSO Communication System

NASA Astrophysics Data System (ADS)

Professor Urmila Bhanja, Associate, Dr.; Khuntia, Arpita; Alamasety Swati, (Student

2017-08-01

Currently, wide bandwidth signal dissemination along with low latency is a leading requisite in various applications. Free space optical wireless communication has introduced as a realistic technology for bridging the gap in present high data transmission fiber connectivity and as a provisional backbone for rapidly deployable wireless communication infrastructure. The manuscript highlights on the implementation of 10Gbps SAC-OCDMA FSO communications using modified two dimensional Golomb code (2D MGC) that possesses better auto correlation, minimum cross correlation and high cardinality. A comparison based on pseudo orthogonal (PSO) matrix code and modified two dimensional Golomb code (2D MGC) is developed in the proposed SAC OCDMA-FSO communication module taking different parameters into account. The simulative outcome signifies that the communication radius is bounded by the multiple access interference (MAI). In this work, a comparison is made in terms of bit error rate (BER), and quality factor (Q) based on modified two dimensional Golomb code (2D MGC) and PSO matrix code. It is observed that the 2D MGC yields better results compared to the PSO matrix code. The simulation results are validated using optisystem version 14.

Color normalization of histology slides using graph regularized sparse NMF

NASA Astrophysics Data System (ADS)

Sha, Lingdao; Schonfeld, Dan; Sethi, Amit

2017-03-01

Computer based automatic medical image processing and quantification are becoming popular in digital pathology. However, preparation of histology slides can vary widely due to differences in staining equipment, procedures and reagents, which can reduce the accuracy of algorithms that analyze their color and texture information. To re- duce the unwanted color variations, various supervised and unsupervised color normalization methods have been proposed. Compared with supervised color normalization methods, unsupervised color normalization methods have advantages of time and cost efficient and universal applicability. Most of the unsupervised color normaliza- tion methods for histology are based on stain separation. Based on the fact that stain concentration cannot be negative and different parts of the tissue absorb different stains, nonnegative matrix factorization (NMF), and particular its sparse version (SNMF), are good candidates for stain separation. However, most of the existing unsupervised color normalization method like PCA, ICA, NMF and SNMF fail to consider important information about sparse manifolds that its pixels occupy, which could potentially result in loss of texture information during color normalization. Manifold learning methods like Graph Laplacian have proven to be very effective in interpreting high-dimensional data. In this paper, we propose a novel unsupervised stain separation method called graph regularized sparse nonnegative matrix factorization (GSNMF). By considering the sparse prior of stain concentration together with manifold information from high-dimensional image data, our method shows better performance in stain color deconvolution than existing unsupervised color deconvolution methods, especially in keeping connected texture information. To utilized the texture information, we construct a nearest neighbor graph between pixels within a spatial area of an image based on their distances using heat kernal in lαβ space. The representation of a pixel in the stain density space is constrained to follow the feature distance of the pixel to pixels in the neighborhood graph. Utilizing color matrix transfer method with the stain concentrations found using our GSNMF method, the color normalization performance was also better than existing methods.

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

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

NASA Astrophysics Data System (ADS)

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

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

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

NASA Astrophysics Data System (ADS)

Thornhill, D. A.; Williams, A. E.; Onasch, T. B.; Wood, E.; Herndon, S. C.; Kolb, C. E.; Knighton, W. B.; Zavala, M.; Molina, L. T.; Marr, L. C.

2009-12-01

The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are responsible for 97% of mobile source emissions of CO, 22% of NOx, 95-97% of aromatics, 72-85% of carbonyls, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction. Nevertheless, the fuel-based inventory suggests that mobile source emissions of CO and NOx are overstated in the official inventory while emissions of VOCs may be understated. For NOx, the fuel-based inventory is lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory.

Fast polar decomposition of an arbitrary matrix

NASA Technical Reports Server (NTRS)

Higham, Nicholas J.; Schreiber, Robert S.

1988-01-01

The polar decomposition of an m x n matrix A of full rank, where m is greater than or equal to n, can be computed using a quadratically convergent algorithm. The algorithm is based on a Newton iteration involving a matrix inverse. With the use of a preliminary complete orthogonal decomposition the algorithm can be extended to arbitrary A. How to use the algorithm to compute the positive semi-definite square root of a Hermitian positive semi-definite matrix is described. A hybrid algorithm which adaptively switches from the matrix inversion based iteration to a matrix multiplication based iteration due to Kovarik, and to Bjorck and Bowie is formulated. The decision when to switch is made using a condition estimator. This matrix multiplication rich algorithm is shown to be more efficient on machines for which matrix multiplication can be executed 1.5 times faster than matrix inversion.

MATRIX METALLOPROTEINS (MMP)-MEDIATED PHOSPHORYLATION OF THE EPIDERMAL GROWTH FACTOR RECEPTOR (EGFR) IN HUMAN AIRWAY EPITHELIAL CELLS (HAEC) EXPOSED TO ZINC (ZN)

EPA Science Inventory

Matrix Metalloproteinase (MMP)-Mediated Phosphorylation of The Epidermal Growth Factor Receptor (EGFR) in Human Airway Epithelial Cells (HAEC) Exposed to Zinc (Zn)
Weidong Wu, James M. Samet, Robert Silbajoris, Lisa A. Dailey, Lee M. Graves, and Philip A. Bromberg
Center fo...

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

ERIC Educational Resources Information Center

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

2015-01-01

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

SOURCE APPORTIONMENT OF PM 2.5 AND CARBON IN SEATTLE USING CHEMICAL MASS BALANCE AND POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

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

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

ERIC Educational Resources Information Center

Beauducel, Andre

2007-01-01

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

Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

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

Peptide-matrix-mediated gene transfer of an oxygen-insensitive hypoxia-inducible factor-1alpha variant for local induction of angiogenesis.

PubMed

Trentin, Diana; Hall, Heike; Wechsler, Sandra; Hubbell, Jeffrey A

2006-02-21

Hypoxia-inducible factor (HIF) constitutes a target in therapeutic angiogenesis. HIF-1alpha functions as a sensor of hypoxia and induces expression of vascular endothelial growth factor (VEGF), which then induces angiogenesis. To explore the potential of HIF-1alpha gene therapy in stimulating wound healing, we delivered a gene encoding a stabilized form of HIF-1alpha, lacking the oxygen-sensitive degradation domain, namely HIF-1alpha deltaODD, by using a previously characterized peptide-based gene delivery vector in fibrin as a surgical matrix. The peptide vector consisted of multiple domains: (i) A cysteine-flanked lysine hexamer provided DNA interactions that were stable extracellularly but destabilized intracellularly after reduction of the formed disulfide bonds. This DNA-binding domain was fused to either (ii) a fibrin-binding peptide for entrapment within the matrix or (iii) a nuclear localization sequence for efficient nuclear targeting. The HIF-1alpha deltaODD gene was expressed and translocated to the nucleus under normoxic conditions, leading to up-regulation of vascular endothelial growth factor (VEGF)-A165 mRNA and protein levels in vitro. When the peptide-DNA nanoparticles entrapped in fibrin matrices were applied to full-thickness dermal wounds in the mouse (10 microg per wound in 30 microl of fibrin), angiogenesis was increased comparably strongly to that induced by VEGF-A165 protein (1.25 microg per wound in 30 microl of fibrin). However, the maturity of the vessels induced by HIF-1alpha deltaODD was significantly higher than that induced by VEGF-A165 protein, as shown by stabilization of the neovessels with smooth muscle. Nonviral, local administration of this potent angiogenesis-inducing gene by using this peptide vector represents a powerful approach in tissue engineering and therapeutic angiogenesis.

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.

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.

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.

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.

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

PubMed

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

2016-03-01

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

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

PubMed

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

2009-01-01

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

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

3D Progressive Damage Modeling for Laminated Composite Based on Crack Band Theory and Continuum Damage Mechanics

NASA Technical Reports Server (NTRS)

Wang, John T.; Pineda, Evan J.; Ranatunga, Vipul; Smeltzer, Stanley S.

2015-01-01

A simple continuum damage mechanics (CDM) based 3D progressive damage analysis (PDA) tool for laminated composites was developed and implemented as a user defined material subroutine to link with a commercially available explicit finite element code. This PDA tool uses linear lamina properties from standard tests, predicts damage initiation with an easy-to-implement Hashin-Rotem failure criteria, and in the damage evolution phase, evaluates the degradation of material properties based on the crack band theory and traction-separation cohesive laws. It follows Matzenmiller et al.'s formulation to incorporate the degrading material properties into the damaged stiffness matrix. Since nonlinear shear and matrix stress-strain relations are not implemented, correction factors are used for slowing the reduction of the damaged shear stiffness terms to reflect the effect of these nonlinearities on the laminate strength predictions. This CDM based PDA tool is implemented as a user defined material (VUMAT) to link with the Abaqus/Explicit code. Strength predictions obtained, using this VUMAT, are correlated with test data for a set of notched specimens under tension and compression loads.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

Matrix modulation and heart failure: new concepts question old beliefs.

PubMed

Deschamps, Anne M; Spinale, Francis G

2005-05-01

Myocardial remodeling is a complex process involving several molecular and cellular factors. Extracellular matrix has been implicated in the remodeling process. Historically, the myocardial extracellular matrix was thought to serve solely as a means to align cells and provide structure to the tissue. Although this is one of its important functions, evidence suggests that the extracellular matrix plays a complex and divergent role in influencing cell behavior. This paper characterizes some of the notable studies on this dynamic entity and on adverse myocardial remodeling that have been published over the past year, which further question the belief that the extracellular matrix is a static structure. Progress has been made in understanding how the extracellular matrix is operative in the three major conditions (myocardial infarction, left ventricular hypertrophy due to overload, and dilated cardiomyopathy) that involve myocardial remodeling. Several studies have examined plasma profiles of matrix metalloproteinases and tissue inhibitors of matrix metalloproteinases following myocardial infarction and during left ventricular hypertrophy as surrogate markers of remodeling/remodeled myocardium. It has been demonstrated that bioactive signaling molecules and growth factors, proteases, and structural proteins influence cell-matrix interactions in the context of left ventricular hypertrophy. Finally, studies that either removed or added tissue inhibitor of metalloproteinases species in the myocardium demonstrated the importance of this regulatory protein in the remodeling process. Understanding the cellular and molecular triggers that in turn give rise to changes in the extracellular matrix could provide opportunities to modify the remodeling process.

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.

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.

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.

The Effect of Multi Wall Carbon Nanotubes on Some Physical Properties of Epoxy Matrix

NASA Astrophysics Data System (ADS)

Al-Saadi, Tagreed M.; hammed Aleabi, Suad; Al-Obodi, Entisar E.; Abdul-Jabbar Abbas, Hadeel

2018-05-01

This research involves using epoxy resin as a matrix for making a composite material, while the multi wall carbon nanotubes (MWNCTs) is used as a reinforcing material with different fractions (0.0,0.02, 0.04, 0.06) of the matrix weight. The mechanical ( hardness ), electrical ( dielectric constant, dielectric loss factor, dielectric strength, electrical conductivity ), and thermal properties (thermal conductivity ) were studied. The results showed the increase of hardness, thermal conductivity, electrical conductivity and break down strength with the increase of MWCNT concentration, but the behavior of dielectric loss factor and dielectric constant is opposite that.

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.

Solute Migration from the Aquifer Matrix into a Solution Conduit and the Reverse.

PubMed

Li, Guangquan; Field, Malcolm S

2016-09-01

A solution conduit has a permeable wall allowing for water exchange and solute transfer between the conduit and its surrounding aquifer matrix. In this paper, we use Laplace Transform to solve a one-dimensional equation constructed using the Euler approach to describe advective transport of solute in a conduit, a production-value problem. Both nonuniform cross-section of the conduit and nonuniform seepage at the conduit wall are considered in the solution. Physical analysis using the Lagrangian approach and a lumping method is performed to verify the solution. Two-way transfer between conduit water and matrix water is also investigated by using the solution for the production-value problem as a first-order approximation. The approximate solution agrees well with the exact solution if dimensionless travel time in the conduit is an order of magnitude smaller than unity. Our analytical solution is based on the assumption that the spatial and/or temporal heterogeneity in the wall solute flux is the dominant factor in the spreading of spring-breakthrough curves, and conduit dispersion is only a secondary mechanism. Such an approach can lead to the better understanding of water exchange and solute transfer between conduits and aquifer matrix. Euler and Lagrangian approaches are used to solve transport in conduit. Two-way transfer between conduit and matrix is investigated. The solution is applicable to transport in conduit of persisting solute from matrix. © 2016, National Ground Water Association.

Osteoarthritis as a disease of the cartilage pericellular matrix.

PubMed

Guilak, Farshid; Nims, Robert; Dicks, Amanda; Wu, Chia-Lung; Meulenbelt, Ingrid

2018-05-22

Osteoarthritis is a painful joint disease characterized by progressive degeneration of the articular cartilage as well as associated changes to the subchondral bone, synovium, and surrounding joint tissues. While the effects of osteoarthritis on the cartilage extracellular matrix (ECM) have been well recognized, it is now becoming apparent that in many cases, the onset of the disease may be initially reflected in the matrix region immediately surrounding the chondrocytes, termed the pericellular matrix (PCM). Growing evidence suggests that the PCM - which along with the enclosed chondrocytes are termed the "chondron" - acts as a critical transducer or "filter" of biochemical and biomechanical signals for the chondrocyte, serving to help regulate the homeostatic balance of chondrocyte metabolic activity in response to environmental signals. Indeed, it appears that alterations in PCM properties and cell-matrix interactions, secondary to genetic, epigenetic, metabolic, or biomechanical stimuli, could in fact serve as initiating or progressive factors for osteoarthritis. Here, we discuss recent advances in the understanding of the role of the PCM, with an emphasis on the reciprocity of changes that occur in this matrix region with disease, as well as how alterations in PCM properties could serve as a driver of ECM-based diseases such as osteoarthritis. Further study of the structure, function, and composition of the PCM in normal and diseased conditions may provide new insights into the understanding of the pathogenesis of osteoarthritis, and presumably new therapeutic approaches for this disease. Copyright © 2017. Published by Elsevier B.V.

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

PubMed

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

2016-07-01

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

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

Fast, J; Zhang, Q; Tilp, A

Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.

Application of the matrix exponential kernel

NASA Technical Reports Server (NTRS)

Rohach, A. F.

1972-01-01

A point matrix kernel for radiation transport, developed by the transmission matrix method, has been used to develop buildup factors and energy spectra through slab layers of different materials for a point isotropic source. Combinations of lead-water slabs were chosen for examples because of the extreme differences in shielding properties of these two materials.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.

1989-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Diagrammatic technique for calculating matrix elements of collective operators in superradiance. [eigenstates for N two-level atom systems

NASA Technical Reports Server (NTRS)

Lee, C. T.

1975-01-01

Adopting the so-called genealogical construction, one can express the eigenstates of collective operators corresponding to a specified mode for an N-atom system in terms of those for an (N-1) atom system. Using these Dicke states as bases and using the Wigner-Eckart theorem, a matrix element of a collective operator of an arbitrary mode can be written as the product of an m-dependent factor and an m-independent reduced matrix element (RME). A set of recursion formulas for the RME is obtained. A graphical representation of the RME on the branching diagram for binary irreducible representations of permutation groups is then introduced. This gives a simple and systematic way of calculating the RME. This method is especially useful when the cooperation number r is close to N/2, where almost exact asymptotic expressions can be obtained easily. The result shows explicity the geometry dependence of superradiance and the relative importance of r-conserving and r-nonconserving processes.

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.

Acid-Base and the Skeleton

NASA Astrophysics Data System (ADS)

Bushinsky, David A.

2008-09-01

Chronic metabolic acidosis increases urine calcium (Ca) excretion in the absence of a concomitant increase in intestinal Ca absorption resulting in a net loss of total body. The source of this additional urine Ca is almost certainly the skeleton, the primary reservoir of body Ca. In vitro metabolic acidosis, modeled as a primary reduction in medium bicarbonate concentration, acutely (<24 h) stimulates Ca efflux primarily through physicochemical mineral dissolution while at later time periods (>24 h) cell-mediated mechanisms predominate. In cultured neonatal mouse calvariae, acidosis-induced, cell-mediated Ca efflux is mediated by effects on both osteoblasts and osteoclasts. Metabolic acidosis inhibits extracellular matrix production by osteoblasts, as determined by measurement of collagen levels and levels for the non-collagenous matrix proteins osteopontin and matrix gla protein. Metabolic acidosis upregulates osteoblastic expression of RANKL (Receptor Activator of NFκB Ligand), an important osteoclastogenic and osteoclast-activating factor. Acidosis also increases osteoclastic activity as measured by release of β-glucuronidase, an enzyme whose secretion correlates with osteoclast-mediated bone resorption.

Convergence analysis of modulus-based matrix splitting iterative methods for implicit complementarity problems.

PubMed

Wang, An; Cao, Yang; Shi, Quan

2018-01-01

In this paper, we demonstrate a complete version of the convergence theory of the modulus-based matrix splitting iteration methods for solving a class of implicit complementarity problems proposed by Hong and Li (Numer. Linear Algebra Appl. 23:629-641, 2016). New convergence conditions are presented when the system matrix is a positive-definite matrix and an [Formula: see text]-matrix, respectively.

Extending the range of real time density matrix renormalization group simulations

NASA Astrophysics Data System (ADS)

Kennes, D. M.; Karrasch, C.

2016-03-01

We discuss a few simple modifications to time-dependent density matrix renormalization group (DMRG) algorithms which allow to access larger time scales. We specifically aim at beginners and present practical aspects of how to implement these modifications within any standard matrix product state (MPS) based formulation of the method. Most importantly, we show how to 'combine' the Schrödinger and Heisenberg time evolutions of arbitrary pure states | ψ 〉 and operators A in the evaluation of 〈A〉ψ(t) = 〈 ψ | A(t) | ψ 〉 . This includes quantum quenches. The generalization to (non-)thermal mixed state dynamics 〈A〉ρ(t) =Tr [ ρA(t) ] induced by an initial density matrix ρ is straightforward. In the context of linear response (ground state or finite temperature T > 0) correlation functions, one can extend the simulation time by a factor of two by 'exploiting time translation invariance', which is efficiently implementable within MPS DMRG. We present a simple analytic argument for why a recently-introduced disentangler succeeds in reducing the effort of time-dependent simulations at T > 0. Finally, we advocate the python programming language as an elegant option for beginners to set up a DMRG code.

Occupational risk factors for urothelial carcinoma: agent-specific results from a case-control study in Germany. MURC Study Group. Multicenter Urothelial and Renal Cancer.

PubMed

Pesch, B; Haerting, J; Ranft, U; Klimpel, A; Oelschlägel, B; Schill, W

2000-04-01

This multicentre population-based case-control study was conducted to estimate the urothelial cancer risk for occupational exposure to aromatic amines, polycyclic aromatic hydrocarbons (PAH), and chlorinated hydrocarbons besides other suspected risk factors. In a population-based multicentre study, 1035 incident urothelial cancer cases and 4298 controls matched for region, sex, and age were interviewed between 1991 and 1995 for their occupational history and lifestyle habits. Exposure to the agents under study was self-assessed as well as expert-rated with two job-exposure matrices and a job task-exposure matrix. Conditional logistic regression was used to calculate smoking adjusted odds ratios (OR) and to control for study centre and age. Urothelial cancer risk following exposure to aromatic amines was only slightly elevated. Among males, substantial exposures to PAH as well as to chlorinated solvents and their corresponding occupational settings were associated with significantly elevated risks after adjustment for smoking (PAH exposure, assessed with a job-exposure matrix: OR = 1.6, 95% CI: 1.1-2.3, exposure to chlorinated solvents, assessed with a job task-exposure matrix: OR = 1.8, 95% CI: 1.2-2.6). Metal degreasing showed an elevated urothelial cancer risk among males (OR = 2.3, 95% CI: 1.4-3.8). In females also, exposure to chlorinated solvents indicated a urothelial cancer risk. Because of small numbers the risk evaluation for females should be treated with caution. Occupational exposure to aromatic amines could not be shown to be as strong a risk factor for urothelial carcinomas as in the past. A possible explanation for this finding is the reduction in exposure over the last 50 years. Our results strengthen the evidence that PAH may have a carcinogenic potential for the urothelium. Furthermore, our results indicate a urothelial cancer risk for the use of chlorinated solvents.

Expression Levels of Myostatin and Matrix Metalloproteinase 14 mRNAs in Uterine Leiomyoma are Correlated With Dysmenorrhea.

PubMed

Tsigkou, Anastasia; Reis, Fernando M; Ciarmela, Pasquapina; Lee, Meng H; Jiang, Bingjie; Tosti, Claudia; Shen, Fang-Rong; Shi, Zhendan; Chen, You-Guo; Petraglia, Felice

2015-12-01

Uterine leiomyoma is the most common benign neoplasm of female reproductive system, found in about 50% of women in reproductive age. The mechanisms of leiomyoma growth include cell proliferation, which is modulated by growth factors, and deposition of extracellular matrix (ECM). Activin A and myostatin are growth factors that play a role in proliferation of leiomyoma cells. Matrix metalloproteinases (MMPs) are known for their ability to remodel the ECM in different biological systems. The aim of this study was to evaluate the expression levels of activin βA-subunit, myostatin, and MMP14 messenger RNAs (mRNAs) in uterine leiomyomas and the possible correlation of these factors with clinical features of the disease. Matrix metalloproteinase 14 was highly expressed in uterine leiomyoma and correlated with myostatin and activin A mRNA expression. Moreover, MMP14 and myostatin mRNA expression correlated significantly and directly with the intensity of dysmenorrhea. Overall, the present findings showed that MMP14 mRNA is highly expressed in uterine leiomyoma, where it correlates with the molecular expression of growth factors and is further increased in cases of intense dysmenorrhea. © The Author(s) 2015.

Implementation of biological tissue Mueller matrix for polarization-sensitive optical coherence tomography based on LabVIEW

NASA Astrophysics Data System (ADS)

Lin, Yongping; Zhang, Xiyang; He, Youwu; Cai, Jianyong; Li, Hui

2018-02-01

The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.

Generation of Viable Cell and Biomaterial Patterns by Laser Transfer

NASA Astrophysics Data System (ADS)

Ringeisen, Bradley

2001-03-01

In order to fabricate and interface biological systems for next generation applications such as biosensors, protein recognition microarrays, and engineered tissues, it is imperative to have a method of accurately and rapidly depositing different active biomaterials in patterns or layered structures. Ideally, the biomaterial structures would also be compatible with many different substrates including technologically relevant platforms such as electronic circuits or various detection devices. We have developed a novel laser-based technique, termed matrix assisted pulsed laser evaporation direct write (MAPLE DW), that is able to direct write patterns and three-dimensional structures of numerous biologically active species ranging from proteins and antibodies to living cells. Specifically, we have shown that MAPLE DW is capable of forming mesoscopic patterns of living prokaryotic cells (E. coli bacteria), living mammalian cells (Chinese hamster ovaries), active proteins (biotinylated bovine serum albumin, horse radish peroxidase), and antibodies specific to a variety of classes of cancer related proteins including intracellular and extracellular matrix proteins, signaling proteins, cell cycle proteins, growth factors, and growth factor receptors. In addition, patterns of viable cells and active biomolecules were deposited on different substrates including metals, semiconductors, nutrient agar, and functionalized glass slides. We will present an explanation of the laser-based transfer mechanism as well as results from our recent efforts to fabricate protein recognition microarrays and tissue-based microfluidic networks.

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

PubMed Central

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

1993-01-01

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

Osteoblastic differentiation of human stem cells derived from bone marrow and periodontal ligament under the effect of enamel matrix derivative and transforming growth factor-beta.

PubMed

Houshmand, Behzad; Behnia, Hossein; Khoshzaban, Ahad; Morad, Golnaz; Behrouzi, Gholamreza; Dashti, Seyedeh Ghazaleh; Khojasteh, Arash

2013-01-01

To increase the understanding of the applicability of biomaterials and growth factors in enhancing stem cell-based bone regeneration modalities, this study evaluated the effects of enamel matrix derivative (EMD) and recombinant human transforming growth factor-beta (rhTGF-β) on osteoblastic differentiation of human bone marrow mesenchymal stem cells (hBMSCs) as well as human periodontal ligament stem cells (hPDLSCs). hBMSCs and hPDLSCs were obtained, and identification of stem cell surface markers was performed according to the criteria of the International Society for Cellular Therapy. Each group of stem cells was separately treated with a serial dilution of EMD (10, 50, and 100 μg/mL) or rhTGF-β (10 ng/mL). Osteoblastic differentiation was examined through in vitro matrix mineralization by alizarin red staining, and mRNA expression of osteopontin and osteonectin was determined by quantitative reverse-transcriptase polymerase chain reaction. hPDLSCs were further assessed for osteocalcin mRNA expression. Stem cells cultured in osteogenic medium were employed as a standard positive control group. In none of the experimental groups were bone-related mRNAs detected subsequent to treatment with EMD for 5, 10, and 15 days. Alizarin red staining on day 21 was negative in EMD-treated BMSC and PDLSC cultures. In rhTGF-β-supplemented BMSC culture, expression of osteonectin mRNA was demonstrated on day 15, which was statistically comparable to the positive control group. Nevertheless, extracellular matrix mineralization was inhibited in both groups of stem cells. Within the limitations of this study, it could be concluded that EMD with a concentration of 10, 50, or 100 μg/mL has no appreciable effect on osteoblastic differentiation of BMSCs and PDLSCs. Application of rhTGF-β increased osteonectin mRNA expression in BMSCs. This finding corroborates the hypothesis that TGF-β might be involved in early osteoblastic maturation.

Limited-memory fast gradient descent method for graph regularized nonnegative matrix factorization.

PubMed

Guan, Naiyang; Wei, Lei; Luo, Zhigang; Tao, Dacheng

2013-01-01

Graph regularized nonnegative matrix factorization (GNMF) decomposes a nonnegative data matrix X[Symbol:see text]R(m x n) to the product of two lower-rank nonnegative factor matrices, i.e.,W[Symbol:see text]R(m x r) and H[Symbol:see text]R(r x n) (r < min {m,n}) and aims to preserve the local geometric structure of the dataset by minimizing squared Euclidean distance or Kullback-Leibler (KL) divergence between X and WH. The multiplicative update rule (MUR) is usually applied to optimize GNMF, but it suffers from the drawback of slow-convergence because it intrinsically advances one step along the rescaled negative gradient direction with a non-optimal step size. Recently, a multiple step-sizes fast gradient descent (MFGD) method has been proposed for optimizing NMF which accelerates MUR by searching the optimal step-size along the rescaled negative gradient direction with Newton's method. However, the computational cost of MFGD is high because 1) the high-dimensional Hessian matrix is dense and costs too much memory; and 2) the Hessian inverse operator and its multiplication with gradient cost too much time. To overcome these deficiencies of MFGD, we propose an efficient limited-memory FGD (L-FGD) method for optimizing GNMF. In particular, we apply the limited-memory BFGS (L-BFGS) method to directly approximate the multiplication of the inverse Hessian and the gradient for searching the optimal step size in MFGD. The preliminary results on real-world datasets show that L-FGD is more efficient than both MFGD and MUR. To evaluate the effectiveness of L-FGD, we validate its clustering performance for optimizing KL-divergence based GNMF on two popular face image datasets including ORL and PIE and two text corpora including Reuters and TDT2. The experimental results confirm the effectiveness of L-FGD by comparing it with the representative GNMF solvers.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

PubMed

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

2011-07-01

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

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

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.

Surface presentation of biochemical cues for stem cell expansion - Spatial distribution of growth factors and self-assembly of extracellular matrix

NASA Astrophysics Data System (ADS)

Liu, Xingyu

Despite its great potential applications to stem cell technology and tissue engineering, matrix presentation of biochemical cues such as growth factors and extracellular matrix (ECM) components remains undefined. This is largely due to the difficulty in preserving the bioactivities of signaling molecules and in controlling the spatial distribution, cellular accessibility, molecular orientation and intermolecular assembly of the biochemical cues. This dissertation comprises of two parts that focuses on understanding surface presentation of a growth factor and ECM components, respectively. This dissertation addresses two fundamental questions in stem cell biology using two biomaterials platforms. How does nanoscale distribution of growth factor impact signaling activation and cellular behaviors of adult neural stem cells? How does ECM self-assembly impact human embryonic stem cell survival and proliferation? The first question was addressed by the design of a novel quantitative platform that allows the control of FGF-2 molecular presentation locally as either monomers or clusters when tethered to a polymeric substrate. This substrate-tethered FGF-2 enables a switch-like signaling activation in response to dose titration of FGF-2. This is in contrast to a continuous MAPK activation pattern elicited by soluble FGF-2. Consequently, cell proliferation, and spreading were also consistent with this FGF-2 does-response pattern. We demonstrated that the combination of FGF-2 concentration and its cluster size, rather than concentration alone, serves as the determinants to govern its biological effect on neural stem cells. The second part of this dissertation was inspired by the challenge that hESCs have extremely low clonal efficiency and hESC survival is critically dependent on cell substrate adhesion. We postulated that ECM integrity is a critical factor in preventing hESC anchorage-dependent apoptosis, and that the matrix for feeder-free culture need to be properly assembled in order to mimic the stem cell niche in vivo. First, we established assays that allow high-throughput quantification of hESC proliferation and ECM deposition. Human ESC survival was found to be highly sensitive to ECM assembly, and was improved by at least 20 times on substrates with well-assembled ECM. ECM polymerization alone improves clonal efficiency by at least 20 fold, from less than 0.1% to be 3-5%. This ratio is further improved to greater than 35% when combined with ROCK inhibitor, suggesting ECM polymerization underlines another critical factor in dictating hESC survival and growth. Given that many important signaling molecules including growth factors and extracellular matrix are highly enriched and restricted at the stem cell niche, we anticipate that our investigation into these questions provides better insight into the physiological roles of the stem cell niche components, and helps us to rationally direct stem cell fates in future stem cell-based therapeutic interventions.

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

Tissue Engineering Using Transfected Growth-Factor Genes

NASA Technical Reports Server (NTRS)

Madry, Henning; Langer, Robert S.; Freed, Lisa E.; Trippel, Stephen; Vunjak-Novakovic, Gordana

2005-01-01

A method of growing bioengineered tissues includes, as a major component, the use of mammalian cells that have been transfected with genes for secretion of regulator and growth-factor substances. In a typical application, one either seeds the cells onto an artificial matrix made of a synthetic or natural biocompatible material, or else one cultures the cells until they secrete a desired amount of an extracellular matrix. If such a bioengineered tissue construct is to be used for surgical replacement of injured tissue, then the cells should preferably be the patient s own cells or, if not, at least cells matched to the patient s cells according to a human-leucocyteantigen (HLA) test. The bioengineered tissue construct is typically implanted in the patient's injured natural tissue, wherein the growth-factor genes enhance metabolic functions that promote the in vitro development of functional tissue constructs and their integration with native tissues. If the matrix is biodegradable, then one of the results of metabolism could be absorption of the matrix and replacement of the matrix with tissue formed at least partly by the transfected cells. The method was developed for articular chondrocytes but can (at least in principle) be extended to a variety of cell types and biocompatible matrix materials, including ones that have been exploited in prior tissue-engineering methods. Examples of cell types include chondrocytes, hepatocytes, islet cells, nerve cells, muscle cells, other organ cells, bone- and cartilage-forming cells, epithelial and endothelial cells, connective- tissue stem cells, mesodermal stem cells, and cells of the liver and the pancreas. Cells can be obtained from cell-line cultures, biopsies, and tissue banks. Genes, molecules, or nucleic acids that secrete factors that influence the growth of cells, the production of extracellular matrix material, and other cell functions can be inserted in cells by any of a variety of standard transfection techniques.

Development and evaluation of Ketoprofen sustained release matrix tablet using Hibiscus rosa-sinensis leaves mucilage.

PubMed

Kaleemullah, M; Jiyauddin, K; Thiban, E; Rasha, S; Al-Dhalli, S; Budiasih, S; Gamal, O E; Fadli, A; Eddy, Y

2017-07-01

Currently, the use of natural gums and mucilage is of increasing importance in pharmaceutical formulations as valuable drug excipient. Natural plant-based materials are economic, free of side effects, biocompatible and biodegradable. Therefore, Ketoprofen matrix tablets were formulated by employing Hibiscus rosa-sinensis leaves mucilage as natural polymer and HPMC (K100M) as a synthetic polymer to sustain the drug release from matrix system. Direct compression method was used to develop sustained released matrix tablets. The formulated matrix tablets were evaluated in terms of physical appearance, weight variation, thickness, diameter, hardness, friability and in vitro drug release. The difference between the natural and synthetic polymers was investigated concurrently. Matrix tablets developed from each formulation passed all standard physical evaluation tests. The dissolution studies of formulated tablets revealed sustained drug release up to 24 h compared to the reference drug Apo Keto® SR tablets. The dissolution data later were fitted into kinetic models such as zero order equation, first order equation, Higuchi equation, Hixson Crowell equation and Korsmeyer-Peppas equation to study the release of drugs from each formulation. The best formulations were selected based on the similarity factor ( f 2 ) value of 50% and more. Through the research, it is found that by increasing the polymers concentration, the rate of drug release decreased for both natural and synthetic polymers. The best formulation was found to be F3 which contained 40% Hibiscus rosa-sinensis mucilage polymer and showed comparable dissolution profile to the reference drug with f 2 value of 78.03%. The release kinetics of this formulation has shown to follow non-Fickian type which involved both diffusion and erosion mechanism. Additionally, the statistical results indicated that there was no significant difference (p > 0.05) between the F3 and reference drug in terms of MDT and T50% with p-values of 1.00 and 0.995 respectively.

The effects of isotope-labeled analogs on the LC-IDMS measurement by comparison of ESI responses and matrix effect of melamine, 13C3-melamine, 13C3+15N3-melamine, and 15N3-melamine.

PubMed

Li, Xiu Qin; Zhang, Qing He; Yang, Zong; Li, Hong Mei; Huang, Dong Feng

2017-05-01

In this paper, the effect of isotope-labeled analogs on the liquid chromatography-isotope dilution mass spectrometry (LC-IDMS) measurement was evaluated based on the comparison research of electrospray ionization responses (ESI) and matrix effect of melamine, 13 C 3 -melamine, 13 C 3 + 15 N 3 -melamine, and 15 N 3 -melamine. The isotope-labeled melamines had similar ionization efficiency with melamine in the electrospray ionization source, but the intensity of corresponding quantitative fragment ions had distinctive differences. Based on the density functional theory at the B3LYP/6-311+G** level, this phenomenon was explained very well. The rare cleavage pathways of melamine, which just could be exactly identified by 15 N-labeled melamines, resulted in the difference of quantitative fragment ions between 15 N-labeled melamines and melamine. The interaction of ESI response between melamine and isotope-labeled melamines was investigated using MRM monitor mode. 15 N-labeled melamine had significant ion inter-suppression effect on melamine, while 13 C-labeled melamine had little influence on melamine. Finally, the influence of different isotope-labeled melamines on the LC-IDMS result was evaluated using the IDMS correction factor (θ). Taking the determination of melamine in milk powder as an example, the matrix effects of different isotope-labeled melamines and melamine had notable difference and the impact of this difference on the measurement results depended on the concentrations of analyte and matrix solution. It was worth noting that 15 N 3 -melamine exhibited significant ion suppression to melamine in matrix solution. The deviation of the results from IDMS method might reach 59% using 15 N 3 -melamine as internal standard in special matrix solution. Graphical Abstract The comparison of ESI responses of melamine, 13 C 3 -melamine, 13 C 3 + 15 N 3 -melamine and 15 N 3 -melamine.

On the differentiation matrix for Daubechies-based wavelets on an interval

NASA Technical Reports Server (NTRS)

Jameson, Leland

1993-01-01

The differentiation matrix for a Daubechies-based wavlet basis defined on an interval will be constructed. It will be shown that the differentiation matrix based on the currently available boundary constructions does not maintain the superconvergence encountered under periodic boundary conditions.

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.

Microsphere-based scaffolds encapsulating chondroitin sulfate or decellularized cartilage

PubMed Central

Gupta, Vineet; Tenny, Kevin M; Barragan, Marilyn; Berkland, Cory J; Detamore, Michael S

2016-01-01

Extracellular matrix materials such as decellularized cartilage (DCC) and chondroitin sulfate (CS) may be attractive chondrogenic materials for cartilage regeneration. The goal of the current study was to investigate the effects of encapsulation of DCC and CS in homogeneous microsphere-based scaffolds, and to test the hypothesis that encapsulation of these extracellular matrix materials would induce chondrogenesis of rat bone marrow stromal cells. Four different types of homogeneous scaffolds were fabricated from microspheres of poly(D,L-lactic-co-glycolic acid): Blank (poly(D,L-lactic-co-glycolic acid) only; negative control), transforming growth factor-β3 encapsulated (positive control), DCC encapsulated, and CS encapsulated. These scaffolds were then seeded with rat bone marrow stromal cells and cultured for 6 weeks. The DCC and CS encapsulation altered the morphological features of the microspheres, resulting in higher porosities in these groups. Moreover, the mechanical properties of the scaffolds were impacted due to differences in the degree of sintering, with the CS group exhibiting the highest compressive modulus. Biochemical evidence suggested a mitogenic effect of DCC and CS encapsulation on rat bone marrow stromal cells with the matrix synthesis boosted primarily by the inherently present extracellular matrix components. An important finding was that the cell seeded CS and DCC groups at week 6 had up to an order of magnitude higher glycosaminoglycan contents than their acellular counterparts. Gene expression results indicated a suppressive effect of DCC and CS encapsulation on rat bone marrow stromal cell chondrogenesis with differences in gene expression patterns existing between the DCC and CS groups. Overall, DCC and CS were easily included in microsphere-based scaffolds; however, there is a requirement to further refine their concentrations to achieve the differentiation profiles we seek in vitro. PMID:27358376

PM 10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone

NASA Astrophysics Data System (ADS)

Alleman, Laurent Y.; Lamaison, Laure; Perdrix, Esperanza; Robache, Antoine; Galloo, Jean-Claude

2010-06-01

The elemental composition data of ambient aerosols collected upon selected wind sectors in the highly industrialised harbour of Dunkirk (France) were interpreted using pollution roses, elemental ratios, Enrichment Factors (EF), Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) receptor model. The objective was to identify the possible sources of PM10 aerosols, their respective chemical tracers and to determine their relative contribution at the sampling site. PM10 particles samples were collected from June 2003 to March 2005 in order to analyse up to 35 elements (Ag, Al, As, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Eu, Fe, K, La, Mg, Mn, Mo, Na, Ni, Pb, Rb, S, Sb, Sc, Si, Sm, Sr, Th, Ti, U, V, Zn and Zr) using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES) and ICP-Mass Spectrometry (MS). A significant effort has been made on estimating the total uncertainty of each result by regularly analysing blanks, quality controls and SRM NIST standards. Based on this procedure, a selected set of 24 "robust" elements was compared to the 35-element matrix in order to evaluate the sturdiness of our PMF statistical treatment. Eight source factors were resolved by PCA for all the wind sectors explaining 90% of the total data variance. The PMF results confirmed that eight physically interpretable factors contributed to the ambient particulate pollution at the sampling site: crustal dust (11%), marine aerosols (12%), petrochemistry activities (9.2%), metallurgical sintering plant (8.6%), metallurgical coke plant (12.6%), ferromanganese plant (6.6%), road transport (15%) and a less clearly interpretable profile probably associated to dust resuspension (13%). These weighted contributions against wind direction frequencies demonstrate that industrial sources are the most important contributors to this site (37%) followed by the natural sources (detrital and marine sources) (23%) and the road transport (15%).

Chondrogenic differentiation of growth factor-stimulated precursor cells in cartilage repair tissue is associated with increased HIF-1alpha activity.

PubMed

Gelse, K; Mühle, C; Knaup, K; Swoboda, B; Wiesener, M; Hennig, F; Olk, A; Schneider, H

2008-12-01

To investigate the chondrogenic potential of growth factor-stimulated periosteal cells with respect to the activity of Hypoxia-inducible Factor 1alpha (HIF-1alpha). Scaffold-bound autologous periosteal cells, which had been activated by Insulin-like Growth Factor 1 (IGF-1) or Bone Morphogenetic Protein 2 (BMP-2) gene transfer using both adeno-associated virus (AAV) and adenoviral (Ad) vectors, were applied to chondral lesions in the knee joints of miniature pigs. Six weeks after transplantation, the repair tissues were investigated for collagen type I and type II content as well as for HIF-1alpha expression. The functional role of phosphatidylinositol 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) and mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) signaling on BMP-2/IGF-1-induced HIF-1alpha expression was assessed in vitro by employing specific inhibitors. Unstimulated periosteal cells formed a fibrous extracellular matrix in the superficial zone and a fibrocartilaginous matrix in deep zones of the repair tissue. This zonal difference was reflected by the absence of HIF-1alpha staining in superficial areas, but moderate HIF-1alpha expression in deep zones. In contrast, Ad/AAVBMP-2-stimulated periosteal cells, and to a lesser degree Ad/AAVIGF-1-infected cells, adopted a chondrocyte-like phenotype with strong intracellular HIF-1alpha staining throughout all zones of the repair tissue and formed a hyaline-like matrix. In vitro, BMP-2 and IGF-1 supplementation increased HIF-1alpha protein levels in periosteal cells, which was based on posttranscriptional mechanisms rather than de novo mRNA synthesis, involving predominantly the MEK/ERK pathway. This pilot experimental study on a relatively small number of animals indicated that chondrogenesis by precursor cells is facilitated in deeper hypoxic zones of cartilage repair tissue and is stimulated by growth factors which enhance HIF-1alpha activity.

Migration of bone marrow and cord blood mesenchymal stem cells in vitro is regulated by stromal-derived factor-1-CXCR4 and hepatocyte growth factor-c-met axes and involves matrix metalloproteinases.

PubMed

Son, Bo-Ra; Marquez-Curtis, Leah A; Kucia, Magda; Wysoczynski, Marcin; Turner, A Robert; Ratajczak, Janina; Ratajczak, Mariusz Z; Janowska-Wieczorek, Anna

2006-05-01

Human mesenchymal stem cells (MSCs) are increasingly being considered in cell-based therapeutic strategies for regeneration of various organs/tissues. However, the signals required for their homing and recruitment to injured sites are not yet fully understood. Because stromal-derived factor (SDF)-1 and hepatocyte growth factor (HGF) become up-regulated during tissue/organ damage, in this study we examined whether these factors chemoattract ex vivo-expanded MSCs derived from bone marrow (BM) and umbilical cord blood (CB). Specifically, we investigated the expression by MSCs of CXCR4 and c-met, the cognate receptors of SDF-1 and HGF, and their functionality after early and late passages of MSCs. We also determined whether MSCs express matrix metalloproteinases (MMPs), including membrane type 1 (MT1)-MMP, matrix-degrading enzymes that facilitate the trafficking of hematopoietic stem cells. We maintained expanded BM- or CB-derived MSCs for up to 15-18 passages with monitoring of the expression of 1) various tissue markers (cardiac and skeletal muscle, neural, liver, and endothelial cells), 2) functional CXCR4 and c-met, and 3) MMPs. We found that for up to 15-18 passages, both BM- and CB-derived MSCs 1) express mRNA for cardiac, muscle, neural, and liver markers, as well as the vascular endothelial (VE) marker VE-cadherin; 2) express CXCR4 and c-met receptors and are strongly attracted by SDF-1 and HGF gradients; 3) express MMP-2 and MT1-MMP transcripts and proteins; and 4) are chemo-invasive across the reconstituted basement membrane Matrigel. These in vitro results suggest that the SDF-1-CXCR4 and HGF-c-met axes, along with MMPs, may be involved in recruitment of expanded MSCs to damaged tissues.

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.

Multifunctional and biologically active matrices from multicomponent polymeric solutions

NASA Technical Reports Server (NTRS)

Kiick, Kristi L. (Inventor); Yamaguchi, Nori (Inventor); Rabolt, John (Inventor); Casper, Cheryl (Inventor)

2012-01-01

A functionalized electrospun matrix for the controlled-release of biologically active agents, such as growth factors, is presented. The functionalized matrix comprises a matrix polymer, a compatibilizing polymer and a biomolecule or other small functioning molecule. In certain aspects the electrospun polymer fibers comprise at least one biologically active molecule functionalized with low molecular weight heparin.

Vascular Morphogenesis in the Context of Inflammation: Self-Organization in a Fibrin-Based 3D Culture System.

PubMed

Rüger, Beate M; Buchacher, Tanja; Giurea, Alexander; Kubista, Bernd; Fischer, Michael B; Breuss, Johannes M

2018-01-01

Introduction: New vessel formation requires a continuous and tightly regulated interplay between endothelial cells with cells of the perivascular microenvironment supported by mechanic-physical and chemical cues from the extracellular matrix. Aim: Here we investigated the potential of small fragments of synovial tissue to form de novo vascular structures in the context of inflammation within three dimensional (3D) fibrin-based matrices in vitro , and assessed the contribution of mesenchymal stromal cell (MSC)-immune cell cross-talk to neovascularization considering paracrine signals in a fibrin-based co-culture model. Material and Methods: Synovial tissue fragments from patients with rheumatoid arthritis (RA) and inflammatory osteoarthritis (OA) were cultivated within 3D fibrin matrices for up to 4 weeks. Cellular and structural re-arrangement of the initially acellular matrix were documented by phase contrast microscopy and characterized by confocal laser-scanning microscopy of topographically intact 3D cultures and by immunohistochemistry. MSC-peripheral blood mononuclear cell (PBMC) co-cultures in the 3D fibrin system specifically addressed the influence of perivascular cell interactions to neo-vessel formation in a pro-inflammatory microenvironment. Cytokine levels in the supernatants of cultured explant tissues and co-cultures were evaluated by the Bio-Plex cytokine assay and ELISA. Results: Vascular outgrowth from the embedded tissue into the fibrin matrix was preceded by leukocyte egress from the tissue fragments. Neo-vessels originating from both the embedded sample and from clusters locally formed by emigrated mononuclear cells were consistently associated with CD45 + leukocytes. MSC and PBMC in co-culture formed vasculogenic clusters. Clusters and cells with endothelial phenotype emerging from them, were surrounded by a collagen IV scaffold. No vascular structures were observed in control 3D monocultures of PBMC or MSC. Paracrine signals released by cultured OA tissue fragments corresponded with elevated levels of granulocyte-colony stimulating factor, vascular endothelial growth factor and interleukin-6 secreted by MSC-PBMC co-cultures. Conclusion: Our results show that synovial tissue fragments with immune cell infiltrates have the potential to form new vessels in initially avascular 3D fibrin-based matrices. Cross-talk and cluster formation of MSC with immune cells within the 3D fibrin environment through self-organization and secretion of pro-angiogenic paracrine factors can support neo-vessel growth.

Platelet-Rich Plasma Peptides: Key for Regeneration

PubMed Central

Sánchez-González, Dolores Javier; Méndez-Bolaina, Enrique; Trejo-Bahena, Nayeli Isabel

2012-01-01

Platelet-derived Growth Factors (GFs) are biologically active peptides that enhance tissue repair mechanisms such as angiogenesis, extracellular matrix remodeling, and cellular effects as stem cells recruitment, chemotaxis, cell proliferation, and differentiation. Platelet-rich plasma (PRP) is used in a variety of clinical applications, based on the premise that higher GF content should promote better healing. Platelet derivatives represent a promising therapeutic modality, offering opportunities for treatment of wounds, ulcers, soft-tissue injuries, and various other applications in cell therapy. PRP can be combined with cell-based therapies such as adipose-derived stem cells, regenerative cell therapy, and transfer factors therapy. This paper describes the biological background of the platelet-derived substances and their potential use in regenerative medicine. PMID:22518192

Interval-valued intuitionistic fuzzy matrix games based on Archimedean t-conorm and t-norm

NASA Astrophysics Data System (ADS)

Xia, Meimei

2018-04-01

Fuzzy game theory has been applied in many decision-making problems. The matrix game with interval-valued intuitionistic fuzzy numbers (IVIFNs) is investigated based on Archimedean t-conorm and t-norm. The existing matrix games with IVIFNs are all based on Algebraic t-conorm and t-norm, which are special cases of Archimedean t-conorm and t-norm. In this paper, the intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm are employed to aggregate the payoffs of players. To derive the solution of the matrix game with IVIFNs, several mathematical programming models are developed based on Archimedean t-conorm and t-norm. The proposed models can be transformed into a pair of primal-dual linear programming models, based on which, the solution of the matrix game with IVIFNs is obtained. It is proved that the theorems being valid in the exiting matrix game with IVIFNs are still true when the general aggregation operator is used in the proposed matrix game with IVIFNs. The proposed method is an extension of the existing ones and can provide more choices for players. An example is given to illustrate the validity and the applicability of the proposed method.

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.

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.

Hyaluronan Induces the Selective Accumulation of Matrix- and Cell-Associated Proteoglycans by Mesangial Cells

PubMed Central

Kastner, Sabine; Thomas, Gareth J.; Jenkins, Robert H.; Davies, Malcolm; Steadman, Robert

2007-01-01

Mesangial cells (MCs) are essential for normal renal function through the synthesis of their own extracellular matrix, which forms the structural support of the renal glomerulus. In many renal diseases this matrix is reorganized in response to a variety of cytokines and growth factors. This study examines proteoglycan and hyaluronan (HA) synthesis by MCs triggered by proinflammatory agents and investigates the effect of an exogenous HA matrix on matrix synthesis by MCs. Metabolic labeling, ion exchange and size exclusion chromatography, Western blotting, and immunocytochemistry were used to identify changes in matrix accumulation. When incubated with interleukin-1, platelet-derived growth factor, or fetal calf serum, MCs initiated rapid HA synthesis associated with the up-regulation of HA synthase-2 and increased the synthesis of versican, perlecan, and decorin/biglycan. HA was both released into the medium and incorporated into extensive pericellular coats. Adding exogenous HA to unstimulated cells that had undetectable pericellular coats of HA selectively reduced perlecan and versican turnover, whereas other proteoglycans were unaffected. These results suggest that high levels of HA in the mesangium in disease is a mechanism controlling the accumulation of specific mesangial matrix components. HA may thus be an attractive target for therapeutic intervention. PMID:17974600

Superfund Chemical Data Matrix (SCDM) Query - Popup

EPA Pesticide Factsheets

This site allows you to to easily query the Superfund Chemical Data Matrix (SCDM) and generate a list of the corresponding Hazardous Ranking System (HRS) factor values, benchmarks, and data elements that you need.

Superfund Chemical Data Matrix (SCDM) Query

EPA Pesticide Factsheets

This site allows you to to easily query the Superfund Chemical Data Matrix (SCDM) and generate a list of the corresponding Hazard Ranking System (HRS) factor values, benchmarks, and data elements that you need.

Improving performances of suboptimal greedy iterative biclustering heuristics via localization.

PubMed

Erten, Cesim; Sözdinler, Melih

2010-10-15

Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance criteria. The fact that the random extraction method based on localization REAL performs better than the representative greedy heuristic methods under same criteria also confirms the effectiveness of the suggested pre-processing method. Supplementary material including code implementations in LEDA C++ library, experimental data, and the results are available at http://code.google.com/p/biclustering/ cesim@khas.edu.tr; melihsozdinler@boun.edu.tr Supplementary data are available at Bioinformatics online.

Tissue architecture and breast cancer: the role of extracellular matrix and steroid hormones

PubMed Central

Hansen, R K; Bissell, M J

2010-01-01

The changes in tissue architecture that accompany the development of breast cancer have been the focus of investigations aimed at developing new cancer therapeutics. As we learn more about the normal mammary gland, we have begun to understand the complex signaling pathways underlying the dramatic shifts in the structure and function of breast tissue. Integrin-, growth factor-, and steroid hormone-signaling pathways all play an important part in maintaining tissue architecture; disruption of the delicate balance of signaling results in dramatic changes in the way cells interact with each other and with the extracellular matrix, leading to breast cancer. The extracellular matrix itself plays a central role in coordinating these signaling processes. In this review, we consider the interrelationships between the extracellular matrix, integrins, growth factors, and steroid hormones in mammary gland development and function. PMID:10903527

Testing of self-repairing composite airplane components by use of CAI and the release of the repair chemicals from carefully inserted small tubes

NASA Astrophysics Data System (ADS)

Dry, Carolyn

2007-04-01

The research on self repair of airplane components, under an SBIR phase II with Wright Patterson Air Force Base, has investigated the attributes and best end use applications for such a technology. These attributes include issues related to manufacturability, cost, potential benefits such as weight reduction, and cost reduction. The goal of our research has been to develop self-repairing composites with unique strength for air vehicles. Our revolutionary approach involves the autonomous release of repair chemicals from within the composite matrix itself. The repair agents are contained in hollow, structural fibers that are embedded within the matrix. Under stress, the composite senses external environmental factors and reacts by releasing the repair agents from within the hollow vessels. This autonomous response occurs wherever and whenever cracking, debonding or other matrix damage transpires. Superior performance over the life of the composite is achieved through this self-repairing mechanism. The advantages to the military would be safely executed missions, fewer repairs and eventually lighter vehicles. In particular the research has addressed the issues by correlating the impact of the various factors, such as 1) delivery vessel placement, shape/size and effect on composite strength, chemicals released and their effect on the matrix, release trigger and efficacy and any impact on matrix properties 2) impact of composite processing methods that involve heat and pressure on the repair vessels. Our self repairing system can be processed at temperatures of 300-350F, repairs in less than 30 seconds and does not damage the composite by repair fiber insertion or chemical release. Scaling up and manufacture of components has revealed that anticipating potential problems allowed us to avoid those associated with processing temperatures and pressures. The presentation will focus on compression after impact testing and the placement of repair fibers/tubes into prepreg laminates.

Alternative dimensional reduction via the density matrix

NASA Astrophysics Data System (ADS)

de Carvalho, C. A.; Cornwall, J. M.; da Silva, A. J.

2001-07-01

We give graphical rules, based on earlier work for the functional Schrödinger equation, for constructing the density matrix for scalar and gauge fields in equilibrium at finite temperature T. More useful is a dimensionally reduced effective action (DREA) constructed from the density matrix by further functional integration over the arguments of the density matrix coupled to a source. The DREA is an effective action in one less dimension which may be computed order by order in perturbation theory or by dressed-loop expansions; it encodes all thermal matrix elements. We term the DREA procedure alternative dimensional reduction, to distinguish it from the conventional dimensionally reduced field theory (DRFT) which applies at infinite T. The DREA is useful because it gives a dimensionally reduced theory usable at any T including infinity, where it yields the DRFT, and because it does not and cannot have certain spurious infinities which sometimes occur in the density matrix itself or the conventional DRFT; these come from ln T factors at infinite temperature. The DREA can be constructed to all orders (in principle) and the only regularizations needed are those which control the ultraviolet behavior of the zero-T theory. An example of spurious divergences in the DRFT occurs in d=2+1φ4 theory dimensionally reduced to d=2. We study this theory and show that the rules for the DREA replace these ``wrong'' divergences in physical parameters by calculable powers of ln T; we also compute the phase transition temperature of this φ4 theory in one-loop order. Our density-matrix construction is equivalent to a construction of the Landau-Ginzburg ``coarse-grained free energy'' from a microscopic Hamiltonian.

Perceived barriers to medical-error reporting: an exploratory investigation.

PubMed

Uribe, Claudia L; Schweikhart, Sharon B; Pathak, Dev S; Dow, Merrell; Marsh, Gail B

2002-01-01

Medical-error reporting is an essential component for patient safety enhancement. Unfortunately, medical errors are largely underreported across healthcare institutions. This problem can be attributed to different factors and barriers present at organizational and individual levels that ultimately prevent individuals from generating the report. This study explored the factors that affect medical-error reporting among physicians and nurses at a large academic medical center located in the midwest United States. A nominal group session was conducted to identify the most relevant factors that act as barriers for error reporting. These factors were then used to design a questionnaire that explored the likelihood of the factors to act as barriers and their likelihood to be modified. Using these two parameters, the results were analyzed and combined into a Factor Relevance Matrix. The matrix identifies the factors for which immediate actions should be undertaken to improve medical-error reporting (immediate action factors). It also identifies factors that require long-term strategies (long-term strategy factors) as well as factors that the organization should be aware of but that are of lower priority (awareness factors). The strategies outlined in this study may assist healthcare organizations in improving medical-error reporting, as part of the efforts toward patient-safety enhancement. Although factors affecting medical-error reporting may vary between different organizations, the process used in identifying the factors and the Factor Relevance Matrix developed in this study are easily adaptable to any organizational setting.

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

PubMed

Nevins, Marc L; Said, Sherif

2017-12-28

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

General Linewidth Formula for Steady-State Multimode Lasing in Arbitrary Cavities

NASA Astrophysics Data System (ADS)

Chong, Y. D.; Stone, A. Douglas

2012-08-01

A formula for the laser linewidth of arbitrary cavities in the multimode nonlinear regime is derived from a scattering analysis of the solutions to semiclassical laser theory. The theory generalizes previous treatments of the effects of gain and openness described by the Petermann factor. The linewidth is expressed using quantities based on the nonlinear scattering matrix, which can be computed from steady-state ab initio laser theory; unlike previous treatments, no passive cavity or phenomenological parameters are involved. We find that low cavity quality factor, combined with significant dielectric dispersion, can cause substantial deviations from the Shawlow-Townes-Petermann theory.

Pre-form ceramic matrix composite cavity and a ceramic matrix composite component

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

Monaghan, Philip Harold; Delvaux, John McConnell; Taxacher, Glenn Curtis

A pre-form CMC cavity and method of forming pre-form CMC cavity for a ceramic matrix component includes providing a mandrel, applying a base ply to the mandrel, laying-up at least one CMC ply on the base ply, removing the mandrel, and densifying the base ply and the at least one CMC ply. The remaining densified base ply and at least one CMC ply form a ceramic matrix component having a desired geometry and a cavity formed therein. Also provided is a method of forming a CMC component.

Organotypic three-dimensional assays based on human leiomyoma–derived matrices

PubMed Central

Dourado, Mauricio Rocha; Sundquist, Elias; Apu, Ehsanul Hoque; Alahuhta, Ilkka; Tuomainen, Katja; Vasara, Jenni; Al-Samadi, Ahmed

2018-01-01

Alongside cancer cells, tumours exhibit a complex stroma containing a repertoire of cells, matrix molecules and soluble factors that actively crosstalk between each other. Recognition of this multifaceted concept of the tumour microenvironment (TME) calls for authentic TME mimetics to study cancer in vitro. Traditionally, tumourigenesis has been investigated in non-human, three-dimensional rat type I collagen containing organotypic discs or by means of mouse sarcoma-derived gel, such as Matrigel®. However, the molecular compositions of these simplified assays do not properly simulate human TME. Here, we review the main properties and benefits of using human leiomyoma discs and their matrix Myogel for in vitro assays. Myoma discs are practical for investigating the invasion of cancer cells, as are cocultures of cancer and stromal cells in a stiff, hypoxic TME mimetic. Myoma discs contain soluble factors and matrix molecules commonly present in neoplastic stroma. In Transwell, IncuCyte, spheroid and sandwich assays, cancer cells move faster and form larger colonies in Myogel than in Matrigel®. Additionally, Myogel can replace Matrigel® in hanging-drop and tube-formation assays. Myogel also suits three-dimensional drug testing and extracellular vesicle interactions. To conclude, we describe the application of our myoma-derived matrices in 3D in vitro cancer assays. This article is part of the discussion meeting issue ‘Extracellular vesicles and the tumour microenvironment’. PMID:29158312

Organotypic three-dimensional assays based on human leiomyoma-derived matrices.

PubMed

Salo, Tuula; Dourado, Mauricio Rocha; Sundquist, Elias; Apu, Ehsanul Hoque; Alahuhta, Ilkka; Tuomainen, Katja; Vasara, Jenni; Al-Samadi, Ahmed

2018-01-05

Alongside cancer cells, tumours exhibit a complex stroma containing a repertoire of cells, matrix molecules and soluble factors that actively crosstalk between each other. Recognition of this multifaceted concept of the tumour microenvironment (TME) calls for authentic TME mimetics to study cancer in vitro Traditionally, tumourigenesis has been investigated in non-human, three-dimensional rat type I collagen containing organotypic discs or by means of mouse sarcoma-derived gel, such as Matrigel ® However, the molecular compositions of these simplified assays do not properly simulate human TME. Here, we review the main properties and benefits of using human leiomyoma discs and their matrix Myogel for in vitro assays. Myoma discs are practical for investigating the invasion of cancer cells, as are cocultures of cancer and stromal cells in a stiff, hypoxic TME mimetic. Myoma discs contain soluble factors and matrix molecules commonly present in neoplastic stroma. In Transwell, IncuCyte, spheroid and sandwich assays, cancer cells move faster and form larger colonies in Myogel than in Matrigel ® Additionally, Myogel can replace Matrigel ® in hanging-drop and tube-formation assays. Myogel also suits three-dimensional drug testing and extracellular vesicle interactions. To conclude, we describe the application of our myoma-derived matrices in 3D in vitro cancer assays.This article is part of the discussion meeting issue 'Extracellular vesicles and the tumour microenvironment'. © 2017 The Authors.

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

PubMed

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

2017-05-01

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

Demineralized bone matrix fibers formable as general and custom 3D printed mold-based implants for promoting bone regeneration.

PubMed

Rodriguez, Rudy U; Kemper, Nathan; Breathwaite, Erick; Dutta, Sucharita M; Hsu, Erin L; Hsu, Wellington K; Francis, Michael P

2016-07-26

Bone repair frequently requires time-consuming implant construction, particularly when using un-formed implants with poor handling properties. We therefore developed osteoinductive, micro-fibrous surface patterned demineralized bone matrix (DBM) fibers for engineering both defect-matched and general three-dimensional implants. Implant molds were filled with demineralized human cortical bone fibers there were compressed and lyophilized, forming mechanically strong shaped DBM scaffolds. Enzyme linked immunosorbent assays and mass spectrometry confirmed that DBM fibers contained abundant osteogenic growth factors (bone morphogenetic proteins, insulin-like growth factor-I) and extracellular matrix proteins. Mercury porosimetry and mechanical testing showed interconnected pores within the mechanically stable, custom DBM fiber scaffolds. Mesenchymal stem cells readily attached to the DBM and showed increasing metabolic activity over time. DBM fibers further increased alkaline phosphatase activity in C2C12 cells. In vivo, DBM implants elicited osteoinductive potential in a mouse muscle pouch, and also promoted spine fusion in a rat arthrodesis model. DBM fibers can be engineered into custom-shaped, osteoinductive and osteoconductive implants with potential for repairing osseous defects with precise fitment, potentially reducing operating time. By providing pre-formed and custom implants, this regenerative allograft may improve patient outcomes following surgical bone repair, while further advancing personalized orthopedic and craniomaxillofacial medicine using three-dimensional-printed tissue molds.

Inverse scattering transform for the time dependent Schrödinger equation with applications to the KPI equation

NASA Astrophysics Data System (ADS)

Zhou, Xin

1990-03-01

For the direct-inverse scattering transform of the time dependent Schrödinger equation, rigorous results are obtained based on an opertor-triangular-factorization approach. By viewing the equation as a first order operator equation, similar results as for the first order n x n matrix system are obtained. The nonlocal Riemann-Hilbert problem for inverse scattering is shown to have solution.

Cell-Based Meniscal Repair Using an Aligned Bioactive Nanofibrous Sheath

DTIC Science & Technology

2016-07-01

STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this proposal is to develop a novel bio ...fibers. Secondly, the NFS will be bio -enhanced by impregnation with an extract derived from decellularized meniscus matrix, which contains molecules and...growth factors specific to this tissue, to increase the formation of fibrocartilage by adult stem cells seeded within the scaffold. This bio

Ionic liquid based vortex assisted liquid-liquid microextraction combined with liquid chromatography mass spectrometry for the determination of bisphenols in thermal papers with the aid of response surface methodology.

PubMed

Asati, Ankita; Satyanarayana, G N V; Panchal, Smita; Thakur, Ravindra Singh; Ansari, Nasreen G; Patel, Devendra K

2017-08-04

A sensitive, rapid and efficient ionic liquid-based vortex assisted liquid-liquid microextraction (IL-VALLME) with Liquid Chromatography Mass spectrometry (LC-MS/MS) method is proposed for the determination of bisphenols in thermal paper. Extraction factors were systematically optimized by response surface methodology. Experimental factors showing significant effects on the analytical responses were evaluated using design of experiment. The limit of detection for Bisphenol-A (BPA) and Bisphenol-S (BPS) in thermal paper were 1.25 and 0.93μgkg -1 respectively. The dynamic linearity range for BPA was between 4 and 100μgkg -1 and the determination of coefficient (R 2 ) was 0.996. The values of the same parameters were 3-100μgkg -1 and 0.998 for BPS. The extraction recoveries of BPA and BPS in thermal paper were 101% and 99%. Percent relative standard deviation (% RSD) for matrix effect and matrix match effects were not more than 10%, for both bisphenols. The proposed method uses a statistical approach for the analysis of bisphenols in environmental samples, and is easy, rapid, requires minimum organic solvents and efficient. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of primaquine diphosphate tablet formulation for controlled drug release using the mixture experimental design.

PubMed

Duque, Marcelo Dutra; Kreidel, Rogério Nepomuceno; Taqueda, Maria Elena Santos; Baby, André Rolim; Kaneko, Telma Mary; Velasco, Maria Valéria Robles; Consiglieri, Vladi Olga

2013-01-01

A tablet formulation based on hydrophilic matrix with a controlled drug release was developed, and the effect of polymer concentrations on the release of primaquine diphosphate was evaluated. To achieve this purpose, a 20-run, four-factor with multiple constraints on the proportions of the components was employed to obtain tablet compositions. Drug release was determined by an in vitro dissolution study in phosphate buffer solution at pH 6.8. The polynomial fitted functions described the behavior of the mixture on simplex coordinate systems to study the effects of each factor (polymer) on tablet characteristics. Based on the response surface methodology, a tablet composition was optimized with the purpose of obtaining a primaquine diphosphate release closer to a zero order kinetic. This formulation released 85.22% of the drug for 8 h and its kinetic was studied regarding to Korsmeyer-Peppas model, (Adj-R(2) = 0.99295) which has confirmed that both diffusion and erosion were related to the mechanism of the drug release. The data from the optimized formulation were very close to the predictions from statistical analysis, demonstrating that mixture experimental design could be used to optimize primaquine diphosphate dissolution from hidroxypropylmethyl cellulose and polyethylene glycol matrix tablets.

Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

PubMed Central

Ghanbari, Yasser; Smith, Alex R.; Schultz, Robert T.; Verma, Ragini

2014-01-01

Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain’s traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933

Identification of Extracellular Matrix Components and Biological Factors in Micronized Dehydrated Human Amnion/Chorion Membrane

PubMed Central

Lei, Jennifer; Priddy, Lauren B.; Lim, Jeremy J.; Massee, Michelle; Koob, Thomas J.

2017-01-01

Objective: The use of bioactive extracellular matrix (ECM) grafts such as amniotic membranes is an attractive treatment option for enhancing wound repair. In this study, the concentrations, activity, and distribution of matrix components, growth factors, proteases, and inhibitors were evaluated in PURION® Processed, micronized, dehydrated human amnion/chorion membrane (dHACM; MiMedx Group, Inc.). Approach: ECM components in dHACM tissue were assessed by using immunohistochemical staining, and growth factors, cytokines, proteases, and inhibitors were quantified by using single and multiplex ELISAs. The activities of proteases that were native to the tissue were determined via gelatin zymography and EnzChek® activity assay. Results: dHACM tissue contained the ECM components collagens I and IV, hyaluronic acid, heparin sulfate proteoglycans, fibronectin, and laminin. In addition, numerous growth factors, cytokines, chemokines, proteases, and protease inhibitors that are known to play a role in the wound-healing process were quantified in dHACM. Though matrix metalloproteinases (MMPs) were present in dHACM tissues, inhibitors of MMPs overwhelmingly outnumbered the MMP enzymes by an overall molar ratio of 28:1. Protease activity assays revealed that the MMPs in the tissue existed primarily either in their latent form or complexed with inhibitors. Innovation: This is the first study to characterize components that function in wound healing, including inhibitor and protease content and activity, in micronized dHACM. Conclusion: A variety of matrix components and growth factors, as well as proteases and their inhibitors, were identified in micronized dHACM, providing a better understanding of how micronized dHACM tissue can be used to effectively promote wound repair. PMID:28224047

Identification of Extracellular Matrix Components and Biological Factors in Micronized Dehydrated Human Amnion/Chorion Membrane.

PubMed

Lei, Jennifer; Priddy, Lauren B; Lim, Jeremy J; Massee, Michelle; Koob, Thomas J

2017-02-01

Objective: The use of bioactive extracellular matrix (ECM) grafts such as amniotic membranes is an attractive treatment option for enhancing wound repair. In this study, the concentrations, activity, and distribution of matrix components, growth factors, proteases, and inhibitors were evaluated in PURION ® Processed, micronized, dehydrated human amnion/chorion membrane (dHACM; MiMedx Group, Inc.). Approach: ECM components in dHACM tissue were assessed by using immunohistochemical staining, and growth factors, cytokines, proteases, and inhibitors were quantified by using single and multiplex ELISAs. The activities of proteases that were native to the tissue were determined via gelatin zymography and EnzChek ® activity assay. Results: dHACM tissue contained the ECM components collagens I and IV, hyaluronic acid, heparin sulfate proteoglycans, fibronectin, and laminin. In addition, numerous growth factors, cytokines, chemokines, proteases, and protease inhibitors that are known to play a role in the wound-healing process were quantified in dHACM. Though matrix metalloproteinases (MMPs) were present in dHACM tissues, inhibitors of MMPs overwhelmingly outnumbered the MMP enzymes by an overall molar ratio of 28:1. Protease activity assays revealed that the MMPs in the tissue existed primarily either in their latent form or complexed with inhibitors. Innovation: This is the first study to characterize components that function in wound healing, including inhibitor and protease content and activity, in micronized dHACM. Conclusion: A variety of matrix components and growth factors, as well as proteases and their inhibitors, were identified in micronized dHACM, providing a better understanding of how micronized dHACM tissue can be used to effectively promote wound repair.

Coordinate regulation of estrogen-mediated fibronectin matrix assembly and epidermal growth factor receptor transactivation by the G protein-coupled receptor, GPR30.

PubMed

Quinn, Jeffrey A; Graeber, C Thomas; Frackelton, A Raymond; Kim, Minsoo; Schwarzbauer, Jean E; Filardo, Edward J

2009-07-01

Estrogen promotes changes in cytoskeletal architecture not easily attributed to the biological action of estrogen receptors, ERalpha and ERbeta. The Gs protein-coupled transmembrane receptor, GPR30, is linked to specific estrogen binding and rapid estrogen-mediated release of heparin-bound epidermal growth factor. Using marker rescue and dominant interfering mutant strategies, we show that estrogen action via GPR30 promotes fibronectin (FN) matrix assembly by human breast cancer cells. Stimulation with 17beta-estradiol or the ER antagonist, ICI 182, 780, results in the recruitment of FN-engaged integrin alpha5beta1 conformers to fibrillar adhesions and the synthesis of FN fibrils. Concurrent with this cellular response, GPR30 promotes the formation of Src-dependent, Shc-integrin alpha5beta1 complexes. Function-blocking antibodies directed against integrin alpha5beta1 or soluble Arg-Gly-Asp peptide fragments derived from FN specifically inhibited GPR30-mediated epidermal growth factor receptor transactivation. Estrogen-mediated FN matrix assembly and epidermal growth factor receptor transactivation were similarly disrupted in integrin beta1-deficient GE11 cells, whereas reintroduction of integrin beta1 into GE11 cells restored these responses. Mutant Shc (317Y/F) blocked GPR30-induced FN matrix assembly and tyrosyl phosphorylation of erbB1. Interestingly, relative to recombinant wild-type Shc, 317Y/F Shc was more readily retained in GPR30-induced integrin alpha5beta1 complexes, yet this mutant did not prevent endogenous Shc-integrin alpha5beta1 complex formation. Our results suggest that GPR30 coordinates estrogen-mediated FN matrix assembly and growth factor release in human breast cancer cells via a Shc-dependent signaling mechanism that activates integrin alpha5beta1.

Design of a factorial experiment with randomization restrictions to assess medical device performance on vascular tissue.

PubMed

Diestelkamp, Wiebke S; Krane, Carissa M; Pinnell, Margaret F

2011-05-20

Energy-based surgical scalpels are designed to efficiently transect and seal blood vessels using thermal energy to promote protein denaturation and coagulation. Assessment and design improvement of ultrasonic scalpel performance relies on both in vivo and ex vivo testing. The objective of this work was to design and implement a robust, experimental test matrix with randomization restrictions and predictive statistical power, which allowed for identification of those experimental variables that may affect the quality of the seal obtained ex vivo. The design of the experiment included three factors: temperature (two levels); the type of solution used to perfuse the artery during transection (three types); and artery type (two types) resulting in a total of twelve possible treatment combinations. Burst pressures of porcine carotid and renal arteries sealed ex vivo were assigned as the response variable. The experimental test matrix was designed and carried out as a split-plot experiment in order to assess the contributions of several variables and their interactions while accounting for randomization restrictions present in the experimental setup. The statistical software package SAS was utilized and PROC MIXED was used to account for the randomization restrictions in the split-plot design. The combination of temperature, solution, and vessel type had a statistically significant impact on seal quality. The design and implementation of a split-plot experimental test-matrix provided a mechanism for addressing the existing technical randomization restrictions of ex vivo ultrasonic scalpel performance testing, while preserving the ability to examine the potential effects of independent factors or variables. This method for generating the experimental design and the statistical analyses of the resulting data are adaptable to a wide variety of experimental problems involving large-scale tissue-based studies of medical or experimental device efficacy and performance.

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.