Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

PubMed

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

Xi jun, Gao; Zi li, Chen; Yong Jiang, Hu

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

Ground reaction force analysed with correlation coefficient matrix in group of stroke patients.

PubMed

Szczerbik, Ewa; Krawczyk, Maciej; Syczewska, Małgorzata

2014-01-01

Stroke is the third cause of death in contemporary society and causes many disorders. Clinical scales, ground reaction force (GRF) and objective gait analysis are used for assessment of patient's rehabilitation progress during treatment. The goal of this paper is to assess whether signal correlation coefficient matrix applied to GRF can be used for evaluation of the status of post-stroke patients. A group of patients underwent clinical assessment and instrumented gait analysis simultaneously three times. The difference between components of patient's GRF (vertical, fore/aft, med/lat) and normal ones (reference GRF of healthy subjects) was calculated as correlation coefficient. Patients were divided into two groups ("worse" and "better") based on the clinical functional scale tests done at the beginning of rehabilitation process. The results obtained by these two groups were compared using statistical analysis. An increase of median value of correlation coefficient is observed in all components of GRF, but only in non-paretic leg. Analysis of GRF signal can be helpful in assessment of post-stroke patients during rehabilitation. Improvement in stroke patients was observed in non-paretic leg of the "worse" group. GRF analysis should not be the only tool for objective validation of patient's improvement, but could be used as additional source of information.

Heat transfer and flow friction correlations for perforated plate matrix heat exchangers

NASA Astrophysics Data System (ADS)

Ratna Raju, L.; Kumar, S. Sunil; Chowdhury, K.; Nandi, T. K.

2017-02-01

Perforated plate matrix heat exchangers (MHE) are constructed of high conductivity perforated plates stacked alternately with low conductivity spacers. They are being increasingly used in many cryogenic applications including Claude cycle or Reversed Brayton cycle cryo-refrigerators and liquefiers. Design of high NTU (number of (heat) transfer unit) cryogenic MHEs requires accurate heat transfer coefficient and flow friction factor. Thermo-hydraulic behaviour of perforated plates strongly depends on the geometrical parameters. Existing correlations, however, are mostly expressed as functions of Reynolds number only. This causes, for a given configuration, significant variations in coefficients from one correlation to the other. In this paper we present heat transfer and flow friction correlations as functions of all geometrical and other controlling variables. A FluentTM based numerical model has been developed for heat transfer and pressure drop studies over a stack of alternately arranged perforated plates and spacers. The model is validated with the data from literature. Generalized correlations are obtained through regression analysis over a large number of computed data.

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

Zainodin, H. J.; Yap, S. J.

2013-09-01

Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.

Cross-Correlations and Structures of Aero-Engine Gas Path System Based on DCCA Coefficient and Rooted Tree

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Fan, Jie; Gao, You

2015-12-01

Identifying the mutual interaction is a crucial problem that facilitates the understanding of emerging structures in complex system. We here focus on aero-engine dynamic as an example of complex system. By applying the detrended cross-correlation analysis (DCCA) coefficient method to aero-engine gas path system, we find that the low-spool rotor speed (N1) and high-spool rotor speed (N2) fluctuation series exhibit cross-correlation characteristic. Further, we employ detrended cross-correlation coefficient matrix and rooted tree to investigate the mutual interactions of other gas path variables. The results can infer that the exhaust gas temperature (EGT), N1, N2, fuel flow (WF) and engine pressure ratio (EPR) are main gas path parameters.

Genetic diversity of popcorn genotypes using molecular analysis.

PubMed

Resh, F S; Scapim, C A; Mangolin, C A; Machado, M F P S; do Amaral, A T; Ramos, H C C; Vivas, M

2015-08-19

In this study, we analyzed dominant molecular markers to estimate the genetic divergence of 26 popcorn genotypes and evaluate whether using various dissimilarity coefficients with these dominant markers influences the results of cluster analysis. Fifteen random amplification of polymorphic DNA primers produced 157 amplified fragments, of which 65 were monomorphic and 92 were polymorphic. To calculate the genetic distances among the 26 genotypes, the complements of the Jaccard, Dice, and Rogers and Tanimoto similarity coefficients were used. A matrix of Dij values (dissimilarity matrix) was constructed, from which the genetic distances among genotypes were represented in a more simplified manner as a dendrogram generated using the unweighted pair-group method with arithmetic average. Clusters determined by molecular analysis generally did not group material from the same parental origin together. The largest genetic distance was between varieties 17 (UNB-2) and 18 (PA-091). In the identification of genotypes with the smallest genetic distance, the 3 coefficients showed no agreement. The 3 dissimilarity coefficients showed no major differences among their grouping patterns because agreement in determining the genotypes with large, medium, and small genetic distances was high. The largest genetic distances were observed for the Rogers and Tanimoto dissimilarity coefficient (0.74), followed by the Jaccard coefficient (0.65) and the Dice coefficient (0.48). The 3 coefficients showed similar estimations for the cophenetic correlation coefficient. Correlations among the matrices generated using the 3 coefficients were positive and had high magnitudes, reflecting strong agreement among the results obtained using the 3 evaluated dissimilarity coefficients.

Aggregation of carbon dioxide sequestration storage assessment units

USGS Publications Warehouse

Blondes, Madalyn S.; Schuenemeyer, John H.; Olea, Ricardo A.; Drew, Lawrence J.

2013-01-01

The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO2) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO2 in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO2 storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.

Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory.

PubMed

Heuett, William J; Beard, Daniel A; Qian, Hong

2008-05-15

Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA).

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.

Statistical properties of cross-correlation in the Korean stock market

NASA Astrophysics Data System (ADS)

Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

2011-01-01

We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S

2016-03-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

Random matrix approach to the dynamics of stock inventory variations

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Mu, Guo-Hua; Kertész, János

2012-09-01

It is well accepted that investors can be classified into groups owing to distinct trading strategies, which forms the basic assumption of many agent-based models for financial markets when agents are not zero-intelligent. However, empirical tests of these assumptions are still very rare due to the lack of order flow data. Here we adopt the order flow data of Chinese stocks to tackle this problem by investigating the dynamics of inventory variations for individual and institutional investors that contain rich information about the trading behavior of investors and have a crucial influence on price fluctuations. We find that the distributions of cross-correlation coefficient Cij have power-law forms in the bulk that are followed by exponential tails, and there are more positive coefficients than negative ones. In addition, it is more likely that two individuals or two institutions have a stronger inventory variation correlation than one individual and one institution. We find that the largest and the second largest eigenvalues (λ1 and λ2) of the correlation matrix cannot be explained by random matrix theory and the projections of investors' inventory variations on the first eigenvector u(λ1) are linearly correlated with stock returns, where individual investors play a dominating role. The investors are classified into three categories based on the cross-correlation coefficients CV R between inventory variations and stock returns. A strong Granger causality is unveiled from stock returns to inventory variations, which means that a large proportion of individuals hold the reversing trading strategy and a small part of individuals hold the trending strategy. Our empirical findings have scientific significance in the understanding of investors' trading behavior and in the construction of agent-based models for emerging stock markets.

Linear analysis near a steady-state of biochemical networks: Control analysis, correlation metrics and circuit theory

PubMed Central

Heuett, William J; Beard, Daniel A; Qian, Hong

2008-01-01

Background Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA). PMID:18482450

Photomask CD and LER characterization using Mueller matrix spectroscopic ellipsometry

NASA Astrophysics Data System (ADS)

Heinrich, A.; Dirnstorfer, I.; Bischoff, J.; Meiner, K.; Ketelsen, H.; Richter, U.; Mikolajick, T.

2014-10-01

Critical dimension and line edge roughness on photomask arrays are determined with Mueller matrix spectroscopic ellipsometry. Arrays with large sinusoidal perturbations are measured for different azimuth angels and compared with simulations based on rigorous coupled wave analysis. Experiment and simulation show that line edge roughness leads to characteristic changes in the different Mueller matrix elements. The influence of line edge roughness is interpreted as an increase of isotropic character of the sample. The changes in the Mueller matrix elements are very similar when the arrays are statistically perturbed with rms roughness values in the nanometer range suggesting that the results on the sinusoidal test structures are also relevant for "real" mask errors. Critical dimension errors and line edge roughness have similar impact on the SE MM measurement. To distinguish between both deviations, a strategy based on the calculation of sensitivities and correlation coefficients for all Mueller matrix elements is shown. The Mueller matrix elements M13/M31 and M34/M43 are the most suitable elements due to their high sensitivities to critical dimension errors and line edge roughness and, at the same time, to a low correlation coefficient between both influences. From the simulated sensitivities, it is estimated that the measurement accuracy has to be in the order of 0.01 and 0.001 for the detection of 1 nm critical dimension error and 1 nm line edge roughness, respectively.

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research.

PubMed

Waller, Niels G

2016-01-01

For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.

Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling

ERIC Educational Resources Information Center

Oort, Frans J.; Jak, Suzanne

2016-01-01

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Band selection method based on spectrum difference in targets of interest in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xiaohan; Yang, Guang; Yang, Yongbo; Huang, Junhua

2016-10-01

While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.

Erratum: Measurement of the electron charge asymmetry in $$\\boldsymbol{p\\bar{p}\\rightarrow W+X \\rightarrow e\

DOE PAGES

Abazov, Victor Mukhamedovich

2015-04-30

The recent paper on the charge asymmetry for electrons from W boson decay has an error in the Tables VII to XI that show the correlation coefficients of systematic uncertainties. Furthermore, the correlation matrix elements shown in the original publication were the square roots of the calculated values.

Visual Working Memory and Perception Speed of 3- to 6-Year-Old Children Tested with a Matrix Film Battery Test

ERIC Educational Resources Information Center

Pittorf, Martin L.; Lehmann, Wolfgang; Huckauf, Anke

2014-01-01

In this study the visual working memory (VWM) and perception speed of 60 children between the ages of three and six years were tested with an age-based, easy-to-handle Matrix Film Battery Test (reliability R?=?0.71). It was thereby affirmed that the VWM is age dependent (correlation coefficient r?=?0.66***) as expected. Furthermore, a significant…

Statistics of time delay and scattering correlation functions in chaotic systems. II. Semiclassical approximation

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

Novaes, Marcel

2015-06-15

We consider S-matrix correlation functions for a chaotic cavity having M open channels, in the absence of time-reversal invariance. Relying on a semiclassical approximation, we compute the average over E of the quantities Tr[S{sup †}(E − ϵ) S(E + ϵ)]{sup n}, for general positive integer n. Our result is an infinite series in ϵ, whose coefficients are rational functions of M. From this, we extract moments of the time delay matrix Q = − iħS{sup †}dS/dE and check that the first 8 of them agree with the random matrix theory prediction from our previous paper [M. Novaes, J. Math. Phys.more » 56, 062110 (2015)].« less

A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.

PubMed

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

2012-01-01

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

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Decomposing Time Series Data by a Non-negative Matrix Factorization Algorithm with Temporally Constrained Coefficients

PubMed Central

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

2017-01-01

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

Examination of the Chayes-Kruskal procedure for testing correlations between proportions

USGS Publications Warehouse

Kork, J.O.

1977-01-01

The Chayes-Kruskal procedure for testing correlations between proportions uses a linear approximation to the actual closure transformation to provide a null value, pij, against which an observed closed correlation coefficient, rij, can be tested. It has been suggested that a significant difference between pij and rij would indicate a nonzero covariance relationship between the ith and jth open variables. In this paper, the linear approximation to the closure transformation is described in terms of a matrix equation. Examination of the solution set of this equation shows that estimation of, or even the identification of, significant nonzero open correlations is essentially impossible even if the number of variables and the sample size are large. The method of solving the matrix equation is described in the appendix. ?? 1977 Plenum Publishing Corporation.

Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

PubMed Central

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

2016-01-01

This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

An experimental study on the noise correlation properties of CBCT projection data

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ouyang, Luo; Ma, Jianhua; Huang, Jing; Chen, Wufan; Wang, Jing

2014-03-01

In this study, we systematically investigated the noise correlation properties among detector bins of CBCT projection data by analyzing repeated projection measurements. The measurements were performed on a TrueBeam on-board CBCT imaging system with a 4030CB flat panel detector. An anthropomorphic male pelvis phantom was used to acquire 500 repeated projection data at six different dose levels from 0.1 mAs to 1.6 mAs per projection at three fixed angles. To minimize the influence of the lag effect, lag correction was performed on the consecutively acquired projection data. The noise correlation coefficient between detector bin pairs was calculated from the corrected projection data. The noise correlation among CBCT projection data was then incorporated into the covariance matrix of the penalized weighted least-squares (PWLS) criterion for noise reduction of low-dose CBCT. The analyses of the repeated measurements show that noise correlation coefficients are non-zero between the nearest neighboring bins of CBCT projection data. The average noise correlation coefficients for the first- and second- order neighbors are 0.20 and 0.06, respectively. The noise correlation coefficients are independent of the dose level. Reconstruction of the pelvis phantom shows that the PWLS criterion with consideration of noise correlation results in a lower noise level as compared to the PWLS criterion without considering the noise correlation at the matched resolution.

DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS.

PubMed

Ling, Ling; Li, Ying; Wang, Sheng; Guo, Liming; Xiao, Chunsheng; Chen, Xuesi; Guo, Xinhua

2018-04-01

Matrix interference ions in low mass range has always been a concern when using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze small molecules (<500 Da). In this work, a novel matrix, N1,N4-dibenzylidenebenzene-1,4-diamine (DBDA) was synthesized for the analyses of small molecules by negative ion MALDI-TOF MS. Notably, only neat ions ([M-H] - ) of fatty acids without matrix interference appeared in the mass spectra and the limit of detection (LOD) reached 0.3 fmol. DBDA also has great performance towards other small molecules such as amino acids, peptides, and nucleotide. Furthermore, with this novel matrix, the free fatty acids in serum were quantitatively analyzed based on the correlation curves with correlation coefficient of 0.99. In addition, UV-Vis experiments and molecular orbital calculations were performed to explore mechanism about DBDA used as matrix in the negative ion mode. The present work shows that the DBDA matrix is a highly sensitive matrix with few interference ions for analysis of small molecules. Meanwhile, DBDA is able to precisely quantify the fatty acids in real biological samples. Graphical Abstract ᅟ.

EMMPRIN and its ligand cyclophilin A as novel diagnostic markers in inflammatory cardiomyopathy.

PubMed

Seizer, Peter; Geisler, Tobias; Bigalke, Boris; Schneider, Martin; Klingel, Karin; Kandolf, Reinhard; Stellos, Konstantinos; Schreieck, Jürgen; Gawaz, Meinrad; May, Andreas E

2013-03-10

During inflammatory cardiomyopathy matrix metalloproteinases are crucially involved in cardiac remodeling. The aim of the present study was to investigate whether the "extracellular matrix metalloproteinase inducer" EMMPRIN (CD147) and its ligand Cyclophilin A (CyPA) are upregulated in inflammatory cardiomyopathy and may serve as diagnostic markers. Therefore, a series of 102 human endomyocardial biopsies were analyzed for the expression of EMMPRIN and CyPA and correlated with histological and immunohistological findings. Endomyocardial biopsies were stained for EMMPRIN and CyPA in addition to standard histology (HE, Trichrom) and immunohistological stainings (MHC-II, CD68, CD3). 39 (38.2%) biopsies met the immunohistological criteria of an inflammatory cardiomyopathy. EMMPRIN, which was predominantly expressed on cardiomyocytes, was slightly (but significantly) upregulated in non inflammatory cardiomyopathies compared to normal histopathological findings and highly upregulated in inflammatory cardiomyopathy compared to both non inflammatory cardiomyopathy and normal histopathology. In contrast, CyPA reveals no enhanced expression in non inflammatory cardiomyopathies and a highly enhanced expression in inflammatory cardiomyopathy, where it is closely associated with leucocytes infiltrates. We found a strong correlation between both EMMPRIN and CyPA with the expression of MHC-II molecules (correlation coefficient 0.475 and 0.527, p<0.05). Moreover, we found a correlation for both EMMPRIN and CyPA with CD68 (correlation coefficient 0.393 and 0.387, p<0.05) and CD3 (correlation coefficient 0.360 and 0.235, p<0.05). EMMPRIN is enhanced in both inflammatory and non inflammatory cardiomyopathies and can serve as a marker of myocardial remodeling. CyPA may represent a novel and specific marker for cardiac inflammation. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Fractal analysis of phasic laser images of the myocardium for the purpose of diagnostics of acute coronary insufficiency

NASA Astrophysics Data System (ADS)

Wanchuliak, O. Y.; Bachinskyi, V. T.

2011-09-01

In this work on the base of Mueller-matrix description of optical anisotropy, the possibility of monitoring of time changes of myocardium tissue birefringence, has been considered. The optical model of polycrystalline networks of myocardium is suggested. The results of investigating the interrelation between the values correlation (correlation area, asymmetry coefficient and autocorrelation function excess) and fractal (dispersion of logarithmic dependencies of power spectra) parameters are presented. They characterize the distributions of Mueller matrix elements in the points of laser images of myocardium histological sections. The criteria of differentiation of death coming reasons are determined.

Predictability of drug release from water-insoluble polymeric matrix tablets.

PubMed

Grund, Julia; Körber, Martin; Bodmeier, Roland

2013-11-01

The purpose of this study was to extend the predictability of an established solution of Fick's second law of diffusion with formulation-relevant parameters and including percolation theory. Kollidon SR (polyvinyl acetate/polyvinylpyrrolidone, 80/20 w/w) matrix tablets with various porosities (10-30% v/v) containing model drugs with different solubilities (Cs=10-170 mg/ml) and in different amounts (A=10-90% w/w) were prepared by direct compression and characterized by drug release and mass loss studies. Drug release was fitted to Fick's second law to obtain the apparent diffusion coefficient. Its changes were correlated with the total porosity of the matrix and the solubility of the drug. The apparent diffusion coefficient was best described by a cumulative normal distribution over the range of total porosities. The mean of the distribution coincided with the polymer percolation threshold, and the minimum and maximum of the distribution were represented by the diffusion coefficient in pore-free polymer and in aqueous medium, respectively. The derived model was verified, and the applicability further extended to a drug solubility range of 10-1000 mg/ml. The developed mathematical model accurately describes and predicts drug release from Kollidon SR matrix tablets. It can efficiently reduce experimental trials during formulation development. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

PubMed Central

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-01-01

Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

Recent mathematical developments in 2D correlation spectroscopy

NASA Astrophysics Data System (ADS)

Noda, I.

2000-03-01

Recent mathematical developments in the field of 2D correlation spectroscopy, especially those related to the statistical theory, are reported. The notion of correlation phase angle is introduced. The significance of correlation phase angle between dynamic fluctuations of signals measured at two different spectral variables may be linked to more commonly known statistical concepts, such as coherence and correlation coefficient. This treatment provides the direct mathematical connection between the synchronous 2D correlation spectrum with a continuous form of the variance-covariance matrix. Moreover, it gives the background for the formal definition of the disrelation spectrum, which may be used as a heuristic substitution for the asynchronous 2D spectrum. The 2D correlation intensity may be separated into two independent factors representing the normalized extent of signal fluctuation coherence (i.e., correlation coefficient) and the magnitude of spectral intensity changes (i.e., variance). Such separation offers a convenient way to artificially enhance the discriminating power of 2D correlation spectra.

DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS

NASA Astrophysics Data System (ADS)

Ling, Ling; Li, Ying; Wang, Sheng; Guo, Liming; Xiao, Chunsheng; Chen, Xuesi; Guo, Xinhua

2018-01-01

Matrix interference ions in low mass range has always been a concern when using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze small molecules (<500 Da). In this work, a novel matrix, N1,N4-dibenzylidenebenzene-1,4-diamine (DBDA) was synthesized for the analyses of small molecules by negative ion MALDI-TOF MS. Notably, only neat ions ([M-H]-) of fatty acids without matrix interference appeared in the mass spectra and the limit of detection (LOD) reached 0.3 fmol. DBDA also has great performance towards other small molecules such as amino acids, peptides, and nucleotide. Furthermore, with this novel matrix, the free fatty acids in serum were quantitatively analyzed based on the correlation curves with correlation coefficient of 0.99. In addition, UV-Vis experiments and molecular orbital calculations were performed to explore mechanism about DBDA used as matrix in the negative ion mode. The present work shows that the DBDA matrix is a highly sensitive matrix with few interference ions for analysis of small molecules. Meanwhile, DBDA is able to precisely quantify the fatty acids in real biological samples. [Figure not available: see fulltext.

Heat Transfer Characteristics of Regenerator Matrix (Case of Packed Wire Gauzes)

NASA Technical Reports Server (NTRS)

Hamaguchi, K.; Takahashi, S.; Miyabe, H.

1984-01-01

The average heat transfer coefficient in the matrix of laminated wire screens (10 to 250 mesh) for a Stirling engine heat exchanger was studied experimentally. The data are correlated by N sub ud = 0.42 R sub ed 0.56 (3 or = R sub ed or = 400), and R sub ed are the Nusselt and Reynolds nubmers based on the wire diameter. The pressure drop decreased and the heat transfer increased as the wire diameter was decreased.

Scaling and correlations in foreign exchange market

NASA Astrophysics Data System (ADS)

Jiang, J.; Ma, K.; Cai, X.

2007-02-01

We observe that the distribution of the relative return, describing the variation of a certain currency, of 74 global currencies obeys a power-law. By using the random matrix theory we find that the distribution of eigenvalues of correlation matrix of relative return also follows a power-law. Using a scaled factorial moment we investigate the distribution of correlation coefficients of the relative return and observe intermittence phenomenon. Furthermore, we define the influence strength for a certain currency, which reflects the influence of its price change to the community interested. By doing that, we find that the distribution of influence strength is again a power-law. Beyond that, we compare the influence strength of Chinese Yuan (RMB) to those of other seven important currencies, which may have some interesting indications.

Structure-function correlations in glaucoma using matrix and standard automated perimetry versus time-domain and spectral-domain OCT devices.

PubMed

Pinto, Luciano Moreira; Costa, Elaine Fiod; Melo, Luiz Alberto S; Gross, Paula Blasco; Sato, Eduardo Toshio; Almeida, Andrea Pereira; Maia, Andre; Paranhos, Augusto

2014-04-10

We examined the structure-function relationship between two perimetric tests, the frequency doubling technology (FDT) matrix and standard automated perimetry (SAP), and two optical coherence tomography (OCT) devices (time-domain and spectral-domain). This cross-sectional study included 97 eyes from 29 healthy individuals, and 68 individuals with early, moderate, or advanced primary open-angle glaucoma. The correlations between overall and sectorial parameters of retinal nerve fiber layer thickness (RNFL) measured with Stratus and Spectralis OCT, and the visual field sensitivity obtained with FDT matrix and SAP were assessed. The relationship also was evaluated using a previously described linear model. The correlation coefficients for the threshold sensitivity measured with SAP and Stratus OCT ranged from 0.44 to 0.79, and those for Spectralis OCT ranged from 0.30 to 0.75. Regarding FDT matrix, the correlation ranged from 0.40 to 0.79 with Stratus OCT and from 0.39 to 0.79 with Spectralis OCT. Stronger correlations were found in the overall measurements and the arcuate sectors for both visual fields and OCT devices. A linear relationship was observed between FDT matrix sensitivity and the OCT devices. The previously described linear model fit the data from SAP and the OCT devices well, particularly in the inferotemporal sector. The FDT matrix and SAP visual sensitivities were related strongly to the RNFL thickness measured with the Stratus and Spectralis OCT devices, particularly in the overall and arcuate sectors. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Combined analysis of magnetic and gravity anomalies using normalized source strength (NSS)

NASA Astrophysics Data System (ADS)

Li, L.; Wu, Y.

2017-12-01

Gravity field and magnetic field belong to potential fields which lead inherent multi-solution. Combined analysis of magnetic and gravity anomalies based on Poisson's relation is used to determinate homology gravity and magnetic anomalies and decrease the ambiguity. The traditional combined analysis uses the linear regression of the reduction to pole (RTP) magnetic anomaly to the first order vertical derivative of the gravity anomaly, and provides the quantitative or semi-quantitative interpretation by calculating the correlation coefficient, slope and intercept. In the calculation process, due to the effect of remanent magnetization, the RTP anomaly still contains the effect of oblique magnetization. In this case the homology gravity and magnetic anomalies display irrelevant results in the linear regression calculation. The normalized source strength (NSS) can be transformed from the magnetic tensor matrix, which is insensitive to the remanence. Here we present a new combined analysis using NSS. Based on the Poisson's relation, the gravity tensor matrix can be transformed into the pseudomagnetic tensor matrix of the direction of geomagnetic field magnetization under the homologous condition. The NSS of pseudomagnetic tensor matrix and original magnetic tensor matrix are calculated and linear regression analysis is carried out. The calculated correlation coefficient, slope and intercept indicate the homology level, Poisson's ratio and the distribution of remanent respectively. We test the approach using synthetic model under complex magnetization, the results show that it can still distinguish the same source under the condition of strong remanence, and establish the Poisson's ratio. Finally, this approach is applied in China. The results demonstrated that our approach is feasible.

Numericware i: Identical by State Matrix Calculator

PubMed Central

Kim, Bongsong; Beavis, William D

2017-01-01

We introduce software, Numericware i, to compute identical by state (IBS) matrix based on genotypic data. Calculating an IBS matrix with a large dataset requires large computer memory and takes lengthy processing time. Numericware i addresses these challenges with 2 algorithmic methods: multithreading and forward chopping. The multithreading allows computational routines to concurrently run on multiple central processing unit (CPU) processors. The forward chopping addresses memory limitation by dividing a dataset into appropriately sized subsets. Numericware i allows calculation of the IBS matrix for a large genotypic dataset using a laptop or a desktop computer. For comparison with different software, we calculated genetic relationship matrices using Numericware i, SPAGeDi, and TASSEL with the same genotypic dataset. Numericware i calculates IBS coefficients between 0 and 2, whereas SPAGeDi and TASSEL produce different ranges of values including negative values. The Pearson correlation coefficient between the matrices from Numericware i and TASSEL was high at .9972, whereas SPAGeDi showed low correlation with Numericware i (.0505) and TASSEL (.0587). With a high-dimensional dataset of 500 entities by 10 000 000 SNPs, Numericware i spent 382 minutes using 19 CPU threads and 64 GB memory by dividing the dataset into 3 pieces, whereas SPAGeDi and TASSEL failed with the same dataset. Numericware i is freely available for Windows and Linux under CC-BY 4.0 license at https://figshare.com/s/f100f33a8857131eb2db. PMID:28469375

On the Feynman-Hellmann theorem in quantum field theory and the calculation of matrix elements

DOE PAGES

Bouchard, Chris; Chang, Chia Cheng; Kurth, Thorsten; ...

2017-07-12

In this paper, the Feynman-Hellmann theorem can be derived from the long Euclidean-time limit of correlation functions determined with functional derivatives of the partition function. Using this insight, we fully develop an improved method for computing matrix elements of external currents utilizing only two-point correlation functions. Our method applies to matrix elements of any external bilinear current, including nonzero momentum transfer, flavor-changing, and two or more current insertion matrix elements. The ability to identify and control all the systematic uncertainties in the analysis of the correlation functions stems from the unique time dependence of the ground-state matrix elements and the fact that all excited states and contact terms are Euclidean-time dependent. We demonstrate the utility of our method with a calculation of the nucleon axial charge using gradient-flowed domain-wall valence quarks on themore » $$N_f=2+1+1$$ MILC highly improved staggered quark ensemble with lattice spacing and pion mass of approximately 0.15 fm and 310 MeV respectively. We show full control over excited-state systematics with the new method and obtain a value of $$g_A = 1.213(26)$$ with a quark-mass-dependent renormalization coefficient.« less

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

Bouchard, Chris; Chang, Chia Cheng; Kurth, Thorsten

In this paper, the Feynman-Hellmann theorem can be derived from the long Euclidean-time limit of correlation functions determined with functional derivatives of the partition function. Using this insight, we fully develop an improved method for computing matrix elements of external currents utilizing only two-point correlation functions. Our method applies to matrix elements of any external bilinear current, including nonzero momentum transfer, flavor-changing, and two or more current insertion matrix elements. The ability to identify and control all the systematic uncertainties in the analysis of the correlation functions stems from the unique time dependence of the ground-state matrix elements and the fact that all excited states and contact terms are Euclidean-time dependent. We demonstrate the utility of our method with a calculation of the nucleon axial charge using gradient-flowed domain-wall valence quarks on themore » $$N_f=2+1+1$$ MILC highly improved staggered quark ensemble with lattice spacing and pion mass of approximately 0.15 fm and 310 MeV respectively. We show full control over excited-state systematics with the new method and obtain a value of $$g_A = 1.213(26)$$ with a quark-mass-dependent renormalization coefficient.« less

Phone camera detection of glucose blood level based on magnetic particles entrapped inside bubble wrap.

PubMed

Martinkova, Pavla; Pohanka, Miroslav

2016-12-18

Glucose is an important diagnostic biochemical marker of diabetes but also for organophosphates, carbamates, acetaminophens or salicylates poisoning. Hence, innovation of accurate and fast detection assay is still one of priorities in biomedical research. Glucose sensor based on magnetic particles (MPs) with immobilized enzymes glucose oxidase (GOx) and horseradish peroxidase (HRP) was developed and the GOx catalyzed reaction was visualized by a smart-phone-integrated camera. Exponential decay concentration curve with correlation coefficient 0.997 and with limit of detection 0.4 mmol/l was achieved. Interfering and matrix substances were measured due to possibility of assay influencing and no effect of the tested substances was observed. Spiked plasma samples were also measured and no influence of plasma matrix on the assay was proved. The presented assay showed complying results with reference method (standard spectrophotometry based on enzymes glucose oxidase and peroxidase inside plastic cuvettes) with linear dependence and correlation coefficient 0.999 in concentration range between 0 and 4 mmol/l. On the grounds of measured results, method was considered as highly specific, accurate and fast assay for detection of glucose.

The number of measurements needed to obtain high reliability for traits related to enzymatic activities and photosynthetic compounds in soybean plants infected with Phakopsora pachyrhizi.

PubMed

Oliveira, Tássia Boeno de; Azevedo Peixoto, Leonardo de; Teodoro, Paulo Eduardo; Alvarenga, Amauri Alves de; Bhering, Leonardo Lopes; Campo, Clara Beatriz Hoffmann

2018-01-01

Asian rust affects the physiology of soybean plants and causes losses in yield. Repeatability coefficients may help breeders to know how many measurements are needed to obtain a suitable reliability for a target trait. Therefore, the objectives of this study were to determine the repeatability coefficients of 14 traits in soybean plants inoculated with Phakopsora pachyrhizi and to establish the minimum number of measurements needed to predict the breeding value with high accuracy. Experiments were performed in a 3x2 factorial arrangement with three treatments and two inoculations in a random block design. Repeatability coefficients, coefficients of determination and number of measurements needed to obtain a certain reliability were estimated using ANOVA, principal component analysis based on the covariance matrix and the correlation matrix, structural analysis and mixed model. It was observed that the principal component analysis based on the covariance matrix out-performed other methods for almost all traits. Significant differences were observed for all traits except internal CO2 concentration for the treatment effects. For the measurement effects, all traits were significantly different. In addition, significant differences were found for all Treatment x Measurement interaction traits except coumestrol, chitinase and chlorophyll content. Six measurements were suitable to obtain a coefficient of determination higher than 0.7 for all traits based on principal component analysis. The information obtained from this research will help breeders and physiologists determine exactly how many measurements are needed to evaluate each trait in soybean plants infected by P. pachyrhizi with a desirable reliability.

The number of measurements needed to obtain high reliability for traits related to enzymatic activities and photosynthetic compounds in soybean plants infected with Phakopsora pachyrhizi

PubMed Central

de Oliveira, Tássia Boeno; Teodoro, Paulo Eduardo; de Alvarenga, Amauri Alves; Bhering, Leonardo Lopes; Campo, Clara Beatriz Hoffmann

2018-01-01

Asian rust affects the physiology of soybean plants and causes losses in yield. Repeatability coefficients may help breeders to know how many measurements are needed to obtain a suitable reliability for a target trait. Therefore, the objectives of this study were to determine the repeatability coefficients of 14 traits in soybean plants inoculated with Phakopsora pachyrhizi and to establish the minimum number of measurements needed to predict the breeding value with high accuracy. Experiments were performed in a 3x2 factorial arrangement with three treatments and two inoculations in a random block design. Repeatability coefficients, coefficients of determination and number of measurements needed to obtain a certain reliability were estimated using ANOVA, principal component analysis based on the covariance matrix and the correlation matrix, structural analysis and mixed model. It was observed that the principal component analysis based on the covariance matrix out-performed other methods for almost all traits. Significant differences were observed for all traits except internal CO2 concentration for the treatment effects. For the measurement effects, all traits were significantly different. In addition, significant differences were found for all Treatment x Measurement interaction traits except coumestrol, chitinase and chlorophyll content. Six measurements were suitable to obtain a coefficient of determination higher than 0.7 for all traits based on principal component analysis. The information obtained from this research will help breeders and physiologists determine exactly how many measurements are needed to evaluate each trait in soybean plants infected by P. pachyrhizi with a desirable reliability. PMID:29438380

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: IV. Generalized matrix analysis of linear compartment systems.

PubMed

Langenbucher, Frieder

2005-01-01

A linear system comprising n compartments is completely defined by the rate constants between any of the compartments and the initial condition in which compartment(s) the drug is present at the beginning. The generalized solution is the time profiles of drug amount in each compartment, described by polyexponential equations. Based on standard matrix operations, an Excel worksheet computes the rate constants and the coefficients, finally the full time profiles for a specified range of time values.

The G matrix under fluctuating correlational mutation and selection.

PubMed

Revell, Liam J

2007-08-01

Theoretical quantitative genetics provides a framework for reconstructing past selection and predicting future patterns of phenotypic differentiation. However, the usefulness of the equations of quantitative genetics for evolutionary inference relies on the evolutionary stability of the additive genetic variance-covariance matrix (G matrix). A fruitful new approach for exploring the evolutionary dynamics of G involves the use of individual-based computer simulations. Previous studies have focused on the evolution of the eigenstructure of G. An alternative approach employed in this paper uses the multivariate response-to-selection equation to evaluate the stability of G. In this approach, I measure similarity by the correlation between response-to-selection vectors due to random selection gradients. I analyze the dynamics of G under several conditions of correlational mutation and selection. As found in a previous study, the eigenstructure of G is stabilized by correlational mutation and selection. However, over broad conditions, instability of G did not result in a decreased consistency of the response to selection. I also analyze the stability of G when the correlation coefficients of correlational mutation and selection and the effective population size change through time. To my knowledge, no prior study has used computer simulations to investigate the stability of G when correlational mutation and selection fluctuate. Under these conditions, the eigenstructure of G is unstable under some simulation conditions. Different results are obtained if G matrix stability is assessed by eigenanalysis or by the response to random selection gradients. In this case, the response to selection is most consistent when certain aspects of the eigenstructure of G are least stable and vice versa.

System of Mueller-Jones matrix polarizing mapping of blood plasma films in breast pathology

NASA Astrophysics Data System (ADS)

Zabolotna, Natalia I.; Radchenko, Kostiantyn O.; Tarnovskiy, Mykola H.

2017-08-01

The combined method of Jones-Mueller matrix mapping and blood plasma films analysis based on the system that proposed in this paper. Based on the obtained data about the structure and state of blood plasma samples the diagnostic conclusions can be make about the state of breast cancer patients ("normal" or "pathology"). Then, by using the statistical analysis obtain statistical and correlational moments for every coordinate distributions; these indicators are served as diagnostic criterias. The final step is to comparing results and choosing the most effective diagnostic indicators. The paper presents the results of Mueller-Jones matrix mapping of optically thin (attenuation coefficient ,τ≤0,1) blood plasma layers.

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

Interacting hadron resonance gas model in the K -matrix formalism

NASA Astrophysics Data System (ADS)

Dash, Ashutosh; Samanta, Subhasis; Mohanty, Bedangadas

2018-05-01

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

Temperature-dependent tensile and shear response of graphite/aluminum

NASA Technical Reports Server (NTRS)

Fujita, T.; Pindera, M. J.; Herakovich, C. T.

1987-01-01

The thermo-mechanical response of unidirectional P100 graphite fiber/6061 aluminum matrix composites was investigated at four temperatures:-150, +75, +250, and +500 F. Two types of tests, off-axis tension and losipescu shear, were used to obtain the desired properties. Good experimental-theoretical correlation was obtained for Exx, vxy, and G12. It is shown that E11 is temperature independent, but E22, v12, and G12 generally decrease with increasing temperature. Compared with rather high longitudinal strength, very low transverse strength was obtained for the graphite/aluminum. The poor transverse strength is believed to be due to the low interfacial bond strength in this material. The strength decrease significantly with increasing temperature. The tensile response at various temperatures is greatly affected by the residual stresses caused by the mismatch in the coefficients of thermal expansion of fibers and matrix. The degradation of the aluminum matrix properties at higher temperatures has a deleterious effect on composite properties. The composite has a very low coefficient of thermal expansion in the fiber direction.

Synthesis of linear regression coefficients by recovering the within-study covariance matrix from summary statistics.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-06-01

Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Field-scale effective matrix diffusion coefficient for fractured rock: results from literature survey.

PubMed

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

2007-08-15

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

Invariant operators, orthogonal bases and correlators in general tensor models

NASA Astrophysics Data System (ADS)

Diaz, Pablo; Rey, Soo-Jong

2018-07-01

We study invariant operators in general tensor models. We show that representation theory provides an efficient framework to count and classify invariants in tensor models of (gauge) symmetry Gd = U (N1) ⊗ ⋯ ⊗ U (Nd). As a continuation and completion of our earlier work, we present two natural ways of counting invariants, one for arbitrary Gd and another valid for large rank of Gd. We construct bases of invariant operators based on the counting, and compute correlators of their elements. The basis associated with finite rank of Gd diagonalizes the two-point function of the free theory. It is analogous to the restricted Schur basis used in matrix models. We show that the constructions get almost identical as we swap the Littlewood-Richardson numbers in multi-matrix models with Kronecker coefficients in general tensor models. We explore the parallelism between matrix model and tensor model in depth from the perspective of representation theory and comment on several ideas for future investigation.

Validating internet research: a test of the psychometric equivalence of internet and in-person samples.

PubMed

Meyerson, Paul; Tryon, Warren W

2003-11-01

This study evaluated the psychometric equivalency of Web-based research. The Sexual Boredom Scale was presented via the World-Wide Web along with five additional scales used to validate it. A subset of 533 participants that matched a previously published sample (Watt & Ewing, 1996) on age, gender, and race was identified. An 8 x 8 correlation matrix from the matched Internet sample was compared via structural equation modeling with a similar 8 x 8 correlation matrix from the previously published study. The Internet and previously published samples were psychometrically equivalent. Coefficient alpha values calculated on the matched Internet sample yielded reliability coefficients almost identical to those for the previously published sample. Factors such as computer administration and uncontrollable administration settings did not appear to affect the results. Demographic data indicated an overrepresentation of males by about 6% and Caucasians by about 13% relative to the U.S. Census (2000). A total of 2,230 participants were obtained in about 8 months without remuneration. These results suggest that data collection on the Web is (1) reliable, (2) valid, (3) reasonably representative, (4) cost effective, and (5) efficient.

A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

NASA Astrophysics Data System (ADS)

Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

2018-04-01

This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

[Correlation of substrate structure and hydraulic characteristics in subsurface flow constructed wetlands].

PubMed

Bai, Shao-Yuan; Song, Zhi-Xin; Ding, Yan-Li; You, Shao-Hong; He, Shan

2014-02-01

The correlation of substrate structure and hydraulic characteristics was studied by numerical simulation combined with experimental method. The numerical simulation results showed that the permeability coefficient of matrix had a great influence on hydraulic efficiency in subsurface flow constructed wetlands. The filler with a high permeability coefficient had a worse flow field distribution in the constructed wetland with single layer structure. The layered substrate structure with the filler permeability coefficient increased from surface to bottom could avoid the short-circuited flow and dead-zones, and thus, increased the hydraulic efficiency. Two parallel pilot-scale constructed wetlands were built according to the numerical simulation results, and tracer experiments were conducted to validate the simulation results. The tracer experiment result showed that hydraulic characteristics in the layered constructed wetland were obviously better than that in the single layer system, and the substrate effective utilization rates were 0.87 and 0.49, respectively. It was appeared that numerical simulation would be favorable for substrate structure optimization in subsurface flow constructed wetlands.

Analysis of cross-correlations between financial markets after the 2008 crisis

NASA Astrophysics Data System (ADS)

Sensoy, A.; Yuksel, S.; Erturk, M.

2013-10-01

We analyze the cross-correlation matrix C of the index returns of the main financial markets after the 2008 crisis using methods of random matrix theory. We test the eigenvalues of C for universal properties of random matrices and find that the majority of the cross-correlation coefficients arise from randomness. We show that the eigenvector of the largest deviating eigenvalue of C represents a global market itself. We reveal that high volatility of financial markets is observed at the same times with high correlations between them which lowers the risk diversification potential even if one constructs a widely internationally diversified portfolio of stocks. We identify and compare the connection and cluster structure of markets before and after the crisis using minimal spanning and ultrametric hierarchical trees. We find that after the crisis, the co-movement degree of the markets increases. We also highlight the key financial markets of pre and post crisis using main centrality measures and analyze the changes. We repeat the study using rank correlation and compare the differences. Further implications are discussed.

TH-A-18C-03: Noise Correlation in CBCT Projection Data and Its Application for Noise Reduction in Low-Dose CBCT

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

ZHANG, H; Huang, J; Ma, J

2014-06-15

Purpose: To study the noise correlation properties of cone-beam CT (CBCT) projection data and to incorporate the noise correlation information to a statistics-based projection restoration algorithm for noise reduction in low-dose CBCT. Methods: In this study, we systematically investigated the noise correlation properties among detector bins of CBCT projection data by analyzing repeated projection measurements. The measurements were performed on a TrueBeam on-board CBCT imaging system with a 4030CB flat panel detector. An anthropomorphic male pelvis phantom was used to acquire 500 repeated projection data at six different dose levels from 0.1 mAs to 1.6 mAs per projection at threemore » fixed angles. To minimize the influence of the lag effect, lag correction was performed on the consecutively acquired projection data. The noise correlation coefficient between detector bin pairs was calculated from the corrected projection data. The noise correlation among CBCT projection data was then incorporated into the covariance matrix of the penalized weighted least-squares (PWLS) criterion for noise reduction of low-dose CBCT. Results: The analyses of the repeated measurements show that noise correlation coefficients are non-zero between the nearest neighboring bins of CBCT projection data. The average noise correlation coefficients for the first- and second- order neighbors are about 0.20 and 0.06, respectively. The noise correlation coefficients are independent of the dose level. Reconstruction of the pelvis phantom shows that the PWLS criterion with consideration of noise correlation (PWLS-Cor) results in a lower noise level as compared to the PWLS criterion without considering the noise correlation (PWLS-Dia) at the matched resolution. Conclusion: Noise is correlated among nearest neighboring detector bins of CBCT projection data. An accurate noise model of CBCT projection data can improve the performance of the statistics-based projection restoration algorithm for low-dose CBCT.« less

An overview of coefficient alpha and a reliability matrix for estimating adequacy of internal consistency coefficients with psychological research measures.

PubMed

Ponterotto, Joseph G; Ruckdeschel, Daniel E

2007-12-01

The present article addresses issues in reliability assessment that are often neglected in psychological research such as acceptable levels of internal consistency for research purposes, factors affecting the magnitude of coefficient alpha (alpha), and considerations for interpreting alpha within the research context. A new reliability matrix anchored in classical test theory is introduced to help researchers judge adequacy of internal consistency coefficients with research measures. Guidelines and cautions in applying the matrix are provided.

Comparison of co-expression measures: mutual information, correlation, and model based indices.

PubMed

Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI networks can safely be replaced by correlation networks when it comes to measuring co-expression relationships in stationary data.

Fourier-Legendre expansion of the one-electron density matrix of ground-state two-electron atoms.

PubMed

Ragot, Sébastien; Ruiz, María Belén

2008-09-28

The density matrix rho(r,r(')) of a spherically symmetric system can be expanded as a Fourier-Legendre series of Legendre polynomials P(l)(cos theta=rr(')rr(')). Application is here made to harmonically trapped electron pairs (i.e., Moshinsky's and Hooke's atoms), for which exact wavefunctions are known, and to the helium atom, using a near-exact wavefunction. In the present approach, generic closed form expressions are derived for the series coefficients of rho(r,r(')). The series expansions are shown to converge rapidly in each case, with respect to both the electron number and the kinetic energy. In practice, a two-term expansion accounts for most of the correlation effects, so that the correlated density matrices of the atoms at issue are essentially a linear functions of P(l)(cos theta)=cos theta. For example, in the case of Hooke's atom, a two-term expansion takes in 99.9% of the electrons and 99.6% of the kinetic energy. The correlated density matrices obtained are finally compared to their determinantal counterparts, using a simplified representation of the density matrix rho(r,r(')), suggested by the Legendre expansion. Interestingly, two-particle correlation is shown to impact the angular delocalization of each electron, in the one-particle space spanned by the r and r(') variables.

A determinant-based criterion for working correlation structure selection in generalized estimating equations.

PubMed

Jaman, Ajmery; Latif, Mahbub A H M; Bari, Wasimul; Wahed, Abdus S

2016-05-20

In generalized estimating equations (GEE), the correlation between the repeated observations on a subject is specified with a working correlation matrix. Correct specification of the working correlation structure ensures efficient estimators of the regression coefficients. Among the criteria used, in practice, for selecting working correlation structure, Rotnitzky-Jewell, Quasi Information Criterion (QIC) and Correlation Information Criterion (CIC) are based on the fact that if the assumed working correlation structure is correct then the model-based (naive) and the sandwich (robust) covariance estimators of the regression coefficient estimators should be close to each other. The sandwich covariance estimator, used in defining the Rotnitzky-Jewell, QIC and CIC criteria, is biased downward and has a larger variability than the corresponding model-based covariance estimator. Motivated by this fact, a new criterion is proposed in this paper based on the bias-corrected sandwich covariance estimator for selecting an appropriate working correlation structure in GEE. A comparison of the proposed and the competing criteria is shown using simulation studies with correlated binary responses. The results revealed that the proposed criterion generally performs better than the competing criteria. An example of selecting the appropriate working correlation structure has also been shown using the data from Madras Schizophrenia Study. Copyright © 2015 John Wiley & Sons, Ltd.

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...

Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming.

PubMed

Li, Yuqin; You, Guirong; Jia, Baoxiu; Si, Hongzong; Yao, Xiaojun

2014-01-01

Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R (2)) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

Correlation, Cost Risk, and Geometry

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1992-01-01

The geometric viewpoint identifies the choice of a correlation matrix for the simulation of cost risk with the pairwise choice of data vectors corresponding to the parameters used to obtain cost risk. The correlation coefficient is the cosine of the angle between the data vectors after translation to an origin at the mean and normalization for magnitude. Thus correlation is equivalent to expressing the data in terms of a non orthogonal basis. To understand the many resulting phenomena requires the use of the tensor concept of raising the index to transform the measured and observed covariant components into contravariant components before vector addition can be applied. The geometric viewpoint also demonstrates that correlation and covariance are geometric properties, as opposed to purely statistical properties, of the variates. Thus, variates from different distributions may be correlated, as desired, after selection from independent distributions. By determining the principal components of the correlation matrix, variates with the desired mean, magnitude, and correlation can be generated through linear transforms which include the eigenvalues and the eigenvectors of the correlation matrix. The conversion of the data to a non orthogonal basis uses a compound linear transformation which distorts or stretches the data space. Hence, the correlated data does not have the same properties as the uncorrelated data used to generate it. This phenomena is responsible for seemingly strange observations such as the fact that the marginal distributions of the correlated data can be quite different from the distributions used to generate the data. The joint effect of statistical distributions and correlation remains a fertile area for further research. In terms of application to cost estimating, the geometric approach demonstrates that the estimator must have data and must understand that data in order to properly choose the correlation matrix appropriate for a given estimate. There is a general feeling by employers and managers that the field of cost requires little technical or mathematical background. Contrary to that opinion, this paper demonstrates that a background in mathematics equivalent to that needed for typical engineering and scientific disciplines at the masters or doctorate level is appropriate within the field of cost risk.

Flow model for open-channel reach or network

USGS Publications Warehouse

Schaffranek, R.W.

1987-01-01

Formulation of a one-dimensional model for simulating unsteady flow in a single open-channel reach or in a network of interconnected channels is presented. The model is both general and flexible in that it can be used to simulate a wide range of flow conditions for various channel configurations. It is based on a four-point (box), implicit, finite-difference approximation of the governing nonlinear flow equations with user-definable weighting coefficients to permit varying the solution scheme from box-centered to fully forward. Unique transformation equations are formulated that permit correlation of the unknowns at the extremities of the channels, thereby reducing coefficient matrix and execution time requirements. Discharges and water-surface elevations computed at intermediate locations within a channel are determined following solution of the transformation equations. The matrix of transformation and boundary-condition equations is solved by Gauss elimination using maximum pivot strategy. Two diverse applications of the model are presented to illustrate its broad utility. (USGS)

Empirical Monod-Beuneu relation of spin relaxation revisited for elemental metals

NASA Astrophysics Data System (ADS)

Szolnoki, L.; Kiss, A.; Forró, L.; Simon, F.

2014-03-01

Monod and Beuneu [P. Monod and F. Beuneu, Phys. Rev. B 19, 911 (1979), 10.1103/PhysRevB.19.911] established the validity of the Elliott-Yafet theory for elemental metals through correlating the experimental electron spin resonance linewidth with the so-called spin-orbit admixture coefficients and the momentum-relaxation theory. The spin-orbit admixture coefficients data were based on atomic spin-orbit splitting. We highlight two shortcomings of the previous description: (i) the momentum-relaxation involves the Debye temperature and the electron-phonon coupling whose variation among the elemental metals was neglected, (ii) the Elliott-Yafet theory involves matrix elements of the spin-orbit coupling (SOC), which are however not identical to the SOC induced energy splitting of the atomic levels, even though the two have similar magnitudes. We obtain the empirical spin-orbit admixture parameters for the alkali metals by considering the proper description of the momentum relaxation theory. In addition we present a model calculation, which highlights the difference between the SOC matrix element and energy splitting.

Laser transit anemometer software development program

NASA Technical Reports Server (NTRS)

Abbiss, John B.

1989-01-01

Algorithms were developed for the extraction of two components of mean velocity, standard deviation, and the associated correlation coefficient from laser transit anemometry (LTA) data ensembles. The solution method is based on an assumed two-dimensional Gaussian probability density function (PDF) model of the flow field under investigation. The procedure consists of transforming the data ensembles from the data acquisition domain (consisting of time and angle information) to the velocity space domain (consisting of velocity component information). The mean velocity results are obtained from the data ensemble centroid. Through a least squares fitting of the transformed data to an ellipse representing the intersection of a plane with the PDF, the standard deviations and correlation coefficient are obtained. A data set simulation method is presented to test the data reduction process. Results of using the simulation system with a limited test matrix of input values is also given.

Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

Raman and Fourier Transform Infrared (FT-IR) Mineral to Matrix Ratios Correlate with Physical Chemical Properties of Model Compounds and Native Bone Tissue.

PubMed

Taylor, Erik A; Lloyd, Ashley A; Salazar-Lara, Carolina; Donnelly, Eve

2017-10-01

Raman and Fourier transform infrared (FT-IR) spectroscopic imaging techniques can be used to characterize bone composition. In this study, our objective was to validate the Raman mineral:matrix ratios (ν 1 PO 4 :amide III, ν 1 PO 4 :amide I, ν 1 PO 4 :Proline + hydroxyproline, ν 1 PO 4 :Phenylalanine, ν 1 PO 4 :δ CH 2 peak area ratios) by correlating them to ash fraction and the IR mineral:matrix ratio (ν 3 PO 4 :amide I peak area ratio) in chemical standards and native bone tissue. Chemical standards consisting of varying ratios of synthetic hydroxyapatite (HA) and collagen, as well as bone tissue from humans, sheep, and mice, were characterized with confocal Raman spectroscopy and FT-IR spectroscopy and gravimetric analysis. Raman and IR mineral:matrix ratio values from chemical standards increased reciprocally with ash fraction (Raman ν 1 PO 4 /Amide III: P < 0.01, R 2  = 0.966; Raman ν 1 PO 4 /Amide I: P < 0.01, R 2  = 0.919; Raman ν 1 PO 4 /Proline + Hydroxyproline: P < 0.01, R 2  = 0.976; Raman ν 1 PO 4 /Phenylalanine: P < 0.01, R 2  = 0.911; Raman ν 1 PO 4 /δ CH 2 : P < 0.01, R 2  = 0.894; IR P < 0.01, R 2  = 0.91). Fourier transform infrared mineral:matrix ratio values from native bone tissue were also similar to theoretical mineral:matrix ratio values for a given ash fraction. Raman and IR mineral:matrix ratio values were strongly correlated ( P < 0.01, R 2  = 0.82). These results were confirmed by calculating the mineral:matrix ratio for theoretical IR spectra, developed by applying the Beer-Lambert law to calculate the relative extinction coefficients of HA and collagen over the same range of wavenumbers (800-1800 cm -1 ). The results confirm that the Raman mineral:matrix bone composition parameter correlates strongly to ash fraction and to its IR counterpart. Finally, the mineral:matrix ratio values of the native bone tissue are similar to those of both chemical standards and theoretical values, confirming the biological relevance of the chemical standards and the characterization techniques.

Identifying Bearing Rotodynamic Coefficients Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter's performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.

Noise correlation in CBCT projection data and its application for noise reduction in low-dose CBCT

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

Zhang, Hua; Ouyang, Luo; Wang, Jing, E-mail: jhma@smu.edu.cn, E-mail: jing.wang@utsouthwestern.edu

2014-03-15

Purpose: To study the noise correlation properties of cone-beam CT (CBCT) projection data and to incorporate the noise correlation information to a statistics-based projection restoration algorithm for noise reduction in low-dose CBCT. Methods: In this study, the authors systematically investigated the noise correlation properties among detector bins of CBCT projection data by analyzing repeated projection measurements. The measurements were performed on a TrueBeam onboard CBCT imaging system with a 4030CB flat panel detector. An anthropomorphic male pelvis phantom was used to acquire 500 repeated projection data at six different dose levels from 0.1 to 1.6 mAs per projection at threemore » fixed angles. To minimize the influence of the lag effect, lag correction was performed on the consecutively acquired projection data. The noise correlation coefficient between detector bin pairs was calculated from the corrected projection data. The noise correlation among CBCT projection data was then incorporated into the covariance matrix of the penalized weighted least-squares (PWLS) criterion for noise reduction of low-dose CBCT. Results: The analyses of the repeated measurements show that noise correlation coefficients are nonzero between the nearest neighboring bins of CBCT projection data. The average noise correlation coefficients for the first- and second-order neighbors are 0.20 and 0.06, respectively. The noise correlation coefficients are independent of the dose level. Reconstruction of the pelvis phantom shows that the PWLS criterion with consideration of noise correlation (PWLS-Cor) results in a lower noise level as compared to the PWLS criterion without considering the noise correlation (PWLS-Dia) at the matched resolution. At the 2.0 mm resolution level in the axial-plane noise resolution tradeoff analysis, the noise level of the PWLS-Cor reconstruction is 6.3% lower than that of the PWLS-Dia reconstruction. Conclusions: Noise is correlated among nearest neighboring detector bins of CBCT projection data. An accurate noise model of CBCT projection data can improve the performance of the statistics-based projection restoration algorithm for low-dose CBCT.« less

Modification of surface morphology of Ti6Al4V alloy manufactured by Laser Sintering

NASA Astrophysics Data System (ADS)

Draganovská, Dagmar; Ižariková, Gabriela; Guzanová, Anna; Brezinová, Janette; Koncz, Juraj

2016-06-01

The paper deals with the evaluation of relation between roughness parameters of Ti6Al4V alloy produced by DMLS and modified by abrasive blasting. There were two types of blasting abrasives that were used - white corundum and Zirblast at three levels of air pressure. The effect of pressure on the value of individual roughness parameters and an influence of blasting media on the parameters for samples blasted by white corundum and Zirblast were evaluated by ANOVA. Based on the measured values, the correlation matrix was set and the standard of correlation statistic importance between the monitored parameters was determined from it. The correlation coefficient was also set.

Weight Vector Fluctuations in Adaptive Antenna Arrays Tuned Using the Least-Mean-Square Error Algorithm with Quadratic Constraint

NASA Astrophysics Data System (ADS)

Zimina, S. V.

2015-06-01

We present the results of statistical analysis of an adaptive antenna array tuned using the least-mean-square error algorithm with quadratic constraint on the useful-signal amplification with allowance for the weight-coefficient fluctuations. Using the perturbation theory, the expressions for the correlation function and power of the output signal of the adaptive antenna array, as well as the formula for the weight-vector covariance matrix are obtained in the first approximation. The fluctuations are shown to lead to the signal distortions at the antenna-array output. The weight-coefficient fluctuations result in the appearance of additional terms in the statistical characteristics of the antenna array. It is also shown that the weight-vector fluctuations are isotropic, i.e., identical in all directions of the weight-coefficient space.

Electrospun polystyrene/oxidized carbon nanotubes film as both sorbent for thin film microextraction and matrix for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

He, Xiao-Mei; Zhu, Gang-Tian; Yin, Jia; Zhao, Qin; Yuan, Bi-Feng; Feng, Yu-Qi

2014-07-18

In the current study, polystyrene/oxidized carbon nanotubes (PS/OCNTs) film was prepared and applied as both an adsorbent of thin film microextraction (TFME) and matrix for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the first time. The uniform size of PS/OCNTs film with OCNTs evenly and firmly immobilized in PS was obtained by electrospinning. And a novel TFME device was developed using the prepared PS/OCNTs film to enrich benzo[a]pyrene (BaP) from water, and also BaP and 1-hydroxypyrene (1-OHP) from urine sample. Then the extracted analytes on the PS/OCNTs film were directly applied to MALDI-MS analysis with PS/OCNTs film as the MALDI matrix. Our results show that PS/OCNTs film is a good TFME adsorbent toward the analytes and an excellent matrix for the sensitive determination of BaP and 1-OHP using MALDI-TOF-MS. The employment of PS/OCNTs as the matrix for MALDI can effectively avoid the large variation of signal intensity normally resulting from heterogeneous distribution of the adsorbed analyte on matrix layer, which therefore significantly improve spot-to-spot reproducibility. The introduction of PS in the film can prevent OCNTs from flying out of MALDI plate to damage the equipment. In addition, PS/OCNTs film also largely extended the duration of ion signal of target analyte compared to OCNTs matrix. The developed method was further successfully used to quantitatively determine BaP in environmental water and 1-OHP in urine samples. The results show that BaP and 1-OHP could be easily detected at concentrations of 50pgmL(-1) and 500pgmL(-1), respectively, indicating the high detection sensitivity of this method. For BaP analysis, the linear range was 0.1-20ngmL(-1) with a correlation coefficient of 0.9970 and the recoveries were in the range of 81.3 to 123.4% with the RSD≤8.5% (n=3); for urinary 1-OHP analysis, the linear range was 0.5-20ngmL(-1) with a correlation coefficient of 0.9937 and the recoveries were in the range of 79.2 to 103.4% with the RSD≤7.6% (n=3). Taken together, the developed method provides a simple, rapid, cost-effective and high-throughput approach for the analysis of BaP in environmental water and endogenous 1-OHP in urine samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Rapid Diffusion of Green Fluorescent Protein in the Mitochondrial Matrix

PubMed Central

Partikian, Arthur; Ölveczky, Bence; Swaminathan, R.; Li, Yuxin; Verkman, A.S.

1998-01-01

Abstract. It is thought that the high protein density in the mitochondrial matrix results in severely restricted solute diffusion and metabolite channeling from one enzyme to another without free aqueous-phase diffusion. To test this hypothesis, we measured the diffusion of green fluorescent protein (GFP) expressed in the mitochondrial matrix of fibroblast, liver, skeletal muscle, and epithelial cell lines. Spot photobleaching of GFP with a 100× objective (0.8-μm spot diam) gave half-times for fluorescence recovery of 15–19 ms with >90% of the GFP mobile. As predicted for aqueous-phase diffusion in a confined compartment, fluorescence recovery was slowed or abolished by increased laser spot size or bleach time, and by paraformaldehyde fixation. Quantitative analysis of bleach data using a mathematical model of matrix diffusion gave GFP diffusion coefficients of 2–3 × 10−7 cm2/s, only three to fourfold less than that for GFP diffusion in water. In contrast, little recovery was found for bleaching of GFP in fusion with subunits of the fatty acid β-oxidation multienzyme complex that are normally present in the matrix. Measurement of the rotation of unconjugated GFP by time-resolved anisotropy gave a rotational correlation time of 23.3 ± 1 ns, similar to that of 20 ns for GFP rotation in water. A rapid rotational correlation time of 325 ps was also found for a small fluorescent probe (BCECF, ∼0.5 kD) in the matrix of isolated liver mitochondria. The rapid and unrestricted diffusion of solutes in the mitochondrial matrix suggests that metabolite channeling may not be required to overcome diffusive barriers. We propose that the clustering of matrix enzymes in membrane-associated complexes might serve to establish a relatively uncrowded aqueous space in which solutes can freely diffuse. PMID:9472034

Modeling and Control of a Tethered Rotorcraft

DTIC Science & Technology

2010-07-30

viscous damper with damping coefficient Cv. Visco-elastic line force is written in terms of components Δx, Δy, and Δz, of the difference vector formed...tether drag coefficient CS = tether damping coefficient Cv = viscous damping coefficient d = diameter of the tether En = n x n identity matrix FA...matrix consisting of Iyy and Izz k = rotor head stiffness KLAT, KLON = steady state flapping gains Ks, Kv = static and viscous stiffness Lj

Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

NASA Technical Reports Server (NTRS)

Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.

1996-01-01

Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

More on rotations as spin matrix polynomials

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

Curtright, Thomas L.

2015-09-15

Any nonsingular function of spin j matrices always reduces to a matrix polynomial of order 2j. The challenge is to find a convenient form for the coefficients of the matrix polynomial. The theory of biorthogonal systems is a useful framework to meet this challenge. Central factorial numbers play a key role in the theoretical development. Explicit polynomial coefficients for rotations expressed either as exponentials or as rational Cayley transforms are considered here. Structural features of the results are discussed and compared, and large j limits of the coefficients are examined.

Matrix-Assisted Plasma Atomization Emission Spectrometry for Surface Sampling Elemental Analysis

PubMed Central

Yuan, Xin; Zhan, Xuefang; Li, Xuemei; Zhao, Zhongjun; Duan, Yixiang

2016-01-01

An innovative technology has been developed involving a simple and sensitive optical spectrometric method termed matrix-assisted plasma atomization emission spectrometry (MAPAES) for surface sampling elemental analysis using a piece of filter paper (FP) for sample introduction. MAPAES was carried out by direct interaction of the plasma tail plume with the matrix surface. The FP absorbs energy from the plasma source and releases combustion heating to the analytes originally present on its surface, thus to promote the atomization and excitation process. The matrix-assisted plasma atomization excitation phenomenon was observed for multiple elements. The FP matrix served as the partial energy producer and also the sample substrate to adsorb sample solution. Qualitative and quantitative determinations of metal ions were achieved by atomic emission measurements for elements Ba, Cu, Eu, In, Mn, Ni, Rh and Y. The detection limits were down to pg level with linear correlation coefficients better than 0.99. The proposed MAPAES provides a new way for atomic spectrometry which offers advantages of fast analysis speed, little sample consumption, less sample pretreatment, small size, and cost-effective. PMID:26762972

Orthogonal Simulation Experiment for Flow Characteristics of Ore in Ore Drawing and Influencing Factors in a Single Funnel Under a Flexible Isolation Layer

NASA Astrophysics Data System (ADS)

Chen, Qingfa; Zhao, Fuyu; Chen, Qinglin; Wang, Yuding; Zhong, Yu; Niu, Wenjing

2017-12-01

A study on the flow characteristics of ore and factors that influence these characteristics is important to master ore flow laws. An orthogonal ore-drawing numerical model was established and the flow characteristics were explored. A weight matrix was obtained and the effect of the factors was determined. It was found that (1) the entire isolation-layer interface presents a Gaussian curve morphology and marked particles in each layer show a funnel morphology; (2) the drawing amount, Q, and the isolation layer half-width, W, are correlated positively with the fall depth, H, of the isolation layer; (3) factors that affect the characteristics sequentially include the particle friction coefficient, the interface friction coefficient, the isolation layer thickness, and the particle radius, and (4) the optimal combination is an isolation layer thickness of 0.005 m, an interface friction coefficient of 0.8, a particle friction coefficient of 0.2, and a particle radius of 0.007 m.

Correlators in tensor models from character calculus

NASA Astrophysics Data System (ADS)

Mironov, A.; Morozov, A.

2017-11-01

We explain how the calculations of [20], which provided the first evidence for non-trivial structures of Gaussian correlators in tensor models, are efficiently performed with the help of the (Hurwitz) character calculus. This emphasizes a close similarity between technical methods in matrix and tensor models and supports a hope to understand the emerging structures in very similar terms. We claim that the 2m-fold Gaussian correlators of rank r tensors are given by r-linear combinations of dimensions with the Young diagrams of size m. The coefficients are made from the characters of the symmetric group Sm and their exact form depends on the choice of the correlator and on the symmetries of the model. As the simplest application of this new knowledge, we provide simple expressions for correlators in the Aristotelian tensor model as tri-linear combinations of dimensions.

Comparison of Spectral Characteristic between LAPAN-A3 and Sentinel-2A

NASA Astrophysics Data System (ADS)

Zylshal, Z.; Sari, N. M.; Nugroho, J. T.; Kushardono, D.

2017-12-01

Indonesian National Institute of Aeronautics and Space (LAPAN) started building its experimental microsatellite back in 2007 and finally able to launch its first microsatellite dubbed as LAPAN-A1/LAPAN-Tubsat. With the launch of LAPAN-A3/LAPAN-IPB, Indonesian experimental satellite programme hit its third generation. LAPAN-A3 is carrying multiple payloads including multispectral push-broom imager, digital matrix camera, as well as video camera. This paper aims to highlight the spectral differences between LAPAN-A3 and the well-established Sentinel-2A multispectral to investigate the potential of using LAPAN-A3 data to complement the other well-established medium resolution satellite data. Comparisons between corresponding bands and band transformations were performed over a dataset. Three areas of interest were chosen as the test sites. Linear regression and Pearson correlation coefficient were then calculated between the corresponding bands. The preliminary results showed a moderate correlation between the two sensors with Pearson correlation coefficient ranging from 0.39 to 0.65. Some issues were found regarding the radiometric quality over the whole scene of LAPAN-A3.

Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays. In order to obtain effective classification, efficient feature extraction scheme is necessary, for which, in the proposed method, the interchannel relationship among electroencephalogram (EEG) data is utilized. It is expected that the correlation obtained from different combination of channels will be different for different mental tasks, which can be exploited to extract distinctive feature. The empirical mode decomposition (EMD) technique is employed on a test EEG signal obtained from a channel, which provides a number of intrinsic mode functions (IMFs), and correlation coefficient is extracted from interchannel IMF data. Simultaneously, different statistical features are also obtained from each IMF. Finally, the feature matrix is formed utilizing interchannel correlation features and intrachannel statistical features of the selected IMFs of EEG signal. Different kernels of the support vector machine (SVM) classifier are used to carry out the classification task. An EEG dataset containing ten different combinations of five different mental tasks is utilized to demonstrate the classification performance and a very high level of accuracy is achieved by the proposed scheme compared to existing methods.

Applications of Correlation Techniques for Battlefield Identification I.

DTIC Science & Technology

1984-06-30

Participants: .. Carolynn Black Rick Clough Jeanie Fiskin Fif Ghobadian P- Bob Hammett Mary Hernried Lee Leong . Joe Martinetto. d ,i,=r:,,ti b ,: ., , . Glenn... equations . The Clinic team named the process of finding the coefficients matrix "backsolving" since the algorithm starts with the. desired result (the...independent of one another. The jth component of each vector satisfies the equation x3(t) -P + YO(t) where xj(t) is the value of the ith characteristic at

Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

NASA Astrophysics Data System (ADS)

Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

2016-11-01

Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

Some Correlation Functions in Matrix Product Ground States of One-Dimensional Two-State Chains

NASA Astrophysics Data System (ADS)

Shariati, Ahmad; Aghamohammadi, Amir; Fatollahi, Amir H.; Khorrami, Mohammad

2014-04-01

Consider one-dimensional chains with nearest neighbour interactions, for which to each site correspond two independent states (say up and down), and the ground state is a matrix product state. It has been shown [23] that for such systems, the ground states are linear combinations of specific vectors which are essentially direct products of specific numbers of ups and downs, symmetrized in a generalized manner. By a generalized manner, it is meant that the coefficient corresponding to the interchange of states of two sites, in not necessarily plus one or minus one, but a phase which depends on the Hamiltonian and the position of the two sites. Such vectors are characterized by a phase χ, the N-th power of which is one (where N is the number of sites), and an integer. Corresponding to χ, there is another integer M which is the smallest positive integer that χM is one. Two classes of correlation functions for such systems (basically correlation functions for such vectors) are calculated. The first class consists of correlation functions of tensor products of one-site diagonal observables; the second class consists of correlation functions of tensor products of less than M one-site observables (but not necessarily diagonal).

Correlation processing of polarization inhomogenous images in laser diagnostics of biological tissues

NASA Astrophysics Data System (ADS)

Trifonyuk, L.

2012-10-01

The model of interaction of laser radiation with biological tissue as a two-component amorphous-crystalline matrix was proposed. The processes of formation of polarization of laser radiation are considered, taking into account birefringence network protein fibrils. Measurement of the coordinate distribution of polarization states in the location of the laser micropolarimetr was conducted .The results of investigating the interrelation between the values of correlation (correlation area, asymmetry coefficient and autocorrelation function excess) and fractal (dispersion of logarithmic dependencies of power spectra) parameters are presented. They characterize the coordinate distributions of polarization azimuth of laser images of histological sections of women's reproductive sphere tissues and pathological changes in human organism. The diagnostic criteria of the prolapse of the vaginal tissue arising are determined.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Parameter identification of thermophilic anaerobic degradation of valerate.

PubMed

Flotats, Xavier; Ahring, Birgitte K; Angelidaki, Irini

2003-01-01

The considered mathematical model of the decomposition of valerate presents three unknown kinetic parameters, two unknown stoichiometric coefficients, and three unknown initial concentrations for biomass. Applying a structural identifiability study, we concluded that it is necessary to perform simultaneous batch experiments with different initial conditions for estimating these parameters. Four simultaneous batch experiments were conducted at 55 degrees C, characterized by four different initial acetate concentrations. Product inhibition of valerate degradation by acetate was considered. Practical identification was done optimizing the sum of the multiple determination coefficients for all measured state variables and for all experiments simultaneously. The estimated values of kinetic parameters and stoichiometric coefficients were characterized by the parameter correlation matrix, the confidence interval, and the student's t-test at 5% significance level with positive results except for the saturation constant, for which more experiments for improving its identifiability should be conducted. In this article, we discuss kinetic parameter estimation methods.

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

Complex Analysis of Diffusion Transport and Microstructure of an Intervertebral Disk.

PubMed

Byvaltsev, V A; Kolesnikov, S I; Belykh, E G; Stepanov, I A; Kalinin, A A; Bardonova, L A; Sudakov, N P; Klimenkov, I V; Nikiforov, S B; Semenov, A V; Perfil'ev, D V; Bespyatykh, I V; Antipina, S L; Giers, M; Prul, M

2017-12-01

We studied the relationship between diffusion transport and morphological and microstructural organization of extracellular matrix of human intervertebral disk. Specimens of the lumbar intervertebral disks without abnormalities were studied ex vivo by diffusion-weighed magnetic resonance imaging, histological and immunohistochemical methods, and electron microscopy. Distribution of the diffusion coefficient in various compartments of the intervertebral disk was studied. Significant correlations between diffusion coefficient and cell density in the nucleus pulposus, posterior aspects of annulus fibrosus, and endplate at the level of the posterior annulus fibrosus were detected for each disk. In disks with nucleus pulposus diffusion coefficient below 15×10 -4 mm 2 /sec, collagens X and XI were detected apart from aggrecan and collagens I and II. The results supplement the concept on the relationship between the microstructure and cell composition of various compartments of the intervertebral disk and parameters of nutrient transport.

Immunohistochemical expression of matrix metalloproteinase 13 in chronic periodontitis.

PubMed

Nagasupriya, Alapati; Rao, Donimukkala Bheemalingeswara; Ravikanth, Manyam; Kumar, Nalabolu Govind; Ramachandran, Cinnamanoor Rajmani; Saraswathi, Thillai Rajashekaran

2014-01-01

The extracellular matrix is a complex integrated system responsible for the physiologic properties of connective tissue. Collagen is the major extracellular component that is altered in pathologic conditions, mainly periodontitis. The destruction involves proteolytic enzymes, primarily matrix metalloproteinases (MMPs), which play a key role in mediating and regulating the connective tissue destruction in periodontitis. The study group included 40 patients with clinically diagnosed chronic periodontitis. The control group included 20 patients with clinically normal gingiva covering impacted third molars undergoing extraction or in areas where crown-lengthening procedures were performed. MMP-13 expression was demonstrated using immunohistochemistry in all the gingival biopsies, and the data were analyzed statistically. MMP-13 expression was observed more in chronic periodontitis when compared with normal gingiva. MMP-13 expression was expressed by fibroblasts, lymphocytes, macrophages, plasma cells, and basal cells of the sulcular epithelium. Comparative evaluation of all the clinical and histologic parameters with MMP-13 expression showed high statistical significance with Spearman correlation coefficient. Elevated levels of MMP-13 may play a role in the pathogenesis of chronic periodontitis. There is a direct correlation of increased expression of MMP-13 with various clinical and histologic parameters in disease severity.

Reduction of thermal stresses in continuous fiber reinforced metal matrix composites with interface layers

NASA Technical Reports Server (NTRS)

Jansson, S.; Leckie, F. A.

1990-01-01

The potential of using an interface layer to reduce thermal stresses in the matrix of composites with a mismatch in coefficients of thermal expansion of fiber and matrix was investigated. It was found that compliant layers, with properties of readily available materials, do not have the potential to reduce thermal stresses significantly. However, interface layers with high coefficient of thermal expansion can compensate for the mismatch and reduce thermal stresses in the matrix significantly.

Mechanical properties of several neat polymer matrix materials and unidirectional carbon fiber-reinforced composites

NASA Technical Reports Server (NTRS)

Coguill, Scott L.; Adams, Donald F.

1989-01-01

The mechanical and physical properties of three neat matrix materials, i.e., PEEK (polyetheretherketone) thermoplastic, Hexcel F155 rubber-toughened epoxy and Hercules 8551-7 rubber-toughened epoxy, were experimentally determined. Twelve unidirectional carbon fiber composites, incorporating matrix materials characterized in this or earlier studies (with one exception; the PISO(sub 2)-TPI matrix itself was not characterized), were also tested. These composite systems included AS4/2220-1, AS4/2220-3, T500/R914, IM6/HX1504, T300/4901A (MDA), T700/4901A (MDA), T300/4901B (MPDA), T700/4901B (MPDA), APC2 (AS4/PEEK, ICI), APC2 (AS4/PEEK, Langley Research Center), AS4/8551-7, and AS4/PISO(sub 2)-TPI. For the neat matrix materials, the tensile, shear, fracture toughness, coefficient of thermal expansion, and coefficient of moisture expansion properties were measured as a function of both temperature and moisture content. For the unidirectional composites, axial and transverse tensile, longitudinal shear, coefficient of thermal expansion, and coefficient of moisture expansion properties were determined, at room temperature and 100 C.

Dissecting random and systematic differences between noisy composite data sets.

PubMed

Diederichs, Kay

2017-04-01

Composite data sets measured on different objects are usually affected by random errors, but may also be influenced by systematic (genuine) differences in the objects themselves, or the experimental conditions. If the individual measurements forming each data set are quantitative and approximately normally distributed, a correlation coefficient is often used to compare data sets. However, the relations between data sets are not obvious from the matrix of pairwise correlations since the numerical value of the correlation coefficient is lowered by both random and systematic differences between the data sets. This work presents a multidimensional scaling analysis of the pairwise correlation coefficients which places data sets into a unit sphere within low-dimensional space, at a position given by their CC* values [as defined by Karplus & Diederichs (2012), Science, 336, 1030-1033] in the radial direction and by their systematic differences in one or more angular directions. This dimensionality reduction can not only be used for classification purposes, but also to derive data-set relations on a continuous scale. Projecting the arrangement of data sets onto the subspace spanned by systematic differences (the surface of a unit sphere) allows, irrespective of the random-error levels, the identification of clusters of closely related data sets. The method gains power with increasing numbers of data sets. It is illustrated with an example from low signal-to-noise ratio image processing, and an application in macromolecular crystallography is shown, but the approach is completely general and thus should be widely applicable.

Needs of caregivers of cancer patients: validation of the Mexican version of the Support Person Unmet Needs Survey (SPUNS-SFM).

PubMed

Doubova, Svetlana V; Aguirre-Hernandez, Rebeca; Infante-Castañeda, Claudia; Martinez-Vega, Ingrid; Pérez-Cuevas, Ricardo

2015-10-01

The purpose of this study was to validate the Mexican version of the Support Person Unmet Needs Survey (SPUNS-SFM). A cross-sectional survey that included 826 primary caregivers of cancer patients was conducted from June to December 2013 at the Oncology Hospital of the Mexican Institute of Social Security in Mexico City. The validation procedure comprised (1) content validity through a group of experts; (2) construct validity through an exploratory factor analysis based on the polychoric correlation matrix; (3) internal consistency using Cronbach's alpha; (4) convergent validity between SPUNS-SFM and quality of life, anxiety-and-depression scales by calculating Spearman's rank correlation coefficient;( 5) discriminative validity through the Wilcoxon rank-sum test; and (6) test-retest reliability using intraclass correlation coefficient. SPUNS-SFM has 23 items with six factors accounting for 65 % of the total variance. The domains were concerns about the future, access and continuity of healthcare, information, work and finance, and personal and emotional needs. Cronbach's alpha values ranged from 0.70 to 0.88 among factors. SPUNS-SFM had moderate convergent validity compared with quality of life and depression-and-anxiety scales and good discriminative validity, revealing high needs for younger caregivers and more emotional needs for caregivers of patients with advanced cancer stages. Intraclass correlation coefficient between SPUNS-SFM measurements was 0.78. SPUNS-SFM is a valid and reliable tool to identify needs of caregivers of cancer patients.

SU-F-R-45: The Prognostic Value of Radiotherapy Based On the Changes of Texture Features Between Pre-Treatment and Post-Treatment FDG PET Image for NSCLC Patients

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

Ma, C; Yin, Y

Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculatedmore » by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.« less

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Random matrix approach to cross correlations in financial data

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki; Gopikrishnan, Parameswaran; Rosenow, Bernd; Amaral, Luís A.; Guhr, Thomas; Stanley, H. Eugene

2002-06-01

We analyze cross correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices C of returns constructed from (i) 30-min returns of 1000 US stocks for the 2-yr period 1994-1995, (ii) 30-min returns of 881 US stocks for the 2-yr period 1996-1997, and (iii) 1-day returns of 422 US stocks for the 35-yr period 1962-1996. We test the statistics of the eigenvalues λi of C against a ``null hypothesis'' - a random correlation matrix constructed from mutually uncorrelated time series. We find that a majority of the eigenvalues of C fall within the RMT bounds [λ-,λ+] for the eigenvalues of random correlation matrices. We test the eigenvalues of C within the RMT bound for universal properties of random matrices and find good agreement with the results for the Gaussian orthogonal ensemble of random matrices-implying a large degree of randomness in the measured cross-correlation coefficients. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the eigenvalues outside the RMT bound display systematic deviations from the RMT prediction. In addition, we find that these ``deviating eigenvectors'' are stable in time. We analyze the components of the deviating eigenvectors and find that the largest eigenvalue corresponds to an influence common to all stocks. Our analysis of the remaining deviating eigenvectors shows distinct groups, whose identities correspond to conventionally identified business sectors. Finally, we discuss applications to the construction of portfolios of stocks that have a stable ratio of risk to return.

Identifying Bearing Rotordynamic Coefficients using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.

Coupled Kardar-Parisi-Zhang Equations in One Dimension

NASA Astrophysics Data System (ADS)

Ferrari, Patrik L.; Sasamoto, Tomohiro; Spohn, Herbert

2013-11-01

Over the past years our understanding of the scaling properties of the solutions to the one-dimensional KPZ equation has advanced considerably, both theoretically and experimentally. In our contribution we export these insights to the case of coupled KPZ equations in one dimension. We establish equivalence with nonlinear fluctuating hydrodynamics for multi-component driven stochastic lattice gases. To check the predictions of the theory, we perform Monte Carlo simulations of the two-component AHR model. Its steady state is computed using the matrix product ansatz. Thereby all coefficients appearing in the coupled KPZ equations are deduced from the microscopic model. Time correlations in the steady state are simulated and we confirm not only the scaling exponent, but also the scaling function and the non-universal coefficients.

Learning coefficient of generalization error in Bayesian estimation and vandermonde matrix-type singularity.

PubMed

Aoyagi, Miki; Nagata, Kenji

2012-06-01

The term algebraic statistics arises from the study of probabilistic models and techniques for statistical inference using methods from algebra and geometry (Sturmfels, 2009 ). The purpose of our study is to consider the generalization error and stochastic complexity in learning theory by using the log-canonical threshold in algebraic geometry. Such thresholds correspond to the main term of the generalization error in Bayesian estimation, which is called a learning coefficient (Watanabe, 2001a , 2001b ). The learning coefficient serves to measure the learning efficiencies in hierarchical learning models. In this letter, we consider learning coefficients for Vandermonde matrix-type singularities, by using a new approach: focusing on the generators of the ideal, which defines singularities. We give tight new bound values of learning coefficients for the Vandermonde matrix-type singularities and the explicit values with certain conditions. By applying our results, we can show the learning coefficients of three-layered neural networks and normal mixture models.

Response of selected binomial coefficients to varying degrees of matrix sparseness and to matrices with known data interrelationships

USGS Publications Warehouse

Archer, A.W.; Maples, C.G.

1989-01-01

Numerous departures from ideal relationships are revealed by Monte Carlo simulations of widely accepted binomial coefficients. For example, simulations incorporating varying levels of matrix sparseness (presence of zeros indicating lack of data) and computation of expected values reveal that not only are all common coefficients influenced by zero data, but also that some coefficients do not discriminate between sparse or dense matrices (few zero data). Such coefficients computationally merge mutually shared and mutually absent information and do not exploit all the information incorporated within the standard 2 ?? 2 contingency table; therefore, the commonly used formulae for such coefficients are more complicated than the actual range of values produced. Other coefficients do differentiate between mutual presences and absences; however, a number of these coefficients do not demonstrate a linear relationship to matrix sparseness. Finally, simulations using nonrandom matrices with known degrees of row-by-row similarities signify that several coefficients either do not display a reasonable range of values or are nonlinear with respect to known relationships within the data. Analyses with nonrandom matrices yield clues as to the utility of certain coefficients for specific applications. For example, coefficients such as Jaccard, Dice, and Baroni-Urbani and Buser are useful if correction of sparseness is desired, whereas the Russell-Rao coefficient is useful when sparseness correction is not desired. ?? 1989 International Association for Mathematical Geology.

Estimation and analysis of interannual variations in tropical oceanic rainfall using data from SSM/I

NASA Technical Reports Server (NTRS)

Berg, Wesley

1992-01-01

Rainfall over tropical ocean regions, particularly in the tropical Pacific, is estimated using Special Sensor Microwave/Imager (SSM/I) data. Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-Matrix algorithm. Comparisons with other satellite techniques are made to validate the SSM/I results for the tropical Pacific. The correlation coefficients are relatively high for the three data sets investigated, especially for the annual case.

Application of Artificial Boundary Conditions in Sensitivity-Based Updating of Finite Element Models

DTIC Science & Technology

2007-06-01

is known as the impedance matrix[ ]( )Z Ω . [ ] [ ] 1( ) ( )Z H −Ω = Ω (12) where [ ] 2( )Z K M j C ⎡ ⎤Ω = −Ω + Ω⎣ ⎦ (13) A. REDUCED ORDER...D.L. A correlation coefficient for modal vector analysis. Proceedings of 1st International Modal Analysis Conference, 1982, 110-116. Anton , H ... Rorres , C ., (2005). Elementary Linear Algebra. New York: John Wiley and Sons. Avitable, Peter (2001, January) Experimental Modal Analysis, A Simple

Measurement of spin correlation between top and antitop quarks produced in $$p\\bar{p}$$ collisions at $$\\sqrt{s} = 1.96$$ TeV

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

Abazov, Victor Mukhamedovich

Here, we present a measurement of the correlation between the spins of t and tbar quarks produced in proton-antiproton collisions at the Tevatron Collider at a center-of-mass energy of 1.96 TeV. We apply a matrix element technique to dilepton and single-lepton+jets final states in data accumulated with the D0 detector that correspond to an integrated luminosity of 9.7 fbmore » $$^{-1}$$. The measured value of the correlation coefficient in the off-diagonal basis, $$O_{off} = 0.89 \\pm 0.22$$ (stat + syst), is in agreement with the standard model prediction, and represents evidence for a top-antitop quark spin correlation difference from zero at a level of 4.2 standard deviations.« less

Measurement of spin correlation between top and antitop quarks produced in $$p\\bar{p}$$ collisions at $$\\sqrt{s} = 1.96$$ TeV

DOE PAGES

Abazov, Victor Mukhamedovich

2016-03-25

Here, we present a measurement of the correlation between the spins of t and tbar quarks produced in proton-antiproton collisions at the Tevatron Collider at a center-of-mass energy of 1.96 TeV. We apply a matrix element technique to dilepton and single-lepton+jets final states in data accumulated with the D0 detector that correspond to an integrated luminosity of 9.7 fbmore » $$^{-1}$$. The measured value of the correlation coefficient in the off-diagonal basis, $$O_{off} = 0.89 \\pm 0.22$$ (stat + syst), is in agreement with the standard model prediction, and represents evidence for a top-antitop quark spin correlation difference from zero at a level of 4.2 standard deviations.« less

Expansion of Tabulated Scattering Matrices in Generalized Spherical Functions

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Yang, Ping

2016-01-01

An efficient way to solve the vector radiative transfer equation for plane-parallel turbid media is to Fourier-decompose it in azimuth. This methodology is typically based on the analytical computation of the Fourier components of the phase matrix and is predicated on the knowledge of the coefficients appearing in the expansion of the normalized scattering matrix in generalized spherical functions. Quite often the expansion coefficients have to be determined from tabulated values of the scattering matrix obtained from measurements or calculated by solving the Maxwell equations. In such cases one needs an efficient and accurate computer procedure converting a tabulated scattering matrix into the corresponding set of expansion coefficients. This short communication summarizes the theoretical basis of this procedure and serves as the user guide to a simple public-domain FORTRAN program.

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

DOE PAGES

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William; ...

2018-01-31

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

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

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

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William

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

Determination of the reduced matrix of the piezoelectric, dielectric, and elastic material constants for a piezoelectric material with C∞ symmetry.

PubMed

Sherrit, Stewart; Masys, Tony J; Wiederick, Harvey D; Mukherjee, Binu K

2011-09-01

We present a procedure for determining the reduced piezoelectric, dielectric, and elastic coefficients for a C(∞) material, including losses, from a single disk sample. Measurements have been made on a Navy III lead zirconate titanate (PZT) ceramic sample and the reduced matrix of coefficients for this material is presented. In addition, we present the transform equations, in reduced matrix form, to other consistent material constant sets. We discuss the propagation of errors in going from one material data set to another and look at the limitations inherent in direct calculations of other useful coefficients from the data.

Molecular dynamics insights into the structural and diffusive properties of ZIF-8/PDMS mixed matrix membranes in the n-butanol/water pervaporation process

NASA Astrophysics Data System (ADS)

Sun, Tao; Fang, Manquan; Wu, Zhen; Yu, Lixin; Li, Jiding

2017-04-01

Molecular dynamics (MD) simulation was used to study the structural and diffusive properties of zeolitic imidazolate framework-8 (ZIF-8)/polydimethylsiloxane (PDMS), a novel alcohol-permselective mixed matrix membrane (MMM). Simulation models of one pure PDMS membrane and three ZIF-8/PDMS MMMs with increasing loadings were successfully constructed. Non-bond energy turned out to be a strong attractive interaction between the PDMS matrix and ZIF-8 cells. The morphology and mobility of PDMS chains were characterized by mean square displacement (MSD). The fraction of free volume (FFV) of the pure membrane and MMMs was calculated and showed declining trends with increasing ZIF-8 loadings. The diffusion coefficients of n-butanol and water molecules were calculated by the Einstein relation. {D}n-\\text{butanol} first increased then decreased, while {D}{{water}} decreased with the increasing loadings. The mechanism of selective diffusion behaviour was investigated and it was found that the inner channels of ZIF-8 provided selective pathways for n-butanol. Diffusion coefficients were correlated with FFV and the results showed that the logarithm of {D}{{water}} demonstrated a good linear relation with the inverse FFV and was in agreement with the free volume theory, while {D}n-\\text{butanol} showed a significant deviation in the case of MMM-1 due to the selective diffusion channels provided by ZIF-8.

Controlled growth of Au nanoparticles in co-evaporated metal/polymer composite films and their optical and electrical properties

NASA Astrophysics Data System (ADS)

Takele, H.; Schürmann, U.; Greve, H.; Paretkar, D.; Zaporojtchenko, V.; Faupel, F.

2006-02-01

Nanocomposite films containing Au nanoparticles embedded in a polymer matrix were prepared by vapour phase co-deposition of Au and polymers (Teflon AF and Poly(α -methylstyrene)) in high vacuum. The microstructure of the composite materials as well as metal content strongly depend on the condensation coefficient of the Au atoms, the deposition rates of the components, the substrate temperature, and the type of polymer matrix. The condensation coefficient, which varies between 0.03 and 1, was determined from energy dispersive X-ray spectrometer (EDX) and surface profilometry. It is shown that the microstructure of nanocomposites (size, size distribution, and interparticle separation of metal clusters), which was determined by transmission electron microscopy, can be controlled by the deposition parameters and the choice of polymer matrix. The optical absorption in the visible region due to the particle plasmon resonance has a strong dependence on the metal filling factor. The correlation between the microstructure of nanocomposites and optical properties, studied using UV-Vis spectroscopy, was also established. Further more, the electrical properties of the composites were studied as a function of the metal volume fraction. It was observed that the nanocomposite films exhibit a percolation threshold at a metal volume fraction of 0.43 and 0.20 for gold nanoclusters in Teflon AF and Poly(α-methylstyrene), respectively.

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.

Size effects on magnetoelectric response of multiferroic composite with inhomogeneities

NASA Astrophysics Data System (ADS)

Yue, Y. M.; Xu, K. Y.; Chen, T.; Aifantis, E. C.

2015-12-01

This paper investigates the influence of size effects on the magnetoelectric performance of multiferroic composite with inhomogeneities. Based on a simple model of gradient elasticity for multiferroic materials, the governing equations and boundary conditions are obtained from an energy variational principle. The general formulation is applied to consider an anti-plane problem of multiferroic composites with inhomogeneities. This problem is solved analytically and the effective magnetoelectric coefficient is obtained. The influence of the internal length (grain size or particle size) on the effective magnetoelectric coefficients of piezoelectric/piezomagnetic nanoscale fibrous composite is numerically evaluated and analyzed. The results suggest that with the increase of the internal length of piezoelectric matrix (PZT and BaTiO3), the magnetoelectric coefficient increases, but the rate of increase is ratcheting downwards. If the internal length of piezoelectric matrix remains unchanged, the magnetoelectric coefficient will decrease with the increase of internal length scale of piezomagnetic nonfiber (CoFe2O3). In a composite consisiting of a piezomagnetic matrix (CoFe2O3) reinforced with piezoelectric nanofibers (BaTiO3), an increase of the internal length in the piezomagnetic matrix, results to a decrease of the magnetoelectric coefficient, with the rate of decrease diminishing.

An Efficient Scheme of Quantum Wireless Multi-hop Communication using Coefficient Matrix

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zha, Xin-Wei; Duan, Ya-Jun; Sun, Xin-Mei

2015-08-01

By defining the coefficient matrix, a new quantum teleportation scheme in quantum wireless multi-hop network is proposed. With the help of intermediate nodes, an unknown qubit state can be teleported between two distant nodes which do not share entanglement in advance. Arbitrary Bell pairs and entanglement swapping are utilized for establishing quantum channel among intermediate nodes. Using collapsed matrix, the initial quantum state can be perfectly recovered at the destination.

Combination of nano-material enrichment and dead-end filtration for uniform and rapid sample preparation in matrix-assisted laser desorption/ionization mass spectrometry.

PubMed

Wu, Zengnan; Khan, Mashooq; Mao, Sifeng; Lin, Ling; Lin, Jin-Ming

2018-05-01

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a fast analysis tool for the detection of a wide range of analytes. However, heterogeneous distribution of matrix/analyte cocrystal, variation in signal intensity and poor experimental reproducibility at different locations of the same spot means difficulty in quantitative analysis. In this work, carbon nanotubes (CNTs) were employed as adsorbent for analyte cum matrix on a conductive porous membrane as a novel mass target plate. The sample pretreatment step was achieved by enrichment and dead-end filtration and dried by a solid-liquid separation. This approach enables the homogeneous distribution of analyte in the matrix, good shot-to-shot reproducibility in signals and quantitative detection of peptide and protein at different concentrations with correlation coefficient (R 2 ) of 0.9920 and 0.9909, respectively. The simple preparation of sample in a short time, uniform distribution of analyte, easy quantitative detection, and high reproducibility makes this technique useful and may diversify the application of MALDI-MS for quantitative detection of a variety of proteins. Copyright © 2018 Elsevier B.V. All rights reserved.

MICRO-SCALE CFD MODELING OF OSCILLATING FLOW IN A REGENERATOR

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

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

2010-04-09

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

Application of principal component analysis in protein unfolding: an all-atom molecular dynamics simulation study.

PubMed

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-28

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide-ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Application of principal component analysis in protein unfolding: An all-atom molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-01

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide—ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

NASA Astrophysics Data System (ADS)

Gligor, M.; Ausloos, M.

2007-05-01

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

Effectiveness of water-air and octanol-air partition coefficients to predict lipophilic flavor release behavior from O/W emulsions.

PubMed

Tamaru, Shunji; Igura, Noriyuki; Shimoda, Mitsuya

2018-01-15

Flavor release from food matrices depends on the partition of volatile flavor compounds between the food matrix and the vapor phase. Thus, we herein investigated the relationship between released flavor concentrations and three different partition coefficients, namely octanol-water, octanol-air, and water-air, which represented the oil, water, and air phases present in emulsions. Limonene, 2-methylpyrazine, nonanal, benzaldehyde, ethyl benzoate, α-terpineol, benzyl alcohol, and octanoic acid were employed. The released concentrations of these flavor compounds from oil-in-water (O/W) emulsions were measured under equilibrium using static headspace gas chromatography. The results indicated that water-air and octanol-air partition coefficients correlated with the logarithms of the released concentrations in the headspace for highly lipophilic flavor compounds. Moreover, the same tendency was observed over various oil volume ratios in the emulsions. Our findings therefore suggest that octanol-air and water-air partition coefficients can be used to predict the released concentration of lipophilic flavor compounds from O/W emulsions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

NASA Astrophysics Data System (ADS)

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen; Ovchinnikov, Mikhail

2011-01-01

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling multispecies processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense. Existing lower and upper bounds on linear correlation coefficients are too loose to serve directly as a method to predict subgrid correlations. Therefore, this paper proposes an alternative method that begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are populated here using a "cSigma" parameterization that we introduce based on the aforementioned bounds on correlations. The method has three advantages: (1) the computational expense is tolerable; (2) the correlations are, by construction, guaranteed to be consistent with each other; and (3) the methodology is fairly general and hence may be applicable to other problems. The method is tested noninteractively using simulations of three Arctic mixed-phase cloud cases from two field experiments: the Indirect and Semi-Direct Aerosol Campaign and the Mixed-Phase Arctic Cloud Experiment. Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.

Judging in Rhythmic Gymnastics at Different Levels of Performance.

PubMed

Leandro, Catarina; Ávila-Carvalho, Lurdes; Sierra-Palmeiro, Elena; Bobo-Arce, Marta

2017-12-01

This study aimed to analyse the quality of difficulty judging in rhythmic gymnastics, at different levels of performance. The sample consisted of 1152 difficulty scores concerning 288 individual routines, performed in the World Championships in 2013. The data were analysed using the mean absolute judge deviation from the final difficulty score, a Cronbach's alpha coefficient and intra-class correlations, for consistency and reliability assessment. For validity assessment, mean deviations of judges' difficulty scores, the Kendall's coefficient of concordance W and ANOVA eta-squared values were calculated. Overall, the results in terms of consistency (Cronbach's alpha mostly above 0.90) and reliability (intra-class correlations for single and average measures above 0.70 and 0.90, respectively) were satisfactory, in the first and third parts of the ranking on all apparatus. The medium level gymnasts, those in the second part of the ranking, had inferior reliability indices and highest score dispersion. In this part, the minimum of corrected item-total correlation of individual judges was 0.55, with most values well below, and the matrix for between-judge correlations identified remarkable inferior correlations. These findings suggest that the quality of difficulty judging in rhythmic gymnastics may be compromised at certain levels of performance. In future, special attention should be paid to the judging analysis of the medium level gymnasts, as well as the Code of Points applicability at this level.

Judging in Rhythmic Gymnastics at Different Levels of Performance

PubMed Central

Ávila-Carvalho, Lurdes; Sierra-Palmeiro, Elena; Bobo-Arce, Marta

2017-01-01

Abstract This study aimed to analyse the quality of difficulty judging in rhythmic gymnastics, at different levels of performance. The sample consisted of 1152 difficulty scores concerning 288 individual routines, performed in the World Championships in 2013. The data were analysed using the mean absolute judge deviation from the final difficulty score, a Cronbach’s alpha coefficient and intra-class correlations, for consistency and reliability assessment. For validity assessment, mean deviations of judges’ difficulty scores, the Kendall’s coefficient of concordance W and ANOVA eta-squared values were calculated. Overall, the results in terms of consistency (Cronbach’s alpha mostly above 0.90) and reliability (intra-class correlations for single and average measures above 0.70 and 0.90, respectively) were satisfactory, in the first and third parts of the ranking on all apparatus. The medium level gymnasts, those in the second part of the ranking, had inferior reliability indices and highest score dispersion. In this part, the minimum of corrected item-total correlation of individual judges was 0.55, with most values well below, and the matrix for between-judge correlations identified remarkable inferior correlations. These findings suggest that the quality of difficulty judging in rhythmic gymnastics may be compromised at certain levels of performance. In future, special attention should be paid to the judging analysis of the medium level gymnasts, as well as the Code of Points applicability at this level. PMID:29339996

Development of an Extended-Release Formulation for Apremilast and a Level A in Vitro-in Vivo Correlation Study in Beagle Dogs.

PubMed

Tang, Meiqiong; Hu, Ping; Huang, Shigui; Zheng, Qiang; Yu, Hao; He, Yun

2016-11-01

The primary objective of the present study was to develop extended-release matrix formulations of apremilast for the oral delivery and to study their in vitro and in vivo correlation. Five extended-release formulations containing hydroxypropylmethylcellulose (HPMC) as the retarding excipient with different release rate of apremilast were prepared. Dissolution tests of all the formulated tablets were performed in water, pH 4.0 and 6.8 buffer solutions. The in vitro release kinetics was studied and supported by Korsmeyer-Peppas's equation as it presented highest values of correlation coefficients (r 2 up to 0.966). Among all formulated tablets, F2 (HPMC 25%) and F4 (HPMC 35%) were selected to perform an in vivo study in beagle dogs to obtain various pharmacokinetic parameters, i.e., peak plasma concentration (C max ), time to peak plasma concentration (t max ), area under the plasma-concentration vs. time curve (AUC). Higher t max and t 1/2 , lower C max and elimination coefficient (K e ) were observed for both extended formulations compared to marketed immediate-release products (Otezla ® ). Level A in vitro-in vivo correlations were created with the help of Wagner-Nelson and numeric deconvolution methods. Both formulations showed good in vitro-in vivo correlations whose accuracies were further verified by an internal validation.

Invertible flexible matrices

NASA Astrophysics Data System (ADS)

Justino, Júlia

2017-06-01

Matrices with coefficients having uncertainties of type o (.) or O (.), called flexible matrices, are studied from the point of view of nonstandard analysis. The uncertainties of the afore-mentioned kind will be given in the form of the so-called neutrices, for instance the set of all infinitesimals. Since flexible matrices have uncertainties in their coefficients, it is not possible to define the identity matrix in an unique way and so the notion of spectral identity matrix arises. Not all nonsingular flexible matrices can be turned into a spectral identity matrix using Gauss-Jordan elimination method, implying that that not all nonsingular flexible matrices have the inverse matrix. Under certain conditions upon the size of the uncertainties appearing in a nonsingular flexible matrix, a general theorem concerning the boundaries of its minors is presented which guarantees the existence of the inverse matrix of a nonsingular flexible matrix.

Role of protein fluctuation correlations in electron transfer in photosynthetic complexes.

PubMed

Nesterov, Alexander I; Berman, Gennady P

2015-04-01

We consider the dependence of the electron transfer in photosynthetic complexes on correlation properties of random fluctuations of the protein environment. The electron subsystem is modeled by a finite network of connected electron (exciton) sites. The fluctuations of the protein environment are modeled by random telegraph processes, which act either collectively (correlated) or independently (uncorrelated) on the electron sites. We derived an exact closed system of first-order linear differential equations with constant coefficients, for the average density matrix elements and for their first moments. Under some conditions, we obtained analytic expressions for the electron transfer rates and found the range of parameters for their applicability by comparing with the exact numerical simulations. We also compared the correlated and uncorrelated regimes and demonstrated numerically that the uncorrelated fluctuations of the protein environment can, under some conditions, either increase or decrease the electron transfer rates.

Techniques for Fault Detection and Visualization of Telemetry Dependence Relationships for Root Cause Fault Analysis in Complex Systems

NASA Astrophysics Data System (ADS)

Guy, Nathaniel

This thesis explores new ways of looking at telemetry data, from a time-correlative perspective, in order to see patterns within the data that may suggest root causes of system faults. It was thought initially that visualizing an animated Pearson Correlation Coefficient (PCC) matrix for telemetry channels would be sufficient to give new understanding; however, testing showed that the high dimensionality and inability to easily look at change over time in this approach impeded understanding. Different correlative techniques, combined with the time curve visualization proposed by Bach et al (2015), were adapted to visualize both raw telemetry and telemetry data correlations. Review revealed that these new techniques give insights into the data, and an intuitive grasp of data families, which show the effectiveness of this approach for enhancing system understanding and assisting with root cause analysis for complex aerospace systems.

Feature extraction using gray-level co-occurrence matrix of wavelet coefficients and texture matching for batik motif recognition

NASA Astrophysics Data System (ADS)

Suciati, Nanik; Herumurti, Darlis; Wijaya, Arya Yudhi

2017-02-01

Batik is one of Indonesian's traditional cloth. Motif or pattern drawn on a piece of batik fabric has a specific name and philosopy. Although batik cloths are widely used in everyday life, but only few people understand its motif and philosophy. This research is intended to develop a batik motif recognition system which can be used to identify motif of Batik image automatically. First, a batik image is decomposed into sub-images using wavelet transform. Six texture descriptors, i.e. max probability, correlation, contrast, uniformity, homogenity and entropy, are extracted from gray-level co-occurrence matrix of each sub-image. The texture features are then matched to the template features using canberra distance. The experiment is performed on Batik Dataset consisting of 1088 batik images grouped into seven motifs. The best recognition rate, that is 92,1%, is achieved using feature extraction process with 5 level wavelet decomposition and 4 directional gray-level co-occurrence matrix.

In Vivo Validation of Volume Flow Measurements of Pulsatile Flow Using a Clinical Ultrasound System and Matrix Array Transducer.

PubMed

Hudson, John M; Williams, Ross; Milot, Laurent; Wei, Qifeng; Jago, James; Burns, Peter N

2017-03-01

The goal of this study was to evaluate the accuracy of a non-invasive C-plane Doppler estimation of pulsatile blood flow in the lower abdominal vessels of a porcine model. Doppler ultrasound measurements from a matrix array transducer system were compared with invasive volume flow measurements made on the same vessels with a surgically implanted ultrasonic transit-time flow probe. For volume flow rates ranging from 60 to 750 mL/min, agreement was very good, with a Pearson correlation coefficient of 0.97 (p < 0.0001) and a mean bias of -4.2%. The combination of 2-D matrix array technology and fast processing gives this Doppler method clinical potential, as many of the user- and system-dependent parameters of previous methods, including explicit vessel angle and diameter measurements, are eliminated. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Principle component analysis (PCA) for investigation of relationship between population dynamics of microbial pathogenesis, chemical and sensory characteristics in beef slices containing Tarragon essential oil.

PubMed

Alizadeh Behbahani, Behrooz; Tabatabaei Yazdi, Farideh; Shahidi, Fakhri; Mortazavi, Seyed Ali; Mohebbi, Mohebbat

2017-04-01

Principle component analysis (PCA) was employed to examine the effect of the exerted treatments on the beef shelf life as well as discovering the correlations between the studied responses. Considering the variability of the dimensions of the responses, correlation coefficients were applied to form the matrix and extract the eigenvalue. Antimicrobial effect was evaluated on 10 pathogenic microorganisms through the methods of hole-plate diffusion method, disk diffusion method, pour plate method, minimum inhibitory concentration and minimum bactericidal/fungicidal concentration. Antioxidant potential and total phenolic content were examined through the method of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Folin-Ciocalteu method, respectively. The components were identified through gas chromatography and gas chromatography/mass spectrometry. Barhang seed mucilage (BSM) based edible coating containing 0, 0.5, 1 and 1.5% (w/w) Tarragon (T) essential oil mix were applied on beef slices to control the growth of pathogenic microorganisms. Microbiological (total viable count, psychrotrophic count, Escherichia coli, Staphylococcus aureus and fungi), chemical (thiobarbituric acid, peroxide value and pH) and sensory characteristics (odor, color and overall acceptability) analysis measurements were made during the storage periodically. PCA was employed to examine the effect of the exerted treatments on the beef shelf life as well as discovering the correlations between the studied responses. Considering the variability of the dimensions of the responses, correlation coefficients were applied to form the matrix and extract the eigenvalue. The PCA showed that the properties of the uncoated meat samples on the 9th, 12th, 15th and 18th days of storage are continuously changing independent of the exerted treatments on the other samples. This reveals the effect of the exerted treatments on the samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Note on coefficient matrices from stochastic Galerkin methods for random diffusion equations

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

Zhou Tao, E-mail: tzhou@lsec.cc.ac.c; Tang Tao, E-mail: ttang@hkbu.edu.h

2010-11-01

In a recent work by Xiu and Shen [D. Xiu, J. Shen, Efficient stochastic Galerkin methods for random diffusion equations, J. Comput. Phys. 228 (2009) 266-281], the Galerkin methods are used to solve stochastic diffusion equations in random media, where some properties for the coefficient matrix of the resulting system are provided. They also posed an open question on the properties of the coefficient matrix. In this work, we will provide some results related to the open question.

[Evaluation of the Peusner's coefficients matrix for polymeric membrane and ternary non-electrolyte solutions].

PubMed

Jasik-Slęzak, Jolanta; Slęzak-Prochazka, Izabella; Slęzak, Andrzej

2014-01-01

A system of network forms of Kedem-Katchalsky (K-K) equations for ternary non-electrolyte solutions is made of eight matrix equations containing Peusner's coefficients R(ij), L(ij), H(ij), W(ij), K(ij), N(ij), S(ij) or P(ij) (i, j ∈ {1, 2, 3}). The equations are the result of symmetric or hybrid transformation of the classic form of K-K equations by the use of methods of Peusner's network thermodynamics (PNT). Calculating concentration dependences of the determinant of Peusner's coefficients matrixes R(ij), L(ij), H(ij), W(ij), S(ij), N(ij), K(ij) and P(ij) (i, j ∈ {1, 2, 3}). The material used in the experiment was a hemodialysis Nephrophan membrane with specified transport properties (L(p), σ, Ω) in aqueous glucose and ethanol solution. The method involved equations for determinants of the matrixes coefficients R(ij), L(ij), H(ij), W(ij), S(ij), N(ij), K(ij) or P(ij) (i, j ∈ {1, 2, 3}). The objective of calculations were dependences of determinants of Peusner's coeffcients matrixes R(ij), L(ij), H(ij), W(ij), S(ij), N(ij), K(ij) or P(ij) (i, j ∈ {1, 2, 3}) within the conditions of solution homogeneity upon an average concentration of one component of solution in the membrane (C1) with a determined value of the second component (C2). The method of calculating the determinants of Peusner's coeffcients matrixes R(ij), L(ij), H(ij), W(ij), S(ij), N(ij), K(ij) or P(ij) (i, j ∈ {1, 2, 3}) is a new tool that may be applicable in studies on membrane transport. Calculations showed that the coefficients are sensitive to concentration and composition of solutions separated by a polymeric membrane.

A fast collocation method for a variable-coefficient nonlocal diffusion model

NASA Astrophysics Data System (ADS)

Wang, Che; Wang, Hong

2017-02-01

We develop a fast collocation scheme for a variable-coefficient nonlocal diffusion model, for which a numerical discretization would yield a dense stiffness matrix. The development of the fast method is achieved by carefully handling the variable coefficients appearing inside the singular integral operator and exploiting the structure of the dense stiffness matrix. The resulting fast method reduces the computational work from O (N3) required by a commonly used direct solver to O (Nlog ⁡ N) per iteration and the memory requirement from O (N2) to O (N). Furthermore, the fast method reduces the computational work of assembling the stiffness matrix from O (N2) to O (N). Numerical results are presented to show the utility of the fast method.

Inter-subject variability of muscle synergies during bench press in power lifters and untrained individuals.

PubMed

Kristiansen, M; Madeleine, P; Hansen, E A; Samani, A

2015-02-01

The purpose of the study was to elucidate the role of expertise on muscle synergies involved in bench press. Ten expert power lifters (EXP) and nine untrained participants (UNT) completed three sets of eight repetitions at 60% of three repetition maximum in bench press. Muscle synergies were extracted from surface electromyography data of 21 bench press cycles using non-negative matrix factorization algorithm. The synergy activation coefficient represents the relative contribution of the muscle synergy to the overall muscle activity pattern, while the muscle synergy vector represents the relative weighting of each muscle within each synergy. Describing more than 90% of the variability, two muscle synergies reflected the eccentric and concentric phase. The cross-correlations (ρ(max)) for synergy activation coefficient 2 (concentric phase) were 0.83 [0.71;0.88] and 0.59 [0.49;0.77] [Median ρ(max) (25th;75th percentile)] (P = 0.001) in UNT and EXP, respectively. Median correlation coefficient (ρ) for muscle synergy vector 2 was 0.15 [-0.08;0.46] and 0.48 [0.02;0.70] (P = 0.03) in UNT and EXP, respectively. Thus, EXP showed larger inter-subject variability than UNT in the synergy activation coefficient during the concentric phase, while the muscle synergy vectors were less variable in EXP. This points at the importance of a specialized neural strategy in elite bench press performance. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Factorization and fitting of molecular scattering information

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

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

1977-12-15

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

Estimating time-varying conditional correlations between stock and foreign exchange markets

NASA Astrophysics Data System (ADS)

Tastan, Hüseyin

2006-02-01

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

Spectra of random networks in the weak clustering regime

NASA Astrophysics Data System (ADS)

Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen; Rodrigues, Francisco A.

2018-03-01

The asymptotic behavior of dynamical processes in networks can be expressed as a function of spectral properties of the corresponding adjacency and Laplacian matrices. Although many theoretical results are known for the spectra of traditional configuration models, networks generated through these models fail to describe many topological features of real-world networks, in particular non-null values of the clustering coefficient. Here we study effects of cycles of order three (triangles) in network spectra. By using recent advances in random matrix theory, we determine the spectral distribution of the network adjacency matrix as a function of the average number of triangles attached to each node for networks without modular structure and degree-degree correlations. Implications to network dynamics are discussed. Our findings can shed light in the study of how particular kinds of subgraphs influence network dynamics.

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling Single Well Injection-Withdrawal (SWIW) Tests for Characterization of Complex Fracture-Matrix Systems

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

Cotte, F.P.; Doughty, C.; Birkholzer, J.

2010-11-01

The ability to reliably predict flow and transport in fractured porous rock is an essential condition for performance evaluation of geologic (underground) nuclear waste repositories. In this report, a suite of programs (TRIPOLY code) for calculating and analyzing flow and transport in two-dimensional fracture-matrix systems is used to model single-well injection-withdrawal (SWIW) tracer tests. The SWIW test, a tracer test using one well, is proposed as a useful means of collecting data for site characterization, as well as estimating parameters relevant to tracer diffusion and sorption. After some specific code adaptations, we numerically generated a complex fracture-matrix system for computationmore » of steady-state flow and tracer advection and dispersion in the fracture network, along with solute exchange processes between the fractures and the porous matrix. We then conducted simulations for a hypothetical but workable SWIW test design and completed parameter sensitivity studies on three physical parameters of the rock matrix - namely porosity, diffusion coefficient, and retardation coefficient - in order to investigate their impact on the fracture-matrix solute exchange process. Hydraulic fracturing, or hydrofracking, is also modeled in this study, in two different ways: (1) by increasing the hydraulic aperture for flow in existing fractures and (2) by adding a new set of fractures to the field. The results of all these different tests are analyzed by studying the population of matrix blocks, the tracer spatial distribution, and the breakthrough curves (BTCs) obtained, while performing mass-balance checks and being careful to avoid some numerical mistakes that could occur. This study clearly demonstrates the importance of matrix effects in the solute transport process, with the sensitivity studies illustrating the increased importance of the matrix in providing a retardation mechanism for radionuclides as matrix porosity, diffusion coefficient, or retardation coefficient increase. Interestingly, model results before and after hydrofracking are insensitive to adding more fractures, while slightly more sensitive to aperture increase, making SWIW tests a possible means of discriminating between these two potential hydrofracking effects. Finally, we investigate the possibility of inferring relevant information regarding the fracture-matrix system physical parameters from the BTCs obtained during SWIW testing.« less

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

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

Telfeyan, Katherine Christina; Ware, Stuart Douglas; Reimus, Paul William

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

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

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

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen

2011-08-16

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense.Existing lower and upper bounds (inequalities) on linear correlation coefficients provide useful guidance, but these bounds are too loose to serve directly as a method to predict subgrid correlations. Therefore,more » this paper proposes an alternative method that is based on a blend of theory and empiricism. The method begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are parameterized here using a cosine row-wise formula that is inspired by the aforementioned bounds on correlations. The method has three advantages: 1) the computational expense is tolerable; 2) the correlations are, by construction, guaranteed to be consistent with each other; and 3) the methodology is fairly general and hence may be applicable to other problems. The method is tested non-interactively using simulations of three Arctic mixed-phase cloud cases from two different field experiments: the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE). Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.« less

Influence of temperature variations on the entropy and correlation of the Grey-Level Co-occurrence Matrix from B-Mode images.

PubMed

Alvarenga, André V; Teixeira, César A; Ruano, Maria Graça; Pereira, Wagner C A

2010-02-01

In this work, the feasibility of texture parameters extracted from B-Mode images were explored in quantifying medium temperature variation. The goal is to understand how parameters obtained from the gray-level content can be used to improve the actual state-of-the-art methods for non-invasive temperature estimation (NITE). B-Mode images were collected from a tissue mimic phantom heated in a water bath. The phantom is a mixture of water, glycerin, agar-agar and graphite powder. This mixture aims to have similar acoustical properties to in vivo muscle. Images from the phantom were collected using an ultrasound system that has a mechanical sector transducer working at 3.5 MHz. Three temperature curves were collected, and variations between 27 and 44 degrees C during 60 min were allowed. Two parameters (correlation and entropy) were determined from Grey-Level Co-occurrence Matrix (GLCM) extracted from image, and then assessed for non-invasive temperature estimation. Entropy values were capable of identifying variations of 2.0 degrees C. Besides, it was possible to quantify variations from normal human body temperature (37 degrees C) to critical values, as 41 degrees C. In contrast, despite correlation parameter values (obtained from GLCM) presented a correlation coefficient of 0.84 with temperature variation, the high dispersion of values limited the temperature assessment.

In situ estimation of the effective chemical diffusion coefficient of a rock matrix in a fractured aquifer

USGS Publications Warehouse

Gebrekristos, R.A.; Shapiro, A.M.; Usher, B.H.

2008-01-01

An in situ method of estimating the effective diffusion coefficient for a chemical constituent that diffuses into the primary porosity of a rock is developed by abruptly changing the concentration of the dissolved constituent in a borehole in contact with the rock matrix and monitoring the time-varying concentration. The experiment was conducted in a borehole completed in mudstone on the campus of the University of the Free State in Bloemfontein, South Africa. Numerous tracer tests were conducted at this site, which left a residual concentration of sodium chloride in boreholes that diffused into the rock matrix over a period of years. Fresh water was introduced into a borehole in contact with the mudstone, and the time-varying increase of chloride was observed by monitoring the electrical conductivity (EC) at various depths in the borehole. Estimates of the effective diffusion coefficient were obtained by interpreting measurements of EC over 34 d. The effective diffusion coefficient at a depth of 36 m was approximately 7.8??10-6 m2/d, but was sensitive to the assumed matrix porosity. The formation factor and mass flux for the mudstone were also estimated from the experiment. ?? Springer-Verlag 2007.

Supportive care needs of Mexican adult cancer patients: validation of the Mexican version of the Short-Form Supportive Care Needs Questionnaire (SCNS-SFM).

PubMed

Doubova, Svetlana V; Aguirre-Hernandez, Rebeca; Gutiérrez-de la Barrera, Marcos; Infante-Castañeda, Claudia; Pérez-Cuevas, Ricardo

2015-09-01

The purpose of this study is to validate the Mexican version of the Short-Form Supportive Care Needs survey (SCNS-SFM). A cross-sectional survey was conducted from June to December 2013 at the Oncology Hospital of the Mexican Institute of Social Security in Mexico City. The study included 825 subsequent cancer patients >20 years of age with all forms of solid cancer. Patients had prior surgical removal of histologically confirmed cancer and attended outpatient consultations. Validation of SCNS-SFM included the following: (1) content validity through a group of experts; (2) construct validity through an exploratory factor analysis based on the polychoric correlation matrix; (3) internal consistency using Cronbach's alpha; (4) convergent validity between SCNS-SFM and quality of life, anxiety, and depression scales by calculating Pearson's correlation coefficient; (5) discriminative validity through analysis of MANOVAs; and (6) test-retest reliability using intraclass correlation coefficient calculations. SCNS-SFM has 33 items with five factors accounting for 59 % of total variance. Cronbach's alpha values ranged from 0.78 to 0.90 among factors. SCNS-SFM has good convergent validity compared with quality of life and depression and anxiety scales and good discriminative validity, revealing great information, psychological support, and physical daily living needs for women, patients <60 years, and high physical daily living needs for those with <1 year since cancer diagnosis, with advanced disease stages and current chemo- or radiotherapy. Intraclass correlation coefficient between SCNS-SFM measurements was 0.9. SCNS-SFM has acceptable psychometric properties and is suitable to evaluate supportive care needs of cancer patients.

Laboratory Experiments to Evaluate Matrix Diffusion of Dissolved Organic Carbon Carbon-14 in Southern Nevada Fractured-rock Aquifers

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

Hershey, Ronald L.; Fereday, Wyatt

Dissolved inorganic carbon (DIC) carbon-14 ( 14C) is used to estimate groundwater ages by comparing the DIC 14C content in groundwater in the recharge area to the DIC 14C content in the downgradient sampling point. However, because of chemical reactions and physical processes between groundwater and aquifer rocks, the amount of DIC 14C in groundwater can change and result in 14C loss that is not because of radioactive decay. This loss of DIC 14C results in groundwater ages that are older than the actual groundwater ages. Alternatively, dissolved organic carbon (DOC) 14C in groundwater does not react chemically with aquifermore » rocks, so DOC 14C ages are generally younger than DIC 14C ages. In addition to chemical reactions, 14C ages may also be altered by the physical process of matrix diffusion. The net effect of a continuous loss of 14C to the aquifer matrix by matrix diffusion and then radioactive decay is that groundwater appears to be older than it actually is. Laboratory experiments were conducted to measure matrix diffusion coefficients for DOC 14C in volcanic and carbonate aquifer rocks from southern Nevada. Experiments were conducted using bromide (Br-) as a conservative tracer and 14C-labeled trimesic acid (TMA) as a surrogate for groundwater DOC. Outcrop samples from six volcanic aquifers and five carbonate aquifers in southern Nevada were used. The average DOC 14C matrix diffusion coefficient for volcanic rocks was 2.9 x 10 -7 cm 2/s, whereas the average for carbonate rocks was approximately the same at 1.7 x 10 -7 cm 2/s. The average Br- matrix diffusion coefficient for volcanic rocks was 10.4 x 10 -7 cm 2/s, whereas the average for carbonate rocks was less at 6.5 x 10 -7 cm 2/s. Carbonate rocks exhibited greater variability in DOC 14C and Br- matrix diffusion coefficients than volcanic rocks. These results confirmed, at the laboratory scale, that the diffusion of DOC 14C into southern Nevada volcanic and carbonate aquifers is slower than DIC 14C. Because of the apparent sorption of 14C-labeled TMA in the experiments, matrix diffusion coefficients are likely even lower. The reasons for the higher than expected Br-/ 14C-labeled TMA are unknown. Because the molecular size of TMA is on the low end of the range in molecular size for typical humic substances, the matrix diffusion coefficients for the 14C-labeled TMA likely represent close to the maximum diffusion rates for DOC 14C in the volcanic and carbonate aquifers in southern Nevada.« less

Quantitative Evaluation of Head and Neck Cancer Treatment-Related Dysphagia in the Development of a Personalized Treatment Deintensification Paradigm.

PubMed

Quon, Harry; Hui, Xuan; Cheng, Zhi; Robertson, Scott; Peng, Luke; Bowers, Michael; Moore, Joseph; Choflet, Amanda; Thompson, Alex; Muse, Mariah; Kiess, Ana; Page, Brandi; Fakhry, Carole; Gourin, Christine; O'Hare, Jolyne; Graham, Peter; Szczesniak, Michal; Maclean, Julia; Cook, Ian; McNutt, Todd

2017-12-01

To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment-related dysphagia (HNCTD). Irradiated HNC subjects seen in follow-up care (April 2015 to December 2015) who prospectively completed the Sydney Swallow Questionnaire (SSQ) and the MD Anderson Dysphagia Inventory (MDADI) concurrently on the web interface to our Oncospace database were evaluated. A correlation matrix quantified the relationship between the SSQ and MDADI. Machine-learning unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis to establish its validity was performed. We identified 89 subjects. The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.69). K-means cluster analysis demonstrated that 3 unique statistical cohorts (elbow criterion) could be identified with CLUSPLOT analysis, confirming that 100% of variances were accounted for. Correlation coefficients between the individual items in the SSQ and the MDADI demonstrated weak to moderate negative correlation, except for SSQ17 (quality of life question). Pilot analysis demonstrates that the MDADI and SSQ are complementary. Three unique clusters of patients can be defined, suggesting that a unique dysphagia signature for HNCTD may be definable. Longitudinal studies relying on only a single PRO, such as MDADI, may be inadequate for classifying HNCTD. Copyright © 2017 Elsevier Inc. All rights reserved.

Field Air Sampling and Simultaneous Chemical and Sensory Analysis of Livestock Odorants with Sorbent Tube GC-MS/Olfactometry

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

Zhang Shicheng; Department of Environmental Science and Engineering, Fudan University, Shanghai 200433; Cai Lingshuang

2009-05-23

Characterization and quantification of livestock odorants is one of the most challenging analytical tasks because odor-causing gases are very reactive, polar and often present at very low concentrations in a complex matrix of less important or irrelevant gases. The objective of this research was to develop a novel analytical method for characterization of the livestock odorants including their odor character, odor intensity, and hedonic tone and to apply this method for quantitative analysis of the key odorants responsible for livestock odor. Sorbent tubes packed with Tenax TA were used for field sampling. The automated one-step thermal desorption module coupled withmore » multidimensional gas chromatography-mass spectrometry/olfactometry system was used for simultaneous chemical and odor analysis. Fifteen odorous VOCs and semi-VOCs identified from different livestock species operations were quantified. Method detection limits ranges from 40 pg for skatole to 3590 pg for acetic acid. In addition, odor character, odor intensity and hedonic tone associated with each of the target odorants are also analyzed simultaneously. We found that the mass of each VOCs in the sample correlates well with the log stimulus intensity. All of the correlation coefficients (R{sup 2}) are greater than 0.74, and the top 10 correlation coefficients were greater than 0.90.« less

Modeling State-Space Aeroelastic Systems Using a Simple Matrix Polynomial Approach for the Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

Pototzky, Anthony S.

2008-01-01

A simple matrix polynomial approach is introduced for approximating unsteady aerodynamics in the s-plane and ultimately, after combining matrix polynomial coefficients with matrices defining the structure, a matrix polynomial of the flutter equations of motion (EOM) is formed. A technique of recasting the matrix-polynomial form of the flutter EOM into a first order form is also presented that can be used to determine the eigenvalues near the origin and everywhere on the complex plane. An aeroservoelastic (ASE) EOM have been generalized to include the gust terms on the right-hand side. The reasons for developing the new matrix polynomial approach are also presented, which are the following: first, the "workhorse" methods such as the NASTRAN flutter analysis lack the capability to consistently find roots near the origin, along the real axis or accurately find roots farther away from the imaginary axis of the complex plane; and, second, the existing s-plane methods, such as the Roger s s-plane approximation method as implemented in ISAC, do not always give suitable fits of some tabular data of the unsteady aerodynamics. A method available in MATLAB is introduced that will accurately fit generalized aerodynamic force (GAF) coefficients in a tabular data form into the coefficients of a matrix polynomial form. The root-locus results from the NASTRAN pknl flutter analysis, the ISAC-Roger's s-plane method and the present matrix polynomial method are presented and compared for accuracy and for the number and locations of roots.

Correlation between centrality metrics and their application to the opinion model

NASA Astrophysics Data System (ADS)

Li, Cong; Li, Qian; Van Mieghem, Piet; Stanley, H. Eugene; Wang, Huijuan

2015-03-01

In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated low-complexity metric, we first study the correlation between centrality metrics in terms of their Pearson correlation coefficient and their similarity in ranking of nodes. In addition to considering the widely used centrality metrics, we introduce a new centrality measure, the degree mass. The mth-order degree mass of a node is the sum of the weighted degree of the node and its neighbors no further than m hops away. We find that the betweenness, the closeness, and the components of the principal eigenvector of the adjacency matrix are strongly correlated with the degree, the 1st-order degree mass and the 2nd-order degree mass, respectively, in both network models and real-world networks. We then theoretically prove that the Pearson correlation coefficient between the principal eigenvector and the 2nd-order degree mass is larger than that between the principal eigenvector and a lower order degree mass. Finally, we investigate the effect of the inflexible contrarians selected based on different centrality metrics in helping one opinion to compete with another in the inflexible contrarian opinion (ICO) model. Interestingly, we find that selecting the inflexible contrarians based on the leverage, the betweenness, or the degree is more effective in opinion-competition than using other centrality metrics in all types of networks. This observation is supported by our previous observations, i.e., that there is a strong linear correlation between the degree and the betweenness, as well as a high centrality similarity between the leverage and the degree.

Correlation filtering in financial time series (Invited Paper)

NASA Astrophysics Data System (ADS)

Aste, T.; Di Matteo, Tiziana; Tumminello, M.; Mantegna, R. N.

2005-05-01

We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al.,1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).

Complex network approach to fractional time series

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

Manshour, Pouya

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacencymore » matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.« less

Global Interactions Analysis of Epileptic ECoG Data

NASA Astrophysics Data System (ADS)

Ortega, Guillermo J.; Sola, Rafael G.; Pastor, Jesús

2007-05-01

Localization of the epileptogenic zone is an important issue in epileptology, even though there is not a unique definition of the epileptic focus. The objective of the present study is to test ultrametric analysis to uncover cortical interactions in human epileptic data. Correlation analysis has been carried out over intraoperative Electro-Corticography (ECoG) data in 2 patients suffering from temporal lobe epilepsy (TLE). Recordings were obtained using a grid of 20 electrodes (5×4) covering the lateral temporal lobe and a strip of either 4 or 8 electrodes at the mesial temporal lobe. Ultrametric analysis was performed in the averaged final correlation matrices. By using the matrix of linear correlation coefficients and the appropriate metric distance between pairs of electrodes time series, we were able to construct Minimum Spanning Trees (MST). The topological connectivity displayed by these trees gives useful and valuable information regarding physiological and pathological information in the temporal lobe of epileptic patients.

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.

Validity of three clinical performance assessments of internal medicine clerks.

PubMed

Hull, A L; Hodder, S; Berger, B; Ginsberg, D; Lindheim, N; Quan, J; Kleinhenz, M E

1995-06-01

To analyze the construct validity of three methods to assess the clinical performances of internal medicine clerks. A multitrait-multimethod (MTMM) study was conducted at the Case Western Reserve University School of Medicine to determine the convergent and divergent validity of a clinical evaluation form (CEF) completed by faculty and residents, an objective structured clinical examination (OSCE), and the medicine subject test of the National Board of Medical Examiners. Three traits were involved in the analysis: clinical skills, knowledge, and personal characteristics. A correlation matrix was computed for 410 third-year students who completed the clerkship between August 1988 and July 1991. There was a significant (p < .01) convergence of the four correlations that assessed the same traits by using different methods. However, the four convergent correlations were of moderate magnitude (ranging from .29 to .47). Divergent validity was assessed by comparing the magnitudes of the convergence correlations with the magnitudes of correlations among unrelated assessments (i.e., different traits by different methods). Seven of nine possible coefficients were smaller than the convergent coefficients, suggesting evidence of divergent validity. A significant CEF method effect was identified. There was convergent validity and some evidence of divergent validity with a significant method effect. The findings were similar for correlations corrected for attenuation. Four conclusions were reached: (1) the reliability of the OSCE must be improved, (2) the CEF ratings must be redesigned to further discriminate among the specific traits assessed, (3) additional methods to assess personal characteristics must be instituted, and (4) several assessment methods should be used to evaluate individual student performances.

Blind source separation of ex-vivo aorta tissue multispectral images

PubMed Central

Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

2015-01-01

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366

Elasto-plastic analysis of interface layers for fiber reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Doghri, I.; Leckie, F. A.

1991-01-01

The mismatch in coefficients of thermal expansion (CTE) of fiber and matrix in metal matrix composites reinforced with ceramic fibers induces high thermal stresses in the matrix. Elasto-plastic analyses - with different degrees of simplification and modelization - show that an interface layer with a sufficiently high CTE can reduce the tensile hoop stress in the matrix substantially.

Nonlinear Finite Element Analysis of Metals and Metal Matrix Composites: A Local-Global Investigation

DTIC Science & Technology

1992-10-01

and SiC/Al [47] possess good chemical bonding and experience mechanical clamping due to the differences in thermal expansion coefficients between...Coefficient of Thermal 2.70 x 10.6 *F-1 4.09 x 10-6 *C-1 Expansion (ca) Poisson’s Ratio (v) 0.25 0.25 Fiber Diameter (d) 0.0056 in 0.014224 cm...Properties of the matrix (as fabricated) Coefficient of Thermal 5.4 x 10-6 "F1 9.72 x 10-6 "C-1 Expansion (a) Poisson’s Ratio (v) 0.351 0.351 Longitudinal

Fate and mobility of pharmaceuticals in solid matrices.

PubMed

Drillia, Panagiota; Stamatelatou, Katerina; Lyberatos, Gerasimos

2005-08-01

The sorption and mobility of six pharmaceuticals were investigated in two soil types with different organic carbon and clay content, and in bacterial biomass (aerobic and anaerobic). The pharmaceuticals examined were carbamazepine, propranolol, diclofenac sodium, clofibric acid, sulfamethoxazole and ofloxacin. The sorption experiments were performed according to the OECD test Guideline 106. The distribution coefficients determined by this batch equilibrium method varied with the pharmaceutical tested and the solid matrix type. Ofloxacin was particularly strongly adsorbed (except of the case of using anaerobic biomass for the solid matrix) while clofibric acid was found to be weakly adsorbed. The fate of pharmaceuticals in soil was also assessed using lysimeters. Important parameters that were studied were: the pharmaceutical loading rate and the hydraulic loading rate for adsorption and the rate and duration of a "rain" event for desorption. Major differences in the mobility of the six pharmaceuticals were observed and correlated with the adsorption/desorption properties of the compounds.

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

NASA Astrophysics Data System (ADS)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property helps to overcome a significant computational bottleneck of geostatistical models due to the poor scaling of the matrix inversion [4,5]. We present applications to real and simulated data sets, including the Walker lake data, and we investigate the SLI performance using various statistical cross validation measures. References [1] T. Hofmann, B. Schlkopf, A.J. Smola, Annals of Statistics, 36, 1171-1220 (2008). [2] D. T. Hristopulos, SIAM Journal on Scientific Computing, 24(6): 2125-2162 (2003). [3] D. T. Hristopulos and S. N. Elogne, IEEE Transactions on Signal Processing, 57(9): 3475-3487 (2009) [4] G. Jona Lasinio, G. Mastrantonio, and A. Pollice, Statistical Methods and Applications, 22(1):97-112 (2013) [5] Sun, Y., B. Li, and M. G. Genton (2012). Geostatistics for large datasets. In: Advances and Challenges in Space-time Modelling of Natural Events, Lecture Notes in Statistics, pp. 55-77. Springer, Berlin-Heidelberg.

Least-Squares Approximation of an Improper Correlation Matrix by a Proper One.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

1989-01-01

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

Procrustes Matching by Congruence Coefficients

ERIC Educational Resources Information Center

Korth, Bruce; Tucker, L. R.

1976-01-01

Matching by Procrustes methods involves the transformation of one matrix to match with another. A special least squares criterion, the congruence coefficient, has advantages as a criterion for some factor analytic interpretations. A Procrustes method maximizing the congruence coefficient is given. (Author/JKS)

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

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

Coupling coefficients for tensor product representations of quantum SU(2)

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

Groenevelt, Wolter, E-mail: w.g.m.groenevelt@tudelft.nl

2014-10-15

We study tensor products of infinite dimensional irreducible {sup *}-representations (not corepresentations) of the SU(2) quantum group. We obtain (generalized) eigenvectors of certain self-adjoint elements using spectral analysis of Jacobi operators associated to well-known q-hypergeometric orthogonal polynomials. We also compute coupling coefficients between different eigenvectors corresponding to the same eigenvalue. Since the continuous spectrum has multiplicity two, the corresponding coupling coefficients can be considered as 2 × 2-matrix-valued orthogonal functions. We compute explicitly the matrix elements of these functions. The coupling coefficients can be considered as q-analogs of Bessel functions. As a results we obtain several q-integral identities involving q-hypergeometricmore » orthogonal polynomials and q-Bessel-type functions.« less

Diffusion coefficients of rare earth elements in fcc Fe: A first-principles study

NASA Astrophysics Data System (ADS)

Wang, Haiyan; Gao, Xueyun; Ren, Huiping; Chen, Shuming; Yao, Zhaofeng

2018-01-01

The diffusion data and corresponding detailed insights are particularly important for the understanding of the related kinetic processes in Fe based alloys, e.g. solute strengthening, phase transition, solution treatment etc. We present a density function theory study of the diffusivity of self and solutes (La, Ce, Y and Nb) in fcc Fe. The five-frequency model was employed to calculate the microscopic parameters in the correlation factors of the solute diffusion. The interactions of the solutes with the first nearest-neighbor vacancy (1nn) are all attractive, and can be well understood on the basis of the combination of the strain-relief effects and the electronic effects. It is found that among the investigated species, Ce is the fastest diffusing solute in fcc Fe matrix followed by Nb, and the diffusion coefficients of these two solutes are about an order of magnitude higher than that of Fe self-diffusion. And the results show that the diffusion coefficient of La is slightly higher than that of Y, and both species are comparable to that of Fe self-diffusion.

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

PubMed

Xiao, Shijie; Xu, Dong; Wu, Jianxin

2015-10-01

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data. Specifically, by introducing a specially designed regularizer to the low-rank representation method, we penalize the corresponding reconstruction coefficients related to the situations where a face is reconstructed by using face images from other subjects or by using itself. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. Moreover, we also develop a new distance metric learning method called ambiguously supervised structural metric learning by using weakly supervised information to seek a discriminative distance metric. Hence, another discriminative affinity matrix can be obtained using the similarity matrix (i.e., the kernel matrix) based on the Mahalanobis distances of the data. Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Comprehensive experiments demonstrate the effectiveness of our approach.

Divergent dispersion behavior of ssDNA fragments during microchip electrophoresis in pDMA and LPA entangled polymer networks

PubMed Central

Fredlake, Christopher P.; Hert, Daniel G.; Niedringhaus, Thomas P.; Lin, Jennifer S.; Barron, Annelise E.

2015-01-01

Resolution of DNA fragments separated by electrophoresis in polymer solutions (“matrices”) is determined by both the spacing between peaks and the width of the peaks. Prior research on the development of high-performance separation matrices has been focused primarily on optimizing DNA mobility and matrix selectivity, and gave less attention to peak broadening. Quantitative data are rare for peak broadening in systems in which high electric field strengths are used (> 150 V/cm), which is surprising since capillary and microchip-based systems commonly run at these field strengths. Here, we report results for a study of band broadening behavior for ssDNA fragments on a glass microfluidic chip, for electric field strengths up to 320 V/cm. We compare dispersion coefficients obtained in a poly(N,N-dimethylacrylamide) (pDMA) separation matrix that was developed for chip-based DNA sequencing with a commercially available linear polyacrylamide (LPA) matrix commonly used in capillaries. Much larger DNA dispersion coefficients were measured in the LPA matrix as compared to the pDMA matrix, and the dependences of dispersion coefficient on DNA size and electric field strength were found to differ quite starkly in the two matrices. These observations lead us to propose that DNA migration mechanisms differ substantially in our custom pDMA matrix compared to the commercially available LPA matrix. We discuss the implications of these results in terms of developing optimal matrices for specific separation (microchip or capillary) platforms. PMID:22648809

Carbonate fuel cell matrix

DOEpatents

Farooque, Mohammad; Yuh, Chao-Yi

1996-01-01

A carbonate fuel cell matrix comprising support particles and crack attenuator particles which are made platelet in shape to increase the resistance of the matrix to through cracking. Also disclosed is a matrix having porous crack attenuator particles and a matrix whose crack attenuator particles have a thermal coefficient of expansion which is significantly different from that of the support particles, and a method of making platelet-shaped crack attenuator particles.

Estimating terpene and terpenoid emissions from conifer oleoresin composition

NASA Astrophysics Data System (ADS)

Flores, Rosa M.; Doskey, Paul V.

2015-07-01

The following algorithm, which is based on the thermodynamics of nonelectrolyte partitioning, was developed to predict emission rates of terpenes and terpenoids from specific storage sites in conifers: Ei =xoriγoripi∘ where Ei is the emission rate (μg C gdw-1 h-1) and pi∘ is the vapor pressure (mm Hg) of the pure liquid terpene or terpenoid, respectively, and xori and γori are the mole fraction and activity coefficient (on a Raoult's law convention), respectively, of the terpene and terpenoid in the oleoresin. Activity coefficients are calculated with Hansen solubility parameters that account for dispersive, polar, and H-bonding interactions of the solutes with the oleoresin matrix. Estimates of pi∘ at 25 °C and molar enthalpies of vaporization are made with the SIMPOL.1 method and are used to estimate pi∘ at environmentally relevant temperatures. Estimated mixing ratios of terpenes and terpenols were comparatively higher above resin-acid- and monoterpene-rich oleoresins, respectively. The results indicated a greater affinity of terpenes and terpenols for the non-functionalized and carboxylic acid containing matrix through dispersive and H-bonding interactions, which are expressed in the emission algorithm by the activity coefficient. The correlation between measured emission rates of terpenes and terpenoids for Pinus strobus and emission rates predicted with the algorithm were very good (R = 0.95). Standard errors for the range and average of monoterpene emission rates were ±6 - ±86% and ±54%, respectively, and were similar in magnitude to reported standard deviations of monoterpene composition of foliar oils (±38 - ±51% and ±67%, respectively).

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

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

Quantitative T2-Mapping and T2⁎-Mapping Evaluation of Changes in Cartilage Matrix after Acute Anterior Cruciate Ligament Rupture and the Correlation between the Results of Both Methods.

PubMed

Tao, Hongyue; Qiao, Yang; Hu, Yiwen; Xie, Yuxue; Lu, Rong; Yan, Xu; Chen, Shuang

2018-01-01

To quantitatively assess changes in cartilage matrix after acute anterior cruciate ligament (ACL) rupture using T2- and T2 ⁎ -mapping and analyze the correlation between the results of both methods. Twenty-three patients and 23 healthy controls were enrolled and underwent quantitative MRI examination. The knee cartilage was segmented into six compartments, including lateral femur (LF), lateral tibia (LT), medial femur (MF), medial tibia (MT), trochlea (Tr), and patella (Pa). T2 and T2 ⁎ values were measured in full-thickness as well as superficial and deep layers of each cartilage compartment. Differences of T2 and T2 ⁎ values between patients and controls were compared using unpaired Student's t -test, and the correlation between their reciprocals was analyzed using Pearson's correlation coefficient. ACL-ruptured patients showed higher T2 and T2 ⁎ values in full-thickness and superficial layers of medial and lateral tibiofemoral joint. Meanwhile, patients exhibited higher T2 ⁎ values in deep layers of lateral tibiofemoral joint. The elevated percentages of T2 and T2 ⁎ value in superficial LT were most significant (20.738%, 17.525%). The reciprocal of T2 ⁎ value was correlated with that of T2 value ( r = 0.886, P < 0.001). The early degeneration could occur in various knee cartilage compartments after acute ACL rupture, especially in the superficial layer of LT. T2 ⁎ -mapping might be more sensitive in detecting deep layer of cartilage than T2-mapping.

Energy: It is life

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

Arques, P.

1998-07-01

The relationships that seem to exist between energy and man are presented in this paper. Habitually, social coefficients are connected to the gross domestic product; some parameters with correlations are: birth rate, infant mortality rate, death rate, literacy, etc. Along with energy these define the optimal energy consumption per capita; the author presents the correlation between these parameters and energy consumed per capita. There exists a high correlation between energy consumption per capita and gross domestic product per capita. The set of parameters considered are correlated with similar values relative to these two parameters. Using data collected on a groupmore » of the different countries of the world, a table of 165 countries and 22 variables has been drawn up. From the [Country x variable] matrix, a correlation table is calculated and a factorial analysis is applied to this matrix. The first factorial plan comprises 57% of the information contained in this table. Results from this first factorial plan are presented. These parameters are analyzed: influence of a country's latitude on its inhabitants' consumption; relationship between consumed energy and gross domestic product; women's fertility rate; birth rate per 1000 population; sex ratio; life expectancy at birth; rate of literacy; death rate; population growth rate. Finally, it is difficult to define precise criteria for: an optimal distribution of population according to age, but with a power consumed of above 300 W per capita, the population becomes younger; the birth rate per 1000 population; the total fertility rate per woman; the population growth rate. The authors determine that optimal energy is approximately between 200 W and 677 W inclusive.« less

Super-resolution study of polymer mobility fluctuations near c*.

PubMed

King, John T; Yu, Changqian; Wilson, William L; Granick, Steve

2014-09-23

Nanoscale dynamic heterogeneities in synthetic polymer solutions are detected using super-resolution optical microscopy. To this end, we map concentration fluctuations in polystyrene-toluene solutions with spatial resolution below the diffraction limit, focusing on critical fluctuations near the polymer overlap concentration, c*. Two-photon super-resolution microscopy was adapted to be applicable in an organic solvent, and a home-built STED-FCS system with stimulated emission depletion (STED) was used to perform fluorescence correlation spectroscopy (FCS). The polystyrene serving as the tracer probe (670 kg mol(-1), radius of gyration RG ≈ 35 nm, end-labeled with a bodipy derivative chromophore) was dissolved in toluene at room temperature (good solvent) and mixed with matrix polystyrene (3,840 kg mol(-1), RG ≈ 97 nm, Mw/Mn = 1.04) whose concentration was varied from dilute to more than 10c*. Whereas for dilute solutions the intensity-intensity correlation function follows a single diffusion process, it splits starting at c* to imply an additional relaxation process provided that the experimental focal area does not greatly exceed the polymer blob size. We identify the slower mode as self-diffusion and the increasingly rapid mode as correlated segment fluctuations that reflect the cooperative diffusion coefficient, Dcoop. These real-space measurements find quantitative agreement between correlation lengths inferred from dynamic measurements and those from determining the limit below which diffusion coefficients are independent of spot size. This study is considered to illustrate the potential of importing into polymer science the techniques of super-resolution imaging.

State-Space System Realization with Input- and Output-Data Correlation

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1997-01-01

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

Development and testing of the Test of Functional Health Literacy in Dentistry (TOFHLiD).

PubMed

Gong, Debra A; Lee, Jessica Y; Rozier, R Gary; Pahel, Bhavna T; Richman, Julia A; Vann, William F

2007-01-01

This study aims to evaluate the reliability and validity of the Test of Functional Health Literacy in Dentistry (TOFHLiD), a new instrument to measure functional oral health literacy. TOFHLiD uses text passages and prompts related to fluoride use and access to care to assess reading comprehension and numerical ability. Parents of pediatric dental patients (n = 102) were administered TOFHLiD, a medical literacy comprehension test (TOFHLA), and two word recognition tests [Rapid Estimate of Adult Literacy in Dentistry (REALD), Rapid Estimate of Adult Literacy in Medicine (REALM)]. This design provided assessments of dental and medical health literacy by all subjects, both measured with two different methods (reading/numeracy ability and word recognition). Construct validity of TOFHLiD was assessed by entering the correlation coefficients for all pairwise comparisons of literacy instruments into a multitrait-multimethod matrix. Internal reliability of TOFHLiD was assessed with Cronbach's alpha. Criterion-related predictive validity was tested by associations between the TOFHLiD scores and the three measures of oral health in multivariate regression analyses. The correlation coefficient for TOFHLiD and REALD-99 scores (monotrait-heteromethod) was high (r = 0.82, P < 0.05). Coefficients between TOFHLiD and TOFHLA (heterotrait-monomethod: r = 0.52) and REALM (heterotrait-heteromethod: r = 0.53) were smaller than coefficients for convergent validity Cronbach's alpha for TOFHLiD was 0.63. TOFHLiD was positively correlated with OHIP-14 (P < 0.05), but not with parent or child oral health. TOFHLA was not related to dental outcomes. TOFHLiD demonstrates good convergent validity but only moderate ability to discriminate between dental and medical health literacy. Its predictive validity is only partially established, and internal consistency just meets the threshold for acceptability. Results provide solid support for more research, but not widespread use in clinical or public health practice.

The Split Coefficient Matrix method for hyperbolic systems of gasdynamic equations

NASA Technical Reports Server (NTRS)

Chakravarthy, S. R.; Anderson, D. A.; Salas, M. D.

1980-01-01

The Split Coefficient Matrix (SCM) finite difference method for solving hyperbolic systems of equations is presented. This new method is based on the mathematical theory of characteristics. The development of the method from characteristic theory is presented. Boundary point calculation procedures consistent with the SCM method used at interior points are explained. The split coefficient matrices that define the method for steady supersonic and unsteady inviscid flows are given for several examples. The SCM method is used to compute several flow fields to demonstrate its accuracy and versatility. The similarities and differences between the SCM method and the lambda-scheme are discussed.

Groundwater quality characterization around Jawaharnagar open dumpsite, Telangana State

NASA Astrophysics Data System (ADS)

Unnisa, Syeda Azeem; Zainab Bi, Shaik

2017-11-01

In the present work groundwater samples were collected from ten different data points in and around Jawaharnagar municipal dumpsite, Telangana State Hyderabad city from May 2015 to May 2016 on monthly basis for groundwater quality characterization. Pearson's correlation coefficient ( r) value was determined using correlation matrix to identify the highly correlated and interrelated water quality standards issued by Bureau of Indian Standard (IS-10500:2012). It is found that most of the groundwater samples are above acceptable limits and are not potable. The chemical analysis results revealed that pH range from 7.2 to 7.8, TA 222 to 427 mg/l, TDS 512 to 854 mg/l, TH 420 to 584 mg/l, Calcium 115 to 140 mg/l, Magnesium 55 to 115 mg/l, Chlorides 202 to 290 mg/l, Sulphates 170 to 250 mg/l, Nitrates 6.5 to 11.3 mg/l, and Fluoride 0.9 to 1.7 mg/l. All samples showed higher range of physicochemical parameters except nitrate content which was lower than permissible limit. Highly positive correlation was observed between pH-TH ( r = 0.5063), TA-Cl- ( r = 0.5896), TDS-SO4 - ( r = 0.5125), Mg2+-NO3 - ( r = 0.5543) and Cl--F- ( r = 0.7786). The groundwater samples in and around Jawaharnagar municipal dumpsite implies that groundwater samples were contaminated by municipal leachate migration from open dumpsite. The results revealed that the systematic calculations of correlation coefficient between water parameters and regression analysis provide qualitative and rapid monitoring of groundwater quality.

Carbonate fuel cell matrix

DOEpatents

Farooque, M.; Yuh, C.Y.

1996-12-03

A carbonate fuel cell matrix is described comprising support particles and crack attenuator particles which are made platelet in shape to increase the resistance of the matrix to through cracking. Also disclosed is a matrix having porous crack attenuator particles and a matrix whose crack attenuator particles have a thermal coefficient of expansion which is significantly different from that of the support particles, and a method of making platelet-shaped crack attenuator particles. 8 figs.

An analytical technique for approximating unsteady aerodynamics in the time domain

NASA Technical Reports Server (NTRS)

Dunn, H. J.

1980-01-01

An analytical technique is presented for approximating unsteady aerodynamic forces in the time domain. The order of elements of a matrix Pade approximation was postulated, and the resulting polynomial coefficients were determined through a combination of least squares estimates for the numerator coefficients and a constrained gradient search for the denominator coefficients which insures stable approximating functions. The number of differential equations required to represent the aerodynamic forces to a given accuracy tends to be smaller than that employed in certain existing techniques where the denominator coefficients are chosen a priori. Results are shown for an aeroelastic, cantilevered, semispan wing which indicate a good fit to the aerodynamic forces for oscillatory motion can be achieved with a matrix Pade approximation having fourth order numerator and second order denominator polynomials.

A new correlation coefficient for bivariate time-series data

NASA Astrophysics Data System (ADS)

Erdem, Orhan; Ceyhan, Elvan; Varli, Yusuf

2014-11-01

The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

The tracer diffusion coefficient of soft nanoparticles in a linear polymer matrix

DOE PAGES

Imel, Adam E.; Rostom, Sahar; Holley, Wade; ...

2017-03-09

The diffusion properties of nanoparticles in polymer nanocomposites are largely unknown and are often difficult to determine experimentally. To address this shortcoming, we have developed a novel method to determine the tracer diffusion coefficient of soft polystyrene nanoparticles in a linear polystyrene matrix. Monitoring the interdiffusion of soft nanoparticles into a linear polystyrene matrix provides the mutual diffusion coefficient of this system, from which the tracer diffusion coefficient of the soft nanoparticle can be determined using the slow mode theory. Utilizing this protocol, the role of nanoparticle molecular weight and rigidity on its tracer diffusion coefficient is provided. These resultsmore » demonstrate that the diffusive behavior of these soft nanoparticles differ from that of star polymers, which is surprising since our recent studies suggest that the nanoparticle interacts with a linear polymer similarly to that of a star polymer. It appears that these deformable nanoparticles mostly closely mimic the diffusive behavior of fractal macromolecular architectures or microgels, where the transport of the nanoparticle relies on the cooperative motion of neighboring linear chains. Finally, the less cross-linked, and thus more deformable, nanoparticles diffuse faster than the more highly crosslinked nanoparticles, presumably because the increased deformability allows the nanoparticle to distort and fit into available space.« less

A computer program to generate equations of motion matrices, L217 (EOM). Volume 1: Engineering and usage

NASA Technical Reports Server (NTRS)

Kroll, R. I.; Clemmons, R. E.

1979-01-01

The equations of motion program L217 formulates the matrix coefficients for a set of second order linear differential equations that describe the motion of an airplane relative to its level equilibrium flight condition. Aerodynamic data from FLEXSTAB or Doublet Lattice (L216) programs can be used to derive the equations for quasi-steady or full unsteady aerodynamics. The data manipulation and the matrix coefficient formulation are described.

Dispersion controlled by permeable surfaces: surface properties and scaling

DOE PAGES

Ling, Bowen; Tartakovsky, Alexandre M.; Battiato, Ilenia

2016-08-25

Permeable and porous surfaces are common in natural and engineered systems. Flow and transport above such surfaces are significantly affected by the surface properties, e.g. matrix porosity and permeability. However, the relationship between such properties and macroscopic solute transport is largely unknown. In this work, we focus on mass transport in a two-dimensional channel with permeable porous walls under fully developed laminar flow conditions. By means of perturbation theory and asymptotic analysis, we derive the set of upscaled equations describing mass transport in the coupled channel–porous-matrix system and an analytical expression relating the dispersion coefficient with the properties of themore » surface, namely porosity and permeability. Our analysis shows that their impact on the dispersion coefficient strongly depends on the magnitude of the Péclet number, i.e. on the interplay between diffusive and advective mass transport. Additionally, we demonstrate different scaling behaviours of the dispersion coefficient for thin or thick porous matrices. Our analysis shows the possibility of controlling the dispersion coefficient, i.e. transverse mixing, by either active (i.e. changing the operating conditions) or passive mechanisms (i.e. controlling matrix effective properties) for a given Péclet number. By elucidating the impact of matrix porosity and permeability on solute transport, our upscaled model lays the foundation for the improved understanding, control and design of microporous coatings with targeted macroscopic transport features.« less

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Comparing PAH availability from manufactured gas plant soils and sediments with chemical and biological tests. 1. PAH release during water desorption and supercritical carbon dioxide extraction.

PubMed

Hawthorne, Steven B; Poppendieck, Dustin G; Grabanski, Carol B; Loehr, Raymond C

2002-11-15

Soil and sediment samples from oil gas (OG) and coal gas (CG) manufactured gas plant (MGP) sites were selected to represent a range of PAH concentrations (150-40,000 mg/kg) and sample matrix compositions. Samples varied from vegetated soils to lampblack soot and had carbon contents from 3 to 87 wt %. SFE desorption (120 min) and water/XAD2 desorption (120 days) curves were determined and fit with a simple two-site model to determine the rapid-released fraction (F) for PAHs ranging from naphthalene to benzo[ghi]perylene. F values varied greatly among the samples, from ca. 10% to >90% for the two- and three-ring PAHs and from <1% to ca. 50% for the five- and six-ring PAHs. Release rates did not correlate with sample matrix characteristics including PAH concentrations, elemental composition (C, H, N, S), or "hard" and "softs" organic carbon, indicating that PAH release cannot easily be estimated on the basis of sample matrix composition. Fvalues for CG site samples obtained with SFE and water desorption agreed well (linear correlation coefficient, r2 = 0.87, slope = 0.93), but SFE yielded higher F values for the OG samples. These behaviors were attributed to the stronger ability of carbon dioxide than water to desorb PAHs from the highly aromatic (hard) carbon of the OG matrixes, while carbon dioxide and water showed similar abilities to desorb PAHs from the more polar (soft) carbon of the CG samples. The combined SFE and water desorption approaches should improve the understanding of PAH sequestration and release from contaminated soils and sediments and provide the basis for subsequent studies using the same samples to compare PAH release with PAH availability to earthworms.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Trends in Effective Diffusion Coefficients for Ion-exchange Strengthening of Soda Lime Silicate Glasses

NASA Astrophysics Data System (ADS)

Karlsson, Stefan; Wondraczek, Lothar; Ali, Sharafat; Jonson, Bo

2017-04-01

Monovalent cations enable efficient ion exchange processes due to their high mobility in silicate glasses. Numerous properties can be modified in this way, e.g., mechanical, optical, electrical or chemical performance. In particular, alkali cation exchange has received significant attention, primarily with respect to introducing compressive stress into the surface region of a glass, which increases mechanical durability. However, most of the present applications rely on specifically tailored matrix compositions in which the cation mobility is enhanced. This largely excludes the major area of soda lime silicates (SLS) such as are commodity in almost all large-scale applications of glasses. Basic understanding of the relations between structural parameters and the effective diffusion coefficients may help to improve ion-exchanged SLS glass products, on the one hand in terms of obtainable strength and on the other in terms of cost. In the present paper, we discuss the trends in the effective diffusion coefficients when exchanging Na+ for various monovalent cations (K+, Cu+, Ag+, Rb+ and Cs+) by drawing relations to physico-chemical properties. Correlations of effective diffusion coefficients were found for the bond dissociation energy and the electronic cation polarizability, indicating that localization and rupture of bonds are of importance for the ion exchange rate.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Minimum number of measurements for evaluating Bertholletia excelsa.

PubMed

Baldoni, A B; Tonini, H; Tardin, F D; Botelho, S C C; Teodoro, P E

2017-09-27

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r, which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.

Does pop music exist? Hierarchical structure in phonographic markets

NASA Astrophysics Data System (ADS)

Buda, Andrzej

2012-11-01

I find a topological arrangement of assets traded in phonographic markets which has associated a meaningful economic taxonomy. I continue using the Minimal Spanning Tree and the correlations between assets, but now outside the stock markets. This is the first attempt to use these methods on phonographic markets where we have artists instead of stocks. The value of an artist is defined by record sales. The graph is obtained starting from the matrix of correlation coefficients computed between the world’s most popular 30 artists by considering the synchronous time evolution of the difference of the logarithm of weekly record sales. This method provides the hierarchical structure of the phonographic market and information on which music genre is meaningful according to customers. Statistical properties (including the Hurst exponent) of weekly record sales in the phonographic market are also discussed.

Evaluation of Immunoassay for the Determination of Pesticides at a Large-Scale Groundwater Contamination Site

USGS Publications Warehouse

Dombrowski, T.R.; Thurman, E.M.; Mohrman, G.B.

1996-01-01

Pesticide concentrations in ground water at Rocky Mountain Arsenal (RMA) near Denver, Colorado, were determined using solid-phase extraction (SPE) gas chromatography/mass spectrometry (GC/MS) procedures and enzyme-linked immunosorbent assay (ELISA) for cyclodiene insecticides and triazine herbicides. Matrix interferences resulted in inconclusive results for some GC/MS analyses due to baseline disturbances and co-elution, but ELISA analyses consistently gave definitive results in a minimum amount of time. ELISA was used initially as a screening method, and pesticide concentrations and plume extents identified by ELISA were confirmed by SPE-GC/MS. A high degree of correlation was seen between results from GC/MS and ELISA methods for the triazine herbicides (correlation coefficient (R2) = 0.99). All areas with high pesticide concentrations were found to be within the boundaries of RMA.

Plunges in the Bombay stock exchange: Characteristics and indicators

NASA Astrophysics Data System (ADS)

Banerjee, Kinjal; Sharma, Chandradew; Bittu, N.

2017-09-01

We study the various sectors of the Bombay Stock Exchange (BSE) for a period of eight years from January 2006-March 2014. Using the data of the daily returns of a period of eight years we investigate the financial cross-correlation co-efficients among the sectors of BSE and Price by Earning (PE) ratio of BSE Sensex. We show that the behavior of these quantities during normal periods and during crisis is very different. We show that the PE ratio shows a particular distinctive trend in the approach to a crash of the financial market and can therefore be used as an indicator of an impending catastrophe. We propose that a model of analysis of crashes in a financial market can be built using two parameters: (i) the PE ratio and (ii) the largest eigenvalue of the cross-correlation matrix.

A 3D reconstruction algorithm for magneto-acoustic tomography with magnetic induction based on ultrasound transducer characteristics.

PubMed

Ma, Ren; Zhou, Xiaoqing; Zhang, Shunqi; Yin, Tao; Liu, Zhipeng

2016-12-21

In this study we present a three-dimensional (3D) reconstruction algorithm for magneto-acoustic tomography with magnetic induction (MAT-MI) based on the characteristics of the ultrasound transducer. The algorithm is investigated to solve the blur problem of the MAT-MI acoustic source image, which is caused by the ultrasound transducer and the scanning geometry. First, we established a transducer model matrix using measured data from the real transducer. With reference to the S-L model used in the computed tomography algorithm, a 3D phantom model of electrical conductivity is set up. Both sphere scanning and cylinder scanning geometries are adopted in the computer simulation. Then, using finite element analysis, the distribution of the eddy current and the acoustic source as well as the acoustic pressure can be obtained with the transducer model matrix. Next, using singular value decomposition, the inverse transducer model matrix together with the reconstruction algorithm are worked out. The acoustic source and the conductivity images are reconstructed using the proposed algorithm. Comparisons between an ideal point transducer and the realistic transducer are made to evaluate the algorithms. Finally, an experiment is performed using a graphite phantom. We found that images of the acoustic source reconstructed using the proposed algorithm are a better match than those using the previous one, the correlation coefficient of sphere scanning geometry is 98.49% and that of cylinder scanning geometry is 94.96%. Comparison between the ideal point transducer and the realistic transducer shows that the correlation coefficients are 90.2% in sphere scanning geometry and 86.35% in cylinder scanning geometry. The reconstruction of the graphite phantom experiment also shows a higher resolution using the proposed algorithm. We conclude that the proposed reconstruction algorithm, which considers the characteristics of the transducer, can obviously improve the resolution of the reconstructed image. This study can be applied to analyse the effect of the position of the transducer and the scanning geometry on imaging. It may provide a more precise method to reconstruct the conductivity distribution in MAT-MI.

Quantifying economic fluctuations by adapting methods of statistical physics

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki

2001-09-01

The first focus of this thesis is the investigation of cross-correlations between the price fluctuations of different stocks using the conceptual framework of random matrix theory (RMT), developed in physics to describe the statistical properties of energy-level spectra of complex nuclei. RMT makes predictions for the statistical properties of matrices that are universal, i.e., do not depend on the interactions between the elements comprising the system. In physical systems, deviations from the predictions of RMT provide clues regarding the mechanisms controlling the dynamics of a given system so this framework is of potential value if applied to economic systems. This thesis compares the statistics of cross-correlation matrix C-whose elements Cij are the correlation coefficients of price fluctuations of stock i and j-against the ``null hypothesis'' of a random matrix having the same symmetry properties. It is shown that comparison of the eigenvalue statistics of C with RMT results can be used to distinguish random and non-random parts of C. The non-random part of C which deviates from RMT results, provides information regarding genuine cross-correlations between stocks. The interpretations and potential practical utility of these deviations are also investigated. The second focus is the characterization of the dynamics of stock price fluctuations. The statistical properties of the changes G Δt in price over a time interval Δ t are quantified and the statistical relation between G Δt and the trading activity-measured by the number of transactions NΔ t in the interval Δt is investigated. The statistical properties of the volatility, i.e., the time dependent standard deviation of price fluctuations, is related to two microscopic quantities: NΔt and the variance W2Dt of the price changes for all transactions in the interval Δ t. In addition, the statistical relationship between G Δt and the number of shares QΔt traded in Δ t is investigated.

Mass-improvement of the vector current in three-flavor QCD

NASA Astrophysics Data System (ADS)

Fritzsch, P.

2018-06-01

We determine two improvement coefficients which are relevant to cancel mass-dependent cutoff effects in correlation functions with operator insertions of the non-singlet local QCD vector current. This determination is based on degenerate three-flavor QCD simulations of non-perturbatively O( a) improved Wilson fermions with tree-level improved gauge action. Employing a very robust strategy that has been pioneered in the quenched approximation leads to an accurate estimate of a counterterm cancelling dynamical quark cutoff effects linear in the trace of the quark mass matrix. To our knowledge this is the first time that such an effect has been determined systematically with large significance.

[Resolving characteristic of CDOM by excitation-emission matrix spectroscopy combined with parallel factor analysis in the seawater of outer Yangtze Estuary in Autumn in 2010].

PubMed

Yan, Li-Hong; Chen, Xue-Jun; Su, Rong-Guo; Han, Xiu-Rong; Zhang, Chuan-Song; Shi, Xiao-Yong

2013-01-01

The distribution and estuarine behavior of fluorescent components of chromophoric dissolved organic matter in the seawater of outer Yangtze Estuary were determined by fluorescence excitation emission matrix spectra combined with parallel factor analysis. Six individual fluorescent components were identified by PARAFAC models, including three terrestrial humic-like components C1 [330 nm/390(430) nm], C2 (390 nm/480 nm), C3 (360 nm/440 nm), marine biological production component C5 (300 nm/400 nm) and protein-like components C4 (290 nm/350 nm) and C6 (275 nm/300 nm). The results indicated that C1, C2, and C3 showed a conservative mixing behavior in the whole estuarine region, especially in high-salinity region. And the fluorescence intensity proportion of C1 and C3 decreased with increase of salinity and fluorescence intensity proportion of C2 kept constant with increase of salinity in the whole estuarine region. While C4 showed conservative mixing behavior in low-salinity region and non-conservative mixing behavior in high-salinity region, and fluorescence intensity proportion of C4 increased with increase of salinity. However, C5 and C6 showed a non-conservative mixing behavior and fluorescence intensity proportion increased with increase of salinity in high-salinity region. Significantly spatial difference was recorded for CDOM absorption coefficient in the coastal region and in the open water areas with the highest value in coastal region and the lowest value in the open water areas. The scope of absorption coefficient and absorption slope was higher in coastal region than that in the open water areas. Significantly positive correlations were found between CDOM absorption coefficient and the fluorescence intensities of C1, C2, C3, and C4, but no significant correlation was found between C5 and C6, suggesting that the river inputs contributed to the coastal areas, while CDOM in the open water areas was affected by terrestrial inputs and phytoplankton degradation.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Steady State Transportation Cooling in Porous Media Under Local, Non-Thermal Equilibrium Fluid Flow

NASA Technical Reports Server (NTRS)

Rodriquez, Alvaro Che

2002-01-01

An analytical solution to the steady-state fluid temperature for 1-D (one dimensional) transpiration cooling has been derived. Transpiration cooling has potential use in the aerospace industry for protection against high heating environments for re-entry vehicles. Literature for analytical treatments of transpiration cooling has been largely confined to the assumption of thermal equilibrium between the porous matrix and fluid. In the present analysis, the fundamental fluid and matrix equations are coupled through a volumetric heat transfer coefficient and investigated in non-thermal equilibrium. The effects of varying the thermal conductivity of the solid matrix and the heat transfer coefficient are investigated. The results are also compared to existing experimental data.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Theoretical models for supercritical fluid extraction.

PubMed

Huang, Zhen; Shi, Xiao-Han; Jiang, Wei-Juan

2012-08-10

For the proper design of supercritical fluid extraction processes, it is essential to have a sound knowledge of the mass transfer mechanism of the extraction process and the appropriate mathematical representation. In this paper, the advances and applications of kinetic models for describing supercritical fluid extraction from various solid matrices have been presented. The theoretical models overviewed here include the hot ball diffusion, broken and intact cell, shrinking core and some relatively simple models. Mathematical representations of these models have been in detail interpreted as well as their assumptions, parameter identifications and application examples. Extraction process of the analyte solute from the solid matrix by means of supercritical fluid includes the dissolution of the analyte from the solid, the analyte diffusion in the matrix and its transport to the bulk supercritical fluid. Mechanisms involved in a mass transfer model are discussed in terms of external mass transfer resistance, internal mass transfer resistance, solute-solid interactions and axial dispersion. The correlations of the external mass transfer coefficient and axial dispersion coefficient with certain dimensionless numbers are also discussed. Among these models, the broken and intact cell model seems to be the most relevant mathematical model as it is able to provide realistic description of the plant material structure for better understanding the mass-transfer kinetics and thus it has been widely employed for modeling supercritical fluid extraction of natural matters. Copyright © 2012 Elsevier B.V. All rights reserved.

Investigation on the Tribological Behavior and Wear Mechanism of Five Different Veneering Porcelains

PubMed Central

Min, Jie; Zhang, Qianqian; Qiu, Xiaoli; Zhu, Minhao; Yu, Haiyang; Gao, Shanshan

2015-01-01

Objectives The primary aim of this research was to investigate the wear behavior and wear mechanism of five different veneering porcelains. Methods Five kinds of veneering porcelains were selected in this research. The surface microhardness of all the samples was measured with a microhardness tester. Wear tests were performed on a ball-on-flat PLINT fretting wear machine, with lubrication of artificial saliva at 37°C. The friction coefficients were recorded by the testing system. The microstructure features, wear volume, and damage morphologies were recorded and analyzed with a confocal laser scanning microscope and a scanning electron microscope. The wear mechanism was then elucidated. Results The friction coefficients of the five veneering porcelains differ significantly. No significant correlation between hardness and wear volume was found for these veneering porcelains. Under lubrication of artificial saliva, the porcelain with higher leucite crystal content exhibited greater wear resistance. Additionally, leucite crystal size and distribution in glass matrix influenced wear behavior. The wear mechanisms for these porcelains were similar: abrasive wear dominates the early stage, whereas delamination was the main damage mode at the later stage. Furthermore, delamination was more prominent for porcelains with larger crystal sizes. Significance Wear compatibility between porcelain and natural teeth is important for dental restorative materials. Investigation on crystal content, size, and distribution in glass matrix can provide insight for the selection of dental porcelains in clinical settings. PMID:26368532

Development and validation of carbofuran and 3-hydroxycarbofuran analysis by high-pressure liquid chromatography with diode array detector (HPLC-DAD) for forensic Veterinary Medicine.

PubMed

Gonçalves, Vagner; Hazarbassanov, Nicolle Queiroz; de Siqueira, Adriana; Florio, Jorge Camilo; Ciscato, Claudia Helena Pastor; Maiorka, Paulo Cesar; Fukushima, André Rinaldi; de Souza Spinosa, Helenice

2017-10-15

Agricultural pesticides used with the criminal intent to intoxicate domestic and wild animals are a serious concern in Veterinary Medicine. In order to identify the pesticide carbofuran and its metabolite 3- hydroxycarbofuran in animals suspected of exogenous intoxication a high pressure liquid chromatography with diode array detector (HPLC-DAD) method was developed and validated in stomach contents, liver, vitreous humor and blood. The method was evaluated using biological samples from seven different animal species. The following parameters of analytical validation were evaluated: linearity, precision, accuracy, selectivity, recovery and matrix effect. The method was linear at the range of 6.25-100μg/mL and the correlation coefficient (r 2 ) values were >0.9811 for all matrices. The precision and accuracy of the method was determined by coefficient of variation (CV) and the relative standard deviation error (RSE), and both were less than 15%. Recovery ranged from 74.29 to 100.1% for carbofuran and from 64.72 to 100.61% for 3-hydroxycarbofuran. There were no significant interfering peaks or matrix effects. This method was suitable for detecting 25 positive cases for carbofuran amongst a total of 64 animal samples suspected of poisoning brought to the Toxicology Diagnostic Laboratory, School of Veterinary Medicine and Animal Sciences, University of Sao Paulo. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans.

PubMed

Boriollo, Marcelo Fabiano Gomes; Rosa, Edvaldo Antonio Ribeiro; Gonçalves, Reginaldo Bruno; Höfling, José Francisco

2006-03-01

The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.

Combined micromechanical and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Concurrent micromechanical tailoring and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, Christos C.

1990-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Creation of a retrospective job-exposure matrix using surrogate measures of exposure for a cohort of US career firefighters from San Francisco, Chicago and Philadelphia

PubMed Central

Dahm, Matthew M; Bertke, Stephen; Allee, Steve; Daniels, Robert D

2015-01-01

Objectives To construct a cohort-specific job-exposure matrix (JEM) using surrogate metrics of exposure for a cancer study on career firefighters from the Chicago, Philadelphia and San Francisco Fire Departments. Methods Departmental work history records, along with data on historical annual fire-runs and hours, were collected from 1950 to 2009 and coded into separate databases. These data were used to create a JEM based on standardised job titles and fire apparatus assignments using several surrogate exposure metrics to estimate firefighters’ exposure to the combustion byproducts of fire. The metrics included duration of exposure (cumulative time with a standardised exposed job title and assignment), fire-runs (cumulative events of potential fire exposure) and time at fire (cumulative hours of potential fire exposure). Results The JEM consisted of 2298 unique job titles alongside 16 174 fire apparatus assignments from the three departments, which were collapsed into 15 standardised job titles and 15 standardised job assignments. Correlations were found between fire-runs and time at fires (Pearson coefficient=0.92), duration of exposure and time at fires (Pearson coefficient=0.85), and duration of exposure and fire-runs (Pearson coefficient=0.82). Total misclassification rates were found to be between 16–30% when using duration of employment as an exposure surrogate, which has been traditionally used in most epidemiological studies, compared with using the duration of exposure surrogate metric. Conclusions The constructed JEM successfully differentiated firefighters based on gradient levels of potential exposure to the combustion byproducts of fire using multiple surrogate exposure metrics. PMID:26163543

Creation of a retrospective job-exposure matrix using surrogate measures of exposure for a cohort of US career firefighters from San Francisco, Chicago and Philadelphia.

PubMed

Dahm, Matthew M; Bertke, Stephen; Allee, Steve; Daniels, Robert D

2015-09-01

To construct a cohort-specific job-exposure matrix (JEM) using surrogate metrics of exposure for a cancer study on career firefighters from the Chicago, Philadelphia and San Francisco Fire Departments. Departmental work history records, along with data on historical annual fire-runs and hours, were collected from 1950 to 2009 and coded into separate databases. These data were used to create a JEM based on standardised job titles and fire apparatus assignments using several surrogate exposure metrics to estimate firefighters' exposure to the combustion byproducts of fire. The metrics included duration of exposure (cumulative time with a standardised exposed job title and assignment), fire-runs (cumulative events of potential fire exposure) and time at fire (cumulative hours of potential fire exposure). The JEM consisted of 2298 unique job titles alongside 16,174 fire apparatus assignments from the three departments, which were collapsed into 15 standardised job titles and 15 standardised job assignments. Correlations were found between fire-runs and time at fires (Pearson coefficient=0.92), duration of exposure and time at fires (Pearson coefficient=0.85), and duration of exposure and fire-runs (Pearson coefficient=0.82). Total misclassification rates were found to be between 16-30% when using duration of employment as an exposure surrogate, which has been traditionally used in most epidemiological studies, compared with using the duration of exposure surrogate metric. The constructed JEM successfully differentiated firefighters based on gradient levels of potential exposure to the combustion byproducts of fire using multiple surrogate exposure metrics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Optimization of anaerobic digestion of a mixture of Zea mays and Miscanthus sacchariflorus silages with various pig manure dosages.

PubMed

Bułkowska, K; Pokój, T; Klimiuk, E; Gusiatin, Z M

2012-12-01

Digestion of crop silage (Zea mays L. and Miscanthus sacchariflorus) with 0%, 7.5%, 12.5% and 25% pig manure as co-substrate was performed in continuous stirred-tank reactors, for a constant hydraulic retention time of 45 d and organic load rate of 2.1 g L(-1)d(-1). A matrix of correlations between biogas/methane production and parameters of anaerobic digestion was created in order to estimate process stability. The values of the correlation coefficients indicated that the most stable anaerobic digestion was achieved using 7.5% and 12.5% pig manure. In contrast, the positive correlation between ammonium and volatile fatty acids (r=0.8698, p<0.001) at 25% pig manure showed process instability. Compared to crop silage alone, pig manure favored the production of biogas and methane; the highest production rates were obtained with 12.5% pig manure. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Watson, Andrew B.

1994-01-01

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Evaluation of the QuEChERS method for the extraction of pharmaceuticals and personal care products from drinking-water treatment sludge with determination by UPLC-ESI-MS/MS.

PubMed

Cerqueira, Maristela B R; Guilherme, Juliana R; Caldas, Sergiane S; Martins, Manoel L; Zanella, Renato; Primel, Ednei G

2014-07-01

A modified version of the QuEChERS method has been evaluated for the determination of 21 pharmaceuticals and 6 personal care products (PPCPs) in drinking-water sludge samples by employing ultra high liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The performance of the method was evaluated through linearity, recovery, precision (intra-day), method detection and quantification limits (MDL and MQL) and matrix effect. The calibration curves prepared in acetonitrile and in the matrix extract showed a correlation coefficient ranging from 0.98 to 0.99. MQLs values were on the ng g(-1) order of magnitude for most compounds. Recoveries between 50% and 93% were reached with RSDs lower than 10% for most compounds. Matrix effect was almost absent with values lower than 16% for 93% of the compounds. By coupling a quick and simple extraction called QuEChERS with the UPLC-MS/MS analysis, a method that is both selective and sensitive was obtained. This methodology was successfully applied to real samples and caffeine and benzophenone-3 were detected in ng g(-1) levels. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development and validation of dried matrix spot sampling for the quantitative determination of amyloid β peptides in cerebrospinal fluid.

PubMed

Delaby, Constance; Gabelle, Audrey; Meynier, Philippe; Loubiere, Vincent; Vialaret, Jérôme; Tiers, Laurent; Ducos, Jacques; Hirtz, Christophe; Lehmann, Sylvain

2014-05-01

The use of dried blood spots on filter paper is well documented as an affordable and practical alternative to classical venous sampling for various clinical needs. This technique has indeed many advantages in terms of collection, biological safety, storage, and shipment. Amyloid β (Aβ) peptides are useful cerebrospinal fluid (CSF) biomarkers for Alzheimer disease diagnosis. However, Aβ determination is hindered by preanalytical difficulties in terms of sample collection and stability in tubes. We compared the quantification of Aβ peptides (1-40, 1-42, and 1-38) by simplex and multiplex ELISA, following either a standard operator method (liquid direct quantification) or after spotting CSF onto dried matrix paper card. The use of dried matrix spot (DMS) overcame preanalytical problems and allowed the determination of Aβ concentrations that were highly commutable (Bland-Altman) with those obtained using CSF in classical tubes. Moreover, we found a positive and significant correlation (r2=0.83, Pearson coefficient p=0.0329) between the two approaches. This new DMS method for CSF represents an interesting alternative that increases the quality and efficiency in preanalytics. This should enable the better exploitation of Aβ analytes for Alzheimer's diagnosis.

Role of tumor–host interactions in interstitial diffusion of macromolecules: Cranial vs. subcutaneous tumors

PubMed Central

Pluen, Alain; Boucher, Yves; Ramanujan, Saroja; McKee, Trevor D.; Gohongi, Takeshi; di Tomaso, Emmanuelle; Brown, Edward B.; Izumi, Yotaro; Campbell, Robert B.; Berk, David A.; Jain, Rakesh K.

2001-01-01

The large size of many novel therapeutics impairs their transport through the tumor extracellular matrix and thus limits their therapeutic effectiveness. We propose that extracellular matrix composition, structure, and distribution determine the transport properties in tumors. Furthermore, because the characteristics of the extracellular matrix largely depend on the tumor–host interactions, we postulate that diffusion of macromolecules will vary with tumor type as well as anatomical location. Diffusion coefficients of macromolecules and liposomes in tumors growing in cranial windows (CWs) and dorsal chambers (DCs) were measured by fluorescence recovery after photobleaching. For the same tumor types, diffusion of large molecules was significantly faster in CW than in DC tumors. The greater diffusional hindrance in DC tumors was correlated with higher levels of collagen type I and its organization into fibrils. For molecules with diameters comparable to the interfibrillar space the diffusion was 5- to 10-fold slower in DC than in CW tumors. The slower diffusion in DC tumors was associated with a higher density of host stromal cells that synthesize and organize collagen type I. Our results point to the necessity of developing site-specific drug carriers to improve the delivery of molecular medicine to solid tumors. PMID:11274375

Rectangular rotation of spherical harmonic expansion of arbitrary high degree and order

NASA Astrophysics Data System (ADS)

Fukushima, Toshio

2017-08-01

In order to move the polar singularity of arbitrary spherical harmonic expansion to a point on the equator, we rotate the expansion around the y-axis by 90° such that the x-axis becomes a new pole. The expansion coefficients are transformed by multiplying a special value of Wigner D-matrix and a normalization factor. The transformation matrix is unchanged whether the coefficients are 4 π fully normalized or Schmidt quasi-normalized. The matrix is recursively computed by the so-called X-number formulation (Fukushima in J Geodesy 86: 271-285, 2012a). As an example, we obtained 2190× 2190 coefficients of the rectangular rotated spherical harmonic expansion of EGM2008. A proper combination of the original and the rotated expansions will be useful in (i) integrating the polar orbits of artificial satellites precisely and (ii) synthesizing/analyzing the gravitational/geomagnetic potentials and their derivatives accurately in the high latitude regions including the arctic and antarctic area.

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

Yeung, Yu-Hong; Pothen, Alex; Halappanavar, Mahantesh

We present an augmented matrix approach to update the solution to a linear system of equations when the coefficient matrix is modified by a few elements within a principal submatrix. This problem arises in the dynamic security analysis of a power grid, where operators need to performmore » $N-x$ contingency analysis, i.e., determine the state of the system when up to $x$ links from $N$ fail. Our algorithms augment the coefficient matrix to account for the changes in it, and then compute the solution to the augmented system without refactoring the modified matrix. We provide two algorithms, a direct method, and a hybrid direct-iterative method for solving the augmented system. We also exploit the sparsity of the matrices and vectors to accelerate the overall computation. Our algorithms are compared on three power grids with PARDISO, a parallel direct solver, and CHOLMOD, a direct solver with the ability to modify the Cholesky factors of the coefficient matrix. We show that our augmented algorithms outperform PARDISO (by two orders of magnitude), and CHOLMOD (by a factor of up to 5). Further, our algorithms scale better than CHOLMOD as the number of elements updated increases. The solutions are computed with high accuracy. Our algorithms are capable of computing $N-x$ contingency analysis on a $778K$ bus grid, updating a solution with $x=20$ elements in $$1.6 \\times 10^{-2}$$ seconds on an Intel Xeon processor.« less

An Initial Non-Equilibrium Porous-Media Model for CFD Simulation of Stirling Regenerators

NASA Technical Reports Server (NTRS)

Tew, Roy; Simon, Terry; Gedeon, David; Ibrahim, Mounir; Rong, Wei

2006-01-01

The objective of this paper is to define empirical parameters (or closwre models) for an initial thermai non-equilibrium porous-media model for use in Computational Fluid Dynamics (CFD) codes for simulation of Stirling regenerators. The two CFD codes currently being used at Glenn Research Center (GRC) for Stirling engine modeling are Fluent and CFD-ACE. The porous-media models available in each of these codes are equilibrium models, which assmne that the solid matrix and the fluid are in thermal equilibrium at each spatial location within the porous medium. This is believed to be a poor assumption for the oscillating-flow environment within Stirling regenerators; Stirling 1-D regenerator models, used in Stirling design, we non-equilibrium regenerator models and suggest regenerator matrix and gas average temperatures can differ by several degrees at a given axial location end time during the cycle. A NASA regenerator research grant has been providing experimental and computational results to support definition of various empirical coefficients needed in defining a noa-equilibrium, macroscopic, porous-media model (i.e., to define "closure" relations). The grant effort is being led by Cleveland State University, with subcontractor assistance from the University of Minnesota, Gedeon Associates, and Sunpower, Inc. Friction-factor and heat-transfer correlations based on data taken with the NASAlSunpower oscillating-flow test rig also provide experimentally based correlations that are useful in defining parameters for the porous-media model; these correlations are documented in Gedeon Associates' Sage Stirling-Code Manuals. These sources of experimentally based information were used to define the following terms and parameters needed in the non-equilibrium porous-media model: hydrodynamic dispersion, permeability, inertial coefficient, fluid effective thermal conductivity (including themal dispersion and estimate of tortuosity effects}, and fluid-solid heat transfer coefficient. Solid effective thermal conductivity (including the effect of tortuosity) was also estimated. Determination of the porous-media model parameters was based on planned use in a CFD model of Infinia's Stirling Technology Demonstration Convertor (TDC), which uses a random-fiber regenerator matrix. The non-equilibrium porous-media model presented is considered to be an initial, or "draft," model for possible incorporation in commercial CFD codes, with the expectation that the empirical parameters will likely need to be updated once resulting Stirling CFD model regenerator and engine results have been analyzed. The emphasis of the paper is on use of available data to define empirical parameters (and closure models) needed in a thermal non-equilibrium porous-media model for Stirling regenerator simulation. Such a model has not yet been implemented by the authors or their associates. However, it is anticipated that a thermal non-equilibrium model such as that presented here, when iacorporated in the CFD codes, will improve our ability to accurately model Stirling regenerators with CFD relative to current thermal-equilibrium porous-media models.

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.

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.

Collaborative sparse priors for multi-view ATR

NASA Astrophysics Data System (ADS)

Li, Xuelu; Monga, Vishal

2018-04-01

Recent work has seen a surge of sparse representation based classification (SRC) methods applied to automatic target recognition problems. While traditional SRC approaches used l0 or l1 norm to quantify sparsity, spike and slab priors have established themselves as the gold standard for providing general tunable sparse structures on vectors. In this work, we employ collaborative spike and slab priors that can be applied to matrices to encourage sparsity for the problem of multi-view ATR. That is, target images captured from multiple views are expanded in terms of a training dictionary multiplied with a coefficient matrix. Ideally, for a test image set comprising of multiple views of a target, coefficients corresponding to its identifying class are expected to be active, while others should be zero, i.e. the coefficient matrix is naturally sparse. We develop a new approach to solve the optimization problem that estimates the sparse coefficient matrix jointly with the sparsity inducing parameters in the collaborative prior. ATR problems are investigated on the mid-wave infrared (MWIR) database made available by the US Army Night Vision and Electronic Sensors Directorate, which has a rich collection of views. Experimental results show that the proposed joint prior and coefficient estimation method (JPCEM) can: 1.) enable improved accuracy when multiple views vs. a single one are invoked, and 2.) outperform state of the art alternatives particularly when training imagery is limited.

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.

Microgravity Geyser and Flow Field Prediction

NASA Technical Reports Server (NTRS)

Hochstein, J. I.; Marchetta, J. G.; Thornton, R. J.

2006-01-01

Modeling and prediction of flow fields and geyser formation in microgravity cryogenic propellant tanks was investigated. A computational simulation was used to reproduce the test matrix of experimental results performed by other investigators, as well as to model the flows in a larger tank. An underprediction of geyser height by the model led to a sensitivity study to determine if variations in surface tension coefficient, contact angle, or jet pipe turbulence significantly influence the simulations. It was determined that computational geyser height is not sensitive to slight variations in any of these items. An existing empirical correlation based on dimensionless parameters was re-examined in an effort to improve the accuracy of geyser prediction. This resulted in the proposal for a re-formulation of two dimensionless parameters used in the correlation; the non-dimensional geyser height and the Bond number. It was concluded that the new non-dimensional geyser height shows little promise. Although further data will be required to make a definite judgement, the reformulation of the Bond number provided correlations that are more accurate and appear to be more general than the previously established correlation.

Quantitative T2-Mapping and T2⁎-Mapping Evaluation of Changes in Cartilage Matrix after Acute Anterior Cruciate Ligament Rupture and the Correlation between the Results of Both Methods

PubMed Central

Tao, Hongyue; Qiao, Yang; Hu, Yiwen; Xie, Yuxue; Lu, Rong; Yan, Xu

2018-01-01

Objectives To quantitatively assess changes in cartilage matrix after acute anterior cruciate ligament (ACL) rupture using T2- and T2⁎-mapping and analyze the correlation between the results of both methods. Methods Twenty-three patients and 23 healthy controls were enrolled and underwent quantitative MRI examination. The knee cartilage was segmented into six compartments, including lateral femur (LF), lateral tibia (LT), medial femur (MF), medial tibia (MT), trochlea (Tr), and patella (Pa). T2 and T2⁎ values were measured in full-thickness as well as superficial and deep layers of each cartilage compartment. Differences of T2 and T2⁎ values between patients and controls were compared using unpaired Student's t-test, and the correlation between their reciprocals was analyzed using Pearson's correlation coefficient. Results ACL-ruptured patients showed higher T2 and T2⁎ values in full-thickness and superficial layers of medial and lateral tibiofemoral joint. Meanwhile, patients exhibited higher T2⁎ values in deep layers of lateral tibiofemoral joint. The elevated percentages of T2 and T2⁎ value in superficial LT were most significant (20.738%, 17.525%). The reciprocal of T2⁎ value was correlated with that of T2 value (r = 0.886, P < 0.001). Conclusion The early degeneration could occur in various knee cartilage compartments after acute ACL rupture, especially in the superficial layer of LT. T2⁎-mapping might be more sensitive in detecting deep layer of cartilage than T2-mapping. PMID:29888279

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

Trafimow, David

2016-01-01

Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.

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.

Element analysis and calculation of the attenuation coefficients for gold, bronze and water matrixes using MCNP, WinXCom and experimental data

NASA Astrophysics Data System (ADS)

Esfandiari, M.; Shirmardi, S. P.; Medhat, M. E.

2014-06-01

In this study, element analysis and the mass attenuation coefficient for matrixes of gold, bronze and water with various impurities and the concentrations of heavy metals (Cu, Mn, Pb and Zn) are evaluated and calculated by the MCNP simulation code for photons emitted from Barium-133, Americium-241 and sources with energies between 1 and 100 keV. The MCNP data are compared with the experimental data and WinXCom code simulated results by Medhat. The results showed that the obtained results of bronze and gold matrix are in good agreement with the other methods for energies above 40 and 60 keV, respectively. However for water matrixes with various impurities, there is a good agreement between the three methods MCNP, WinXCom and the experimental one in low and high energies.

[Determination of azoxystrobin residues in fruits and vegetables by gas chromatography/mass spectrometry with solid-phase extraction].

PubMed

Bo, Haibo

2007-11-01

A method was developed for the determination of azoxystrobin residues in fruits and vegetables by gas chromatography/mass spectrometry (GC/MS). Azoxystrobin residues were extracted with ethyl acetate-cyclohexane (1 : 1, v/v) by ultrasonication and then they were cleaned up on a silica solid-phase extraction (SPE) column to obtain an extract suitable for analysis by GC/MS in the selective ion monitoring (SIM) mode (the selected ion: m/z 344, 372, 388 and 403). The calibration curves were linear between area and concentration of azoxystrobin from 0.01 to 1.0 mg/kg with the correlation coefficient greater than 0.99. The average recoveries from spiked fruit and vegetable matrixes at three concentrations of 0.01, 0.1, 1.0 mg/kg ranged from 85.2% to 98.2% with relative standard deviation less than 21.5%. The limit of detection was 0.01 mg/kg and the limit of quantity was 0.05 mg/kg in fruit and vegetable matrixes, respectively.

3D Mueller-matrix mapping of biological optically anisotropic networks

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Ushenko, V. O.; Bodnar, G. B.; Zhytaryuk, V. G.; Prydiy, O. G.; Koval, G.; Lukashevich, I.; Vanchuliak, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Mechanical properties of neat polymer matrix materials and their unidirectional carbon fiber-reinforced composites

NASA Technical Reports Server (NTRS)

Zimmerman, Richard S.; Adams, Donald F.

1988-01-01

The mechanical properties of two neat resin systems for use in carbon fiber epoxy composites were characterized. This included tensile and shear stiffness and strengths, coefficients of thermal and moisture expansion, and fracture toughness. Tests were conducted on specimens in the dry and moisture-saturated states, at temperatures of 23, 82 and 121 C. The neat resins tested were American Cyanamid 1806 and Union Carbide ERX-4901B(MPDA). Results were compared to previously tested neat resins. Four unidirectional carbon fiber reinforced composites were mechanically characterized. Axial and transverse tension and in-plane shear strengths and stiffness were measured, as well as transverse coefficients of thermal and moisture expansion. Tests were conducted on dry specimens only at 23 and 100 C. The materials tested were AS4/3502, AS6/5245-C, T300/BP907, and C6000/1806 unidirectional composites. Scanning electron microscopic examination of fracture surfaces was performed to permit the correlation of observed failure modes with the environmental test conditions.

[Study on the characteristics of radiance calibration using nonuniformity extended source].

PubMed

Wang, Jian-Wei; Huang, Min; Xiangli, Bin; Tu, Xiao-Long

2013-07-01

Integrating sphere and diffuser are always used as extended source, and they have different effects on radiance calibration of imaging spectrometer with parameter difference. In the present paper, a mathematical model based on the theory of radiative transfer and calibration principle is founded to calculate the irradiance and calibration coefficients on CCD, taking relatively poor uniformity lights-board calibration system for example. The effects of the nonuniformity on the calibration was analyzed, which makes up the correlation of calibration coefficient matrix under ideal and unideal situation. The results show that the nonuniformity makes the viewing angle and the position of the point of intersection of the optical axis and the diffuse reflection plate have relatively large effects on calibration, while the observing distance's effect is small; under different viewing angles, a deviation value can be found that makes the calibration results closest to the desired results. So, the calibration error can be reduced by choosing appropriate deviation value.

Improved flexoelectricity in PVDF/barium strontium titanate (BST) nanocomposites

NASA Astrophysics Data System (ADS)

Hu, Xinping; Zhou, Yang; Liu, Jie; Chu, Baojin

2018-04-01

The flexoelectric effect of polymers is normally much weaker than that of ferroelectric oxides. In order to improve the flexoelectric response of the poly(vinylidene fluoride) (PVDF) ferroelectric polymer, PVDF/Ba0.67Si0.33TiO3 (BST) nanocomposites were fabricated. BST nanofibers were prepared by the electrospinning method, and the fibers were further surface modified with H2O2 to achieve a stronger interfacial interaction between the fibers and polymer matrix. Due to the high dielectric properties and strong flexoelectric effect of the BST, both dielectric constant and flexoelectric response of the composite with 25 vol. % surface modified BST are 3-4 times higher than those of PVDF. The dependence of the dielectric constant and the flexoelectric coefficient on the composition of the nanocomposites can be fitted by the empirical Yamada model, and the dielectric constant and the flexoelectric coefficient are correlated by a linear relationship. This study provides an approach to enhance the flexoelectric response of PVDF-based polymers.

Allelic database and accession divergence of a Brazilian mango collection based on microsatellite markers.

PubMed

Dos Santos Ribeiro, I C N; Lima Neto, F P; Santos, C A F

2012-12-19

Allelic patterns and genetic distances were examined in a collection of 103 foreign and Brazilian mango (Mangifera indica) accessions in order to develop a reference database to support cultivar protection and breeding programs. An UPGMA dendrogram was generated using Jaccard's coefficients from a distance matrix based on 50 alleles of 12 microsatellite loci. The base pair number was estimated by the method of inverse mobility. The cophenetic correlation was 0.8. The accessions had a coefficient of similarity from 30 to 100%, which reflects high genetic variability. Three groups were observed in the UPGMA dendrogram; the first group was formed predominantly by foreign accessions, the second group was formed by Brazilian accessions, and the Dashehari accession was isolated from the others. The 50 microsatellite alleles did not separate all 103 accessions, indicating that there are duplicates in this mango collection. These 12 microsatellites need to be validated in order to establish a reliable set to identify mango cultivars.

Optimized data fusion for K-means Laplacian clustering

PubMed Central

Yu, Shi; Liu, Xinhai; Tranchevent, Léon-Charles; Glänzel, Wolfgang; Suykens, Johan A. K.; De Moor, Bart; Moreau, Yves

2011-01-01

Motivation: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically. Results: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix. Availability: The MATLAB code of algorithms implemented in this paper is downloadable from http://homes.esat.kuleuven.be/~sistawww/bioi/syu/oklc.html. Contact: shiyu@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20980271

Line mixing in a N2-broadened CO2 Q branch observed with a tunable diode laser

NASA Technical Reports Server (NTRS)

Gentry, Bruce; Strow, L. Larrabee

1987-01-01

Line-mixing effects have been observed in the infrared Q branch of the (11/1/0,03/1/0)I-00/0/0 band of CO2 at 2076/cm. A tunable diode laser spectrometer was used to record spectra of CO2 broadened by N2 and O2 at total pressures ranging from 100 to 720 torr. The observed absorption coefficients are up to 65 percent lower than those calculated using an isolated Lorentzian line approximation. A simple energy gap scaling law is used to determine the off-diagonal relaxation matrix elements from the known pressure-broadening coefficients. The spectra calculated using these matrix elements reproduces the observed absorption coefficients to within several percent.

Complex network analysis of conventional and Islamic stock market in Indonesia

NASA Astrophysics Data System (ADS)

Rahmadhani, Andri; Purqon, Acep; Kim, Sehyun; Kim, Soo Yong

2015-09-01

The rising popularity of Islamic financial products in Indonesia has become a new interesting topic to be analyzed recently. We introduce a complex network analysis to compare conventional and Islamic stock market in Indonesia. Additionally, Random Matrix Theory (RMT) has been added as a part of reference to expand the analysis of the result. Both of them are based on the cross correlation matrix of logarithmic price returns. Closing price data, which is taken from June 2011 to July 2012, is used to construct logarithmic price returns. We also introduce the threshold value using winner-take-all approach to obtain scale-free property of the network. This means that the nodes of the network that has a cross correlation coefficient below the threshold value should not be connected with an edge. As a result, we obtain 0.5 as the threshold value for all of the stock market. From the RMT analysis, we found that there is only market wide effect on both stock market and no clustering effect has been found yet. From the network analysis, both of stock market networks are dominated by the mining sector. The length of time series of closing price data must be expanded to get more valuable results, even different behaviors of the system.

A combined approach of physicochemical and biological methods for the characterization of petroleum hydrocarbon-contaminated soil.

PubMed

Masakorala, Kanaji; Yao, Jun; Chandankere, Radhika; Liu, Haijun; Liu, Wenjuan; Cai, Minmin; Choi, Martin M F

2014-01-01

Main physicochemical and microbiological parameters of collected petroleum-contaminated soils with different degrees of contamination from DaGang oil field (southeast of Tianjin, northeast China) were comparatively analyzed in order to assess the influence of petroleum contaminants on the physicochemical and microbiological properties of soil. An integration of microcalorimetric technique with urease enzyme analysis was used with the aim to assess a general status of soil metabolism and the potential availability of nitrogen nutrient in soils stressed by petroleum-derived contaminants. The total petroleum hydrocarbon (TPH) content of contaminated soils varied from 752.3 to 29,114 mg kg(−1). Although the studied physicochemical and biological parameters showed variations dependent on TPH content, the correlation matrix showed also highly significant correlation coefficients among parameters, suggesting their utility in describing a complex matrix such as soil even in the presence of a high level of contaminants. The microcalorimetric measures gave evidence of microbial adaptation under highest TPH concentration; this would help in assessing the potential of a polluted soil to promote self-degradation of oil-derived hydrocarbon under natural or assisted remediation. The results highlighted the importance of the application of combined approach in the study of those parameters driving the soil amelioration and bioremediation.

Analysis of some metallic elements and metalloids composition and relationships in parasol mushroom Macrolepiota procera.

PubMed

Falandysz, Jerzy; Sapkota, Atindra; Dryżałowska, Anna; Mędyk, Małgorzata; Feng, Xinbin

2017-06-01

The aim of the study was to characterise the multi-elemental composition and associations between a group of 32 elements and 16 rare earth elements collected by mycelium from growing substrates and accumulated in fruiting bodies of Macrolepiota procera from 16 sites from the lowland areas of Poland. The elements were quantified by inductively coupled plasma quadrupole mass spectrometry using validated method. The correlation matrix obtained from a possible 48 × 16 data matrix has been used to examine if any association exits between 48 elements in mushrooms foraged from 16 sampling localizations by multivariate approach using principal component (PC) analysis. The model could explain up to 93% variability by eight factors for which an eigenvalue value was ≥1. Absolute values of the correlation coefficient were above 0.72 (significance at p < 0.05) for 43 elements. From a point of view by consumer, the absolute content of Cd, Hg, Pb in caps of M. procera collected from background (unpolluted) areas could be considered elevated while sporadic/occasional ingestion of this mushroom is considered safe. The multivariate functional analysis revealed on associated accumulation of many elements in this mushroom. M. procera seem to possess some features of a bio-indicative species for anthropogenic Pb but also for some geogenic metals.

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.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Two SPSS programs for interpreting multiple regression results.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J; Chico, Eliseo

2010-02-01

When multiple regression is used in explanation-oriented designs, it is very important to determine both the usefulness of the predictor variables and their relative importance. Standardized regression coefficients are routinely provided by commercial programs. However, they generally function rather poorly as indicators of relative importance, especially in the presence of substantially correlated predictors. We provide two user-friendly SPSS programs that implement currently recommended techniques and recent developments for assessing the relevance of the predictors. The programs also allow the user to take into account the effects of measurement error. The first program, MIMR-Corr.sps, uses a correlation matrix as input, whereas the second program, MIMR-Raw.sps, uses the raw data and computes bootstrap confidence intervals of different statistics. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from http://brm.psychonomic-journals.org/content/supplemental.

Genetic diversity and relationship of Hedychium from Northeast India as dissected using PCA analysis and hierarchical clustering.

PubMed

Basak, Supriyo; Ramesh, Aadi Moolam; Kesari, Vigya; Parida, Ajay; Mitra, Sudip; Rangan, Latha

2014-12-01

Molecular genetic fingerprints of eleven Hedychium species from Northeast India were developed using PCR based markers. Fifteen inter-simple sequence repeats (ISSRs) and five amplified fragment length polymorphism (AFLP) primers produced 547 polymorphic fragments. Positive correlation (r = 0.46) was observed between the mean genetic similarity and genetic diversity parameters at the inter-species level. AFLP and ISSR markers were able to group the species according to its altitude and intensity of flower aroma. Cophenetic correlation coefficients between the dendrogram and the original similarity matrix were significant for ISSR (r = 0.89) compared to AFLP (r = 0.83) markers. This genetic characterization of Hedychium from Northeast India contributes to the knowledge of genetic structure of the species and can be used to define strategies for their conservation and management.

Estimates of genetic and environmental (co)variances for first lactation on milk yield, survival, and calving interval.

PubMed

Dong, M C; van Vleck, L D

1989-03-01

Variance and covariance components for milk yield, survival to second freshening, calving interval in first lactation were estimated by REML with the expectation and maximization algorithm for an animal model which included herd-year-season effects. Cows without calving interval but with milk yield were included. Each of the four data sets of 15 herds included about 3000 Holstein cows. Relationships across herds were ignored to enable inversion of the coefficient matrix of mixed model equations. Quadratics and their expectations were accumulated herd by herd. Heritability of milk yield (.32) agrees with reports by same methods. Heritabilities of survival (.11) and calving interval(.15) are slightly larger and genetic correlations smaller than results from different methods of estimation. Genetic correlation between milk yield and calving interval (.09) indicates genetic ability to produce more milk is lightly associated with decreased fertility.

Changes of hierarchical network in local and world stock market

NASA Astrophysics Data System (ADS)

Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

2017-10-01

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

MATIN: a random network coding based framework for high quality peer-to-peer live video streaming.

PubMed

Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

2013-01-01

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

A novel mathematical model considering change of diffusion coefficient for predicting dissolution behavior of acetaminophen from wax matrix dosage form.

PubMed

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

2012-05-30

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

Diffusive processes in a stochastic magnetic field

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

Wang, H.; Vlad, M.; Vanden Eijnden, E.

1995-05-01

The statistical representation of a fluctuating (stochastic) magnetic field configuration is studied in detail. The Eulerian correlation functions of the magnetic field are determined, taking into account all geometrical constraints: these objects form a nondiagonal matrix. The Lagrangian correlations, within the reasonable Corrsin approximation, are reduced to a single scalar function, determined by an integral equation. The mean square perpendicular deviation of a geometrical point moving along a perturbed field line is determined by a nonlinear second-order differential equation. The separation of neighboring field lines in a stochastic magnetic field is studied. We find exponentiation lengths of both signs describing,more » in particular, a decay (on the average) of any initial anisotropy. The vanishing sum of these exponentiation lengths ensures the existence of an invariant which was overlooked in previous works. Next, the separation of a particle`s trajectory from the magnetic field line to which it was initially attached is studied by a similar method. Here too an initial phase of exponential separation appears. Assuming the existence of a final diffusive phase, anomalous diffusion coefficients are found for both weakly and strongly collisional limits. The latter is identical to the well known Rechester-Rosenbluth coefficient, which is obtained here by a more quantitative (though not entirely deductive) treatment than in earlier works.« less

Influence of microarchitecture alterations on ultrasonic backscattering in an experimental simulation of bovine cancellous bone aging.

PubMed

Apostolopoulos, K N; Deligianni, D D

2008-02-01

An experimental model which can simulate physical changes that occur during aging was developed in order to evaluate the effects of change of mineral content and microstructure on ultrasonic properties of bovine cancellous bone. Timed immersion in hydrochloric acid was used to selectively alter the mineral content. Scanning electron microscopy and histological staining of the acid-treated trabeculae demonstrated a heterogeneous structure consisting of a mineralized core and a demineralized layer. The presence of organic matrix contributed very little to normalized broadband ultrasound attenuation (nBUA) and speed of sound. All three ultrasonic parameters, speed of sound, nBUA and backscatter coefficient, were sensitive to changes in apparent density of bovine cancellous bone. A two-component model utilizing a combination of two autocorrelation functions (a densely populated model and a spherical distribution) was used to approximate the backscatter coefficient. The predicted attenuation due to scattering constituted a significant part of the measured total attenuation (due to both scattering and absorption mechanisms) for bovine cancellous bone. Linear regression, performed between trabecular thickness values and estimated from the model correlation lengths, showed significant linear correlation, with R(2)=0.81 before and R(2)=0.80 after demineralization. The accuracy of estimation was found to increase with trabecular thickness.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Fast evaluation of scaled opposite spin second-order Møller-Plesset correlation energies using auxiliary basis expansions and exploiting sparsity.

PubMed

Jung, Yousung; Shao, Yihan; Head-Gordon, Martin

2007-09-01

The scaled opposite spin Møller-Plesset method (SOS-MP2) is an economical way of obtaining correlation energies that are computationally cheaper, and yet, in a statistical sense, of higher quality than standard MP2 theory, by introducing one empirical parameter. But SOS-MP2 still has a fourth-order scaling step that makes the method inapplicable to very large molecular systems. We reduce the scaling of SOS-MP2 by exploiting the sparsity of expansion coefficients and local integral matrices, by performing local auxiliary basis expansions for the occupied-virtual product distributions. To exploit sparsity of 3-index local quantities, we use a blocking scheme in which entire zero-rows and columns, for a given third global index, are deleted by comparison against a numerical threshold. This approach minimizes sparse matrix book-keeping overhead, and also provides sufficiently large submatrices after blocking, to allow efficient matrix-matrix multiplies. The resulting algorithm is formally cubic scaling, and requires only moderate computational resources (quadratic memory and disk space) and, in favorable cases, is shown to yield effective quadratic scaling behavior in the size regime we can apply it to. Errors associated with local fitting using the attenuated Coulomb metric and numerical thresholds in the blocking procedure are found to be insignificant in terms of the predicted relative energies. A diverse set of test calculations shows that the size of system where significant computational savings can be achieved depends strongly on the dimensionality of the system, and the extent of localizability of the molecular orbitals. Copyright 2007 Wiley Periodicals, Inc.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

Ceramic matrix composite turbine engine vane

NASA Technical Reports Server (NTRS)

Prill, Lisa A. (Inventor); Schaff, Jeffery R. (Inventor); Shi, Jun (Inventor)

2012-01-01

A vane has an airfoil shell and a spar within the shell. The vane has an outboard shroud at an outboard end of the shell and an inboard platform at an inboard end of the shell. The shell includes a region having a depth-wise coefficient of thermal expansion and a second coefficient of thermal expansion transverse thereto, the depth-wise coefficient of thermal expansion being greater than the second coefficient of thermal expansion.

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

NASA Astrophysics Data System (ADS)

Prószyński, W.; Kwaśniak, M.

2018-03-01

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

Retention of aroma compounds: an interlaboratory study on the effect of the composition of food matrices on thermodynamic parameters in comparison with water.

PubMed

Kopjar, Mirela; Andriot, Isabelle; Saint-Eve, Anne; Souchon, Isabelle; Guichard, Elisabeth

2010-06-01

Partition coefficients give an indication of the retention of aroma compounds by the food matrix. Data in the literature are obtained by various methods, under various conditions and expressed in various units, and it is thus difficult to compare the results. The aim of the present study was first to obtain gas/water and gas/matrix partition coefficients of selected aroma compounds, at different temperatures, in order to calculate thermodynamic parameters and second to compare the retention of these aroma compounds in different food matrices. Yogurts containing lipids and proteins induced a higher retention of aroma compounds than model gel matrices. The observed effects strongly depend on hydrophobicity of aroma compounds showing a retention for ethyl hexanoate and a salting out effect for ethyl acetate. A small but noticeable decrease in enthalpy of affinity is observed for ethyl butyrate and ethyl hexanoate between water and food matrices, suggesting that the energy needed for the volatilization is lower in matrices than in water. The composition and complexity of a food matrix influence gas/matrix partition coefficients or aroma compounds in function of their hydrophobicity and to a lower extent enthalpy of vaporization. Copyright (c) 2010 Society of Chemical Industry.

Family nonuniversal Z' models with protected flavor-changing interactions

NASA Astrophysics Data System (ADS)

Celis, Alejandro; Fuentes-Martín, Javier; Jung, Martin; Serôdio, Hugo

2015-07-01

We define a new class of Z' models with neutral flavor-changing interactions at tree level in the down-quark sector. They are related in an exact way to elements of the quark mixing matrix due to an underlying flavored U(1)' gauge symmetry, rendering these models particularly predictive. The same symmetry implies lepton-flavor nonuniversal couplings, fully determined by the gauge structure of the model. Our models allow us to address presently observed deviations from the standard model and specific correlations among the new physics contributions to the Wilson coefficients C9,10' ℓ can be tested in b →s ℓ+ℓ- transitions. We furthermore predict lepton-universality violations in Z' decays, testable at the LHC.

The longitudinal interplay between negative and positive symptom trajectories in patients under antipsychotic treatment: a post hoc analysis of data from a randomized, 1-year pragmatic trial.

PubMed

Chen, Lei; Johnston, Joseph A; Kinon, Bruce J; Stauffer, Virginia; Succop, Paul; Marques, Tiago R; Ascher-Svanum, Haya

2013-11-28

Schizophrenia is a highly heterogeneous disorder with positive and negative symptoms being characteristic manifestations of the disease. While these two symptom domains are usually construed as distinct and orthogonal, little is known about the longitudinal pattern of negative symptoms and their linkage with the positive symptoms. This study assessed the temporal interplay between these two symptom domains and evaluated whether the improvements in these symptoms were inversely correlated or independent with each other. This post hoc analysis used data from a multicenter, randomized, open-label, 1-year pragmatic trial of patients with schizophrenia spectrum disorder who were treated with first- and second-generation antipsychotics in the usual clinical settings. Data from all treatment groups were pooled resulting in 399 patients with complete data on both the negative and positive subscale scores from the Positive and Negative Syndrome Scale (PANSS). Individual-based growth mixture modeling combined with interplay matrix was used to identify the latent trajectory patterns in terms of both the negative and positive symptoms. Pearson correlation coefficients were calculated to examine the relationship between the changes of these two symptom domains within each combined trajectory pattern. We identified four distinct negative symptom trajectories and three positive symptom trajectories. The trajectory matrix formed 11 combined trajectory patterns, which evidenced that negative and positive symptom trajectories moved generally in parallel. Correlation coefficients for changes in negative and positive symptom subscale scores were positive and statistically significant (P < 0.05). Overall, the combined trajectories indicated three major distinct patterns: (1) dramatic and sustained early improvement in both negative and positive symptoms (n = 70, 18%), (2) mild and sustained improvement in negative and positive symptoms (n = 237, 59%), and (3) no improvement in either negative or positive symptoms (n = 82, 21%). This study of symptom trajectories over 1 year shows that changes in negative and positive symptoms were neither inversely nor independently related with each other. The positive association between these two symptom domains supports the notion that different symptom domains in schizophrenia may depend on each other through a unified upstream pathological disease process.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Determination of uric acid level by polyaniline and poly (allylamine): Based biosensor

PubMed Central

Wathoni, Nasrul; Hasanah, Aliya Nur; Gozali, Dolih; Wahyuni, Yeni; Fauziah, Lia Layusa

2014-01-01

The uric acid biosensor has been much developed by immobilizing uricase enzyme into the membrane of conductive polymer and the membrane of polyelectrolyte such as polyaniline (PANI) and poly (allylamine) (PAA) respectively. The purpose of this research was to create a new amperometric uric acid biosensor by immobilization of uricase in combination between PANI and PAA membranes. The working electrode was Pt plate (0.5 mm). The auxiliary and the reference electrode were Pt wire 0.4 mm and Ag/AgCl respectively. Uricase, uric acid, PAA, pyrrole and glutaraldehyde were supplied from Sigma. All other chemical was obtained from Merck. The biosensor was created by immobilizing of uricase by a glutaraldehyde crosslinking procedure on PANI composite film on the surface of a platinum electrode while the polyelectrolyte layer of PAA were prepared via layer-by-layer assembly on the electrode, functioning as H2O2-selective film. Standard of deviation, coefficient of variation (CV) and coefficient of correlation (r) analysis were used in this study. The biosensor had a good linearity with a correlation coefficient of 0.993 and it could be used up to 27 times with the CV value of 3.97%. The presence of other compounds such as glucose and ascorbic acid gave 1.3 ± 1.13% and 3.27 ± 2.29% respectively on the interference effect toward the current response of uric acid biosensor. The polymer combination of PANI and PAA can be used as a selective matrix of uric acid biosensor. PMID:24696812

Validity and reliability of the Turkish version of the European Health Literacy Survey Questionnaire.

PubMed

Abacigil, Filiz; Harlak, Hacer; Okyay, Pinar; Kiraz, Didem Evci; Gursoy Turan, Selen; Saruhan, Gulnur; Karakaya, Kagan; Tuzun, Hakan; Baran Deniz, Emine; Tontus, Omer; Beser, Erdal

2018-04-10

Health literacy is a public health priority which refers to individual's knowledge, motivation and competence to access, understand, appraise and apply health information to prevent disease and promote health in daily life. This study aimed to adapt European Health Literacy Survey Questionnaire (HLS-EU-Q47) into Turkish and to investigate its psychometric properties. The questionnaire was translated into Turkish by using both group translation and expert opinion methods. Forward translation-back translation method was used for language validity and the final Turkish version (HLS-TR) was formed. HLS-EU-Q47 and Health Awareness Scale (HAS) were administered to 505 respondents. The scale reliability was examined using Crohnbach's alpha coefficient and the construct validity was assessed by principal axis factoring procedure. The convergent validity was obtained by Pearson correlation coefficients between HLS-TR and HAS scores and discriminant validity was examined comparing the scores of participants who were stratified according to ages, educational status, gender, general health status and social status. Cronbach's alpha coefficient for the whole scale was 0.95. Principal axis factoring extracted nine factors which eigenvalues were >1 and explained 50.01% of total variance. Factor matrix displayed that all items gave greater load in factor 1, showing that health literacy measured with one factor. Positive and significant correlation was found between HLS-TR and HAS. Significant relations were found between HLS-TR scores and selected determinants of health. This study revealed that the HLS-TR was a valid and reliable measuring instrument with appropriate psychometric characteristics.

A note on the upper bound of the spectral radius for SOR iteration matrix

NASA Astrophysics Data System (ADS)

Chang, D.-W. Da-Wei

2004-05-01

Recently, Wang and Huang (J. Comput. Appl. Math. 135 (2001) 325, Corollary 4.7) established the following estimation on the upper bound of the spectral radius for successive overrelaxation (SOR) iteration matrix:ρSOR≤1-ω+ωρGSunder the condition that the coefficient matrix A is a nonsingular M-matrix and ω≥1, where ρSOR and ρGS are the spectral radius of SOR iteration matrix and Gauss-Seidel iteration matrix, respectively. In this note, we would like to point out that the above estimation is not valid in general.

Seamless metal-clad fiber-reinforced organic matrix composite structures and process for their manufacture

NASA Technical Reports Server (NTRS)

Bluck, Raymond M. (Inventor); Bush, Harold G. (Inventor); Johnson, Robert R. (Inventor)

1990-01-01

A metallic outer sleeve is provided which is capable of enveloping a hollow metallic inner member having continuous reinforcing fibers attached to the distal end thereof. The inner member is then introduced into outer sleeve until inner member is completely enveloped by outer sleeve. A liquid matrix member is then injected into space between inner member and outer sleeve. A pressurized heat transfer medium is flowed through the inside of inner member, thereby forming a fiber reinforced matrix composite material. The wall thicknesses of both inner member and outer sleeve are then reduced to the appropriate size by chemical etching, to adjust the thermal expansion coefficient of the metal-clad composite structure to the desired value. thereby forming a fiber reinforced matrix composite material. The wall thicknesses of both inner member and outer sleeve are then reduced to the appropriate size by chemical etching, to adjust the thermal expansion coefficient of the metal-clad composite structure to the desired value. The novelty of this invention resides in the development of a efficient method of producing seamless metal clad fiber reinforced organic matrix composite structures.

Wavefront aberrations: analytical method to convert Zernike coefficients from a pupil to a scaled arbitrarily decentered one

NASA Astrophysics Data System (ADS)

Comastri, S. A.; Perez, Liliana I.; Pérez, Gervasio D.; Bastida, K.; Martin, G.

2008-04-01

The wavefront aberration of any image forming system and, in particular, of a human eye, is often expanded in Zernike modes each mode being weighed by a coefficient that depends both on the image forming components of the system and on the contour, size and centering of the pupil. In the present article, expanding up to 7th order the wavefront aberration, an analytical method to compute a new set of Zernike coefficients corresponding to a pupil in terms of an original set evaluated via ray tracing for a dilated and transversally arbitrarily displaced pupil is developed. A transformation matrix of dimension 36×36 is attained multiplying the scaling-horizontal traslation matrix previously derived by appropriate rotation matrices. Multiplying the original coefficients by this transformation matrix, analytical formulas for each new coefficient are attained and supplied and, for the information concerning the wavefront aberration to be available, these formulas must be employed in cases in which the new pupil is contained in the original one. The use of these analytical formulas is exemplified applying them to study the effect of pupil contraction and/or decentering in 3 situations: calculation of corneal aberrations of a keratoconic subject for the natural photopic pupil size and various decenterings; coma compensation by means of pupil shift in a fictitious system solely having primary aberrations and evaluation of the amount of astigmatism and coma of a hypothetical system originally having spherical aberration alone.

Helium measurements of pore fluids obtained from the San Andreas Fault Observatory at Depth (SAFOD, USA) drill cores

NASA Astrophysics Data System (ADS)

Ali, S.; Stute, M.; Torgersen, T.; Winckler, G.; Kennedy, B. M.

2011-02-01

4He accumulated in fluids is a well established geochemical tracer used to study crustal fluid dynamics. Direct fluid samples are not always collectable; therefore, a method to extract rare gases from matrix fluids of whole rocks by diffusion has been adapted. Helium was measured on matrix fluids extracted from sandstones and mudstones recovered during the San Andreas Fault Observatory at Depth (SAFOD) drilling in California, USA. Samples were typically collected as subcores or from drillcore fragments. Helium concentration and isotope ratios were measured 4-6 times on each sample, and indicate a bulk 4He diffusion coefficient of 3.5 ± 1.3 × 10-8 cm2 s-1 at 21°C, compared to previously published diffusion coefficients of 1.2 × 10-18 cm2 s-1 (21°C) to 3.0 × 10-15 cm2 s-1 (150°C) in the sands and clays. Correcting the diffusion coefficient of 4Hewater for matrix porosity (˜3%) and tortuosity (˜6-13) produces effective diffusion coefficients of 1 × 10-8 cm2 s-1 (21°C) and 1 × 10-7 (120°C), effectively isolating pore fluid 4He from the 4He contained in the rock matrix. Model calculations indicate that <6% of helium initially dissolved in pore fluids was lost during the sampling process. Complete and quantitative extraction of the pore fluids provide minimum in situ porosity values for sandstones 2.8 ± 0.4% (SD, n = 4) and mudstones 3.1 ± 0.8% (SD, n = 4).

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

Matrix metalloproteinase 9 and transglutaminase 2 expression at the ocular surface in patients with different forms of dry eye disease.

PubMed

Aragona, Pasquale; Aguennouz, M'Hammed; Rania, Laura; Postorino, Elisa; Sommario, Margherita Serena; Roszkowska, Anna Maria; De Pasquale, Maria Grazia; Pisani, Antonina; Puzzolo, Domenico

2015-01-01

To evaluate the expression of matrix metalloproteinase 9 (MMP9) and transglutaminase 2 (TG2) in different forms of dry eye. Case control study. Seventy-five female subjects divided into 3 groups: group 1, 15 healthy controls; group 2, 30 subjects with Sjögren syndrome (SS); and group 3, 30 subjects with Meibomian gland dysfunction (MGD). A clinical assessment was carried out and impression cytologic specimens were processed for immunoperoxidase staining for MMP9 and TG2 and real-time polymerase chain reaction analyses were carried out for MMP9, TG2, interleukin-6, interferon-γ, B-cell lymphoma 2, and caspase 3. To study MMP9 and TG2 expression after anti-inflammatory treatment, patients were divided into 2 subgroups, one treated with saline and the other treated with saline plus topical corticosteroid eye drops (0.5% loteprednol etabonate) 4 times daily for 15 days. For statistical analysis, Student t test, Mann-Whitney U test, and Spearman's correlation coefficient were used as appropriate. Conjunctival expression of MMP9 and TG2. MMP9 and TG2 expression were higher in both patient groups than in controls (P < 0.0001). Group 2 patients showed higher expression than group 3 (P < 0.0001). The Spearman's correlation coefficient showed in group 2 a positive correlation between MMP9 and TG2 expression (ρ = 0.437; P = 0.01), but no correlation in group 3 (ρ = 0.143; P = 0.45). Corticosteroid treatment significantly reduced MMP9 and TG2 expression in both groups, ameliorating symptoms and signs. A much higher percentage reduction was observed in SS. The pathogenic mechanisms of the 2 forms of dry eye give an account for the different MMP9 and TG2 expressions in the 2 groups of patients. The higher expression in SS is determined by the direct autoimmune insult to the ocular surface epithelia, whereas in MGD patients, with an epithelial damage due to an unbalanced tear secretion, the molecules expression is significantly lower, although higher than in controls. The corticosteroid treatment induced a reduction of both molecules, although higher in SS than in MGD, because of its direct inhibitory effect on inflammation. Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Sensitivity Analysis of Nuclide Importance to One-Group Neutron Cross Sections

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

Sekimoto, Hiroshi; Nemoto, Atsushi; Yoshimura, Yoshikane

The importance of nuclides is useful when investigating nuclide characteristics in a given neutron spectrum. However, it is derived using one-group microscopic cross sections, which may contain large errors or uncertainties. The sensitivity coefficient shows the effect of these errors or uncertainties on the importance.The equations for calculating sensitivity coefficients of importance to one-group nuclear constants are derived using the perturbation method. Numerical values are also evaluated for some important cases for fast and thermal reactor systems.Many characteristics of the sensitivity coefficients are derived from the derived equations and numerical results. The matrix of sensitivity coefficients seems diagonally dominant. However,more » it is not always satisfied in a detailed structure. The detailed structure of the matrix and the characteristics of coefficients are given.By using the obtained sensitivity coefficients, some demonstration calculations have been performed. The effects of error and uncertainty of nuclear data and of the change of one-group cross-section input caused by fuel design changes through the neutron spectrum are investigated. These calculations show that the sensitivity coefficient is useful when evaluating error or uncertainty of nuclide importance caused by the cross-section data error or uncertainty and when checking effectiveness of fuel cell or core design change for improving neutron economy.« less

Tasseled cap transformation for HJ multispectral remote sensing data

NASA Astrophysics Data System (ADS)

Han, Ling; Han, Xiaoyong

2015-12-01

The tasseled cap transformation of remote sensing data has been widely used in environment, agriculture, forest and ecology. Tasseled cap transformation coefficients matrix of HJ multi-spectrum data has been established through Givens rotation matrix to rotate principal component transform vector to whiteness, greenness and blueness direction of ground object basing on 24 scenes year-round HJ multispectral remote sensing data. The whiteness component enhances the brightness difference of ground object, and the greenness component preserves more detailed information of vegetation change while enhances the vegetation characteristic, and the blueness component significantly enhances factory with blue plastic house roof around the town and also can enhance brightness of water. Tasseled cap transformation coefficients matrix of HJ will enhance the application effect of HJ multispectral remote sensing data in their application fields.

An indirect approach to the extensive calculation of relationship coefficients

PubMed Central

Colleau, Jean-Jacques

2002-01-01

A method was described for calculating population statistics on relationship coefficients without using corresponding individual data. It relied on the structure of the inverse of the numerator relationship matrix between individuals under investigation and ancestors. Computation times were observed on simulated populations and were compared to those incurred with a conventional direct approach. The indirect approach turned out to be very efficient for multiplying the relationship matrix corresponding to planned matings (full design) by any vector. Efficiency was generally still good or very good for calculating statistics on these simulated populations. An extreme implementation of the method is the calculation of inbreeding coefficients themselves. Relative performances of the indirect method were good except when many full-sibs during many generations existed in the population. PMID:12270102

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.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

MATIN: A Random Network Coding Based Framework for High Quality Peer-to-Peer Live Video Streaming

PubMed Central

Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

2013-01-01

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay. PMID:23940530

Unconfined lateral diffusion and an estimate of pericellular matrix viscosity revealed by measuring the mobility of gold-tagged lipids

PubMed Central

1993-01-01

Nanovid (video-enhanced) microscopy was used to determine whether lateral diffusion in the plasma membrane of colloidal gold-tagged lipid molecules is confined or is unrestricted. Confinement could be produced by domains within the plane of the plasma membrane or by filamentous barriers within the pericellular matrix. Fluorescein- phosphatidylethanolamine (F1-PE), incorporated into the plasma membranes of cultured fibroblasts, epithelial cells and keratocytes, was labeled with 30-nm colloidal gold conjugated to anti-fluorescein (anti-F1). The trajectories of the gold-labeled lipids were used to compute diffusion coefficients (DG) and to test for restricted motion. On the cell lamella, the gold-labeled lipids diffused freely in the plasma membrane. Since the gold must move through the pericellular matrix as the attached lipid diffuses in the plasma membrane, this result suggests that any extensive filamentous barriers in the pericellular matrix are at least 40 nm from the plasma membrane surface. The average diffusion coefficients ranged from 1.1 to 1.7 x 10(-9) cm2/s. These values were lower than the average diffusion coefficients (DF) (5.4 to 9.5 x 10(-9) cm2/s) obtained by FRAP. The lower DG is partially due to the pericellular matrix as demonstrated by the result that heparinase treatment of keratocytes significantly increased DG to 2.8 x 10(-9) cm2/s, but did not affect DF. Pericellular matrix viscosity was estimated from the frictional coefficients computed from DG and DF and ranged from 0.5 to 0.9 poise for untreated cells. Heparinase treatment of keratocytes decreased the apparent viscosity to approximately 0.1 poise. To evaluate the presence of domains or barriers, the trajectories and corresponding mean square displacement (MSD) plots of gold-labeled lipids were compared to the trajectories and MSD plots resulting from computer simulations of random walks within corrals. Based on these comparisons, we conclude that, if there are domains limiting the diffusion of F1-PE, most are larger than 5 microns in diameter. PMID:8416991

Thermal stability and temperature coefficients of four rare-earth-cobalt matrix magnets heated in dry air

NASA Astrophysics Data System (ADS)

Strnat, R. M. W.; Liu, S.; Strnat, K. J.

1982-03-01

Flux-loss characteristics during long-term air aging of four rare-earth-cobalt matrix magnet types were measured. Irreversible losses and reversible temperature coefficients on heating above room temperature are reported. Purely magnetic and permanent microstructure-related changes during aging were differentiated by measuring hysteresis curves before and after long-term exposure. Three commercial polymer-bonded magnets using different rare-earth-cobalt-transition metal alloys and a solder-matrix magnet with Sm(Co, Cu, Fe, Zr)7.4 were studied. They were cycled between 25 °C and maximum temperatures to 150 °C (25 ° intervals) as applicable. Aging data at 50 and 125 °C for an exposure time of 3300 h are reported. The 2-17 samples have a stability far superior to bonded 1-5. The soft metal binder imparts significantly better aging behavior on precipitation-hardened 2-17 magnet alloys above 100 °C than an epoxy resin matrix.

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.

A generalization of random matrix theory and its application to statistical physics.

PubMed

Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

2017-02-01

To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.

Scale-Dependent Fracture-Matrix Interactions And Their Impact on Radionuclide Transport - Final Report

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

Detwiler, Russell

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

Dynamic evolution of cross-correlations in the Chinese stock market.

PubMed

Ren, Fei; Zhou, Wei-Xing

2014-01-01

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.

Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

PubMed Central

Ren, Fei; Zhou, Wei-Xing

2014-01-01

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management. PMID:24867071

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

Hu, P; Wang, J; Zhong, H

Purpose: To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. Methods: 40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Waveletmore » GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) were calculated to assess the reproducibility. Results: 403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5). Conclusion: The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.« less

An Efficient Spectral Method for Ordinary Differential Equations with Rational Function Coefficients

NASA Technical Reports Server (NTRS)

Coutsias, Evangelos A.; Torres, David; Hagstrom, Thomas

1994-01-01

We present some relations that allow the efficient approximate inversion of linear differential operators with rational function coefficients. We employ expansions in terms of a large class of orthogonal polynomial families, including all the classical orthogonal polynomials. These families obey a simple three-term recurrence relation for differentiation, which implies that on an appropriately restricted domain the differentiation operator has a unique banded inverse. The inverse is an integration operator for the family, and it is simply the tridiagonal coefficient matrix for the recurrence. Since in these families convolution operators (i.e. matrix representations of multiplication by a function) are banded for polynomials, we are able to obtain a banded representation for linear differential operators with rational coefficients. This leads to a method of solution of initial or boundary value problems that, besides having an operation count that scales linearly with the order of truncation N, is computationally well conditioned. Among the applications considered is the use of rational maps for the resolution of sharp interior layers.

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Correlation of human papillomavirus status with apparent diffusion coefficient of diffusion-weighted MRI in head and neck squamous cell carcinomas.

PubMed

Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P

2016-04-01

Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.

How Habitat Change and Rainfall Affect Dung Beetle Diversity in Caatinga, a Brazilian Semi-Arid Ecosystem

PubMed Central

Liberal, Carolina Nunes; de Farias, Ângela Maria Isidro; Meiado, Marcos Vinicius; Filgueiras, Bruno K. C.; Iannuzzi, Luciana

2011-01-01

The aim of the present study was to evaluate how dung beetle communities respond to both environment and rainfall in the Caatinga, a semi-arid ecosystem in northeastern Brazil. The communities were sampled monthly from May 2006 to April 2007 using pitfall traps baited with human feces in two environments denominated “land use area” and “undisturbed area.” Abundance and species richness were compared between the two environments and two seasons (dry and wet season) using a generalized linear model with a Poisson error distribution. Diversity was compared between the two environments (land use area and undisturbed area) and seasons (dry and wet) using the Two-Way ANOVA test. Non-metric multidimensional scaling was performed on the resemblance matrix of Bray-Curtis distances (with 1000 random restarts) to determine whether disturbance affected the abundance and species composition of the dung beetle communities. Spearman's correlation coefficient was used to determine whether rainfall was correlated with abundance and species richness. A total of 1097 specimens belonging to 13 species were collected. The most abundant and frequent species was Dichotomius geminatus Arrow (Coleoptera: Scarabaeidae). The environment exerted an influence over abundance. Abundance and diversity were affected by season, with an increase in abundance at the beginning of the wet season. The correlation coefficient values were high and significant for abundance and species richness, which were both correlated to rainfall. In conclusion, the restriction of species to some environments demonstrates the need to preserve these areas in order to avoid possible local extinction. Therefore, in extremely seasonable environments, such as the Caatinga, seasonal variation strongly affects dung beetle communities. PMID:22224924

How habitat change and rainfall affect dung beetle diversity in Caatinga, a Brazilian semi-arid ecosystem.

PubMed

Liberal, Carolina Nunes; de Farias, Ângela Maria Isidro; Meiado, Marcos Vinicius; Filgueiras, Bruno K C; Iannuzzi, Luciana

2011-01-01

The aim of the present study was to evaluate how dung beetle communities respond to both environment and rainfall in the Caatinga, a semi-arid ecosystem in northeastern Brazil. The communities were sampled monthly from May 2006 to April 2007 using pitfall traps baited with human feces in two environments denominated "land use area" and "undisturbed area." Abundance and species richness were compared between the two environments and two seasons (dry and wet season) using a generalized linear model with a Poisson error distribution. Diversity was compared between the two environments (land use area and undisturbed area) and seasons (dry and wet) using the Two-Way ANOVA test. Non-metric multidimensional scaling was performed on the resemblance matrix of Bray-Curtis distances (with 1000 random restarts) to determine whether disturbance affected the abundance and species composition of the dung beetle communities. Spearman's correlation coefficient was used to determine whether rainfall was correlated with abundance and species richness. A total of 1097 specimens belonging to 13 species were collected. The most abundant and frequent species was Dichotomius geminatus Arrow (Coleoptera: Scarabaeidae). The environment exerted an influence over abundance. Abundance and diversity were affected by season, with an increase in abundance at the beginning of the wet season. The correlation coefficient values were high and significant for abundance and species richness, which were both correlated to rainfall. In conclusion, the restriction of species to some environments demonstrates the need to preserve these areas in order to avoid possible local extinction. Therefore, in extremely seasonable environments, such as the Caatinga, seasonal variation strongly affects dung beetle communities.

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc. PMID:26981409

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

Spatial and temporal variation of sources contributing to quasi-ultrafine particulate matter PM0.36 in Augsburg, Germany.

PubMed

Li, Fengxia; Schnelle-Kreis, Jürgen; Cyrys, Josef; Wolf, Kathrin; Karg, Erwin; Gu, Jianwei; Orasche, Jürgen; Abbaszade, Gülcin; Peters, Annette; Zimmermann, Ralf

2018-08-01

to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources. 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions. 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby. temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP. Copyright © 2018 Elsevier B.V. All rights reserved.

Isotropic matrix elements of the collision integral for the Boltzmann equation

NASA Astrophysics Data System (ADS)

Ender, I. A.; Bakaleinikov, L. A.; Flegontova, E. Yu.; Gerasimenko, A. B.

2017-09-01

We have proposed an algorithm for constructing matrix elements of the collision integral for the nonlinear Boltzmann equation isotropic in velocities. These matrix elements have been used to start the recurrent procedure for calculating matrix elements of the velocity-nonisotropic collision integral described in our previous publication. In addition, isotropic matrix elements are of independent interest for calculating isotropic relaxation in a number of physical kinetics problems. It has been shown that the coefficients of expansion of isotropic matrix elements in Ω integrals are connected by the recurrent relations that make it possible to construct the procedure of their sequential determination.

Comparative test on several forms of background error covariance in 3DVar

NASA Astrophysics Data System (ADS)

Shao, Aimei

2013-04-01

The background error covariance matrix (Hereinafter referred to as B matrix) plays an important role in the three-dimensional variational (3DVar) data assimilation method. However, it is difficult to get B matrix accurately because true atmospheric state is unknown. Therefore, some methods were developed to estimate B matrix (e.g. NMC method, innovation analysis method, recursive filters, and ensemble method such as EnKF). Prior to further development and application of these methods, the function of several B matrixes estimated by these methods in 3Dvar is worth studying and evaluating. For this reason, NCEP reanalysis data and forecast data are used to test the effectiveness of the several B matrixes with VAF (Huang, 1999) method. Here the NCEP analysis is treated as the truth and in this case the forecast error is known. The data from 2006 to 2007 is used as the samples to estimate B matrix and the data in 2008 is used to verify the assimilation effects. The 48h and 24h forecast valid at the same time is used to estimate B matrix with NMC method. B matrix can be represented by a correlation part (a non-diagonal matrix) and a variance part (a diagonal matrix of variances). Gaussian filter function as an approximate approach is used to represent the variation of correlation coefficients with distance in numerous 3DVar systems. On the basis of the assumption, the following several forms of B matrixes are designed and test with VAF in the comparative experiments: (1) error variance and the characteristic lengths are fixed and setted to their mean value averaged over the analysis domain; (2) similar to (1), but the mean characteristic lengths reduce to 50 percent for the height and 60 percent for the temperature of the original; (3) similar to (2), but error variance calculated directly by the historical data is space-dependent; (4) error variance and characteristic lengths are all calculated directly by the historical data; (5) B matrix is estimated directly by the historical data; (6) similar to (5), but a localization process is performed; (7) B matrix is estimated by NMC method but error variance is reduced by 1.7 times in order that the value is close to that calculated from the true forecast error samples; (8) similar to (7), but the localization similar to (6) is performed. Experimental results with the different B matrixes show that for the Gaussian-type B matrix the characteristic lengths calculated from the true error samples don't bring a good analysis results. However, the reduced characteristic lengths (about half of the original one) can lead to a good analysis. If the B matrix estimated directly from the historical data is used in 3DVar, the assimilation effect can not reach to the best. The better assimilation results are generated with the application of reduced characteristic length and localization. Even so, it hasn't obvious advantage compared with Gaussian-type B matrix with the optimal characteristic length. It implies that the Gaussian-type B matrix, widely used for operational 3DVar system, can get a good analysis with the appropriate characteristic lengths. The crucial problem is how to determine the appropriate characteristic lengths. (This work is supported by the National Natural Science Foundation of China (41275102, 40875063), and the Fundamental Research Funds for the Central Universities (lzujbky-2010-9) )

Porosimetric, Thermal and Strength Tests of Aerated and Nonaerated Concretes

NASA Astrophysics Data System (ADS)

Strzałkowski, Jarosław; Garbalińska, Halina

2017-10-01

The paper presents the results of porosimetry tests of lightweight concretes, obtained with three research methods. Impact of different porosity structures on the basic thermal and strength properties was also evaluated. Tests were performed, using the pressure gauge method on fresh concrete mixes, as well as using the mercury porosimetry test and optic RapidAir method on specimens prepared from mature composites. The study was conducted on lightweight concretes, based on expanded clay aggregate and fly ash aggregate, in two variants: with non-aerated and aerated cement matrix. In addition, two reference concretes, based on normal aggregate, were prepared, also in two variants of matrix aeration. Changes in thermal conductivity λ and volumetric specific heat cv throughout the first three months of curing of the concretes were examined. Additionally, tests for compressive strength on cubic samples were performed during the first three months of curing. It was found that the pressure gauge method, performed on a fresh mix, gave lowered values of porosity, compared to the other methods. The mercury porosity tests showed high sensitivity in evaluation of pores smaller than 30μm. Unfortunately, this technique is not suitable for analysing pores greater than 300μm. On the other hand, the optical method proves good in evaluation of large pores, greater than 300μm. The paper also presents results of correlation of individual methods of porosity testing. A consolidated graph of the pore structure, derived from both mercury and optical methods, was presented, too. For the all of six tested concretes, differential graphs of porosity, prepared with both methods, show a very broad convergence. The thermal test results indicate usefulness of aeration of the cement matrix of the composites based on lightweight aggregates for the further reduction of the thermal conductivity coefficient λ of the materials. The lowest values of the λ coefficient were obtained for the aerated concretes based of fly ash aggregate. A diminishing influence of aeration on the volumetric heat capacity cv is clearly seen. Simultaneous aeration of the matrix and use of lightweight aggregates brought about also a significant decrease in the average compressive strength fcm of the tested composites.

A tire contact solution technique

NASA Technical Reports Server (NTRS)

Tielking, J. T.

1983-01-01

An efficient method for calculating the contact boundary and interfacial pressure distribution was developed. This solution technique utilizes the discrete Fourier transform to establish an influence coefficient matrix for the portion of the pressurized tire surface that may be in the contact region. This matrix is used in a linear algebra algorithm to determine the contact boundary and the array of forces within the boundary that are necessary to hold the tire in equilibrium against a specified contact surface. The algorithm also determines the normal and tangential displacements of those points on the tire surface that are included in the influence coefficient matrix. Displacements within and outside the contact region are calculated. The solution technique is implemented with a finite-element tire model that is based on orthotropic, nonlinear shell of revolution elements which can respond to nonaxisymmetric loads. A sample contact solution is presented.

A Note on Substructuring Preconditioning for Nonconforming Finite Element Approximations of Second Order Elliptic Problems

NASA Technical Reports Server (NTRS)

Maliassov, Serguei

1996-01-01

In this paper an algebraic substructuring preconditioner is considered for nonconforming finite element approximations of second order elliptic problems in 3D domains with a piecewise constant diffusion coefficient. Using a substructuring idea and a block Gauss elimination, part of the unknowns is eliminated and the Schur complement obtained is preconditioned by a spectrally equivalent very sparse matrix. In the case of quasiuniform tetrahedral mesh an appropriate algebraic multigrid solver can be used to solve the problem with this matrix. Explicit estimates of condition numbers and implementation algorithms are established for the constructed preconditioner. It is shown that the condition number of the preconditioned matrix does not depend on either the mesh step size or the jump of the coefficient. Finally, numerical experiments are presented to illustrate the theory being developed.

Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

NASA Astrophysics Data System (ADS)

Dyar, M. D.; Carmosino, M. L.; Breves, E. A.; Ozanne, M. V.; Clegg, S. M.; Wiens, R. C.

2012-04-01

A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the response variables as possible while avoiding multicollinearity between principal components. When the selected number of principal components is projected back into the original feature space of the spectra, 6144 correlation coefficients are generated, a small fraction of which are mathematically significant to the regression. In contrast, the lasso models require only a small number (< 24) of non-zero correlation coefficients (β values) to determine the concentration of each of the ten major elements. Causality between the positively-correlated emission lines chosen by the lasso and the elemental concentration was examined. In general, the higher the lasso coefficient (β), the greater the likelihood that the selected line results from an emission of that element. Emission lines with negative β values should arise from elements that are anti-correlated with the element being predicted. For elements except Fe, Al, Ti, and P, the lasso-selected wavelength with the highest β value corresponds to the element being predicted, e.g. 559.8 nm for neutral Ca. However, the specific lines chosen by the lasso with positive β values are not always those from the element being predicted. Other wavelengths and the elements that most strongly correlate with them to predict concentration are obviously related to known geochemical correlations or close overlap of emission lines, while others must result from matrix effects. Use of the lasso technique thus directly informs our understanding of the underlying physical processes that give rise to LIBS emissions by determining which lines can best represent concentration, and which lines from other elements are causing matrix effects.

Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

PubMed

Alves, E O S; Cerqueira-Silva, C B M; Souza, A M; Santos, C A F; Lima Neto, F P; Corrêa, R X

2012-03-14

We investigated seven distance measures in a set of observations of physicochemical variables of mango (Mangifera indica) submitted to multivariate analyses (distance, projection and grouping). To estimate the distance measurements, five mango progeny (total of 25 genotypes) were analyzed, using six fruit physicochemical descriptors (fruit weight, equatorial diameter, longitudinal diameter, total soluble solids in °Brix, total titratable acidity, and pH). The distance measurements were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency. The Spearman correlation coefficients between the seven distance measurements were, except for the Mahalanobis' generalized distance (0.41 ≤ rs ≤ 0.63), high and significant (rs ≥ 0.91; P < 0.001). Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements and grouping methods gave different values for distortion (-116.5 ≤ D ≤ 74.5), cophenetic correlation (0.26 ≤ rc ≤ 0.76) and stress (-1.9 ≤ S ≤ 58.9). Choice of distance measurement and analysis methods influence the.

Brominated flame retardants in the hair and serum samples from an e-waste recycling area in southeastern China: the possibility of using hair for biomonitoring.

PubMed

Liang, Si; Xu, Feng; Tang, Weibiao; Zhang, Zheng; Zhang, Wei; Liu, Lili; Wang, Junxia; Lin, Kuangfei

2016-08-01

Hair samples and paired serum samples were collected from e-waste and urban areas in Wenling of Zhejiang Province, China. The PBDE and DBDPE concentrations in hair and serum samples from e-waste workers were significantly higher than those of non-occupational residents and urban residents. BDE209 was the dominating BFRs in hair and serum samples from the e-waste area, while DBDPE was the major BFRs from the urban area. Statistically significant correlations were observed between hair level and serum level for some substances (BDE209, DBDPE, BDE99, BDE47, BDE28, and BDE17), although the PBDE congener profiles in hair were different from those in the serum. A statistically significant positive correlation between the PBDE concentrations and the working age, as well as gender difference, was observed in e-waste workers. Different sources of PBDEs and DBDPE in three groups were identified by principal component analysis and spearman correlation coefficient. Hair is suggested to be a useful matrix for biomonitoring the PBDE exposure in humans.

Pattern recognition of the targets with help of polarization properties of the signal

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; de Rivera, Luis N.; Castellanos, Aldo B.; Popov, Anatoly V.

1999-10-01

We proposed to use the possibility of recognition of the targets on background of the scattering from the surface, weather objects with the help of polarimetric 3-cm radar. It has been investigated such polarization characteristics: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy section was less than 1 dB at ranges up to 15 km and less than 1.5 dB at ranges up to 100 km. During the experiments urban objects and 6 various ships of small displacement having the closest values of the backscattering cross-section were used. The analysis has shown: the factor of the polarization selection for anisotropy objects and weather objects had the values about 0.02-0.08 Isotropy had the values of polarimetric correlation factor for hydrometers about 0.7-0.8, for earth surface about 0.8-0.9, for sea surface - from 0.33 to 0.7. The results of the work of recognition algorithm of a class 'concrete objects', and 'metal objects' are submitted as example in the paper. The result of experiments have shown that the probability of correct recognition of the identified objects was in the limits from 0.93 to 0.97.

Rate-Dependent Behavior of the Amorphous Phase of Spider Dragline Silk

PubMed Central

Patil, Sandeep P.; Markert, Bernd; Gräter, Frauke

2014-01-01

The time-dependent stress-strain behavior of spider dragline silk was already observed decades ago, and has been attributed to the disordered sequences in silk proteins, which compose the soft amorphous matrix. However, the actual molecular origin and magnitude of internal friction within the amorphous matrix has remained inaccessible, because experimentally decomposing the mechanical response of the amorphous matrix from the embedded crystalline units is challenging. Here, we used atomistic molecular dynamics simulations to obtain friction forces for the relative sliding of peptide chains of Araneus diadematus spider silk within bundles of these chains as a representative unit of the amorphous matrix in silk fibers. We computed the friction coefficient and coefficient of viscosity of the amorphous phase to be in the order of 10−6 Ns/m and 104 Ns/m2, respectively, by extrapolating our simulation data to the viscous limit. Finally, we used a finite element method for the amorphous phase, solely based on parameters derived from molecular dynamics simulations including the newly determined coefficient of viscosity. With this model the time scales of stress relaxation, creep, and hysteresis were assessed, and found to be in line with the macroscopic time-dependent response of silk fibers. Our results suggest the amorphous phase to be the primary source of viscosity in silk and open up the avenue for finite element method studies of silk fiber mechanics including viscous effects. PMID:24896131

Improving the accuracy of central difference schemes

NASA Technical Reports Server (NTRS)

Turkel, Eli

1988-01-01

General difference approximations to the fluid dynamic equations require an artificial viscosity in order to converge to a steady state. This artificial viscosity serves two purposes. One is to suppress high frequency noise which is not damped by the central differences. The second purpose is to introduce an entropy-like condition so that shocks can be captured. These viscosities need a coefficient to measure the amount of viscosity to be added. In the standard scheme, a scalar coefficient is used based on the spectral radius of the Jacobian of the convective flux. However, this can add too much viscosity to the slower waves. Hence, it is suggested that a matrix viscosity be used. This gives an appropriate viscosity for each wave component. With this matrix valued coefficient, the central difference scheme becomes closer to upwind biased methods.

New Measurement for Correlation of Co-evolution Relationship of Subsequences in Protein.

PubMed

Gao, Hongyun; Yu, Xiaoqing; Dou, Yongchao; Wang, Jun

2015-12-01

Many computational tools have been developed to measure the protein residues co-evolution. Most of them only focus on co-evolution for pairwise residues in a protein sequence. However, number of residues participate in co-evolution might be multiple. And some co-evolved residues are clustered in several distinct regions in primary structure. Therefore, the co-evolution among the adjacent residues and the correlation between the distinct regions offer insights into function and evolution of the protein and residues. Subsequence is used to represent the adjacent multiple residues in one distinct region. In the paper, co-evolution relationship in each subsequence is represented by mutual information matrix (MIM). Then, Pearson's correlation coefficient: R value is developed to measure the similarity correlation of two MIMs. MSAs from Catalytic Data Base (Catalytic Site Atlas, CSA) are used for testing. R value characterizes a specific class of residues. In contrast to individual pairwise co-evolved residues, adjacent residues without high individual MI values are found since the co-evolved relationship among them is similar to that among another set of adjacent residues. These subsequences possess some flexibility in the composition of side chains, such as the catalyzed environment.

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

Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.

PubMed

Anthur, Aravind P; Panapakkam, Vivek; Vujicic, Vidak; Merghem, Kamel; Lelarge, Francois; Ramdane, Abderrahim; Barry, Liam P

2016-06-01

We use four-wave mixing to measure the correlation coefficient of comb tones in a quantum-dash mode-locked laser under passive and active locked regimes. We study the uncertainty in the measurement of the correlation coefficient of the proposed method.

Challenge of assessing symptoms in seriously ill intensive care unit patients: can proxy reporters help?

PubMed

Puntillo, Kathleen A; Neuhaus, John; Arai, Shoshana; Paul, Steven M; Gropper, Michael A; Cohen, Neal H; Miaskowski, Christine

2012-10-01

Determine levels of agreement among intensive care unit patients and their family members, nurses, and physicians (proxies) regarding patients' symptoms and compare levels of mean intensity (i.e., the magnitude of a symptom sensation) and distress (i.e., the degree of emotionality that a symptom engenders) of symptoms among patients and proxy reporters. Prospective study of proxy reporters of symptoms in seriously ill patients. Two intensive care units in a tertiary medical center in the Western United States. Two hundred and forty-five intensive care unit patients, 243 family members, 103 nurses, and 92 physicians. None. On the basis of the magnitude of intraclass correlation coefficients, where coefficients from .35 to .78 are considered to be appropriately robust, correlation coefficients between patients' and family members' ratings met this criterion (≥.35) for intensity in six of ten symptoms. No intensity ratings between patients and nurses had intraclass correlation coefficients >.32. Three symptoms had intensity correlation coefficients of ≥.36 between patients' and physicians' ratings. Correlation coefficients between patients and family members were >.40 for five symptom-distress ratings. No symptoms had distress correlation coefficients of ≥.28 between patients' and nurses' ratings. Two symptoms had symptom-distress correlation coefficients between patients' and physicians' ratings at >.39. Family members, nurses, and physicians reported higher symptom-intensity scores than patients did for 80%, 60%, and 60% of the symptoms, respectively. Family members, nurses, and physicians reported higher symptom-distress scores than patients did for 90%, 70%, and 80% of the symptoms, respectively. Patient-family intraclass correlation coefficients were sufficiently close for us to consider using family members to help assess intensive care unit patients' symptoms. Relatively low intraclass correlation coefficients between intensive care unit clinicians' and patients' symptom ratings indicate that some proxy raters overestimate whereas others underestimate patients' symptoms. Proxy overestimation of patients' symptom scores warrants further study because this may influence decisions about treating patients' symptoms.

Application of Temperature Sensitivities During Iterative Strain-Gage Balance Calibration Analysis

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2011-01-01

A new method is discussed that may be used to correct wind tunnel strain-gage balance load predictions for the influence of residual temperature effects at the location of the strain-gages. The method was designed for the iterative analysis technique that is used in the aerospace testing community to predict balance loads from strain-gage outputs during a wind tunnel test. The new method implicitly applies temperature corrections to the gage outputs during the load iteration process. Therefore, it can use uncorrected gage outputs directly as input for the load calculations. The new method is applied in several steps. First, balance calibration data is analyzed in the usual manner assuming that the balance temperature was kept constant during the calibration. Then, the temperature difference relative to the calibration temperature is introduced as a new independent variable for each strain--gage output. Therefore, sensors must exist near the strain--gages so that the required temperature differences can be measured during the wind tunnel test. In addition, the format of the regression coefficient matrix needs to be extended so that it can support the new independent variables. In the next step, the extended regression coefficient matrix of the original calibration data is modified by using the manufacturer specified temperature sensitivity of each strain--gage as the regression coefficient of the corresponding temperature difference variable. Finally, the modified regression coefficient matrix is converted to a data reduction matrix that the iterative analysis technique needs for the calculation of balance loads. Original calibration data and modified check load data of NASA's MC60D balance are used to illustrate the new method.

Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.

PubMed

Rastegar, Seyed Omid; Gu, Tingyue

2017-03-24

In this work, a new correlation for the axial dispersion coefficient was obtained using experimental data in the literature for axial dispersion in fixed-bed columns packed with particles. The Chung and Wen correlation, the De Ligny correlation are two popular empirical correlations. However, the former lacks the molecular diffusion term and the latter does not consider bed voidage. The new axial dispersion coefficient correlation in this work was based on additional experimental data in the literature by considering both molecular diffusion and bed voidage. It is more comprehensive and accurate. The Peclet number correlation from the new axial dispersion coefficient correlation on the average leads to 12% lower Peclet number values compared to the values from the Chung and Wen correlation, and in many cases much smaller than those from the De Ligny correlation. Copyright © 2017 Elsevier B.V. All rights reserved.

Asymmetric correlation matrices: an analysis of financial data

NASA Astrophysics Data System (ADS)

Livan, G.; Rebecchi, L.

2012-06-01

We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.

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

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

A Markov model for blind image separation by a mean-field EM algorithm.

PubMed

Tonazzini, Anna; Bedini, Luigi; Salerno, Emanuele

2006-02-01

This paper deals with blind separation of images from noisy linear mixtures with unknown coefficients, formulated as a Bayesian estimation problem. This is a flexible framework, where any kind of prior knowledge about the source images and the mixing matrix can be accounted for. In particular, we describe local correlation within the individual images through the use of Markov random field (MRF) image models. These are naturally suited to express the joint pdf of the sources in a factorized form, so that the statistical independence requirements of most independent component analysis approaches to blind source separation are retained. Our model also includes edge variables to preserve intensity discontinuities. MRF models have been proved to be very efficient in many visual reconstruction problems, such as blind image restoration, and allow separation and edge detection to be performed simultaneously. We propose an expectation-maximization algorithm with the mean field approximation to derive a procedure for estimating the mixing matrix, the sources, and their edge maps. We tested this procedure on both synthetic and real images, in the fully blind case (i.e., no prior information on mixing is exploited) and found that a source model accounting for local autocorrelation is able to increase robustness against noise, even space variant. Furthermore, when the model closely fits the source characteristics, independence is no longer a strict requirement, and cross-correlated sources can be separated, as well.

Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival

PubMed Central

Pérez-Beteta, Julián; Luque, Belén; Arregui, Elena; Calvo, Manuel; Borrás, José M; López, Carlos; Martino, Juan; Velasquez, Carlos; Asenjo, Beatriz; Benavides, Manuel; Herruzo, Ismael; Martínez-González, Alicia; Pérez-Romasanta, Luis; Arana, Estanislao; Pérez-García, Víctor M

2016-01-01

Objective: The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. Methods: 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan–Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman's correlation coefficient. Results: Kaplan–Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Conclusion: Heterogeneity measures computed on the post-contrast pre-operative T1 weighted MR images of patients with GBM are predictors of survival. Advances in knowledge: Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour. PMID:27319577

Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival.

PubMed

Molina, David; Pérez-Beteta, Julián; Luque, Belén; Arregui, Elena; Calvo, Manuel; Borrás, José M; López, Carlos; Martino, Juan; Velasquez, Carlos; Asenjo, Beatriz; Benavides, Manuel; Herruzo, Ismael; Martínez-González, Alicia; Pérez-Romasanta, Luis; Arana, Estanislao; Pérez-García, Víctor M

2016-07-04

The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T 1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan-Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman's correlation coefficient. Kaplan-Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Heterogeneity measures computed on the post-contrast pre-operative T 1 weighted MR images of patients with GBM are predictors of survival. Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour.

Predictive model to describe water migration in cellular solid foods during storage.

PubMed

Voogt, Juliën A; Hirte, Anita; Meinders, Marcel B J

2011-11-01

Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Water migration in cellular solid foods involves migration through both the air cells and the solid matrix. For systems in which the water migration distance is large compared with the cell wall thickness of the solid matrix, the overall water flux through the system is dominated by the flux through the air. For these systems, water migration can be approximated well by a Fickian diffusion model. The effective diffusion coefficient can be expressed in terms of the material properties of the solid matrix (i.e. the density, sorption isotherm and diffusion coefficient of water in the solid matrix) and the morphological properties of the cellular structure (i.e. water vapour permeability and volume fraction of the solid matrix). The water vapour permeability is estimated from finite element method modelling using a simplified model for the cellular structure. It is shown that experimentally observed dynamical water profiles of bread rolls that differ in crust permeability are predicted well by the Fickian diffusion model. Copyright © 2011 Society of Chemical Industry.

ANALYSIS OF A CLASSIFICATION ERROR MATRIX USING CATEGORICAL DATA TECHNIQUES.

USGS Publications Warehouse

Rosenfield, George H.; Fitzpatrick-Lins, Katherine

1984-01-01

Summary form only given. A classification error matrix typically contains tabulation results of an accuracy evaluation of a thematic classification, such as that of a land use and land cover map. The diagonal elements of the matrix represent the counts corrected, and the usual designation of classification accuracy has been the total percent correct. The nondiagonal elements of the matrix have usually been neglected. The classification error matrix is known in statistical terms as a contingency table of categorical data. As an example, an application of these methodologies to a problem of remotely sensed data concerning two photointerpreters and four categories of classification indicated that there is no significant difference in the interpretation between the two photointerpreters, and that there are significant differences among the interpreted category classifications. However, two categories, oak and cottonwood, are not separable in classification in this experiment at the 0. 51 percent probability. A coefficient of agreement is determined for the interpreted map as a whole, and individually for each of the interpreted categories. A conditional coefficient of agreement for the individual categories is compared to other methods for expressing category accuracy which have already been presented in the remote sensing literature.

Quantitative Analysis of Clopidogrel Bisulphate and Aspirin by First Derivative Spectrophotometric Method in Tablets

PubMed Central

Game, Madhuri D.; Gabhane, K. B.; Sakarkar, D. M.

2010-01-01

A simple, accurate and precise spectrophotometric method has been developed for simultaneous estimation of clopidogrel bisulphate and aspirin by employing first order derivative zero crossing method. The first order derivative absorption at 232.5 nm (zero cross point of aspirin) was used for clopidogrel bisulphate and 211.3 nm (zero cross point of clopidogrel bisulphate) for aspirin.Both the drugs obeyed linearity in the concentration range of 5.0 μg/ml to 25.0 μg/ml (correlation coefficient r2<1). No interference was found between both determined constituents and those of matrix. The method was validated statistically and recovery studies were carried out to confirm the accuracy of the method. PMID:21969765

Dispersion of carbon nanotubes in melt compounded polypropylene based composites investigated by THz spectroscopy.

PubMed

Casini, R; Papari, G; Andreone, A; Marrazzo, D; Patti, A; Russo, P

2015-07-13

We investigate the use of Terahertz (THz) Time Domain Spectroscopy (TDS) as a tool for the measurement of the index dispersion of multi-walled carbon nanotubes (MWCNT) in polypropylene (PP) based composites. Samples containing 0.5% by volume concentration of non-functionalized and functionalized carbon nanotubes are prepared by melt compounding technology. Results indicate that the THz response of the investigated nanocomposites is strongly dependent on the kind of nanotube functionalization, which in turn impacts on the level of dispersion inside the polymer matrix. We show that specific dielectric parameters such as the refractive index and the absorption coefficient measured by THz spectroscopy can be both correlated to the index of dispersion as estimated using conventional optical microscopy.

Bayesian and Phylogenic Approaches for Studying Relationships among Table Olive Cultivars.

PubMed

Ben Ayed, Rayda; Ennouri, Karim; Ben Amar, Fathi; Moreau, Fabienne; Triki, Mohamed Ali; Rebai, Ahmed

2017-08-01

To enhance table olive tree authentication, relationship, and productivity, we consider the analysis of 18 worldwide table olive cultivars (Olea europaea L.) based on morphological, biological, and physicochemical markers analyzed by bioinformatic and biostatistic tools. Accordingly, we assess the relationships between the studied varieties, on the one hand, and the potential productivity-quantitative parameter links on the other hand. The bioinformatic analysis based on the graphical representation of the matrix of Euclidean distances, the principal components analysis, unweighted pair group method with arithmetic mean, and principal coordinate analysis (PCoA) revealed three major clusters which were not correlated with the geographic origin. The statistical analysis based on Kendall's and Spearman correlation coefficients suggests two highly significant associations with both fruit color and pollinization and the productivity character. These results are confirmed by the multiple linear regression prediction models. In fact, based on the coefficient of determination (R 2 ) value, the best model demonstrated the power of the pollinization on the tree productivity (R 2  = 0.846). Moreover, the derived directed acyclic graph showed that only two direct influences are detected: effect of tolerance on fruit and stone symmetry on side and effect of tolerance on stone form and oil content on the other side. This work provides better understanding of the diversity available in worldwide table olive cultivars and supplies an important contribution for olive breeding and authenticity.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

Determination of benzothiazole and benzotriazole derivates in tire and clothing textile samples by high performance liquid chromatography-electrospray ionization tandem mass spectrometry.

PubMed

Avagyan, Rozanna; Sadiktsis, Ioannis; Thorsén, Gunnar; Östman, Conny; Westerholm, Roger

2013-09-13

A high performance liquid chromatography-tandem mass spectrometry method utilizing electrospray ionization in positive and negative mode has been developed for the separation and detection of benzothiazole and benzotriazole derivates. Ultra-sonication assisted solvent extraction of these compounds has also been developed and the overall method demonstrated on a selected clothing textile and an automobile tire sample. Matrix effects and extraction recoveries, as well as linearity and limits of detection have been evaluated. The calibration curves spanned over more than two orders of magnitude with coefficients of correlation R(2)>0.99 and the limits of detection and the limits of quantification were in the range 1.7-58pg injected and 18-140pg/g, respectively. The extraction recoveries ranged between 69% and 102% and the matrix effects between 75% and 101%. Benzothiazole and benzotriazole derivates were determined in the textile sample and benzothiazole derivatives determined in the tire sample with good analytical performance. Copyright © 2013 Elsevier B.V. All rights reserved.

Aspects regarding the correlation between the physical-mechanical and tribological characteristics of composites materials reinforced with carbon fibers

NASA Astrophysics Data System (ADS)

Caliman, R.

2017-08-01

The purpose of this paper is to highlight a number of factors that influence the physical-mechanical and tribological characteristics of sintered composite materials. Such factors are grouped generally in two categories: technological parameters (pressure compacting, sintering temperature, sintering duration, heat treatment) and the receipt of sintered composite materials. In this paper is presented a program of experiments developed both in composite materials sintered polymer matrix (non-metallic) and in the metal matrix (eg., Al) which was prepared in advance a methodology original production and research for this particular type of materials. The experiments have focused development and testing of a number of 14 polymer composite and 5 composite sintered Al base, in both situations armed with carbon fiber in various forms. Tribological tests followed the establishment of the coefficient of friction and wear rate of the sliding speed at the constant values (v = 7.2 mm/s) and the normal load (N = 8 daN) and for different orientations of the fibers to the direction of sliding: normal (N type), parallel (P) and antiparallel-perpendicular (AP type).

Osteogenic potential of mesenchymal cells embedded in the provisional matrix after a 6-week healing period in augmented and non-augmented extraction sockets: an immunohistochemical prospective pilot study in humans.

PubMed

Heberer, Susanne; Wustlich, Alexander; Lage, Hermann; Nelson, John J; Nelson, Katja

2012-01-01

The aim of the present clinical study was the evaluation of the osteogenic potential of mesenchymal cells embedded in the provisional matrix of non-augmented and with Bio-Oss collagen-augmented human extraction sockets after 6 weeks of healing time. Twenty-five patients with 47 extraction sites participated in the present study. After tooth removal, the extraction sockets were augmented with Bio-Oss collagen or not augmented. At implant placement, bone biopsies of the extraction sockets were obtained. The immunohistochemical analysis of the osteogenic potential of the mesenchymal cells in the provisional matrix was performed using three monoclonal antibodies: core-binding factor α1 (Cbfa1)/runt-related protein (Runx)2, osteonectin (OSN/secreted protein acidic and rich in cyst [SPARC]) and osteocalcin (OC). The statistical analysis was performed using two-factorial analysis for repeated measures, Mann-Whitney U-test and Spearman's rank-order correlation coefficient. Of 47 extraction sockets examined, 17 sockets demonstrated an almost complete ossification. Hence, the provisional matrix of the 30 remaining extraction sockets (21 non-augmented, 9 augmented) was immunohistochemically investigated. No evidence of acute or chronic inflammation was noted in any of the specimens. In the provisional matrix of the non-grafted socket, the median amount of Cbfa1/Runx2-positive cells was 72.3%, of OSN (SPARC) 66.9% and of OC 23.4%, whereas in the grafted sockets the median rate of immunopositive cells staining with Cbfa1/Runx2 was 73.3%, of OSN (SPARC) 61.4% and of OC 20.1%. There was no significant difference in the proportion of positive cells expressed by Cbfa1/Runx2, OSN/SPARC and OC between the grafted and non-grafted socket. Furthermore, the cell density did not correlate to the quantity of stained cells independent of the used proteins. After a 6-week healing period, the provisional matrix was demonstrated to have a high proportion of cells displaying a maturation of mature osteoprogenitor cells to osteoblasts. The grafting procedure did not influence the quantity of osteogenic cells in the extraction socket. © 2011 John Wiley & Sons A/S.

Covariance, correlation matrix, and the multiscale community structure of networks.

PubMed

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Correlation and interaction visualization of altmetric indicators extracted from scholarly social network activities: dimensions and structure.

PubMed

Liu, Chun Li; Xu, Yue Quan; Wu, Hui; Chen, Si Si; Guo, Ji Jun

2013-11-25

Citation counts for peer-reviewed articles and the impact factor of journals have long been indicators of article importance or quality. In the Web 2.0 era, growing numbers of scholars are using scholarly social network tools to communicate scientific ideas with colleagues, thereby making traditional indicators less sufficient, immediate, and comprehensive. In these new situations, the altmetric indicators offer alternative measures that reflect the multidimensional nature of scholarly impact in an immediate, open, and individualized way. In this direction of research, some studies have demonstrated the correlation between altmetrics and traditional metrics with different samples. However, up to now, there has been relatively little research done on the dimension and interaction structure of altmetrics. Our goal was to reveal the number of dimensions that altmetric indicators should be divided into and the structure in which altmetric indicators interact with each other. Because an article-level metrics dataset is collected from scholarly social media and open access platforms, it is one of the most robust samples available to study altmetric indicators. Therefore, we downloaded a large dataset containing activity data in 20 types of metrics present in 33,128 academic articles from the application programming interface website. First, we analyzed the correlation among altmetric indicators using Spearman rank correlation. Second, we visualized the multiple correlation coefficient matrixes with graduated colors. Third, inputting the correlation matrix, we drew an MDS diagram to demonstrate the dimension for altmetric indicators. For correlation structure, we used a social network map to represent the social relationships and the strength of relations. We found that the distribution of altmetric indicators is significantly non-normal and positively skewed. The distribution of downloads and page views follows the Pareto law. Moreover, we found that the Spearman coefficients from 91.58% of the pairs of variables indicate statistical significance at the .01 level. The non-metric MDS map divided the 20 altmetric indicators into three clusters: traditional metrics, active altmetrics, and inactive altmetrics. The social network diagram showed two subgroups that are tied to each other but not to other groups, thus indicating an intersection between altmetrics and traditional metric indicators. Altmetrics complement, and most correlate significantly with, traditional measures. Therefore, in future evaluations of the social impact of articles, we should consider not only traditional metrics but also active altmetrics. There may also be a transfer phenomenon for the social impact of academic articles. The impact transfer path has transfer, or intermediate, stations that transport and accelerate article social impact from active altmetrics to traditional metrics and vice versa. This discovery will be helpful to explain the impact transfer mechanism of articles in the Web 2.0 era. Hence, altmetrics are in fact superior to traditional filters for assessing scholarly impact in multiple dimensions and in terms of social structure.

Deriving the Intrahepatic Arteriovenous Shunt Rate from CT Images and Biochemical Data Instead of from Arterial Perfusion Scintigraphy in Hepatic Arterial Infusion Chemotherapy

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

Ozaki, Toshiro, E-mail: ganronbun@amail.plala.or.jp; Seki, Hiroshi; Shiina, Makoto

2009-09-15

The purpose of the present study was to elucidate a method for predicting the intrahepatic arteriovenous shunt rate from computed tomography (CT) images and biochemical data, instead of from arterial perfusion scintigraphy, because adverse exacerbated systemic effects may be induced in cases where a high shunt rate exists. CT and arterial perfusion scintigraphy were performed in patients with liver metastases from gastric or colorectal cancer. Biochemical data and tumor marker levels of 33 enrolled patients were measured. The results were statistically verified by multiple regression analysis. The total metastatic hepatic tumor volume (V{sub metastasized}), residual hepatic parenchyma volume (V{sub residual};more » calculated from CT images), and biochemical data were treated as independent variables; the intrahepatic arteriovenous (IHAV) shunt rate (calculated from scintigraphy) was treated as a dependent variable. The IHAV shunt rate was 15.1 {+-} 11.9%. Based on the correlation matrixes, the best correlation coefficient of 0.84 was established between the IHAV shunt rate and V{sub metastasized} (p < 0.01). In the multiple regression analysis with the IHAV shunt rate as the dependent variable, the coefficient of determination (R{sup 2}) was 0.75, which was significant at the 0.1% level with two significant independent variables (V{sub metastasized} and V{sub residual}). The standardized regression coefficients ({beta}) of V{sub metastasized} and V{sub residual} were significant at the 0.1 and 5% levels, respectively. Based on this result, we can obtain a predicted value of IHAV shunt rate (p < 0.001) using CT images. When a high shunt rate was predicted, beneficial and consistent clinical monitoring can be initiated in, for example, hepatic arterial infusion chemotherapy.« less

Mapping the neuropsychological profile of temporal lobe epilepsy using cognitive network topology and graph theory.

PubMed

Kellermann, Tanja S; Bonilha, Leonardo; Eskandari, Ramin; Garcia-Ramos, Camille; Lin, Jack J; Hermann, Bruce P

2016-10-01

Normal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC. Neuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed. The community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE. Adults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

Molecular dimensions and surface diffusion assisted mechanically robust slippery perfluoropolyether impregnated mesoporous alumina interfaces

NASA Astrophysics Data System (ADS)

Rowthu, Sriharitha; Balic, Edin E.; Hoffmann, Patrik

2017-12-01

Accomplishing mechanically robust omniphobic surfaces is a long-existing challenge, and can potentially find applications in bioengineering, tribology and paint industries. Slippery liquid impregnated mesoporous α-Al2O3 interfaces are achieved with water, alkanes, water based and oil based high viscosity acrylic paints. Incredibly high abrasion-resistance (wear coefficients ≤10-8 mm3 N-1 m-1) and ultra-low friction coefficients (≥0.025) are attained, attributing to the hard alumina matrix and continuous replenishment of perfluoropolyether aided by capillarity and surface diffusion processes. A variety of impregnating liquids employed suggest that large molecules, faster surface diffusion and lowest evaporation rate generate the rare combination of high wear-resistance and omniphobicity. It is noteworthy that these novel liquid impregnated Al2O3 composites exhibit outstanding load bearing capacity up to 350 MPa; three orders of magnitude higher than achievable by the state of the art omniphobic surfaces. Further, our developed thermodynamic calculations suggest that the relative thermodynamic stability of liquid impregnated composites is linearly proportional to the spreading coefficient (S) of the impregnating liquid with the matrix material and is an important tool for the selection of an appropriate matrix material for a given liquid.

Automatic numerical evaluation of vacancy-mediated transport for arbitrary crystals: Onsager coefficients in the dilute limit using a Green function approach

NASA Astrophysics Data System (ADS)

Trinkle, Dallas R.

2017-10-01

A general solution for vacancy-mediated diffusion in the dilute-vacancy/dilute-solute limit for arbitrary crystal structures is derived from the master equation. A general numerical approach to the vacancy lattice Green function reduces to the sum of a few analytic functions and numerical integration of a smooth function over the Brillouin zone for arbitrary crystals. The Dyson equation solves for the Green function in the presence of a solute with arbitrary but finite interaction range to compute the transport coefficients accurately, efficiently and automatically, including cases with very large differences in solute-vacancy exchange rates. The methodology takes advantage of the space group symmetry of a crystal to reduce the complexity of the matrix inversion in the Dyson equation. An open-source implementation of the algorithm is available, and numerical results are presented for the convergence of the integration error of the bare vacancy Green function, and tracer correlation factors for a variety of crystals including wurtzite (hexagonal diamond) and garnet.

Fish skin as a model membrane: structure and characteristics.

PubMed

Konrádsdóttir, Fífa; Loftsson, Thorsteinn; Sigfússon, Sigurdur Dadi

2009-01-01

Synthetic and cell-based membranes are frequently used during drug formulation development for the assessment of drug availability. However, most of the currently used membranes do not mimic mucosal membranes well, especially the aqueous mucous layer of the membranes. In this study we evaluated catfish (Anarichas lupus L) skin as a model membrane. Permeation of hydrocortisone, lidocaine hydrochloride, benzocaine, diethylstilbestrol, naproxen, picric acid and sodium nitrate through skin from a freshly caught catfish was determined in Franz diffusion cells. Both lipophilic and hydrophilic molecules permeate through catfish skin via hydrated channels or aqueous pores. No correlation was observed between the octanol/water partition coefficient of the permeating molecules and their permeability coefficient through the skin. Permeation through catfish skin was found to be diffusion controlled. The results suggest that permeation through the fish skin proceeds via a diffusion-controlled process, a process that is similar to drug permeation through the aqueous mucous layer of a mucosal membrane. In addition, the fish skin, with its collagen matrix structure, appears to possess similar properties to the eye sclera.

Development and Preliminary Validation of the Coma Arousal Communication Scale.

PubMed

Garin, Julie; Reina, Margot; DeiCas, Paula; Rousseaux, Marc

To develop a Coma Arousal Communication Scale and perform preliminary validation. A group of experts developed a questionnaire to assess communication between patients emerging from coma and caregiver (participation, communication modes, and themes) and the strategies used to facilitate communication. To assess the scale's psychometric characteristics, it was presented to the caregivers of 40 inpatients admitted to 5 coma units and (to obtain reference data) to 29 control participants. The Coma Arousal Communication Scale displayed good intra- and interrater reliability as judged by intraclass correlation coefficients (between 0.76 and 0.98) and Bland and Altman plots. Cohen κ coefficient revealed moderate to almost perfect levels of agreement for most individual items and slight levels for a few items dealing with compensatory strategies. We observed good internal consistency, relations with the Wessex Head Injury Matrix, and sensitivity to change for patients who had sustained brain injury in the previous 6 months. The Coma Arousal Communication Scale provides accurate information about communication skills of individuals emerging from coma. However, some compensatory strategies adopted by caregivers are difficult to characterize.

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

NASA Technical Reports Server (NTRS)

Frenkiel, Francois N.

1958-01-01

In reading the publications on turbulence of different authors, one often runs the risk of confusing the various correlation coefficients and turbulence spectra. We have made a point of defining, by appropriate concepts, the differences which exist between these functions. Besides, we introduce in the symbols a few new characteristics of turbulence. In the first chapter, we study some relations between the correlation coefficients and the different turbulence spectra. Certain relations are given by means of demonstrations which could be called intuitive rather than mathematical. In this way we demonstrate that the correlation coefficients between the simultaneous turbulent velocities at two points are identical, whether studied in Lagrange's or in Euler's systems. We then consider new spectra of turbulence, obtained by study of the simultaneous velocities along a straight line of given direction. We determine some relations between these spectra and the correlation coefficients. Examining the relation between the spectrum of the turbulence measured at a fixed point and the longitudinal-correlation curve given by G. I. Taylor, we find that this equation is exact only when the coefficient is very small.

What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation.

PubMed

Chebib, Jobran; Guillaume, Frédéric

2017-10-01

Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co) variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient.

PubMed

Adler, Jeremy; Parmryd, Ingela

2010-08-01

The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2018-04-01

Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. Associations between 18 F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [-0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between 18 F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV max and KI 67 was 0.28 (95% CI = [-0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K trans and KI 67 was -0.68 (95% CI = [-0.91; -0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was -0.61 (95% CI = [-0.84; -0.38]). In 2 studies (117 patients), relationships between 18 F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [-0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was -0.53 (95% CI = [-0.74; -0.32]). Associations between 18 F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [-0.20; 1.08]). ADC may predict cell count and proliferation activity, and SUV max may predict expression of HIF-1α in HNSCC. SUV max cannot be used as surrogate marker for expression of KI 67 and p53. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Banana fluxes in the plateau regime for a nonaxisymmetrically confined plasma

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

Balescu, R.; Fantechi, S.

1990-09-01

The banana (or banana-plateau) fluxes, related to the generalized stresses {l angle}{bold B}{center dot}{del}{center dot}{pi}{sup {alpha}({ital n})}{r angle}, {l angle}{bold B}{sub {ital T}}{center dot}{del}{center dot}{pi}{sup {alpha}({ital n})}{r angle} have been determined in the plateau regime, for a plasma confined by a toroidal magnetic field of arbitrary geometry. The complete set of transport coefficients for both the parallel'' (ambipolar) and toroidal'' (nonambipolar) banana fluxes was obtained in the 13-moment (13M) approximation, going beyond the previously known expressions in the nonaxisymmetric case. The main emphasis is laid on the structure of the transport matrix and of its coefficients. It is shown thatmore » the Onsager symmetry of this matrix partly breaks down (for the mixed electron--ion coefficients) in a nonaxisymmetrically confined plasma.« less

High-precision Predictions for the Acoustic Scale in the Nonlinear Regime

NASA Astrophysics Data System (ADS)

Seo, Hee-Jong; Eckel, Jonathan; Eisenstein, Daniel J.; Mehta, Kushal; Metchnik, Marc; Padmanabhan, Nikhil; Pinto, Phillip; Takahashi, Ryuichi; White, Martin; Xu, Xiaoying

2010-09-01

We measure shifts of the acoustic scale due to nonlinear growth and redshift distortions to a high precision using a very large volume of high-force-resolution simulations. We compare results from various sets of simulations that differ in their force, volume, and mass resolution. We find a consistency within 1.5σ for shift values from different simulations and derive shift α(z) - 1 = (0.300 ± 0.015) %[D(z)/D(0)]2 using our fiducial set. We find a strong correlation with a non-unity slope between shifts in real space and in redshift space and a weak correlation between the initial redshift and low redshift. Density-field reconstruction not only removes the mean shifts and reduces errors on the mean, but also tightens the correlations. After reconstruction, we recover a slope of near unity for the correlation between the real and redshift space and restore a strong correlation between the initial and the low redshifts. We derive propagators and mode-coupling terms from our N-body simulations and compare with the Zel'dovich approximation and the shifts measured from the χ2 fitting, respectively. We interpret the propagator and the mode-coupling term of a nonlinear density field in the context of an average and a dispersion of its complex Fourier coefficients relative to those of the linear density field; from these two terms, we derive a signal-to-noise ratio of the acoustic peak measurement. We attempt to improve our reconstruction method by implementing 2LPT and iterative operations, but we obtain little improvement. The Fisher matrix estimates of uncertainty in the acoustic scale is tested using 5000 h -3 Gpc3 of cosmological Particle-Mesh simulations from Takahashi et al. At an expected sample variance level of 1%, the agreement between the Fisher matrix estimates based on Seo and Eisenstein and the N-body results is better than 10%.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Ex-vivo UV autofluorescence imaging and fluorescence spectroscopy of atherosclerotic pathology in human aorta

NASA Astrophysics Data System (ADS)

Lewis, William; Williams, Maura; Franco, Walfre

2017-02-01

The aim of our study was to identify fluorescence excitation-emission pairs correlated with atherosclerotic pathology in ex-vivo human aorta. Wide-field images of atherosclerotic human aorta were captured using UV and visible excitation and emission wavelength pairs of several known fluorophores to investigate correspondence with gross pathologic features. Fluorescence spectroscopy and histology were performed on 21 aortic samples. A matrix of Pearson correlation coefficients were determined for the relationship between relevant histologic features and the intensity of emission for 427 wavelength pairs. A multiple linear regression analysis indicated that elastin (370/460 nm) and tryptophan (290/340 nm) fluorescence predicted 58% of the variance in intima thickness (R-squared = 0.588, F(2,18) = 12.8, p=.0003), and 48% of the variance in media thickness (R-squared = 0.483, F(2,18) = 8.42, p=.002), suggesting that endogenous fluorescence intensity at these wavelengths can be utilized for improved pathologic characterization of atherosclerotic plaques.

Cross-cultural adaptation, validation and reliability of the brazilian version of the Richmond Compulsive Buying Scale.

PubMed

Leite, Priscilla; Rangé, Bernard; Kukar-Kiney, Monika; Ridgway, Nancy; Monroe, Kent; Ribas Junior, Rodolfo; Landeira Fernandez, J; Nardi, Antonio Egidio; Silva, Adriana

2013-03-01

To present the process of transcultural adaptation of the Richmond Compulsive Buying Scale to Brazilian Portuguese. For the semantic adaptation step, the scale was translated to Portuguese and then back-translated to English by two professional translators and one psychologist, without any communication between them. The scale was then applied to 20 participants from the general population for language adjustments. For the construct validation step, an exploratory factor analysis was performed, using the scree plot test, principal component analysis for factor extraction, and Varimax rotation. For convergent validity, the correlation matrix was analyzed through Pearson's coefficient. The scale showed easy applicability, satisfactory internal consistency (Cronbach's alpha=.87), and a high correlation with other rating scales for compulsive buying disorder, indicating that it is suitable to be used in the assessment and diagnosis of compulsive buying disorder, as it presents psychometric validity. The Brazilian Portuguese version of the Richmond Compulsive Buying Scale has good validity and reliability.

Structure-activity relationships between sterols and their thermal stability in oil matrix.

PubMed

Hu, Yinzhou; Xu, Junli; Huang, Weisu; Zhao, Yajing; Li, Maiquan; Wang, Mengmeng; Zheng, Lufei; Lu, Baiyi

2018-08-30

Structure-activity relationships between 20 sterols and their thermal stabilities were studied in a model oil system. All sterol degradations were found to be consistent with a first-order kinetic model with determination of coefficient (R 2 ) higher than 0.9444. The number of double bonds in the sterol structure was negatively correlated with the thermal stability of sterol, whereas the length of the branch chain was positively correlated with the thermal stability of sterol. A quantitative structure-activity relationship (QSAR) model to predict thermal stability of sterol was developed by using partial least squares regression (PLSR) combined with genetic algorithm (GA). A regression model was built with R 2 of 0.806. Almost all sterol degradation constants can be predicted accurately with R 2 of cross-validation equals to 0.680. Four important variables were selected in optimal QSAR model and the selected variables were observed to be related with information indices, RDF descriptors, and 3D-MoRSE descriptors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reduction of matrix effects and improvement of sensitivity during determination of two chloridazon degradation products in aqueous matrices by using UPLC-ESI-MS/MS.

PubMed

Kowal, Sebastian; Balsaa, Peter; Werres, Friedrich; Schmidt, Torsten C

2012-06-01

The development and validation of a sensitive and reliable detection method for the determination of two polar degradation products, desphenyl-chloridazon (DPC) and methyl-desphenyl-chloridazon (MDPC) in surface water, ground water and drinking water is presented. The method is based on direct large volume injection ultra-performance liquid chromatography electrospray tandem mass spectrometry. This simple but powerful analytical method for polar substances in the aquatic environment is usually hampered by varying matrix effects, depending on the nature of different water bodies. For the two examined degradation products, the matrix effects are particularly strong compared with other polar degradation products of pesticides. Therefore, matrix effects were studied thoroughly with the aim of minimising them and improving sensitivity during determination by postcolumn addition of ammonia solution as a modifier. An internal standard was used in order to compensate for remaining matrix effects. The calibration curve shows very good coefficients of correlation (0.9994 for DPC and 0.9999 for MDPC). Intraday precision values were lower than 5 % for DPC, 3 % for MDPC and the limits of detection were 10 ng/L for both substances. The method was successfully used in a national round robin test with a deviation between 3 and 8 % from target values. Finally, about 1,000 samples from different water bodies have been examined with this method in the Rhine and Ruhr region of North-Rhine-Westphalia (Germany) and in the European Union. Approximately 76 % of analysed samples contained measurable amounts of DPC at concentrations up to 8 μg/L while 53 % of the samples showed MDPC concentrations up to 2.3 μg/L.

NASA supercritical airfoils: A matrix of family-related airfoils

NASA Technical Reports Server (NTRS)

Harris, Charles D.

1990-01-01

The NASA supercritical airfoil development program is summarized in a chronological fashion. Some of the airfoil design guidelines are discussed, and coordinates of a matrix of family related supercritical airfoils ranging from thicknesses of 2 to 18 percent and over a design lift coefficient range from 0 to 1.0 are presented.

Multipole expansions and Fock symmetry of the hydrogen atom

NASA Astrophysics Data System (ADS)

Meremianin, A. V.; Rost, J.-M.

2006-10-01

The main difficulty in utilizing the O(4) symmetry of the hydrogen atom in practical calculations is the dependence of the Fock stereographic projection on energy. This is due to the fact that the wavefunctions of the states with different energies are proportional to the hyperspherical harmonics (HSH) corresponding to different points on the hypersphere. Thus, the calculation of the matrix elements reduces to the problem of re-expanding HSH in terms of HSH depending on different points on the hypersphere. We solve this problem by applying the technique of multipole expansions for four-dimensional HSH. As a result, we obtain the multipole expansions whose coefficients are the matrix elements of the boost operator taken between hydrogen wavefunctions (i.e., hydrogen form factors). The explicit expressions for those coefficients are derived. It is shown that the hydrogen matrix elements can be presented as derivatives of an elementary function. Such an operator representation is convenient for the derivation of recurrence relations connecting matrix elements between states corresponding to different values of the quantum numbers n and l.

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

Correlation Coefficients: Appropriate Use and Interpretation.

PubMed

Schober, Patrick; Boer, Christa; Schwarte, Lothar A

2018-05-01

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

Orthogonal Polynomials on the Unit Circle with Fibonacci Verblunsky Coefficients, II. Applications

NASA Astrophysics Data System (ADS)

Damanik, David; Munger, Paul; Yessen, William N.

2013-10-01

We consider CMV matrices with Verblunsky coefficients determined in an appropriate way by the Fibonacci sequence and present two applications of the spectral theory of such matrices to problems in mathematical physics. In our first application we estimate the spreading rates of quantum walks on the line with time-independent coins following the Fibonacci sequence. The estimates we obtain are explicit in terms of the parameters of the system. In our second application, we establish a connection between the classical nearest neighbor Ising model on the one-dimensional lattice in the complex magnetic field regime, and CMV operators. In particular, given a sequence of nearest-neighbor interaction couplings, we construct a sequence of Verblunsky coefficients, such that the support of the Lee-Yang zeros of the partition function for the Ising model in the thermodynamic limit coincides with the essential spectrum of the CMV matrix with the constructed Verblunsky coefficients. Under certain technical conditions, we also show that the zeros distribution measure coincides with the density of states measure for the CMV matrix.

Gaining insights into reactive fluid-fractured rock systems using the temporal moments of a tracer breakthrough curve.

PubMed

Mukhopadhyay, Sumit; Liu, H-H; Spycher, N; Kennedy, B M

2014-03-01

In this paper, we show that the tracer breakthrough curves (BTCs), when the tracer chemically interacts with the solid matrix of a fractured rock, are considerably different than when it does not. Of particular interest, is the presence of a long pseudo steady state zone in the BTCs, where the tracer concentration is more or less constant over a long period of time. However, such a zone of constant concentration is not visible when either the tracer does not interact with the solid, or does so at an extremely fast rate. We show that these characteristics of the BTCs could be correlated to the parameters of the system. We develop expressions for the mean residence time and its variance for a chemically active and inactive tracer. We show that chemical interaction between the tracer and the solid increases the mean residence time and the increase depends on the distribution coefficient. We also show that the variance of residence time for a chemically active tracer is much larger than that for an inactive tracer, and it depends on both the distribution coefficient and the rate of chemical reaction. We verify these calculations against synthetic tracer BTCs, where the temporal moments are calculated by numerically integrating the tracer evolution curves. Even though we developed the mathematical expressions assuming an idealized fracture-matrix system, we believe that the mathematical expressions developed in this paper can be useful in gaining insights into reactive transport in a real fractured rock system. Published by Elsevier B.V.

Rate-dependent behavior of the amorphous phase of spider dragline silk.

PubMed

Patil, Sandeep P; Markert, Bernd; Gräter, Frauke

2014-06-03

The time-dependent stress-strain behavior of spider dragline silk was already observed decades ago, and has been attributed to the disordered sequences in silk proteins, which compose the soft amorphous matrix. However, the actual molecular origin and magnitude of internal friction within the amorphous matrix has remained inaccessible, because experimentally decomposing the mechanical response of the amorphous matrix from the embedded crystalline units is challenging. Here, we used atomistic molecular dynamics simulations to obtain friction forces for the relative sliding of peptide chains of Araneus diadematus spider silk within bundles of these chains as a representative unit of the amorphous matrix in silk fibers. We computed the friction coefficient and coefficient of viscosity of the amorphous phase to be in the order of 10(-6) Ns/m and 10(4) Ns/m(2), respectively, by extrapolating our simulation data to the viscous limit. Finally, we used a finite element method for the amorphous phase, solely based on parameters derived from molecular dynamics simulations including the newly determined coefficient of viscosity. With this model the time scales of stress relaxation, creep, and hysteresis were assessed, and found to be in line with the macroscopic time-dependent response of silk fibers. Our results suggest the amorphous phase to be the primary source of viscosity in silk and open up the avenue for finite element method studies of silk fiber mechanics including viscous effects. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Analytical Solutions for the Resonance Response of Goupillaud-type Elastic Media Using Z-transform Methods

DTIC Science & Technology

2012-02-01

using z-transform methods. The determinant of the resulting global system matrix in the z-space |Am| is a palindromic polynomial with real...resulting global system matrix in the z-space |Am| is a palindromic polynomial with real coefficients. The zeros of the palindromic polynomial are distinct...Goupillaud-type multilayered media. In addition, the present treatment uses a global matrix method that is attributed to Knopoff [16], rather than the

High frequency resolution terahertz time-domain spectroscopy

NASA Astrophysics Data System (ADS)

Sangala, Bagvanth Reddy

2013-12-01

A new method for the high frequency resolution terahertz time-domain spectroscopy is developed based on the characteristic matrix method. This method is useful for studying planar samples or stack of planar samples. The terahertz radiation was generated by optical rectification in a ZnTe crystal and detected by another ZnTe crystal via electro-optic sampling method. In this new characteristic matrix based method, the spectra of the sample and reference waveforms will be modeled by using characteristic matrices. We applied this new method to measure the optical constants of air. The terahertz transmission through the layered systems air-Teflon-air-Quartz-air and Nitrogen gas-Teflon-Nitrogen gas-Quartz-Nitrogen gas was modeled by the characteristic matrix method. A transmission coefficient is derived from these models which was optimized to fit the experimental transmission coefficient to extract the optical constants of air. The optimization of an error function involving the experimental complex transmission coefficient and the theoretical transmission coefficient was performed using patternsearch algorithm of MATLAB. Since this method takes account of the echo waveforms due to reflections in the layered samples, this method allows analysis of longer time-domain waveforms giving rise to very high frequency resolution in the frequency-domain. We have presented the high frequency resolution terahertz time-domain spectroscopy of air and compared the results with the literature values. We have also fitted the complex susceptibility of air to the Lorentzian and Gaussian functions to extract the linewidths.

Multicollinearity in canonical correlation analysis in maize.

PubMed

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

A systematic study of multiple minerals precipitation modelling in wastewater treatment.

PubMed

Kazadi Mbamba, Christian; Tait, Stephan; Flores-Alsina, Xavier; Batstone, Damien J

2015-11-15

Mineral solids precipitation is important in wastewater treatment. However approaches to minerals precipitation modelling are varied, often empirical, and mostly focused on single precipitate classes. A common approach, applicable to multi-species precipitates, is needed to integrate into existing wastewater treatment models. The present study systematically tested a semi-mechanistic modelling approach, using various experimental platforms with multiple minerals precipitation. Experiments included dynamic titration with addition of sodium hydroxide to synthetic wastewater, and aeration to progressively increase pH and induce precipitation in real piggery digestate and sewage sludge digestate. The model approach consisted of an equilibrium part for aqueous phase reactions and a kinetic part for minerals precipitation. The model was fitted to dissolved calcium, magnesium, total inorganic carbon and phosphate. Results indicated that precipitation was dominated by the mineral struvite, forming together with varied and minor amounts of calcium phosphate and calcium carbonate. The model approach was noted to have the advantage of requiring a minimal number of fitted parameters, so the model was readily identifiable. Kinetic rate coefficients, which were statistically fitted, were generally in the range 0.35-11.6 h(-1) with confidence intervals of 10-80% relative. Confidence regions for the kinetic rate coefficients were often asymmetric with model-data residuals increasing more gradually with larger coefficient values. This suggests that a large kinetic coefficient could be used when actual measured data is lacking for a particular precipitate-matrix combination. Correlation between the kinetic rate coefficients of different minerals was low, indicating that parameter values for individual minerals could be independently fitted (keeping all other model parameters constant). Implementation was therefore relatively flexible, and would be readily expandable to include other minerals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Correlates of anxiety and depression among patients with type 2 diabetes mellitus.

PubMed

Balhara, Yatan Pal Singh; Sagar, Rajesh

2011-07-01

Research has established the relation between diabetes and depression. Both diabetes and anxiety/depression are independently associated with increased morbidity and mortality. The present study aims at assessing the prevalence of anxiety/depression among outpatients receiving treatment for type 2 diabetes. The study was conducted in the endocrinology outpatient department of an urban tertiary care center. The instruments used included a semi-structured questionnaire, HbA1c levels, fasting blood glucose and postprandial blood glucose, Brief Patient Health Questionnaire, and Hospital Anxiety and Depression Scale (HADS). Analysis was carried out using the SPSS version 16.0. Pearson's correlation coefficient was calculated to find out the correlations. ANOVA was carried out for the in between group comparisons. There was a significant correlation between the HADS-Anxiety scale and Body Mass Index (BMI) with a correlation coefficient of 0.34 (P = 0.008). Also, a significant correlation existed between HADS-Depression scale and BMI (correlation coefficient, 0.36; P = 0.004). Significant correlation were observed between the duration of daily physical exercise and HADS-Anxiety (coefficient of correlation, -0.25; P = 0.04) scores. HADS-Anxiety scores were found to be related to HbA1c levels (correlation-coefficient, 0.41; P = 0.03) and postprandial blood glucose levels (correlation-coefficient, 0.51; P = 0.02). Monitoring of biochemical parameters like HbA1c and postprandial blood glucose levels and BMI could be a guide to development of anxiety in these patients. Also, physical exercise seems to have a protective effect on anxiety in those with type 2 diabetes mellitus.

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

Evaluation of the collaborative network of highly correlating skin proteins and its change following treatment with glucocorticoids

PubMed Central

2010-01-01

Background Glucocorticoids (GC) represent the core treatment modality for many inflammatory diseases. Its mode of action is difficult to grasp, not least because it includes direct modulation of many components of the extracellular matrix as well as complex anti-inflammatory effects. Protein expression profile of skin proteins is being changed with topical application of GC, however, the knowledge about singular markers in this regard is only patchy and collaboration is ill defined. Material/Methods Scar formation was observed under different doses of GC, which were locally applied on the back skin of mice (1 to 3 weeks). After euthanasia we analyzed protein expression of collagen I and III (picrosirius) in scar tissue together with 16 additional protein markers, which are involved in wound healing, with immunhistochemistry. For assessing GC's effect on co-expression we compared our results with a model of random figures to estimate how many significant correlations should be expected by chance. Results GC altered collagen and protein expression with distinct results in different areas of investigation. Most often we observed a reduced expression after application of low dose GC. In the scar infiltrate a multivariate analysis confirmed the significant impact of both GC concentrations. Calculation of Spearman's correlation coefficient similarly resulted in a significant impact of GC, and furthermore, offered the possibility to grasp the entire interactive profile in between all variables studied. The biological markers, which were connected by significant correlations could be arranged in a highly cross-linked network that involved most of the markers measured. A marker highly cross-linked with more than 3 significant correlations was indicated by a higher variation of all its correlations to the other variables, resulting in a standard deviation of > 0.2. Conclusion In addition to immunohistochemical analysis of single protein markers multivariate analysis of co-expressions by use of correlation coefficients reveals the complexity of biological relationships and identifies complex biological effects of GC on skin scarring. Depiction of collaborative clusters will help to understand functional pathways. The functional importance of highly cross-linked proteins will have to be proven in subsequent studies. PMID:20509951

The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

ERIC Educational Resources Information Center

Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.

2010-01-01

In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…

Least-Squares Approximation of an Improper by a Proper Correlation Matrix Using a Semi-Infinite Convex Program. Research Report 87-7.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based on a solution for C. I. Mosier's oblique Procrustes rotation problem offered by J. M. F. ten Berge and K. Nevels (1977). It is shown that the minimization problem…

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

PubMed

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Interphase layer optimization for metal matrix composites with fabrication considerations

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A methodology is presented to reduce the final matrix microstresses for metal matrix composites by concurrently optimizing the interphase characteristics and fabrication process. Application cases include interphase tailoring with and without fabrication considerations for two material systems, graphite/copper and silicon carbide/titanium. Results indicate that concurrent interphase/fabrication optimization produces significant reductions in the matrix residual stresses and strong coupling between interphase and fabrication tailoring. The interphase coefficient of thermal expansion and the fabrication consolidation pressure are the most important design parameters and must be concurrently optimized to further reduce the microstresses to more desirable magnitudes.

Quantum Double of Yangian of strange Lie superalgebra Qn and multiplicative formula for universal R-matrix

NASA Astrophysics Data System (ADS)

Stukopin, Vladimir

2018-02-01

Main result is the multiplicative formula for universal R-matrix for Quantum Double of Yangian of strange Lie superalgebra Qn type. We introduce the Quantum Double of the Yangian of the strange Lie superalgebra Qn and define its PBW basis. We compute the Hopf pairing for the generators of the Yangian Double. From the Hopf pairing formulas we derive a factorized multiplicative formula for the universal R-matrix of the Yangian Double of the Lie superalgebra Qn . After them we obtain coefficients in this multiplicative formula for universal R-matrix.

The longitudinal interplay between negative and positive symptom trajectories in patients under antipsychotic treatment: a post hoc analysis of data from a randomized, 1-year pragmatic trial

PubMed Central

2013-01-01

Background Schizophrenia is a highly heterogeneous disorder with positive and negative symptoms being characteristic manifestations of the disease. While these two symptom domains are usually construed as distinct and orthogonal, little is known about the longitudinal pattern of negative symptoms and their linkage with the positive symptoms. This study assessed the temporal interplay between these two symptom domains and evaluated whether the improvements in these symptoms were inversely correlated or independent with each other. Methods This post hoc analysis used data from a multicenter, randomized, open-label, 1-year pragmatic trial of patients with schizophrenia spectrum disorder who were treated with first- and second-generation antipsychotics in the usual clinical settings. Data from all treatment groups were pooled resulting in 399 patients with complete data on both the negative and positive subscale scores from the Positive and Negative Syndrome Scale (PANSS). Individual-based growth mixture modeling combined with interplay matrix was used to identify the latent trajectory patterns in terms of both the negative and positive symptoms. Pearson correlation coefficients were calculated to examine the relationship between the changes of these two symptom domains within each combined trajectory pattern. Results We identified four distinct negative symptom trajectories and three positive symptom trajectories. The trajectory matrix formed 11 combined trajectory patterns, which evidenced that negative and positive symptom trajectories moved generally in parallel. Correlation coefficients for changes in negative and positive symptom subscale scores were positive and statistically significant (P < 0.05). Overall, the combined trajectories indicated three major distinct patterns: 1) dramatic and sustained early improvement in both negative and positive symptoms (n = 70, 18%), 2) mild and sustained improvement in negative and positive symptoms (n = 237, 59%), and 3) no improvement in either negative or positive symptoms (n = 82, 21%). Conclusions This study of symptom trajectories over 1 year shows that changes in negative and positive symptoms were neither inversely nor independently related with each other. The positive association between these two symptom domains supports the notion that different symptom domains in schizophrenia may depend on each other through a unified upstream pathological disease process. PMID:24283222

Evaluation of the Correlation Coefficient of Polyethylene Glycol Treated and Direct Prolactin Results and Comparability with Different Assay System Results.

PubMed

Pal, Shyamali

2017-12-01

The presence of Macro prolactin is a significant cause of elevated prolactin resulting in misdiagnosis in all automated systems. Poly ethylene glycol (PEG) pretreatment is the preventive process but such process includes the probability of loss of a fraction of bioactive prolactin. Surprisingly, PEG treated EQAS & IQAS samples in Cobas e 411 are found out to be correlating with direct results of at least 3 immunoassay systems and treated and untreated Cobas e 411 results are comparable by a correlation coefficient. Comparison of EQAS, IQAS and patient samples were done to find out the trueness of such correlation factor. Study with patient's results have established the correlation coefficient is valid for very small concentration of prolactin also. EQAS, IQAS and 150 patient samples were treated with PEG and prolactin results of treated and untreated samples obtained from Roche Cobas e 411. 25 patient's results (treated) were compared with direct results in Advia Centaur, Architect I & Access2 systems. Correlation coefficient was obtained from trend line of the treated and untreated results. Two tailed p-value obtained from regression coefficient(r) and sample size. The correlation coefficient is in the range (0.761-0.771). Reverse correlation range is (1.289-1.301). r value of two sets of calculated results were 0.995. Two tailed p- value is zero approving dismissal of null hypothesis. The z-score of EQAS does not always assure authenticity of resultsPEG precipitation is correlated by the factor 0.761 even in very small concentrationsAbbreviationsGFCgel filtration chromatographyPEGpolyethylene glycolEQASexternal quality assurance systemM-PRLmacro prolactinPRLprolactinECLIAelectro-chemiluminescence immunoassayCLIAclinical laboratory improvement amendmentsIQASinternal quality assurance systemrregression coefficient.

Asymptotic Expansion of β Matrix Models in the One-cut Regime

NASA Astrophysics Data System (ADS)

Borot, G.; Guionnet, A.

2013-01-01

We prove the existence of a 1/ N expansion to all orders in β matrix models with a confining, offcritical potential corresponding to an equilibrium measure with a connected support. Thus, the coefficients of the expansion can be obtained recursively by the "topological recursion" derived in Chekhov and Eynard (JHEP 0612:026, 2006). Our method relies on the combination of a priori bounds on the correlators and the study of Schwinger-Dyson equations, thanks to the uses of classical complex analysis techniques. These a priori bounds can be derived following (Boutet de Monvel et al. in J Stat Phys 79(3-4):585-611, 1995; Johansson in Duke Math J 91(1):151-204, 1998; Kriecherbauer and Shcherbina in Fluctuations of eigenvalues of matrix models and their applications, 2010) or for strictly convex potentials by using concentration of measure (Anderson et al. in An introduction to random matrices, Sect. 2.3, Cambridge University Press, Cambridge, 2010). Doing so, we extend the strategy of Guionnet and Maurel-Segala (Ann Probab 35:2160-2212, 2007), from the hermitian models ( β = 2) and perturbative potentials, to general β models. The existence of the first correction in 1/ N was considered in Johansson (1998) and more recently in Kriecherbauer and Shcherbina (2010). Here, by taking similar hypotheses, we extend the result to all orders in 1/ N.

Comparison of Protein Immunoprecipitation-Multiple Reaction Monitoring with ELISA for Assay of Biomarker Candidates in Plasma

PubMed Central

2013-01-01

Quantitative analysis of protein biomarkers in plasma is typically done by ELISA, but this method is limited by the availability of high-quality antibodies. An alternative approach is protein immunoprecipitation combined with multiple reaction monitoring mass spectrometry (IP-MRM). We compared IP-MRM to ELISA for the analysis of six colon cancer biomarker candidates (metalloproteinase inhibitor 1 (TIMP1), cartilage oligomeric matrix protein (COMP), thrombospondin-2 (THBS2), endoglin (ENG), mesothelin (MSLN) and matrix metalloproteinase-9 (MMP9)) in plasma from colon cancer patients and noncancer controls. Proteins were analyzed by multiplex immunoprecipitation from plasma with the ELISA capture antibodies, further purified by SDS-PAGE, digested and analyzed by stable isotope dilution MRM. IP-MRM provided linear responses (r = 0.978–0.995) between 10 and 640 ng/mL for the target proteins spiked into a “mock plasma” matrix consisting of 60 mg/mL bovine serum albumin. Measurement variation (coefficient of variation at the limit of detection) for IP-MRM assays ranged from 2.3 to 19%, which was similar to variation for ELISAs of the same samples. IP-MRM and ELISA measurements for all target proteins except ENG were highly correlated (r = 0.67–0.97). IP-MRM with high-quality capture antibodies thus provides an effective alternative method to ELISA for protein quantitation in biological fluids. PMID:24224610

Dynamic Textures Modeling via Joint Video Dictionary Learning.

PubMed

Wei, Xian; Li, Yuanxiang; Shen, Hao; Chen, Fang; Kleinsteuber, Martin; Wang, Zhongfeng

2017-04-06

Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series. Hence, a dynamic scene sequence is represented by an appropriate transition matrix associated with a dictionary. In order to ensure the stability of JVDL, we impose several constraints on such transition matrix and dictionary. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. Moreover, such learned JVDL parameters can be used for various DT applications, such as DT synthesis and recognition. Experimental results demonstrate the strong competitiveness of the proposed JVDL approach in comparison with state-of-the-art video representation methods. Especially, it performs significantly better in dealing with DT synthesis and recognition on heavily corrupted data.

Minimum spanning tree filtering of correlations for varying time scales and size of fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; Forczek, Marcin; DroŻdŻ, Stanisław

2017-05-01

Based on a recently proposed q -dependent detrended cross-correlation coefficient, ρq [J. Kwapień, P. Oświęcimka, and S. Drożdż, Phys. Rev. E 92, 052815 (2015), 10.1103/PhysRevE.92.052815], we generalize the concept of the minimum spanning tree (MST) by introducing a family of q -dependent minimum spanning trees (q MST s ) that are selective to cross-correlations between different fluctuation amplitudes and different time scales of multivariate data. They inherit this ability directly from the coefficients ρq, which are processed here to construct a distance matrix being the input to the MST-constructing Kruskal's algorithm. The conventional MST with detrending corresponds in this context to q =2 . In order to illustrate their performance, we apply the q MSTs to sample empirical data from the American stock market and discuss the results. We show that the q MST graphs can complement ρq in disentangling "hidden" correlations that cannot be observed in the MST graphs based on ρDCCA, and therefore, they can be useful in many areas where the multivariate cross-correlations are of interest. As an example, we apply this method to empirical data from the stock market and show that by constructing the q MSTs for a spectrum of q values we obtain more information about the correlation structure of the data than by using q =2 only. More specifically, we show that two sets of signals that differ from each other statistically can give comparable trees for q =2 , while only by using the trees for q ≠2 do we become able to distinguish between these sets. We also show that a family of q MSTs for a range of q expresses the diversity of correlations in a manner resembling the multifractal analysis, where one computes a spectrum of the generalized fractal dimensions, the generalized Hurst exponents, or the multifractal singularity spectra: the more diverse the correlations are, the more variable the tree topology is for different q 's. As regards the correlation structure of the stock market, our analysis exhibits that the stocks belonging to the same or similar industrial sectors are correlated via the fluctuations of moderate amplitudes, while the largest fluctuations often happen to synchronize in those stocks that do not necessarily belong to the same industry.

The Lehmer Matrix and Its Recursive Analogue

DTIC Science & Technology

2010-01-01

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

Transfer matrix method for four-flux radiative transfer.

PubMed

Slovick, Brian; Flom, Zachary; Zipp, Lucas; Krishnamurthy, Srini

2017-07-20

We develop a transfer matrix method for four-flux radiative transfer, which is ideally suited for studying transport through multiple scattering layers. The model predicts the specular and diffuse reflection and transmission of multilayer composite films, including interface reflections, for diffuse or collimated incidence. For spherical particles in the diffusion approximation, we derive closed-form expressions for the matrix coefficients and show remarkable agreement with numerical Monte Carlo simulations for a range of absorption values and film thicknesses, and for an example multilayer slab.

The Accuracy of Serum Matrix Metalloproteinase-9 for Predicting Hemorrhagic Transformation After Acute Ischemic Stroke: A Systematic Review and Meta-Analysis.

PubMed

Wang, Lu; Wei, Chenchen; Deng, Linghui; Wang, Ziqiong; Song, Mengyuan; Xiong, Yao; Liu, Ming

2018-06-01

Hemorrhagic transformation is a serious complication of acute ischemic stroke, which may cause detrimental outcomes and the delayed use of anticoagulation therapy. Early predicting and identifying the patients at high risk of hemorrhagic transformation before clinical deterioration occurrence become a research priority. To study the value of plasma matrix metalloproteinase-9 predicting hemorrhagic transformation after ischemic stroke. We searched PubMed, Ovid, Cochrane Library, and other 2 Chinese databases to identify literatures published up to September 2017 and performed meta-analysis by STATA (version 12.0, StataCorp LP, College Station, TX). Twelve studies incorporating 1492 participants were included and 7 studies were included in the quantitative statistical analysis. The pooled sensitivity was 85% (95% confidence interval [CI]: 75%, 91%) and the pooled specificity was 79% (95% CI: 67%, 87%). The area under the receiver operating characteristic curve was .89 (95% CI .86, .91). Significant heterogeneity for all estimates value existed (all the P value < .05 and I 2  > 50%). There is no threshold effect with P value greater than .05 of the correlation coefficient. Meta-regression and subgroup analysis showed cut-off value and hemorrhagic subtype contributed to heterogeneity. Deeks' funnel plot indicated no significant publication bias for 7 quantitative analysis studies. Matrix metalloproteinase-9 has high predictive value for hemorrhagic transformation after acute ischemic stroke. It may be useful to test matrix metalloproteinase-9 to exclude patients at low risk of hemorrhage for precise treatment in the future clinical work. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Anthropometry of Women of the U.S. Army--1977. Report Number 4. Correlation Coefficients

DTIC Science & Technology

1980-02-01

S.... •, 0 76 x:. ADo5 //64 ! TECHNICAL REPORT NATICK/TR-80/016 (/ II ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY-1977 Report No. 4 Correlation...NUMBER NATICK/TR-80/016 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY--1977 Technical Report REPORT NO... Anthropometry Survey(s) Coefficients of correlation Measurement(s) U.S. Army Correlation coefficients Body size Military personnel Equation(s) Sizes

Trust in Leadership DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

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

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

Modeling visibility in the Paso del Norte (PDN) Region

NASA Astrophysics Data System (ADS)

Medina Calderon, Richard

Poor visibility is a subject of growing public concern throughout the U.S, and an active area of research. Its societal impacts on air quality, aviation transport and traffic are significant. Aerosols play a fundamental role in the attenuation of solar radiation, and also affect visibility. The scattering and extinction coefficients of aerosol particles in the Paso del Norte Region have been calculated using the T- matrix model in conjunction with a laser particle counter. Inter-comparison of the model's results of the scattering and absorption coefficients against the corresponding data from a Photoacustic extinctiometer instrument (which measures in-situ absorption and scattering coefficients of aerosol particles) shows excellent agreement. In addition, the volume-weighted method is used to determine the composite index of refraction which is representative of the aerosols for the Paso del Norte Region to obtain information of the type of aerosol particles present in the Region. The Single Scattering Albedo has also been retrieved using this methodology to obtain further insight into the type of aerosols present on a given day. Finally, the Koschmieder equation has been used to calculate the visual range or visibility, and was correlated with the PM2.5 and PM10 particle concentration present in the Region. Our methodology will allow a better understanding of the size and type of aerosol particles that are most detrimental to the visibility for the Paso Del Norte Region.

Modelling of individual subject ozone exposure response kinetics.

PubMed

Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

2012-06-01

A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

Fluid-structure finite-element vibrational analysis

NASA Technical Reports Server (NTRS)

Feng, G. C.; Kiefling, L.

1974-01-01

A fluid finite element has been developed for a quasi-compressible fluid. Both kinetic and potential energy are expressed as functions of nodal displacements. Thus, the formulation is similar to that used for structural elements, with the only differences being that the fluid can possess gravitational potential, and the constitutive equations for fluid contain no shear coefficients. Using this approach, structural and fluid elements can be used interchangeably in existing efficient sparse-matrix structural computer programs such as SPAR. The theoretical development of the element formulations and the relationships of the local and global coordinates are shown. Solutions of fluid slosh, liquid compressibility, and coupled fluid-shell oscillation problems which were completed using a temporary digital computer program are shown. The frequency correlation of the solutions with classical theory is excellent.

Development and application of a sol-gel immunosorbent-based method for the determination of isoproturon in surface water.

PubMed

Zhang, Xiuli; Martens, Dieter; Krämer, Petra M; Kettrup, Antonius A; Liang, Xinmiao

2006-01-13

An immunosorbent was fabricated by encapsulation of monoclonal anti-isoproturon antibodies in sol-gel matrix. The immunosorbent-based loading, rinsing and eluting processes were optimized. Based on these optimizations, the sol-gel immunosorbent (SG-IS) selectively extracted isoproturon from an artificial mixture of 68 pesticides. In addition to this high selectivity, the SG-IS proved to be reusable. The SG-IS was combined with liquid chromatography-tandem mass spectrometry (LC-MS-MS) to determine isoproturon in surface water, and the linear range was up to 2.2 microg/l with correlation coefficient higher than 0.99 and relative standard deviation (RSD) lower than 5% (n=8). The limit of quantitation (LOQ) for 25-ml surface water sample was 5 ng/l.

Solute Transport of Negatively Charged Contrast Agents Across Articular Surface of Injured Cartilage.

PubMed

Kokkonen, H T; Chin, H C; Töyräs, J; Jurvelin, J S; Quinn, T M

2017-04-01

Solute transport through the extracellular matrix (ECM) is crucial to chondrocyte metabolism. Cartilage injury affects solute transport in cartilage due to alterations in ECM structure and solute-matrix interactions. Therefore, cartilage injury may be detected by using contrast agent-based clinical imaging. In the present study, effects of mechanical injury on transport of negatively charged contrast agents in cartilage were characterized. Using cartilage plugs injured by mechanical compression protocol, effective partition coefficients and diffusion fluxes of iodine- and gadolinium-based contrast agents were measured using high resolution microCT imaging. For all contrast agents studied, effective diffusion fluxes increased significantly, particularly at early times during the diffusion process (38 and 33% increase after 4 min, P < 0.05 for iodine and Gd-DTPA; and 76% increase after 10 min for diatrizoate, P < 0.05). Effective partition coefficients were unaffected in mechanically injured cartilage. Mechanical injury reduced PG content and collagen integrity in cartilage superficial zone. This study suggests that alterations in contrast agent diffusion flux, a non-equilibrium transport parameter, provides a more sensitive indicator for assessment of cartilage matrix integrity than partition coefficient and the equilibrium distribution of solute. These findings may help in developing clinical methods of contrast agent-based imaging to detect cartilage injury.

Self-similarity and quasi-idempotence in neural networks and related dynamical systems.

PubMed

Minati, Ludovico; Winkel, Julia; Bifone, Angelo; Oświęcimka, Paweł; Jovicich, Jorge

2017-04-01

Self-similarity across length scales is pervasively observed in natural systems. Here, we investigate topological self-similarity in complex networks representing diverse forms of connectivity in the brain and some related dynamical systems, by considering the correlation between edges directly connecting any two nodes in a network and indirect connection between the same via all triangles spanning the rest of the network. We note that this aspect of self-similarity, which is distinct from hierarchically nested connectivity (coarse-grain similarity), is closely related to idempotence of the matrix representing the graph. We introduce two measures, ι(1) and ι(∞), which represent the element-wise correlation coefficients between the initial matrix and the ones obtained after squaring it once or infinitely many times, and term the matrices which yield large values of these parameters "quasi-idempotent". These measures delineate qualitatively different forms of "shallow" and "deep" quasi-idempotence, which are influenced by nodal strength heterogeneity. A high degree of quasi-idempotence was observed for partially synchronized mean-field Kuramoto oscillators with noise, electronic chaotic oscillators, and cultures of dissociated neurons, wherein the expression of quasi-idempotence correlated strongly with network maturity. Quasi-idempotence was also detected for macro-scale brain networks representing axonal connectivity, synchronization of slow activity fluctuations during idleness, and co-activation across experimental tasks, and preliminary data indicated that quasi-idempotence of structural connectivity may decrease with ageing. This initial study highlights that the form of network self-similarity indexed by quasi-idempotence is detectable in diverse dynamical systems, and draws attention to it as a possible basis for measures representing network "collectivity" and pattern formation.

Self-similarity and quasi-idempotence in neural networks and related dynamical systems

NASA Astrophysics Data System (ADS)

Minati, Ludovico; Winkel, Julia; Bifone, Angelo; Oświecimka, Paweł; Jovicich, Jorge

2017-04-01

Self-similarity across length scales is pervasively observed in natural systems. Here, we investigate topological self-similarity in complex networks representing diverse forms of connectivity in the brain and some related dynamical systems, by considering the correlation between edges directly connecting any two nodes in a network and indirect connection between the same via all triangles spanning the rest of the network. We note that this aspect of self-similarity, which is distinct from hierarchically nested connectivity (coarse-grain similarity), is closely related to idempotence of the matrix representing the graph. We introduce two measures, ι ( 1 ) and ι ( ∞ ) , which represent the element-wise correlation coefficients between the initial matrix and the ones obtained after squaring it once or infinitely many times, and term the matrices which yield large values of these parameters "quasi-idempotent". These measures delineate qualitatively different forms of "shallow" and "deep" quasi-idempotence, which are influenced by nodal strength heterogeneity. A high degree of quasi-idempotence was observed for partially synchronized mean-field Kuramoto oscillators with noise, electronic chaotic oscillators, and cultures of dissociated neurons, wherein the expression of quasi-idempotence correlated strongly with network maturity. Quasi-idempotence was also detected for macro-scale brain networks representing axonal connectivity, synchronization of slow activity fluctuations during idleness, and co-activation across experimental tasks, and preliminary data indicated that quasi-idempotence of structural connectivity may decrease with ageing. This initial study highlights that the form of network self-similarity indexed by quasi-idempotence is detectable in diverse dynamical systems, and draws attention to it as a possible basis for measures representing network "collectivity" and pattern formation.

Novel insights into anoxic/aerobic(1)/aerobic(2) biological fluidized-bed system for coke wastewater treatment by fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

PubMed

Ou, Hua-Se; Wei, Chao-Hai; Mo, Ce-Hui; Wu, Hai-Zhen; Ren, Yuan; Feng, Chun-Hua

2014-10-01

Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) was applied to investigate the contaminant removal efficiency and fluorescent characteristic variations in a full scale coke wastewater (CWW) treatment plant with a novel anoxic/aerobic(1)/aerobic(2) (A/O(1)/O(2)) process, which combined with internal-loop fluidized-bed reactor. Routine monitoring results indicated that primary contaminants in CWW, such as phenols and free cyanide, were removed efficiently in A/O(1)/O(2) process (removal efficiency reached 99% and 95%, respectively). Three-dimensional excitation-emission matrix fluorescence spectroscopy and PARAFAC identified three fluorescent components, including two humic-like fluorescence components (C1 and C3) and one protein-like component (C2). Principal component analysis revealed that C1 and C2 correlated with COD (correlation coefficient (r)=0.782, p<0.01 and r=0.921, p<0.01), respectively) and phenols (r=0.796, p<0.01 and r=0.914, p<0.01, respectively), suggesting that C1 and C2 might be associated with the predominating aromatic contaminants in CWW. C3 correlated with mixed liquor suspended solids (r=0.863, p<0.01) in fluidized-bed reactors, suggesting that it might represent the biological dissolved organic matter. In A/O(1)/O(2) process, the fluorescence intensities of C1 and C2 consecutively decreased, indicating the degradation of aromatic contaminants. Correspondingly, the fluorescence intensity of C3 increased in aerobic(1) stage, suggesting an increase of biological dissolved organic matter. Copyright © 2014 Elsevier Ltd. All rights reserved.

Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

Black phosphorus-assisted laser desorption ionization mass spectrometry for the determination of low-molecular-weight compounds in biofluids.

PubMed

He, Xiao-Mei; Ding, Jun; Yu, Lei; Hussain, Dilshad; Feng, Yu-Qi

2016-09-01

Quantitative analysis of small molecules by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been a challenging task due to matrix-derived interferences in low m/z region and poor reproducibility of MS signal response. In this study, we developed an approach by applying black phosphorus (BP) as a matrix-assisted laser desorption ionization (MALDI) matrix for the quantitative analysis of small molecules for the first time. Black phosphorus-assisted laser desorption/ionization mass spectrometry (BP/ALDI-MS) showed clear background and exhibited superior detection sensitivity toward quaternary ammonium compounds compared to carbon-based materials. By combining stable isotope labeling (SIL) strategy with BP/ALDI-MS (SIL-BP/ALDI-MS), a variety of analytes labeled with quaternary ammonium group were sensitively detected. Moreover, the isotope-labeled forms of analytes also served as internal standards, which broadened the analyte coverage of BP/ALDI-MS and improved the reproducibility of MS signals. Based on these advantages, a reliable method for quantitative analysis of aldehydes from complex biological samples (saliva, urine, and serum) was successfully established. Good linearities were obtained for five aldehydes in the range of 0.1-20.0 μM with correlation coefficients (R (2)) larger than 0.9928. The LODs were found to be 20 to 100 nM. Reproducibility of the method was obtained with intra-day and inter-day relative standard deviations (RSDs) less than 10.4 %, and the recoveries in saliva samples ranged from 91.4 to 117.1 %. Taken together, the proposed SIL-BP/ALDI-MS strategy has proved to be a reliable tool for quantitative analysis of aldehydes from complex samples. Graphical Abstract An approach for the determination of small molecules was developed by using black phosphorus (BP) as a matrix-assisted laser desorption ionization (MALDI) matrix.

[Correlation of molecular weight and nanofiltration mass transfer coefficient of phenolic acid composition from Salvia miltiorrhiza].

PubMed

Li, Cun-Yu; Wu, Xin; Gu, Jia-Mei; Li, Hong-Yang; Peng, Guo-Ping

2018-04-01

Based on the molecular sieving and solution-diffusion effect in nanofiltration separation, the correlation between initial concentration and mass transfer coefficient of three typical phenolic acids from Salvia miltiorrhiza was fitted to analyze the relationship among mass transfer coefficient, molecular weight and concentration. The experiment showed a linear relationship between operation pressure and membrane flux. Meanwhile, the membrane flux was gradually decayed with the increase of solute concentration. On the basis of the molecular sieving and solution-diffusion effect, the mass transfer coefficient and initial concentration of three phenolic acids showed a power function relationship, and the regression coefficients were all greater than 0.9. The mass transfer coefficient and molecular weight of three phenolic acids were negatively correlated with each other, and the order from high to low is protocatechualdehyde >rosmarinic acid> salvianolic acid B. The separation mechanism of nanofiltration for phenolic acids was further clarified through the analysis of the correlation of molecular weight and nanofiltration mass transfer coefficient. The findings provide references for nanofiltration separation, especially for traditional Chinese medicine with phenolic acids. Copyright© by the Chinese Pharmaceutical Association.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Improved definition of crustal anomalies for Magsat data

NASA Technical Reports Server (NTRS)

1981-01-01

A scheme was developed for separating the portions of the magnetic field measured by the Magsat 1 satellite that arise from internal and external sources. To test this method, a set of sample coefficients were used to compute the field values along a simulated satellite orbit. This data was then used to try to recover the original coefficients. Matrix inversion and recursive least squares methods were used to solve for the input coefficients. The accuracy of the two methods are compared.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Extension of latin hypercube samples with correlated variables.

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

Hora, Stephen Curtis; Helton, Jon Craig; Sallaberry, Cedric J. PhD.

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« less

On the role of covariance information for GRACE K-band observations in the Celestial Mechanics Approach

NASA Astrophysics Data System (ADS)

Bentel, Katrin; Meyer, Ulrich; Arnold, Daniel; Jean, Yoomin; Jäggi, Adrian

2017-04-01

The Astronomical Institute at the University of Bern (AIUB) derives static and time-variable gravity fields by means of the Celestial Mechanics Approach (CMA) from GRACE (level 1B) data. This approach makes use of the close link between orbit and gravity field determination. GPS-derived kinematic GRACE orbit positions, inter-satellite K-band observations, which are the core observations of GRACE, and accelerometer data are combined to rigorously estimate orbit and spherical harmonic gravity field coefficients in one adjustment step. Pseudo-stochastic orbit parameters are set up to absorb unmodeled noise. The K-band range measurements in along-track direction lead to a much higher correlation of the observations in this direction compared to the other directions and thus, to north-south stripes in the unconstrained gravity field solutions, so-called correlated errors. By using a full covariance matrix for the K-band observations the correlation can be taken into account. One possibility is to derive correlation information from post-processing K-band residuals. This is then used in a second iteration step to derive an improved gravity field solution. We study the effects of pre-defined covariance matrices and residual-derived covariance matrices on the final gravity field product with the CMA.

Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

ERIC Educational Resources Information Center

Mitchell, Mark L.

Understanding correlation coefficients is difficult for students. A free computer program that helps introductory psychology students distinguish between positive and negative correlation, and which also teaches them to understand the differences between correlation coefficients of different size is described in this paper. The program is…

Reproducibility of graph metrics of human brain structural networks.

PubMed

Duda, Jeffrey T; Cook, Philip A; Gee, James C

2014-01-01

Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. The reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are used to examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm.

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Novel Calibration Algorithm for a Three-Axis Strapdown Magnetometer

PubMed Central

Liu, Yan Xia; Li, Xi Sheng; Zhang, Xiao Juan; Feng, Yi Bo

2014-01-01

A complete error calibration model with 12 independent parameters is established by analyzing the three-axis magnetometer error mechanism. The said model conforms to an ellipsoid restriction, the parameters of the ellipsoid equation are estimated, and the ellipsoid coefficient matrix is derived. However, the calibration matrix cannot be determined completely, as there are fewer ellipsoid parameters than calibration model parameters. Mathematically, the calibration matrix derived from the ellipsoid coefficient matrix by a different matrix decomposition method is not unique, and there exists an unknown rotation matrix R between them. This paper puts forward a constant intersection angle method (angles between the geomagnetic field and gravitational field are fixed) to estimate R. The Tikhonov method is adopted to solve the problem that rounding errors or other errors may seriously affect the calculation results of R when the condition number of the matrix is very large. The geomagnetic field vector and heading error are further corrected by R. The constant intersection angle method is convenient and practical, as it is free from any additional calibration procedure or coordinate transformation. In addition, the simulation experiment indicates that the heading error declines from ±1° calibrated by classical ellipsoid fitting to ±0.2° calibrated by a constant intersection angle method, and the signal-to-noise ratio is 50 dB. The actual experiment exhibits that the heading error is further corrected from ±0.8° calibrated by the classical ellipsoid fitting to ±0.3° calibrated by a constant intersection angle method. PMID:24831110

Development of a clinical diagnostic matrix for characterizing inherited epidermolysis bullosa.

PubMed

Yenamandra, V K; Moss, C; Sreenivas, V; Khan, M; Sivasubbu, S; Sharma, V K; Sethuraman, G

2017-06-01

Accurately diagnosing the subtype of epidermolysis bullosa (EB) is critical for management and genetic counselling. Modern laboratory techniques are largely inaccessible in developing countries, where the diagnosis remains clinical and often inaccurate. To develop a simple clinical diagnostic tool to aid in the diagnosis and subtyping of EB. We developed a matrix indicating presence or absence of a set of distinctive clinical features (as rows) for the nine most prevalent EB subtypes (as columns). To test an individual patient, presence or absence of these features was compared with the findings expected in each of the nine subtypes to see which corresponded best. If two or more diagnoses scored equally, the diagnosis with the greatest number of specific features was selected. The matrix was tested using findings from 74 genetically characterized patients with EB aged > 6 months by an investigator blinded to molecular diagnosis. For concordance, matrix diagnoses were compared with molecular diagnoses. Overall, concordance between the matrix and molecular diagnoses for the four major types of EB was 91·9%, with a kappa coefficient of 0·88 [95% confidence interval (CI) 0·81-0·95; P < 0·001]. The matrix achieved a 75·7% agreement in classifying EB into its nine subtypes, with a kappa coefficient of 0·73 (95% CI 0·69-0·77; P < 0·001). The matrix appears to be simple, valid and useful in predicting the type and subtype of EB. An electronic version will facilitate further testing. © 2016 British Association of Dermatologists.

Seasonal characterization of CDOM for lakes in semiarid regions of Northeast China using excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC)

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Li, Lin; Zang, Shuying; Shao, Tiantian; Li, Sijia; Du, Jia

2016-03-01

The seasonal characteristics of fluorescent components in chromophoric dissolved organic matter (CDOM) for lakes in the semiarid region of Northeast China were examined by excitation-emission matrix (EEM) spectra and parallel factor analysis (PARAFAC). Two humic-like (C1 and C2) and protein-like (C3 and C4) components were identified using PARAFAC. The average fluorescence intensity of the four components differed under seasonal variation from June and August 2013 to February and April 2014. Components 1 and 2 exhibited a strong linear correlation (R2 = 0.628). Significantly positive linear relationships between CDOM absorption coefficients a(254) (R2 = 0.72, 0.46, p < 0.01), a(280) (R2 = 0.77, 0.47, p < 0.01), a(350) (R2 = 0.76, 0.78, p < 0.01) and Fmax for two humic-like components (C1 and C2) were exhibited, respectively. A significant relationship (R2 = 0.930) was found between salinity and dissolved organic carbon (DOC). However, almost no obvious correlation was found between salinity and EEM-PARAFAC-extracted components except for C3 (R2 = 0.469). Results from this investigation demonstrate that the EEM-PARAFAC technique can be used to evaluate the seasonal dynamics of CDOM fluorescent components for inland waters in the semiarid regions of Northeast China, and to quantify CDOM components for other waters with similar environmental conditions.

Hair cortisol detection in dairy cattle by using EIA: protocol validation and correlation with faecal cortisol metabolites.

PubMed

Tallo-Parra, O; Manteca, X; Sabes-Alsina, M; Carbajal, A; Lopez-Bejar, M

2015-06-01

Hair may be a useful matrix to detect cumulative cortisol concentrations in studies of animal welfare and chronic stress. The aim of this study was to validate a protocol for cortisol detection in hair from dairy cattle by enzyme immunoassay (EIA). Seventeen adult Holstein-Friesian dairy cows were used during the milking period. Hair cortisol concentration was assessed in 25-day-old hair samples taken from the frontal region of the head, analysing black and white coloured hair separately. Concentrations of cortisol metabolites were determined in faeces collected twice a week during the same period of time. There was a high correlation between cortisol values in faeces and cortisol in white colour hair samples but such correlation was not significant with the black colour hair samples. The intra- and inter-assay coefficients of variation were 4.9% and 10.6%, respectively. The linearity showed R 2=0.98 and mean percentage error of -10.8 ± 1.55%. The extraction efficiency was 89.0 ± 23.52% and the parallelism test showed similar slopes. Cortisol detection in hair by using EIA seems to be a valid method to represent long-term circulating cortisol levels in dairy cattle.

Temporal correlation coefficient for directed networks.

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.

Correlation characteristics of phase and amplitude chimeras in an ensemble of nonlocally coupled maps

NASA Astrophysics Data System (ADS)

Vadivasova, T. E.; Strelkova, G. I.; Bogomolov, S. A.; Anishchenko, V. S.

2017-01-01

Correlation characteristics of chimera states have been calculated using the coefficient of mutual correlation of elements in a closed-ring ensemble of nonlocally coupled chaotic maps. Quantitative differences between the coefficients of mutual correlation for phase and amplitude chimeras are established for the first time.

Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Vermeer, K. A.; van der Schoot, J.; Lemij, H. G.; de Boer, J. F.

2013-03-01

Recently, a method to determine the retinal nerve fiber layer (RNFL) attenuation coefficient, based on normalization on the retinal pigment epithelium, was introduced. In contrast to conventional RNFL thickness measures, this novel measure represents a scattering property of the RNFL tissue. In this paper, we compare the RNFL thickness and the RNFL attenuation coefficient on 10 normal and 8 glaucomatous eyes by analyzing the correlation coefficient and the receiver operator curves (ROCs). The thickness and attenuation coefficient showed moderate correlation (r=0.82). Smaller correlation coefficients were found within normal (r=0.55) and glaucomatous (r=0.48) eyes. The full separation between normal and glaucomatous eyes based on the RNFL attenuation coefficient yielded an area under the ROC (AROC) of 1.0. The AROC for the RNFL thickness was 0.9875. No statistically significant difference between the two measures was found by comparing the AROC. RNFL attenuation coefficients may thus replace current RNFL thickness measurements or be combined with it to improve glaucoma diagnosis.

[Application of wavelet transform and neural network in the near-infrared spectrum analysis of oil shale].

PubMed

Li, Su-Yi; Ji, Yan-Ju; Liu, Wei-Yu; Wang, Zhi-Hong

2013-04-01

In the present study, an innovative method is proposed, employing both wavelet transform and neural network, to analyze the near-infrared spectrum data in oil shale survey. The method entails using db8 wavelet at 3 levels decomposition to process raw data, using the transformed data as the input matrix, and creating the model through neural network. To verify the validity of the method, this study analyzes 30 synthesized oil shale samples, in which 20 samples are randomly selected for network training, the other 10 for model prediction, and uses the full spectrum and the wavelet transformed spectrum to carry out 10 network models, respectively. Results show that the mean speed of the full spectrum neural network modeling is 570.33 seconds, and the predicted residual sum of squares (PRESS) and correlation coefficient of prediction are 0.006 012 and 0.843 75, respectively. In contrast, the mean speed of the wavelet network modeling method is 3.15 seconds, and the mean PRESS and correlation coefficient of prediction are 0.002 048 and 0.953 19, respectively. These results demonstrate that the wavelet neural network modeling method is significantly superior to the full spectrum neural network modeling method. This study not only provides a new method for more efficient and accurate detection of the oil content of oil shale, but also indicates the potential for applying wavelet transform and neutral network in broad near-infrared spectrum analysis.

An efficient and accurate 3D displacements tracking strategy for digital volume correlation

NASA Astrophysics Data System (ADS)

Pan, Bing; Wang, Bo; Wu, Dafang; Lubineau, Gilles

2014-07-01

Owing to its inherent computational complexity, practical implementation of digital volume correlation (DVC) for internal displacement and strain mapping faces important challenges in improving its computational efficiency. In this work, an efficient and accurate 3D displacement tracking strategy is proposed for fast DVC calculation. The efficiency advantage is achieved by using three improvements. First, to eliminate the need of updating Hessian matrix in each iteration, an efficient 3D inverse compositional Gauss-Newton (3D IC-GN) algorithm is introduced to replace existing forward additive algorithms for accurate sub-voxel displacement registration. Second, to ensure the 3D IC-GN algorithm that converges accurately and rapidly and avoid time-consuming integer-voxel displacement searching, a generalized reliability-guided displacement tracking strategy is designed to transfer accurate and complete initial guess of deformation for each calculation point from its computed neighbors. Third, to avoid the repeated computation of sub-voxel intensity interpolation coefficients, an interpolation coefficient lookup table is established for tricubic interpolation. The computational complexity of the proposed fast DVC and the existing typical DVC algorithms are first analyzed quantitatively according to necessary arithmetic operations. Then, numerical tests are performed to verify the performance of the fast DVC algorithm in terms of measurement accuracy and computational efficiency. The experimental results indicate that, compared with the existing DVC algorithm, the presented fast DVC algorithm produces similar precision and slightly higher accuracy at a substantially reduced computational cost.

Exploring multicollinearity using a random matrix theory approach.

PubMed

Feher, Kristen; Whelan, James; Müller, Samuel

2012-01-01

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.

Neutrinoless ββ decay mediated by the exchange of light and heavy neutrinos: the role of nuclear structure correlations

NASA Astrophysics Data System (ADS)

Menéndez, J.

2018-01-01

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

Parametric studies to determine the effect of compliant layers on metal matrix composite systems

NASA Technical Reports Server (NTRS)

Caruso, J. J.; Chamis, C. C.; Brown, H. C.

1990-01-01

Computational simulation studies are conducted to identify compliant layers to reduce matrix stresses which result from the coefficient of thermal expansion mismatch and the large temperature range over which the current metal matrix composites will be used. The present study includes variations of compliant layers and their properties to determine their influence on unidirectional composite and constituent response. Two simulation methods are used for these studies. The first approach is based on a three-dimensional linear finite element analysis of a 9 fiber unidirectional composite system. The second approach is a micromechanics based nonlinear computer code developed to determine the behavior of metal matrix composite system for thermal and mechanical loads. The results show that an effective compliant layer for the SCS 6 (SiC)/Ti-24Al-11Nb (Ti3Al + Nb) and SCS 6 (SiC)/Ti-15V-3Cr-3Sn-3Al (Ti-15-3) composite systems should have modulus 15 percent that of the matrix and a coefficient of thermal expansion of the compliant layer roughly equal to that of the composite system without the CL. The matrix stress in the longitudinal and the transverse tangent (loop) direction are tensile for the Ti3Al + Nb and Ti-15-3 composite systems upon cool down from fabrication. The fiber longitudinal stress is compressive from fabrication cool down. Addition of a recommended compliant layer will result in a reduction in the composite modulus.

Eigenvalue density of cross-correlations in Sri Lankan financial market

NASA Astrophysics Data System (ADS)

Nilantha, K. G. D. R.; Ranasinghe; Malmini, P. K. C.

2007-05-01

We apply the universal properties with Gaussian orthogonal ensemble (GOE) of random matrices namely spectral properties, distribution of eigenvalues, eigenvalue spacing predicted by random matrix theory (RMT) to compare cross-correlation matrix estimators from emerging market data. The daily stock prices of the Sri Lankan All share price index and Milanka price index from August 2004 to March 2005 were analyzed. Most eigenvalues in the spectrum of the cross-correlation matrix of stock price changes agree with the universal predictions of RMT. We find that the cross-correlation matrix satisfies the universal properties of the GOE of real symmetric random matrices. The eigen distribution follows the RMT predictions in the bulk but there are some deviations at the large eigenvalues. The nearest-neighbor spacing and the next nearest-neighbor spacing of the eigenvalues were examined and found that they follow the universality of GOE. RMT with deterministic correlations found that each eigenvalue from deterministic correlations is observed at values, which are repelled from the bulk distribution.

Channel correlation of free space optical communication systems with receiver diversity in non-Kolmogorov atmospheric turbulence

NASA Astrophysics Data System (ADS)

Ma, Jing; Fu, Yulong; Tan, Liying; Yu, Siyuan; Xie, Xiaolong

2018-05-01

Spatial diversity as an effective technique to mitigate the turbulence fading has been widely utilized in free space optical (FSO) communication systems. The received signals, however, will suffer from channel correlation due to insufficient spacing between component antennas. In this paper, the new expressions of the channel correlation coefficient and specifically its components (the large- and small-scale channel correlation coefficients) for a plane wave with aperture effects are derived for horizontal link in moderate-to-strong turbulence, using a non-Kolmogorov spectrum that has a generalized power law in the range of 3-4 instead of the fixed classical Kolmogorov power law of 11/3. And then the influence of power law variations on the channel correlation coefficient and its components are analysed. The numerical results indicated that various value of the power law lead to varying effects on the channel correlation coefficient and its components. This work will help with the further investigation on the fading correlation in spatial diversity systems.

Design of rapid hardening engineered cementitious composites for sustainable construction

NASA Astrophysics Data System (ADS)

Marushchak, Uliana; Sanytsky, Myroslav; Sydor, Nazar

2017-12-01

This paper deals with design of environmentally friendly Rapid Hardening Engineered Cementitious Composite (RHECC) nanomodified with ultrafine mineral additives, polycarboxylate ether based superplasticizer, calcium hydrosilicate nanoparticles and dispersal reinforced by fibers. The incremental coefficient of surface activity was proposed in order to estimation of ultrafine supplementary materials (fly ash, methakaolin, microsilica) efficiency. A characterization of RHECC's compressive and flexural properties at different ages is reported in this paper. Early compressive strength of ECC is 45-50 MPa, standard strength - 84-95 MPa and parameter Rc2/Rc28 - 65-70%. The microstructure of the cement matrix and RHECC was investigated. The use of ultrafine mineral supplementary materials provides reinforcement of structure on micro- and nanoscale level (cementing matrix) due to formation of sub-microreinforcing hydrate phase as AFt- and C-S-H phases in unclinker part of cement matrix, resulting in the phenomena of "self-reinforcement" on the microstructure level. Designed RHECC may be regarded as lower brittle since the crack resistance coefficient is higher comparison to conventional fine grain concrete.

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

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

NASA Astrophysics Data System (ADS)

Zhao, Jinping; Cao, Yong; Wang, Xin

2018-06-01

In order to study the temporal variations of correlations between two time series, a running correlation coefficient (RCC) could be used. An RCC is calculated for a given time window, and the window is then moved sequentially through time. The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient, calculated with the data within the time window, which we call the local running correlation coefficient (LRCC). The LRCC is calculated via the two anomalies corresponding to the two local means, meanwhile, the local means also vary. It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means. To address this problem, two unchanged means obtained from all available data are adopted to calculate an RCC, which is called the synthetic running correlation coefficient (SRCC). When the anomaly variations are dominant, the two RCCs are similar. However, when the variations of the means are dominant, the difference between the two RCCs becomes obvious. The SRCC reflects the correlations of both the anomaly variations and the variations of the means. Therefore, the SRCCs from different time points are intercomparable. A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data. The SRCC always meets this criterion, while the LRCC sometimes fails. Therefore, the SRCC is better than the LRCC for running correlations. We suggest using the SRCC to calculate the RCCs.

Research on soundproof properties of cylindrical shells of generalized phononic crystals

NASA Astrophysics Data System (ADS)

Liu, Ru; Shu, Haisheng; Wang, Xingguo

2017-04-01

Based on the previous studies, the concept of generalized phononic crystals (GPCs) is further introduced into the cylindrical shell structures in this paper. And a type of cylindrical shells of generalized phononic crystals (CS-GPCs) is constructed, the structural field and acoustic-structural coupled field of the composite cylindrical shells are examined respectively. For the structural field, the transfer matrix method of mechanical state vector is adopted to build the transfer matrix of radial waves propagating from inside to outside. For the acoustic-structural coupled field, the expressions of the acoustic transmission/reflection coefficients and the sound insulation of acoustic waves with the excitation of center line sound source are set up. And the acoustic transmission coefficient and the frequency response of sound insulation in this mode were numerical calculated. Furthermore, the theoretical analysis results are verified by using the method of combining the numerical calculation and finite element simulation. Finally, the effects of inner and outer fluid parameters on the transmission/reflection coefficients of CS-GPCs are analyzed in detail.

Basis Function Approximation of Transonic Aerodynamic Influence Coefficient Matrix

NASA Technical Reports Server (NTRS)

Li, Wesley W.; Pak, Chan-gi

2011-01-01

A technique for approximating the modal aerodynamic influence coefficients matrices by using basis functions has been developed and validated. An application of the resulting approximated modal aerodynamic influence coefficients matrix for a flutter analysis in transonic speed regime has been demonstrated. This methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The method requires the unsteady aerodynamics in frequency-domain. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root-locus et cetera. The unsteady aeroelastic analysis for design optimization using unsteady transonic aerodynamic approximation is being demonstrated using the ZAERO flutter solver (ZONA Technology Incorporated, Scottsdale, Arizona). The technique presented has been shown to offer consistent flutter speed prediction on an aerostructures test wing 2 configuration with negligible loss in precision in transonic speed regime. These results may have practical significance in the analysis of aircraft aeroelastic calculation and could lead to a more efficient design optimization cycle.

Linear and Nonlinear Optical Properties of Spherical Quantum Dots: Effects of Hydrogenic Impurity and Conduction Band Non-Parabolicity

NASA Astrophysics Data System (ADS)

Rezaei, G.; Vaseghi, B.; Doostimotlagh, N. A.

2012-03-01

Simultaneous effects of an on-center hydrogenic impurity and band edge non-parabolicity on intersubband optical absorption coefficients and refractive index changes of a typical GaAs/AlxGa1-x As spherical quantum dot are theoretically investigated, using the Luttinger—Kohn effective mass equation. So, electronic structure and optical properties of the system are studied by means of the matrix diagonalization technique and compact density matrix approach, respectively. Finally, effects of an impurity, band edge non-parabolicity, incident light intensity and the dot size on the linear, the third-order nonlinear and the total optical absorption coefficients and refractive index changes are investigated. Our results indicate that, the magnitudes of these optical quantities increase and their peaks shift to higher energies as the influences of the impurity and the band edge non-parabolicity are considered. Moreover, incident light intensity and the dot size have considerable effects on the optical absorption coefficients and refractive index changes.

Determine the permeability of an amorphous mixture of polydimethylsiloxane and dealuminated zeolite ZSM-5 to various ethanol-water solutions using molecular simulations.

EPA Science Inventory

An amorphous mixture of PDMS and multi-cellular fragments of ZSM-5 is brought together to approximate the properties of a mixed matrix membrane of PDMS with ZSM-5. The permeability coefficient of the amorphous mixture for pure water is the product of the diffusion coefficient of...

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Reflectionless CMV Matrices and Scattering Theory

NASA Astrophysics Data System (ADS)

Chu, Sherry; Landon, Benjamin; Panangaden, Jane

2015-04-01

Reflectionless CMV matrices are studied using scattering theory. By changing a single Verblunsky coefficient, a full-line CMV matrix can be decoupled and written as the sum of two half-line operators. Explicit formulas for the scattering matrix associated to the coupled and decoupled operators are derived. In particular, it is shown that a CMV matrix is reflectionless iff the scattering matrix is off-diagonal which in turn provides a short proof of an important result of Breuer et al. (Commun Math Phys 295:531-550, 2010). These developments parallel those recently obtained for Jacobi matrices Jakšić et al. (Commun Math Phys 827-838, 2014).

The temperature-dependent diffusion coefficient of helium in zirconium carbide studied with first-principles calculations

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

Yang, Xiao-Yong; Lu, Yong; Zhang, Ping, E-mail: zhang-ping@iapcm.ac.cn

2015-04-28

The temperature-dependent diffusion coefficient of interstitial helium in zirconium carbide (ZrC) matrix is calculated based on the transition state theory. The microscopic parameters in the activation energy and prefactor are obtained from first-principles total energy and phonon frequency calculations including the all atoms. The obtained activation energy is 0.78 eV, consistent with experimental value. Besides, we evaluated the influence of C and Zr vacancies as the perturbation on helium diffusion, and found the C vacancy seems to confine the mobility of helium and the Zr vacancy promotes helium diffusion in some extent. These results provide a good reference to understand themore » behavior of helium in ZrC matrix.« less

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.

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.

Multiscale polarization diagnostics of birefringent networks in problems of necrotic changes diagnostics

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Yu.; Ushenko, Yu. O.; Ushenko, V. O.; Besaha, R. N.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Wavelet analysis of birefringence images of myocardium tissue

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Yu.; Ushenko, Yu. O.; Kushnerik, L.; Soltys, I. V.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance

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

Putter, Roland de; Wagner, Christian; Verde, Licia

2012-04-01

Accurate power spectrum (or correlation function) covariance matrices are a crucial requirement for cosmological parameter estimation from large scale structure surveys. In order to minimize reliance on computationally expensive mock catalogs, it is important to have a solid analytic understanding of the different components that make up a covariance matrix. Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This beat coupling effect has been derived analytically in perturbation theory andmore » while it has been tested with simulations, some questions remain unanswered. Moreover, there is an additional effect of these large modes, which has so far not been included in analytic studies, namely the effect on the estimated average density which enters the power spectrum estimate. In this article, we work out analytic, perturbation theory based expressions including both the beat coupling and this local average effect and we show that while, when isolated, beat coupling indeed causes large excess covariance in agreement with the literature, in a realistic scenario this is compensated almost entirely by the local average effect, leaving only ∼ 10% of the excess. We test our analytic expressions by comparison to a suite of large N-body simulations, using both full simulation boxes and subboxes thereof to study cases without beat coupling, with beat coupling and with both beat coupling and the local average effect. For the variances, we find excellent agreement with the analytic expressions for k < 0.2 hMpc{sup −1} at z = 0.5, while the correlation coefficients agree to beyond k = 0.4 hMpc{sup −1}. As expected, the range of agreement increases towards higher redshift and decreases slightly towards z = 0. We finish by including the large-mode effects in a full covariance matrix description for arbitrary survey geometry and confirming its validity using simulations. This may be useful as a stepping stone towards building an actual galaxy (or other tracer's) power spectrum covariance matrix.« less

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Expression levels of matrix metalloproteinase-9 and gram-negative bacteria in symptomatic and asymptomatic periapical lesions.

PubMed

Ahmed, Geraldine M; El-Baz, Alaa A; Hashem, Ahmed Abdel Rahman; Shalaan, Abeer K

2013-04-01

The aim of this study was to test the hypothesis that the expression of matrix metalloproteinase (MMP)-9 is significantly elevated in patients with symptomatic apical periodontitis and to correlate this with the detected amount of gram-negative bacteria. Twenty-six patients with periapical lesions involving at least 2 teeth were included in this study. The patients were divided into 2 groups: the symptomatic (SYM) group included 13 patients expressing pain with periapical lesions, and the asymptomatic (ASYM) group included 13 patients expressing no pain. Root canal treatment was performed followed by endodontic surgery and periapical lesion collection. Periapical lesions were serially cut into 4-μ sections. Some sections were processed for histologic examination using hematoxylin-eosin stain. Other sections were processed for immunohistochemical examination. For MMP-9, the area fraction of the positive cells was measured, and the percentage of the MMP-9-immunopositive area to the total area of the microscopic field was calculated. For gram-negative stain cells, the number of cells showing the pink-red color was counted per microscopic field. The Student's t test was used to compare the SYM and ASYM groups. The Pearson correlation coefficient was used to determine a significant correlation between the number of cells and the MMP-9 level. The significance level was set at P ≤ .05. The SYM group showed a statistically significantly higher mean number of gram-negative cells (P = .001) and MMP-9 area percent (P < .001) than the ASYM group. There was a statistically significant positive (r = .927) correlation between the number of gram-negative cells and the MMP-9 area percent (P< .001). There is good evidence to suspect a significant role of gram-negative bacteria and MMP-9 in symptomatic periapical lesions. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

PubMed

Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R software is available at https://github.com/angy89/RobustSparseCorrelation. aserra@unisa.it or robtag@unisa.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Rapid and selective screening of melamine in bovine milk using molecularly imprinted matrix solid-phase dispersion coupled with liquid chromatography-ultraviolet detection.

PubMed

Yan, Hongyuan; Cheng, Xiaoling; Sun, Ning; Cai, Tianyu; Wu, Ruijun; Han, Kun

2012-11-01

A simple, convenient and high selective molecularly imprinted matrix solid-phase dispersion (MI-MSPD) using water-compatible cyromazine-imprinted polymer as adsorbent was proposed for the rapid screening of melamine from bovine milk coupled with liquid chromatography-ultraviolet detection. The molecularly imprinted polymers (MIPs) synthesized by cyromazine as dummy template and reformative methanol-water system as reaction medium showed higher affinity and selectivity to melamine, and so they were applied as the specific dispersant of MSPD to extraction of melamine and simultaneously eliminate the effect of template leakage on quantitative analysis. Under the optimized conditions, good linearity was obtained in a range of 0.24-60.0μgg(-1) with the correlation coefficient of 0.9994. The recoveries of melamine at three spiked levels were ranged from 86.0 to 96.2% with the relative standard deviation (RSD)≤4.0%. This proposed MI-MSPD method combined the advantages of MSPD and MIPs, and could be used as an alternative tool for analyzing the residues of melamine in complex milk samples. Copyright © 2012 Elsevier B.V. All rights reserved.

A rapid liquid chromatography tandem mass spectrometry-based method for measuring propranolol on dried blood spots.

PubMed

Della Bona, Maria Luisa; Malvagia, Sabrina; Villanelli, Fabio; Giocaliere, Elisa; Ombrone, Daniela; Funghini, Silvia; Filippi, Luca; Cavallaro, Giacomo; Bagnoli, Paola; Guerrini, Renzo; la Marca, Giancarlo

2013-05-05

Propranolol, a non-selective beta blocker drug, is used in young infants and newborns for treating several heart diseases; its pharmacokinetics has been extensively evaluated in adult patients using extrapolation to treat pediatric population. The purpose of the present study was to develop and validate a method to measure propranolol levels in dried blood spots. The analysis was performed by using liquid chromatography/tandem mass spectrometry operating in multiple reaction monitoring mode. The calibration curve in matrix was linear in the concentration range of 2.5-200 μg/L with correlation coefficient r=0.9996. Intra-day and inter-day precisions and biases were less than 8.0% (n=10) and 11.5% (n=10) respectively. The recoveries ranged from 94 to 100% and the matrix effect did not result in a severe signal suppression. Propranolol on dried blood spot showed a good stability at three different temperatures for one month. This paper describes a micromethod for measuring propranolol levels on dried blood spot, which determines a great advantage in neonates or young infants during pharmacokinetic studies because of less invasive sampling and small blood volume required. Copyright © 2013 Elsevier B.V. All rights reserved.

Determination of trigonelline, nicotinic acid, and caffeine in Yunnan Arabica coffee by microwave-assisted extraction and HPLC with two columns in series.

PubMed

Liu, Hongcheng; Shao, Jinliang; Li, Qiwan; Li, Yangang; Yan, Hong Mei; He, Lizhong

2012-01-01

A simple, rapid method was developed for simultaneous extraction of trigonelline, nicotinic acid, and caffeine from coffee, and separation by two chromatographic columns in series. The trigonelline, nicotinic acid, and caffeine were extracted with microwave-assisted extraction (MAE). The optimal conditions selected were 3 min, 200 psi, and 120 degrees C. The chromatographic separation was performed with two columns in series, polyaromatic hydrocarbon C18 (250 x 4.6 mm id, 5 microm particle size) and Bondapak NH2 (300 x 3.9 mm id, 5 microm particle size). Isocratic elution was with 0.02 M phosphoric acid-methanol (70 + 30, v/v) mobile phase at a flow rate of 0.8 mL/min. Good recoveries and RSD values were found for all analytes in the matrix. The LOD of the three compounds was 0.02 mg/L, and the LOQ was 0.005% in the matrix. The concentrations of trigonelline, nicotinic acid, and caffeine in instant coffee, roasted coffee, and raw coffee (Yunnan Arabica coffee) were assessed by MAE and hot water extraction; the correlation coefficients between concentrations of the three compounds obtained were close to 1.

Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

ERIC Educational Resources Information Center

Vos, Pauline

2009-01-01

When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

Diffusion of tricarboxylic acid cycle enzymes in the mitochondrial matrix in vivo. Evidence for restricted mobility of a multienzyme complex.

PubMed

Haggie, Peter M; Verkman, A S

2002-10-25

It has been proposed that enzymes in many metabolic pathways, including the tricarboxylic acid cycle in the mitochondrial matrix, are physically associated to facilitate substrate channeling and overcome diffusive barriers. We have used fluorescence recovery after photobleaching to measure the diffusional mobilities of chimeras consisting of green fluorescent protein (GFP) fused to the C terminus of four tricarboxylic acid cycle enzymes: malate dehydrogenase, citrate synthase, isocitrate dehydrogenase, and succinyl-CoA synthetase. The GFP-enzyme chimeras were localized selectively in the mitochondrial matrix in transfected Chinese hamster ovary (CHO) and COS7 cells. Laser photobleaching using a 0.7-microm diameter spot demonstrated restricted diffusion of the GFP-enzyme chimeras. Interestingly, all four chimeras had similar diffusional characteristics, approximately 45% of each chimera was mobile and had a diffusion coefficient of 4 x 10(-8) cm(2)/s. In contrast, unconjugated GFP in the mitochondrial matrix (targeted using COX8 leader sequence) diffused freely (nearly 100% mobility) with a greater diffusion coefficient of 20 x 10(-8) cm(2)/s. The mobility of the GFP-enzyme chimeras was insensitive to substrate source, ATP depletion, or inhibition of the adenine nucleotide translocase. These results indicate similar mobility characteristics of unrelated tricarboxylic acid cycle enzymes having different sizes and physical properties, providing biophysical evidence for a diffusible multienzyme complex in the mitochondrial matrix.

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Correlating PMC-MMC Bonded Joint 3D FEA with Test

NASA Technical Reports Server (NTRS)

Jacobson, Mindy; Rodini, Benjamin; Chen, Wayne C.; Flom, Yury A.; Posey, Alan J.

2005-01-01

A viewgraph presentation on the correlation of Polymer Matrix Composites (PMC) and Metal Matrix Composites (MMC) bonded joints using three dimensional finite element analyses with materials tests is shown.

Kinetic modelling of a diesel-polluted clayey soil bioremediation process.

PubMed

Fernández, Engracia Lacasa; Merlo, Elena Moliterni; Mayor, Lourdes Rodríguez; Camacho, José Villaseñor

2016-07-01

A mathematical model is proposed to describe a diesel-polluted clayey soil bioremediation process. The reaction system under study was considered a completely mixed closed batch reactor, which initially contacted a soil matrix polluted with diesel hydrocarbons, an aqueous liquid-specific culture medium and a microbial inoculation. The model coupled the mass transfer phenomena and the distribution of hydrocarbons among four phases (solid, S; water, A; non-aqueous liquid, NAPL; and air, V) with Monod kinetics. In the first step, the model simulating abiotic conditions was used to estimate only the mass transfer coefficients. In the second step, the model including both mass transfer and biodegradation phenomena was used to estimate the biological kinetic and stoichiometric parameters. In both situations, the model predictions were validated with experimental data that corresponded to previous research by the same authors. A correct fit between the model predictions and the experimental data was observed because the modelling curves captured the major trends for the diesel distribution in each phase. The model parameters were compared to different previously reported values found in the literature. Pearson correlation coefficients were used to show the reproducibility level of the model. Copyright © 2016. Published by Elsevier B.V.

Correlation between structural and transport properties of electron beam irradiated PrMnO3 compounds

NASA Astrophysics Data System (ADS)

Christopher, Benedict; Rao, Ashok; Nagaraja, B. S.; Shyam Prasad, K.; Okram, G. S.; Sanjeev, Ganesh; Petwal, Vikash Chandra; Verma, Vijay Pal; Dwivedi, Jishnu; Poornesh, P.

2018-02-01

The structural, electrical, magnetic, and thermal properties of electron beam (EB) irradiated PrMnO3 manganites were investigated in the present communication. X-ray diffraction data reveals that all samples are single phased with orthorhombic distorted structure (Pbnm). Furthermore, the diffracted data are analyzed in detail using Rietveld refinement technique. It is observed that the EB dosage feebly disturbs the MnO6 octahedra. The electrical resistivity of all the samples exhibits semiconducting behavior. Small polaron hopping model is conveniently employed to investigate the semiconducting nature of the pristine as well as EB irradiated samples. The Seebeck coefficient (S) of the pristine as well as the irradiated samples exhibit large positive values at lower temperatures, signifying holes as the dominant charge carriers. The analysis of Seebeck coefficient data confirms that the small polaron hopping mechanism assists the thermoelectric transport property in the high temperature region. The magnetic measurements confirm the existence of paramagnetic (PM) to ferromagnetic (FM) behavior for the pristine and irradiated samples. In the lower temperature regime, coexistence of FM clusters and AFM matrix is dominating. Thus, the complex magnetic behavior of the compound has been explained in terms of rearrangement of antiferromagnetically coupled ionic moments.

Sensing Membrane Stresses by Protein Insertions

PubMed Central

Campelo, Felix; Kozlov, Michael M.

2014-01-01

Protein domains shallowly inserting into the membrane matrix are ubiquitous in peripheral membrane proteins involved in various processes of intracellular membrane shaping and remodeling. It has been suggested that these domains sense membrane curvature through their preferable binding to strongly curved membranes, the binding mechanism being mediated by lipid packing defects. Here we make an alternative statement that shallow protein insertions are universal sensors of the intra-membrane stresses existing in the region of the insertion embedding rather than sensors of the curvature per se. We substantiate this proposal computationally by considering different independent ways of the membrane stress generation among which some include changes of the membrane curvature whereas others do not alter the membrane shape. Our computations show that the membrane-binding coefficient of shallow protein insertions is determined by the resultant stress independently of the way this stress has been produced. By contrast, consideration of the correlation between the insertion binding and the membrane curvature demonstrates that the binding coefficient either increases or decreases with curvature depending on the factors leading to the curvature generation. To validate our computational model, we treat quantitatively the experimental results on membrane binding by ALPS1 and ALPS2 motifs of ArfGAP1. PMID:24722359

Select-divide-and-conquer method for large-scale configuration interaction

NASA Astrophysics Data System (ADS)

Bunge, Carlos F.; Carbó-Dorca, Ramon

2006-07-01

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,…,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0≡{T0egy,T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates Ks with attributes above T1⩽T0. An eigenproblem of dimension d0+d1 for S0+S1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j ⩾2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0,1,2,…,R} regulate accuracy; for large-dimensional S, high accuracy requires S0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24×106, involving 1.2×1012 nonzero matrix elements, and 8.4×109 Slater determinants.

Thermal Expansion Behavior of Hot-Pressed Engineered Matrices

NASA Technical Reports Server (NTRS)

Raj, S. V.

2016-01-01

Advanced engineered matrix composites (EMCs) require that the coefficient of thermal expansion (CTE) of the engineered matrix (EM) matches those of the fiber reinforcements as closely as possible in order to reduce thermal compatibility strains during heating and cooling of the composites. The present paper proposes a general concept for designing suitable matrices for long fiber reinforced composites using a rule of mixtures (ROM) approach to minimize the global differences in the thermal expansion mismatches between the fibers and the engineered matrix. Proof-of-concept studies were conducted to demonstrate the validity of the concept.

Perturbed generalized multicritical one-matrix models

NASA Astrophysics Data System (ADS)

Ambjørn, J.; Chekhov, L.; Makeenko, Y.

2018-03-01

We study perturbations around the generalized Kazakov multicritical one-matrix model. The multicritical matrix model has a potential where the coefficients of zn only fall off as a power 1 /n s + 1. This implies that the potential and its derivatives have a cut along the real axis, leading to technical problems when one performs perturbations away from the generalized Kazakov model. Nevertheless it is possible to relate the perturbed partition function to the tau-function of a KdV hierarchy and solve the model by a genus expansion in the double scaling limit.

Continuum modeling of large lattice structures: Status and projections

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Mikulas, Martin M., Jr.

1988-01-01

The status and some recent developments of continuum modeling for large repetitive lattice structures are summarized. Discussion focuses on a number of aspects including definition of an effective substitute continuum; characterization of the continuum model; and the different approaches for generating the properties of the continuum, namely, the constitutive matrix, the matrix of mass densities, and the matrix of thermal coefficients. Also, a simple approach is presented for generating the continuum properties. The approach can be used to generate analytic and/or numerical values of the continuum properties.

TU-AB-BRA-05: Repeatability of [F-18]-NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

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

Lin, C; Bradshaw, T; Perk, T

2015-06-15

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative {sup 18}F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm{sup 3} for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)« less

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

Quantifying fluctuations in economic systems by adapting methods of statistical physics

NASA Astrophysics Data System (ADS)

Stanley, H. E.; Gopikrishnan, P.; Plerou, V.; Amaral, L. A. N.

2000-12-01

The emerging subfield of econophysics explores the degree to which certain concepts and methods from statistical physics can be appropriately modified and adapted to provide new insights into questions that have been the focus of interest in the economics community. Here we give a brief overview of two examples of research topics that are receiving recent attention. A first topic is the characterization of the dynamics of stock price fluctuations. For example, we investigate the relation between trading activity - measured by the number of transactions NΔ t - and the price change GΔ t for a given stock, over a time interval [t, t+ Δt] . We relate the time-dependent standard deviation of price fluctuations - volatility - to two microscopic quantities: the number of transactions NΔ t in Δ t and the variance WΔ t2 of the price changes for all transactions in Δ t. Our work indicates that while the pronounced tails in the distribution of price fluctuations arise from WΔ t, the long-range correlations found in ∣ GΔ t∣ are largely due to NΔ t. We also investigate the relation between price fluctuations and the number of shares QΔ t traded in Δ t. We find that the distribution of QΔ t is consistent with a stable Lévy distribution, suggesting a Lévy scaling relationship between QΔ t and NΔ t, which would provide one explanation for volume-volatility co-movement. A second topic concerns cross-correlations between the price fluctuations of different stocks. We adapt a conceptual framework, random matrix theory (RMT), first used in physics to interpret statistical properties of nuclear energy spectra. RMT makes predictions for the statistical properties of matrices that are universal, that is, do not depend on the interactions between the elements comprising the system. In physics systems, deviations from the predictions of RMT provide clues regarding the mechanisms controlling the dynamics of a given system, so this framework can be of potential value if applied to economic systems. We discuss a systematic comparison between the statistics of the cross-correlation matrix C - whose elements Cij are the correlation-coefficients between the returns of stock i and j - and that of a random matrix having the same symmetry properties. Our work suggests that RMT can be used to distinguish random and non-random parts of C; the non-random part of C, which deviates from RMT results provides information regarding genuine cross-correlations between stocks.

Performance analysis of structured gradient algorithm. [for adaptive beamforming linear arrays

NASA Technical Reports Server (NTRS)

Godara, Lal C.

1990-01-01

The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.

Group identification in Indonesian stock market

NASA Astrophysics Data System (ADS)

Nurriyadi Suparno, Ervano; Jo, Sung Kyun; Lim, Kyuseong; Purqon, Acep; Kim, Soo Yong

2016-08-01

The characteristic of Indonesian stock market is interesting especially because it represents developing countries. We investigate the dynamics and structures by using Random Matrix Theory (RMT). Here, we analyze the cross-correlation of the fluctuations of the daily closing price of stocks from the Indonesian Stock Exchange (IDX) between January 1, 2007, and October 28, 2014. The eigenvalue distribution of the correlation matrix consists of noise which is filtered out using the random matrix as a control. The bulk of the eigenvalue distribution conforms to the random matrix, allowing the separation of random noise from original data which is the deviating eigenvalues. From the deviating eigenvalues and the corresponding eigenvectors, we identify the intrinsic normal modes of the system and interpret their meaning based on qualitative and quantitative approach. The results show that the largest eigenvector represents the market-wide effect which has a predominantly common influence toward all stocks. The other eigenvectors represent highly correlated groups within the system. Furthermore, identification of the largest components of the eigenvectors shows the sector or background of the correlated groups. Interestingly, the result shows that there are mainly two clusters within IDX, natural and non-natural resource companies. We then decompose the correlation matrix to investigate the contribution of the correlated groups to the total correlation, and we find that IDX is still driven mainly by the market-wide effect.

Correlation Between Geometric Similarity of Ice Shapes and the Resulting Aerodynamic Performance Degradation: A Preliminary Investigation Using WIND

NASA Technical Reports Server (NTRS)

Wright, William B.; Chung, James

1999-01-01

Aerodynamic performance calculations were performed using WIND on ten experimental ice shapes and the corresponding ten ice shapes predicted by LEWICE 2.0. The resulting data for lift coefficient and drag coefficient are presented. The difference in aerodynamic results between the experimental ice shapes and the LEWICE ice shapes were compared to the quantitative difference in ice shape geometry presented in an earlier report. Correlations were generated to determine the geometric features which have the most effect on performance degradation. Results show that maximum lift and stall angle can be correlated to the upper horn angle and the leading edge minimum thickness. Drag coefficient can be correlated to the upper horn angle and the frequency-weighted average of the Fourier coefficients. Pitching moment correlated with the upper horn angle and to a much lesser extent to the upper and lower horn thicknesses.

Confidence Intervals and "F" Tests for Intraclass Correlation Coefficients Based on Three-Way Mixed Effects Models

ERIC Educational Resources Information Center

Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.

2011-01-01

Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…

The Feasibility of Analytic Models for Academic Planning: A Preliminary Analysis of Seven Quarters of Observations on the "Induced Course Load Matrix."

ERIC Educational Resources Information Center

Jewett, Frank I.; And Others

This paper reports on a project undertaken at Humboldt State College, California, to estimate the coefficients of the so-called "induced course load matrix," perhaps the single most vital component of some models that are being developed to aid administrative planning and decisionmaking in institutions of higher education. Chapter I, the…

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

Statistics of time delay and scattering correlation functions in chaotic systems. I. Random matrix theory

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

Novaes, Marcel

2015-06-15

We consider the statistics of time delay in a chaotic cavity having M open channels, in the absence of time-reversal invariance. In the random matrix theory approach, we compute the average value of polynomial functions of the time delay matrix Q = − iħS{sup †}dS/dE, where S is the scattering matrix. Our results do not assume M to be large. In a companion paper, we develop a semiclassical approximation to S-matrix correlation functions, from which the statistics of Q can also be derived. Together, these papers contribute to establishing the conjectured equivalence between the random matrix and the semiclassical approaches.

Correlation tests of the engine performance parameter by using the detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.

POLYMAT-C: a comprehensive SPSS program for computing the polychoric correlation matrix.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2015-09-01

We provide a free noncommercial SPSS program that implements procedures for (a) obtaining the polychoric correlation matrix between a set of ordered categorical measures, so that it can be used as input for the SPSS factor analysis (FA) program; (b) testing the null hypothesis of zero population correlation for each element of the matrix by using appropriate simulation procedures; (c) obtaining valid and accurate confidence intervals via bootstrap resampling for those correlations found to be significant; and (d) performing, if necessary, a smoothing procedure that makes the matrix amenable to any FA estimation procedure. For the main purpose (a), the program uses a robust unified procedure that allows four different types of estimates to be obtained at the user's choice. Overall, we hope the program will be a very useful tool for the applied researcher, not only because it provides an appropriate input matrix for FA, but also because it allows the researcher to carefully check the appropriateness of the matrix for this purpose. The SPSS syntax, a short manual, and data files related to this article are available as Supplemental materials that are available for download with this article.

On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms

NASA Astrophysics Data System (ADS)

Schaffrin, Burkhard; Felus, Yaron A.

2008-06-01

The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model ( Y- E Y = ( X- E X ) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E Y and E X . Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem by using the nonlinear Euler-Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition. For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335-342). The differences between the standard least-squares and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion matrix of the estimated parameters.

Construction of SO(5)⊃SO(3) spherical harmonics and Clebsch-Gordan coefficients

NASA Astrophysics Data System (ADS)

Caprio, M. A.; Rowe, D. J.; Welsh, T. A.

2009-07-01

The SO(5)⊃SO(3) spherical harmonics form a natural basis for expansion of nuclear collective model angular wave functions. They underlie the recently-proposed algebraic method for diagonalization of the nuclear collective model Hamiltonian in an SU(1,1)×SO(5) basis. We present a computer code for explicit construction of the SO(5)⊃SO(3) spherical harmonics and use them to compute the Clebsch-Gordan coefficients needed for collective model calculations in an SO(3)-coupled basis. With these Clebsch-Gordan coefficients it becomes possible to compute the matrix elements of collective model observables by purely algebraic methods. Program summaryProgram title: GammaHarmonic Catalogue identifier: AECY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 346 421 No. of bytes in distributed program, including test data, etc.: 16 037 234 Distribution format: tar.gz Programming language: Mathematica 6 Computer: Any which supports Mathematica Operating system: Any which supports Mathematica; tested under Microsoft Windows XP and Linux Classification: 4.2 Nature of problem: Explicit construction of SO(5) ⊃ SO(3) spherical harmonics on S. Evaluation of SO(3)-reduced matrix elements and SO(5) ⊃ SO(3) Clebsch-Gordan coefficients (isoscalar factors). Solution method: Construction of SO(5) ⊃ SO(3) spherical harmonics by orthonormalization, obtained from a generating set of functions, according to the method of Rowe, Turner, and Repka [1]. Matrix elements and Clebsch-Gordan coefficients follow by construction and integration of SO(3) scalar products. Running time: Depends strongly on the maximum SO(5) and SO(3) representation labels involved. A few minutes for the calculation in the Mathematica notebook. References: [1] D.J. Rowe, P.S. Turner, J. Repka, J. Math. Phys. 45 (2004) 2761.

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

A Practical Theory of Micro-Solar Power Sensor Networks

DTIC Science & Technology

2009-04-20

Simulation Platform TOSSIM [LLWC03] ns-2 Matlab C++ AVRORA [TLP05] Reference Hardware Mica2 WINS, Medusa Mica Mica2, Medusa Mica2 Simulated Power Power...scale. From this raw data, we can 162 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 Correlation coefficient F re qu en cy Histogram of correlation...0.5 0.6 0.7 0.8 0.9 1 0 1 2 Correlation coefficient F re qu en cy Histogram of correlation coefficient with solar radiation measurement (Turbidity at

A Stress Gradient Failure Theory for Textile Structural Composites

DTIC Science & Technology

2006-05-01

additional element failures occur. Incorporation of thermal stresses and investigation of the coefficient of thermal expansion is another potential...avenue for further development of the failure modeling. Due to mismatches between the coefficient of thermal expansion of constituent materials...directly from ABAQUS software, which yields element volumes as outputs, thus the volume of all matrix elements can be compared to the volume of all