Pre-Processed Recursive Lattice Reduction for Complexity Reduction in Spatially and Temporally Correlated MIMO Channels

NASA Astrophysics Data System (ADS)

An, Chan-Ho; Yang, Janghoon; Jang, Seunghun; Kim, Dong Ku

In this letter, a pre-processed lattice reduction (PLR) scheme is developed for the lattice reduction aided (LRA) detection of multiple input multiple-output (MIMO) systems in spatially correlated channel. The PLR computes the LLL-reduced matrix of the equivalent matrix, which is the product of the present channel matrix and unimodular transformation matrix for LR of spatial correlation matrix, rather than the present channel matrix itself. In conjunction with PLR followed by recursive lattice reduction (RLR) scheme [7], pre-processed RLR (PRLR) is shown to efficiently carry out the LR of the channel matrix, especially for the burst packet message in spatially and temporally correlated channel while matching the performance of conventional LRA detection.

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

DOEpatents

Chew, Peter A; Bader, Brett W

2012-10-16

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

Geographically weighted regression model on poverty indicator

NASA Astrophysics Data System (ADS)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

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

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Source imaging of drums in the APNEA system

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

Hensley, D.

1995-12-31

The APNea System is a neutron assay device utilizing both a passive mode and a differential-dieaway active mode. The total detection efficiency is not spatially uniform, even for an empty chamber, and a drum matrix in the chamber can severely distort this response. In order to achieve a response which is independent of the way the source material is distributed in a drum, an imaging procedure has been developed which treats the drum as a number of virtual (sub)volumes. Since each virtual volume of source material is weighted with the appropriate instrument parameters (detection efficiency and thermal flux), the finalmore » assay result is essentially independent of the actual distribution of the source material throughout the drum and its matrix.« less

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

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/

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

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

2018-01-01

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

Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation.

PubMed

Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

2016-02-07

Time-of-flight (TOF) positron emission tomography (PET) technology has recently regained popularity in clinical PET studies for improving image quality and lesion detectability. Using TOF information, the spatial location of annihilation events is confined to a number of image voxels along each line of response, thereby the cross-dependencies of image voxels are reduced, which in turns results in improved signal-to-noise ratio and convergence rate. In this work, we propose a novel approach to further improve the convergence of the expectation maximization (EM)-based TOF PET image reconstruction algorithm through subsetization of emission data over TOF bins as well as azimuthal bins. Given the prevalence of TOF PET, we elaborated the practical and efficient implementation of TOF PET image reconstruction through the pre-computation of TOF weighting coefficients while exploiting the same in-plane and axial symmetries used in pre-computation of geometric system matrix. In the proposed subsetization approach, TOF PET data were partitioned into a number of interleaved TOF subsets, with the aim of reducing the spatial coupling of TOF bins and therefore to improve the convergence of the standard maximum likelihood expectation maximization (MLEM) and ordered subsets EM (OSEM) algorithms. The comparison of on-the-fly and pre-computed TOF projections showed that the pre-computation of the TOF weighting coefficients can considerably reduce the computation time of TOF PET image reconstruction. The convergence rate and bias-variance performance of the proposed TOF subsetization scheme were evaluated using simulated, experimental phantom and clinical studies. Simulations demonstrated that as the number of TOF subsets is increased, the convergence rate of MLEM and OSEM algorithms is improved. It was also found that for the same computation time, the proposed subsetization gives rise to further convergence. The bias-variance analysis of the experimental NEMA phantom and a clinical FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation

NASA Astrophysics Data System (ADS)

Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

2016-02-01

Time-of-flight (TOF) positron emission tomography (PET) technology has recently regained popularity in clinical PET studies for improving image quality and lesion detectability. Using TOF information, the spatial location of annihilation events is confined to a number of image voxels along each line of response, thereby the cross-dependencies of image voxels are reduced, which in turns results in improved signal-to-noise ratio and convergence rate. In this work, we propose a novel approach to further improve the convergence of the expectation maximization (EM)-based TOF PET image reconstruction algorithm through subsetization of emission data over TOF bins as well as azimuthal bins. Given the prevalence of TOF PET, we elaborated the practical and efficient implementation of TOF PET image reconstruction through the pre-computation of TOF weighting coefficients while exploiting the same in-plane and axial symmetries used in pre-computation of geometric system matrix. In the proposed subsetization approach, TOF PET data were partitioned into a number of interleaved TOF subsets, with the aim of reducing the spatial coupling of TOF bins and therefore to improve the convergence of the standard maximum likelihood expectation maximization (MLEM) and ordered subsets EM (OSEM) algorithms. The comparison of on-the-fly and pre-computed TOF projections showed that the pre-computation of the TOF weighting coefficients can considerably reduce the computation time of TOF PET image reconstruction. The convergence rate and bias-variance performance of the proposed TOF subsetization scheme were evaluated using simulated, experimental phantom and clinical studies. Simulations demonstrated that as the number of TOF subsets is increased, the convergence rate of MLEM and OSEM algorithms is improved. It was also found that for the same computation time, the proposed subsetization gives rise to further convergence. The bias-variance analysis of the experimental NEMA phantom and a clinical FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

Spatiotemporal study of elderly suicide in Korea by age cohort.

PubMed

Joo, Y

2017-01-01

This study analyzed the spatiotemporal pattern and spatial diffusion of elderly suicide by age cohort, in Korea. The research investigated the elderly suicide rates of the 232 municipal units in South Korea between 2001 and 2011. The Gi* score, which is a spatially weighted indicator of area attributes, was used to identify hot spots and the spatiotemporal pattern of elderly suicide in the nation during the last 10 years. The spatial Markov matrix and spatial dynamic panel data model were employed to identify and estimate the diffusion effect. The suicide rate among elderly individuals 75 years and older was substantially higher than the rate for those between 65 and 74 years of age; however, the spatial patterns of the suicide clusters were similar between the two groups. From 2001 to 2011, the spatial distribution of elderly suicide hot spots differed each year. For both age cohorts, elderly suicide hot spots developed around the north area of South Korea in 2001 and moved to the mid-east area and the mid-western coastal area over 10 years. The spatial Markov matrix indicates that the change in the suicide rate of one area was affected by the suicide rates of neighbouring areas from the previous year, which suggests that suicide increase in one area inflates a neighbouring area's suicide rate over time. Using a spatial dynamic panel data model, elderly suicide diffusion effects were found to be statistically significant for both age cohorts even after economic and demographic indicators and a time variable are included. For individuals 75 years and older, the diffusion effect appeared to be larger. This study demonstrates that elderly suicide can spread spatially over time in both age cohorts. Thus, it is necessary to design a place-based and age-differentiated intervention policy that precisely considers the spatial diffusion of elderly suicide. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

A Derivatization and Validation Strategy for Determining the Spatial Localization of Endogenous Amine Metabolites in Tissues using MALDI Imaging Mass Spectrometry

PubMed Central

Manier, M. Lisa; Spraggins, Jeffrey M.; Reyzer, Michelle L.; Norris, Jeremy L.; Caprioli, Richard M.

2014-01-01

Imaging mass spectrometry (IMS) studies increasingly focus on endogenous small molecular weight metabolites and consequently bring special analytical challenges. Since analytical tissue blanks do not exist for endogenous metabolites, careful consideration must be given to confirm molecular identity. Here we present approaches for the improvement in detection of endogenous amine metabolites such as amino acids and neurotransmitters in tissues through chemical derivatization and matrix-assisted laser desorption/ionization (MALDI) IMS. Chemical derivatization with 4-hydroxy-3-methoxycinnamaldehyde (CA) was used to improve sensitivity and specificity. CA was applied to the tissue via MALDI sample targets precoated with a mixture of derivatization reagent and ferulic acid (FA) as a MALDI matrix. Spatial distributions of chemically derivatized endogenous metabolites in tissue were determined by high-mass resolution and MSn imaging mass spectrometry. We highlight an analytical strategy for metabolite validation whereby tissue extracts are analyzed by high-performance liquid chromatography (HPLC)-MS/MS to unambiguously identify metabolites and distinguish them from isobaric compounds. PMID:25044893

Filtering of non-linear instabilities

NASA Technical Reports Server (NTRS)

Khosla, P. K.; Rubin, S. G.

1978-01-01

For Courant numbers larger than one and cell Reynolds numbers larger than two, oscillations and in some cases instabilities are typically found with implicit numerical solutions of the fluid dynamics equations. This behavior has sometimes been associated with the loss of diagonal dominance of the coefficient matrix. It is shown that these problems can be related to the choice of the spatial differences, with the resulting instability related to aliasing or nonlinear interaction. Appropriate filtering can reduce the intensity of these oscillations and possibly eliminate the instability. These filtering procedures are equivalent to a weighted average of conservation and nonconservation differencing. The entire spectrum of filtered equations retains a three point character as well as second order spatial accuracy. Burgers equation was considered as a model.

Generalized sidelobe canceller beamforming method for ultrasound imaging.

PubMed

Wang, Ping; Li, Na; Luo, Han-Wu; Zhu, Yong-Kun; Cui, Shi-Gang

2017-03-01

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

Education And Gender Bias in the Sex Ratio At Birth: Evidence From India

PubMed Central

ECHÁVARRI, REBECA A.; EZCURRA, ROBERTO

2010-01-01

This article investigates the possible existence of a nonlinear link between female disadvantage in natality and education. To this end, we devise a theoretical model based on the key role of social interaction in explaining people’s acquisition of preferences, which justifies the existence of a nonmonotonic relationship between female disadvantage in natality and education. The empirical validity of the proposed model is examined for the case of India, using district-level data. In this context, our econometric analysis pays particular attention to the role of spatial dependence to avoid any potential problems of misspecification. The results confirm that the relationship between the sex ratio at birth and education in India follows an inverted U-shape. This finding is robust to the inclusion of additional explanatory variables in the analysis, and to the choice of the spatial weight matrix used to quantify the spatial interdependence between the sample districts. PMID:20355693

Education and gender bias in the sex ratio at birth: evidence from India.

PubMed

Echávarri, Rebeca A; Ezcurra, Roberto

2010-02-01

This article investigates the possible existence of a nonlinear link between female disadvantage in natality and education. To this end, we devise a theoretical model based on the key role of social interaction in explaining people's acquisition of preferences, which justifies the existence of a nonmonotonic relationship between female disadvantage in natality and education. The empirical validity of the proposed model is examined for the case of India, using district-level data. In this context, our econometric analysis pays particular attention to the role of spatial dependence to avoid any potential problems of misspecification. The results confirm that the relationship between the sex ratio at birth and education in India follows an inverted U-shape. This finding is robust to the inclusion of additional explanatory variables in the analysis, and to the choice of the spatial weight matrix used to quantify the spatial interdependence between the sample districts.

A theory for modeling ground-water flow in heterogeneous media

USGS Publications Warehouse

Cooley, Richard L.

2004-01-01

Construction of a ground-water model for a field area is not a straightforward process. Data are virtually never complete or detailed enough to allow substitution into the model equations and direct computation of the results of interest. Formal model calibration through optimization, statistical, and geostatistical methods is being applied to an increasing extent to deal with this problem and provide for quantitative evaluation and uncertainty analysis of the model. However, these approaches are hampered by two pervasive problems: 1) nonlinearity of the solution of the model equations with respect to some of the model (or hydrogeologic) input variables (termed in this report system characteristics) and 2) detailed and generally unknown spatial variability (heterogeneity) of some of the system characteristics such as log hydraulic conductivity, specific storage, recharge and discharge, and boundary conditions. A theory is developed in this report to address these problems. The theory allows construction and analysis of a ground-water model of flow (and, by extension, transport) in heterogeneous media using a small number of lumped or smoothed system characteristics (termed parameters). The theory fully addresses both nonlinearity and heterogeneity in such a way that the parameters are not assumed to be effective values. The ground-water flow system is assumed to be adequately characterized by a set of spatially and temporally distributed discrete values, ?, of the system characteristics. This set contains both small-scale variability that cannot be described in a model and large-scale variability that can. The spatial and temporal variability in ? are accounted for by imagining ? to be generated by a stochastic process wherein ? is normally distributed, although normality is not essential. Because ? has too large a dimension to be estimated using the data normally available, for modeling purposes ? is replaced by a smoothed or lumped approximation y?. (where y is a spatial and temporal interpolation matrix). Set y?. has the same form as the expected value of ?, y 'line' ? , where 'line' ? is the set of drift parameters of the stochastic process; ?. is a best-fit vector to ?. A model function f(?), such as a computed hydraulic head or flux, is assumed to accurately represent an actual field quantity, but the same function written using y?., f(y?.), contains error from lumping or smoothing of ? using y?.. Thus, the replacement of ? by y?. yields nonzero mean model errors of the form E(f(?)-f(y?.)) throughout the model and covariances between model errors at points throughout the model. These nonzero means and covariances are evaluated through third and fifth-order accuracy, respectively, using Taylor series expansions. They can have a significant effect on construction and interpretation of a model that is calibrated by estimating ?.. Vector ?.. is estimated as 'hat' ? using weighted nonlinear least squares techniques to fit a set of model functions f(y'hat' ?) to a. corresponding set of observations of f(?), Y. These observations are assumed to be corrupted by zero-mean, normally distributed observation errors, although, as for ?, normality is not essential. An analytical approximation of the nonlinear least squares solution is obtained using Taylor series expansions and perturbation techniques that assume model and observation errors to be small. This solution is used to evaluate biases and other results to second-order accuracy in the errors. The correct weight matrix to use in the analysis is shown to be the inverse of the second-moment matrix E(Y-f(y?.))(Y-f(y?.))', but the weight matrix is assumed to be arbitrary in most developments. The best diagonal approximation is the inverse of the matrix of diagonal elements of E(Y-f(y?.))(Y-f(y?.))', and a method of estimating this diagonal matrix when it is unknown is developed using a special objective function to compute 'hat' ?. When considered to be an estimate of f

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species

PubMed Central

Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011–12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales. PMID:28005942

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species.

PubMed

Kajzer-Bonk, Joanna; Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011-12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales.

Tumor detection in mice by measurement of fluorescence decay time matrices

NASA Astrophysics Data System (ADS)

Cubeddu, R.; Pifferi, A.; Taroni, P.; Valentini, G.; Canti, G.

1995-12-01

An intensified CCD video camera has been used to measure the spatial distribution of the fluorescence decay time in tumor-bearing mice sensitized with hematoporphyrin derivative. Mice were injected with five doses of sensitizer, ranging from 0.1 to 10 mg / kg body weight. For any drug dose the decay time of the exogenous fluorescence in the tumor is always significantly longer than in normal tissues. The image created by associating a gray-shade scale to the decay time matrix of each mouse permits a reliable and precise detection of the neoplasia.

Lagrange constraint neural network for audio varying BSS

NASA Astrophysics Data System (ADS)

Szu, Harold H.; Hsu, Charles C.

2002-03-01

Lagrange Constraint Neural Network (LCNN) is a statistical-mechanical ab-initio model without assuming the artificial neural network (ANN) model at all but derived it from the first principle of Hamilton and Lagrange Methodology: H(S,A)= f(S)- (lambda) C(s,A(x,t)) that incorporates measurement constraint C(S,A(x,t))= (lambda) ([A]S-X)+((lambda) 0-1)((Sigma) isi -1) using the vector Lagrange multiplier-(lambda) and a- priori Shannon Entropy f(S) = -(Sigma) i si log si as the Contrast function of unknown number of independent sources si. Szu et al. have first solved in 1997 the general Blind Source Separation (BSS) problem for spatial-temporal varying mixing matrix for the real world remote sensing where a large pixel footprint implies the mixing matrix [A(x,t)] necessarily fill with diurnal and seasonal variations. Because the ground truth is difficult to be ascertained in the remote sensing, we have thus illustrated in this paper, each step of the LCNN algorithm for the simulated spatial-temporal varying BSS in speech, music audio mixing. We review and compare LCNN with other popular a-posteriori Maximum Entropy methodologies defined by ANN weight matrix-[W] sigmoid-(sigma) post processing H(Y=(sigma) ([W]X)) by Bell-Sejnowski, Amari and Oja (BSAO) called Independent Component Analysis (ICA). Both are mirror symmetric of the MaxEnt methodologies and work for a constant unknown mixing matrix [A], but the major difference is whether the ensemble average is taken at neighborhood pixel data X's in BASO or at the a priori sources S variables in LCNN that dictates which method works for spatial-temporal varying [A(x,t)] that would not allow the neighborhood pixel average. We expected the success of sharper de-mixing by the LCNN method in terms of a controlled ground truth experiment in the simulation of variant mixture of two music of similar Kurtosis (15 seconds composed of Saint-Saens Swan and Rachmaninov cello concerto).

Effect of bidispersity in grafted chain length on grafted chain conformations and potential of mean force between polymer grafted nanoparticles in a homopolymer matrix.

PubMed

Nair, Nitish; Wentzel, Nathaniel; Jayaraman, Arthi

2011-05-21

In efforts to produce polymeric materials with tailored physical properties, significant interest has grown around the ability to control the spatial organization of nanoparticles in polymer nanocomposites. One way to achieve controlled particle arrangement is by grafting the nanoparticle surface with polymers that are compatible with the matrix, thus manipulating the interfacial interactions between the nanoparticles and the polymer matrix. Previous work has shown that the molecular weight of the grafted polymer, both at high grafting density and low grafting density, plays a key role in dictating the effective inter-particle interactions in a polymer matrix. At high grafting density nanoparticles disperse (aggregate) if the graft molecular weight is higher (lower) than the matrix molecular weight. At low grafting density the longer grafts can better shield the nanoparticle surface from direct particle-particle contacts than the shorter grafts and lead to the dispersion of the grafted particles in the matrix. Despite the importance of graft molecular weight, and evidence of non-trivial effects of polydispersity of chains grafted on flat surfaces, most theoretical work on polymer grafted nanoparticles has only focused on monodisperse grafted chains. In this paper, we focus on how bidispersity in grafted chain lengths affects the grafted chain conformations and inter-particle interactions in an implicit solvent and in a dense homopolymer polymer matrix. We first present the effects of bidispersity on grafted chain conformations in a single polymer grafted particle using purely Monte Carlo (MC) simulations. This is followed by calculations of the potential of mean force (PMF) between two grafted particles in a polymer matrix using a self-consistent Polymer Reference Interaction Site Model theory-Monte Carlo simulation approach. Monte Carlo simulations of a single polymer grafted particle in an implicit solvent show that in the bidisperse polymer grafted particles with an equal number of short and long grafts at low to medium grafting density, the short grafts are in a more coiled up conformation (lower radius of gyration) than their monodisperse counterparts to provide a larger free volume to the longer grafts so they can gain conformational entropy. The longer grafts do not show much difference in conformation from their monodisperse counterparts at low grafting density, but at medium grafting density the longer grafts exhibit less stretched conformations (lower radius of gyration) as compared to their monodisperse counterparts. In the presence of an explicit homopolymer matrix, the longer grafts are more compressed by the matrix homopolymer chains than the short grafts. We observe that the potential of mean force between bidisperse grafted particles has features of the PMF of monodisperse grafted particles with short grafts and monodisperse grafted particles with long grafts. The value of the PMF at contact is governed by the short grafts and values at large inter-particle distances are governed by the longer grafts. Further comparison of the PMF for bidisperse and monodisperse polymer grafted particles in a homopolymer matrix at varying parameters shows that the effects of matrix chain length, matrix packing fraction, grafting density, and particle curvature on the PMF between bidisperse polymer grafted particles are similar to those seen between monodisperse polymer grafted particles. © 2011 American Institute of Physics.

Constructing statistically unbiased cortical surface templates using feature-space covariance

NASA Astrophysics Data System (ADS)

Parvathaneni, Prasanna; Lyu, Ilwoo; Huo, Yuankai; Blaber, Justin; Hainline, Allison E.; Kang, Hakmook; Woodward, Neil D.; Landman, Bennett A.

2018-03-01

The choice of surface template plays an important role in cross-sectional subject analyses involving cortical brain surfaces because there is a tendency toward registration bias given variations in inter-individual and inter-group sulcal and gyral patterns. In order to account for the bias and spatial smoothing, we propose a feature-based unbiased average template surface. In contrast to prior approaches, we factor in the sample population covariance and assign weights based on feature information to minimize the influence of covariance in the sampled population. The mean surface is computed by applying the weights obtained from an inverse covariance matrix, which guarantees that multiple representations from similar groups (e.g., involving imaging, demographic, diagnosis information) are down-weighted to yield an unbiased mean in feature space. Results are validated by applying this approach in two different applications. For evaluation, the proposed unbiased weighted surface mean is compared with un-weighted means both qualitatively and quantitatively (mean squared error and absolute relative distance of both the means with baseline). In first application, we validated the stability of the proposed optimal mean on a scan-rescan reproducibility dataset by incrementally adding duplicate subjects. In the second application, we used clinical research data to evaluate the difference between the weighted and unweighted mean when different number of subjects were included in control versus schizophrenia groups. In both cases, the proposed method achieved greater stability that indicated reduced impacts of sampling bias. The weighted mean is built based on covariance information in feature space as opposed to spatial location, thus making this a generic approach to be applicable to any feature of interest.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Proving Program Termination With Matrix Weighted Digraphs

NASA Technical Reports Server (NTRS)

Dutle, Aaron

2015-01-01

Program termination analysis is an important task in logic and computer science. While determining if a program terminates is known to be undecidable in general, there has been a significant amount of attention given to finding sufficient and computationally practical conditions to prove termination. One such method takes a program and builds from it a matrix weighted digraph. These are directed graphs whose edges are labeled by square matrices with entries in {-1,0,1}, equipped with a nonstandard matrix multiplication. Certain properties of this digraph are known to imply the termination of the related program. In particular, termination of the program can be determined from the weights of the circuits in the digraph. In this talk, the motivation for addressing termination and how matrix weighted digraphs arise will be briefly discussed. The remainder of the talk will describe an efficient method for bounding the weights of a finite set of the circuits in a matrix weighted digraph, which allows termination of the related program to be deduced.

Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography.

PubMed

Yalavarthy, Phaneendra K; Pogue, Brian W; Dehghani, Hamid; Paulsen, Keith D

2007-06-01

Diffuse optical tomography (DOT) involves estimation of tissue optical properties using noninvasive boundary measurements. The image reconstruction procedure is a nonlinear, ill-posed, and ill-determined problem, so overcoming these difficulties requires regularization of the solution. While the methods developed for solving the DOT image reconstruction procedure have a long history, there is less direct evidence on the optimal regularization methods, or exploring a common theoretical framework for techniques which uses least-squares (LS) minimization. A generalized least-squares (GLS) method is discussed here, which takes into account the variances and covariances among the individual data points and optical properties in the image into a structured weight matrix. It is shown that most of the least-squares techniques applied in DOT can be considered as special cases of this more generalized LS approach. The performance of three minimization techniques using the same implementation scheme is compared using test problems with increasing noise level and increasing complexity within the imaging field. Techniques that use spatial-prior information as constraints can be also incorporated into the GLS formalism. It is also illustrated that inclusion of spatial priors reduces the image error by at least a factor of 2. The improvement of GLS minimization is even more apparent when the noise level in the data is high (as high as 10%), indicating that the benefits of this approach are important for reconstruction of data in a routine setting where the data variance can be known based upon the signal to noise properties of the instruments.

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

PubMed Central

Strauß, Magdalena E.; Mezzetti, Maura; Leorato, Samantha

2018-01-01

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms. PMID:29492375

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.

Characteristics of global organic matrix in normal and pimpled chicken eggshells.

PubMed

Liu, Z; Song, L; Zhang, F; He, W; Linhardt, R J

2017-10-01

The organic matrix from normal and pimpled calcified chicken eggshells were dissociated into acid-insoluble, water-insoluble, and facultative-soluble (both acid- and water-soluble) components, to understand the influence of shell matrix on eggshell qualities. A linear correlation was shown among these 3 matrix components in normal eggshells but was not observed in pimpled eggshells. In pimpled eggshells, the percentage contents of all 4 groups of matrix (the total matrix, acid-insoluble matrix, water-insoluble matrix, and facultative-soluble matrix) were significantly higher than that in normal eggshells. The amounts of both total matrix and acid-insoluble matrix in individual pimpled calcified shells were high, even though their weight was much lower than a normal eggshell. In both normal and pimpled eggshells, the calcified eggshell weight and shell thickness significantly and positively correlated with the amounts of all 4 groups of matrix in an individual calcified shell. In normal eggshells, the calcified shell thickness and shell breaking strength showed no significant correlations with the percentage contents of all 4 groups of matrix. In normal eggshells, only the shell membrane weight significantly correlated with the constituent ratios of both acid-insoluble matrix and facultative-soluble matrix in the whole matrix. In pimpled eggshells, 3 variables (calcified shell weight, shell thickness, and breaking strength) were significantly correlated with the constituent proportions of both acid-insoluble matrix and facultative-matrix. This study suggests that mechanical properties of normal eggshells may not linearly depend on the organic matrix content in the calcified eggshells and that pimpled eggshells might result by the disequilibrium enrichment of some proteins with negative effects. © 2017 Poultry Science Association Inc.

Evidence of low molecular weight components in the organic matrix of the reef building coral, Stylophora pistillata.

PubMed

Puverel, S; Houlbrèque, F; Tambutté, E; Zoccola, D; Payan, P; Caminiti, N; Tambutté, S; Allemand, D

2007-08-01

Biominerals contain both inorganic and organic components. Organic components are collectively termed the organic matrix, and this matrix has been reported to play a crucial role in mineralization. Several matrix proteins have been characterized in vertebrates, but only a few in invertebrates, primarily in Molluscs and Echinoderms. Methods classically used to extract organic matrix proteins eliminate potential low molecular weight matrix components, since cut-offs ranging from 3.5 to 10 kDa are used to desalt matrix extracts. Consequently, the presence of such components remains unknown and these are never subjected to further analyses. In the present study, we have used microcolonies from the Scleractinian coral Stylophora pistillata to study newly synthesized matrix components by labelling them with 14C-labelled amino acids. Radioactive matrix components were investigated by a method in which both total organic matrix and fractions of matrix below and above 5 kDa were analyzed. Using this method and SDS-PAGE analyses, we were able to detect the presence of low molecular mass matrix components (<3.5 kDa), but no free amino acids in the skeletal organic matrix. Since more than 98% of the 14C-labelled amino acids were incorporated into low molecular weight molecules, these probably form the bulk of newly synthesized organic matrix components. Our results suggest that these low molecular weight components may be peptides, which can be involved in the regulation of coral skeleton mineralization.

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

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

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is basedmore » on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan{sup ©}600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.« less

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

PubMed Central

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Niu, Tianye; Zhu, Lei

2016-01-01

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan©600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan©600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution. PMID:27147376

Extracting spatial information from networks with low-order eigenvectors

NASA Astrophysics Data System (ADS)

Cucuringu, Mihai; Blondel, Vincent D.; Van Dooren, Paul

2013-03-01

We consider the problem of inferring meaningful spatial information in networks from incomplete information on the connection intensity between the nodes of the network. We consider two spatially distributed networks: a population migration flow network within the US, and a network of mobile phone calls between cities in Belgium. For both networks we use the eigenvectors of the Laplacian matrix constructed from the link intensities to obtain informative visualizations and capture natural geographical subdivisions. We observe that some low-order eigenvectors localize very well and seem to reveal small geographically cohesive regions that match remarkably well with political and administrative boundaries. We discuss possible explanations for this observation by describing diffusion maps and localized eigenfunctions. In addition, we discuss a possible connection with the weighted graph cut problem, and provide numerical evidence supporting the idea that lower-order eigenvectors point out local cuts in the network. However, we do not provide a formal and rigorous justification for our observations.

Robust mosiacs of close-range high-resolution images

NASA Astrophysics Data System (ADS)

Song, Ran; Szymanski, John E.

2008-03-01

This paper presents a robust algorithm which relies only on the information contained within the captured images for the construction of massive composite mosaic images from close-range and high-resolution originals, such as those obtained when imaging architectural and heritage structures. We first apply Harris algorithm to extract a selection of corners and, then, employ both the intensity correlation and the spatial correlation between the corresponding corners for matching them. Then we estimate the eight-parameter projective transformation matrix by the genetic algorithm. Lastly, image fusion using a weighted blending function together with intensity compensation produces an effective seamless mosaic image.

Exposure matrix development for the Libby cohort.

PubMed

Noonan, C W

2006-11-01

The Libby, MT, cohort includes current and former residents with potential historical exposure to asbestos-contaminated vermiculite. This cohort includes individuals with a broad range of exposure experiences and work histories. While both occupational and nonoccupational exposure pathways were found to be relevant in recent investigations of health effects among this cohort, there has not been a comprehensive approach to characterizing these varied exposure pathways. Any approach toward assessing historical exposures among this population must account for three general categories: (1) occupational exposures, (2) residential exposures, and (3) exposures related to a variety of nonoccupational activities thought to be associated with vermiculite/asbestos exposure in this community. First, a job exposure matrix is commonly used in occupational epidemiology to assess historical worker exposures, allowing for the incorporation of numerous occupational categories and weighting factors applied to specific jobs for different time periods. Second, residential exposures can best be quantified by integrating individuals' residential histories with data on environmental asbestos contamination in the community. Previous soil or sediment sampling as well as air modeling could inform estimates of time- and spatial-dependent exposure concentrations for a residential exposure matrix. Finally, exposure opportunities due to nonoccupational activities could be weighted by factors such as time, geography, environmental sampling, and an assessment of the relative importance for each pathway. These three matrices for occupational, residential, and activity exposure pathways could be combined or used separately to provide a more comprehensive and quantitative, or semiquantitative, assessment of individual exposure in future epidemiological studies of this cohort.

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Dynamic remodeling of microbial biofilms by functionally distinct exopolysaccharides.

PubMed

Chew, Su Chuen; Kundukad, Binu; Seviour, Thomas; van der Maarel, Johan R C; Yang, Liang; Rice, Scott A; Doyle, Patrick; Kjelleberg, Staffan

2014-08-05

Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus. Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation. Importance: Most bacteria grow as biofilms in the environment or in association with eukaryotic hosts. Removal of biofilms that form on surfaces is a challenge in clinical and industrial settings. One of the defining features of a biofilm is its extracellular matrix. The matrix has a heterogeneous structure and is formed from a secretion of various biopolymers, including proteins, extracellular DNA, and polysaccharides. It is generally known to interact with biofilm cells, thus affecting cell physiology and cell-cell communication. Despite the fact that the matrix may comprise up to 90% of the biofilm dry weight, how the matrix properties affect biofilm structure, maturation, and interspecies interactions remain largely unexplored. This study reveals that bacteria can use specific extracellular polymers to modulate the physical properties of their microenvironment. This in turn impacts biofilm structure, differentiation, and interspecies interactions. Copyright © 2014 Chew et al.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS.

PubMed

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H] + ). Identifying and distinguishing the molecular ions of lipids (m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS. Graphical Abstract ᅟ.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS

NASA Astrophysics Data System (ADS)

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H]+). Identifying and distinguishing the molecular ions of lipids ( m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS.

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

The performance evaluation model of mining project founded on the weight optimization entropy value method

NASA Astrophysics Data System (ADS)

Mao, Chao; Chen, Shou

2017-01-01

According to the traditional entropy value method still have low evaluation accuracy when evaluating the performance of mining projects, a performance evaluation model of mineral project founded on improved entropy is proposed. First establish a new weight assignment model founded on compatible matrix analysis of analytic hierarchy process (AHP) and entropy value method, when the compatibility matrix analysis to achieve consistency requirements, if it has differences between subjective weights and objective weights, moderately adjust both proportions, then on this basis, the fuzzy evaluation matrix for performance evaluation. The simulation experiments show that, compared with traditional entropy and compatible matrix analysis method, the proposed performance evaluation model of mining project based on improved entropy value method has higher accuracy assessment.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

Spatial and thematic assessment of object-based forest stand delineation using an OFA-matrix

NASA Astrophysics Data System (ADS)

Hernando, A.; Tiede, D.; Albrecht, F.; Lang, S.

2012-10-01

The delineation and classification of forest stands is a crucial aspect of forest management. Object-based image analysis (OBIA) can be used to produce detailed maps of forest stands from either orthophotos or very high resolution satellite imagery. However, measures are then required for evaluating and quantifying both the spatial and thematic accuracy of the OBIA output. In this paper we present an approach for delineating forest stands and a new Object Fate Analysis (OFA) matrix for accuracy assessment. A two-level object-based orthophoto analysis was first carried out to delineate stands on the Dehesa Boyal public land in central Spain (Avila Province). Two structural features were first created for use in class modelling, enabling good differentiation between stands: a relational tree cover cluster feature, and an arithmetic ratio shadow/tree feature. We then extended the OFA comparison approach with an OFA-matrix to enable concurrent validation of thematic and spatial accuracies. Its diagonal shows the proportion of spatial and thematic coincidence between a reference data and the corresponding classification. New parameters for Spatial Thematic Loyalty (STL), Spatial Thematic Loyalty Overall (STLOVERALL) and Maximal Interfering Object (MIO) are introduced to summarise the OFA-matrix accuracy assessment. A stands map generated by OBIA (classification data) was compared with a map of the same area produced from photo interpretation and field data (reference data). In our example the OFA-matrix results indicate good spatial and thematic accuracies (>65%) for all stand classes except for the shrub stands (31.8%), and a good STLOVERALL (69.8%). The OFA-matrix has therefore been shown to be a valid tool for OBIA accuracy assessment.

A Chebyshev matrix method for spatial modes of the Orr-Sommerfeld equation

NASA Technical Reports Server (NTRS)

Danabasoglu, G.; Biringen, S.

1989-01-01

The Chebyshev matrix collocation method is applied to obtain the spatial modes of the Orr-Sommerfeld equation for Poiseuille flow and the Blausius boundary layer. The problem is linearized by the companion matrix technique for semi-infinite domain using a mapping transformation. The method can be easily adapted to problems with different boundary conditions requiring different transformations.

Effects of error covariance structure on estimation of model averaging weights and predictive performance

USGS Publications Warehouse

Lu, Dan; Ye, Ming; Meyer, Philip D.; Curtis, Gary P.; Shi, Xiaoqing; Niu, Xu-Feng; Yabusaki, Steve B.

2013-01-01

When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cekresolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.

High-Resolution Echo-Planar Spectroscopic Imaging of the Human Calf

PubMed Central

Weis, Jan; Bruvold, Morten; Ortiz-Nieto, Francisco; Ahlström, Håkan

2014-01-01

Background This study exploits the speed benefits of echo-planar spectroscopic imaging (EPSI) to acquire lipid spectra of skeletal muscle. The main purpose was to develop a high-resolution EPSI technique for clinical MR scanner, to visualise the bulk magnetic susceptibility (BMS) shifts of extra-myocellular lipid (EMCL) spectral lines, and to investigate the feasibility of this method for the assessment of intra-myocellular (IMCL) lipids. Methods The study group consisted of six healthy volunteers. A two dimensional EPSI sequence with point-resolved spectroscopy (PRESS) spatial localization was implemented on a 3T clinical MR scanner. Measurements were performed by means of 64×64 spatial matrix and nominal voxel size 3×3×15 mm3. The total net measurement time was 3 min 12 sec for non-water-suppressed (1 acquisition) and 12 min 48 sec for water-suppressed scans (4 acquisitions). Results Spectra of the human calf had a very good signal-to-noise ratio and linewidths sufficient to differentiate IMCL resonances from EMCL. The use of a large spatial matrix reduces inter-voxel signal contamination of the strong EMCL signals. Small voxels enabled visualisation of the methylene EMCL spectral line splitting and their BMS shifts up to 0.5 ppm relative to the correspondent IMCL line. The mean soleus muscle IMCL content of our six volunteers was 0.30±0.10 vol% (range 0.18–0.46) or 3.6±1.2 mmol/kg wet weight (range: 2.1–5.4). Conclusion This study demonstrates that high-spatial resolution PRESS EPSI of the muscle lipids is feasible on standard clinical scanners. PMID:24498129

Saliency Detection via Absorbing Markov Chain With Learnt Transition Probability.

PubMed

Lihe Zhang; Jianwu Ai; Bowen Jiang; Huchuan Lu; Xiukui Li

2018-02-01

In this paper, we propose a bottom-up saliency model based on absorbing Markov chain (AMC). First, a sparsely connected graph is constructed to capture the local context information of each node. All image boundary nodes and other nodes are, respectively, treated as the absorbing nodes and transient nodes in the absorbing Markov chain. Then, the expected number of times from each transient node to all other transient nodes can be used to represent the saliency value of this node. The absorbed time depends on the weights on the path and their spatial coordinates, which are completely encoded in the transition probability matrix. Considering the importance of this matrix, we adopt different hierarchies of deep features extracted from fully convolutional networks and learn a transition probability matrix, which is called learnt transition probability matrix. Although the performance is significantly promoted, salient objects are not uniformly highlighted very well. To solve this problem, an angular embedding technique is investigated to refine the saliency results. Based on pairwise local orderings, which are produced by the saliency maps of AMC and boundary maps, we rearrange the global orderings (saliency value) of all nodes. Extensive experiments demonstrate that the proposed algorithm outperforms the state-of-the-art methods on six publicly available benchmark data sets.

Fast higher-order MR image reconstruction using singular-vector separation.

PubMed

Wilm, Bertram J; Barmet, Christoph; Pruessmann, Klaas P

2012-07-01

Medical resonance imaging (MRI) conventionally relies on spatially linear gradient fields for image encoding. However, in practice various sources of nonlinear fields can perturb the encoding process and give rise to artifacts unless they are suitably addressed at the reconstruction level. Accounting for field perturbations that are neither linear in space nor constant over time, i.e., dynamic higher-order fields, is particularly challenging. It was previously shown to be feasible with conjugate-gradient iteration. However, so far this approach has been relatively slow due to the need to carry out explicit matrix-vector multiplications in each cycle. In this work, it is proposed to accelerate higher-order reconstruction by expanding the encoding matrix such that fast Fourier transform can be employed for more efficient matrix-vector computation. The underlying principle is to represent the perturbing terms as sums of separable functions of space and time. Compact representations with this property are found by singular-vector analysis of the perturbing matrix. Guidelines for balancing the accuracy and speed of the resulting algorithm are derived by error propagation analysis. The proposed technique is demonstrated for the case of higher-order field perturbations due to eddy currents caused by diffusion weighting. In this example, image reconstruction was accelerated by two orders of magnitude.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry

PubMed Central

Zubair, Faizan; Laibinis, Paul E.; Swisher, William G.; Yang, Junhai; Spraggins, Jeffrey M.; Norris, Jeremy L.; Caprioli, Richard M.

2017-01-01

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. PMID:27676701

Investigation of colloidal graphite as a matrix for matrix-assisted laser desorption/ionisation mass spectrometry of low molecular weight analytes.

PubMed

Warren, Alexander D; Conway, Ulric; Arthur, Christopher J; Gates, Paul J

2016-07-01

The analysis of low molecular weight compounds by matrix-assisted laser desorption/ionisation mass spectrometry is problematic due to the interference and suppression of analyte ionisation by the matrices typically employed - which are themselves low molecular weight compounds. The application of colloidal graphite is demonstrated here as an easy to use matrix that can promote the ionisation of a wide range of analytes including low molecular weight organic compounds, complex natural products and inorganic complexes. Analyte ionisation with colloidal graphite is compared with traditional organic matrices along with various other sources of graphite (e.g. graphite rods and charcoal pencils). Factors such as ease of application, spectra reproducibility, spot longevity, spot-to-spot reproducibility and spot homogeneity (through single spot imaging) are explored. For some analytes, considerable matrix suppression effects are observed resulting in spectra completely devoid of matrix ions. We also report the observation of radical molecular ions [M(-●) ] in the negative ion mode, particularly with some aromatic analytes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

High resolution mass spectrometry method and system for analysis of whole proteins and other large molecules

DOEpatents

Reilly, Peter T. A. [Knoxville, TN; Harris, William A [Naperville, IL

2010-03-02

A matrix assisted laser desorption/ionization (MALDI) method and related system for analyzing high molecular weight analytes includes the steps of providing at least one matrix-containing particle inside an ion trap, wherein at least one high molecular weight analyte molecule is provided within the matrix-containing particle, and MALDI on the high molecular weight particle while within the ion trap. A laser power used for ionization is sufficient to completely vaporize the particle and form at least one high molecular weight analyte ion, but is low enough to avoid fragmenting the high molecular weight analyte ion. The high molecular weight analyte ion is extracted out from the ion trap, and is then analyzed using a detector. The detector is preferably a pyrolyzing and ionizing detector.

Unsupervised Unmixing of Hyperspectral Images Accounting for Endmember Variability.

PubMed

Halimi, Abderrahim; Dobigeon, Nicolas; Tourneret, Jean-Yves

2015-12-01

This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing, accounting for endmember variability. The pixels are modeled by a linear combination of endmembers weighted by their corresponding abundances. However, the endmembers are assumed random to consider their variability in the image. An additive noise is also considered in the proposed model, generalizing the normal compositional model. The proposed algorithm exploits the whole image to benefit from both spectral and spatial information. It estimates both the mean and the covariance matrix of each endmember in the image. This allows the behavior of each material to be analyzed and its variability to be quantified in the scene. A spatial segmentation is also obtained based on the estimated abundances. In order to estimate the parameters associated with the proposed Bayesian model, we propose to use a Hamiltonian Monte Carlo algorithm. The performance of the resulting unmixing strategy is evaluated through simulations conducted on both synthetic and real data.

Filtering of non-linear instabilities. [from finite difference solution of fluid dynamics equations

NASA Technical Reports Server (NTRS)

Khosla, P. K.; Rubin, S. G.

1979-01-01

For Courant numbers larger than one and cell Reynolds numbers larger than two, oscillations and in some cases instabilities are typically found with implicit numerical solutions of the fluid dynamics equations. This behavior has sometimes been associated with the loss of diagonal dominance of the coefficient matrix. It is shown here that these problems can in fact be related to the choice of the spatial differences, with the resulting instability related to aliasing or nonlinear interaction. Appropriate 'filtering' can reduce the intensity of these oscillations and in some cases possibly eliminate the instability. These filtering procedures are equivalent to a weighted average of conservation and non-conservation differencing. The entire spectrum of filtered equations retains a three-point character as well as second-order spatial accuracy. Burgers equation has been considered as a model. Several filters are examined in detail, and smooth solutions have been obtained for extremely large cell Reynolds numbers.

Using phase information to enhance speckle noise reduction in the ultrasonic NDE of coarse grain materials

NASA Astrophysics Data System (ADS)

Lardner, Timothy; Li, Minghui; Gachagan, Anthony

2014-02-01

Materials with a coarse grain structure are becoming increasingly prevalent in industry due to their resilience to stress and corrosion. These materials are difficult to inspect with ultrasound because reflections from the grains lead to high noise levels which hinder the echoes of interest. Spatially Averaged Sub-Aperture Correlation Imaging (SASACI) is an advanced array beamforming technique that uses the cross-correlation between images from array sub-apertures to generate an image weighting matrix, in order to reduce noise levels. This paper presents a method inspired by SASACI to further improve imaging using phase information to refine focusing and reduce noise. A-scans from adjacent array elements are cross-correlated using both signal amplitude and phase to refine delay laws and minimize phase aberration. The phase-based and amplitude-based corrected images are used as inputs to a two-dimensional cross-correlation algorithm that will output a weighting matrix that can be applied to any conventional image. This approach was validated experimentally using a 5MHz array a coarse grained Inconel 625 step wedge, and compared to the Total Focusing Method (TFM). Initial results have seen SNR improvements of over 20dB compared to TFM, and a resolution that is much higher.

NOTE: A positive contrast, tri-modality tissue marker for breast tumour localization

NASA Astrophysics Data System (ADS)

Li, Yangmei; Xiong Wang, Jian; Holloway, Claire; Plewes, Donald B.

2007-02-01

A new interstitial breast localization marker is proposed which exhibits positive contrast in T1-weighted MRI, ultrasound and x-ray mammography. Unlike previous markers which provide MRI contrast on the basis of a susceptibility-induced signal void, this marker provides a clear positive contrast without any loss of signal or spatial distortion. The marker is composed of 400 µm diameter copper microspheres suspended in a Gd-DTPA-doped gel matrix. Optimal contrast in T1-weighted spoiled gradient recalled MRI was found to occur with the addition of 10 mM Gd-DTPA. Ultrasound contrast was generated on the basis of scattering from the copper microspheres. X-ray contrast was provided by the high x-ray attenuation properties of the copper microspheres. The study demonstrates potential suitability of the marker for use as a breast localization marker based on ex vivo studies of chicken breast.

Detection of high molecular weight proteins by MALDI imaging mass spectrometry.

PubMed

Mainini, Veronica; Bovo, Giorgio; Chinello, Clizia; Gianazza, Erica; Grasso, Marco; Cattoretti, Giorgio; Magni, Fulvio

2013-06-01

MALDI imaging mass spectrometry (IMS) is a unique technology to explore the spatial distribution of biomolecules directly on tissues. It allows the in situ investigation of a large number of small proteins and peptides. Detection of high molecular weight proteins through MALDI IMS still represents an important challenge, as it would allow the direct investigation of the distribution of more proteins involved in biological processes, such as cytokines, enzymes, neuropeptide precursors and receptors. In this work we compare the traditional method performed with sinapinic acid with a comparable protocol using ferulic acid as the matrix. Data show a remarkable increase of signal acquisition in the mass range of 20k to 150k Th. Moreover, we report molecular images of biomolecules above 70k Th, demonstrating the possibility of expanding the application of this technology both in clinical investigations and basic science.

Three-dimensional modelling of slope stability using the Local Factor of Safety concept

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Extracellular matrix remodeling and matrix metalloproteinase inhibition in visceral adipose during weight cycling in mice.

PubMed

Caria, Cíntia Rabelo E Paiva; Gotardo, Érica Martins Ferreira; Santos, Paola Souza; Acedo, Simone Coghetto; de Morais, Thainá Rodrigues; Ribeiro, Marcelo Lima; Gambero, Alessandra

2017-10-15

Extracellular matrix (ECM) remodeling is necessary for a health adipose tissue (AT) expansion and also has a role during weight loss. We investigate the ECM alteration during weight cycling (WC) in mice and the role of matrix metalloproteinases (MMPs) was assessed using GM6001, an MMP inhibitor, during weight loss (WL). Obesity was induced in mice by a high-fat diet. Obese mice were subject to caloric restriction for WL followed by reintroduction to high-fat diet for weight regain (WR), resulting in a WC protocol. In addition, mice were treated with GM6001 during WL period and the effects were observed after WR. Activity and expression of MMPs was intense during WL. MMP inhibition during WL results in inflammation and collagen content reduction. MMP inhibition during WL period interferes with the period of subsequent expansion of AT resulting in improvements in local inflammation and systemic metabolic alterations induced by obesity. Our results suggest that MMPs inhibition could be an interesting target to improve adipose tissue inflammation during WL and to support weight cyclers. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

Iterative image-domain decomposition for dual-energy CT

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

Niu, Tianye; Dong, Xue; Petrongolo, Michael

2014-04-15

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm ismore » formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.« less

Flow environment and matrix structure interact to determine spatial competition in Pseudomonas aeruginosa biofilms.

PubMed

Nadell, Carey D; Ricaurte, Deirdre; Yan, Jing; Drescher, Knut; Bassler, Bonnie L

2017-01-13

Bacteria often live in biofilms, which are microbial communities surrounded by a secreted extracellular matrix. Here, we demonstrate that hydrodynamic flow and matrix organization interact to shape competitive dynamics in Pseudomonas aeruginosa biofilms. Irrespective of initial frequency, in competition with matrix mutants, wild-type cells always increase in relative abundance in planar microfluidic devices under simple flow regimes. By contrast, in microenvironments with complex, irregular flow profiles - which are common in natural environments - wild-type matrix-producing and isogenic non-producing strains can coexist. This result stems from local obstruction of flow by wild-type matrix producers, which generates regions of near-zero shear that allow matrix mutants to locally accumulate. Our findings connect the evolutionary stability of matrix production with the hydrodynamics and spatial structure of the surrounding environment, providing a potential explanation for the variation in biofilm matrix secretion observed among bacteria in natural environments.

An Application of Semi-parametric Estimator with Weighted Matrix of Data Depth in Variance Component Estimation

NASA Astrophysics Data System (ADS)

Pan, X. G.; Wang, J. Q.; Zhou, H. Y.

2013-05-01

The variance component estimation (VCE) based on semi-parametric estimator with weighted matrix of data depth has been proposed, because the coupling system model error and gross error exist in the multi-source heterogeneous measurement data of space and ground combined TT&C (Telemetry, Tracking and Command) technology. The uncertain model error has been estimated with the semi-parametric estimator model, and the outlier has been restrained with the weighted matrix of data depth. On the basis of the restriction of the model error and outlier, the VCE can be improved and used to estimate weighted matrix for the observation data with uncertain model error or outlier. Simulation experiment has been carried out under the circumstance of space and ground combined TT&C. The results show that the new VCE based on the model error compensation can determine the rational weight of the multi-source heterogeneous data, and restrain the outlier data.

General formalism for partial spatial coherence in reflection Mueller matrix polarimetry.

PubMed

Ossikovski, Razvigor; Hingerl, Kurt

2016-09-01

Starting from the first principles, we derive the expressions governing partially coherent Mueller matrix reflection polarimetry on spatially inhomogeneous samples. These are reported both in their general form and in the practically important specific form for two juxtaposed media.

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

How to deal with the high condition number of the noise covariance matrix of gravity field functionals synthesised from a satellite-only global gravity field model?

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-03-01

The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.

Magnetic resonance imaging (MRI) and relaxation time mapping of concrete

NASA Astrophysics Data System (ADS)

Beyea, Steven Donald

2001-07-01

The use of Magnetic Resonance Imaging (MRI) of water in concrete is presented. This thesis will approach the problem of MR imaging of concrete by attempting to design new methods, suited to concrete materials, rather than attempting to force the material to suit the method. A number of techniques were developed, which allow the spatial observation of water in concrete in up to three dimensions, and permits the determination of space resolved moisture content, as well as local NMR relaxation times. These methods are all based on the Single-Point Imaging (SPI) method. The development of these new methods will be described, and the techniques validated using phantom studies. The study of one-dimensional moisture transport in drying concrete was performed using SPI. This work examined the effect of initial mixture proportions and hydration time on the drying behaviour of concrete, over a period of three months. Studies of drying concrete were also performed using spatial mapping of the spin-lattice (T1) and effective spin-spin (T2*) relaxation times, thereby permitting the observation of changes in the water occupied pore surface-to-volume ratio (S/V) as a function of drying. Results of this work demonstrated changes in the S/V due to drying, hydration and drying induced microcracking. Three-dimensional MRI of concrete was performed using SPRITE (Single-Point Ramped Imaging with T1 Enhancement) and turboSPI (turbo Single Point Imaging). While SPRITE allows for weighting of MR images using T 1 and T2*, turboSPI allows T2 weighting of the resulting images. Using relaxation weighting it was shown to be possible to discriminate between water contained within a hydrated cement matrix, and water in highly porous aggregates, used to produce low-density concrete. Three dimensional experiments performed using SPRITE and turboSPI examined the role of self-dessication, drying, initial aggregate saturation and initial mixture conditions on the transport of moisture between porous aggregates and the hydrated matrix. The results demonstrate that water is both added and removed from the aggregates, depending upon the physical conditions. The images also appear to show an influx of cement products into cracks in the solid aggregate. (Abstract shortened by UMI.)

Physical, Spatial, and Molecular Aspects of Extracellular Matrix of In Vivo Niches and Artificial Scaffolds Relevant to Stem Cells Research

PubMed Central

Akhmanova, Maria; Osidak, Egor; Domogatsky, Sergey; Rodin, Sergey; Domogatskaya, Anna

2015-01-01

Extracellular matrix can influence stem cell choices, such as self-renewal, quiescence, migration, proliferation, phenotype maintenance, differentiation, or apoptosis. Three aspects of extracellular matrix were extensively studied during the last decade: physical properties, spatial presentation of adhesive epitopes, and molecular complexity. Over 15 different parameters have been shown to influence stem cell choices. Physical aspects include stiffness (or elasticity), viscoelasticity, pore size, porosity, amplitude and frequency of static and dynamic deformations applied to the matrix. Spatial aspects include scaffold dimensionality (2D or 3D) and thickness; cell polarity; area, shape, and microscale topography of cell adhesion surface; epitope concentration, epitope clustering characteristics (number of epitopes per cluster, spacing between epitopes within cluster, spacing between separate clusters, cluster patterns, and level of disorder in epitope arrangement), and nanotopography. Biochemical characteristics of natural extracellular matrix molecules regard diversity and structural complexity of matrix molecules, affinity and specificity of epitope interaction with cell receptors, role of non-affinity domains, complexity of supramolecular organization, and co-signaling by growth factors or matrix epitopes. Synergy between several matrix aspects enables stem cells to retain their function in vivo and may be a key to generation of long-term, robust, and effective in vitro stem cell culture systems. PMID:26351461

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification.

PubMed

Chang, S; Wong, K W; Zhang, W; Zhang, Y

1999-08-10

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

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

NASA Astrophysics Data System (ADS)

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

1999-08-01

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

Release from or through a wax matrix system. IV. Generalized expression of the release process for a reservoir device tablet.

PubMed

Yonezawa, Yorinobu; Ishida, Sumio; Suzuki, Shinobu; Sunada, Hisakazu

2002-09-01

Generalization of the release process through the wax matrix layer was examined by use of a reservoir device tablet. The wax matrix layer of the reservoir device tablet was prepared from a physical mixture of lactose and hydrogenated castor oil to simplify the release properties. Release through the wax matrix layer showed zero-order kinetics in a steady state after a given lag time, and could be divided into two stages. The first stage was the formation process of water channel by dissolving the soluble component in the wax matrix layer. The lag time obtained by applying the square root law equation was well connected with the amount of the matrix layer and mixed weight ratio of components in this layer. The second stage was the zero-order release process of drug in the reservoir through the wax matrix layer, because the effective surface area was fixed. The release rate constants were connected with thickness of the matrix layer and permeability coefficient, and the permeability coefficients were connected with the diffusion coefficient of drug and porosity. Hence the release rate constant could be connected with the amount of matrix layer and the mixed weight ratio of components in the matrix layer. It was therefore suggested that the release process could be generalized using the amount of matrix layer and the mixed weight ratio of components in the matrix layer.

Graph Theory Roots of Spatial Operators for Kinematics and Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Spatial operators have been used to analyze the dynamics of robotic multibody systems and to develop novel computational dynamics algorithms. Mass matrix factorization, inversion, diagonalization, and linearization are among several new insights obtained using such operators. While initially developed for serial rigid body manipulators, the spatial operators and the related mathematical analysis have been shown to extend very broadly including to tree and closed topology systems, to systems with flexible joints, links, etc. This work uses concepts from graph theory to explore the mathematical foundations of spatial operators. The goal is to study and characterize the properties of the spatial operators at an abstract level so that they can be applied to a broader range of dynamics problems. The rich mathematical properties of the kinematics and dynamics of robotic multibody systems has been an area of strong research interest for several decades. These properties are important to understand the inherent physical behavior of systems, for stability and control analysis, for the development of computational algorithms, and for model development of faithful models. Recurring patterns in spatial operators leads one to ask the more abstract question about the properties and characteristics of spatial operators that make them so broadly applicable. The idea is to step back from the specific application systems, and understand more deeply the generic requirements and properties of spatial operators, so that the insights and techniques are readily available across different kinematics and dynamics problems. In this work, techniques from graph theory were used to explore the abstract basis for the spatial operators. The close relationship between the mathematical properties of adjacency matrices for graphs and those of spatial operators and their kernels were established. The connections hold across very basic requirements on the system topology, the nature of the component bodies, the indexing schemes, etc. The relationship of the underlying structure is intimately connected with efficient, recursive computational algorithms. The results provide the foundational groundwork for a much broader look at the key problems in kinematics and dynamics. The properties of general graphs and trees of nodes and edge were examined, as well as the properties of adjacency matrices that are used to describe graph connectivity. The nilpotency property of such matrices for directed trees was reviewed, and the adjacency matrices were generalized to the notion of block weighted adjacency matrices that support block matrix elements. This leads us to the development of the notion of Spatial Kernel Operator SKO kernels. These kernels provide the basis for the development of SKO resolvent operators.

A spatial operator algebra for manipulator modeling and control

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Spatial, Temporal, and Matrix Variability of Clostridium botulinum Type E Toxin Gene Distribution at Great Lakes Beaches

PubMed Central

Oster, Ryan J.; Haack, Sheridan K.; Fogarty, Lisa R.; Tucker, Taaja R.; Riley, Stephen C.

2015-01-01

Clostridium botulinum type E toxin is responsible for extensive mortality of birds and fish in the Great Lakes. The C. botulinum bontE gene that produces the type E toxin was amplified with quantitative PCR from 150 sloughed algal samples (primarily Cladophora species) collected during summer 2012 from 10 Great Lakes beaches in five states; concurrently, 74 sediment and 37 water samples from four sites were also analyzed. The bontE gene concentration in algae was significantly higher than in water and sediment (P < 0.05), suggesting that algal mats provide a better microenvironment for C. botulinum. The bontE gene was detected most frequently in algae at Jeorse Park and Portage Lake Front beaches (Lake Michigan) and Bay City State Recreation Area beach on Saginaw Bay (Lake Huron), where 77, 100, and 83% of these algal samples contained the bontE gene, respectively. The highest concentration of bontE was detected at Bay City (1.98 × 105 gene copies/ml of algae or 5.21 × 106 g [dry weight]). This study revealed that the bontE gene is abundant in the Great Lakes but that it has spatial, temporal, and matrix variability. Further, embayed beaches, low wave height, low wind velocity, and greater average water temperature enhance the bontE occurrence. PMID:25888178

Language of administration and neuropsychological test performance in neurologically intact Hispanic American bilingual adults.

PubMed

Gasquoine, Philip Gerard; Croyle, Kristin L; Cavazos-Gonzalez, Cynthia; Sandoval, Omar

2007-11-01

This study compared the performance of Hispanic American bilingual adults on Spanish and English language versions of a neuropsychological test battery. Language achievement test scores were used to divide 36 bilingual, neurologically intact, Hispanic Americans from south Texas into Spanish-dominant, balanced, and English-dominant bilingual groups. They were administered the eight subtests of the Bateria Neuropsicologica and the Matrix Reasoning subtest of the WAIS-III in Spanish and English. Half the participants were tested in Spanish first. Balanced bilinguals showed no significant differences in test scores between Spanish and English language administrations. Spanish and/or English dominant bilinguals showed significant effects of language of administration on tests with higher language compared to visual perceptual weighting (Woodcock-Munoz Language Survey-Revised, Letter Fluency, Story Memory, and Stroop Color and Word Test). Scores on tests with higher visual-perceptual weighting (Matrix Reasoning, Figure Memory, Wisconsin Card Sorting Test, and Spatial Span), were not significantly affected by language of administration, nor were scores on the Spanish/California Verbal Learning Test, and Digit Span. A problem was encountered in comparing false positive rates in each language, as Spanish norms fell below English norms, resulting in a much higher false positive rate in English across all bilingual groupings. Use of a comparison standard (picture vocabulary score) reduced false positive rates in both languages, but the higher false positive rate in English persisted.

A Familiar Pattern? Semantic Memory Contributes to the Enhancement of Visuo-Spatial Memories

ERIC Educational Resources Information Center

Riby, Leigh M.; Orme, Elizabeth

2013-01-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a…

Optimal Frequency-Domain System Realization with Weighting

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Maghami, Peiman G.

1999-01-01

Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation uses a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. Three different approaches are introduced to fine-tune the model using nonlinear programming methods to minimize the desired cost function. The first method uses an eigenvalue assignment technique to reassign a subset of system poles to improve the identified model. The second method deals with the model in the real Schur or modal form, reassigns a subset of system poles, and adjusts the columns (rows) of the input (output) influence matrix using a nonlinear optimizer. The third method also optimizes a subset of poles, but the input and output influence matrices are refined at every optimization step through least-squares procedures.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

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

Social patterns revealed through random matrix theory

NASA Astrophysics Data System (ADS)

Sarkar, Camellia; Jalan, Sarika

2014-11-01

Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.

Classification and identification of molecules through factor analysis method based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Flexible proton 3D MR spectroscopic imaging of the prostate with low-power adiabatic pulses for volume selection and spiral readout.

PubMed

Steinseifer, Isabell K; Philips, Bart W J; Gagoski, Borjan; Weiland, Elisabeth; Scheenen, Tom W J; Heerschap, Arend

2017-03-01

Cartesian k-space sampling in three-dimensional magnetic resonance spectroscopic imaging (MRSI) of the prostate limits the selection of voxel size and acquisition time. Therefore, large prostates are often scanned at reduced spatial resolutions to stay within clinically acceptable measurement times. Here we present a semilocalized adiabatic selective refocusing (sLASER) sequence with gradient-modulated offset-independent adiabatic (GOIA) refocusing pulses and spiral k-space acquisition (GOIA-sLASER-Spiral) for fast prostate MRSI with enhanced resolution and extended matrix sizes. MR was performed at 3 tesla with an endorectal receive coil. GOIA-sLASER-Spiral at an echo time (TE) of 90 ms was compared to a point-resolved spectroscopy sequence (PRESS) with weighted, elliptical phase encoding at an TE of 145 ms using simulations and measurements of phantoms and patients (n = 9). GOIA-sLASER-Spiral acquisition allows prostate MR spectra to be obtained in ∼5 min with a quality comparable to those acquired with a common Cartesian PRESS protocol in ∼9 min, or at an enhanced spatial resolution showing more precise tissue allocation of metabolites. Extended field of views (FOVs) and matrix sizes for large prostates are possible without compromising spatial resolution or measurement time. The flexibility of spiral sampling enables prostate MRSI with a wide range of resolutions and FOVs without undesirable increases in acquisition times, as in Cartesian encoding. This approach is suitable for routine clinical exams of prostate metabolites. Magn Reson Med 77:928-935, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

PubMed

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

2017-05-04

Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

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

PubMed

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

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (p<0.001) for predicting the task being performed within each scan using artifact-cleaned components. The NMF algorithms, which suppressed negative BOLD signal, had the poorest accuracy compared to the ICA and sparse coding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (p<0.001). Lower classification accuracy occurred when the extracted spatial maps contained more CSF regions (p<0.001). The success of sparse coding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

Newly developed surface coil for endoluminal MRI, depiction of pig gastric wall layers and vascular architecture in ex vivo study.

PubMed

Morita, Yoshinori; Kutsumi, Hiromu; Yoshinaka, Hayato; Matsuoka, Yuichiro; Kuroda, Kagayaki; Gotanda, Masakazu; Sekino, Naomi; Kumamoto, Etsuko; Yoshida, Masaru; Inokuchi, Hideto; Azuma, Takeshi

2009-01-01

The purpose of this study was to visualize the gastric wall layers and to depict the vascular architecture in vitro by using resected porcine stomachs studied with high-spatial resolution magnetic resonance (MR) imaging. Normal dissected porcine stomach samples (n = 4) were examined with a 3 Tesla MR system using a newly developed surface coil. MR images were obtained by the surface coil as receiver and a head coil as transmitter. High-spatial-resolution spin-echo MR images were obtained with a field of view of 8 x 8 cm, a matrix of 256 x 128 and slice thicknesses of 3 and 5 mm. T1 and T2-weighted MR images clearly depicted the normal porcine gastric walls as consisting of four distinct layers. In addition, vascular architectures in proper muscle layers were also visualized, which were confirmed by histological examinations to correspond to blood vessels. High-spatial-resolution MR imaging using a surface coil placed closely to the gastric wall enabled the differentiation of porcine gastric wall layers and the depiction of the blood vessels in proper muscle layer in this experimental study.

Peptidylation for the determination of low-molecular-weight compounds by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Tang, Feng; Cen, Si-Ying; He, Huan; Liu, Yi; Yuan, Bi-Feng; Feng, Yu-Qi

2016-05-23

Determination of low-molecular-weight compounds by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has been a great challenge in the analytical research field. Here we developed a universal peptide-based derivatization (peptidylation) strategy for the sensitive analysis of low-molecular-weight compounds by MALDI-TOF-MS. Upon peptidylation, the molecular weights of target analytes increase, thus avoiding serious matrix ion interference in the low-molecular-weight region in MALDI-TOF-MS. Since peptides typically exhibit good signal response during MALDI-TOF-MS analysis, peptidylation endows high detection sensitivities of low-molecular-weight analytes. As a proof-of-concept, we analyzed low-molecular-weight compounds of aldehydes and thiols by the developed peptidylation strategy. Our results showed that aldehydes and thiols can be readily determined upon peptidylation, thus realizing the sensitive and efficient determination of low-molecular-weight compounds by MALDI-TOF-MS. Moreover, target analytes also can be unambiguously detected in biological samples using the peptidylation strategy. The established peptidylation strategy is a universal strategy and can be extended to the sensitive analysis of various low-molecular-weight compounds by MALDI-TOF-MS, which may be potentially used in areas such as metabolomics.

Remote sensing using MIMO systems

DOEpatents

Bikhazi, Nicolas; Young, William F; Nguyen, Hung D

2015-04-28

A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.

A Truncated Nuclear Norm Regularization Method Based on Weighted Residual Error for Matrix Completion.

PubMed

Qing Liu; Zhihui Lai; Zongwei Zhou; Fangjun Kuang; Zhong Jin

2016-01-01

Low-rank matrix completion aims to recover a matrix from a small subset of its entries and has received much attention in the field of computer vision. Most existing methods formulate the task as a low-rank matrix approximation problem. A truncated nuclear norm has recently been proposed as a better approximation to the rank of matrix than a nuclear norm. The corresponding optimization method, truncated nuclear norm regularization (TNNR), converges better than the nuclear norm minimization-based methods. However, it is not robust to the number of subtracted singular values and requires a large number of iterations to converge. In this paper, a TNNR method based on weighted residual error (TNNR-WRE) for matrix completion and its extension model (ETNNR-WRE) are proposed. TNNR-WRE assigns different weights to the rows of the residual error matrix in an augmented Lagrange function to accelerate the convergence of the TNNR method. The ETNNR-WRE is much more robust to the number of subtracted singular values than the TNNR-WRE, TNNR alternating direction method of multipliers, and TNNR accelerated proximal gradient with Line search methods. Experimental results using both synthetic and real visual data sets show that the proposed TNNR-WRE and ETNNR-WRE methods perform better than TNNR and Iteratively Reweighted Nuclear Norm (IRNN) methods.

Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data

NASA Astrophysics Data System (ADS)

Ge, Yong; Avitabile, Valerio; Heuvelink, Gerard B. M.; Wang, Jianghao; Herold, Martin

2014-09-01

Biomass is a key environmental variable that influences many biosphere-atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance-covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.

Polymer, metal and ceramic matrix composites for advanced aircraft engine applications

NASA Technical Reports Server (NTRS)

Mcdanels, D. L.; Serafini, T. T.; Dicarlo, J. A.

1985-01-01

Advanced aircraft engine research within NASA Lewis is being focused on propulsion systems for subsonic, supersonic, and hypersonic aircraft. Each of these flight regimes requires different types of engines, but all require advanced materials to meet their goals of performance, thrust-to-weight ratio, and fuel efficiency. The high strength/weight and stiffness/weight properties of resin, metal, and ceramic matrix composites will play an increasingly key role in meeting these performance requirements. At NASA Lewis, research is ongoing to apply graphite/polyimide composites to engine components and to develop polymer matrices with higher operating temperature capabilities. Metal matrix composites, using magnesium, aluminum, titanium, and superalloy matrices, are being developed for application to static and rotating engine components, as well as for space applications, over a broad temperature range. Ceramic matrix composites are also being examined to increase the toughness and reliability of ceramics for application to high-temperature engine structures and components.

A rough set approach for determining weights of decision makers in group decision making.

PubMed

Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.

Laser desorption ionization mass spectrometry: Recent progress in matrix-free and label-assisted techniques.

PubMed

Mandal, Arundhoti; Singha, Monisha; Addy, Partha Sarathi; Basak, Amit

2017-10-13

The MALDI-based mass spectrometry, over the last three decades, has become an important analytical tool. It is a gentle ionization technique, usually applicable to detect and characterize analytes with high molecular weights like proteins and other macromolecules. The earlier difficulty of detection of analytes with low molecular weights like small organic molecules and metal ion complexes with this technique arose due to the cluster of peaks in the low molecular weight region generated from the matrix. To detect such molecules and metal ion complexes, a four-prong strategy has been developed. These include use of alternate matrix materials, employment of new surface materials that require no matrix, use of metabolites that directly absorb the laser light, and the laser-absorbing label-assisted LDI-MS (popularly known as LALDI-MS). This review will highlight the developments with all these strategies with a special emphasis on LALDI-MS. © 2017 Wiley Periodicals, Inc.

A fully redundant double difference algorithm for obtaining minimum variance estimates from GPS observations

NASA Technical Reports Server (NTRS)

Melbourne, William G.

1986-01-01

In double differencing a regression system obtained from concurrent Global Positioning System (GPS) observation sequences, one either undersamples the system to avoid introducing colored measurement statistics, or one fully samples the system incurring the resulting non-diagonal covariance matrix for the differenced measurement errors. A suboptimal estimation result will be obtained in the undersampling case and will also be obtained in the fully sampled case unless the color noise statistics are taken into account. The latter approach requires a least squares weighting matrix derived from inversion of a non-diagonal covariance matrix for the differenced measurement errors instead of inversion of the customary diagonal one associated with white noise processes. Presented is the so-called fully redundant double differencing algorithm for generating a weighted double differenced regression system that yields equivalent estimation results, but features for certain cases a diagonal weighting matrix even though the differenced measurement error statistics are highly colored.

An Alternating Least Squares Method for the Weighted Approximation of a Symmetric Matrix.

ERIC Educational Resources Information Center

ten Berge, Jos M. F.; Kiers, Henk A. L.

1993-01-01

R. A. Bailey and J. C. Gower explored approximating a symmetric matrix "B" by another, "C," in the least squares sense when the squared discrepancies for diagonal elements receive specific nonunit weights. A solution is proposed where "C" is constrained to be positive semidefinite and of a fixed rank. (SLD)

Simultaneous determination of multiclass emerging contaminants in aquatic plants by ultrasound-assisted matrix solid-phase dispersion and GC-MS.

PubMed

Aznar, Ramón; Albero, Beatriz; Sánchez-Brunete, Consuelo; Miguel, Esther; Martín-Girela, Isabel; Tadeo, José L

2017-03-01

A multiresidue method was developed for the simultaneous determination of 31 emerging contaminants (pharmaceutical compounds, hormones, personal care products, biocides, and flame retardants) in aquatic plants. Analytes were extracted by ultrasound-assisted matrix solid-phase dispersion (UA-MSPD) and determined by gas chromatography-mass spectrometry after sylilation, The method was validated for different aquatic plants (Typha angustifolia, Arundo donax, and Lemna minor) and a semiaquatic cultivated plant (Oryza sativa) with good recoveries at concentrations of 100 and 25 ng g -1 wet weight, ranging from 70 to 120 %, and low method detection limits (0.3 to 2.2 ng g -1 wet weight). A significant difference of the chromatographic response was observed for some compounds in neat solvent versus matrix extracts, and therefore, quantification was carried out using matrix-matched standards in order to overcome this matrix effect. Aquatic plants taken from rivers located at three Spanish regions were analyzed, and the compounds detected were parabens, bisphenol A, benzophenone-3, cyfluthrin, and cypermethrin. The levels found ranged from 6 to 25 ng g -1 wet weight except for cypermethrin that was detected at 235 ng g -1 wet weight in O. sativa samples.

Analysis of modified SMI method for adaptive array weight control

NASA Technical Reports Server (NTRS)

Dilsavor, R. L.; Moses, R. L.

1989-01-01

An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

Method development for compositional analysis of low molecular weight poly(vinyl acetate) by matrix-assisted/laser desorption-mass spectrometry and its application to analysis of chewing gum.

PubMed

Tisdale, Evgenia; Wilkins, Charles

2014-04-11

The influence of the sample preparation parameters (the choice of the solvent and of the matrix:analyte ratio) was investigated and optimal conditions were established for MALDI mass spectrometry analysis of the pristine low molecular weight polyvinyl acetate (PVAc). It was demonstrated that comparison of polymer's and solvent's Hansen solubility parameters could be used as a guide when choosing the solvent for MALDI sample preparation. The highest intensity PVAc signals were obtained when ethyl acetate was used as a solvent along with the lowest matrix-analyte ratio (2,5-dihydroxybenzoic acid was used as a matrix in all experiments). The structure of the PVAc was established with high accuracy using the matrix-assisted laser desorption/ionization-Fourier transform mass spectrometry (MALDI-FTMS) analysis. It was demonstrated that PVAc undergoes unimolecular decomposition by losing acetic acid molecules from its backbone under the conditions of FTMS measurements. Number and weight average molecular weights as well as polydispersity indices were determined with both MALDI-TOF and MALDI-FTMS methods. The sample preparation protocol developed was applied to the analysis of a chewing gum and the molecular weight and structure of the polyvinyl acetate present in the sample were established. Thus, it was shown that optimized MALDI mass spectrometry could be used successfully for characterization of polyvinyl acetate in commercially available chewing gum. Copyright © 2014 Elsevier B.V. All rights reserved.

Gyroaveraging operations using adaptive matrix operators

NASA Astrophysics Data System (ADS)

Dominski, Julien; Ku, Seung-Hoe; Chang, Choong-Seock

2018-05-01

A new adaptive scheme to be used in particle-in-cell codes for carrying out gyroaveraging operations with matrices is presented. This new scheme uses an intermediate velocity grid whose resolution is adapted to the local thermal Larmor radius. The charge density is computed by projecting marker weights in a field-line following manner while preserving the adiabatic magnetic moment μ. These choices permit to improve the accuracy of the gyroaveraging operations performed with matrices even when strong spatial variation of temperature and magnetic field is present. Accuracy of the scheme in different geometries from simple 2D slab geometry to realistic 3D toroidal equilibrium has been studied. A successful implementation in the gyrokinetic code XGC is presented in the delta-f limit.

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Color matrix display simulation based upon luminance and chromatic contrast sensitivity of early vision

NASA Technical Reports Server (NTRS)

Martin, Russel A.; Ahumada, Albert J., Jr.; Larimer, James O.

1992-01-01

This paper describes the design and operation of a new simulation model for color matrix display development. It models the physical structure, the signal processing, and the visual perception of static displays, to allow optimization of display design parameters through image quality measures. The model is simple, implemented in the Mathematica computer language, and highly modular. Signal processing modules operate on the original image. The hardware modules describe backlights and filters, the pixel shape, and the tiling of the pixels over the display. Small regions of the displayed image can be visualized on a CRT. Visual perception modules assume static foveal images. The image is converted into cone catches and then into luminance, red-green, and blue-yellow images. A Haar transform pyramid separates the three images into spatial frequency and direction-specific channels. The channels are scaled by weights taken from human contrast sensitivity measurements of chromatic and luminance mechanisms at similar frequencies and orientations. Each channel provides a detectability measure. These measures allow the comparison of images displayed on prospective devices and, by that, the optimization of display designs.

Thermal stability relationships between PMR-15 resin and its composites

NASA Technical Reports Server (NTRS)

Bowles, Kenneth J.; Jayne, Douglas; Leonhardt, Todd A.; Bors, Dennis

1993-01-01

A study was conducted to investigate the relationship between the thermo-oxidative stability of PMR-15 matrix resin and the stability of graphite-fiber-reinforced composites that contain this resin as the matrix material. Three areas were investigated. The first was the effect of fiber/matrix interfacial bond strength on the isothermal aging weight loss of composites. By using type-A graphite fibers produced by Hercules, it was possible to study composites reinforced with fibers that were processed to receive different surface treatments. One of the fibers was untreated, a second fiber was treated by oxidation to enhance fiber/matrix bonding, and the third type of fiber was coated with an epoxy sizing. These treatments produced three significantly different interfacial bond strengths. The epoxy sizing on the third fiber was quickly oxidized from the bare fiber surfaces at 288, 316, and 343 C. The weight loss due to the removal of the sizing was constant at 1.5 percent. This initial weight loss was not observed in thermo-oxidative stability studies of composites. The PMR-15 matrix satisfactorily protected the reinforcemnt at all three temperatures.

The spatial QRS-T angle in the Frank vectorcardiogram: accuracy of estimates derived from the 12-lead electrocardiogram.

PubMed

Schreurs, Charlotte A; Algra, Annemijn M; Man, Sum-Che; Cannegieter, Suzanne C; van der Wall, Ernst E; Schalij, Martin J; Kors, Jan A; Swenne, Cees A

2010-01-01

The spatial QRS-T angle (SA), a predictor of sudden cardiac death, is a vectorcardiographic variable. Gold standard vertorcardiograms (VCGs) are recorded by using the Frank electrode positions. However, with the commonly available 12-lead ECG, VCGs must be synthesized by matrix multiplication (inverse Dower matrix/Kors matrix). Alternatively, Rautaharju proposed a method to calculate SA directly from the 12-lead ECG. Neither spatial angles computed by using the inverse Dower matrix (SA-D) nor by using the Kors matrix (SA-K) or by using Rautaharju's method (SA-R) have been validated with regard to the spatial angles as directly measured in the Frank VCG (SA-F). Our present study aimed to perform this essential validation. We analyzed SAs in 1220 simultaneously recorded 12-lead ECGs and VCGs, in all data, in SA-F-based tertiles, and after stratification according to pathology or sex. Linear regression of SA-K, SA-D, and SA-R on SA-F yielded offsets of 0.01 degree, 20.3 degrees, and 28.3 degrees and slopes of 0.96, 0.86, and 0.79, respectively. The bias of SA-K with respect to SA-F (mean +/- SD, -3.2 degrees +/- 13.9 degrees) was significantly (P < .001) smaller than the bias of both SA-D and SA-R with respect to SA-F (8.0 degrees +/- 18.6 degrees and 9.8 degrees +/- 24.6 degrees, respectively); tertile analysis showed a much more homogeneous behavior of the bias in SA-K than of both the bias in SA-D and in SA-R. In pathologic ECGs, there was no significant bias in SA-K; bias in men and women did not differ. SA-K resembled SA-F best. In general, when there is no specific reason either to synthesize VCGs with the inverse Dower matrix or to calculate the spatial QRS-T angle with Rautaharju's method, it seems prudent to use the Kors matrix. Copyright 2010 Elsevier Inc. All rights reserved.

Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries

PubMed Central

Law, Jane

2016-01-01

Intrinsic conditional autoregressive modeling in a Bayeisan hierarchical framework has been increasingly applied in small-area ecological studies. This study explores the specifications of spatial structure in this Bayesian framework in two aspects: adjacency, i.e., the set of neighbor(s) for each area; and (spatial) weight for each pair of neighbors. Our analysis was based on a small-area study of falling injuries among people age 65 and older in Ontario, Canada, that was aimed to estimate risks and identify risk factors of such falls. In the case study, we observed incorrect adjacencies information caused by deficiencies in the digital map itself. Further, when equal weights was replaced by weights based on a variable of expected count, the range of estimated risks increased, the number of areas with probability of estimated risk greater than one at different probability thresholds increased, and model fit improved. More importantly, significance of a risk factor diminished. Further research to thoroughly investigate different methods of variable weights; quantify the influence of specifications of spatial weights; and develop strategies for better defining spatial structure of a map in small-area analysis in Bayesian hierarchical spatial modeling is recommended. PMID:29546147

The sintered microsphere matrix for bone tissue engineering: in vitro osteoconductivity studies.

PubMed

Borden, Mark; Attawia, Mohamed; Laurencin, Cato T

2002-09-05

A tissue engineering approach has been used to design three-dimensional synthetic matrices for bone repair. The osteoconductivity and degradation profile of a novel polymeric bone-graft substitute was evaluated in an in vitro setting. Using the copolymer poly(lactide-co-glycolide) [PLAGA], a sintering technique based on microsphere technology was used to fabricate three-dimensional porous scaffolds for bone regeneration. Osteoblasts and fibroblasts were seeded onto a 50:50 PLAGA scaffold. Morphologic evaluation through scanning electron microscopy demonstrated that both cell types attached and spread over the scaffold. Cells migrated through the matrix using cytoplasmic extensions to bridge the structure. Cross-sectional images indicated that cellular proliferation had penetrated into the matrix approximately 700 microm from the surface. Examination of the surfaces of cell/matrix constructs demonstrated that cellular proliferation had encompassed the pores of the matrix by 14 days of cell culture. With the aim of optimizing polymer composition and polymer molecular weight, a degradation study was conducted utilizing the matrix. The results demonstrate that degradation of the sintered matrix is dependent on molecular weight, copolymer ratio, and pore volume. From this data, it was determined that 75:25 PLAGA with an initial molecular weight of 100,000 has an optimal degradation profile. These studies show that the sintered microsphere matrix has an osteoconductive structure capable of functioning as a cellular scaffold with a degradation profile suitable for bone regeneration. Copyright 2002 Wiley Periodicals, Inc.

Ultrasound Technologies for the Spatial Patterning of Cells and Extracellular Matrix Proteins and the Vascularization of Engineered Tissue

NASA Astrophysics Data System (ADS)

Garvin, Kelley A.

Technological advancements in the field of tissue engineering could save the lives of thousands of organ transplant patients who die each year while waiting for donor organs. Currently, two of the primary challenges preventing tissue engineers from developing functional replacement tissues and organs are the need to recreate complex cell and extracellular microenvironments and to vascularize the tissue to maintain cell viability and function. Ultrasound is a form of mechanical energy that can noninvasively and nondestructively interact with tissues at the cell and protein level. In this thesis, novel ultrasound-based technologies were developed for the spatial patterning of cells and extracellular matrix proteins and the vascularization of three-dimensional engineered tissue constructs. Acoustic radiation forces associated with ultrasound standing wave fields were utilized to noninvasively control the spatial organization of cells and cell-bound extracellular matrix proteins within collagen-based engineered tissue. Additionally, ultrasound induced thermal mechanisms were exploited to site-specifically pattern various extracellular matrix collagen microstructures within a single engineered tissue construct. Finally, ultrasound standing wave field technology was used to promote the rapid and extensive vascularization of three-dimensional tissue constructs. As such, the ultrasound technologies developed in these studies have the potential to provide the field of tissue engineering with novel strategies to spatially pattern cells and extracellular matrix components and to vascularize engineered tissue, and thus, could advance the fabrication of functional replacement tissues and organs in the field of tissue engineering.

Rich structure in the correlation matrix spectra in non-equilibrium steady states

NASA Astrophysics Data System (ADS)

Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H.

2017-01-01

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

Direct Measurement of the Density Matrix of a Quantum System

NASA Astrophysics Data System (ADS)

Thekkadath, G. S.; Giner, L.; Chalich, Y.; Horton, M. J.; Banker, J.; Lundeen, J. S.

2016-09-01

One drawback of conventional quantum state tomography is that it does not readily provide access to single density matrix elements since it requires a global reconstruction. Here, we experimentally demonstrate a scheme that can be used to directly measure individual density matrix elements of general quantum states. The scheme relies on measuring a sequence of three observables, each complementary to the last. The first two measurements are made weak to minimize the disturbance they cause to the state, while the final measurement is strong. We perform this joint measurement on polarized photons in pure and mixed states to directly measure their density matrix. The weak measurements are achieved using two walk-off crystals, each inducing a polarization-dependent spatial shift that couples the spatial and polarization degrees of freedom of the photons. This direct measurement method provides an operational meaning to the density matrix and promises to be especially useful for large dimensional states.

Direct Measurement of the Density Matrix of a Quantum System.

PubMed

Thekkadath, G S; Giner, L; Chalich, Y; Horton, M J; Banker, J; Lundeen, J S

2016-09-16

One drawback of conventional quantum state tomography is that it does not readily provide access to single density matrix elements since it requires a global reconstruction. Here, we experimentally demonstrate a scheme that can be used to directly measure individual density matrix elements of general quantum states. The scheme relies on measuring a sequence of three observables, each complementary to the last. The first two measurements are made weak to minimize the disturbance they cause to the state, while the final measurement is strong. We perform this joint measurement on polarized photons in pure and mixed states to directly measure their density matrix. The weak measurements are achieved using two walk-off crystals, each inducing a polarization-dependent spatial shift that couples the spatial and polarization degrees of freedom of the photons. This direct measurement method provides an operational meaning to the density matrix and promises to be especially useful for large dimensional states.

Rich structure in the correlation matrix spectra in non-equilibrium steady states.

PubMed

Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H

2017-01-17

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

16 CFR 303.10 - Fiber content of special types of products.

Code of Federal Regulations, 2010 CFR

2010-01-01

... percentages of such components by weight. (2) If the components of such fibers are of a matrix-fibril configuration, the term matrix-fibril fiber or matrix fiber may be used in setting forth the information...% Biconstituent Fiber (65% Nylon, 35% Polyester) 80% Matrix Fiber (60% Nylon, 40% Polyester) 15% Polyester 5...

[Locally weighted least squares estimation of DPOAE evoked by continuously sweeping primaries].

PubMed

Han, Xiaoli; Fu, Xinxing; Cui, Jie; Xiao, Ling

2013-12-01

Distortion product otoacoustic emission (DPOAE) signal can be used for diagnosis of hearing loss so that it has an important clinical value. Continuously using sweeping primaries to measure DPOAE provides an efficient tool to record DPOAE data rapidly when DPOAE is measured in a large frequency range. In this paper, locally weighted least squares estimation (LWLSE) of 2f1-f2 DPOAE is presented based on least-squares-fit (LSF) algorithm, in which DPOAE is evoked by continuously sweeping tones. In our study, we used a weighted error function as the loss function and the weighting matrixes in the local sense to obtain a smaller estimated variance. Firstly, ordinary least squares estimation of the DPOAE parameters was obtained. Then the error vectors were grouped and the different local weighting matrixes were calculated in each group. And finally, the parameters of the DPOAE signal were estimated based on least squares estimation principle using the local weighting matrixes. The simulation results showed that the estimate variance and fluctuation errors were reduced, so the method estimates DPOAE and stimuli more accurately and stably, which facilitates extraction of clearer DPOAE fine structure.

A rough set approach for determining weights of decision makers in group decision making

PubMed Central

Yang, Qiang; Du, Ping-an; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs’ decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member’ decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs’ evaluations and selections. PMID:28234974

Surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) of low molecular weight organic compounds and synthetic polymers using zinc oxide (ZnO) nanoparticles.

PubMed

Watanabe, Takehiro; Kawasaki, Hideya; Yonezawa, Tetsu; Arakawa, Ryuichi

2008-08-01

We have developed surface-assisted laser desorption/ionization mass spectrometry using zinc oxide (ZnO) nanoparticles with anisotropic shapes (ZnO-SALDI-MS). The mass spectra showed low background noises in the low m/z, i.e. less than 500 u region. Thus, we succeeded in SALDI ionization on low molecular weight organic compounds, such as verapamil hydrochloride, testosterone, and polypropylene glycol (PPG) (average molecular weight 400) without using a liquid matrix or buffers such as citric acids. In addition, we found that ZnO-SALDI has advantages in post-source decay (PSD) analysis and produced a simple mass spectrum for phospholipids. The ZnO-SALDI spectra for synthetic polymers of polyethylene glycol (PEG), polystyrene (PS) and polymethylmethacrylate (PMMA) showed the sensitivity and molecular weight distribution to be comparable to matrix-assisted laser desorption/ionization (MALDI) spectra with a 2,5-dihydroxybenzoic acid (DHB) matrix. ZnO-SALDI shows good performance for synthetic polymers as well as low molecular weight organic compounds. Copyright (c) 2008 John Wiley & Sons, Ltd.

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.

Effect of Matrix Size on the Image Quality of Ultra-high-resolution CT of the Lung: Comparison of 512 × 512, 1024 × 1024, and 2048 × 2048.

PubMed

Hata, Akinori; Yanagawa, Masahiro; Honda, Osamu; Kikuchi, Noriko; Miyata, Tomo; Tsukagoshi, Shinsuke; Uranishi, Ayumi; Tomiyama, Noriyuki

2018-01-16

This study aimed to assess the effect of matrix size on the spatial resolution and image quality of ultra-high-resolution computed tomography (U-HRCT). Slit phantoms and 11 cadaveric lungs were scanned on U-HRCT. Slit phantom scans were reconstructed using a 20-mm field of view (FOV) with 1024 matrix size and a 320-mm FOV with 512, 1024, and 2048 matrix sizes. Cadaveric lung scans were reconstructed using 512, 1024, and 2048 matrix sizes. Three observers subjectively scored the images on a three-point scale (1 = worst, 3 = best), in terms of overall image quality, noise, streak artifact, vessel, bronchi, and image findings. The median score of the three observers was evaluated by Wilcoxon signed-rank test with Bonferroni correction. Noise was measured quantitatively and evaluated with the Tukey test. A P value of <.05 was considered significant. The maximum spatial resolution was 0.14 mm; among the 320-mm FOV images, the 2048 matrix had the highest resolution and was significantly better than the 1024 matrix in terms of overall quality, solid nodule, ground-glass opacity, emphysema, intralobular reticulation, honeycombing, and clarity of vessels (P < .05). Both the 2048 and 1024 matrices performed significantly better than the 512 matrix (P < .001), except for noise and streak artifact. The visual and quantitative noise decreased significantly in the order of 512, 1024, and 2048 (P < .001). In U-HRCT scans, a large matrix size maintained the spatial resolution and improved the image quality and assessment of lung diseases, despite an increase in image noise, when compared to a 512 matrix size. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Highly conductive composites for fuel cell flow field plates and bipolar plates

DOEpatents

Jang, Bor Z; Zhamu, Aruna; Song, Lulu

2014-10-21

This invention provides a fuel cell flow field plate or bipolar plate having flow channels on faces of the plate, comprising an electrically conductive polymer composite. The composite is composed of (A) at least 50% by weight of a conductive filler, comprising at least 5% by weight reinforcement fibers, expanded graphite platelets, graphitic nano-fibers, and/or carbon nano-tubes; (B) polymer matrix material at 1 to 49.9% by weight; and (C) a polymer binder at 0.1 to 10% by weight; wherein the sum of the conductive filler weight %, polymer matrix weight % and polymer binder weight % equals 100% and the bulk electrical conductivity of the flow field or bipolar plate is at least 100 S/cm. The invention also provides a continuous process for cost-effective mass production of the conductive composite-based flow field or bipolar plate.

Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection.

PubMed

Wang, Haoran; Yuan, Chunfeng; Hu, Weiming; Ling, Haibin; Yang, Wankou; Sun, Changyin

2014-02-01

In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach.

Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

PubMed Central

Pnevmatikakis, Eftychios A.; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A.; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M.; Peterka, Darcy S.; Yuste, Rafael; Paninski, Liam

2016-01-01

SUMMARY We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multineuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. PMID:26774160

Matrix Sublimation/Recrystallization for Imaging Proteins by Mass Spectrometry at High Spatial Resolution

PubMed Central

Yang, Junhai; Caprioli, Richard M.

2011-01-01

We have employed matrix deposition by sublimation for protein image analysis on tissue sections using a hydration/recrystallization process that produces high quality MALDI mass spectra and high spatial resolution ion images. We systematically investigated different washing protocols, the effect of tissue section thickness, the amount of sublimated matrix per unit area and different recrystallization conditions. The results show that an organic solvent rinse followed by ethanol/water rinses substantially increased sensitivity for the detection of proteins. Both the thickness of tissue section and amount of sinapinic acid sublimated per unit area have optimal ranges for maximal protein signal intensity. Ion images of mouse and rat brain sections at 50, 20 and 10 µm spatial resolution are presented and are correlated with H&E stained optical images. For targeted analysis, histology directed imaging can be performed using this protocol where MS analysis and H&E staining are performed on the same section. PMID:21639088

Carbon nanodots as a matrix for the analysis of low-molecular-weight molecules in both positive- and negative-ion matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantification of glucose and uric acid in real samples.

PubMed

Chen, Suming; Zheng, Huzhi; Wang, Jianing; Hou, Jian; He, Qing; Liu, Huihui; Xiong, Caiqiao; Kong, Xianglei; Nie, Zongxiu

2013-07-16

Carbon nanodots were applied for the first time as a new matrix for the analysis of low-molecular-weight compounds by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in both positive- and negative-ion modes. A wide range of small molecules including amino acids, peptides, fatty acids, as well as β-agonists and neutral oligosaccharides were analyzed by MALDI MS with carbon nanodots as the matrix, and the lowest 0.2 fmol limits-of-detection were obtained for octadecanoic acid. Clear sodium and potassium adducts and deprotonated signals were produced in positive- and negative-ion modes. Furthermore, the glucose and uric acid in real samples were quantitatively determined by the internal standard method with the linear range of 0.5-9 mM and 0.1-1.8 mM (R(2) > 0.999), respectively. This work gives new insight into the application of carbon nanodots and provides a general approach for rapid analysis of low-molecular-weight compounds.

Algebro-geometric approach for a centrally extended Uq[sl(2|2)] R-matrix

NASA Astrophysics Data System (ADS)

Martins, M. J.

2017-04-01

In this paper we investigate the algebraic geometric nature of a solution of the Yang-Baxter equation based on the quantum deformation of the centrally extended sl (2 | 2) superalgebra proposed by Beisert and Koroteev [1]. We derive an alternative representation for the R-matrix in which the matrix elements are given in terms of rational functions depending on weights sited on a degree six surface. For generic gauge the weights geometry are governed by a genus one ruled surface while for a symmetric gauge choice the weights lie instead on a genus five curve. We have written down the polynomial identities satisfied by the R-matrix entries needed to uncover the corresponding geometric properties. For arbitrary gauge the R-matrix geometry is argued to be birational to the direct product CP1 ×CP1 × A where A is an Abelian surface. For the symmetric gauge we present evidences that the geometric content is that of a surface of general type lying on the so-called Severi line with irregularity two and geometric genus nine. We discuss potential geometric degenerations when the two free couplings are restricted to certain one-dimensional subspaces.

A Method of Q-Matrix Validation for the Linear Logistic Test Model

PubMed Central

Baghaei, Purya; Hohensinn, Christine

2017-01-01

The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices. PMID:28611721

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.

Use of the maximum entropy method to retrieve the vertical atmospheric ozone profile and predict atmospheric ozone content

NASA Technical Reports Server (NTRS)

Turner, B. Curtis

1992-01-01

A method is developed for prediction of ozone levels in planetary atmospheres. This method is formulated in terms of error covariance matrices, and is associated with both direct measurements, a priori first guess profiles, and a weighting function matrix. This is described by the following linearized equation: y = A(matrix) x X + eta, where A is the weighting matrix and eta is noise. The problems to this approach are: (1) the A matrix is near singularity; (2) the number of unknowns in the profile exceeds the number of data points, therefore, the solution may not be unique; and (3) even if a unique solution exists, eta may cause the solution to be ill conditioned.

Gyroaveraging operations using adaptive matrix operators

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

Dominski, Julien; Ku, Seung -Hoe; Chang, Choong -Seock

A new adaptive scheme to be used in particle-in-cell codes for carrying out gyroaveraging operations with matrices is presented. This new scheme uses an intermediate velocity grid whose resolution is adapted to the local thermal Larmor radius. The charge density is computed by projecting marker weights in a field-line following manner while preserving the adiabatic magnetic moment μ. These choices permit to improve the accuracy of the gyroaveraging operations performed with matrices even when strong spatial variation of temperature and magnetic field is present. Accuracy of the scheme in different geometries from simple 2D slab geometry to realistic 3D toroidalmore » equilibrium has been studied. As a result, a successful implementation in the gyrokinetic code XGC is presented in the delta-f limit.« less

Compression of Born ratio for fluorescence molecular tomography/x-ray computed tomography hybrid imaging: methodology and in vivo validation.

PubMed

Mohajerani, Pouyan; Ntziachristos, Vasilis

2013-07-01

The 360° rotation geometry of the hybrid fluorescence molecular tomography/x-ray computed tomography modality allows for acquisition of very large datasets, which pose numerical limitations on the reconstruction. We propose a compression method that takes advantage of the correlation of the Born-normalized signal among sources in spatially formed clusters to reduce the size of system model. The proposed method has been validated using an ex vivo study and an in vivo study of a nude mouse with a subcutaneous 4T1 tumor, with and without inclusion of a priori anatomical information. Compression rates of up to two orders of magnitude with minimum distortion of reconstruction have been demonstrated, resulting in large reduction in weight matrix size and reconstruction time.

Gyroaveraging operations using adaptive matrix operators

DOE PAGES

Dominski, Julien; Ku, Seung -Hoe; Chang, Choong -Seock

2018-05-17

A new adaptive scheme to be used in particle-in-cell codes for carrying out gyroaveraging operations with matrices is presented. This new scheme uses an intermediate velocity grid whose resolution is adapted to the local thermal Larmor radius. The charge density is computed by projecting marker weights in a field-line following manner while preserving the adiabatic magnetic moment μ. These choices permit to improve the accuracy of the gyroaveraging operations performed with matrices even when strong spatial variation of temperature and magnetic field is present. Accuracy of the scheme in different geometries from simple 2D slab geometry to realistic 3D toroidalmore » equilibrium has been studied. As a result, a successful implementation in the gyrokinetic code XGC is presented in the delta-f limit.« less

Flight Control System for the CRCA (Control Reconfigurable Combat Aircraft) Using a Command Generator Tracker with PI (Plus Integral) Feedback and Kalman Filter. Volume 2

DTIC Science & Technology

1989-03-01

IAutomatic Control, AC-22, p 883-885, 1977 /Syntax check EIGA=EIG(A); EIGB=EIG(B); [M,N)=SIZE(EIGA); [PR] SIZE(EIGB); FOR 11I:M,FOR JlI:P,.... EIGAB=EIGA...AIM = implicit model A matrix I/ QI = weighting matrix, ouputs mimic model I/ RI = weighting matrix, controls mimic model // QIHAT = implicit cost II...the dimension is less than 1. // NINPUTS (the number of controls and outputs) is the flag for the dimensio // of the connections. /- // The name of

SMI adaptive antenna arrays for weak interfering signals. [Sample Matrix Inversion

NASA Technical Reports Server (NTRS)

Gupta, Inder J.

1986-01-01

The performance of adaptive antenna arrays in the presence of weak interfering signals (below thermal noise) is studied. It is shown that a conventional adaptive antenna array sample matrix inversion (SMI) algorithm is unable to suppress such interfering signals. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is redefined such that the effect of thermal noise on the weights of adaptive arrays is reduced. Thus, the weights are dictated by relatively weak signals. It is shown that the modified algorithm provides the desired interference protection.

A Model for the Oxidation of Carbon Silicon Carbide Composite Structures

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.

2004-01-01

A mathematical theory and an accompanying numerical scheme have been developed for predicting the oxidation behavior of carbon silicon carbide (C/SiC) composite structures. The theory is derived from the mechanics of the flow of ideal gases through a porous solid. The result of the theoretical formulation is a set of two coupled nonlinear differential equations written in terms of the oxidant and oxide partial pressures. The differential equations are solved simultaneously to obtain the partial vapor pressures of the oxidant and oxides as a function of the spatial location and time. The local rate of carbon oxidation is determined using the map of the local oxidant partial vapor pressure along with the Arrhenius rate equation. The nonlinear differential equations are cast into matrix equations by applying the Bubnov-Galerkin weighted residual method, allowing for the solution of the differential equations numerically. The numerical method is demonstrated by utilizing the method to model the carbon oxidation and weight loss behavior of C/SiC specimens during thermogravimetric experiments. The numerical method is used to study the physics of carbon oxidation in carbon silicon carbide composites.

Low molecular weight polylactic acid as a matrix for the delayed release of pesticides.

PubMed

Zhao, Jing; Wilkins, Richard M

2005-05-18

Low molecular weight polylactic acid (LMW PLA) was used as a matrix to formulate biodegradable matrix granules and films with bromacil using a melt process. The compatibility of the PLA with bromacil was evaluated. The release characteristics of the formulations were investigated in vitro. The degradation and erosion of the formulations were monitored by pH and gravimetric analysis during the course of release. Various granules and films had similar biphasic release patterns, a delayed release followed by an explosive release. The release rates were independent of bromacil content in the matrix, but varied with the geometry of matrices. The mechanisms of diffusion and erosion were involved in the release. The delayed release of the formulations was dominantly governed by the degradation and erosion of PLA. LMW PLA underwent bulk erosion. LMW PLA-based matrix formulations could thus be useful for the application of pesticides to sensitive targets such as seed treatment.

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…

Modeling of non-uniform spatial arrangement of fibers in a ceramic matrix composite

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

Yang, S.; Tewari, A.; Gokhale, A.M.

In the unidirectional fiber reinforced composites, the spatial agreement of fibers is often non-uniform. These non-uniformities are linked to the processing conditions, and they affect the properties of the composite. In this contribution, a recently developed digital image analysis technique is used to quantify the non-uniform spatial arrangement of Nicalon fibers in a ceramic matrix composite (CMC). These quantitative data are utilized to develop a six parameter computer simulated microstructure model that is statistically equivalent to the non-uniform microstructure of the CMC. The simulated microstructure can be utilized as a RVE for the micro-mechanical modeling studies.

An efficient method for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

An efficient method of computation of the manipulator inertia matrix is presented. Using spatial notations, the method leads to the definition of the composite rigid-body spatial inertia, which is a spatial representation of the notion of augmented body. The previously proposed methods, the physical interpretations leading to their derivation, and their redundancies are analyzed. The proposed method achieves a greater efficiency by eliminating the redundancy in the intrinsic equations as well as by a better choice of coordinate frame for their projection. In this case, removing the redundancy leads to greater efficiency of the computation in both serial and parallel senses.

A Study on 3-Body Abrasive Wear Behaviour of Aluminium 8011 / Graphite Metal Matrix Composite

NASA Astrophysics Data System (ADS)

Latha Shankar, B.; Anil, K. C.; Patil, Rahul

2016-09-01

Metals and alloys have found their vital role in many applications like structural, corrosive, tribological, etc., in engineering environment. The alloys/composites having high strength to low weight ratio have gained attention of many researchers recently. In this work, graphite reinforced Aluminium 8011 metal matrix composite was prepared by conventional stir casting route, by varying the weight % of reinforcement. Uniform distribution of Graphite in matrix alloy was confirmed by optical micrographs. Prepared composite specimens were subjected to 3-body abrasive testing by varying applied load and time, the silica particles of 400 grit size were used as abrasive particles. It was observed that with the increase of weight% of Graphite the wear resistance of composite was also increasing and on comparison it was found that reinforced composite gives good wear resistance than base alloy.

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.

Platelet geometry sensing spatially regulates α-granule secretion to enable matrix self-deposition

PubMed Central

Sakurai, Yumiko; Fitch-Tewfik, Jennifer L.; Qiu, Yongzhi; Ahn, Byungwook; Myers, David R.; Tran, Reginald; Fay, Meredith E.; Ding, Lingmei; Spearman, Paul W.; Michelson, Alan D.; Flaumenhaft, Robert

2015-01-01

Although the biology of platelet adhesion on subendothelial matrix after vascular injury is well characterized, how the matrix biophysical properties affect platelet physiology is unknown. Here we demonstrate that geometric orientation of the matrix itself regulates platelet α-granule secretion, a key component of platelet activation. Using protein microcontact printing, we show that platelets spread beyond the geometric constraints of fibrinogen or collagen micropatterns with <5-µm features. Interestingly, α-granule exocytosis and deposition of the α-granule contents such as fibrinogen and fibronectin were primarily observed in those areas of platelet extension beyond the matrix protein micropatterns. This enables platelets to “self-deposit” additional matrix, provide more cellular membrane to extend spreading, and reinforce platelet-platelet connections. Mechanistically, this phenomenon is mediated by actin polymerization, Rac1 activation, and αIIbβ3 integrin redistribution and activation, and is attenuated in gray platelet syndrome platelets, which lack α-granules, and Wiskott-Aldrich syndrome platelets, which have cytoskeletal defects. Overall, these studies demonstrate how platelets transduce geometric cues of the underlying matrix geometry into intracellular signals to extend spreading, which endows platelets spatial flexibility when spreading onto small sites of exposed subendothelium. PMID:25964667

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Sequential design of discrete linear quadratic regulators via optimal root-locus techniques

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Yates, Robert E.; Ganesan, Sekar

1989-01-01

A sequential method employing classical root-locus techniques has been developed in order to determine the quadratic weighting matrices and discrete linear quadratic regulators of multivariable control systems. At each recursive step, an intermediate unity rank state-weighting matrix that contains some invariant eigenvectors of that open-loop matrix is assigned, and an intermediate characteristic equation of the closed-loop system containing the invariant eigenvalues is created.

WALLY 1 ...A large, principal components regression program with varimax rotation of the factor weight matrix

Treesearch

James R. Wallis

1965-01-01

Written in Fortran IV and MAP, this computer program can handle up to 120 variables, and retain 40 principal components. It can perform simultaneous regression of up to 40 criterion variables upon the varimax rotated factor weight matrix. The columns and rows of all output matrices are labeled by six-character alphanumeric names. Data input can be from punch cards or...

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

PubMed

You, Li; Brown, Joel S; Thuijsman, Frank; Cunningham, Jessica J; Gatenby, Robert A; Zhang, Jingsong; Staňková, Kateřina

2017-12-21

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T + ), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T P ), and (3) those independent of testosterone (T - ). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T -  cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

CPDES3: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in three dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on three-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES3 allows each spatial operator to have 7, 15, 19, or 27 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect induces which is vectorizable on some of the newer scientific computers.

CPDES2: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in two dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on two-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES2 allows each spatial operator to have 5 or 9 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect indices which is vectorizable on some of the newer scientific computers.

Estimating neighborhood variability with a binary comparison matrix.

USGS Publications Warehouse

Murphy, D.L.

1985-01-01

A technique which utilizes a binary comparison matrix has been developed to implement a neighborhood function for a raster format data base. The technique assigns an index value to the center pixel of 3- by 3-pixel neighborhoods. The binary comparison matrix provides additional information not found in two other neighborhood variability statistics; the function is sensitive to both the number of classes within the neighborhood and the frequency of pixel occurrence in each of the classes. Application of the function to a spatial data base from the Kenai National Wildlife Refuge, Alaska, demonstrates 1) the numerical distribution of the index values, and 2) the spatial patterns exhibited by the numerical values. -Author

Spatial coding-based approach for partitioning big spatial data in Hadoop

NASA Astrophysics Data System (ADS)

Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai

2017-09-01

Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix-assisted laser desorption ionization imaging and spatial segmentation.

PubMed

Ernst, Günther; Guntinas-Lichius, Orlando; Hauberg-Lotte, Lena; Trede, Dennis; Becker, Michael; Alexandrov, Theodore; von Eggeling, Ferdinand

2015-07-01

Despite efforts in localization of key proteins using immunohistochemistry, the complex proteomic composition of pleomorphic adenomas has not yet been characterized. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging) allows label-free and spatially resolved detection of hundreds of proteins directly from tissue sections and of histomorphological regions by finding colocalized molecular signals. Spatial segmentation of MALDI imaging data is an algorithmic method for finding regions of similar proteomic composition as functionally similar regions. We investigated 2 pleomorphic adenomas by applying spatial segmentation to the MALDI imaging data of tissue sections. The spatial segmentation subdivided the tissue in a good accordance with the tissue histology. Numerous molecular signals colocalized with histologically defined tissue regions were found. Our study highlights the cellular transdifferentiation within the pleomorphic adenoma. It could be shown that spatial segmentation of MALDI imaging data is a promising approach in the emerging field of digital histological analysis and characterization of tumors. © 2014 Wiley Periodicals, Inc.

Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.

PubMed

Tiezzi, Francesco; Maltecca, Christian

2015-04-02

Genomic BLUP (GBLUP) can predict breeding values for non-phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The G matrix can be constructed from thousands of markers spread across the genome. The strongest assumption of G and consequently of GBLUP is that all markers contribute equally to the genetic variance of a trait. This assumption is violated for traits that are controlled by a small number of quantitative trait loci (QTL) or individual QTL with large effects. In this paper, we investigate the performance of using a weighted genomic relationship matrix (wG) that takes into consideration the genetic architecture of the trait in order to improve predictive ability for a wide range of traits. Multiple methods were used to calculate weights for several economically relevant traits in US Holstein dairy cattle. Predictive performance was tested by k-means cross-validation. Relaxing the GBLUP assumption of equal marker contribution by increasing the weight that is given to a specific marker in the construction of the trait-specific G resulted in increased predictive performance. The increase was strongest for traits that are controlled by a small number of QTL (e.g. fat and protein percentage). Furthermore, bias in prediction estimates was reduced compared to that resulting from the use of regular G. Even for traits with low heritability and lower general predictive performance (e.g. calving ease traits), weighted G still yielded a gain in accuracy. Genomic relationship matrices weighted by marker realized variance yielded more accurate and less biased predictions for traits regulated by few QTL. Genome-wide association analyses were used to derive marker weights for creating weighted genomic relationship matrices. However, this can be cumbersome and prone to low stability over generations because of erosion of linkage disequilibrium between markers and QTL. Future studies may include other sources of information, such as functional annotation and gene networks, to better exploit the genetic architecture of traits and produce more stable predictions.

Polymer Molecular Weight Analysis by [Superscript 1]H NMR Spectroscopy

ERIC Educational Resources Information Center

Izunobi, Josephat U.; Higginbotham, Clement L.

2011-01-01

The measurement and analysis of molecular weight and molecular weight distribution remain matters of fundamental importance for the characterization and physical properties of polymers. Gel permeation chromatography (GPC) is the most routinely used method for the molecular weight determination of polymers whereas matrix-assisted laser…

Abrasion resistant composition

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

Fischer, Keith D; Barnes, Christopher A; Henderson, Stephen L

A surface covering composition of abrasion resistant character adapted for disposition in overlying bonded relation to a metal substrate. The surface covering composition includes metal carbide particles within a metal matrix at a packing factor of not less than about 0.6. Not less than about 40 percent by weight of the metal carbide particles are characterized by an effective diameter in the range of +14-32 mesh prior to introduction to the metal matrix. Not less than about 3 percent by weight of the metal carbide particles are characterized by an effective diameter of +60 mesh prior to introduction to themore » metal matrix.« less

An Empirical State Error Covariance Matrix for the Weighted Least Squares Estimation Method

NASA Technical Reports Server (NTRS)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the un-certainty in the estimated states. By a reinterpretation of the equations involved in the weighted least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. This proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. Results based on the proposed technique will be presented for a simple, two observer, measurement error only problem.

Characterization of PMR-15 polyimide composition in thermo-oxidatively exposed graphite fiber composites

NASA Technical Reports Server (NTRS)

Alston, W. B.

1980-01-01

The contributions of individual resin components to total resin weight loss in 600 F air aged Celion 6000/PMR-15 polyimide composites were determined from the overall resin weight loss in the composite by chemically separating the PMR-15 matrix resin into its monomeric components. The individual resin components were also analyzed by spectroscopic techniques in order to elucidate curing and degradation mechanisms of the PMR-15 matrix resin. The isothermal weight loss of the individual resin components during prolonged 600 F thermo-oxidative aging of the composite was correlated to the changes observed in the Fourier Transform infrared spectra and Fourier Transform nuclear magnetic resonance spectra of the individual resin components. The correlation was used to identify the molecular site of the thermo-oxidative changes in PMR-15 polyimide matrix resin during 600 F curing the prolonged 600 F thermo-oxidative aging.

Polyimide molding powder, coating, adhesive, and matrix resin

NASA Technical Reports Server (NTRS)

St.clair, Terry L. (Inventor); Progar, Donald J. (Inventor)

1992-01-01

The invention is a polyimide prepared from 3,4'-oxydianiline (3,4'-ODA) and 4,4'-oxydiphthalic anhydride (ODPA), in 2-methoxyethyl ether (diglyme). The polymer was prepared in ultra high molecular weight and in a controlled molecular weight form which has a 2.5 percent offset in stoichiometry (excess diamine) with a 5.0 percent level of phthalic anhydride as an endcap. This controlled molecular weight form allows for greatly improved processing of the polymer for moldings, adhesive bonding, and composite fabrication. The higher molecular weight version affords tougher films and coatings. The overall polymer structure groups in the dianhydride, the diamine, and a metal linkage in the diamine affords adequate flow properties for making this polymer useful as a molding powder, adhesive, and matrix resin.

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

NASA Astrophysics Data System (ADS)

Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

2017-10-01

Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

Quantifying spatial and temporal trends in beach-dune volumetric changes using spatial statistics

NASA Astrophysics Data System (ADS)

Eamer, Jordan B. R.; Walker, Ian J.

2013-06-01

Spatial statistics are generally underutilized in coastal geomorphology, despite offering great potential for identifying and quantifying spatial-temporal trends in landscape morphodynamics. In particular, local Moran's Ii provides a statistical framework for detecting clusters of significant change in an attribute (e.g., surface erosion or deposition) and quantifying how this changes over space and time. This study analyzes and interprets spatial-temporal patterns in sediment volume changes in a beach-foredune-transgressive dune complex following removal of invasive marram grass (Ammophila spp.). Results are derived by detecting significant changes in post-removal repeat DEMs derived from topographic surveys and airborne LiDAR. The study site was separated into discrete, linked geomorphic units (beach, foredune, transgressive dune complex) to facilitate sub-landscape scale analysis of volumetric change and sediment budget responses. Difference surfaces derived from a pixel-subtraction algorithm between interval DEMs and the LiDAR baseline DEM were filtered using the local Moran's Ii method and two different spatial weights (1.5 and 5 m) to detect statistically significant change. Moran's Ii results were compared with those derived from a more spatially uniform statistical method that uses a simpler student's t distribution threshold for change detection. Morphodynamic patterns and volumetric estimates were similar between the uniform geostatistical method and Moran's Ii at a spatial weight of 5 m while the smaller spatial weight (1.5 m) consistently indicated volumetric changes of less magnitude. The larger 5 m spatial weight was most representative of broader site morphodynamics and spatial patterns while the smaller spatial weight provided volumetric changes consistent with field observations. All methods showed foredune deflation immediately following removal with increased sediment volumes into the spring via deposition at the crest and on lobes in the lee, despite erosion on the stoss slope and dune toe. Generally, the foredune became wider by landward extension and the seaward slope recovered from erosion to a similar height and form to that of pre-restoration despite remaining essentially free of vegetation.

A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

PubMed

Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

2017-05-01

Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Complete spatiotemporal characterization and optical transfer matrix inversion of a 420 mode fiber.

PubMed

Carpenter, Joel; Eggleton, Benjamin J; Schröder, Jochen

2016-12-01

The ability to measure a scattering medium's optical transfer matrix, the mapping between any spatial input and output, has enabled applications such as imaging to be performed through media which would otherwise be opaque due to scattering. However, the scattering of light occurs not just in space, but also in time. We complete the characterization of scatter by extending optical transfer matrix methods into the time domain, allowing any spatiotemporal input state at one end to be mapped directly to its corresponding spatiotemporal output state. We have measured the optical transfer function of a multimode fiber in its entirety; it consists of 420 modes in/out at 32768 wavelengths, the most detailed complete characterization of multimode waveguide light propagation to date, to the best of our knowledge. We then demonstrate the ability to generate any spatial/polarization state at the output of the fiber at any wavelength, as well as predict the temporal response of any spatial/polarization input state.

Complex mode indication function and its applications to spatial domain parameter estimation

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

This paper introduces the concept of the Complex Mode Indication Function (CMIF) and its application in spatial domain parameter estimation. The concept of CMIF is developed by performing singular value decomposition (SVD) of the Frequency Response Function (FRF) matrix at each spectral line. The CMIF is defined as the eigenvalues, which are the square of the singular values, solved from the normal matrix formed from the FRF matrix, [ H( jω)] H[ H( jω)], at each spectral line. The CMIF appears to be a simple and efficient method for identifying the modes of the complex system. The CMIF identifies modes by showing the physical magnitude of each mode and the damped natural frequency for each root. Since multiple reference data is applied in CMIF, repeated roots can be detected. The CMIF also gives global modal parameters, such as damped natural frequencies, mode shapes and modal participation vectors. Since CMIF works in the spatial domain, uneven frequency spacing data such as data from spatial sine testing can be used. A second-stage procedure for accurate damped natural frequency and damping estimation as well as mode shape scaling is also discussed in this paper.

Heterogeneous Link Weight Promotes the Cooperation in Spatial Prisoner's Dilemma

NASA Astrophysics Data System (ADS)

Ma, Zhi-Qin; Xia, Cheng-Yi; Sun, Shi-Wen; Wang, Li; Wang, Huai-Bin; Wang, Juan

The spatial structure has often been identified as a prominent mechanism that substantially promotes the cooperation level in prisoner's dilemma game. In this paper we introduce a weighting mechanism into the spatial prisoner's dilemma game to explore the cooperative behaviors on the square lattice. Here, three types of weight distributions: exponential, power-law and uniform distributions are considered, and the weight is assigned to links between players. Through large-scale numerical simulations we find, compared with the traditional spatial game, that this mechanism can largely enhance the frequency of cooperators. For most ranges of b, we find that the power-law distribution enables the highest promotion of cooperation and the uniform one leads to the lowest enhancement, whereas the exponential one lies often between them. The great improvement of cooperation can be caused by the fact that the distributional link weight yields inhomogeneous interaction strength among individuals, which can facilitate the formation of cooperative clusters to resist the defector's invasion. In addition, the impact of amplitude of the undulation of weight distribution and noise strength on cooperation is also investigated for three kinds of weight distribution. Current researches can aid in the further understanding of evolutionary cooperation in biological and social science.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

A Study on Effect of Graphite Particles on Tensile, Hardness and Machinability of Aluminium 8011 Matrix Material

NASA Astrophysics Data System (ADS)

Latha Shankar, B.; Anil, K. C.; Karabasappagol, Prasann J.

2016-09-01

Industrial application point of view, metal matrix composites in general and Aluminium alloy matrix composites in particular are ideal candidates because of their favourable engineering properties. Being lightweight Aluminium matrix composites are widely used in aircraft, defence and automotive industries. In this work Aluminium 8011 metal matrix was reinforced with fine Graphite particles of 50 μm. developed by two-step Stir casting method. Graphite weight %was varied in the range 2, 4, 6 and 8%. Uniform dispersion of graphite particle is examined under optical microscope. Tensile test coupons were prepared as per standard to determine % of elongation and tensile strength for various % of graphite particle. Hardness of developed composite for various % of graphite particle and Machinability parameters were also studied for effect on surface finish. It was observed that with increase of weight percentage of Graphite particles up to 8% in Aluminium 8011 alloy matrix there was increase in tensile strength, decrease in % of elongation with increase in hardness. Machinability study revealed that, there was decrease in surface roughness with increase in Graphite content.

Polar decomposition for attitude determination from vector observations

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.

1993-01-01

This work treats the problem of weighted least squares fitting of a 3D Euclidean-coordinate transformation matrix to a set of unit vectors measured in the reference and transformed coordinates. A closed-form analytic solution to the problem is re-derived. The fact that the solution is the closest orthogonal matrix to some matrix defined on the measured vectors and their weights is clearly demonstrated. Several known algorithms for computing the analytic closed form solution are considered. An algorithm is discussed which is based on the polar decomposition of matrices into the closest unitary matrix to the decomposed matrix and a Hermitian matrix. A somewhat longer improved algorithm is suggested too. A comparison of several algorithms is carried out using simulated data as well as real data from the Upper Atmosphere Research Satellite. The comparison is based on accuracy and time consumption. It is concluded that the algorithms based on polar decomposition yield a simple although somewhat less accurate solution. The precision of the latter algorithms increase with the number of the measured vectors and with the accuracy of their measurement.

On the transfer matrix of the supersymmetric eight-vertex model. I. Periodic boundary conditions

NASA Astrophysics Data System (ADS)

Hagendorf, Christian; Liénardy, Jean

2018-03-01

The square-lattice eight-vertex model with vertex weights a, b, c, d obeying the relation (a^2+ab)(b^2+ab) = (c^2+ab)(d^2+ab) and periodic boundary conditions is considered. It is shown that the transfer matrix of the model for L  =  2n  +  1 vertical lines and periodic boundary conditions along the horizontal direction possesses the doubly degenerate eigenvalue \\Thetan = (a+b){\\hspace{0pt}}2n+1 . This proves a conjecture by Stroganov from 2001. The proof uses the supersymmetry of a related XYZ spin-chain Hamiltonian. The eigenstates of the transfer matrix corresponding to \\Thetan are shown to be the ground states of the spin-chain Hamiltonian. Moreover, for positive vertex weights \\Thetan is the largest eigenvalue of the transfer matrix.

Evolution of In-Situ Generated Reinforcement Precipitates in Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Sen, S.; Kar, S. K.; Catalina, A. V.; Stefanescu, D. M.; Dhindaw, B. K.

2004-01-01

Due to certain inherent advantages, in-situ production of Metal Matrix Composites (MMCs) have received considerable attention in the recent past. ln-situ techniques typically involve a chemical reaction that results in precipitation of a ceramic reinforcement phase. The size and spatial distribution of these precipitates ultimately determine the mechanical properties of these MMCs. In this paper we will investigate the validity of using classical growth laws and analytical expressions to describe the interaction between a precipitate and a solid-liquid interface (SLI) to predict the size and spatial evolution of the in-situ generated precipitates. Measurements made on size and distribution of Tic precipitates in a Ni&I matrix will be presented to test the validity of such an approach.

Decentralized state estimation for a large-scale spatially interconnected system.

PubMed

Liu, Huabo; Yu, Haisheng

2018-03-01

A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Matrix-free and material-enhanced laser desorption/ionization mass spectrometry for the analysis of low molecular weight compounds.

PubMed

Rainer, Matthias; Qureshi, Muhammad Nasimullah; Bonn, Günther Karl

2011-06-01

The application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for the analysis of low molecular weight (LMW) compounds, such as pharmacologically active constituents or metabolites, is usually hampered by employing conventional MALDI matrices owing to interferences caused by matrix molecules below 700 Da. As a consequence, interpretation of mass spectra remains challenging, although matrix suppression can be achieved under certain conditions. Unlike the conventional MALDI methods which usually suffer from background signals, matrix-free techniques have become more and more popular for the analysis of LMW compounds. In this review we describe recently introduced materials for laser desorption/ionization (LDI) as alternatives to conventionally applied MALDI matrices. In particular, we want to highlight a new method for LDI which is referred to as matrix-free material-enhanced LDI (MELDI). In matrix-free MELDI it could be clearly shown, that besides chemical functionalities, the material's morphology plays a crucial role regarding energy-transfer capabilities. Therefore, it is of great interest to also investigate parameters such as particle size and porosity to study their impact on the LDI process. Especially nanomaterials such as diamond-like carbon, C(60) fullerenes and nanoparticulate silica beads were found to be excellent energy-absorbing materials in matrix-free MELDI.

Graphene as a Novel Matrix for the Analysis of Small Molecules by MALDI-TOF MS

PubMed Central

Dong, Xiaoli; Cheng, Jinsheng; Li, Jinghong; Wang, Yinsheng

2010-01-01

Graphene was utilized for the first time as matrix for the analysis of low-molecular weight compounds using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Polar compounds including amino acids, polyamines, anticancer drugs and nucleosides could be successfully analyzed. Additionally, nonpolar compounds including steroids could be detected with high resolution and sensitivity. Compared with conventional matrix, graphene exhibited high desorption/ionization efficiency for nonpolar compounds. The graphene matrix functions as substrate to trap analytes, and it transfers energy to the analytes upon laser irradiation, which allowed for the analytes to be readily desorbed/ionized and interference of intrinsic matrix ions to be eliminated. The use of graphene as matrix avoided the fragmentation of analytes and provided good reproducibility and high salt tolerance, underscoring the potential application of graphene as matrix for MALDI-MS analysis of practical samples in complex sample matrices. We also demonstrated that the use of graphene as adsorbent for the solid-phase extraction of squalene could improve greatly the detection limit. This work not only opens a new field for applications of graphene, but also offers a new technique for high-speed analysis of low-molecular weight compounds in areas such as metabolism research and natural products characterization. PMID:20565059

Rapid motif compliance scoring with match weight sets.

PubMed

Venezia, D; O'Hara, P J

1993-02-01

Most current implementations of motif matching in biological sequences have sacrificed the generality of weight matrix scoring for shorter runtimes. The program MOTIF incorporates a weight matrix and a rapid, backtracking tree-search algorithm to score motif compliance with greatly enhanced performance while placing no constraints on the motif. In addition, any positions within a motif can be marked as 'inviolate', thereby requiring an exact match. MOTIF allows a choice of regular expression formats and can use both motif and sequence libraries as either targets or queries. Nucleic acid sequences can optionally be translated by MOTIF in any frame(s) and used against peptide motifs.

Thermo-oxidative stability studies of PMR-15 polymer matrix composites reinforced with various fibers

NASA Technical Reports Server (NTRS)

Bowles, Kenneth J.

1990-01-01

An experimental study was conducted to measure the thermo-oxidative stability of PMR-15 polymer matrix composites reinforced with various fibers and to observe differences in the way they degrade in air. The fibers that were studied included graphite and the thermally stable Nicalon and Nextel ceramic fibers. Weight loss rates for the different composites were assessed as a function of mechanical properties, specimen geometry, fiber sizing, and interfacial bond strength. Differences were observed in rates of weight loss, matrix cracking, geometry dependency, and fiber-sizing effects. It was shown that Celion 6000 fiber-reinforced composites do not exhibit a straight-line Arrhenius relationship at temperatures above 316 C.

Role of the Euclidean signature in lattice calculations of quasidistributions and other nonlocal matrix elements

NASA Astrophysics Data System (ADS)

Briceño, Raúl A.; Hansen, Maxwell T.; Monahan, Christopher J.

2017-07-01

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate that the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Finally we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.

Role of the Euclidean signature in lattice calculations of quasidistributions and other nonlocal matrix elements

DOE PAGES

Briceno, Raul A.; Hansen, Maxwell T.; Monahan, Christopher J.

2017-07-11

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate thatmore » the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Lastly, we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.« less

An Empirical State Error Covariance Matrix for Batch State Estimation

NASA Technical Reports Server (NTRS)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty. Also, in its most straight forward form, the technique only requires supplemental calculations to be added to existing batch algorithms. The generation of this direct, empirical form of the state error covariance matrix is independent of the dimensionality of the observations. Mixed degrees of freedom for an observation set are allowed. As is the case with any simple, empirical sample variance problems, the presented approach offers an opportunity (at least in the case of weighted least squares) to investigate confidence interval estimates for the error covariance matrix elements. The diagonal or variance terms of the error covariance matrix have a particularly simple form to associate with either a multiple degree of freedom chi-square distribution (more approximate) or with a gamma distribution (less approximate). The off diagonal or covariance terms of the matrix are less clear in their statistical behavior. However, the off diagonal covariance matrix elements still lend themselves to standard confidence interval error analysis. The distributional forms associated with the off diagonal terms are more varied and, perhaps, more approximate than those associated with the diagonal terms. Using a simple weighted least squares sample problem, results obtained through use of the proposed technique are presented. The example consists of a simple, two observer, triangulation problem with range only measurements. Variations of this problem reflect an ideal case (perfect knowledge of the range errors) and a mismodeled case (incorrect knowledge of the range errors).

Thermo-Oxidative Stability of Graphite/PMR-15 Composites: Effect of Fiber Surface Modification on Composite Shear Properties

NASA Technical Reports Server (NTRS)

Madhukar, Madhu S.; Bowles, Kenneth J.; Papadopolous, Demetrios S.

1994-01-01

Experiments were conducted to establish a correlation between the weight loss of a polyimide (PMR- 15) matrix and graphite fibers and the in-plane shear properties of their unidirectional composites subjected to different isothermal aging times up to 1000 hr at 316 C. The role of fiber surface treatment on the composite degradation during the thermo-oxidative aging was investigated by using A4 graphite fibers with three surface modifications: untreated (AU-4), surface treated (AS-4), and surface treated and sized with an epoxy-compatible sizing (AS-4G). The weight loss of the matrix fibers, and composites was determined during the aging. The effect of thermal aging was seen in all the fiber samples in terms of weight loss and reduction in fiber diameter. Calculated values of weight loss fluxes for different surfaces of rectangular unidirectional composite plates showed that the largest weight loss occurred at those cut surfaces where fibers were perpendicular to the surface. Consequently, the largest amount of damage was also noted on these cut surfaces. Optical observation of the neat matrix and composite plates subjected to different aging times revealed that the degradation (such as matrix microcracking and void growth) occurred in a thin surface layer near the specimen edges. The in-plane shear modulus of the composites was unaffected by the fiber surface treatment and the thermal aging. The shear strength of the composites with the untreated fibers was the lowest and it decreased with aging. A fracture surface examination of the composites with untreated fibers suggested that the weak interface allowed the oxidation reaction to proceed along the interface and thus expose the inner material to further oxidation. The results indicated that the fiber-matrix interface affected the composite degradation process during its thermal aging and that the the weak interface accelerated the composite degradation.

On evolutionary spatial heterogeneous games

NASA Astrophysics Data System (ADS)

Fort, H.

2008-03-01

How cooperation between self-interested individuals evolve is a crucial problem, both in biology and in social sciences, that is far from being well understood. Evolutionary game theory is a useful approach to this issue. The simplest model to take into account the spatial dimension in evolutionary games is in terms of cellular automata with just a one-parameter payoff matrix. Here, the effects of spatial heterogeneities of the environment and/or asymmetries in the interactions among the individuals are analysed through different extensions of this model. Instead of using the same universal payoff matrix, bimatrix games in which each cell at site ( i, j) has its own different ‘temptation to defect’ parameter T(i,j) are considered. First, the case in which these individual payoffs are constant in time is studied. Second, an evolving evolutionary spatial game such that T=T(i,j;t), i.e. besides depending on the position evolves (by natural selection), is used to explore the combination of spatial heterogeneity and natural selection of payoff matrices.

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.

MSFC Combustion Devices in 2001

NASA Technical Reports Server (NTRS)

Dexter, Carol; Turner, James (Technical Monitor)

2001-01-01

The objectives of the project detailed in this viewgraph presentation were to reduce thrust assembly weights to create lighter engines and to increase the cycle life and/or operating temperatures. Information is given on material options (metal matrix composites and polymer matrix composites), ceramic matrix composites subscale liners, lightweight linear chambers, lightweight injector development, liquid/liquid preburner tasks, and vortex chamber tasks.

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

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

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

DOE PAGES

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-06-27

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution

NASA Astrophysics Data System (ADS)

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution.

PubMed

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution. Graphical Abstract ᅟ.

Supervised orthogonal discriminant subspace projects learning for face recognition.

PubMed

Chen, Yu; Xu, Xiao-Hong

2014-02-01

In this paper, a new linear dimension reduction method called supervised orthogonal discriminant subspace projection (SODSP) is proposed, which addresses high-dimensionality of data and the small sample size problem. More specifically, given a set of data points in the ambient space, a novel weight matrix that describes the relationship between the data points is first built. And in order to model the manifold structure, the class information is incorporated into the weight matrix. Based on the novel weight matrix, the local scatter matrix as well as non-local scatter matrix is defined such that the neighborhood structure can be preserved. In order to enhance the recognition ability, we impose an orthogonal constraint into a graph-based maximum margin analysis, seeking to find a projection that maximizes the difference, rather than the ratio between the non-local scatter and the local scatter. In this way, SODSP naturally avoids the singularity problem. Further, we develop an efficient and stable algorithm for implementing SODSP, especially, on high-dimensional data set. Moreover, the theoretical analysis shows that LPP is a special instance of SODSP by imposing some constraints. Experiments on the ORL, Yale, Extended Yale face database B and FERET face database are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of SODSP. Copyright © 2013 Elsevier Ltd. All rights reserved.

A New Approach to Improving the Performance of Non-Ideal Explosives Containing Ammonium Nitrate

DTIC Science & Technology

1975-03-01

Amatol (60 ammonium nitrate and 40 TNT, by weight) and Amatex-20 (20 RDX , 40 TNT and 40 ammonium nitrate, by weight) . Experimental detonation...compositions in which TNT is the matrix holding solid AN or AN + RDX suspended. The compo- sitions used herein were made of ingredients blended in...provide two matrix levels of pressure and tempera- ture (that of TNT and that of RDX /TNT) for evaluating the improvements induced in the rate

Modifying Matrix Materials to Increase Wetting and Adhesion

NASA Technical Reports Server (NTRS)

Zhong, Katie

2011-01-01

In an alternative approach to increasing the degrees of wetting and adhesion between the fiber and matrix components of organic-fiber/polymer matrix composite materials, the matrix resins are modified. Heretofore, it has been common practice to modify the fibers rather than the matrices: The fibers are modified by chemical and/or physical surface treatments prior to combining the fibers with matrix resins - an approach that entails considerable expense and usually results in degradation (typically, weakening) of fibers. The alternative approach of modifying the matrix resins does not entail degradation of fibers, and affords opportunities for improving the mechanical properties of the fiber composites. The alternative approach is more cost-effective, not only because it eliminates expensive fiber-surface treatments but also because it does not entail changes in procedures for manufacturing conventional composite-material structures. The alternative approach is best described by citing an example of its application to a composite of ultra-high-molecular- weight polyethylene (UHMWPE) fibers in an epoxy matrix. The epoxy matrix was modified to a chemically reactive, polarized epoxy nano-matrix to increase the degrees of wetting and adhesion between the fibers and the matrix. The modification was effected by incorporating a small proportion (0.3 weight percent) of reactive graphitic nanofibers produced from functionalized nanofibers into the epoxy matrix resin prior to combining the resin with the UHMWPE fibers. The resulting increase in fiber/matrix adhesion manifested itself in several test results, notably including an increase of 25 percent in the maximum fiber pullout force and an increase of 60-65 percent in fiber pullout energy. In addition, it was conjectured that the functionalized nanofibers became involved in the cross linking reaction of the epoxy resin, with resultant enhancement of the mechanical properties and lower viscosity of the matrix.

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

PubMed

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright © 2012 Elsevier Ltd. All rights reserved.

Composite Reinforcement by Magnetic Control of Fiber Density and Orientation.

PubMed

Goldberg, Omri; Greenfeld, Israel; Wagner, H Daniel

2018-05-08

The flexural rigidity of cylindrical specimens, composed of epoxy reinforced by short, magnetized glass fibers, was enhanced using weak magnetic fields (<100 mT). By spatially controlling the magnitude and direction of the field, and thereby the torques and forces acting locally on the fibers, the orientation and concentration of the fillers in the matrix could be tuned prior to curing. Unidirectional alignment of the fibers, achieved using an air-core solenoid, improved the contribution of the fibers to the flexure modulus by a factor of 3. When a ring-shaped permanent magnet was utilized, the glass fibers were migrated preferentially near the rod boundary, and as a result, the contribution of the fibers to the flexure modulus doubled. The fiber length, density, and orientation distributions were extracted by μCT image analysis, allowing comparison of the experimental flexure modulus to a modified rule of mixtures prediction. The ability to magnetically control the fiber distribution in reinforced composites demonstrated in this study may be applied in the fabrication of complex micro- and macroscale structures with spatially variable anisotropy, allowing features such as crack diversion, strengthening of highly loaded regions, as well as economic management of materials and weight.

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.

A Electro-Optical Image Algebra Processing System for Automatic Target Recognition

NASA Astrophysics Data System (ADS)

Coffield, Patrick Cyrus

The proposed electro-optical image algebra processing system is designed specifically for image processing and other related computations. The design is a hybridization of an optical correlator and a massively paralleled, single instruction multiple data processor. The architecture of the design consists of three tightly coupled components: a spatial configuration processor (the optical analog portion), a weighting processor (digital), and an accumulation processor (digital). The systolic flow of data and image processing operations are directed by a control buffer and pipelined to each of the three processing components. The image processing operations are defined in terms of basic operations of an image algebra developed by the University of Florida. The algebra is capable of describing all common image-to-image transformations. The merit of this architectural design is how it implements the natural decomposition of algebraic functions into spatially distributed, point use operations. The effect of this particular decomposition allows convolution type operations to be computed strictly as a function of the number of elements in the template (mask, filter, etc.) instead of the number of picture elements in the image. Thus, a substantial increase in throughput is realized. The implementation of the proposed design may be accomplished in many ways. While a hybrid electro-optical implementation is of primary interest, the benefits and design issues of an all digital implementation are also discussed. The potential utility of this architectural design lies in its ability to control a large variety of the arithmetic and logic operations of the image algebra's generalized matrix product. The generalized matrix product is the most powerful fundamental operation in the algebra, thus allowing a wide range of applications. No other known device or design has made this claim of processing speed and general implementation of a heterogeneous image algebra.

Algorithm for pose estimation based on objective function with uncertainty-weighted measuring error of feature point cling to the curved surface.

PubMed

Huo, Ju; Zhang, Guiyang; Yang, Ming

2018-04-20

This paper is concerned with the anisotropic and non-identical gray distribution of feature points clinging to the curved surface, upon which a high precision and uncertainty-resistance algorithm for pose estimation is proposed. Weighted contribution of uncertainty to the objective function of feature points measuring error is analyzed. Then a novel error objective function based on the spatial collinear error is constructed by transforming the uncertainty into a covariance-weighted matrix, which is suitable for the practical applications. Further, the optimized generalized orthogonal iterative (GOI) algorithm is utilized for iterative solutions such that it avoids the poor convergence and significantly resists the uncertainty. Hence, the optimized GOI algorithm extends the field-of-view applications and improves the accuracy and robustness of the measuring results by the redundant information. Finally, simulation and practical experiments show that the maximum error of re-projection image coordinates of the target is less than 0.110 pixels. Within the space 3000  mm×3000  mm×4000  mm, the maximum estimation errors of static and dynamic measurement for rocket nozzle motion are superior to 0.065° and 0.128°, respectively. Results verify the high accuracy and uncertainty attenuation performance of the proposed approach and should therefore have potential for engineering applications.

Reliability-Weighted Integration of Audiovisual Signals Can Be Modulated by Top-down Attention

PubMed Central

Noppeney, Uta

2018-01-01

Abstract Behaviorally, it is well established that human observers integrate signals near-optimally weighted in proportion to their reliabilities as predicted by maximum likelihood estimation. Yet, despite abundant behavioral evidence, it is unclear how the human brain accomplishes this feat. In a spatial ventriloquist paradigm, participants were presented with auditory, visual, and audiovisual signals and reported the location of the auditory or the visual signal. Combining psychophysics, multivariate functional MRI (fMRI) decoding, and models of maximum likelihood estimation (MLE), we characterized the computational operations underlying audiovisual integration at distinct cortical levels. We estimated observers’ behavioral weights by fitting psychometric functions to participants’ localization responses. Likewise, we estimated the neural weights by fitting neurometric functions to spatial locations decoded from regional fMRI activation patterns. Our results demonstrate that low-level auditory and visual areas encode predominantly the spatial location of the signal component of a region’s preferred auditory (or visual) modality. By contrast, intraparietal sulcus forms spatial representations by integrating auditory and visual signals weighted by their reliabilities. Critically, the neural and behavioral weights and the variance of the spatial representations depended not only on the sensory reliabilities as predicted by the MLE model but also on participants’ modality-specific attention and report (i.e., visual vs. auditory). These results suggest that audiovisual integration is not exclusively determined by bottom-up sensory reliabilities. Instead, modality-specific attention and report can flexibly modulate how intraparietal sulcus integrates sensory signals into spatial representations to guide behavioral responses (e.g., localization and orienting). PMID:29527567

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia

PubMed Central

McBratney, Alex B.; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson’s correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (−0.34), mid-slope position (−0.29), multi-resolution valley bottom flatness index (−0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged. PMID:29682425

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia.

PubMed

Malone, Brendan P; McBratney, Alex B; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson's correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (-0.34), mid-slope position (-0.29), multi-resolution valley bottom flatness index (-0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged.

A scoping review of spatial cluster analysis techniques for point-event data.

PubMed

Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott

2013-05-01

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

NASA Astrophysics Data System (ADS)

Cai, Jingya; Pang, Zhiguo; Fu, Jun'e.

2018-04-01

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

Resource availability, matrix quality, microclimate, and spatial pattern as predictors of patch use by the Karner blue butterfly

USGS Publications Warehouse

Grundel, R.; Pavlovic, N.B.

2007-01-01

Determination of which aspects of habitat quality and habitat spatial arrangement best account for variation in a species’ distribution can guide management for organisms such as the Karner blue butterfly (Lycaeides melissa samuelis), a federally endangered subspecies inhabiting savannas of Midwest and Eastern United States. We examined the extent to which three sets of predictors, (1) larval host plant (Lupinus perennis, wild lupine) availability, (2) characteristics of the matrix surrounding host plant patches, and (3) factors affecting a patch’s thermal environment, accounted for variation in lupine patch use by Karner blues at Indiana Dunes National Lakeshore, Indiana and Fort McCoy, Wisconsin, USA. Each predictor set accounted for 7–13% of variation in patch occupancy by Karner blues at both sites and in larval feeding activity among patches at Indiana Dunes. Patch area, an indicator of host plant availability, was an exception, accounting for 30% of variation in patch occupancy at Indiana Dunes. Spatially structured patterns of patch use across the landscape accounted for 9–16% of variation in patch use and explained more variation in larval feeding activity than did spatial autocorrelation between neighboring patches. Because of this broader spatial trend across sites, a given management action may be more effective in promoting patch use in some portions of the landscape than in others. Spatial trend, resource availability, matrix quality, and microclimate, in general, accounted for similar amounts of variation in patch use and each should be incorporated into habitat management planning for the Karner blue butterfly.

Analysis of Modified SMI Method for Adaptive Array Weight Control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Dilsavor, Ronald Louis

1989-01-01

An adaptive array is used to receive a desired signal in the presence of weak interference signals which need to be suppressed. A modified sample matrix inversion (SMI) algorithm controls the array weights. The modification leads to increased interference suppression by subtracting a fraction of the noise power from the diagonal elements of the covariance matrix. The modified algorithm maximizes an intuitive power ratio criterion. The expected values and variances of the array weights, output powers, and power ratios as functions of the fraction and the number of snapshots are found and compared to computer simulation and real experimental array performance. Reduced-rank covariance approximations and errors in the estimated covariance are also described.

Explicit formula for the Holevo bound for two-parameter qubit-state estimation problem

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

Suzuki, Jun, E-mail: junsuzuki@uec.ac.jp

The main contribution of this paper is to derive an explicit expression for the fundamental precision bound, the Holevo bound, for estimating any two-parameter family of qubit mixed-states in terms of quantum versions of Fisher information. The obtained formula depends solely on the symmetric logarithmic derivative (SLD), the right logarithmic derivative (RLD) Fisher information, and a given weight matrix. This result immediately provides necessary and sufficient conditions for the following two important classes of quantum statistical models; the Holevo bound coincides with the SLD Cramér-Rao bound and it does with the RLD Cramér-Rao bound. One of the important results ofmore » this paper is that a general model other than these two special cases exhibits an unexpected property: the structure of the Holevo bound changes smoothly when the weight matrix varies. In particular, it always coincides with the RLD Cramér-Rao bound for a certain choice of the weight matrix. Several examples illustrate these findings.« less

b matrix errors in echo planar diffusion tensor imaging

PubMed Central

Boujraf, Saïd; Luypaert, Robert; Osteaux, Michel

2001-01-01

Diffusion‐weighted magnetic resonance imaging (DW‐MRI) is a recognized tool for early detection of infarction of the human brain. DW‐MRI uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive parameters that reflect the translational mobility of the water molecules in tissues. If diffusion‐weighted images with different values of b matrix are acquired during one individual investigation, it is possible to calculate apparent diffusion coefficient maps that are the elements of the diffusion tensor. The diffusion tensor elements represent the apparent diffusion coefficient of protons of water molecules in each pixel in the corresponding sample. The relation between signal intensity in the diffusion‐weighted images, diffusion tensor, and b matrix is derived from the Bloch equations. Our goal is to establish the magnitude of the error made in the calculation of the elements of the diffusion tensor when the imaging gradients are ignored. PACS number(s): 87.57. –s, 87.61.–c PMID:11602015

N-(1-Naphthyl) Ethylenediamine Dinitrate: A New Matrix for Negative Ion MALDI-TOF MS Analysis of Small Molecules

NASA Astrophysics Data System (ADS)

Chen, Rui; Chen, Suming; Xiong, Caiqiao; Ding, Xunlei; Wu, Chih-Che; Chang, Huan-Cheng; Xiong, Shaoxiang; Nie, Zongxiu

2012-09-01

An organic salt, N-(1-naphthyl) ethylenediamine dinitrate (NEDN), with rationally designed properties of a strong UV absorbing chromophore, hydrogen binding and nitrate anion donors, has been employed as a matrix to analyze small molecules ( m/z < 1000) such as oligosaccharides, peptides, metabolites and explosives using negative ion matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Compared with conventional matrixes such as α-cyano-4-hydroxycinnamic acid (CCA) and 2,5-dihydroxybenzoic acid (DHB), NEDN provides a significant improvement in detection sensitivity and yields very few matrix-associated fragment and cluster ions interfering with MS analysis. For low-molecular-weight saccharides, the lowest detection limit achieved ranges from 500 amol to 5 pmol, depending on the molecular weight and the structure of the analytes. Additionally, the mass spectra in the lower mass range ( m/z < 200) consist of only nitrate and nitric acid cluster ions, making the matrix particularly useful for structural identification of oligosaccharides by post-source decay (PSD) MALDI-MS. Such a characteristic is illustrated by using maltoheptaose as a model system. This work demonstrates that NEDN is a novel negative ion-mode matrix for MALDI-MS analysis of small molecules with nitrate anion attachment.

Hierarchical spatial segregation of two Mediterranean vole species: the role of patch-network structure and matrix composition.

PubMed

Pita, Ricardo; Lambin, Xavier; Mira, António; Beja, Pedro

2016-09-01

According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e., many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from within-patches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.

Direct Visualization of Neurotransmitters in Rat Brain Slices by Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI - MS)

NASA Astrophysics Data System (ADS)

Fernandes, Anna Maria A. P.; Vendramini, Pedro H.; Galaverna, Renan; Schwab, Nicolas V.; Alberici, Luciane C.; Augusti, Rodinei; Castilho, Roger F.; Eberlin, Marcos N.

2016-12-01

Mass spectrometry imaging (MSI) of neurotransmitters has so far been mainly performed by matrix-assisted laser desorption/ionization (MALDI) where derivatization reagents, deuterated matrix and/or high resolution, or tandem MS have been applied to circumvent problems with interfering ion peaks from matrix and from isobaric species. We herein describe the application of desorption electrospray ionization mass spectrometry imaging (DESI)-MSI in rat brain coronal and sagittal slices for direct spatial monitoring of neurotransmitters and choline with no need of derivatization reagents and/or deuterated materials. The amino acids γ-aminobutyric (GABA), glutamate, aspartate, serine, as well as acetylcholine, dopamine, and choline were successfully imaged using a commercial DESI source coupled to a hybrid quadrupole-Orbitrap mass spectrometer. The spatial distribution of the analyzed compounds in different brain regions was determined. We conclude that the ambient matrix-free DESI-MSI is suitable for neurotransmitter imaging and could be applied in studies that involve evaluation of imbalances in neurotransmitters levels.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization

PubMed Central

Bonjean, Maxime; Baker, Tanya; Bazhenov, Maxim; Cash, Sydney; Halgren, Eric; Sejnowski, Terrence

2012-01-01

Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas. PMID:22496571

Escherichia coli Biofilms Have an Organized and Complex Extracellular Matrix Structure

PubMed Central

Hung, Chia; Zhou, Yizhou; Pinkner, Jerome S.; Dodson, Karen W.; Crowley, Jan R.; Heuser, John; Chapman, Matthew R.; Hadjifrangiskou, Maria; Henderson, Jeffrey P.; Hultgren, Scott J.

2013-01-01

ABSTRACT Bacterial biofilms are ubiquitous in nature, and their resilience is derived in part from a complex extracellular matrix that can be tailored to meet environmental demands. Although common developmental stages leading to biofilm formation have been described, how the extracellular components are organized to allow three-dimensional biofilm development is not well understood. Here we show that uropathogenic Escherichia coli (UPEC) strains produce a biofilm with a highly ordered and complex extracellular matrix (ECM). We used electron microscopy (EM) techniques to image floating biofilms (pellicles) formed by UPEC. EM revealed intricately constructed substructures within the ECM that encase individual, spatially segregated bacteria with a distinctive morphology. Mutational and biochemical analyses of these biofilms confirmed curli as a major matrix component and revealed important roles for cellulose, flagella, and type 1 pili in pellicle integrity and ECM infrastructure. Collectively, the findings of this study elucidated that UPEC pellicles have a highly organized ultrastructure that varies spatially across the multicellular community. PMID:24023384

Preparation of SiC based Aluminium metal matrix nano composites by high intensity ultrasonic cavitation process and evaluation of mechanical and tribological properties

NASA Astrophysics Data System (ADS)

Murthy, N. V.; Prasad Reddy, A.; Selvaraj, N.; Rao, C. S. P.

2016-09-01

Request augments on a worldwide scale for the new materials. The metal matrix nano composites can be used in numerous applications of helicopter structural parts, gas turbine exit guide vane's, space shuttle, and other structural applications. The key mailman to ameliorate performance of composite matrix in aluminium alloy metal reinforces nano particles in the matrix of alloy uniformly, which ameliorates composite properties without affecting limit of ductility. The ultrasonic assisted stir casting helped agitation was successfully used to fabricate Al 2219 metal matrix of alloy reinforced with (0.5, 1, 1.5 and 2) wt.% of nano silicon carbide (SiC) particles of different sizes 50nm and 150nm. The micrographs of scanning electron microscopy of nano composite were investigated it reveals that the uniform dispersion of nano particles silicon carbide in aluminium alloy 2219 matrix and with the low porosity. How the specific wear rate was vary with increasing weight percentage of nano particles at constant load and speed as shown in results and discussions. And the mechanical properties showed that the ultimate tensile strength and hardness of metal matrix nano composite AA 2219 / nano SiC of 50nm and 150nm lean to augment with increase weight percentage of silicon carbide content in the matrix alloy.

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

Spatially varying dispersion to model breakthrough curves.

PubMed

Li, Guangquan

2011-01-01

Often the water flowing in a karst conduit is a combination of contaminated water entering at a sinkhole and cleaner water released from the limestone matrix. Transport processes in the conduit are controlled by advection, mixing (dilution and dispersion), and retention-release. In this article, a karst transport model considering advection, spatially varying dispersion, and dilution (from matrix seepage) is developed. Two approximate Green's functions are obtained using transformation of variables, respectively, for the initial-value problem and for the boundary-value problem. A numerical example illustrates that mixing associated with strong spatially varying conduit dispersion can cause strong skewness and long tailing in spring breakthrough curves. Comparison of the predicted breakthrough curve against that measured from a dye-tracing experiment between Ames Sink and Indian Spring, Northwest Florida, shows that the conduit dispersivity can be as large as 400 m. Such a large number is believed to imply strong solute interaction between the conduit and the matrix and/or multiple flow paths in a conduit network. It is concluded that Taylor dispersion is not dominant in transport in a karst conduit, and the complicated retention-release process between mobile- and immobile waters may be described by strong spatially varying conduit dispersion. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

Sources and mass inventory of sedimentary polycyclic aromatic hydrocarbons in the Gulf of Thailand: Implications for pathways and energy structure in SE Asia.

PubMed

Hu, Limin; Shi, Xuefa; Qiao, Shuqing; Lin, Tian; Li, Yuanyuan; Bai, Yazhi; Wu, Bin; Liu, Shengfa; Kornkanitnan, Narumol; Khokiattiwong, Somkiat

2017-01-01

Surface sediments obtained from a matrix of 92 sample sites in the Gulf of Thailand (GOT) were analyzed for a comprehensive study of the distribution, sources, and mass inventory of polycyclic aromatic hydrocarbons (PAHs) to assess their input pathways and impacts of the regional land-based energy structure on the deposition of PAHs on the adjacent continental margins. The concentration of 16 PAHs in the GOT ranged from 2.6 to 78.1ng/g (dry weight), and the mean concentration was 19.4±15.1ng/g. The spatial distribution pattern of 16 PAH was generally consistent with that of sediment grain size, suggesting the influence of regional hydrodynamic conditions. Correlation and principal component analysis of the PAHs indicated that direct land-based inputs were dominantly responsible for the occurrence of PAHs in the upper GOT and the low molecular weight (LMW) PAHs in the coastal region could be from petrogenic sources. A positive matrix factorization (PMF) model apportioned five contributors: petroleum residues (~44%), biomass burning (~13%), vehicular emissions (~11%), coal combustion (~6%), and air-water exchange (~25%). Gas absorption may be a significant external input pathway for the volatile PAHs in the open GOT, which further implies that atmospheric loading could be important for the sink of PAHs in the open sea of the Southeast Asia (SE Asia). The different PAH source patterns obtained and a significant disparity of PAH mass inventory in the sediments along the East and Southeast Asia continental margins can be ascribed mainly to different land-based PAH emission features under the varied regional energy structure in addition to the depositional environment and climatic conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Cyclodextrin-supported organic matrix for application of MALDI-MS for forensics. Soft-ionization to obtain protonated molecules of low molecular weight compounds

NASA Astrophysics Data System (ADS)

Yonezawa, Tetsu; Asano, Takashi; Fujino, Tatsuya; Nishihara, Hiroshi

2013-06-01

A mass measurement technique for detecting low-molecular-weight drugs with a cyclodextrin-supported organic matrix was investigated. By using cyclodextrin-supported 2,4,6-trihydroxyacetophenone (THAP), the matrix-related peaks of drugs were suppressed. The peaks of protonated molecules of the sample and THAP were mainly observed, and small fragments were detected in a few cases. Despite the Na+ and K+ peaks were observed in the spectrum, Na+ or K+ adduct sample molecules were undetected, owing to the sugar units of cyclodextrin. The advantages of MALDI-MS with cyclodextrin-supported matrices as an analytical tool for forensic samples are discussed. The suppression of alkali adducted molecules and desorption process are also discussed.

The development and mechanical characterization of aluminium copper-carbon fiber metal matrix hybrid composite

NASA Astrophysics Data System (ADS)

Manzoor, M. U.; Feroze, M.; Ahmad, T.; Kamran, M.; Butt, M. T. Z.

2018-04-01

Metal matrix composites (MMCs) come under advanced materials that can be used for a wide range of industrial applications. MMCs contain a non-metallic reinforcement incorporated into a metallic matrix which can enhance properties over base metal alloys. Copper-Carbon fiber reinforced aluminium based hybrid composites were prepared by compo casting method. 4 weight % copper was used as alloying element with Al because of its precipitation hardened properties. Different weight compositions of composites were developed and characterized by mechanical testing. A significant improvement in tensile strength and micro hardness were found, before and after heat treatment of the composite. The SEM analysis of the fractured surfaces showed dispersed and embedded Carbon fibers within the network leading to the enhanced strength.

Graph Theoretic Foundations of Multibody Dynamics Part I: Structural Properties

PubMed Central

Jain, Abhinandan

2011-01-01

This is the first part of two papers that use concepts from graph theory to obtain a deeper understanding of the mathematical foundations of multibody dynamics. The key contribution is the development of a unifying framework that shows that key analytical results and computational algorithms in multibody dynamics are a direct consequence of structural properties and require minimal assumptions about the specific nature of the underlying multibody system. This first part focuses on identifying the abstract graph theoretic structural properties of spatial operator techniques in multibody dynamics. The second part paper exploits these structural properties to develop a broad spectrum of analytical results and computational algorithms. Towards this, we begin with the notion of graph adjacency matrices and generalize it to define block-weighted adjacency (BWA) matrices and their 1-resolvents. Previously developed spatial operators are shown to be special cases of such BWA matrices and their 1-resolvents. These properties are shown to hold broadly for serial and tree topology multibody systems. Specializations of the BWA and 1-resolvent matrices are referred to as spatial kernel operators (SKO) and spatial propagation operators (SPO). These operators and their special properties provide the foundation for the analytical and algorithmic techniques developed in the companion paper. We also use the graph theory concepts to study the topology induced sparsity structure of these operators and the system mass matrix. Similarity transformations of these operators are also studied. While the detailed development is done for the case of rigid-link multibody systems, the extension of these techniques to a broader class of systems (e.g. deformable links) are illustrated. PMID:22102790

Effect of Forging Parameters on Low Cycle Fatigue Behaviour of Al/Basalt Short Fiber Metal Matrix Composites

PubMed Central

Karthigeyan, R.; Ranganath, G.

2013-01-01

This paper deals with metal matrix composites (MMCs) of Al 7075 alloy containing different weight percentage (2.5, 5, 7.5, and 10) basalt short fiber reinforcement and unreinforced matrix alloy. The samples were produced by the permanent stir casting technique. The casting ingots were cut into blanks to be forged in single stage and double stage, using MN press and graphite-based lubricant. The microstructures and fatigue properties of the matrix alloy and MMC samples were investigated in the as cast state and in the single and double stage forging operations. The microstructure results showed that the forged sample had a uniform distribution of the basalt short fiber throughout the specimens. Evaluation of the fatigue properties showed that the forged samples had higher values than those of the as cast counterparts. After forging, the enhancement of the fatigue strength of the matrix alloy was so significant and high in the case of 2.5 and 5.0 wt. percentage basalt short fiber reinforced MMC, and there was no enhancement in 7.5 and 10 weight percentages short fiber reinforced MMCs. The fracture damage was mainly due to decohesion at the matrix-fiber interface. PMID:24298207

Effect of forging parameters on low cycle fatigue behaviour of Al/basalt short fiber metal matrix composites.

PubMed

Karthigeyan, R; Ranganath, G

2013-01-01

This paper deals with metal matrix composites (MMCs) of Al 7075 alloy containing different weight percentage (2.5, 5, 7.5, and 10) basalt short fiber reinforcement and unreinforced matrix alloy. The samples were produced by the permanent stir casting technique. The casting ingots were cut into blanks to be forged in single stage and double stage, using MN press and graphite-based lubricant. The microstructures and fatigue properties of the matrix alloy and MMC samples were investigated in the as cast state and in the single and double stage forging operations. The microstructure results showed that the forged sample had a uniform distribution of the basalt short fiber throughout the specimens. Evaluation of the fatigue properties showed that the forged samples had higher values than those of the as cast counterparts. After forging, the enhancement of the fatigue strength of the matrix alloy was so significant and high in the case of 2.5 and 5.0 wt. percentage basalt short fiber reinforced MMC, and there was no enhancement in 7.5 and 10 weight percentages short fiber reinforced MMCs. The fracture damage was mainly due to decohesion at the matrix-fiber interface.

Determination of Interlaminar Toughness of IM7/977-2 Composites at Temperature Extremes and Different Thicknesses

NASA Technical Reports Server (NTRS)

Johnson, W. S.; Pavlick, M. M.; Oliver, M. S.

2005-01-01

Composite materials are being used in the aerospace industry as a means of reducing vehicle weight. In particular, polymer matrix composites (PMC) are good candidates due to their high strength-to-weight and high stiffness-to-weight ratios. Future reusable space launch vehicles and space exploration structures will need advanced light weight composites in order to minimize vehicle weight while demonstrating robustness and durability, guaranteeing high factors of safety. In particular, the implementation of composite cryogenic propellant fuel tanks (cryotanks) for future reusable launch vehicles (RLVs) could greatly reduce the vehicle's weight versus identically sized cryotanks constructed of metallic materials. One candidate composite material for future cryotank designs is IM7/977-2, which is a graphite/epoxy system. A successful candidate must demonstrate reasonable structural properties over a wide range of temperatures. Since the matrix material is normally the weak link in the composite, tests that emphasize matrix-dominated behavior need to be conducted. Therefore, the objective of this work is to determine the mode I interlaminar fracture toughness of "unidirectional" 8-ply and 16-ply IM7/977-2 through experimental testing. Tests were performed at -196 degrees Celsius (-320 degrees Fahrenheit), 22 degrees Celsius (72 degrees Fahrenheit), 93 degrees Celsius (200 degrees Fahrenheit) and 160 degrees C (320 degrees Fahrenheit). Low temperature testing was completed while the specimen was submerged in a liquid nitrogen bath. High temperature testing was completed in a temperature-controlled oven.

On the time-weighted quadratic sum of linear discrete systems

NASA Technical Reports Server (NTRS)

Jury, E. I.; Gutman, S.

1975-01-01

A method is proposed for obtaining the time-weighted quadratic sum for linear discrete systems. The formula of the weighted quadratic sum is obtained from matrix z-transform formulation. In addition, it is shown that this quadratic sum can be derived in a recursive form for several useful weighted functions. The discussion presented parallels that of MacFarlane (1963) for weighted quadratic integral for linear continuous systems.

A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

Infrared maritime target detection using a probabilistic single Gaussian model of sea clutter in Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei

2018-02-01

For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.

Uncovering the spatial structure of mobility networks

NASA Astrophysics Data System (ADS)

Louail, Thomas; Lenormand, Maxime; Picornell, Miguel; García Cantú, Oliva; Herranz, Ricardo; Frias-Martinez, Enrique; Ramasco, José J.; Barthelemy, Marc

2015-01-01

The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has relevance for many applications. An important example is seen in origin-destination matrices, which contain the complete information on commuting flows, but are difficult to analyze and compare. We propose here a versatile method, which extracts a coarse-grained signature of mobility networks, under the form of a 2 × 2 matrix that separates the flows into four categories. We apply this method to origin-destination matrices extracted from mobile phone data recorded in 31 Spanish cities. We show that these cities essentially differ by their proportion of two types of flows: integrated (between residential and employment hotspots) and random flows, whose importance increases with city size. Finally, the method allows the determination of categories of networks, and in the mobility case, the classification of cities according to their commuting structure.

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.

Stochastic theory of photon flow in homogeneous and heterogeneous anisotropic biological and artificial material

NASA Astrophysics Data System (ADS)

Miller, Steven D.

1995-05-01

Standard Monte Carlo methods used in photon diffusion score absorbed photons or statistical weight deposited within voxels comprising a mesh. An alternative approach to a stochastic description is considered for rapid surface flux calculations and finite medias. Matrix elements are assigned to a spatial lattice whose function is to score vector intersections of scattered photons making transitions into either the forward or back solid angle half spaces. These complete matrix elements can be related to the directional fluxes within the lattice space. This model differentiates between ballistic, quasi-ballistic, and highly diffuse photon contributions, and effectively models the subsurface generation of a scattered light flux from a ballistic source. The connection between a path integral and diffusion is illustrated. Flux perturbations can be effectively illustrated for tissue-tumor-tissue and for 3 layer systems with strong absorption in one or more layers. For conditions where the diffusion theory has difficulties such as strong absorption, highly collimated sources, small finite volumes, and subsurface regions, the computation time of the algorithm is rapid with good accuracy and compliments other description of photon diffusion. The model has the potential to do computations relevant to photodynamic therapy (PDT) and analysis of laser beam interaction with tissues.

Photomatrix LED therapy of extensive cutaneous pathology

NASA Astrophysics Data System (ADS)

Zharov, Vladimir P.; Menyaev, Yulian A.; Zharova, I. Z.; Leviev, Dmitry O.; Tsarev, V. N.; Sarantsev, V. P.; Krusic, Joze

2000-05-01

Standard sources of radiation have not sufficient efficiency at treating spatially extended pathology, especially when pathologic areas involve opposite sides of the human being's body or when they are uneven in shape. The typical examples of such pathology are extensive burns, oedema, inflammatory processes, infectious wounds, actinic keratosis, psoriasis, arthritis and neurological diseases. Superbright LEDs gathered in a matrix and grasping the area of irradiation are the most suitable sources of radiation. This article presents the result of investigation of the effectiveness of various types of the blue-to-infrared spectrum range LED array that allow irradiating a surface with an area from several cm2 to several thousand cm2 including the whole human being's body with the intensity varying from 1 to 100 mW/cm2. Besides the matrixes, composed of separate light diodes, modular systems with separate monolithic hybrid chips with a high density of positioning the sources of radiation are considered. The peculiarities and results of applying such systems to treat oedema, cancer, weight regulation, neurological diseases, different infections diseases in combination with PDT, stomatitis and paradontosis are analyzed. The parameters of the photomatrix LED for different spectral regions and different geometry from flat shape to semispherical and cylindrical are presented. The perspective combination photomatrix LED with another therapeutical devices including photovacuum and photomagnetic therapy are considered.

Polarization characterization of an LCTV with a Mueller matrix imaging polarimeter

NASA Astrophysics Data System (ADS)

Pezzaniti, J. Larry; Chipman, Russell A.; Gregory, Don A.

1993-10-01

The polarization properties of a TVT-6000 LCTV have been investigated. Mueller matrices of multiple ray paths through the TVT-6000 were measured for a single (typical) pixel, and through several pixels, using an imaging polarimeter. The TVT-6000 was characterized as a function of applied voltage and angle of incidence. From the Mueller matrices, the spatially dependent retardance, diattenuation, and depolarization are calculated and displayed as topographic maps. In another set of measurements, the LCTV is illuminated with a plane wave, and the spatial distribution of polarization in the Far Field Diffraction Pattern is measured in Mueller matrix form.

Direct-laser metal writing of surface acoustic wave transducers for integrated-optic spatial light modulators in lithium niobate

NASA Astrophysics Data System (ADS)

Datta, Bianca C.; Savidis, Nickolaos; Moebius, Michael; Jolly, Sundeep; Mazur, Eric; Bove, V. Michael

2017-02-01

Recently, the fabrication of high-resolution silver nanostructures using a femtosecond laser-based direct write process in a gelatin matrix was reported. The application of direct metal writing towards feature development has also been explored with direct metal fusion, in which metal is fused onto the surface of the substrate via a femtosecond laser process. In this paper, we present a comparative study of gelatin matrix and metal fusion approaches for directly laser-written fabrication of surface acoustic wave transducers on a lithium niobate substrate for application in integrated optic spatial light modulators.

Detection of LSB+/-1 steganography based on co-occurrence matrix and bit plane clipping

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Aghaeinia, Hassan; Faez, Karim; Mehrabi, Mohammad Ali

2010-01-01

Spatial LSB+/-1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB+/-1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB+/-1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB+/-1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB+/-1 steganographic method for grayscale images.

Analytical Micromechanics Modeling Technique Developed for Ceramic Matrix Composites Analysis

NASA Technical Reports Server (NTRS)

Min, James B.

2005-01-01

Ceramic matrix composites (CMCs) promise many advantages for next-generation aerospace propulsion systems. Specifically, carbon-reinforced silicon carbide (C/SiC) CMCs enable higher operational temperatures and provide potential component weight savings by virtue of their high specific strength. These attributes may provide systemwide benefits. Higher operating temperatures lessen or eliminate the need for cooling, thereby reducing both fuel consumption and the complex hardware and plumbing required for heat management. This, in turn, lowers system weight, size, and complexity, while improving efficiency, reliability, and service life, resulting in overall lower operating costs.

The Mastery Matrix for Integration Praxis: The development of a rubric for integration practice in addressing weight-related public health problems.

PubMed

Berge, Jerica M; Adamek, Margaret; Caspi, Caitlin; Grannon, Katherine Y; Loth, Katie A; Trofholz, Amanda; Nanney, Marilyn S

2018-06-01

In response to the limitations of siloed weight-related intervention approaches, scholars have called for greater integration that is intentional, strategic, and thoughtful between researchers, health care clinicians, community members, and policy makers as a way to more effectively address weight and weight-related (e.g., obesity, diabetes, cardiovascular disease, cancer) public health problems. The Mastery Matrix for Integration Praxis was developed by the Healthy Eating and Activity across the Lifespan (HEAL) team in 2017 to advance the science and praxis of integration across the domains of research, clinical practice, community, and policy to address weight-related public health problems. Integrator functions were identified and developmental stages were created to generate a rubric for measuring mastery of integration. Creating a means to systematically define and evaluate integration praxis and expertise will allow for more individuals and teams to master integration in order to work towards promoting a culture of health. Copyright © 2018 Elsevier Inc. All rights reserved.

Development of formula varsity race car chassis

NASA Astrophysics Data System (ADS)

Abdullah, M. A.; Mansur, M. R.; Tamaldin, N.; Thanaraj, K.

2013-12-01

Three chassis designs have been developed using commercial computer aided design (CAD) software. The design is based on the specifications of UTeM Formula VarsityTM 2012 (FV2012). The selection of the design is derived from weighted matrix which consists of reliability, cost, time consumption and weight. The score of the matrix is formulated based on relative weighted factor among the selections. All three designs are then fabricated using selected materials available. The actual cost, time consumption and weight of the chassis's are compared with the theoretical weighted scores. Standard processes of cuttings, fittings and welding are performed in chassis mock up and fabrication. The chassis is later assembled together with suspension systems, steering linkages, brake systems, engine system, and drive shaft systems. Once the chassis is assembled, the studies of driver's ergonomic and part accessibility are performed. The completion in final fittings and assembly of the race car and its reliability demonstrate an outstanding design for manufacturing (DFM) practices of the chassis.

A Limited Comparison of the Thermal Durability of Polyimide Candidate Matrix Polymers with PMR-15

NASA Technical Reports Server (NTRS)

Bowles, Kenneth J.; Papadopoulos, Demetrios S.; Scheiman, Daniel A.; Inghram, Linda L.; McCorkle, Linda S.; Klans, Ojars V.

2003-01-01

Studies were conducted with six different candidate high-temperature neat matrix resin specimens of varied geometric shapes to investigate the mechanisms involved in the thermal degradation of polyimides like PMR-15. The metrics for assessing the quality of these candidates were chosen to be glass transition temperature (T(sub g)), thermo-oxidative stability, dynamic mechanical properties, microstructural changes, and dimensional stability. The processing and mechanical properties were not investigated in the study reported herein. The dimensional changes and surface layer growth were measured and recorded. The data were in agreement with earlier published data. An initial weight increase reaction was observed to be dominating at the lower temperatures. However, at the more elevated temperatures, the weight loss reactions were prevalent and probably masked the weight gain reaction. These data confirmed the findings of the existence of an initial weight gain reaction previously reported. Surface- and core-dependent weight losses were shown to control the polymer degradation at the higher temperatures.

AMES Stereo Pipeline Derived DEM Accuracy Experiment Using LROC-NAC Stereopairs and Weighted Spatial Dependence Simulation for Lunar Site Selection

NASA Astrophysics Data System (ADS)

Laura, J. R.; Miller, D.; Paul, M. V.

2012-03-01

An accuracy assessment of AMES Stereo Pipeline derived DEMs for lunar site selection using weighted spatial dependence simulation and a call for outside AMES derived DEMs to facilitate a statistical precision analysis.

The BMS4 algebra at spatial infinity

NASA Astrophysics Data System (ADS)

Troessaert, Cédric

2018-04-01

We show how a global BMS4 algebra appears as part of the asymptotic symmetry algebra at spatial infinity. Using linearised theory, we then show that this global BMS4 algebra is the one introduced by Strominger as a symmetry of the S-matrix.

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.

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

Inkjet-printed gold nanoparticle surfaces for the detection of low molecular weight biomolecules by laser desorption/ionization mass spectrometry.

PubMed

Marsico, Alyssa L M; Creran, Brian; Duncan, Bradley; Elci, S Gokhan; Jiang, Ying; Onasch, Timothy B; Wormhoudt, Joda; Rotello, Vincent M; Vachet, Richard W

2015-11-01

Effective detection of low molecular weight compounds in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is often hindered by matrix interferences in the low m/z region of the mass spectrum. Here, we show that monolayer-protected gold nanoparticles (AuNPs) can serve as alternate matrices for the very sensitive detection of low molecular weight compounds such as amino acids. Amino acids can be detected at low fmol levels with minimal interferences by properly choosing the AuNP deposition method, density, size, and monolayer surface chemistry. By inkjet-printing AuNPs at various densities, we find that AuNP clusters are essential for obtaining the greatest sensitivity. Graphical Abstract ᅟ.

SMI adaptive antenna arrays for weak interfering signals

NASA Technical Reports Server (NTRS)

Gupta, I. J.

1987-01-01

The performance of adaptive antenna arrays is studied when a sample matrix inversion (SMI) algorithm is used to control array weights. It is shown that conventional SMI adaptive antennas, like other adaptive antennas, are unable to suppress weak interfering signals (below thermal noise) encountered in broadcasting satellite communication systems. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is modified such that the effect of thermal noise on the weights of the adaptive array is reduced. Thus, the weights are dictated by relatively weak coherent signals. It is shown that the modified algorithm provides the desired interference protection. The use of defocused feeds as auxiliary elements of an SMI adaptive array is also discussed.

Efficient and precise calculation of the b-matrix elements in diffusion-weighted imaging pulse sequences.

PubMed

Zubkov, Mikhail; Stait-Gardner, Timothy; Price, William S

2014-06-01

Precise NMR diffusion measurements require detailed knowledge of the cumulative dephasing effect caused by the numerous gradient pulses present in most NMR pulse sequences. This effect, which ultimately manifests itself as the diffusion-related NMR signal attenuation, is usually described by the b-value or the b-matrix in the case of multidirectional diffusion weighting, the latter being common in diffusion-weighted NMR imaging. Neglecting some of the gradient pulses introduces an error in the calculated diffusion coefficient reaching in some cases 100% of the expected value. Therefore, ensuring the b-matrix calculation includes all the known gradient pulses leads to significant error reduction. Calculation of the b-matrix for simple gradient waveforms is rather straightforward, yet it grows cumbersome when complexly shaped and/or numerous gradient pulses are introduced. Making three broad assumptions about the gradient pulse arrangement in a sequence results in an efficient framework for calculation of b-matrices as well providing some insight into optimal gradient pulse placement. The framework allows accounting for the diffusion-sensitising effect of complexly shaped gradient waveforms with modest computational time and power. This is achieved by using the b-matrix elements of the simple unmodified pulse sequence and minimising the integration of the complexly shaped gradient waveform in the modified sequence. Such re-evaluation of the b-matrix elements retains all the analytical relevance of the straightforward approach, yet at least halves the amount of symbolic integration required. The application of the framework is demonstrated with the evaluation of the expression describing the diffusion-sensitizing effect, caused by different bipolar gradient pulse modules. Copyright © 2014 Elsevier Inc. All rights reserved.

Relationships between species feeding traits and environmental conditions in fish communities: a three-matrix approach.

PubMed

Brind'Amour, Anik; Boisclair, Daniel; Dray, Stéphane; Legendre, Pierre

2011-03-01

Understanding the relationships between species biological traits and the environment is crucial to predicting the effect of habitat perturbations on fish communities. It is also an essential step in the assessment of the functional diversity. Using two complementary three-matrix approaches (fourth-corner and RLQ analyses), we tested the hypothesis that feeding-oriented traits determine the spatial distributions of littoral fish species by assessing the relationship between fish spatial distributions, fish species traits, and habitat characteristics in two Laurentian Shield lakes. Significant associations between the feeding-oriented traits and the environmental characteristics suggested that fish communities in small lakes (displaying low species richness) can be spatially structured. Three groups of traits, mainly categorized by the species spatial and temporal feeding activity, were identified. The water column may be divided in two sections, each of them corresponding to a group of traits related to the vertical distribution of the prey coupled with the position of the mouth. Lake areas of low structural complexity were inhabited by functional assemblages dominated by surface feeders while structurally more complex areas were occupied by mid-water and benthic feeders. A third group referring to the time of feeding activity was observed. Our work could serve as a guideline study to evaluate species traits x environment associations at multiple spatial scales. Our results indicate that three-matrix statistical approaches are powerful tools that can be used to study such relationships. These recent statistical approaches open up new research directions such as the study of spatially based biological functions in lakes. They also provide new analytical tools for determining, for example, the potential size of freshwater protected areas.

A novel three-stage distance-based consensus ranking method

NASA Astrophysics Data System (ADS)

Aghayi, Nazila; Tavana, Madjid

2018-05-01

In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

Optimal weighting in fNL constraints from large scale structure in an idealised case

NASA Astrophysics Data System (ADS)

Slosar, Anže

2009-03-01

We consider the problem of optimal weighting of tracers of structure for the purpose of constraining the non-Gaussianity parameter fNL. We work within the Fisher matrix formalism expanded around fiducial model with fNL = 0 and make several simplifying assumptions. By slicing a general sample into infinitely many samples with different biases, we derive the analytic expression for the relevant Fisher matrix element. We next consider weighting schemes that construct two effective samples from a single sample of tracers with a continuously varying bias. We show that a particularly simple ansatz for weighting functions can recover all information about fNL in the initial sample that is recoverable using a given bias observable and that simple division into two equal samples is considerably suboptimal when sampling of modes is good, but only marginally suboptimal in the limit where Poisson errors dominate.

Drude weight of the spin-(1)/(2) XXZ chain: Density matrix renormalization group versus exact diagonalization

NASA Astrophysics Data System (ADS)

Karrasch, C.; Hauschild, J.; Langer, S.; Heidrich-Meisner, F.

2013-06-01

We revisit the problem of the spin Drude weight D of the integrable spin-1/2 XXZ chain using two complementary approaches, exact diagonalization (ED) and the time-dependent density-matrix renormalization group (tDMRG). We pursue two main goals. First, we present extensive results for the temperature dependence of D. By exploiting time translation invariance within tDMRG, one can extract D for significantly lower temperatures than in previous tDMRG studies. Second, we discuss the numerical quality of the tDMRG data and elaborate on details of the finite-size scaling of the ED results, comparing calculations carried out in the canonical and grand-canonical ensembles. Furthermore, we analyze the behavior of the Drude weight as the point with SU(2)-symmetric exchange is approached and discuss the relative contribution of the Drude weight to the sum rule as a function of temperature.

Switching Matrix For Optical Signals

NASA Technical Reports Server (NTRS)

Grove, Charles H.

1990-01-01

Proposed matrix of electronically controlled shutters switches signals in optical fibers between multiple input and output channels. Size, weight, and power consumption reduced. Device serves as building block for small, low-power, broad-band television- and data-signal-switching systems providing high isolation between nominally disconnected channels.

Nanomaterials as Assisted Matrix of Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Analysis of Small Molecules.

PubMed

Lu, Minghua; Yang, Xueqing; Yang, Yixin; Qin, Peige; Wu, Xiuru; Cai, Zongwei

2017-04-21

Matrix-assisted laser desorption/ionization (MALDI), a soft ionization method, coupling with time-of-flight mass spectrometry (TOF MS) has become an indispensible tool for analyzing macromolecules, such as peptides, proteins, nucleic acids and polymers. However, the application of MALDI for the analysis of small molecules (<700 Da) has become the great challenge because of the interference from the conventional matrix in low mass region. To overcome this drawback, more attention has been paid to explore interference-free methods in the past decade. The technique of applying nanomaterials as matrix of laser desorption/ionization (LDI), also called nanomaterial-assisted laser desorption/ionization (nanomaterial-assisted LDI), has attracted considerable attention in the analysis of low-molecular weight compounds in TOF MS. This review mainly summarized the applications of different types of nanomaterials including carbon-based, metal-based and metal-organic frameworks as assisted matrices for LDI in the analysis of small biological molecules, environmental pollutants and other low-molecular weight compounds.

Nanomaterials as Assisted Matrix of Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Analysis of Small Molecules

PubMed Central

Lu, Minghua; Yang, Xueqing; Yang, Yixin; Qin, Peige; Wu, Xiuru; Cai, Zongwei

2017-01-01

Matrix-assisted laser desorption/ionization (MALDI), a soft ionization method, coupling with time-of-flight mass spectrometry (TOF MS) has become an indispensible tool for analyzing macromolecules, such as peptides, proteins, nucleic acids and polymers. However, the application of MALDI for the analysis of small molecules (<700 Da) has become the great challenge because of the interference from the conventional matrix in low mass region. To overcome this drawback, more attention has been paid to explore interference-free methods in the past decade. The technique of applying nanomaterials as matrix of laser desorption/ionization (LDI), also called nanomaterial-assisted laser desorption/ionization (nanomaterial-assisted LDI), has attracted considerable attention in the analysis of low-molecular weight compounds in TOF MS. This review mainly summarized the applications of different types of nanomaterials including carbon-based, metal-based and metal-organic frameworks as assisted matrices for LDI in the analysis of small biological molecules, environmental pollutants and other low-molecular weight compounds. PMID:28430138

Reversible gelling culture media for in-vitro cell culture in three-dimensional matrices

DOEpatents

An, Yuehuei H.; Mironov, Vladimir A.; Gutowska, Anna

2000-01-01

A gelling cell culture medium useful for forming a three dimensional matrix for cell culture in vitro is prepared by copolymerizing an acrylamide derivative with a hydrophilic comonomer to form a reversible (preferably thermally reversible) gelling linear random copolymer in the form of a plurality of linear chains having a plurality of molecular weights greater than or equal to a minimum gelling molecular weight cutoff, mixing the copolymer with an aqueous solvent to form a reversible gelling solution and adding a cell culture medium to the gelling solution to form the gelling cell culture medium. Cells such as chondrocytes or hepatocytes are added to the culture medium to form a seeded culture medium, and temperature of the medium is raised to gel the seeded culture medium and form a three dimensional matrix containing the cells. After propagating the cells in the matrix, the cells may be recovered by lowering the temperature to dissolve the matrix and centrifuging.

The spectrum of a vertex model and related spin one chain sitting in a genus five curve

NASA Astrophysics Data System (ADS)

Martins, M. J.

2017-11-01

We derive the transfer matrix eigenvalues of a three-state vertex model whose weights are based on a R-matrix not of difference form with spectral parameters lying on a genus five curve. We have shown that the basic building blocks for both the transfer matrix eigenvalues and Bethe equations can be expressed in terms of meromorphic functions on an elliptic curve. We discuss the properties of an underlying spin one chain originated from a particular choice of the R-matrix second spectral parameter. We present numerical and analytical evidences that the respective low-energy excitations can be gapped or massless depending on the strength of the interaction coupling. In the massive phase we provide analytical and numerical evidences in favor of an exact expression for the lowest energy gap. We point out that the critical point separating these two distinct physical regimes coincides with the one in which the weights geometry degenerate into union of genus one curves.

In situ analysis of the organic framework in the prismatic layer of mollusc shell.

PubMed

Tong, Hua; Hu, Jiming; Ma, Wentao; Zhong, Guirong; Yao, Songnian; Cao, Nianxing

2002-06-01

A novel in situ analytic approach was constructed by means of ion sputtering, decalcification and deprotein techniques combining with scanning electron microscopy (SEM) and transmission electron microscope (TEM) ultrastructural analysis. The method was employed to determine the spatial distribution of the organic framework outside and the inner crystal and organic/inorganic interface spatial geometrical relationship in the prismatic layer of cristaris plicate (leach). The results show that there is a substructure of organic matrix in the intracrystalline region. The prismatic layer forms according to strict hierarchical configuration of regular pattern. Each unit of organic template of prismatic layer can uniquely determine the column crystal growth direction, spatial orientation and size. Cavity templates are responsible for supporting. limiting size and shape and determining the crystal growth spatial orientation, while the intracrystal organic matrix is responsible for providing nucleation point and inducing the nucleation process of calcite. The stereo hierarchical fabrication of prismatic layer was elucidated for the first time.

Calibration of the ROSAT HRI Spectral Response

NASA Technical Reports Server (NTRS)

Prestwich, Andrea

1998-01-01

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases-with time and also is a function of position on the detector. To complicate matters further, the satellite is "wobbled", possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT HRI from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Calibration of the ROSAT HRI Spectral Response

NASA Technical Reports Server (NTRS)

Prestwich, Andrea H.; Silverman, John; McDowell, Jonathan; Callanan, Paul; Snowden, Steve

2000-01-01

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex

PubMed Central

Markov, N. T.; Ercsey-Ravasz, M. M.; Ribeiro Gomes, A. R.; Lamy, C.; Magrou, L.; Vezoli, J.; Misery, P.; Falchier, A.; Quilodran, R.; Gariel, M. A.; Sallet, J.; Gamanut, R.; Huissoud, C.; Clavagnier, S.; Giroud, P.; Sappey-Marinier, D.; Barone, P.; Dehay, C.; Toroczkai, Z.; Knoblauch, K.; Van Essen, D. C.; Kennedy, H.

2014-01-01

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks. PMID:23010748

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

DOE PAGES

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

2015-11-22

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

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

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

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.

Formulating face verification with semidefinite programming.

PubMed

Yan, Shuicheng; Liu, Jianzhuang; Tang, Xiaoou; Huang, Thomas S

2007-11-01

This paper presents a unified solution to three unsolved problems existing in face verification with subspace learning techniques: selection of verification threshold, automatic determination of subspace dimension, and deducing feature fusing weights. In contrast to previous algorithms which search for the projection matrix directly, our new algorithm investigates a similarity metric matrix (SMM). With a certain verification threshold, this matrix is learned by a semidefinite programming approach, along with the constraints of the kindred pairs with similarity larger than the threshold, and inhomogeneous pairs with similarity smaller than the threshold. Then, the subspace dimension and the feature fusing weights are simultaneously inferred from the singular value decomposition of the derived SMM. In addition, the weighted and tensor extensions are proposed to further improve the algorithmic effectiveness and efficiency, respectively. Essentially, the verification is conducted within an affine subspace in this new algorithm and is, hence, called the affine subspace for verification (ASV). Extensive experiments show that the ASV can achieve encouraging face verification accuracy in comparison to other subspace algorithms, even without the need to explore any parameters.

Analyzing Impact Area of Osym Offices in Istanbul by Idw Method

NASA Astrophysics Data System (ADS)

Kalkan, Y.; Ozturk, O.; Gülnerman, A. G.; Bilgi, S.

2016-12-01

OSYM is the main institute for organizing the national level large scale exams in Turkey. According to the Ministry of National Education of Turkey data, there are 17.588.958 students in the country. Therefore, OSYM has a significant role for everyone from every level of education. More than 15% of the total students are studying in Istanbul. These students have various exams throughout a year, which brings some procedures for each exam to be applied. OSYM Coordination Offices were founded to meet the demands and procedures of these exams and applicants. There are 9 Coordination Offices in Istanbul. Moreover, OSYM Application Centers were founded as support units to OSYM Coordination Offices. These units are under the high schools. There are 67 OSYM Application Centers in Istanbul. In the study, spatial distribution of OSYM Coordination Offices and OSYM Application Centers in Istanbul have been studied related to the transportation network of each district of Istanbul city. Origin Destination Cost Matrix (ODCM) and Invers Distance Weighting (IDW) Method were used to visualize the distribution of OSYM Coordination Offices and Application Centers accessibilities. ODCM measures the nearest paths along the transportation network from origins to destinations. IDW is one of the several interpolation methods allocating values to unknown points. ODCM Method was used to calculate the distances over the transportation network. The results obtained from ODCM Method were used in IDW Method to interpolate the weightings of the OSYM offices and centers. Accessibility of the OSYM Coordination Offices and Application Centers has been detected according to surrounding transportation network. Spatial distribution of existing offices and application centers were evaluated by districts of Istanbul city in conclusion of the study by the ODCM and IDW Methods.

Non-covalent interactions of a drug molecule encapsulated in a hybrid silica gel.

PubMed

Paul, Geo; Steuernagel, Stefan; Koller, Hubert

2007-12-28

The drug molecule Propranolol has been encapsulated by a sol-gel process in an organic-inorganic hybrid matrix by in-situ self-assembly; the 2D HETCOR solid state NMR spectroscopy provides direct proof of the intimate spatial relationship between the host matrix and guest drug molecules.

The derivative and tangent operators of a motion in Lorentzian space

NASA Astrophysics Data System (ADS)

Durmaz, Olgun; Aktaş, Buşra; Gündoğan, Hali˙t

In this paper, by using Lorentzian matrix multiplication, L-Tangent operator is obtained in Lorentzian space. The L-Tangent operators related with planar, spherical and spatial motion are computed via special matrix groups. L-Tangent operators are related to vectors. Some illustrative examples for applications of L-Tangent operators are also presented.

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

Briceno, Raul A.; Hansen, Maxwell T.; Monahan, Christopher J.

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate thatmore » the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Lastly, we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.« less

Generation of organized germ layers from a single mouse embryonic stem cell.

PubMed

Poh, Yeh-Chuin; Chen, Junwei; Hong, Ying; Yi, Haiying; Zhang, Shuang; Chen, Junjian; Wu, Douglas C; Wang, Lili; Jia, Qiong; Singh, Rishi; Yao, Wenting; Tan, Youhua; Tajik, Arash; Tanaka, Tetsuya S; Wang, Ning

2014-05-30

Mammalian inner cell mass cells undergo lineage-specific differentiation into germ layers of endoderm, mesoderm and ectoderm during gastrulation. It has been a long-standing challenge in developmental biology to replicate these organized germ layer patterns in culture. Here we present a method of generating organized germ layers from a single mouse embryonic stem cell cultured in a soft fibrin matrix. Spatial organization of germ layers is regulated by cortical tension of the colony, matrix dimensionality and softness, and cell-cell adhesion. Remarkably, anchorage of the embryoid colony from the 3D matrix to collagen-1-coated 2D substrates of ~1 kPa results in self-organization of all three germ layers: ectoderm on the outside layer, mesoderm in the middle and endoderm at the centre of the colony, reminiscent of generalized gastrulating chordate embryos. These results suggest that mechanical forces via cell-matrix and cell-cell interactions are crucial in spatial organization of germ layers during mammalian gastrulation. This new in vitro method could be used to gain insights on the mechanisms responsible for the regulation of germ layer formation.

Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm

NASA Astrophysics Data System (ADS)

Zhang, Siqian; Kuang, Gangyao

2014-10-01

In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

Geostatistical borehole image-based mapping of karst-carbonate aquifer pores

USGS Publications Warehouse

Michael Sukop,; Cunningham, Kevin J.

2016-01-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes.

Cost-effective optical switch matrix for microwave phased-array

NASA Technical Reports Server (NTRS)

Pan, J. J.; Chia, S. L.; Li, W. Z.; Grove, C. H.

1991-01-01

An all-fiber (6x6) optical shutter switch matrix with the control system for microwave phased array has been demonstrated. The device offers the advantages of integrated configuration, low cost, low power consumption, small size, and light weight. The maximum extinction ratio (among 36 individual pixel) of this switch matrix at 840 nm is 24.2 dB, and the switching time is less than 120 microsec. In addition to phased array application, this low cost switch matrix is extremely attractive for fiber optic switching networks.

Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization

NASA Astrophysics Data System (ADS)

Khaki, M.; Schumacher, M.; Forootan, E.; Kuhn, M.; Awange, J. L.; van Dijk, A. I. J. M.

2017-10-01

Assimilation of terrestrial water storage (TWS) information from the Gravity Recovery And Climate Experiment (GRACE) satellite mission can provide significant improvements in hydrological modelling. However, the rather coarse spatial resolution of GRACE TWS and its spatially correlated errors pose considerable challenges for achieving realistic assimilation results. Consequently, successful data assimilation depends on rigorous modelling of the full error covariance matrix of the GRACE TWS estimates, as well as realistic error behavior for hydrological model simulations. In this study, we assess the application of local analysis (LA) to maximize the contribution of GRACE TWS in hydrological data assimilation. For this, we assimilate GRACE TWS into the World-Wide Water Resources Assessment system (W3RA) over the Australian continent while applying LA and accounting for existing spatial correlations using the full error covariance matrix. GRACE TWS data is applied with different spatial resolutions including 1° to 5° grids, as well as basin averages. The ensemble-based sequential filtering technique of the Square Root Analysis (SQRA) is applied to assimilate TWS data into W3RA. For each spatial scale, the performance of the data assimilation is assessed through comparison with independent in-situ ground water and soil moisture observations. Overall, the results demonstrate that LA is able to stabilize the inversion process (within the implementation of the SQRA filter) leading to less errors for all spatial scales considered with an average RMSE improvement of 54% (e.g., 52.23 mm down to 26.80 mm) for all the cases with respect to groundwater in-situ measurements. Validating the assimilated results with groundwater observations indicates that LA leads to 13% better (in terms of RMSE) assimilation results compared to the cases with Gaussian errors assumptions. This highlights the great potential of LA and the use of the full error covariance matrix of GRACE TWS estimates for improved data assimilation results.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

In silico study on the effects of matrix structure in controlled drug release

NASA Astrophysics Data System (ADS)

Villalobos, Rafael; Cordero, Salomón; Maria Vidales, Ana; Domínguez, Armando

2006-07-01

Purpose: To study the effects of drug concentration and spatial distribution of the medicament, in porous solid dosage forms, on the kinetics and total yield of drug release. Methods: Cubic networks are used as models of drug release systems. They were constructed by means of the dual site-bond model framework, which allows a substrate to have adequate geometrical and topological distribution of its pore elements. Drug particles can move inside the networks by following a random walk model with excluded volume interactions between the particles. The drug release time evolution for different drug concentration and different initial drug spatial distribution has been monitored. Results: The numerical results show that in all the studied cases, drug release presents an anomalous behavior, and the consequences of the matrix structural properties, i.e., drug spatial distribution and drug concentration, on the drug release profile have been quantified. Conclusions: The Weibull function provides a simple connection between the model parameters and the microstructure of the drug release device. A critical modeling of drug release from matrix-type delivery systems is important in order to understand the transport mechanisms that are implicated, and to predict the effect of the device design parameters on the release rate.

Further studies on stability analysis of nonlinear Roesser-type two-dimensional systems

NASA Astrophysics Data System (ADS)

Dai, Xiao-Lin

2014-04-01

This paper is concerned with further relaxations of the stability analysis of nonlinear Roesser-type two-dimensional (2D) systems in the Takagi-Sugeno fuzzy form. To achieve the goal, a novel slack matrix variable technique, which is homogenous polynomially parameter-dependent on the normalized fuzzy weighting functions with arbitrary degree, is developed and the algebraic properties of the normalized fuzzy weighting functions are collected into a set of augmented matrices. Consequently, more information about the normalized fuzzy weighting functions is involved and the relaxation quality of the stability analysis is significantly improved. Moreover, the obtained result is formulated in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed result.

Glass transition behavior of polystyrene/silica nanocomposites.

NASA Astrophysics Data System (ADS)

Xie, Yuping; Sen, Sudeepto; Kumar, Sanat; Bansal, Amitabh

2006-03-01

The change in thermomechanical properties of nano-filled polymers is of considerable scientific and technological interest. The interaction between the nanofillers and the matrix polymer controls the nanocomposite properties. We will present the results from recent and ongoing DSC experiments on polystyrene/silica nanocomposites. Polystyrene of different molecular weights (and from different sources) and silica nanoparticles 10-15 nm in diameter (both as received from Nissan and surface modified by grafted or physisorbed polystyrene) are being used to process the nanocomposites. We are studying trends in the glass transition behavior by changing the matrix molecular weights and the silica weight fractions. Recent data indicate that the glass transition temperature can both decrease and increase depending on the polymer-nanofiller combination as well as the thermal treatment of the nanocomposites prior to the DSC runs.

Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

NASA Astrophysics Data System (ADS)

Islamiyati, A.; Fatmawati; Chamidah, N.

2018-03-01

The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

Spatial Pattern of Copper Phosphate Precipitation Involves in Copper Accumulation and Resistance of Unsaturated Pseudomonas putida CZ1 Biofilm.

PubMed

Chen, Guangcun; Lin, Huirong; Chen, Xincai

2016-12-28

Bacterial biofilms are spatially structured communities that contain bacterial cells with a wide range of physiological states. The spatial distribution and speciation of copper in unsaturated Pseudomonas putida CZ1 biofilms that accumulated 147.0 mg copper per g dry weight were determined by transmission electron microscopy coupled with energy dispersive X-ray analysis, and micro-X-ray fluorescence microscopy coupled with micro-X-ray absorption near edge structure (micro-XANES) analysis. It was found that copper was mainly precipitated in a 75 μm thick layer as copper phosphate in the middle of the biofilm, while there were two living cell layers in the air-biofilm and biofilm-medium interfaces, respectively, distinguished from the copper precipitation layer by two interfaces. The X-ray absorption fine structure analysis of biofilm revealed that species resembling Cu₃(PO₄)₂ predominated in biofilm, followed by Cu-Citrate- and Cu-Glutathione-like species. Further analysis by micro-XANES revealed that 94.4% of copper were Cu₃(PO₄)₂-like species in the layer next to the air interface, whereas the copper species of the layer next to the medium interface were composed by 75.4% Cu₃(PO₄)₂, 10.9% Cu-Citrate-like species, and 11.2% Cu-Glutathione-like species. Thereby, it was suggested that copper was initially acquired by cells in the biofilm-air interface as a citrate complex, and then transported out and bound by out membranes of cells, released from the copper-bound membranes, and finally precipitated with phosphate in the extracellular matrix of the biofilm. These results revealed a clear spatial pattern of copper precipitation in unsaturated biofilm, which was responsible for the high copper tolerance and accumulation of the biofilm.

Properties Of Carbon/Carbon and Carbon/Phenolic Composites

NASA Technical Reports Server (NTRS)

Mathis, John R.; Canfield, A. R.

1993-01-01

Report presents data on physical properties of carbon-fiber-reinforced carbon-matrix and phenolic-matrix composite materials. Based on tests conducted on panels, cylinders, blocks, and formed parts. Data used by designers to analyze thermal-response and stress levels and develop structural systems ensuring high reliability at minimum weight.

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…

Determination of phytate in high molecular weight, charged organic matrices by two-dimensional size exclusion-ion chromatography

USDA-ARS?s Scientific Manuscript database

A two-dimensional chromatography method for analyzing anionic targets (specifically phytate) in complex matrices is described. Prior to quantification by anion exchange chromatography, the sample matrix was prepared by size exclusion chromatography, which removed the majority of matrix complexities....

Mapping of Mechanical Strains and Stresses around Quiescent Engineered Three-Dimensional Epithelial Tissues

PubMed Central

Gjorevski, Nikolce; Nelson, Celeste M.

2012-01-01

Understanding how physical signals guide biological processes requires qualitative and quantitative knowledge of the mechanical forces generated and sensed by cells in a physiologically realistic three-dimensional (3D) context. Here, we used computational modeling and engineered epithelial tissues of precise geometry to define the experimental parameters that are required to measure directly the mechanical stress profile of 3D tissues embedded within native type I collagen. We found that to calculate the stresses accurately in these settings, we had to account for mechanical heterogeneities within the matrix, which we visualized and quantified using confocal reflectance and atomic force microscopy. Using this technique, we were able to obtain traction forces at the epithelium-matrix interface, and to resolve and quantify patterns of mechanical stress throughout the surrounding matrix. We discovered that whereas single cells generate tension by contracting and pulling on the matrix, the contraction of multicellular tissues can also push against the matrix, causing emergent compression. Furthermore, tissue geometry defines the spatial distribution of mechanical stress across the epithelium, which communicates mechanically over distances spanning hundreds of micrometers. Spatially resolved mechanical maps can provide insight into the types and magnitudes of physical parameters that are sensed and interpreted by multicellular tissues during normal and pathological processes. PMID:22828342

Fast global image smoothing based on weighted least squares.

PubMed

Min, Dongbo; Choi, Sunghwan; Lu, Jiangbo; Ham, Bumsub; Sohn, Kwanghoon; Do, Minh N

2014-12-01

This paper presents an efficient technique for performing a spatially inhomogeneous edge-preserving image smoothing, called fast global smoother. Focusing on sparse Laplacian matrices consisting of a data term and a prior term (typically defined using four or eight neighbors for 2D image), our approach efficiently solves such global objective functions. In particular, we approximate the solution of the memory-and computation-intensive large linear system, defined over a d-dimensional spatial domain, by solving a sequence of 1D subsystems. Our separable implementation enables applying a linear-time tridiagonal matrix algorithm to solve d three-point Laplacian matrices iteratively. Our approach combines the best of two paradigms, i.e., efficient edge-preserving filters and optimization-based smoothing. Our method has a comparable runtime to the fast edge-preserving filters, but its global optimization formulation overcomes many limitations of the local filtering approaches. Our method also achieves high-quality results as the state-of-the-art optimization-based techniques, but runs ∼10-30 times faster. Besides, considering the flexibility in defining an objective function, we further propose generalized fast algorithms that perform Lγ norm smoothing (0 < γ < 2) and support an aggregated (robust) data term for handling imprecise data constraints. We demonstrate the effectiveness and efficiency of our techniques in a range of image processing and computer graphics applications.

A weight modification sequential method for VSC-MTDC power system state estimation

NASA Astrophysics Data System (ADS)

Yang, Xiaonan; Zhang, Hao; Li, Qiang; Guo, Ziming; Zhao, Kun; Li, Xinpeng; Han, Feng

2017-06-01

This paper presents an effective sequential approach based on weight modification for VSC-MTDC power system state estimation, called weight modification sequential method. The proposed approach simplifies the AC/DC system state estimation algorithm through modifying the weight of state quantity to keep the matrix dimension constant. The weight modification sequential method can also make the VSC-MTDC system state estimation calculation results more ccurate and increase the speed of calculation. The effectiveness of the proposed weight modification sequential method is demonstrated and validated in modified IEEE 14 bus system.

Variational Optimization of the Second-Order Density Matrix Corresponding to a Seniority-Zero Configuration Interaction Wave Function.

PubMed

Poelmans, Ward; Van Raemdonck, Mario; Verstichel, Brecht; De Baerdemacker, Stijn; Torre, Alicia; Lain, Luis; Massaccesi, Gustavo E; Alcoba, Diego R; Bultinck, Patrick; Van Neck, Dimitri

2015-09-08

We perform a direct variational determination of the second-order (two-particle) density matrix corresponding to a many-electron system, under a restricted set of the two-index N-representability P-, Q-, and G-conditions. In addition, we impose a set of necessary constraints that the two-particle density matrix must be derivable from a doubly occupied many-electron wave function, i.e., a singlet wave function for which the Slater determinant decomposition only contains determinants in which spatial orbitals are doubly occupied. We rederive the two-index N-representability conditions first found by Weinhold and Wilson and apply them to various benchmark systems (linear hydrogen chains, He, N2, and CN(-)). This work is motivated by the fact that a doubly occupied many-electron wave function captures in many cases the bulk of the static correlation. Compared to the general case, the structure of doubly occupied two-particle density matrices causes the associate semidefinite program to have a very favorable scaling as L(3), where L is the number of spatial orbitals. Since the doubly occupied Hilbert space depends on the choice of the orbitals, variational calculation steps of the two-particle density matrix are interspersed with orbital-optimization steps (based on Jacobi rotations in the space of the spatial orbitals). We also point to the importance of symmetry breaking of the orbitals when performing calculations in a doubly occupied framework.

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.

Wiener-matrix image restoration beyond the sampling passband

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.

1991-01-01

A finer-than-sampling-lattice resolution image can be obtained using multiresponse image gathering and Wiener-matrix restoration. The multiresponse image gathering weighs the within-passband and aliased signal components differently, allowing the Wiener-matrix restoration filter to unscramble these signal components and restore spatial frequencies beyond the sampling passband of the photodetector array. A multiresponse images can be reassembled into a single minimum mean square error image with a resolution that is sq rt A times finer than the photodetector-array sampling lattice.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

A photoreversible protein-patterning approach for guiding stem cell fate in three-dimensional gels

NASA Astrophysics Data System (ADS)

Deforest, Cole A.; Tirrell, David A.

2015-05-01

Although biochemically patterned hydrogels are capable of recapitulating many critical aspects of the heterogeneous cellular niche, exercising spatial and temporal control of the presentation and removal of biomolecular signalling cues in such systems has proved difficult. Here, we demonstrate a synthetic strategy that exploits two bioorthogonal photochemistries to achieve reversible immobilization of bioactive full-length proteins with good spatial and temporal control within synthetic, cell-laden biomimetic scaffolds. A photodeprotection-oxime-ligation sequence permits user-defined quantities of proteins to be anchored within distinct subvolumes of a three-dimensional matrix, and an ortho-nitrobenzyl ester photoscission reaction facilitates subsequent protein removal. By using this approach to pattern the presentation of the extracellular matrix protein vitronectin, we accomplished reversible differentiation of human mesenchymal stem cells to osteoblasts in a spatially defined manner. Our protein-patterning approach should provide further avenues to probe and direct changes in cell physiology in response to dynamic biochemical signalling.

Dynamic Remodeling of Microbial Biofilms by Functionally Distinct Exopolysaccharides

PubMed Central

Chew, Su Chuen; Kundukad, Binu; Seviour, Thomas; van der Maarel, Johan R. C.; Yang, Liang; Rice, Scott A.; Doyle, Patrick

2014-01-01

ABSTRACT Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus. Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation. PMID:25096883

Robustness of Thirty Meter Telescope primary mirror control

NASA Astrophysics Data System (ADS)

Macmynowski, Douglas G.; Thompson, Peter M.; Shelton, Chris; Roberts, Lewis C., Jr.

2010-07-01

The primary mirror control system for the Thirty Meter Telescope (TMT) maintains the alignment of the 492 segments in the presence of both quasi-static (gravity and thermal) and dynamic disturbances due to unsteady wind loads. The latter results in a desired control bandwidth of 1Hz at high spatial frequencies. The achievable bandwidth is limited by robustness to (i) uncertain telescope structural dynamics (control-structure interaction) and (ii) small perturbations in the ill-conditioned influence matrix that relates segment edge sensor response to actuator commands. Both of these effects are considered herein using models of TMT. The former is explored through multivariable sensitivity analysis on a reduced-order Zernike-basis representation of the structural dynamics. The interaction matrix ("A-matrix") uncertainty has been analyzed theoretically elsewhere, and is examined here for realistic amplitude perturbations due to segment and sensor installation errors, and gravity and thermal induced segment motion. The primary influence of A-matrix uncertainty is on the control of "focusmode"; this is the least observable mode, measurable only through the edge-sensor (gap-dependent) sensitivity to the dihedral angle between segments. Accurately estimating focus-mode will require updating the A-matrix as a function of the measured gap. A-matrix uncertainty also results in a higher gain-margin requirement for focus-mode, and hence the A-matrix and CSI robustness need to be understood simultaneously. Based on the robustness analysis, the desired 1 Hz bandwidth is achievable in the presence of uncertainty for all except the lowest spatial-frequency response patterns of the primary mirror.

Hyaluronan influence on the onset of chondrogenic differentiation of mesenchymal stem cells.

PubMed

Dvorakova, Jana; Velebny, Vladimir; Kubala, Lukas

2008-10-01

Hyaluronan (HA) is an abundant component of chondrogenic tissue hence it is often used as a fundamental constituent in cartilage tissue substitutes. However, effects of different molecular weight HA on chondrogenic differentiation are not clear. The aim was to evaluate modulation of mesenchymal stem cell (MSC) early chondrogenesis by HA of molecular weights 100, 600 and 1 500 kDa. HA was applied on MSCs cultured in a pellet system for one, two and three weeks. Chondrogenesis was evaluated by determinations of gene expression of transcription factor Sox-9 and extracellular matrix proteins collagen type II and XI, aggrecan, and COMP by Real-Time PCR and completed with histological analysis. Upon chondrogenic induction, the respective pellets revealed active transcription of the chondrogenic genes together with proceeding accumulation of glycosaminoglycan (GAG) rich extracellular matrix. Sox-9 was also expressed in non-chondrogenic MSC controls. HA treated pellets were not significantly influenced on day 7 of culture. However, on day 14, lowered expression in some of the extracellular matrix proteins appeared together with a moderately smaller amount of GAG content in pellet sections. Nevertheless, the analysis on day 21 has demonstrated that HA did not affect the outcome of the differentiation by the end of the culture. Any difference regarding the molecular weight of the HA was not found. It could be speculated that HA induced a time shift in the phase of the dominant matrix protein onset which was in full compensated by the end of the evaluated time period. Thus, data suggest that HA of any tested molecular weight does not significantly modulate chondrogenesis of MSCs in pellet system.

Spatial distribution of low birthweight infants in Taubaté, São Paulo, Brazil

PubMed Central

Nascimento, Luiz Fernando C.; Costa, Thais Moreira; Zöllner, Maria Stella A. da C.

2013-01-01

OBJECTIVE: To identify the spatial pattern of low birth weight infants in the city of Taubaté, São Paulo, Southeast Brazil. METHODS: Ecological and exploratory study, developed with the data acquired from the Health Department of Taubaté, regarding the period from January 1st 2006 and December 31st 2010. Birth certificates were used to obtain the data from infants weighing less than 2500g. A digital basis of census tracts was applied and the Global Moran index (IM) was estimated. Thematic maps were built for the distribution of low birth weight, health centers and tracts, according to the priority care (Moran map). The adopted statistical significance was α=5% and TerraView software conducted the spatial analysis. RESULTS: There were 18,915 live births during the study period, with 1,817 low birth weight infants (9.6%). The low birth weight infants' prevalence during the period ranged from 9.3 to 9.8%. A total of 1,185 infants with known addresses, compatible with the digital base (65.2% of low birth weight infants), were included. The IM for low birth weight was 0.12, with p<0.01; regarding the health centers distribution, IM was -0.07, with p=0.01. The Moran map identified 11 census tracts with high priority for intervention by health managers, located in the outskirts of the city. CONCLUSIONS: The spatial analysis identified the low birth weight distribution by census tracts and the sectors with a high priority for intervention. PMID:24473951

Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares.

PubMed

Zhou, Zhenyu; Liu, Wei; Cui, Jiali; Wang, Xunheng; Arias, Diana; Wen, Ying; Bansal, Ravi; Hao, Xuejun; Wang, Zhishun; Peterson, Bradley S; Xu, Dongrong

2011-02-01

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model. Copyright © 2011 Elsevier Inc. All rights reserved.

Metacommunity composition of web-spiders in a fragmented neotropical forest: relative importance of environmental and spatial effects.

PubMed

Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M

2012-01-01

The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.

Polyethylene composites containing a phase change material having a C14 straight chain hydrocarbon

DOEpatents

Salyer, Ival O.

1987-01-01

A composite useful in thermal energy storage, said composite being formed of a polyethylene matrix having a straight chain alkyl hydrocarbon incorporated therein, said polyethylene being crosslinked to such a degree that said polyethylene matrix is form stable and said polyethylene matrix is capable of absorbing at least 10% by weight of said straight chain alkyl hydrocarbon; the composite is useful in forming pellets or sheets having thermal energy storage characteristics.

Metal Matrix Composite LOX Turbopump Housing via Novel Tool-less Net-Shape Pressure Infiltration Casting Technology

NASA Technical Reports Server (NTRS)

Shah, Sandeep; Lee, Jonathan; Bhat, Biliyar; Wells, Doug; Gregg, Wayne; Marsh, Matthew; Genge, Gary; Forbes, John; Salvi, Alex; Cornie, James A.

2003-01-01

Metal matrix composites for propulsion components offer high performance and affordability, resulting in low weight and cost. The following sections in this viewgraph presentation describe the pressure infiltration casting of a metal matrix composite LOX turbopump housing: 1) Baseline Pump Design and Stress Analysis; 2) Tool-less Advanced Pressure Infiltration Casting Process; 3) Preform Splicing and Joining for Large Components such as Pump Housing; 4) Fullscale Pump Housing Redesign.

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

PubMed

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

2015-09-15

This work presented a highly sensitive bacterial antibiotic susceptibility test through β-lactamase assay using Parylene-matrix chip. β-lactamases (EC 3.5.2.6) are an important family of enzymes that confer resistance to β-lactam antibiotics by catalyzing the hydrolysis of these antibiotics. Here we present a highly sensitive assay to quantitate β-lactamase-mediated hydrolysis of penicillin into penicilloic acid. Typically, MALDI-TOF mass spectrometry has been used to quantitate low molecular weight analytes and to discriminate them from noise peaks of matrix fragments that occur at low m/z ratios (m/z<500). The β-lactamase assay for the Escherichia coli antibiotic susceptibility test was carried out using Parylene-matrix chip and MALDI-TOF mass spectrometry. The Parylene-matrix chip was successfully used to quantitate penicillin (m/z: [PEN+H](+)=335.1 and [PEN+Na](+)=357.8) and penicilloic acid (m/z: [PA+H](+)=353.1) in a β-lactamase assay with minimal interference of low molecular weight noise peaks. The β-lactamase assay was carried out with an antibiotic-resistant E. coli strain and an antibiotic-susceptible E. coli strain, revealing that the minimum number of E. coli cells required to screen for antibiotic resistance was 1000 cells for the MALDI-TOF mass spectrometry/Parylene-matrix chip assay. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial-Operator Algebra For Flexible-Link Manipulators

NASA Technical Reports Server (NTRS)

Jain, Abhinandan; Rodriguez, Guillermo

1994-01-01

Method of computing dynamics of multiple-flexible-link robotic manipulators based on spatial-operator algebra, which originally applied to rigid-link manipulators. Aspects of spatial-operator-algebra approach described in several previous articles in NASA Tech Briefs-most recently "Robot Control Based on Spatial-Operator Algebra" (NPO-17918). In extension of spatial-operator algebra to manipulators with flexible links, each link represented by finite-element model: mass of flexible link apportioned among smaller, lumped-mass rigid bodies, coupling of motions expressed in terms of vibrational modes. This leads to operator expression for modal-mass matrix of link.

Pixelated filters for spatial imaging

NASA Astrophysics Data System (ADS)

Mathieu, Karine; Lequime, Michel; Lumeau, Julien; Abel-Tiberini, Laetitia; Savin De Larclause, Isabelle; Berthon, Jacques

2015-10-01

Small satellites are often used by spatial agencies to meet scientific spatial mission requirements. Their payloads are composed of various instruments collecting an increasing amount of data, as well as respecting the growing constraints relative to volume and mass; So small-sized integrated camera have taken a favored place among these instruments. To ensure scene specific color information sensing, pixelated filters seem to be more attractive than filter wheels. The work presented here, in collaboration with Institut Fresnel, deals with the manufacturing of this kind of component, based on thin film technologies and photolithography processes. CCD detectors with a pixel pitch about 30 μm were considered. In the configuration where the matrix filters are positioned the closest to the detector, the matrix filters are composed of 2x2 macro pixels (e.g. 4 filters). These 4 filters have a bandwidth about 40 nm and are respectively centered at 550, 700, 770 and 840 nm with a specific rejection rate defined on the visible spectral range [500 - 900 nm]. After an intense design step, 4 thin-film structures have been elaborated with a maximum thickness of 5 μm. A run of tests has allowed us to choose the optimal micro-structuration parameters. The 100x100 matrix filters prototypes have been successfully manufactured with lift-off and ion assisted deposition processes. High spatial and spectral characterization, with a dedicated metrology bench, showed that initial specifications and simulations were globally met. These excellent performances knock down the technological barriers for high-end integrated specific multi spectral imaging.

Investigation on Mechanical Properties of Graphene Oxide reinforced GFRP

NASA Astrophysics Data System (ADS)

Arun, G. K.; Sreenivas, Nikhil; Brahma Reddy, Kesari; Sai Krishna Reddy, K.; Shashi Kumar, M. E.; Pramod, R.

2018-02-01

Graphene and E-glass fibres individually find a very wide field of applications because of their various mechanical and chemical properties. Recently graphene has attracted both academic and industrial interest because it can produce a dramatic improvement in properties at very low filler content. The primary interest of this venture is to investigate on Graphene reinforced polymer matrix nanocomposites and finding the mechanical properties. The composites were fabricated by Hand Lay Process and have been evaluated by the addition of Graphene with 1, 1.5, 2, 2.5 and 3 by weight% as reinforcement in composites. The theoretical and experimental results validate the increase in properties such as tensile strength, hardness and flexural strength with increase in weight proportions from 1% to 3% of graphene powder. It was observed that the composite material with 2.5% weight fraction of graphene yielded superior properties over other weight percentages. Graphene reinforced polymer matrix nanocomposites finds its major applications in the manufacture of aircraft bodies, ballistic missiles, sporting equipment, marine applications and extraterrestrial ventures.

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.

Cooled Ceramic Matrix Composite Propulsion Structures Demonstrated

NASA Technical Reports Server (NTRS)

Jaskowiak, Martha H.; Dickens, Kevin W.

2005-01-01

NASA's Next Generation Launch Technology (NGLT) Program has successfully demonstrated cooled ceramic matrix composite (CMC) technology in a scramjet engine test. This demonstration represented the world s largest cooled nonmetallic matrix composite panel fabricated for a scramjet engine and the first cooled nonmetallic composite to be tested in a scramjet facility. Lightweight, high-temperature, actively cooled structures have been identified as a key technology for enabling reliable and low-cost space access. Tradeoff studies have shown this to be the case for a variety of launch platforms, including rockets and hypersonic cruise vehicles. Actively cooled carbon and CMC structures may meet high-performance goals at significantly lower weight, while improving safety by operating with a higher margin between the design temperature and material upper-use temperature. Studies have shown that using actively cooled CMCs can reduce the weight of the cooled flow-path component from 4.5 to 1.6 lb/sq ft and the weight of the propulsion system s cooled surface area by more than 50 percent. This weight savings enables advanced concepts, increased payload, and increased range. The ability of the cooled CMC flow-path components to operate over 1000 F hotter than the state-of-the-art metallic concept adds system design flexibility to space-access vehicle concepts. Other potential system-level benefits include smaller fuel pumps, lower part count, lower cost, and increased operating margin.

Comparison of Adjacency and Distance-Based Approaches for Spatial Analysis of Multimodal Traffic Crash Data

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Many studies have utilized the spatial correlations among traffic crash data to develop crash prediction models with the aim to investigate the influential factors or predict crash counts at different sites. The spatial correlation have been observed to account for heterogeneity in different forms of weight matrices which improves the estimation performance of models. But very rarely have the weight matrices been compared for the prediction accuracy for estimation of crash counts. This study was targeted at the comparison of two different approaches for modelling the spatial correlations among crash data at macro-level (County). Multivariate Full Bayesian crash prediction models were developed using Decay-50 (distance-based) and Queen-1 (adjacency-based) weight matrices for simultaneous estimation crash counts of four different modes: vehicle, motorcycle, bike, and pedestrian. The goodness-of-fit and different criteria for accuracy at prediction of crash count reveled the superiority of Decay-50 over Queen-1. Decay-50 was essentially different from Queen-1 with the selection of neighbors and more robust spatial weight structure which rendered the flexibility to accommodate the spatially correlated crash data. The consistently better performance of Decay-50 at prediction accuracy further bolstered its superiority. Although the data collection efforts to gather centroid distance among counties for Decay-50 may appear to be a downside, but the model has a significant edge to fit the crash data without losing the simplicity of computation of estimated crash count.

Delivering both sum and difference beam distributions to a planar monopulse antenna array

DOEpatents

Strassner, II, Bernd H.

2015-12-22

A planar monopulse radar apparatus includes a planar distribution matrix coupled to a planar antenna array having a linear configuration of antenna elements. The planar distribution matrix is responsive to first and second pluralities of weights applied thereto for providing both sum and difference beam distributions across the antenna array.

Development of Improved Environmental Resistant Organic-Reinforced Materials Systems

DTIC Science & Technology

1975-11-01

Advanced composites , graphite and boron reinforced laminates, moisture resistance, environmental resistance, organic matrix composites . 20. ABSTRACT...in November 1975 for publication. Efforts at TOD were conducted within the Advanced Composites Engineering Departmfntrunde; L technical...weight makes^organic matrix advanced composites hardware extremely attractive for today s modern Air Force weapons systems. Accordingly, such

Calculating the permeability coefficients of mixed matrix membranes of polydimethylsiloxane and silicalite crystals to various ethanol-water solutions using molecular simulations.

EPA Science Inventory

The permeability coefficients of mixed matrix membranes of polydimethylsiloxane (PDMS) and silicalite crystal are taken as the sum of the permeability coefficients of membrane components each weighted by their associated mass fraction. The permeability coefficient of a membrane c...

Identification of Bacteria Using Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry

ERIC Educational Resources Information Center

Kedney, Mollie G.; Strunk, Kevin B.; Giaquinto, Lisa M.; Wagner, Jennifer A.; Pollack, Sidney; Patton, Walter A.

2007-01-01

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS or simply MALDI) has become ubiquitous in the identification and analysis of biomacromolecules. As a technique that allows for the molecular weight determination of otherwise nonvolatile molecules, MALDI has had a profound impact in the molecular…

Light weight polymer matrix composite material

NASA Technical Reports Server (NTRS)

Bowles, Kenneth J. (Inventor); Lowell, Carl E. (Inventor)

1991-01-01

A graphite fiber reinforced polymer matrix is layed up, cured, and thermally aged at about 750.degree. F. in the presence of an inert gas. The heat treatment improves the structural integrity and alters the electrical conductivity of the materials. In the preferred embodiment PMR-15 polyimides and Celion-6000 graphite fibers are used.

Chemical, Calcium Phosphate Cements for Geothermal Wells - Corrosion Protection, Bond Strength and Matrix Self-Healing

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

Sugama, Toshifumi

The data set shows performance of economical calcium phosphate cement (Fondu) blended with fly ash, class F (FAF) in carbon steel corrosion protection tests (corrosion rate, corrosion current and potential), bond- and matrix strength, as well as matrix strength recovery after imposed damage at 300C. The corrosion protection and lap-shear bond strength data are given for different Fondu/FAF ratios, the matrix strength data recoveries are reported for 60/40 weight % Fondu/FAF ratios. Effect of sodium phosphate on bond strength, corrosion protection and self-healing is demonstrated.

Biomass Morphology Subjected to Different Chemical Treatment

NASA Astrophysics Data System (ADS)

Sutan, Norsuzailina Mohamed; Masjida Mazlan, Siti; Taib, Siti Noor Linda; Lee, Delsye Teo Ching; Hassan, Alsidqi; Kudnie Sahari, Siti; Mohamad Said, Khairul Anwar; Rahman Sobuz, Habibur

2018-03-01

A growing interest of sugarcane bagasse fibre composite has been observed in recent years due to its attractiveness properties such as low specific weight, renewable source and producible with low investment at low cost. However, these materials have a low interfacial adhesion between fibre and matrix which lead to reduction in certain mechanical properties of the composite. To overcome this problem, studies show that certain chemical treatments on the surface of the fibres are some alternatives that significantly increase the adhesion reinforcement/matrix, in some cases improving its mechanical properties. The objective of this study was to evaluate the effect of different type of chemical treatment which are alkali and acid treatment on sugarcane bagasse fibre surface morphology. Seeking to improve the adhesion fibre matrix, the fibre has been treated with 5% of NaOH and 5% of HCL solution with added of bagasse fibre used in the range of 0% to 3% of cement weight respectively. Through SEM investigation, it is confirmed that chemical treatment helps to remove hemicelluloses from raw bagasse fiber as well as improved fibre matrix adhesion.

Determination of polycyclic aromatic hydrocarbons with molecular weight 300 and 302 in environmental-matrix standard reference materials by gas chromatography/mass spectrometry.

PubMed

Schubert, Patricia; Schantz, Michele M; Sander, Lane C; Wise, Stephen A

2003-01-15

An analytical approach based on gas chromatography/ mass spectrometry (GC/MS) is presented for the measurement of polycyclic aromatic hydrocarbons with molecular weight (MW) 300 and 302 in environmental samples. Three different GC stationary phases [5% and 50% phenyl methylpolysiloxane and dimethyl (50% liquid crystalline) polysiloxane] were compared, and retention indexes (RI) are given for 23 individual MW 302 isomers. Identification of MW 300 and 302 isomers in four environmental-matrix Standard Reference Materials (SRMs) (SRM 1597, coal tar extract; SRM 1648 and SRM 1649a, air particulate matter; and SRM 1941, marine sediment) was based on the comparison of RI data and mass spectra from authentic standards. Dibenzo[a,l]pyrene, which is of considerable interest because of its high carcinogenicity, was identified and quantified in the four environmental-matrix SRMs. A total of 23 isomers of MW 302 and four isomers of MW 300 were quantified in four different environmental-matrix SRMs, and the results are compared to previously reported results based on liquid chromatography with fluorescence detection.

On the influence of surface patterning on tissue self-assembly and mechanics.

PubMed

Coppola, Valerio; Ventre, Maurizio; Natale, Carlo F; Rescigno, Francesca; Netti, Paolo A

2018-04-28

Extracellular matrix assembly and composition influence the biological and mechanical functions of tissues. Developing strategies to control the spatial arrangement of cells and matrix is of central importance for tissue engineering-related approaches relying on self-assembling and scaffoldless processes. Literature reports demonstrated that signals patterned on material surfaces are able to control cell positioning and matrix orientation. However, the mechanisms underlying the interactions between material signals and the structure of the de novo synthesized matrix are far from being thoroughly understood. In this work, we investigated the ordering effect provided by nanoscale topographic patterns on the assembly of tissue sheets grown in vitro. We stimulated MC3T3-E1 preosteoblasts to produce and assemble a collagen-rich matrix on substrates displaying patterns with long- or short-range order. Then, we investigated microstructural features and mechanical properties of the tissue in uniaxial tension. Our results demonstrate that patterned material surfaces are able to control the initial organization of cells in close contact to the surface; then cell-generated contractile forces profoundly remodel tissue structure towards mechanically stable spatial patterns. Such a remodelling effect acts both locally, as it affects cell and nuclear shape and globally, by affecting the gross mechanical response of the tissue. Such an aspect of dynamic interplay between cells and the surrounding matrix must be taken into account when designing material platform for the in vitro generation of tissue with specific microstructural assemblies. Copyright © 2018 John Wiley & Sons, Ltd.

Alumina forming iron base superalloy

DOEpatents

Yamamoto, Yukinori; Muralidharan, Govindarajan; Brady, Michael P.

2014-08-26

An austenitic stainless steel alloy, consists essentially of, in weight percent 2.5 to 4 Al; 25 to 35 Ni; 12 to 19 Cr; at least 1, up to 4 total of at least one element selected from the group consisting of Nb and Ta; 0.5 to 3 Ti; less than 0.5 V; 0.1 to 1 of at least on element selected from the group consisting of Zr and Hf; 0.03 to 0.2 C; 0.005 to 0.1 B; and base Fe. The weight percent Fe is greater than the weight percent Ni. The alloy forms an external continuous scale including alumina, and contains coherent precipitates of .gamma.'-Ni.sub.3Al, and a stable essentially single phase FCC austenitic matrix microstructure. The austenitic matrix is essentially delta-ferrite-free and essentially BCC-phase-free.

Cell and method for electrolysis of water and anode

NASA Technical Reports Server (NTRS)

Aylward, J. R. (Inventor)

1981-01-01

An electrolytic cell for converting water vapor to oxygen and hydrogen include an anode comprising a foraminous conductive metal substrate with a 65-85 weight percent iridium oxide coating and 15-35 weight percent of a high temperature resin binder. A matrix member contains an electrolyte to which a cathode substantially inert. The foraminous metal member is most desirably expanded tantalum mesh, and the cell desirably includes reservoir elements of porous sintered metal in contact with the anode to receive and discharge electrolyte to the matrix member as required. Upon entry of a water vapor containing airstream into contact with the outer surface of the anode and thence into contact with iridium oxide coating, the water vapor is electrolytically converted to hydrogen ions and oxygen with the hydrogen ions migrating through the matrix to the cathode and the oxygen gas produced at the anode to enrich the air stream passing by the anode.

Production and mechanical properties of Al-SiC metal matrix composites

NASA Astrophysics Data System (ADS)

Karvanis, K.; Fasnakis, D.; Maropoulos, A.; Papanikolaou, S.

2016-11-01

The usage of Al-SiC Metal Matrix Composites is constantly increasing in the last years due to their unique properties such as light weight, high strength, high specific modulus, high fatigue strength, high hardness and low density. Al-SiC composites of various carbide compositions were produced using a centrifugal casting machine. The mechanical properties, tensile and compression strength, hardness and drop-weight impact strength were studied in order to determine the optimum carbide % in the metal matrix composites. Scanning electron microscopy was used to study the microstructure-property correlation. It was observed that the tensile and the compressive strength of the composites increased as the proportion of silicon carbide became higher in the composites. Also with increasing proportion of silicon carbide in the composite, the material became harder and appeared to have smaller values for total displacement and total energy during impact testing.

Nanocellular foam with solid flame retardant

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

Chen, Liang; Kelly-Rowley, Anne M.; Bunker, Shana P.

Prepare nanofoam by (a) providing an aqueous solution of a flame retardant dissolved in an aqueous solvent, wherein the flame retardant is a solid at 23.degree. C. and 101 kiloPascals pressure when in neat form; (b) providing a fluid polymer composition selected from a solution of polymer dissolved in a water-miscible solvent or a latex of polymer particles in a continuous aqueous phase; (c) mixing the aqueous solution of flame retardant with the fluid polymer composition to form a mixture; (d) removing water and, if present, solvent from the mixture to produce a polymeric composition having less than 74 weight-percentmore » flame retardant based on total polymeric composition weight; (e) compound the polymeric composition with a matrix polymer to form a matrix polymer composition; and (f) foam the matrix polymer composition into nanofoam having a porosity of at least 60 percent.« less

Compressive and shear buckling analysis of metal matrix composite sandwich panels under different thermal environments

NASA Technical Reports Server (NTRS)

Ko, William L.; Jackson, Raymond H.

1993-01-01

Combined inplane compressive and shear buckling analysis was conducted on flat rectangular sandwich panels using the Raleigh-Ritz minimum energy method with a consideration of transverse shear effect of the sandwich core. The sandwich panels were fabricated with titanium honeycomb core and laminated metal matrix composite face sheets. The results show that slightly slender (along unidirectional compressive loading axis) rectangular sandwich panels have the most desirable stiffness-to-weight ratios for aerospace structural applications; the degradation of buckling strength of sandwich panels with rising temperature is faster in shear than in compression; and the fiber orientation of the face sheets for optimum combined-load buckling strength of sandwich panels is a strong function of both loading condition and panel aspect ratio. Under the same specific weight and panel aspect ratio, a sandwich panel with metal matrix composite face sheets has much higher buckling strength than one having monolithic face sheets.

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

Imaging bolometer

DOEpatents

Wurden, G.A.

1999-01-19

Radiation-hard, steady-state imaging bolometer is disclosed. A bolometer employing infrared (IR) imaging of a segmented-matrix absorber of plasma radiation in a cooled-pinhole camera geometry is described. The bolometer design parameters are determined by modeling the temperature of the foils from which the absorbing matrix is fabricated by using a two-dimensional time-dependent solution of the heat conduction equation. The resulting design will give a steady-state bolometry capability, with approximately 100 Hz time resolution, while simultaneously providing hundreds of channels of spatial information. No wiring harnesses will be required, as the temperature-rise data will be measured via an IR camera. The resulting spatial data may be used to tomographically investigate the profile of plasmas. 2 figs.

Imaging bolometer

DOEpatents

Wurden, Glen A.

1999-01-01

Radiation-hard, steady-state imaging bolometer. A bolometer employing infrared (IR) imaging of a segmented-matrix absorber of plasma radiation in a cooled-pinhole camera geometry is described. The bolometer design parameters are determined by modeling the temperature of the foils from which the absorbing matrix is fabricated by using a two-dimensional time-dependent solution of the heat conduction equation. The resulting design will give a steady-state bolometry capability, with approximately 100 Hz time resolution, while simultaneously providing hundreds of channels of spatial information. No wiring harnesses will be required, as the temperature-rise data will be measured via an IR camera. The resulting spatial data may be used to tomographically investigate the profile of plasmas.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatially weighted mutual information image registration for image guided radiation therapy.

PubMed

Park, Samuel B; Rhee, Frank C; Monroe, James I; Sohn, Jason W

2010-09-01

To develop a new metric for image registration that incorporates the (sub)pixelwise differential importance along spatial location and to demonstrate its application for image guided radiation therapy (IGRT). It is well known that rigid-body image registration with mutual information is dependent on the size and location of the image subset on which the alignment analysis is based [the designated region of interest (ROI)]. Therefore, careful review and manual adjustments of the resulting registration are frequently necessary. Although there were some investigations of weighted mutual information (WMI), these efforts could not apply the differential importance to a particular spatial location since WMI only applies the weight to the joint histogram space. The authors developed the spatially weighted mutual information (SWMI) metric by incorporating an adaptable weight function with spatial localization into mutual information. SWMI enables the user to apply the selected transform to medically "important" areas such as tumors and critical structures, so SWMI is neither dominated by, nor neglects the neighboring structures. Since SWMI can be utilized with any weight function form, the authors presented two examples of weight functions for IGRT application: A Gaussian-shaped weight function (GW) applied to a user-defined location and a structures-of-interest (SOI) based weight function. An image registration example using a synthesized 2D image is presented to illustrate the efficacy of SWMI. The convergence and feasibility of the registration method as applied to clinical imaging is illustrated by fusing a prostate treatment planning CT with a clinical cone beam CT (CBCT) image set acquired for patient alignment. Forty-one trials are run to test the speed of convergence. The authors also applied SWMI registration using two types of weight functions to two head and neck cases and a prostate case with clinically acquired CBCT/ MVCT image sets. The SWMI registration with a Gaussian weight function (SWMI-GW) was tested between two different imaging modalities: CT and MRI image sets. SWMI-GW converges 10% faster than registration using mutual information with an ROI. SWMI-GW as well as SWMI with SOI-based weight function (SWMI-SOI) shows better compensation of the target organ's deformation and neighboring critical organs' deformation. SWMI-GW was also used to successfully fuse MRI and CT images. Rigid-body image registration using our SWMI-GW and SWMI-SOI as cost functions can achieve better registration results in (a) designated image region(s) as well as faster convergence. With the theoretical foundation established, we believe SWMI could be extended to larger clinical testing.

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Staring 2-D hadamard transform spectral imager

DOEpatents

Gentry, Stephen M [Albuquerque, NM; Wehlburg, Christine M [Albuquerque, NM; Wehlburg, Joseph C [Albuquerque, NM; Smith, Mark W [Albuquerque, NM; Smith, Jody L [Albuquerque, NM

2006-02-07

A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.

[Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China.

PubMed

Liu, Yuan Yuan; Liu, Xue Lu

2016-04-22

Based on "patch-corridor-matrix" pattern, spatial scale effect of landscape pattern was studied in Yongdeng County of Lanzhou City, Gansu Province, China. The results showed that the grassland was the matrix of landscape structure in the studied area, road and river played the corridor role, and the other landscape elements (cultivated land, forest land, garden land, residential land, industrial and mineral land, public management and service land, and the other land) acted as patches. The patch level index and the landscape level index all showed obvious dependence on spatial extent. The scale effect of patch index of different landscape elements existed differently in different extent intervals, so did the scale effect of the landscape level index. Within the extent of 1-20 km, the scale effect showed the most obvious difference between the element types and the index types, while it became smaller in 21-90 km, and disappeared beyond 90 km. 90 km×90 km might be the effective extent to study the dependence of spatial extent of landscape structure.

Context-aware and locality-constrained coding for image categorization.

PubMed

Xiao, Wenhua; Wang, Bin; Liu, Yu; Bao, Weidong; Zhang, Maojun

2014-01-01

Improving the coding strategy for BOF (Bag-of-Features) based feature design has drawn increasing attention in recent image categorization works. However, the ambiguity in coding procedure still impedes its further development. In this paper, we introduce a context-aware and locality-constrained Coding (CALC) approach with context information for describing objects in a discriminative way. It is generally achieved by learning a word-to-word cooccurrence prior to imposing context information over locality-constrained coding. Firstly, the local context of each category is evaluated by learning a word-to-word cooccurrence matrix representing the spatial distribution of local features in neighbor region. Then, the learned cooccurrence matrix is used for measuring the context distance between local features and code words. Finally, a coding strategy simultaneously considers locality in feature space and context space, while introducing the weight of feature is proposed. This novel coding strategy not only semantically preserves the information in coding, but also has the ability to alleviate the noise distortion of each class. Extensive experiments on several available datasets (Scene-15, Caltech101, and Caltech256) are conducted to validate the superiority of our algorithm by comparing it with baselines and recent published methods. Experimental results show that our method significantly improves the performance of baselines and achieves comparable and even better performance with the state of the arts.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

On using smoothing spline and residual correction to fuse rain gauge observations and remote sensing data

NASA Astrophysics Data System (ADS)

Huang, Chengcheng; Zheng, Xiaogu; Tait, Andrew; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Li, Tao; Wang, Zhonglei

2014-01-01

Partial thin-plate smoothing spline model is used to construct the trend surface.Correction of the spline estimated trend surface is often necessary in practice.Cressman weight is modified and applied in residual correction.The modified Cressman weight performs better than Cressman weight.A method for estimating the error covariance matrix of gridded field is provided.

A feedforward artificial neural network based on quantum effect vector-matrix multipliers.

PubMed

Levy, H J; McGill, T C

1993-01-01

The vector-matrix multiplier is the engine of many artificial neural network implementations because it can simulate the way in which neurons collect weighted input signals from a dendritic arbor. A new technology for building analog weighting elements that is theoretically capable of densities and speeds far beyond anything that conventional VLSI in silicon could ever offer is presented. To illustrate the feasibility of such a technology, a small three-layer feedforward prototype network with five binary neurons and six tri-state synapses was built and used to perform all of the fundamental logic functions: XOR, AND, OR, and NOT.

Replacement of MDA with more oxidatively stable diamines in PMR-polyimides

NASA Technical Reports Server (NTRS)

Alston, W. B.

1985-01-01

Studies are performed to investigate the effect of substituting 4,4'-oxydianiline and 1,1-bis(4-aminophenyl)-1-phenyl-2,2,2-trifluoroethane for the 4,4'-methylenedianiline in PMR polyimide matrix resin. Graphite fiber reinforced composites are fabricated from unsized Celion 6000 and PMR-polyimide matrix resins having formulated molecular weights in the range of 1500 to 2400. The composite processing characteristics are investigated and the initial room temperature and 316 C (600 F) composite mechanical properties are determined. Comparative 316 C composite weight losses and 316 C mechanical properties retention after prolonged 316 C air exposure are also determined.

A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; Pepijn Veefkind, J.; de Graaf, Martin; Sneep, Maarten; Stammes, Piet; de Haan, Johan F.; Sanders, Abram F. J.; Apituley, Arnoud; Tuinder, Olaf; Levelt, Pieternel F.

2018-06-01

This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758-770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe.

Effect of landscape matrix type on nesting ecology of the Northern Cardinal

Treesearch

R.A. Sargent; J.C. Kilgo; B.R. Chapman; K.V. Miller

2015-01-01

Spatial distribution of forests relative to other habitats in a landscape may influence nest success of songbirds. For example, nest predation in mature forests increases as the percentage of clear-cut land in the surrounding matrix increases (Yahner and Scott 1988). Blake and Karr (1987) noted that birds breeding in forest fragments may incorporate adjacent habitats,...

Unifying research on the fragmentation of terrestrial and aquatic habitats: patches, connectivity and the matrix in riverscapes

USGS Publications Warehouse

Eros, Tibor; Grant, Evan H. Campbell

2015-01-01

Fragmentation of habitats is a critical issue in the conservation and management of stream networks across spatial scales. Although the effects of individual barriers (e.g. dams) are well documented, we argue that a more comprehensive patch–matrix landscape model will improve our understanding of fragmentation effects and improve management in riverscapes.

Magnetic resonance microscopy for assessment of morphological changes in hydrating hydroxypropylmethyl cellulose matrix tablets in situ.

PubMed

Kulinowski, Piotr; Młynarczyk, Anna; Dorożyński, Przemysław; Jasiński, Krzysztof; Gruwel, Marco L H; Tomanek, Bogusław; Węglarz, Władysław P

2012-12-01

To resolve contradictions found in morphology of hydrating hydroxypropylmethyl cellulose (HPMC) matrix as studied using Magnetic Resonance Imaging (MRI) techniques. Until now, two approaches were used in the literature: either two or three regions that differ in physicochemical properties were identified. Multiparametric, spatially and temporally resolved T(2) MR relaxometry in situ was applied to study the hydration progress in HPMC matrix tablets using a 11.7 T MRI system. Two spin-echo based pulse sequences-one of them designed to specifically study short T(2) signals-were used. Two components in the T(2) decay envelope were estimated and spatial distributions of their parameters, i.e. amplitudes and T(2) values, were obtained. Based on the data, five different regions and their temporal evolution were identified: dry glassy, hydrated solid like, two interface layers and gel layer. The regions were found to be separated by four evolving fronts identified as penetration, full hydration, total gelification and apparent erosion. The MRI results showed morphological details of the hydrating HPMC matrices matching compound theoretical models. The proposed method will allow for adequate evaluation of controlled release polymeric matrix systems loaded with drug substances of different solubility.

The cost of space independence in P300-BCI spellers.

PubMed

Chennu, Srivas; Alsufyani, Abdulmajeed; Filetti, Marco; Owen, Adrian M; Bowman, Howard

2013-07-29

Though non-invasive EEG-based Brain Computer Interfaces (BCI) have been researched extensively over the last two decades, most designs require control of spatial attention and/or gaze on the part of the user. In healthy adults, we compared the offline performance of a space-independent P300-based BCI for spelling words using Rapid Serial Visual Presentation (RSVP), to the well-known space-dependent Matrix P300 speller. EEG classifiability with the RSVP speller was as good as with the Matrix speller. While the Matrix speller's performance was significantly reliant on early, gaze-dependent Visual Evoked Potentials (VEPs), the RSVP speller depended only on the space-independent P300b. However, there was a cost to true spatial independence: the RSVP speller was less efficient in terms of spelling speed. The advantage of space independence in the RSVP speller was concomitant with a marked reduction in spelling efficiency. Nevertheless, with key improvements to the RSVP design, truly space-independent BCIs could approach efficiencies on par with the Matrix speller. With sufficiently high letter spelling rates fused with predictive language modelling, they would be viable for potential applications with patients unable to direct overt visual gaze or covert attentional focus.

Protein addressing on patterned microchip by coupling chitosan electrodeposition and 'electro-click' chemistry.

PubMed

Shi, Xiao-Wen; Qiu, Ling; Nie, Zhen; Xiao, Ling; Payne, Gregory F; Du, Yumin

2013-12-01

Many applications in proteomics and lab-on-chip analysis require methods that guide proteins to assemble at surfaces with high spatial and temporal control. Electrical inputs are particularly convenient to control, and there has been considerable effort to discover simple and generic mechanisms that allow electrical inputs to trigger protein assembly on-demand. Here, we report the electroaddressing of a protein to a patterned surface by coupling two generic electroaddressing mechanisms. First, we electrodeposit the stimuli-responsive film-forming aminopolysaccharide chitosan to form a hydrogel matrix at the electrode surface. After deposition, the matrix is chemically functionalized with alkyne groups. Second, we ''electro-click' an azide-tagged protein to the functionalized matrix using electrical signals to trigger conjugation by Huisgen 1,3-dipolar cycloadditions. Specifically, a cathodic potential is applied to the matrix-coated electrode to reduce Cu(II) to Cu(I) which is required for the click reaction. Using fluorescently-labeled bovine serum albumin as our model, we demonstrate that protein conjugation can be controlled spatially and temporally. We anticipate that the coupling of polysaccharide electrodeposition and electro-click chemistry will provide a simple and generic approach to electroaddress proteins within compatible hydrogel matrices.

ASTM and VAMAS activities in titanium matrix composites test methods development

NASA Technical Reports Server (NTRS)

Johnson, W. S.; Harmon, D. M.; Bartolotta, P. A.; Russ, S. M.

1994-01-01

Titanium matrix composites (TMC's) are being considered for a number of aerospace applications ranging from high performance engine components to airframe structures in areas that require high stiffness to weight ratios at temperatures up to 400 C. TMC's exhibit unique mechanical behavior due to fiber-matrix interface failures, matrix cracks bridged by fibers, thermo-viscoplastic behavior of the matrix at elevated temperatures, and the development of significant thermal residual stresses in the composite due to fabrication. Standard testing methodology must be developed to reflect the uniqueness of this type of material systems. The purpose of this paper is to review the current activities in ASTM and Versailles Project on Advanced Materials and Standards (VAMAS) that are directed toward the development of standard test methodology for titanium matrix composites.

Studies on Relaxation Behavior of Corona Poled Aromatic Dipolar Molecules in a Polymer Matrix

DTIC Science & Technology

1990-08-03

concentration upto 30 weight percent. Orientation As expected optically responsive molecules are randomly oriented in the polymer matrix although a small amount...INSERT Figure 4 The retention of SH intensity of the small molecule such as MNA was found to be very poor in the PMMA matrix while the larger rodlike...Polym. Prepr. Am. Chem. Soc., Div. Polym. Chem. 24(2), 309 (1983). 16.- H. Ringsdorf and H. W. Schmidt. Makromol. Chem. 185, 1327 (1984). 17. S. Musikant

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.

One-Piece Leak-Proof Battery

DOEpatents

Verhoog, Roelof

1999-03-23

The casing of a leak-proof one-piece battery is made of a material comprising a mixture of at least a matrix based on polypropylene and an alloy of a polyamide and a polypropylene. The ratio of the matrix to the alloy is in the range 0.5 to 6 by weight. The alloy forms elongate arborescent inclusions in the matrix such that, on average, the largest dimension of a segment of the arborescence is at least twenty times the smallest dimension of the segment.

Second level semi-degenerate fields in W_3 Toda theory: matrix element and differential equation

NASA Astrophysics Data System (ADS)

Belavin, Vladimir; Cao, Xiangyu; Estienne, Benoit; Santachiara, Raoul

2017-03-01

In a recent study we considered W_3 Toda 4-point functions that involve matrix elements of a primary field with the highest-weight in the adjoint representation of sl_3 . We generalize this result by considering a semi-degenerate primary field, which has one null vector at level two. We obtain a sixth-order Fuchsian differential equation for the conformal blocks. We discuss the presence of multiplicities, the matrix elements and the fusion rules.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Predicting neo-adjuvant chemotherapy response and progression-free survival of locally advanced breast cancer using textural features of intratumoral heterogeneity on F-18 FDG PET/CT and diffusion-weighted MR imaging.

PubMed

Yoon, Hai-Jeon; Kim, Yemi; Chung, Jin; Kim, Bom Sahn

2018-03-30

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence. © 2018 Wiley Periodicals, Inc.

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

PubMed

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

2015-11-07

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

Tularosa Basin Play Fairway: Weights of Evidence Models

DOE Data Explorer

Adam Brandt

2015-12-01

These models are related to weights of evidence play fairway anlaysis of the Tularosa Basin, New Mexico and Texas. They were created through Spatial Data Modeler: ArcMAP 9.3 geoprocessing tools for spatial data modeling using weights of evidence, logistic regression, fuzzy logic and neural networks. It used to identify high values for potential geothermal plays and low values. The results are relative not only within the Tularosa Basin, but also throughout New Mexico, Utah, Nevada, and other places where high to moderate enthalpy geothermal systems are present (training sites).

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

Distribution Analysis of Anthocyanins, Sugars, and Organic Acids in Strawberry Fruits Using Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry.

PubMed

Enomoto, Hirofumi; Sato, Kei; Miyamoto, Koji; Ohtsuka, Akira; Yamane, Hisakazu

2018-05-16

Anthocyanins, sugars, and organic acids contribute to the appearance, health benefits, and taste of strawberries. However, their spatial distribution in the ripe fruit has been fully unrevealed. Therefore, we performed matrix-assisted laser desorption/ionization, MALDI-IMS, analysis to investigate their spatial distribution in ripe strawberries. The detection sensitivity was improved by using the TM-Sprayer for matrix application. In the receptacle, pelargonidins were distributed in the skin, cortical, and pith tissues, whereas cyanidins and delphinidins were slightly localized in the skin. In the achene, mainly cyanidins were localized in the outside of the skin. Citric acid was mainly distributed in the upper and bottom side of cortical tissue. Although hexose was distributed almost equally throughout the fruits, sucrose was mainly distributed in the upper side of cortical and pith tissues. These results suggest that using the TM-Sprayer in MALDI-IMS was useful for microscopic distribution analysis of anthocyanins, sugars, and organic acids in strawberries.

Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.

PubMed

Sukop, Michael C; Cunningham, Kevin J

2016-03-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.

Three dimensional time reversal optical tomography

NASA Astrophysics Data System (ADS)

Wu, Binlin; Cai, W.; Alrubaiee, M.; Xu, M.; Gayen, S. K.

2011-03-01

Time reversal optical tomography (TROT) approach is used to detect and locate absorptive targets embedded in a highly scattering turbid medium to assess its potential in breast cancer detection. TROT experimental arrangement uses multi-source probing and multi-detector signal acquisition and Multiple-Signal-Classification (MUSIC) algorithm for target location retrieval. Light transport from multiple sources through the intervening medium with embedded targets to the detectors is represented by a response matrix constructed using experimental data. A TR matrix is formed by multiplying the response matrix by its transpose. The eigenvectors with leading non-zero eigenvalues of the TR matrix correspond to embedded objects. The approach was used to: (a) obtain the location and spatial resolution of an absorptive target as a function of its axial position between the source and detector planes; and (b) study variation in spatial resolution of two targets at the same axial position but different lateral positions. The target(s) were glass sphere(s) of diameter ~9 mm filled with ink (absorber) embedded in a 60 mm-thick slab of Intralipid-20% suspension in water with an absorption coefficient μa ~ 0.003 mm-1 and a transport mean free path lt ~ 1 mm at 790 nm, which emulate the average values of those parameters for human breast tissue. The spatial resolution and accuracy of target location depended on axial position, and target contrast relative to the background. Both the targets could be resolved and located even when they were only 4-mm apart. The TROT approach is fast, accurate, and has the potential to be useful in breast cancer detection and localization.

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.

Polyhedral oligomeric silsesquioxane grafted polymer in polymeric foam

DOEpatents

King, Bruce A.; Patankar, Kshitish A.; Costeux, Stephane; Jeon, Hyun K.

2017-01-17

A polymeric foam article with a polymer matrix defining multiple cells therein has a polymer component with a first polymer that is a polyhedral oligomeric silsesquioxane grafted polymer that has a weight-average molecular weight of two kilograms per mole or higher and 200 kilograms per mole or lower.

NASA Astrophysics Data System (ADS)

2017-10-01

Different possible selections of the weighting matrices W1 and W2 will lead to different methods of subspace identification. In this study, the robust combined algorithm proposed by Van Overschee and De Moor [24] has been employed. In this algorithm, the weighting matrixes are chosen to be W1 = I and W2 =ΠUf⊥.

Spatial orientation of the vestibular system

NASA Technical Reports Server (NTRS)

Raphan, T.; Dai, M.; Cohen, B.

1992-01-01

1. A simplified three-dimensional state space model of visual vestibular interaction was formulated. Matrix and dynamical system operators representing coupling from the semicircular canals and the visual system to the velocity storage integrator were incorporated into the model. 2. It was postulated that the system matrix for a tilted position was a composition of two linear transformations of the system matrix for the upright position. One transformation modifies the eigenvalues of the system matrix while another rotates the pitch and roll eigenvectors with the head, while maintaining the yaw axis eigenvector approximately spatially invariant. Using this representation, the response characteristics of the pitch, roll, and yaw eye velocity were obtained in terms of the eigenvalues and associated eigenvectors. 3. Using OKAN data obtained from monkeys and comparing to the model predictions, the eigenvalues and eigenvectors of the system matrix were identified as a function of tilt to the side or of tilt to the prone positions, using a modification of the Marquardt algorithm. The yaw eigenvector for right-side-down tilt and for downward pitch cross-coupling was approximately 30 degrees from the spatial vertical. For the prone position, the eigenvector was computed to be approximately 20 degrees relative to the spatial vertical. For both side-down and prone positions, oblique OKN induced along eigenvector directions generated OKAN which decayed to zero along a straight line with approximately a single time constant. This was verified by a spectral analysis of the residual sequence about the straight line fit to the decaying data. The residual sequence was associated with a narrow autocorrelation function and a wide power spectrum. 4. Parameters found using the Marquardt algorithm were incorporated into the model. Diagonal matrices in a head coordinate frame were introduced to represent the direct pathway and the coupling of the visual system to the integrator. Model simulations predicted the behavior of yaw and pitch OKN and OKAN when the animal was upright, as well as the cross-coupling in the tilted position. The trajectories in velocity space were also accurately simulated. 5. There were similarities between the monkey eigenvectors and human perception of the spatial vertical. For side-down tilts and downward eye velocity cross-coupling, there was only an Aubert (A) effect. For upward eye velocity cross-coupling there were both Muller (E) and Aubert (A) effects. The mean of the eigenvectors for upward and downward eye velocities overlay human 1 x g perceptual data.(ABSTRACT TRUNCATED AT 400 WORDS).

Targeted Multiplex Imaging Mass Spectrometry in Transmission Geometry for Subcellular Spatial Resolution

PubMed Central

Lavenant, Gwendoline Thiery; Zavalin, Andrey I.; Caprioli, Richard M.

2013-01-01

Targeted multiplex Imaging Mass Spectrometry utilizes several different antigen-specific primary antibodies, each directly labeled with a unique photocleavable mass tag, to detect multiple antigens in a single tissue section. Each photocleavable mass tag bound to an antibody has a unique molecular weight and can be readily ionized by laser desorption ionization mass spectrometry. This manuscript describes a mass spectrometry method that allows imaging of targeted single cells within tissue using transmission geometry laser desorption ionization mass spectrometry. Transmission geometry focuses the laser beam on the back side of the tissue placed on a glass slide, providing a 2 μm diameter laser spot irradiating the biological specimen. This matrix-free method enables simultaneous localization at the sub-cellular level of multiple antigens using specific tagged antibodies. We have used this technology to visualize the co-expression of synaptophysin and two major hormones peptides, insulin and somatostatin, in duplex assays in beta and delta cells contained in a human pancreatic islet. PMID:23397138

[An improved low spectral distortion PCA fusion method].

PubMed

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

Oxidation Behavior of Carbon Fiber-Reinforced Composites

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.

2008-01-01

OXIMAP is a numerical (FEA-based) solution tool capable of calculating the carbon fiber and fiber coating oxidation patterns within any arbitrarily shaped carbon silicon carbide composite structure as a function of time, temperature, and the environmental oxygen partial pressure. The mathematical formulation is derived from the mechanics of the flow of ideal gases through a chemically reacting, porous solid. The result of the formulation is a set of two coupled, non-linear differential equations written in terms of the oxidant and oxide partial pressures. The differential equations are solved simultaneously to obtain the partial vapor pressures of the oxidant and oxides as a function of the spatial location and time. The local rate of carbon oxidation is determined at each time step using the map of the local oxidant partial vapor pressure along with the Arrhenius rate equation. The non-linear differential equations are cast into matrix equations by applying the Bubnov-Galerkin weighted residual finite element method, allowing for the solution of the differential equations numerically.

Targeted Multiplex Imaging Mass Spectrometry in Transmission Geometry for Subcellular Spatial Resolution

NASA Astrophysics Data System (ADS)

Thiery-Lavenant, Gwendoline; Zavalin, Andre I.; Caprioli, Richard M.

2013-04-01

Targeted multiplex imaging mass spectrometry utilizes several different antigen-specific primary antibodies, each directly labeled with a unique photocleavable mass tag, to detect multiple antigens in a single tissue section. Each photocleavable mass tag bound to an antibody has a unique molecular weight and can be readily ionized by laser desorption ionization mass spectrometry. This article describes a mass spectrometry method that allows imaging of targeted single cells within tissue using transmission geometry laser desorption ionization mass spectrometry. Transmission geometry focuses the laser beam on the back side of the tissue placed on a glass slide, providing a 2 μm diameter laser spot irradiating the biological specimen. This matrix-free method enables simultaneous localization at the sub-cellular level of multiple antigens using specific tagged antibodies. We have used this technology to visualize the co-expression of synaptophysin and two major hormones peptides, insulin and somatostatin, in duplex assays in beta and delta cells contained in a human pancreatic islet.

Effect of Coconut, Sisal and Jute Fibers on the Properties of Starch/Gluten/Glycerol Matrix

USDA-ARS?s Scientific Manuscript database

Coconut, sisal and jute fibers were added as reinforcement materials in a biodegradable polymer matrix comprised of starch/gluten/glycerol. The content of fibers used in the composites varied from 5% to 30% by weight of the total polymers (starch and gluten). Materials were processed in a Haake torq...

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Sex differences in the weighting of metric and categorical information in spatial location memory.

PubMed

Holden, Mark P; Duff-Canning, Sarah J; Hampson, Elizabeth

2015-01-01

According to the Category Adjustment model, remembering a spatial location involves the Bayesian combination of fine-grained and categorical information about that location, with each cue weighted by its relative certainty. However, individuals may differ in terms of their certainty about each cue, resulting in estimates that rely more or less on metric or categorical representations. To date, though, very little research has examined individual differences in the relative weighting of these cues in spatial location memory. Here, we address this gap in the literature. Participants were asked to recall point locations in uniform geometric shapes and in photographs of complex, natural scenes. Error patterns were analyzed for evidence of a sex difference in the relative use of metric and categorical information. As predicted, women placed relatively more emphasis on categorical cues, while men relied more heavily on metric information. Location reproduction tasks showed a similar effect, implying that the sex difference arises early in spatial processing, possibly during encoding.

A spatially constrained ecological classification: rationale, methodology and implementation

Treesearch

Franz Mora; Louis Iverson; Louis Iverson

2002-01-01

The theory, methodology and implementation for an ecological and spatially constrained classification are presented. Ecological and spatial relationships among several landscape variables are analyzed in order to define a new approach for a landscape classification. Using ecological and geostatistical analyses, several ecological and spatial weights are derived to...

Evaluation of Goal Programming for the Optimal Assignment of Inspectors to Construction Projects

DTIC Science & Technology

1988-09-01

Inputs ..... .............. 90 Equation Coefficients . ....... .. 90 Weights, Priorities and the AHP . . 91 Right-Hand Side Values ........ .. 91...the AHP Hierarchy with k Levels . . 36 3. Sample Matrix for Pairwise Comparison ........ .. 37 4. Assignment of I and p for Example Problem...Weights for Example Problem ... 61 3. AHP Weights and Coefficient ci, Values. ........ 63 vii AFIT/GEM/LSM/88S-16 Abstract The purpose of this study was

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

Some optimal considerations in attitude control systems. [evaluation of value of relative weighting between time and fuel for relay control law

NASA Technical Reports Server (NTRS)

Boland, J. S., III

1973-01-01

The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.

Eigenvectors of optimal color spectra.

PubMed

Flinkman, Mika; Laamanen, Hannu; Tuomela, Jukka; Vahimaa, Pasi; Hauta-Kasari, Markku

2013-09-01

Principal component analysis (PCA) and weighted PCA were applied to spectra of optimal colors belonging to the outer surface of the object-color solid or to so-called MacAdam limits. The correlation matrix formed from this data is a circulant matrix whose biggest eigenvalue is simple and the corresponding eigenvector is constant. All other eigenvalues are double, and the eigenvectors can be expressed with trigonometric functions. Found trigonometric functions can be used as a general basis to reconstruct all possible smooth reflectance spectra. When the spectral data are weighted with an appropriate weight function, the essential part of the color information is compressed to the first three components and the shapes of the first three eigenvectors correspond to one achromatic response function and to two chromatic response functions, the latter corresponding approximately to Munsell opponent-hue directions 9YR-9B and 2BG-2R.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

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

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

3-dimensional magnetotelluric inversion including topography using deformed hexahedral edge finite elements and direct solvers parallelized on symmetric multiprocessor computers - Part II: direct data-space inverse solution

NASA Astrophysics Data System (ADS)

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

2016-01-01

Following the creation described in Part I of a deformable edge finite-element simulator for 3-D magnetotelluric (MT) responses using direct solvers, in Part II we develop an algorithm named HexMT for 3-D regularized inversion of MT data including topography. Direct solvers parallelized on large-RAM, symmetric multiprocessor (SMP) workstations are used also for the Gauss-Newton model update. By exploiting the data-space approach, the computational cost of the model update becomes much less in both time and computer memory than the cost of the forward simulation. In order to regularize using the second norm of the gradient, we factor the matrix related to the regularization term and apply its inverse to the Jacobian, which is done using the MKL PARDISO library. For dense matrix multiplication and factorization related to the model update, we use the PLASMA library which shows very good scalability across processor cores. A synthetic test inversion using a simple hill model shows that including topography can be important; in this case depression of the electric field by the hill can cause false conductors at depth or mask the presence of resistive structure. With a simple model of two buried bricks, a uniform spatial weighting for the norm of model smoothing recovered more accurate locations for the tomographic images compared to weightings which were a function of parameter Jacobians. We implement joint inversion for static distortion matrices tested using the Dublin secret model 2, for which we are able to reduce nRMS to ˜1.1 while avoiding oscillatory convergence. Finally we test the code on field data by inverting full impedance and tipper MT responses collected around Mount St Helens in the Cascade volcanic chain. Among several prominent structures, the north-south trending, eruption-controlling shear zone is clearly imaged in the inversion.

A weighted adjustment of a similarity transformation between two point sets containing errors

NASA Astrophysics Data System (ADS)

Marx, C.

2017-10-01

For an adjustment of a similarity transformation, it is often appropriate to consider that both the source and the target coordinates of the transformation are affected by errors. For the least squares adjustment of this problem, a direct solution is possible in the cases of specific-weighing schemas of the coordinates. Such a problem is considered in the present contribution and a direct solution is generally derived for the m-dimensional space. The applied weighing schema allows (fully populated) point-wise weight matrices for the source and target coordinates, both weight matrices have to be proportional to each other. Additionally, the solutions of two borderline cases of this weighting schema are derived, which only consider errors in the source or target coordinates. The investigated solution of the rotation matrix of the adjustment is independent of the scaling between the weight matrices of the source and the target coordinates. The mentioned borderline cases, therefore, have the same solution of the rotation matrix. The direct solution method is successfully tested on an example of a 3D similarity transformation using a comparison with an iterative solution based on the Gauß-Helmert model.

Efficient Computation Of Manipulator Inertia Matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1991-01-01

Improved method for computation of manipulator inertia matrix developed, based on concept of spatial inertia of composite rigid body. Required for implementation of advanced dynamic-control schemes as well as dynamic simulation of manipulator motion. Motivated by increasing demand for fast algorithms to provide real-time control and simulation capability and, particularly, need for faster-than-real-time simulation capability, required in many anticipated space teleoperation applications.

The nuclear matrix prepared by amine modification

PubMed Central

Wan, Katherine M.; Nickerson, Jeffrey A.; Krockmalnic, Gabriela; Penman, Sheldon

1999-01-01

The nucleus is spatially ordered by attachments to a nonchromatin nuclear structure, the nuclear matrix. The nuclear matrix and chromatin are intimately connected and integrated structures, and so a major technical challenge in nuclear matrix research has been to remove chromatin while retaining a native nuclear matrix. Most methods for removing chromatin require first a nuclease digestion and then a salt extraction to remove cut chromatin. We have hypothesized that cut chromatin is held in place by charge interactions involving nucleosomal amino groups. We have tested this hypothesis by chemically modifying amino groups after nuclease digestion. By using this protocol, chromatin could be effectively removed at physiological ionic strength. We compared the ultrastructure and composition of this nuclear matrix preparation with the traditional high-salt nuclear matrix and with the third nuclear matrix preparation that we have developed from which chromatin is removed after extensive crosslinking. All three matrix preparations reveal internal nuclear matrix structures that are built on a network of branched filaments of about 10 nm diameter. That such different chromatin-removal protocols reveal similar principles of nuclear matrix construction increases our confidence that we are observing important architectural elements of the native structure in the living cell. PMID:9927671

Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models.

PubMed

Li, Lianfa; Laurent, Olivier; Wu, Jun

2016-02-05

Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced exposure or higher socioeconomic status with lower vulnerability. Our Bayesian models effectively combined a priori knowledge with training data to infer the posterior association of air pollution with term birth weight and to evaluate the influence of the tract-level factors on spatial variability of such association. This study contributes new findings about non-linear influences of socio-demographic factors, land-use patterns, and unaccounted exposures on spatial variability of the effects of air pollution.

From nano- to macro-scale: nanotechnology approaches for spatially controlled delivery of bioactive factors for bone and cartilage engineering.

PubMed

Santo, Vítor E; Gomes, Manuela E; Mano, João F; Reis, Rui L

2012-07-01

The field of biomaterials has advanced towards the molecular and nanoscale design of bioactive systems for tissue engineering, regenerative medicine and drug delivery. Spatial cues are displayed in the 3D extracellular matrix and can include signaling gradients, such as those observed during chemotaxis. Architectures range from the nanometer to the centimeter length scales as exemplified by extracellular matrix fibers, cells and macroscopic shapes. The main focus of this review is the application of a biomimetic approach by the combination of architectural cues, obtained through the application of micro- and nanofabrication techniques, with the ability to sequester and release growth factors and other bioactive agents in a spatiotemporal controlled manner for bone and cartilage engineering.

Dynamics of fractional condensation of a substance on a probe for spectral analysis

NASA Astrophysics Data System (ADS)

Zakharov, Yu. A.; Kokorina, O. B.; Lysogorskiĭ, Yu. V.; Sevastianov, A. A.

2008-11-01

The fractional separation of trace metals on a cold tungsten probe from salt matrix vapor, which interferes with the spectral analysis, is studied. The spatial structure of the vapor flows of sodium chloride, potassium sulfate, and indium atoms is visualized at characteristic wavelengths as they interact with the probe. The vapor flow rate and the probe orientation were varied. It is found that the smoke of the matrix does not prevent the deposition of the metal on the probe because of spatial separation of these fractions and that the detrimental effect of thermal gas expansion and other factors is eliminated. The sensitivity of the atomic absorption analysis of indium impurities in these salts is increased by an order of magnitude.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Vertices cannot be hidden from quantum spatial search for almost all random graphs

NASA Astrophysics Data System (ADS)

Glos, Adam; Krawiec, Aleksandra; Kukulski, Ryszard; Puchała, Zbigniew

2018-04-01

In this paper, we show that all nodes can be found optimally for almost all random Erdős-Rényi G(n,p) graphs using continuous-time quantum spatial search procedure. This works for both adjacency and Laplacian matrices, though under different conditions. The first one requires p=ω (log ^8(n)/n), while the second requires p≥ (1+ɛ )log (n)/n, where ɛ >0. The proof was made by analyzing the convergence of eigenvectors corresponding to outlying eigenvalues in the \\Vert \\cdot \\Vert _∞ norm. At the same time for p<(1-ɛ )log (n)/n, the property does not hold for any matrix, due to the connectivity issues. Hence, our derivation concerning Laplacian matrix is tight.

Expanding (3+1)-dimensional universe from a lorentzian matrix model for superstring theory in (9+1) dimensions.

PubMed

Kim, Sang-Woo; Nishimura, Jun; Tsuchiya, Asato

2012-01-06

We reconsider the matrix model formulation of type IIB superstring theory in (9+1)-dimensional space-time. Unlike the previous works in which the Wick rotation was used to make the model well defined, we regularize the Lorentzian model by introducing infrared cutoffs in both the spatial and temporal directions. Monte Carlo studies reveal that the two cutoffs can be removed in the large-N limit and that the theory thus obtained has no parameters other than one scale parameter. Moreover, we find that three out of nine spatial directions start to expand at some "critical time," after which the space has SO(3) symmetry instead of SO(9).

WE-FG-207B-04: Noise Suppression for Energy-Resolved CT Via Variance Weighted Non-Local Filtration

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

Harms, J; Zhu, L

Purpose: The photon starvation problem is exacerbated in energy-resolved CT, since the detected photons are shared by multiple energy channels. Using pixel similarity-based non-local filtration, we aim to produce accurate and high-resolution energy-resolved CT images with significantly reduced noise. Methods: Averaging CT images reconstructed from different energy channels reduces noise at the price of losing spectral information, while conventional denoising techniques inevitably degrade image resolution. Inspired by the fact that CT images of the same object at different energies share the same structures, we aim to reduce noise of energy-resolved CT by averaging only pixels of similar materials - amore » non-local filtration technique. For each CT image, an empirical exponential model is used to calculate the material similarity between two pixels based on their CT values and the similarity values are organized in a matrix form. A final similarity matrix is generated by averaging these similarity matrices, with weights inversely proportional to the estimated total noise variance in the sinogram of different energy channels. Noise suppression is achieved for each energy channel via multiplying the image vector by the similarity matrix. Results: Multiple scans on a tabletop CT system are used to simulate 6-channel energy-resolved CT, with energies ranging from 75 to 125 kVp. On a low-dose acquisition at 15 mA of the Catphan©600 phantom, our method achieves the same image spatial resolution as a high-dose scan at 80 mA with a noise standard deviation (STD) lower by a factor of >2. Compared with another non-local noise suppression algorithm (ndiNLM), the proposed algorithms obtains images with substantially improved resolution at the same level of noise reduction. Conclusion: We propose a noise-suppression method for energy-resolved CT. Our method takes full advantage of the additional structural information provided by energy-resolved CT and preserves image values at each energy level. Research reported in this publication was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

Magnetic resonance microscopy for assessment of morphological changes in hydrating hydroxypropylmethylcellulose matrix tablets in situ-is it possible to detect phenomena related to drug dissolution within the hydrated matrices?

PubMed

Kulinowski, Piotr; Młynarczyk, Anna; Jasiński, Krzysztof; Talik, Przemysław; Gruwel, Marco L H; Tomanek, Bogusław; Węglarz, Władysław P; Dorożyński, Przemysław

2014-09-01

So far, the hydrated part of the HPMC matrix has commonly been denoted as a "gel" or "pseudogel" layer. No MRI-based results have been published regarding observation of internal phenomena related to drug dissolution inside swelling polymeric matrices during hydration. The purpose of the study was to detect such phenomena. Multiparametric, spatially and temporally resolved T2 MR relaxometry, in situ, was applied to study formation of the hydration progress in HPMC matrix tablets loaded with L-dopa and ketoprofen using a 11.7 T MRI system. Two spin-echo based pulse sequences were used, one of them specifically designed to study short T2 signals. Two components in the T2 decay envelope were estimated and spatial distributions of their parameters, i.e. amplitudes and T2 values, were obtained. Based on the data, different region formation patterns (i.e. multilayer structure) were registered depending on drug presence and solubility. Inside the matrix with incorporated sparingly soluble drug a specific layer formation due to drug dissolution was detected, whereas a matrix with very slightly soluble drug does not form distinct external "gel-like" layer. We have introduced a new paradigm in the characterization of hydrating matrices using (1)H MRI methods. It reflects molecular mobility and concentration of water inside the hydrated matrix. For the first time, drug dissolution related phenomena, i.e. particular front and region formation, were observed by MRI methods.

Minimizing the stochasticity of halos in large-scale structure surveys

NASA Astrophysics Data System (ADS)

Hamaus, Nico; Seljak, Uroš; Desjacques, Vincent; Smith, Robert E.; Baldauf, Tobias

2010-08-01

In recent work (Seljak, Hamaus, and Desjacques 2009) it was found that weighting central halo galaxies by halo mass can significantly suppress their stochasticity relative to the dark matter, well below the Poisson model expectation. This is useful for constraining relations between galaxies and the dark matter, such as the galaxy bias, especially in situations where sampling variance errors can be eliminated. In this paper we extend this study with the goal of finding the optimal mass-dependent halo weighting. We use N-body simulations to perform a general analysis of halo stochasticity and its dependence on halo mass. We investigate the stochasticity matrix, defined as Cij≡⟨(δi-biδm)(δj-bjδm)⟩, where δm is the dark matter overdensity in Fourier space, δi the halo overdensity of the i-th halo mass bin, and bi the corresponding halo bias. In contrast to the Poisson model predictions we detect nonvanishing correlations between different mass bins. We also find the diagonal terms to be sub-Poissonian for the highest-mass halos. The diagonalization of this matrix results in one large and one low eigenvalue, with the remaining eigenvalues close to the Poisson prediction 1/n¯, where n¯ is the mean halo number density. The eigenmode with the lowest eigenvalue contains most of the information and the corresponding eigenvector provides an optimal weighting function to minimize the stochasticity between halos and dark matter. We find this optimal weighting function to match linear mass weighting at high masses, while at the low-mass end the weights approach a constant whose value depends on the low-mass cut in the halo mass function. This weighting further suppresses the stochasticity as compared to the previously explored mass weighting. Finally, we employ the halo model to derive the stochasticity matrix and the scale-dependent bias from an analytical perspective. It is remarkably successful in reproducing our numerical results and predicts that the stochasticity between halos and the dark matter can be reduced further when going to halo masses lower than we can resolve in current simulations.

Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference.

PubMed

Xiao, Yangfan; Yi, Shanzhen; Tang, Zhongqian

2017-12-01

Flood is the most common natural hazard in the world and has caused serious loss of life and property. Assessment of flood prone areas is of great importance for watershed management and reduction of potential loss of life and property. In this study, a framework of multi-criteria analysis (MCA) incorporating geographic information system (GIS), fuzzy analytic hierarchy process (AHP) and spatial ordered weighted averaging (OWA) method was developed for flood hazard assessment. The factors associated with geographical, hydrological and flood-resistant characteristics of the basin were selected as evaluation criteria. The relative importance of the criteria was estimated through fuzzy AHP method. The OWA method was utilized to analyze the effects of different risk attitudes of the decision maker on the assessment result. The spatial ordered weighted averaging method with spatially variable risk preference was implemented in the GIS environment to integrate the criteria. The advantage of the proposed method is that it has considered spatial heterogeneity in assigning risk preference in the decision-making process. The presented methodology has been applied to the area including Hanyang, Caidian and Hannan of Wuhan, China, where flood events occur frequently. The outcome of flood hazard distribution presents a tendency of high risk towards populated and developed areas, especially the northeast part of Hanyang city, which has suffered frequent floods in history. The result indicates where the enhancement projects should be carried out first under the condition of limited resources. Finally, sensitivity of the criteria weights was analyzed to measure the stability of results with respect to the variation of the criteria weights. The flood hazard assessment method presented in this paper is adaptable for hazard assessment of a similar basin, which is of great significance to establish counterplan to mitigate life and property losses. Copyright © 2017 Elsevier B.V. All rights reserved.

Cascaded VLSI Chips Help Neural Network To Learn

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher; Thakoor, Anilkumar P.

1993-01-01

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Spatial variation in attributable risks.

PubMed

Congdon, Peter

2015-01-01

The attributable risk (AR) measures the contribution of a particular risk factor to a disease, and allows estimation of disease rates specific to that risk. While previous studies consider variability in ARs over demographic categories, this paper considers the extent of spatial variability in ARs estimated from multilevel data with confounders both at individual and geographic levels. A case study considers the AR for diabetes in relation to elevated BMI, and area rates for diabetes attributable to excess weight. Contextual adjustment includes known area variables, and unobserved spatially clustered influences, while spatial heterogeneity (effect modification) is considered in terms of varying effects of elevated BMI by neighbourhood deprivation category. The application is to patient register data in London, with clear evidence of spatial variation in ARs, and in small area diabetes rates attributable to excess weight. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial operator approach to flexible multibody system dynamics and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1991-01-01

The inverse and forward dynamics problems for flexible multibody systems were solved using the techniques of spatially recursive Kalman filtering and smoothing. These algorithms are easily developed using a set of identities associated with mass matrix factorization and inversion. These identities are easily derived using the spatial operator algebra developed by the author. Current work is aimed at computational experiments with the described algorithms and at modelling for control design of limber manipulator systems. It is also aimed at handling and manipulation of flexible objects.

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.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

A familiar pattern? Semantic memory contributes to the enhancement of visuo-spatial memories.

PubMed

Riby, Leigh M; Orme, Elizabeth

2013-03-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a change-detection paradigm; this was also associated with increased P300 and N400 components as well as a sustained negative slow wave (NSW). In contrast, processing of the low semantic stimuli was associated with an increased N200 and a reduction in the P300. These findings suggest that semantic content can aid in reducing early visual processing of information and subsequent memory load by unitizing complex patterns into familiar forms. The N400/NSW may be associated with the requirements for maintaining visuo-spatial information about semantic forms such as orientation and relative location. Evidence for individual differences in semantic elaboration strategies used by participants is also discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dutra, L. V.; Mascarenhas, N. D. A.; Mitsuo, Fernando Augusta, II

1984-01-01

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas.

Spectral-Spatial Shared Linear Regression for Hyperspectral Image Classification.

PubMed

Haoliang Yuan; Yuan Yan Tang

2017-04-01

Classification of the pixels in hyperspectral image (HSI) is an important task and has been popularly applied in many practical applications. Its major challenge is the high-dimensional small-sized problem. To deal with this problem, lots of subspace learning (SL) methods are developed to reduce the dimension of the pixels while preserving the important discriminant information. Motivated by ridge linear regression (RLR) framework for SL, we propose a spectral-spatial shared linear regression method (SSSLR) for extracting the feature representation. Comparing with RLR, our proposed SSSLR has the following two advantages. First, we utilize a convex set to explore the spatial structure for computing the linear projection matrix. Second, we utilize a shared structure learning model, which is formed by original data space and a hidden feature space, to learn a more discriminant linear projection matrix for classification. To optimize our proposed method, an efficient iterative algorithm is proposed. Experimental results on two popular HSI data sets, i.e., Indian Pines and Salinas demonstrate that our proposed methods outperform many SL methods.

Effect of endodontic irrigants on biofilm matrix polysaccharides.

PubMed

Tawakoli, P N; Ragnarsson, K T; Rechenberg, D K; Mohn, D; Zehnder, M

2017-02-01

To specifically investigate the effect of endodontic irrigants at their clinical concentration on matrix polysaccharides of cultured biofilms. Saccharolytic effects of 3% H 2 O 2 , 2% chlorhexidine (CHX), 17% EDTA, 5% NaOCl and 0.9% saline (control) were tested using agarose (α 1-3 and β 1-4 glycosidic bonds) blocks (n = 3) in a weight assay. The irrigants were also applied to three-species biofilms (Streptococcus mutans UAB 159, Streptococcus oralis OMZ 607 and Actinomyces oris OMZ 745) grown anaerobically on hydroxyapatite discs (n = 6). Glycoconjugates in the matrix and total bacterial cell volumes were determined using combined Concanavalin A-/Syto 59-staining and confocal laser-scanning microscopy. Volumes of each scanned area (triplicates/sample) were calculated using Imaris software. Data were compared between groups using one-way anova/Tukey HSD, α = 0.05. The weight assay revealed that NaOCl was the only irrigant under investigation capable of dissolving the agarose blocks. NaOCl eradicated stainable matrix and bacteria in cultured biofilms after 1 min of exposure (P < 0.05 compared to all groups, volumes in means ± standard deviation, 10 -3  mm 3 per 0.6 mm 2 disc; NaOCl matrix: 0.10 ± 0.08, bacteria: 0.03 ± 0.06; saline control matrix: 4.01 ± 1.14, bacteria: 11.56 ± 3.02). EDTA also appeared to have some effect on the biofilm matrix (EDTA matrix: 1.90 ± 0.33, bacteria: 9.26 ± 2.21), whilst H 2 O 2 and CHX merely reduced bacterial cell volumes. Sodium hypochlorite can break glycosidic bonds. It dissolves glycoconjugates in the biofilm matrix. It also lyses bacterial cells. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

A review of the feasibility of lightening structural polymeric composites with voids without compromising mechanical properties.

PubMed

Rutz, Benjamin H; Berg, John C

2010-10-15

High performance polymer-fiber composites are high strength, low weight materials that have many applications, many of which would benefit from a decrease in weight, without a decrease in material properties. Generally, the fibers serve as the main load carriers, while the matrix serves to distribute load and protect the fibers from the environment. Thus, it is postulated that if the volume fraction of matrix is reduced, while still ensuring complete wetting of the fibers by the matrix, the per unit weight, i.e., specific, mechanical properties could be improved. This can be done by introducing small, spherical bubbles. Given the small average inter-fiber distance and assuming that the bubbles must not interact with the surface of the reinforcements the bubble diameter would need to be less than 1 μm. Introducing bubbles this small and ensuring that they do not form, or become attached, on the surface of the reinforcement are significant challenges. Two methods to produce such bubbles and the effect of these bubbles on mechanical properties of neat resins are reviewed: the addition of hollow spherical fillers, called microballoons, and the creation of bubbles from blowing agents. Microballoons in resins are a class of materials called syntactic foams. Although commercial microballoons are too large, smaller diameters can be made and could be used to reduce the weight of a reinforced composite on the order of 10%. The use of a physical blowing agent to produce bubbles in a composite is also considered. However, traditional polymer foaming techniques may be inadequate, as nucleation on the reinforcing phase is likely, and the bubbles formed are generally too large, so the use of blowing agent wells is considered. Blowing agent wells are discontinuous regions made from copolymer micelles or immiscible polymers that act as reservoirs of blowing agent. Additionally, the use of nano-sized materials for use as heterogeneous nucleation sites and secondary reinforcement of the matrix is also considered. Bubbles made from blowing agent could reduce the weight slightly more than using hollow spheres, but the reduction would also be of the order of 10%. Copyright © 2010 Elsevier B.V. All rights reserved.

Formulation of a Nonlinear, Compatible Finite Element for the Analysis of Laminated Composites.

DTIC Science & Technology

1982-12-01

be gained through weight savings are obvious. The other advantage, which is being exploited in the design of the forward swept wing (2), is the...components of strain can also be represented in matrix form, ’-. fe t [LJfjut W’here + ~(3.211) The L - operator matrix can be broken down into linear, Loand

Process for the production of superconductor containing filaments

DOEpatents

Tuominen, Olli P.; Hoyt, Matthew B.; Mitchell, David F.; Morgan, Carol W.; Roberts, Clyde Gordon; Tyler, Robert A.

2002-01-01

Superconductor containing filaments having embedments of superconducting material surrounded by a rayon matrix are formed by preparing a liquid suspension which contains at least 10 weight percent superconducting material; forming a multicomponent filament having a core of the suspension and a viscose sheath which contains cellulose xanthate; and thereafter, regenerating cellulose from the cellulose xanthate to form a rayon matrix.

SU-E-J-157: Improving the Quality of T2-Weighted 4D Magnetic Resonance Imaging for Clinical Evaluation

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

Du, D; Mutic, S; Hu, Y

2014-06-01

Purpose: To develop an imaging technique that enables us to acquire T2- weighted 4D Magnetic Resonance Imaging (4DMRI) with sufficient spatial coverage, temporal resolution and spatial resolution for clinical evaluation. Methods: T2-weighed 4DMRI images were acquired from a healthy volunteer using a respiratory amplitude triggered T2-weighted Turbo Spin Echo sequence. 10 respiratory states were used to equally sample the respiratory range based on amplitude (0%, 20%i, 40%i, 60%i, 80%i, 100%, 80%e, 60%e, 40%e and 20%e). To avoid frequent scanning halts, a methodology was devised that split 10 respiratory states into two packages in an interleaved manner and packages were acquiredmore » separately. Sixty 3mm sagittal slices at 1.5mm in-plane spatial resolution were acquired to offer good spatial coverage and reasonable spatial resolution. The in-plane field of view was 375mm × 260mm with nominal scan time of 3 minutes 42 seconds. Acquired 2D images at the same respiratory state were combined to form the 3D image set corresponding to that respiratory state and reconstructed in the coronal view to evaluate whether all slices were at the same respiratory state. 3D image sets of 10 respiratory states represented a complete 4D MRI image set. Results: T2-weighted 4DMRI image were acquired in 10 minutes which was within clinical acceptable range. Qualitatively, the acquired MRI images had good image quality for delineation purposes. There were no abrupt position changes in reconstructed coronal images which confirmed that all sagittal slices were in the same respiratory state. Conclusion: We demonstrated it was feasible to acquire T2-weighted 4DMRI image set within a practical amount of time (10 minutes) that had good temporal resolution (10 respiratory states), spatial resolution (1.5mm × 1.5mm × 3.0mm) and spatial coverage (60 slices) for future clinical evaluation.« less

Mechanical properties of high density polyethylene--pennycress press cake composites

USDA-ARS?s Scientific Manuscript database

Pennycress press cake (PPC) is evaluated as a bio-based fiber reinforcement. PPC is a by-product of crop seed oil extraction. Composites with a high density polyethylene (HDPE) matrix are created by twin screw compounding of 25% by weight of PPC and either 0% or 5% by weight of maleated polyethyle...

Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms.

ERIC Educational Resources Information Center

Kiers, Henk A. L.

1997-01-01

A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)

Fractography of poly(methyl methacrylates).

PubMed

Kusy, R P; Turner, D T

1975-07-01

For convenience in clinical manipulation, it is the practice to fabricate PMMA protheses from mixtures of powder and monomer. When the monomer is subsequently polymerized an unusual 2-phase polymeric material results in which grains of PMMA are dispersed in a matrix of the same polymer. The mechanical properties of the 2-phase materials are inferior in certain respects relative to 1-phase polymers. The purpose of the present work is to evaluate the failure of 2-phase materials by microscopical examination of their fracture surfaces. A granular microstructure was clearly distinguishable and a distinction made between materials which fail exclusively by transgranular fracture and others which additionally exhibit intergranular fracture. In order to interpret markings observed on the fracture surfaces of the complex 2-phase systems a study was made of the influence of molecular weight on the fractography of 1-phase PMMA. Molecular weight was reduced by degradation of samples by exposure to gamma-rays. The spacing of periodic rib markings on fracture surfaces was found to decrease with molecular weight and this relationship used to provide an estimate of the molecular weight of polymer in the matrix of 2-phase materials.

Using molecular recognition of beta-cyclodextrin to determine molecular weights of low-molecular-weight explosives by MALDI-TOF mass spectrometry.

PubMed

Zhang, Min; Shi, Zhen; Bai, Yinjuan; Gao, Yong; Hu, Rongzu; Zhao, Fenqi

2006-02-01

This study presents a novel method for determining the molecular weights of low molecular weight (MW) energetic compounds through their complexes of beta-cyclodextrin (beta-CD) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in a mass range of 500 to 1700 Da, avoiding matrix interference. The MWs of one composite explosive composed of 2,6-DNT, TNT, and RDX, one propellant with unknown components, and 14 single-compound explosives (RDX, HMX, 3,4-DNT, 2,6-DNT, 2,5-DNT, 2,4,6-TNT, TNAZ, DNI, BTTN, NG, TO, NTO, NP, and 662) were measured. The molecular recognition and inclusion behavior of beta-CD to energetic materials (EMs) were investigated. The results show that (1) the established method is sensitive, simple, accurate, and suitable for determining the MWs of low-MW single-compound explosives and energetic components in composite explosives and propellants; and (2) beta-CD has good inclusion and modular recognition abilities to the above EMs.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

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

Mahon, R; Weiss, E; Karki, K

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from themore » delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use in specific applications such as tissue classification and changes during radiation therapy utilizing a standard imaging protocol. Authors have the following disclosures: a research agreement with Philips Medical systems (Hugo, Weiss), a license agreement with Varian Medical Systems (Hugo, Weiss), research grants from the National Institute of Health (Hugo, Weiss), UpToDate royalties (Weiss), and none(Mahon, Ford, Karki). Authors have no potential conflicts of interest to disclose.« less

Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

PubMed

Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

2017-04-01

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

Compensation for the phase-type spatial periodic modulation of the near-field beam at 1053 nm

NASA Astrophysics Data System (ADS)

Gao, Yaru; Liu, Dean; Yang, Aihua; Tang, Ruyu; Zhu, Jianqiang

2017-10-01

A phase-only spatial light modulator is used to provide and compensate for the spatial periodic modulation (SPM) of the near-field beam at the near infrared at 1053nm wavelength with an improved iterative weight-based method. The transmission characteristics of the incident beam has been changed by a spatial light modulator (SLM) to shape the spatial intensity of the output beam. The propagation and reverse propagation of the light in free space are two important processes in the iterative process. The based theory is the beam angular spectrum transmit formula (ASTF) and the principle of the iterative weight-based method. We have made two improvements to the originally proposed iterative weight-based method. We select the appropriate parameter by choosing the minimum value of the output beam contrast degree and use the MATLAB built-in angle function to acquire the corresponding phase of the light wave function. The required phase that compensates for the intensity distribution of the incident SPM beam is iterated by this algorithm, which can decrease the magnitude of the SPM of the intensity on the observation plane. The experimental results show that the phase-type SPM of the near-field beam is subject to a certain restriction. We have also analyzed some factors that make the results imperfect. The experiment results verifies the possible applicability of this iterative weight-based method to compensate for the SPM of the near-field beam.

Critical Behavior of Spatial Evolutionary Game with Altruistic to Spiteful Preferences on Two-Dimensional Lattices

NASA Astrophysics Data System (ADS)

Yang, Bo; Li, Xiao-Teng; Chen, Wei; Liu, Jian; Chen, Xiao-Song

2016-10-01

Self-questioning mechanism which is similar to single spin-flip of Ising model in statistical physics is introduced into spatial evolutionary game model. We propose a game model with altruistic to spiteful preferences via weighted sums of own and opponent's payoffs. This game model can be transformed into Ising model with an external field. Both interaction between spins and the external field are determined by the elements of payoff matrix and the preference parameter. In the case of perfect rationality at zero social temperature, this game model has three different phases which are entirely cooperative phase, entirely non-cooperative phase and mixed phase. In the investigations of the game model with Monte Carlo simulation, two paths of payoff and preference parameters are taken. In one path, the system undergoes a discontinuous transition from cooperative phase to non-cooperative phase with the change of preference parameter. In another path, two continuous transitions appear one after another when system changes from cooperative phase to non-cooperative phase with the prefenrence parameter. The critical exponents v, β, and γ of two continuous phase transitions are estimated by the finite-size scaling analysis. Both continuous phase transitions have the same critical exponents and they belong to the same universality class as the two-dimensional Ising model. Supported by the National Natural Science Foundation of China under Grant Nos. 11121403 and 11504384

A multimodal imaging workflow to visualize metal mixtures in the human placenta and explore colocalization with biological response markers.

PubMed

Niedzwiecki, Megan M; Austin, Christine; Remark, Romain; Merad, Miriam; Gnjatic, Sacha; Estrada-Gutierrez, Guadalupe; Espejel-Nuñez, Aurora; Borboa-Olivares, Hector; Guzman-Huerta, Mario; Wright, Rosalind J; Wright, Robert O; Arora, Manish

2016-04-01

Fetal exposure to essential and toxic metals can influence life-long health trajectories. The placenta regulates chemical transmission from maternal circulation to the fetus and itself exhibits a complex response to environmental stressors. The placenta can thus be a useful matrix to monitor metal exposures and stress responses in utero, but strategies to explore the biologic effects of metal mixtures in this organ are not well-developed. In this proof-of-concept study, we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to measure the distributions of multiple metals in placental tissue from a low-birth-weight pregnancy, and we developed an approach to identify the components of metal mixtures that colocalized with biological response markers. Our novel workflow, which includes custom-developed software tools and algorithms for spatial outlier identification and background subtraction in multidimensional elemental image stacks, enables rapid image processing and seamless integration of data from elemental imaging and immunohistochemistry. Using quantitative spatial statistics, we identified distinct patterns of metal accumulation at sites of inflammation. Broadly, our multiplexed approach can be used to explore the mechanisms mediating complex metal exposures and biologic responses within placentae and other tissue types. Our LA-ICP-MS image processing workflow can be accessed through our interactive R Shiny application 'shinyImaging', which is available at or through our laboratory's website, .

Robust k-mer frequency estimation using gapped k-mers

PubMed Central

Ghandi, Mahmoud; Mohammad-Noori, Morteza

2013-01-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome. PMID:23861010

Robust k-mer frequency estimation using gapped k-mers.

PubMed

Ghandi, Mahmoud; Mohammad-Noori, Morteza; Beer, Michael A

2014-08-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.

Mercury in fruiting bodies of dark honey fungus (Armillaria solidipes) and beneath substratum soils collected from spatially distant areas.

PubMed

Falandysz, Jerzy; Mazur, Aneta; Kojta, Anna K; Jarzyńska, Grażyna; Drewnowska, Małgorzata; Dryżałowska, Anna; Nnorom, Innocent C

2013-03-15

This paper reports data on bioconcentration potential and baseline mercury concentrations of fruiting bodies of dark honey fungus (Armillaria solidipes) Peck and soil substrate layer (0-10 cm) from 12 spatially distant sites across Poland. Mercury content of caps, stipes and soil samples were determined using validated analytical procedure including cold-vapor atomic absorption spectroscopy after thermal decomposition of the sample matrix and further amalgamation and desorption of mercury from gold wool. Mean mercury concentrations ranged from 20 ± 8 to 300 ± 70 ng g(-1) dry weight (dw) in caps, from 20 ± 6 to 160 ± 40 ng g(-1) dw in stipes, and in underlying soil were from 20 ± 2 to 100 ± 130 ng g(-1) dw. The results showed that stipes mercury concentrations were 1.1- to 1.7-fold lower than those of caps. All caps and the majority of stipes were characterized by bioconcentration factor values > 1, indicating that dark honey fungus can be characterized as a moderate mercury accumulator. Occasional or relatively frequent eating of meals including caps of dark honey fungus is considered safe in view of the low total mercury content, and the mercury intake rates are below the current reference dose and provisionally tolerable weekly intake limits for this hazardous metal. © 2012 Society of Chemical Industry.

Visible-light induced anti-bacterial and self-cleaning waterborne polyacrylic coating modified with TiO2/polypyrrole nanocomposite; preparation and characterization

NASA Astrophysics Data System (ADS)

Nosrati, Rahimeh; Olad, Ali; Maryami, Fatemeh

2018-07-01

Nowadays, self-cleaning technology is used in various industries to decreasing the time, energy consumption and costs of surface servicing as well as the increasing of surface durability. Self-cleaning and anti-bacterial coatings can be made by the addition of suitable additives to a polymer matrix with good properties. In the present research, TiO2/polypyrrole nanocomposites were prepared in different TiO2 to polypyrrole weight ratios and used in various percent as an additive in waterborne commercial grade polyacrylic latex. Characterization and evaluation of structural and morphological features of nanocomposites and coatings were performed by FTIR, XRD, UV-Vis and FESEM techniques. By the addition of prepared nanocomposites as an additive to the polyacrylic matrix, the hydrophilic, water resistant, anti-bacterial, and photocatalytic coatings were prepared. The TiO2 to polypyrrole weight ratio of TiO2/polypyrrole nanocomposites and the percent of nanocomposite additive in the polymeric matrix were optimized. According to the results, the coating containing 2% and 3% of TiO2/polypyrrole nanocomposite with TiO2 to polypyrrole weight ratio of 100:10 are proposed as the best coating formulations in the formulations examined in this work, due to their good properties in the most of experiments.

FastSKAT: Sequence kernel association tests for very large sets of markers.

PubMed

Lumley, Thomas; Brody, Jennifer; Peloso, Gina; Morrison, Alanna; Rice, Kenneth

2018-06-22

The sequence kernel association test (SKAT) is widely used to test for associations between a phenotype and a set of genetic variants that are usually rare. Evaluating tail probabilities or quantiles of the null distribution for SKAT requires computing the eigenvalues of a matrix related to the genotype covariance between markers. Extracting the full set of eigenvalues of this matrix (an n×n matrix, for n subjects) has computational complexity proportional to n 3 . As SKAT is often used when n>104, this step becomes a major bottleneck in its use in practice. We therefore propose fastSKAT, a new computationally inexpensive but accurate approximations to the tail probabilities, in which the k largest eigenvalues of a weighted genotype covariance matrix or the largest singular values of a weighted genotype matrix are extracted, and a single term based on the Satterthwaite approximation is used for the remaining eigenvalues. While the method is not particularly sensitive to the choice of k, we also describe how to choose its value, and show how fastSKAT can automatically alert users to the rare cases where the choice may affect results. As well as providing faster implementation of SKAT, the new method also enables entirely new applications of SKAT that were not possible before; we give examples grouping variants by topologically associating domains, and comparing chromosome-wide association by class of histone marker. © 2018 WILEY PERIODICALS, INC.

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

Impact of salt form and molecular weight of chitosan on swelling and drug release from chitosan matrix tablets.

PubMed

Huanbutta, Kampanart; Cheewatanakornkool, Kamonrak; Terada, Katsuhide; Nunthanid, Jurairat; Sriamornsak, Pornsak

2013-08-14

Magnetic resonance imaging (MRI) and gravimetric techniques were used to assess swelling and erosion behaviors of hydrophilic matrix tablets made of chitosan. The impact of salt form, molecular weight (MW) and dissolution medium on swelling behavior and drug (theophylline) release was studied. The matrix tablets made of chitosan glycolate (CGY) showed the greatest swelling in both acid and neutral media, compared to chitosan aspartate, chitosan glutamate and chitosan lactate. MRI illustrated that swelling region of CGY in both media was not different in the first 100 min but glassy region (dry core) in 0.1N HCl was less than in pH 6.8 buffer. The tablets prepared from chitosan with high MW swelled greater than those of low MW. Moreover, CGY can delay drug release in the acid condition due to thick swollen gel and low erosion rate. Therefore, CGY may be suitably applied as sustained drug release polymer or enteric coating material. Copyright © 2013 Elsevier Ltd. All rights reserved.

A note on the estimation of the Pareto efficient set for multiobjective matrix permutation problems.

PubMed

Brusco, Michael J; Steinley, Douglas

2012-02-01

There are a number of important problems in quantitative psychology that require the identification of a permutation of the n rows and columns of an n × n proximity matrix. These problems encompass applications such as unidimensional scaling, paired-comparison ranking, and anti-Robinson forms. The importance of simultaneously incorporating multiple objective criteria in matrix permutation applications is well recognized in the literature; however, to date, there has been a reliance on weighted-sum approaches that transform the multiobjective problem into a single-objective optimization problem. Although exact solutions to these single-objective problems produce supported Pareto efficient solutions to the multiobjective problem, many interesting unsupported Pareto efficient solutions may be missed. We illustrate the limitation of the weighted-sum approach with an example from the psychological literature and devise an effective heuristic algorithm for estimating both the supported and unsupported solutions of the Pareto efficient set. © 2011 The British Psychological Society.

Approaches for the analysis of low molecular weight compounds with laser desorption/ionization techniques and mass spectrometry.

PubMed

Bergman, Nina; Shevchenko, Denys; Bergquist, Jonas

2014-01-01

This review summarizes various approaches for the analysis of low molecular weight (LMW) compounds by different laser desorption/ionization mass spectrometry techniques (LDI-MS). It is common to use an agent to assist the ionization, and small molecules are normally difficult to analyze by, e.g., matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) using the common matrices available today, because the latter are generally small organic compounds themselves. This often results in severe suppression of analyte peaks, or interference of the matrix and analyte signals in the low mass region. However, intrinsic properties of several LDI techniques such as high sensitivity, low sample consumption, high tolerance towards salts and solid particles, and rapid analysis have stimulated scientists to develop methods to circumvent matrix-related issues in the analysis of LMW molecules. Recent developments within this field as well as historical considerations and future prospects are presented in this review.

Characterization of an alkaline protease associated with a granulosis virus of Plodia interpunctella.

PubMed

Tweeten, K A; Bulla, L A; Consigli, R A

1978-06-01

An alkaline protease was found to be associated with the granulosis virus of the Indian meal moth. Plodia interpunctella. The protease was located within the protein matrix of the occluded virus and hydrolyzed the major constituent of this matrix, a 28,000-dalton protein (granulin), to a mixture of polypeptides ranging in molecular weight from 10,000 to 27,000. A rapid, sensitive assay for the protease was developed using radioactively labeled granulosis virus as substrate. With this assay, the proteolytic activity could be detected by measuring the release of acid-soluble peptides from the labeled virus. The protease had a pH optimum of 10.5 and a temperature optimum of 40 degrees C and was inhibited by diisopropyl phosphorofluoridate, phenylmethylsulfonyl fluoride, and L-(1-tosylamido-2-phenyl) ethyl chloromethyl ketone. Purification of the protease from matrix protein was achieved by anion-exchange and gel permeation chromatography. The molecular weight of the isolated protease, determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and gel filtration, was approximately 14,000.

Method for estimating power outages and restoration during natural and man-made events

DOEpatents

Omitaomu, Olufemi A.; Fernandez, Steven J.

2016-01-05

A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.

Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

PubMed Central

Kosik, Ivan; Raess, Avery

2015-01-01

Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

USGS Publications Warehouse

Haney, Matthew M.; Mikesell, T. Dylan; van Wijk, Kasper; Nakahara, Hisashi

2012-01-01

Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.

The concentration parameter thermal microstresses as the thermophysical characteristics of two-phase materials

NASA Astrophysics Data System (ADS)

Kuanishev, V. T.; Sachkov, I. N.; Sorogin, I. G.; Sorogina, T. I.

2017-11-01

Thermal strength is one of the main thermophysical characteristics of structural materials. For homogeneous systems it is determined by the strength characteristics of the material. While for inhomogeneous systems, in particular, multiphase ones, it is necessary to consider the nature of the microstructure. Heat resistant real materials such as steels are known to be multi-phase systems. One of the mechanisms of their destruction is associated with the presence of propagating heat fluxes that generate thermal stresses. The aim of this paper is to evaluate the patterns of the formation of spatial distributions of thermal stresses in matrix systems of round inclusions characterized by different mutual disposition. The spatial distributions of thermal stresses in a two-phase material characterized by a matrix structure with round inclusions are investigated. For the numerical solution of the problem of stationary thermal conductivity the finite element method with discretization of the medium by triangular elements is used. It was found that at certain points in the medium the values of thermal stresses are ten times higher than the average for the material. It is shown that the spatial distribution and the local magnitude of the temperature gradient depend on the shape of the particles of the phase components and the values of their thermal conductivities. It is considered that the elastic moduli of inclusion and matrix differ little from each other.

Local pressure and matrix component effects on verteporfin distribution in pancreatic tumors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nieskoski, Michael D.; Marra, Kayla; Gunn, Jason R.; Doyley, Marvin; Samkoe, Kimberly S.; Pereira, Stephen P.; Trembly, B. Stuart; Pogue, Brian W.

2017-02-01

Pancreatic tumors are characterized by large interstitial hypertension from enhanced deposition of extracellular matrix components, resulting in widespread vascular collapse and reduced molecular uptake of systemically delivered therapies. Although the origins of hypoperfusion is debated amongst researchers, spatial distribution of collagen density and hyaluronic acid content have shown to be a key metric in understanding the lack of efficacy for both acute and chronic therapies in these tumors. In this study, the AsPC-1 tumor model was used both subcutaneously and orthotopically to study the measurable factors which are related to this. A conventional piezoelectric pressure catheter was used to measure total tissue pressure (TTP), defined as a combination of solid stress (SS) and interstitial fluid pressure (IFP), TTP = SS + IFP, in multiple locations within the tumor interstitium. Matrix components such as collagen and hyaluronic acid were scored using masson's trichrome stain and hyaluronic acid binding protein (HABP), respectively, and co-registered with values of TTP. The results show that these key measurements are related to the spatial distribution of verteporfin in the same tumors. Photodynamic treatment with verteporfin is known to ablate large regions of tumor tissue and also allow better permeability for chemotherapies. The study of spatial distribution of verteporfin in relation to stromal content and TTP will help us better control these types of combination therapies.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Neural Representation of Spatial Topology in the Rodent Hippocampus

PubMed Central

Chen, Zhe; Gomperts, Stephen N.; Yamamoto, Jun; Wilson, Matthew A.

2014-01-01

Pyramidal cells in the rodent hippocampus often exhibit clear spatial tuning in navigation. Although it has been long suggested that pyramidal cell activity may underlie a topological code rather than a topographic code, it remains unclear whether an abstract spatial topology can be encoded in the ensemble spiking activity of hippocampal place cells. Using a statistical approach developed previously, we investigate this question and related issues in greater details. We recorded ensembles of hippocampal neurons as rodents freely foraged in one and two-dimensional spatial environments, and we used a “decode-to-uncover” strategy to examine the temporally structured patterns embedded in the ensemble spiking activity in the absence of observed spatial correlates during periods of rodent navigation or awake immobility. Specifically, the spatial environment was represented by a finite discrete state space. Trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a state transition matrix. From this state transition matrix, we inferred a topology graph that defined the connectivity in the state space. In both one and two-dimensional environments, the extracted behavior patterns from the rodent hippocampal population codes were compared against randomly shuffled spike data. In contrast to a topographic code, our results support the efficiency of topological coding in the presence of sparse sample size and fuzzy space mapping. This computational approach allows us to quantify the variability of ensemble spiking activity, to examine hippocampal population codes during off-line states, and to quantify the topological complexity of the environment. PMID:24102128

Relative risk for HIV in India - An estimate using conditional auto-regressive models with Bayesian approach.

PubMed

Kandhasamy, Chandrasekaran; Ghosh, Kaushik

2017-02-01

Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information. We use R and WinBugs software to fit these models to the 2011 HIV data. Based on the Deviance Information Criterion, the convolution model using distance-based weight matrix and covariate information on female sex workers, literacy rate and intravenous drug users is found to have the best fit. The relative risk of HIV for the various states is estimated using the best model and the states are then classified into the risk categories based on these estimated values. An HIV risk map of India is constructed based on these results. The choice of the final model suggests that an HIV control strategy which focuses on the female sex workers, intravenous drug users and literacy rate would be most effective. Copyright © 2017 Elsevier Ltd. All rights reserved.

1,2-diketones promoted degradation of poly(epsilon-caprolactone)

NASA Astrophysics Data System (ADS)

Danko, Martin; Borska, Katarina; Ragab, Sherif Shaban; Janigova, Ivica; Mosnacek, Jaroslav

2012-07-01

Photochemical reactions of Benzil and Camphorquinone were used for modification of poly(ɛ-caprolactone) polymer films. Photochemistry of dopants was followed by infrared spectroscopy, changes on polymer chains of matrix were followed by gel permeation chromatography. Benzoyl peroxide was efficiently photochemically generated from benzyl in solid polymer matrix in the presence of air. Following decomposition of benzoyl peroxide led to degradation of matrix. Photochemical transformation of benzil in vacuum led to hydrogen abstraction from the polymer chains in higher extent, which resulted to chains recombination and formation of gel. Photochemical transformation of camphorquinone to corresponding camphoric peroxide was not observed. Only decrease of molecular weight of polymer matrix doped with camphorquinone was observed during the irradiation.

Analysis of metal-matrix composite structures. I - Micromechanics constitutive theory. II - Laminate analyses

NASA Technical Reports Server (NTRS)

Arenburg, R. T.; Reddy, J. N.

1991-01-01

The micromechanical constitutive theory is used to examine the nonlinear behavior of continuous-fiber-reinforced metal-matrix composite structures. Effective lamina constitutive relations based on the Abouli micromechanics theory are presented. The inelastic matrix behavior is modeled by the unified viscoplasticity theory of Bodner and Partom. The laminate constitutive relations are incorporated into a first-order deformation plate theory. The resulting boundary value problem is solved by utilizing the finite element method. Attention is also given to computational aspects of the numerical solution, including the temporal integration of the inelastic strains and the spatial integration of bending moments. Numerical results the nonlinear response of metal matrix composites subjected to extensional and bending loads are presented.

Spatially Resolved Quantification of the Surface Reactivity of Solid Catalysts.

PubMed

Huang, Bing; Xiao, Li; Lu, Juntao; Zhuang, Lin

2016-05-17

A new property is reported that accurately quantifies and spatially describes the chemical reactivity of solid surfaces. The core idea is to create a reactivity weight function peaking at the Fermi level, thereby determining a weighted summation of the density of states of a solid surface. When such a weight function is defined as the derivative of the Fermi-Dirac distribution function at a certain non-zero temperature, the resulting property is the finite-temperature chemical softness, termed Fermi softness (SF ), which turns out to be an accurate descriptor of the surface reactivity. The spatial image of SF maps the reactive domain of a heterogeneous surface and even portrays morphological details of the reactive sites. SF analyses reveal that the reactive zones on a Pt3 Y(111) surface are the platinum sites rather than the seemingly active yttrium sites, and the reactivity of the S-dimer edge of MoS2 is spatially anisotropic. Our finding is of fundamental and technological significance to heterogeneous catalysis and industrial processes demanding rational design of solid catalysts. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spectral statistics of random geometric graphs

NASA Astrophysics Data System (ADS)

Dettmann, C. P.; Georgiou, O.; Knight, G.

2017-04-01

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short-range correlations in the level spacings of the spectrum via the nearest-neighbour and next-nearest-neighbour spacing distribution and long-range correlations via the spectral rigidity Δ3 statistic. These correlations in the level spacings give information about localisation of eigenvectors, level of community structure and the level of randomness within the networks. We find a parameter-dependent transition between Poisson and Gaussian orthogonal ensemble statistics. That is the spectral statistics of spatial random geometric graphs fits the universality of random matrix theory found in other models such as Erdős-Rényi, Barabási-Albert and Watts-Strogatz random graphs.

Separation of distinct adhesion complexes and associated cytoskeleton by a micro-stencil-printing method.

PubMed

Caballero, David; Osmani, Naël; Georges-Labouesse, Elisabeth; Labouesse, Michel; Riveline, Daniel

2012-01-01

Adhesion between cells and the extracellular matrix is mediated by different types of transmembraneous proteins. Their associations to specific partners lead to the assembly of contacts such as focal adhesions and hemidesmosomes. The spatial overlap between both contacts within cells has however limited the study of each type of contact. Here we show that with "stampcils" focal contacts and hemidesmosomes can be spatially separated: cells are plated within the cavities of a stencil and the grids of the stencil serve as stamps for grafting an extracellular matrix protein-fibronectin. Cells engage new contacts on stamped zones leading to the segregation of adhesions and their associated cytoskeletons, i.e., actin and intermediate filaments of keratins. This new method should provide new insights into cell contacts compositions and dynamics.

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

PubMed

Qiu, W; Titley-Peloquin, D; Soleimani, M

2012-11-01

Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Eigentime identities for on weighted polymer networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Tang, Hualong; Zou, Jiahui; He, Di; Sun, Yu; Su, Weiyi

2018-01-01

In this paper, we first analytically calculate the eigenvalues of the transition matrix of a structure with very complex architecture and their multiplicities. We call this structure polymer network. Based on the eigenvalues obtained in the iterative manner, we then calculate the eigentime identity. We highlight two scaling behaviors (logarithmic and linear) for this quantity, strongly depending on the value of the weight factor. Finally, by making use of the obtained eigenvalues, we determine the weighted counting of spanning trees.

Spatiotemporal Interpolation for Environmental Modelling

PubMed Central

Susanto, Ferry; de Souza, Paulo; He, Jing

2016-01-01

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

Fast automated segmentation of multiple objects via spatially weighted shape learning

NASA Astrophysics Data System (ADS)

Chandra, Shekhar S.; Dowling, Jason A.; Greer, Peter B.; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-01

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice’s similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

Fast automated segmentation of multiple objects via spatially weighted shape learning.

PubMed

Chandra, Shekhar S; Dowling, Jason A; Greer, Peter B; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-21

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

Quantum Monte Carlo calculations of electromagnetic transitions in $^8$Be with meson-exchange currents derived from chiral effective field theory

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

Pastore, S.; Wiringa, Robert B.; Pieper, Steven C.

2014-08-01

We report quantum Monte Carlo calculations of electromagnetic transitions inmore » $^8$Be. The realistic Argonne $$v_{18}$$ two-nucleon and Illinois-7 three-nucleon potentials are used to generate the ground state and nine excited states, with energies that are in excellent agreement with experiment. A dozen $M1$ and eight $E2$ transition matrix elements between these states are then evaluated. The $E2$ matrix elements are computed only in impulse approximation, with those transitions from broad resonant states requiring special treatment. The $M1$ matrix elements include two-body meson-exchange currents derived from chiral effective field theory, which typically contribute 20--30\\% of the total expectation value. Many of the transitions are between isospin-mixed states; the calculations are performed for isospin-pure states and then combined with the empirical mixing coefficients to compare to experiment. In general, we find that transitions between states that have the same dominant spatial symmetry are in decent agreement with experiment, but those transitions between different spatial symmetries are often significantly underpredicted.« less

First Human Brain Imaging by the jPET-D4 Prototype With a Pre-Computed System Matrix

NASA Astrophysics Data System (ADS)

Yamaya, Taiga; Yoshida, Eiji; Obi, Takashi; Ito, Hiroshi; Yoshikawa, Kyosan; Murayama, Hideo

2008-10-01

The jPET-D4 is a novel brain PET scanner which aims to achieve not only high spatial resolution but also high scanner sensitivity by using 4-layer depth-of-interaction (DOI) information. The dimensions of a system matrix for the jPET-D4 are 3.3 billion (lines-of-response) times 5 million (image elements) when a standard field-of-view (FOV) of 25 cm diameter is sampled with a (1.5 mm)3 voxel . The size of the system matrix is estimated as 117 petabytes (PB) with the accuracy of 8 bytes per element. An on-the-fly calculation is usually used to deal with such a huge system matrix. However we cannot avoid extension of the calculation time when we improve the accuracy of system modeling. In this work, we implemented an alternative approach based on pre-calculation of the system matrix. A histogram-based 3D OS-EM algorithm was implemented on a desktop workstation with 32 GB memory installed. The 117 PB system matrix was compressed under the limited amount of computer memory by (1) eliminating zero elements, (2) applying the DOI compression (DOIC) method and (3) applying rotational symmetry and an axial shift property of the crystal arrangement. Spanning, which degrades axial resolution, was not applied. The system modeling and the DOIC method, which had been validated in 2D image reconstruction, were expanded into 3D implementation. In particular, a new system model including the DOIC transformation was introduced to suppress resolution loss caused by the DOIC method. Experimental results showed that the jPET-D4 has almost uniform spatial resolution of better than 3 mm over the FOV. Finally the first human brain images were obtained with the jPET-D4.

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Sub-Audible Speech Recognition Based upon Electromyographic Signals

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C. (Inventor); Agabon, Shane T. (Inventor); Lee, Diana D. (Inventor)

2012-01-01

Method and system for processing and identifying a sub-audible signal formed by a source of sub-audible sounds. Sequences of samples of sub-audible sound patterns ("SASPs") for known words/phrases in a selected database are received for overlapping time intervals, and Signal Processing Transforms ("SPTs") are formed for each sample, as part of a matrix of entry values. The matrix is decomposed into contiguous, non-overlapping two-dimensional cells of entries, and neural net analysis is applied to estimate reference sets of weight coefficients that provide sums with optimal matches to reference sets of values. The reference sets of weight coefficients are used to determine a correspondence between a new (unknown) word/phrase and a word/phrase in the database.

Closed-form solutions for linear regulator-design of mechanical systems including optimal weighting matrix selection

NASA Technical Reports Server (NTRS)

Hanks, Brantley R.; Skelton, Robert E.

1991-01-01

This paper addresses the restriction of Linear Quadratic Regulator (LQR) solutions to the algebraic Riccati Equation to design spaces which can be implemented as passive structural members and/or dampers. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical systems. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist. Some examples of simple spring mass systems are shown to illustrate key points.

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

Lee, J.R.; Kim, J.H.

The weight loss and flexural property changes of the autoclave cured carbon/epoxy (0{degree}){sub 8} laminates toughened by CTBN at the temperatures of 200, 250 and 300{degree}C for the endurance times of 1, 2, 4, 8 and 16 hours were measured. The matrix resins is composed of 100 phr of tetrafunctional epoxy resin (MY-720), 28 phr of Diamine-diphenyl sulfone (DDS) and 1 phr of Borontrifluoride monoethylene amine (BF{sub 3}{center_dot}MEA). The added contents of CTBN were 5, 10 and 15% by weight to the matrix resins. The addition of CTBN improves the thermal stability of the carbon/epoxy specimens in terms of weightmore » loss and flexural modulus. But the flexural strength was decreased by addition of CTBN.« less

Metal Matrix Composites for Rocket Engine Applications

NASA Technical Reports Server (NTRS)

McDonald, Kathleen R.; Wooten, John R.

2000-01-01

This document is from a presentation about the applications of Metal Matrix Composites (MMC) in rocket engines. Both NASA and the Air Force have goals which would reduce the costs and the weight of launching spacecraft. Charts show the engine weight distribution for both reuseable and expendable engine components. The presentation reviews the operating requirements for several components of the rocket engines. The next slide reviews the potential benefits of MMCs in general and in use as materials for Advanced Pressure Casting. The next slide reviews the drawbacks of MMCs. The reusable turbopump housing is selected to review for potential MMC application. The presentation reviews solutions for reusable turbopump materials, pointing out some of the issues. It also reviews the development of some of the materials.

Communication: Hilbert-space partitioning of the molecular one-electron density matrix with orthogonal projectors

NASA Astrophysics Data System (ADS)

Vanfleteren, Diederik; Van Neck, Dimitri; Bultinck, Patrick; Ayers, Paul W.; Waroquier, Michel

2010-12-01

A double-atom partitioning of the molecular one-electron density matrix is used to describe atoms and bonds. All calculations are performed in Hilbert space. The concept of atomic weight functions (familiar from Hirshfeld analysis of the electron density) is extended to atomic weight matrices. These are constructed to be orthogonal projection operators on atomic subspaces, which has significant advantages in the interpretation of the bond contributions. In close analogy to the iterative Hirshfeld procedure, self-consistency is built in at the level of atomic charges and occupancies. The method is applied to a test set of about 67 molecules, representing various types of chemical binding. A close correlation is observed between the atomic charges and the Hirshfeld-I atomic charges.

A novel spatially-explicit condition for the onset of waterborne diseases in complex environments

NASA Astrophysics Data System (ADS)

Mari, L.; Gatto, M.; Bertuzzo, E.; Casagrandi, R.; Righetto, L.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

In spatial models of waterborne infections the condition that all the local reproduction numbers be larger than one is neither necessary nor sufficient for outbreaks to occur. Here, to properly determine epidemic onset conditions, we examine the transition from stable to unstable of the disease-free equilibrium of a system of nonlinear differential equations characterizing the evolution of susceptible and infected individuals within their respective settlements, and pathogen concentration in their accessible environment. Two different network connectivity layers are assumed to link human settlements: hydrologic pathways serve as ecological corridors for pathogens, while human mobility acts as disease vehicle through susceptibles contracting the disease and asymptomatic infectives shedding bacteria at their temporary destinations. We show that an epidemic outbreak can be triggered if the dominant eigenvalue of a generalized reproduction matrix G0, suitably accounting for spatial distribution of human settlements, hydrological pathways for pathogen dispersal and pathogen redistribution mechanisms due to human mobility, is larger than unity. Matrix G0 and its dominant eigenvalue thus replace the usual reproduction number whenever spatial effects on disease propagation cannot be ignored. Conversely, our novel criterion decays into the standard onset condition based on local reproduction numbers in nonspatial settings. By analyzing realistic test cases we show that within a connected network system the disease can start even if all the local reproduction numbers are smaller than unity, or might not start even if all the local reproduction numbers are larger than unity. We also show that onset geography in complex environments is linked to the dominant eigenvector of matrix G0. Applications to cholera outbreaks in developing countries demonstrate that our approach can be successfully used for disease prediction and emergency management.

The non-human primate striatum undergoes marked prolonged remodeling during postnatal development

PubMed Central

Martin, Lee J.; Cork, Linda C.

2014-01-01

We examined the postnatal ontogeny of the striatum in rhesus monkeys (Macaca mulatta) to identify temporal and spatial patterns of histological and chemical maturation. Our goal was to determine whether this forebrain structure is developmentally static or dynamic in postnatal life. Brains from monkeys at 1 day, 1, 4, 6, 9, and 12 months of age (N = 12) and adult monkeys (N = 4) were analyzed. Nissl staining was used to assess striatal volume, cytoarchitecture, and apoptosis. Immunohistochemistry was used to localize and measure substance P (SP), leucine-enkephalin (LENK), tyrosine hydroxylase (TH), and calbindin D28 (CAL) immunoreactivities. Mature brain to body weight ratio was achieved at 4 months of age, and striatal volume increased from ∼1.2 to ∼1.4 cm3 during the first postnatal year. Nissl staining identified, prominently in the caudate nucleus, developmentally persistent discrete cell islands with neuronal densities greater than the surrounding striatal parenchyma (matrix). Losses in neuronal density were observed in island and matrix regions during maturation, and differential developmental programmed cell death was observed in islands and matrix regions. Immunohistochemistry revealed striking changes occurring postnatally in striatal chemical neuroanatomy. At birth, the immature dopaminergic nigrostriatal innervation was characterized by islands enriched in TH-immunoreactive puncta (putative terminals) in the neuropil; TH-enriched islands aligned completely with areas enriched in SP immunoreactivity but low in LENK immunoreactivity. These areas enriched in SP immunoreactivity but low in LENK immunoreactivity were identified as striosome and matrix areas, respectively, because CAL immunoreactivity clearly delineated these territories. SP, LENK, and CAL immunoreactivities appeared as positive neuronal cell bodies, processes, and puncta. The matrix compartment at birth contained relatively low TH-immunoreactive processes and few SP-positive neurons but was densely populated with LENK-immunoreactive neurons. The nucleus accumbens part of the ventral striatum also showed prominent differences in SP, LENK, and CAL immunoreactivities in shell and core territories. During 12 months of postnatal maturation salient changes occurred in neurotransmitter marker localization: TH-positive afferents densely innervated the matrix to exceed levels of immunoreactivity in the striosomes; SP immunoreactivity levels increased in the matrix; and LENK-immunoreactivity levels decreased in the matrix and increased in the striosomes. At 12 months of age, striatal chemoarchitecture was similar qualitatively to adult patterns, but quantitatively different in LENK and SP in caudate, putamen, and nucleus accumbens. This study shows for the first time that the rhesus monkey striatum requires more than 12 months after birth to develop an adult-like pattern of chemical neuroanatomy and that principal neurons within striosomes and matrix have different developmental programs for neuropeptide expression. We conclude that postnatal maturation of the striatal mosaic in primates is not static but, rather, is a protracted and dynamic process that requires many synchronous and compartment-selective changes in afferent innervation and in the expression of genes that regulate neuronal phenotypes. PMID:25294985

Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

Warm-up with weighted bat and adjustment of upper limb muscle activity in bat swinging under movement correction conditions.

PubMed

Ohta, Yoichi; Ishii, Yasumitsu; Ikudome, Sachi; Nakamoto, Hiroki

2014-02-01

The effects of weighted bat warm-up on adjustment of upper limb muscle activity were investigated during baseball bat swinging under dynamic conditions that require a spatial and temporal adjustment of the swinging to hit a moving target. Seven male college baseball players participated in this study. Using a batting simulator, the task was to swing the standard bat coincident with the arrival timing and position of a moving target after three warm-up swings using a standard or weighted bat. There was no significant effect of weighted bat warm-up on muscle activity before impact associated with temporal or spatial movement corrections. However, lower inhibition of the extensor carpi ulnaris muscle activity was observed in a velocity-changed condition in the weighted bat warm-up, as compared to a standard bat warm-up. It is suggested that weighted bat warm-up decreases the adjustment ability associated with inhibition of muscle activation under movement correction conditions.

When Height Carries Weight: Communicating Hidden Object Properties for Joint Action.

PubMed

Schmitz, Laura; Vesper, Cordula; Sebanz, Natalie; Knoblich, Günther

2018-06-24

In the absence of pre-established communicative conventions, people create novel communication systems to successfully coordinate their actions toward a joint goal. In this study, we address two types of such novel communication systems: sensorimotor communication, where the kinematics of instrumental actions are systematically modulated, versus symbolic communication. We ask which of the two systems co-actors preferentially create when aiming to communicate about hidden object properties such as weight. The results of three experiments consistently show that actors who knew the weight of an object transmitted this weight information to their uninformed co-actors by systematically modulating their instrumental actions, grasping objects of particular weights at particular heights. This preference for sensorimotor communication was reduced in a fourth experiment where co-actors could communicate with weight-related symbols. Our findings demonstrate that the use of sensorimotor communication extends beyond the communication of spatial locations to non-spatial, hidden object properties. © 2018 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Spatializing health research: what we know and where we are heading

PubMed Central

Yang, Tse-Chuan; Shoff, Carla; Noah, Aggie J.

2013-01-01

Beyond individual-level factors, researchers have adopted a spatial perspective to explore potentially modifiable environmental determinants of health. A spatial perspective can be integrated into health research by incorporating spatial data into studies or analyzing georeferenced data. Given the rapid changes in data collection methods and the complex dynamics between individuals and environment, we argue that GIS functions have shortcomings with respect to analytical capability and are limited when it comes to visualizing the temporal component in spatio-temporal data. In addition, we maintain that relatively little effort has been made to handle spatial heterogeneity. To that end, health researchers should be persuaded to better justify the theoretical meaning underlying the spatial matrix in analysis, while spatial data collectors, GIS specialists, spatial analysis methodologists, and the different breeds of users should be encouraged to work together making health research move forward through addressing these issues. PMID:23733281

A new third order finite volume weighted essentially non-oscillatory scheme on tetrahedral meshes

NASA Astrophysics Data System (ADS)

Zhu, Jun; Qiu, Jianxian

2017-11-01

In this paper a third order finite volume weighted essentially non-oscillatory scheme is designed for solving hyperbolic conservation laws on tetrahedral meshes. Comparing with other finite volume WENO schemes designed on tetrahedral meshes, the crucial advantages of such new WENO scheme are its simplicity and compactness with the application of only six unequal size spatial stencils for reconstructing unequal degree polynomials in the WENO type spatial procedures, and easy choice of the positive linear weights without considering the topology of the meshes. The original innovation of such scheme is to use a quadratic polynomial defined on a big central spatial stencil for obtaining third order numerical approximation at any points inside the target tetrahedral cell in smooth region and switch to at least one of five linear polynomials defined on small biased/central spatial stencils for sustaining sharp shock transitions and keeping essentially non-oscillatory property simultaneously. By performing such new procedures in spatial reconstructions and adopting a third order TVD Runge-Kutta time discretization method for solving the ordinary differential equation (ODE), the new scheme's memory occupancy is decreased and the computing efficiency is increased. So it is suitable for large scale engineering requirements on tetrahedral meshes. Some numerical results are provided to illustrate the good performance of such scheme.

High and low molecular weight hyaluronic acid differentially influence macrophage activation

PubMed Central

Rayahin, Jamie E.; Buhrman, Jason S.; Zhang, Yu; Koh, Timothy J.; Gemeinhart, Richard A.

2015-01-01

Macrophages exhibit phenotypic diversity permitting wide-ranging roles in maintaining physiologic homeostasis. Hyaluronic acid, a major glycosaminoglycan of the extracellular matrix, has been shown to have differential signaling based on its molecular weight. With this in mind, the main objective of this study was to elucidate the role of hyaluronic acid molecular weight on macrophage activation and reprogramming. Changes in macrophage activation were assessed by activation state selective marker measurement, specifically quantitative real time polymerase chain reaction, and cytokine enzyme-linked immunoassays, after macrophage treatment with differing molecular weights of hyaluronic acid under four conditions: the resting state, concurrent with classical activation, and following inflammation involving either classically or alternatively activated macrophages. Regardless of initial polarization state, low molecular weight hyaluronic acid induced a classically activated-like state, confirmed by up-regulation of pro-inflammatory genes, including nos2, tnf, il12b, and cd80, and enhanced secretion of nitric oxide and TNF-α. High molecular weight hyaluronic acid promoted an alternatively activated-like state, confirmed by up regulation of pro-resolving gene transcription, including arg1, il10, and mrc1, and enhanced arginase activity. Overall, our observations suggest that macrophages undergo phenotypic changes dependent on molecular weight of hyaluronan that correspond to either (1) pro-inflammatory response for low molecular weight HA or (2) pro-resolving response for high molecular weight HA. These observations bring significant further understanding of the influence of extracellular matrix polymers, hyaluronic acid in particular, on regulating the inflammatory response of macrophages. This knowledge can be used to guide the design of HA-containing biomaterials to better utilize the natural response to HAs. PMID:26280020

Identifying areas at risk of low birth weight using spatial epidemiology: A small area surveillance study.

PubMed

Insaf, Tabassum Z; Talbot, Thomas

2016-07-01

To assess the geographic distribution of Low Birth Weight (LBW) in New York State among singleton births using a spatial regression approach in order to identify priority areas for public health actions. LBW was defined as birth weight less than 2500g. Geocoded data from 562,586 birth certificates in New York State (years 2008-2012) were merged with 2010 census data at the tract level. To provide stable estimates and maintain confidentiality, data were aggregated to yield 1268 areas of analysis. LBW prevalence among singleton births was related with area-level behavioral, socioeconomic and demographic characteristics using a Poisson mixed effects spatial error regression model. Observed low birth weight showed statistically significant auto-correlation in our study area (Moran's I 0.16 p value 0.0005). After over-dispersion correction and accounting for fixed effects for selected social determinants, spatial autocorrelation was fully accounted for (Moran's I-0.007 p value 0.241). The proportion of LBW was higher in areas with larger Hispanic or Black populations and high smoking prevalence. Smoothed maps with predicted prevalence were developed to identify areas at high risk of LBW. Spatial patterns of residual variation were analyzed to identify unique risk factors. Neighborhood racial composition contributes to disparities in LBW prevalence beyond differences in behavioral and socioeconomic factors. Small-area analyses of LBW can identify areas for targeted interventions and display unique local patterns that should be accounted for in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

User's Guide for ERB 7 Matrix. Volume 1: Experiment Description and Quality Control Report for Year 1

NASA Technical Reports Server (NTRS)

Tighe, R. J.; Shen, M. Y. H.

1984-01-01

The Nimbus 7 ERB MATRIX Tape is a computer program in which radiances and irradiances are converted into fluxes which are used to compute the basic scientific output parameters, emitted flux, albedo, and net radiation. They are spatially averaged and presented as time averages over one-day, six-day, and monthly periods. MATRIX data for the period November 16, 1978 through October 31, 1979 are presented. Described are the Earth Radiation Budget experiment, the Science Quality Control Report, Items checked by the MATRIX Science Quality Control Program, and Science Quality Control Data Analysis Report. Additional material from the detailed scientific quality control of the tapes which may be very useful to a user of the MATRIX tapes is included. Known errors and data problems and some suggestions on how to use the data for further climatologic and atmospheric physics studies are also discussed.

Matrix-free mass spectrometric imaging using laser desorption ionisation Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Goodwin, Richard J A; Pitt, Andrew R; Harrison, David; Weidt, Stefan K; Langridge-Smith, Pat R R; Barrett, Michael P; Logan Mackay, C

2011-04-15

Mass spectrometry imaging (MSI) is a powerful tool in metabolomics and proteomics for the spatial localization and identification of pharmaceuticals, metabolites, lipids, peptides and proteins in biological tissues. However, sample preparation remains a crucial variable in obtaining the most accurate distributions. Common washing steps used to remove salts, and solvent-based matrix application, allow analyte spreading to occur. Solvent-free matrix applications can reduce this risk, but increase the possibility of ionisation bias due to matrix adhesion to tissue sections. We report here the use of matrix-free MSI using laser desorption ionisation performed on a 12 T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. We used unprocessed tissue with no post-processing following thaw-mounting on matrix-assisted laser desorption ionisation (MALDI) indium-tin oxide (ITO) target plates. The identification and distribution of a range of phospholipids in mouse brain and kidney sections are presented and compared with previously published MALDI time-of-flight (TOF) MSI distributions. Copyright © 2011 John Wiley & Sons, Ltd.

Laser-based methods for the analysis of low molecular weight compounds in biological matrices.

PubMed

Kiss, András; Hopfgartner, Gérard

2016-07-15

Laser-based desorption and/or ionization methods play an important role in the field of the analysis of low molecular-weight compounds (LMWCs) because they allow direct analysis with high-throughput capabilities. In the recent years there were several new improvements in ionization methods with the emergence of novel atmospheric ion sources such as laser ablation electrospray ionization or laser diode thermal desorption and atmospheric pressure chemical ionization and in sample preparation methods with the development of new matrix compounds for matrix-assisted laser desorption/ionization (MALDI). Also, the combination of ion mobility separation with laser-based ionization methods starts to gain popularity with access to commercial systems. These developments have been driven mainly by the emergence of new application fields such as MS imaging and non-chromatographic analytical approaches for quantification. This review aims to present these new developments in laser-based methods for the analysis of low-molecular weight compounds by MS and several potential applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Nanostructured solid substrates for efficient laser desorption/ionization mass spectrometry (LDI-MS) of low molecular weight compounds.

PubMed

Silina, Yuliya E; Volmer, Dietrich A

2013-12-07

Analytical applications often require rapid measurement of compounds from complex sample mixtures. High-speed mass spectrometry approaches frequently utilize techniques based on direct ionization of the sample by laser irradiation, mostly by means of matrix-assisted laser desorption/ionization (MALDI). Compounds of low molecular weight are difficult to analyze by MALDI, however, because of severe interferences in the low m/z range from the organic matrix used for desorption/ionization. In recent years, surface-assisted laser desorption/ionization (SALDI) techniques have shown promise for small molecule analysis, due to the unique properties of nanostructured surfaces, in particular, the lack of a chemical background in the low m/z range and enhanced production of analyte ions by SALDI. This short review article presents a summary of the most promising recent developments in SALDI materials for MS analysis of low molecular weight analytes, with emphasis on nanostructured materials based on metals and semiconductors.

αAMG based on Weighted Matching for Systems of Elliptic PDEs Arising From Displacement and Mixed Methods

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

D'Ambra, P.; Vassilevski, P. S.

2014-05-30

Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG) are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near-null kernel of the underlined matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aimed to obtain a composite solver with a desired convergence rate. Each new multigrid component relies on a current (general) smooth vector and exploits pairwise aggregation based on weighted matching in a matrix graph to define a new automatic, general-purpose coarsening process, which we refer to as “the compatible weighted matching”. Inmore » this work, we present results that broaden the applicability of our method to different finite element discretizations of elliptic PDEs. In particular, we consider systems arising from displacement methods in linear elasticity problems and saddle-point systems that appear in the application of the mixed method to Darcy problems.« less

Performance of hybrid nano-micro reinforced mg metal matrix composites brake calliper: simulation approach

NASA Astrophysics Data System (ADS)

Fatchurrohman, N.; Chia, S. T.

2017-10-01

Most commercial vehicles use brake calliper made of grey cast iron (GCI) which possesses heavy weight. This contributes to the total weight of the vehicle which can lead to higher fuel consumption. Another major problem is GCI calliper tends to deflect during clamping action, known as “bending of bridge”. This will result in extended pedal travel. Magnesium metal matrix composites (Mg-MMC) has a potential application in the automotive industry since it having a lower density, higher strength and very good modulus of elasticity as compared to GCI. This paper proposed initial development of hybrid Mg-MMC brake calliper. This was achieved by analyzing the performance of hybrid nano-micro reinforced Mg-MMC and comparing with the conventional GCI brake calliper. It was performed using simulation in ANSYS, a finite element analysis (FEA) software. The results show that hybrid Mg-MMC has better performance in terms of reduction the weight of the brake calliper, reduction in total deformation/deflection and better ability to withstand equivalent elastic strain.

Designing dairy desserts for weight management: Structure, physical properties and in vitro gastric digestion.

PubMed

Borreani, Jennifer; Llorca, Empar; Quiles, Amparo; Hernando, Isabel

2017-04-01

The first aim of this study was to observe the effect of adding dairy proteins and reducing the cream content in order to obtain healthier dairy desserts for use in weight management. The extra-whey protein low-cream sample had the densest, firmest matrix, which is related to increased satiety. The second aim was to investigate the in vitro gastric digestion behavior of whey and casein proteins in a heat-treated semisolid real food. The extra-casein protein sample matrix broke down more slowly than the others because the caseins clotted at the gastric pH. Despite being heated, the whey proteins in the panna cottas were more resistant to pepsin digestion than caseins; this is related with a higher satiety capacity. These findings suggest that the combination of reducing fat content (to obtain a reduced energy density product) and adding whey protein (to increase satiety capacity) allows obtaining dairy desserts for weight management. Copyright © 2016 Elsevier Ltd. All rights reserved.

A fast new algorithm for a robot neurocontroller using inverse QR decomposition

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

Morris, A.S.; Khemaissia, S.

2000-01-01

A new adaptive neural network controller for robots is presented. The controller is based on direct adaptive techniques. Unlike many neural network controllers in the literature, inverse dynamical model evaluation is not required. A numerically robust, computationally efficient processing scheme for neutral network weight estimation is described, namely, the inverse QR decomposition (INVQR). The inverse QR decomposition and a weighted recursive least-squares (WRLS) method for neural network weight estimation is derived using Cholesky factorization of the data matrix. The algorithm that performs the efficient INVQR of the underlying space-time data matrix may be implemented in parallel on a triangular array.more » Furthermore, its systolic architecture is well suited for VLSI implementation. Another important benefit is well suited for VLSI implementation. Another important benefit of the INVQR decomposition is that it solves directly for the time-recursive least-squares filter vector, while avoiding the sequential back-substitution step required by the QR decomposition approaches.« less

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.

Low-Cost Resin Transfer Molding Process Developed for High-Temperature Polyimide Matrix Composites

NASA Technical Reports Server (NTRS)

1996-01-01

The use of high-temperature polymer matrix composites (PMC's) in aircraft engine applications can significantly reduce engine weight and improve performance and fuel efficiency. High-temperature PMC's, such as those based on the PMR-15 polyimide matrix resin developed by the NASA Lewis Research Center, have been used extensively in military applications where performance improvements have justified their use regardless of the cost involved in producing the component. However, in commercial engines cost is a primary driver, and PMC components must be produced at costs comparable to those of the metal components that they will replace.

An experimental SMI adaptive antenna array simulator for weak interfering signals

NASA Technical Reports Server (NTRS)

Dilsavor, Ronald S.; Gupta, Inder J.

1991-01-01

An experimental sample matrix inversion (SMI) adaptive antenna array for suppressing weak interfering signals is described. The experimental adaptive array uses a modified SMI algorithm to increase the interference suppression. In the modified SMI algorithm, the sample covariance matrix is redefined to reduce the effect of thermal noise on the weights of an adaptive array. This is accomplished by subtracting a fraction of the smallest eigenvalue of the original covariance matrix from its diagonal entries. The test results obtained using the experimental system are compared with theoretical results. The two show a good agreement.

Method and Apparatus for Improved Spatial Light Modulation

NASA Technical Reports Server (NTRS)

Soutar, Colin (Inventor); Juday, Richard D. (Inventor)

2000-01-01

A method and apparatus for modulating a light beam in an optical processing system is described. Preferably, an electrically-controlled polarizer unit and/or an analyzer unit are utilized in combination with a spatial light modulator and a controller. Preferably, the spatial light modulator comprises a pixelated birefringent medium such as a liquid crystal video display. The combination of the electrically controlled polarizer unit and analyzer unit make it simple and fast to reconfigure the modulation described by the Jones matrix of the spatial light modulator. A particular optical processing objective is provided to the controller. The controller performs calculations and supplies control signals to the polarizer unit, the analyzer unit, and the spatial light modulator in order to obtain the optical processing objective.

Method and Apparatus for Improved Spatial Light Modulation

NASA Technical Reports Server (NTRS)

Colin, Soutar (Inventor); Juday, Richard D. (Inventor)

1999-01-01

A method and apparatus for modulating a light beam in an optical processing system is described. Preferably, an electrically-controlled polarizer unit and/or an analyzer unit are utilized in combination with a spatial light modulator and a controller. Preferably, the spatial light modulator comprises a pixelated birefringent medium such as a liquid crystal video display. The combination of the electrically controlled polarizer unit and analyzer unit make it simple and fast to reconfigure the modulation described by the Jones matrix of the spatial light modulator. A particular optical processing objective is provided to the controller. The controller performs calculations and supplies control signals to the polarizer unit, the analyzer unit, and the spatial light modulator in order to obtain die optical processing objective.

3D ToF-SIMS Analysis of Peptide Incorporation into MALDI Matrix Crystals with Sub-micrometer Resolution.

PubMed

Körsgen, Martin; Pelster, Andreas; Dreisewerd, Klaus; Arlinghaus, Heinrich F

2016-02-01

The analytical sensitivity in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is largely affected by the specific analyte-matrix interaction, in particular by the possible incorporation of the analytes into crystalline MALDI matrices. Here we used time-of-flight secondary ion mass spectrometry (ToF-SIMS) to visualize the incorporation of three peptides with different hydrophobicities, bradykinin, Substance P, and vasopressin, into two classic MALDI matrices, 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (HCCA). For depth profiling, an Ar cluster ion beam was used to gradually sputter through the matrix crystals without causing significant degradation of matrix or biomolecules. A pulsed Bi3 ion cluster beam was used to image the lateral analyte distribution in the center of the sputter crater. Using this dual beam technique, the 3D distribution of the analytes and spatial segregation effects within the matrix crystals were imaged with sub-μm resolution. The technique could in the future enable matrix-enhanced (ME)-ToF-SIMS imaging of peptides in tissue slices at ultra-high resolution. Graphical Abstract ᅟ.

3D ToF-SIMS Analysis of Peptide Incorporation into MALDI Matrix Crystals with Sub-micrometer Resolution

NASA Astrophysics Data System (ADS)

Körsgen, Martin; Pelster, Andreas; Dreisewerd, Klaus; Arlinghaus, Heinrich F.

2016-02-01

The analytical sensitivity in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is largely affected by the specific analyte-matrix interaction, in particular by the possible incorporation of the analytes into crystalline MALDI matrices. Here we used time-of-flight secondary ion mass spectrometry (ToF-SIMS) to visualize the incorporation of three peptides with different hydrophobicities, bradykinin, Substance P, and vasopressin, into two classic MALDI matrices, 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (HCCA). For depth profiling, an Ar cluster ion beam was used to gradually sputter through the matrix crystals without causing significant degradation of matrix or biomolecules. A pulsed Bi3 ion cluster beam was used to image the lateral analyte distribution in the center of the sputter crater. Using this dual beam technique, the 3D distribution of the analytes and spatial segregation effects within the matrix crystals were imaged with sub-μm resolution. The technique could in the future enable matrix-enhanced (ME)-ToF-SIMS imaging of peptides in tissue slices at ultra-high resolution.

Streptococcus mutans-derived extracellular matrix in cariogenic oral biofilms.

PubMed

Klein, Marlise I; Hwang, Geelsu; Santos, Paulo H S; Campanella, Osvaldo H; Koo, Hyun

2015-01-01

Biofilms are highly structured microbial communities that are enmeshed in a self-produced extracellular matrix. Within the complex oral microbiome, Streptococcus mutans is a major producer of extracellular polymeric substances including exopolysaccharides (EPS), eDNA, and lipoteichoic acid (LTA). EPS produced by S. mutans-derived exoenzymes promote local accumulation of microbes on the teeth, while forming a spatially heterogeneous and diffusion-limiting matrix that protects embedded bacteria. The EPS-rich matrix provides mechanical stability/cohesiveness and facilitates the creation of highly acidic microenvironments, which are critical for the pathogenesis of dental caries. In parallel, S. mutans also releases eDNA and LTA, which can contribute with matrix development. eDNA enhances EPS (glucan) synthesis locally, increasing the adhesion of S. mutans to saliva-coated apatitic surfaces and the assembly of highly cohesive biofilms. eDNA and other extracellular substances, acting in concert with EPS, may impact the functional properties of the matrix and the virulence of cariogenic biofilms. Enhanced understanding about the assembly principles of the matrix may lead to efficacious approaches to control biofilm-related diseases.

Streptococcus mutans-derived extracellular matrix in cariogenic oral biofilms

PubMed Central

Klein, Marlise I.; Hwang, Geelsu; Santos, Paulo H. S.; Campanella, Osvaldo H.; Koo, Hyun

2015-01-01

Biofilms are highly structured microbial communities that are enmeshed in a self-produced extracellular matrix. Within the complex oral microbiome, Streptococcus mutans is a major producer of extracellular polymeric substances including exopolysaccharides (EPS), eDNA, and lipoteichoic acid (LTA). EPS produced by S. mutans-derived exoenzymes promote local accumulation of microbes on the teeth, while forming a spatially heterogeneous and diffusion-limiting matrix that protects embedded bacteria. The EPS-rich matrix provides mechanical stability/cohesiveness and facilitates the creation of highly acidic microenvironments, which are critical for the pathogenesis of dental caries. In parallel, S. mutans also releases eDNA and LTA, which can contribute with matrix development. eDNA enhances EPS (glucan) synthesis locally, increasing the adhesion of S. mutans to saliva-coated apatitic surfaces and the assembly of highly cohesive biofilms. eDNA and other extracellular substances, acting in concert with EPS, may impact the functional properties of the matrix and the virulence of cariogenic biofilms. Enhanced understanding about the assembly principles of the matrix may lead to efficacious approaches to control biofilm-related diseases. PMID:25763359

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Body weight of hypersonic aircraft, part 1

NASA Technical Reports Server (NTRS)

Ardema, Mark D.

1988-01-01

The load bearing body weight of wing-body and all-body hypersonic aircraft is estimated for a wide variety of structural materials and geometries. Variations of weight with key design and configuration parameters are presented and discussed. Both hot and cool structure approaches are considered in isotropic, organic composite, and metal matrix composite materials; structural shells are sandwich or skin-stringer. Conformal and pillow-tank designs are investigated for the all-body shape. The results identify the most promising hypersonic aircraft body structure design approaches and their weight trends. Geometric definition of vehicle shapes and structural analysis methods are presented in appendices.

Distributed multi-criteria model evaluation and spatial association analysis

NASA Astrophysics Data System (ADS)

Scherer, Laura; Pfister, Stephan

2015-04-01

Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the high spatial association with the aridity index (ratio of mean annual precipitation to mean annual potential evapotranspiration). This association was still significant when controlling for slopes which manifested the second highest spatial association. In line with these findings, overall model efficiency of the entire Mississippi watershed appeared better when weighted with mean observed river discharge. Furthermore, the model received the highest rating with regards to PBIAS and was judged worst when considering NSE as the most comprehensive indicator. No universal performance indicator exists that considers all aspects of a hydrograph. Therefore, sound model evaluation must take into account multiple criteria. Since model efficiency varies in space which is masked by aggregated ratings spatially explicit model goodness should be communicated as standard praxis - at least as a measure of spatial variability of indicators. Furthermore, transparent documentation of the evaluation procedure also with regards to weighting of aggregated model performance is crucial but often lacking in published research. Finally, the high spatial association between model performance and aridity highlights the need to improve modelling schemes for arid conditions as priority over other aspects that might weaken model goodness.

More box codes

NASA Technical Reports Server (NTRS)

Solomon, G.

1992-01-01

A new investigation shows that, starting from the BCH (21,15;3) code represented as a 7 x 3 matrix and adding a row and column to add even parity, one obtains an 8 x 4 matrix (32,15;8) code. An additional dimension is obtained by specifying odd parity on the rows and even parity on the columns, i.e., adjoining to the 8 x 4 matrix, the matrix, which is zero except for the fourth column (of all ones). Furthermore, any seven rows and three columns will form the BCH (21,15;3) code. This box code has the same weight structure as the quadratic residue and BCH codes of the same dimensions. Whether there exists an algebraic isomorphism to either code is as yet unknown.

Empirical State Error Covariance Matrix for Batch Estimation

NASA Technical Reports Server (NTRS)

Frisbee, Joe

2015-01-01

State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the uncertainty in the estimated states. By a reinterpretation of the equations involved in the weighted batch least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. The proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. This empirical error covariance matrix may be calculated as a side computation for each unique batch solution. Results based on the proposed technique will be presented for a simple, two observer and measurement error only problem.

Electrolyte matrix for molten carbonate fuel cells

DOEpatents

Huang, C.M.; Yuh, C.Y.

1999-02-09

A matrix is described for a carbonate electrolyte including a support material and an additive constituent having a relatively low melting temperature and a relatively high coefficient of thermal expansion. The additive constituent is from 3 to 45 weight percent of the matrix and is formed from raw particles whose diameter is in a range of 0.1 {micro}m to 20 {micro}m and whose aspect ratio is in a range of 1 to 50. High energy intensive milling is used to mix the support material and additive constituent during matrix formation. Also disclosed is the use of a further additive constituent comprising an alkaline earth containing material. The further additive is mixed with the support material using high energy intensive milling. 5 figs.

Electrolyte matrix for molten carbonate fuel cells

DOEpatents

Huang, Chao M.; Yuh, Chao-Yi

1999-01-01

A matrix for a carbonate electrolyte including a support material and an additive constituent having a relatively low melting temperature and a relatively high coefficient of thermal expansion. The additive constituent is from 3 to 45 weight percent of the matrix and is formed from raw particles whose diameter is in a range of 0.1 .mu.m to 20 .mu.m and whose aspect ratio is in a range of 1 to 50. High energy intensive milling is used to mix the support material and additive constituent during matrix formation. Also disclosed is the use of a further additive constituent comprising an alkaline earth containing material. The further additive is mixed with the support material using high energy intensive milling.

1,2-diketones promoted degradation of poly(epsilon-caprolactone)

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

Danko, Martin; Borska, Katarina; Ragab, Sherif Shaban

2012-07-11

Photochemical reactions of Benzil and Camphorquinone were used for modification of poly({epsilon}-caprolactone) polymer films. Photochemistry of dopants was followed by infrared spectroscopy, changes on polymer chains of matrix were followed by gel permeation chromatography. Benzoyl peroxide was efficiently photochemically generated from benzyl in solid polymer matrix in the presence of air. Following decomposition of benzoyl peroxide led to degradation of matrix. Photochemical transformation of benzil in vacuum led to hydrogen abstraction from the polymer chains in higher extent, which resulted to chains recombination and formation of gel. Photochemical transformation of camphorquinone to corresponding camphoric peroxide was not observed. Only decreasemore » of molecular weight of polymer matrix doped with camphorquinone was observed during the irradiation.« less

Relationship between diffusivity of water molecules inside hydrating tablets and their drug release behavior elucidated by magnetic resonance imaging.

PubMed

Kikuchi, Shingo; Onuki, Yoshinori; Kuribayashi, Hideto; Takayama, Kozo

2012-01-01

We reported previously that sustained release matrix tablets showed zero-order drug release without being affected by pH change. To understand drug release mechanisms more fully, we monitored the swelling and erosion of hydrating tablets using magnetic resonance imaging (MRI). Three different types of tablets comprised of polyion complex-forming materials and a hydroxypropyl methylcellulose (HPMC) were used. Proton density- and diffusion-weighted images of the hydrating tablets were acquired at intervals. Furthermore, apparent self-diffusion coefficient maps were generated from diffusion-weighted imaging to evaluate the state of hydrating tablets. Our findings indicated that water penetration into polyion complex tablets was faster than that into HPMC matrix tablets. In polyion complex tablets, water molecules were dispersed homogeneously and their diffusivity was relatively high, whereas in HPMC matrix tablets, water molecule movement was tightly restricted within the gel. An optimal tablet formulation determined in a previous study had water molecule penetration and diffusivity properties that appeared intermediate to those of polyion complex and HPMC matrix tablets; water molecules were capable of penetrating throughout the tablets and relatively high diffusivity was similar to that in the polyion complex tablet, whereas like the HPMC matrix tablet, it was well swollen. This study succeeded in characterizing the tablet hydration process. MRI provides profound insight into the state of water molecules in hydrating tablets; thus, it is a useful tool for understanding drug release mechanisms at a molecular level.

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.

Alternative CHCA-based matrices for the analysis of low molecular weight compounds by UV-MALDI-tandem mass spectrometry.

PubMed

Porta, Tiffany; Grivet, Chantal; Knochenmuss, Richard; Varesio, Emmanuel; Hopfgartner, Gérard

2011-02-01

Analysis of low molecular weight compounds (LMWC) in complex matrices by vacuum matrix-assisted laser desorption/ionization (MALDI) often suffers from matrix interferences, which can severely degrade limits of quantitation. It is, therefore, useful to have available a range of suitable matrices, which exhibit complementary regions of interference. Two newly synthesized α-cyanocinnamic acid derivatives are reported here; (E)-2-cyano-3-(naphthalen-2-yl)acrylic acid (NpCCA) and (2E)-3-(anthracen-9-yl)-2-cyanoprop-2enoic acid (AnCCA). Along with the commonly used α-cyano-4-hydroxycinnamic acid (CHCA), and the recently developed 4-chloro-α-cyanocinnamic acid (Cl-CCA) matrices, these constitute a chemically similar series of matrices covering a range of molecular weights, and with correspondingly differing ranges of spectral interference. Their performance was compared by measuring the signal-to-noise ratios (S/N) of 47 analytes, mostly pharmaceuticals, with the different matrices using the selected reaction monitoring (SRM) mode on a triple quadrupole instrument equipped with a vacuum MALDI source. AnCCA, NpCCA and Cl-CCA were found to offer better signal-to-noise ratios in SRM mode than CHCA, but Cl-CCA yielded the best results for 60% of the compounds tested. To better understand the relative performance of this matrix series, the proton affinities (PAs) were measured using the kinetic method. Their relative values were: AnCCA > CHCA > NpCCA > Cl-CCA. This ordering is consistent with the performance data. The synthesis of the new matrices is straightforward and they provide (1) tunability of matrix background interfering ions and (2) enhanced analyte response for certain classes of compounds. Copyright © 2011 John Wiley & Sons, Ltd.

Schema vs. primitive perceptual grouping: the relative weighting of sequential vs. spatial cues during an auditory grouping task in frogs.

PubMed

Farris, Hamilton E; Ryan, Michael J

2017-03-01

Perceptually, grouping sounds based on their sources is critical for communication. This is especially true in túngara frog breeding aggregations, where multiple males produce overlapping calls that consist of an FM 'whine' followed by harmonic bursts called 'chucks'. Phonotactic females use at least two cues to group whines and chucks: whine-chuck spatial separation and sequence. Spatial separation is a primitive cue, whereas sequence is schema-based, as chuck production is morphologically constrained to follow whines, meaning that males cannot produce the components simultaneously. When one cue is available, females perceptually group whines and chucks using relative comparisons: components with the smallest spatial separation or those closest to the natural sequence are more likely grouped. By simultaneously varying the temporal sequence and spatial separation of a single whine and two chucks, this study measured between-cue perceptual weighting during a specific grouping task. Results show that whine-chuck spatial separation is a stronger grouping cue than temporal sequence, as grouping is more likely for stimuli with smaller spatial separation and non-natural sequence than those with larger spatial separation and natural sequence. Compared to the schema-based whine-chuck sequence, we propose that spatial cues have less variance, potentially explaining their preferred use when grouping during directional behavioral responses.

Random matrix theory filters and currency portfolio optimisation

NASA Astrophysics Data System (ADS)

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

2010-04-01

Random matrix theory (RMT) filters have recently been shown to improve the optimisation of financial portfolios. This paper studies the effect of three RMT filters on realised portfolio risk, using bootstrap analysis and out-of-sample testing. We considered the case of a foreign exchange and commodity portfolio, weighted towards foreign exchange, and consisting of 39 assets. This was intended to test the limits of RMT filtering, which is more obviously applicable to portfolios with larger numbers of assets. We considered both equally and exponentially weighted covariance matrices, and observed that, despite the small number of assets involved, RMT filters reduced risk in a way that was consistent with a much larger S&P 500 portfolio. The exponential weightings indicated showed good consistency with the value suggested by Riskmetrics, in contrast to previous results involving stocks. This decay factor, along with the low number of past moves preferred in the filtered, equally weighted case, displayed a trend towards models which were reactive to recent market changes. On testing portfolios with fewer assets, RMT filtering provided less or no overall risk reduction. In particular, no long term out-of-sample risk reduction was observed for a portfolio consisting of 15 major currencies and commodities.

Considerations in high resolution skeletal muscle DTI using single-shot EPI with stimulated echo preparation and SENSE

PubMed Central

Karampinos, Dimitrios C.; Banerjee, Suchandrima; King, Kevin F.; Link, Thomas M.; Majumdar, Sharmila

2011-01-01

Previous studies have shown that skeletal muscle diffusion tensor imaging (DTI) can non-invasively probe changes in the muscle fiber architecture and microstructure in diseased and damaged muscles. However, DTI fiber reconstruction in small muscles and in muscle regions close to aponeuroses and tendons remains challenging because of partial volume effects. Increasing the spatial resolution of skeletal muscle single-shot diffusion weighted (DW)-EPI can be hindered by the inherently low SNR of muscle DW-EPI due to the short muscle T2 and the high sensitivity of single-shot EPI to off-resonance effects and T2* blurring. In the present work, eddy-current compensated diffusion-weighted stimulated echo preparation is combined with sensitivity encoding (SENSE) to maintain good SNR properties and reduce the sensitivity to distortions and T2* blurring in high resolution skeletal muscle single-shot DW-EPI. An analytical framework is developed for optimizing the reduction factor and diffusion weighting time to achieve maximum SNR. Arguments for the selection of the experimental parameters are then presented considering the compromise between SNR, B0-induced distortions, T2* blurring effects and tissue incoherent motion effects. Based on the selected parameters in a high resolution skeletal muscle single-shot DW-EPI protocol, imaging protocols at lower acquisition matrix sizes are defined with matched bandwidth in the phase-encoding direction and SNR. In vivo results show that high resolution skeletal muscle DTI with minimized sensitivity to geometric distortions and T2* blurring is feasible using the proposed methodology. In particular, a significant benefit is demonstrated from reducing partial volume effects on resolving multi-pennate muscles and muscles with small cross sections in calf muscle DTI. PMID:22081519