partial correlation coefficients: Topics by WorldWideScience.org

Sample records for partial correlation coefficients

Clustering stocks using partial correlation coefficients

Science.gov (United States)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.
ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

Science.gov (United States)

Kim, Seongho

2015-11-01

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.
Clustering Coefficients for Correlation Networks

Directory of Open Access Journals (Sweden)

Naoki Masuda

2018-03-01

Full Text Available 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
Clustering Coefficients for Correlation Networks.

Science.gov (United States)

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
Clustering Coefficients for Correlation Networks

Science.gov (United States)

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
Partial distance correlation with methods for dissimilarities

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.

2014-01-01

Distance covariance and distance correlation are scalar coefficients that characterize independence of random vectors in arbitrary dimension. Properties, extensions, and applications of distance correlation have been discussed in the recent literature, but the problem of defining the partial distance correlation has remained an open question of considerable interest. The problem of partial distance correlation is more complex than partial correlation partly because the squared distance covari...
Partial Correlation Matrix Estimation using Ridge Penalty Followed by Thresholding and Reestimation

Science.gov (United States)

2014-01-01

Summary Motivated by the problem of construction gene co-expression network, we propose a statistical framework for estimating high-dimensional partial correlation matrix by a three-step approach. We first obtain a penalized estimate of a partial correlation matrix using ridge penalty. Next we select the non-zero entries of the partial correlation matrix by hypothesis testing. Finally we reestimate the partial correlation coefficients at these non-zero entries. In the second step, the null distribution of the test statistics derived from penalized partial correlation estimates has not been established. We address this challenge by estimating the null distribution from the empirical distribution of the test statistics of all the penalized partial correlation estimates. Extensive simulation studies demonstrate the good performance of our method. Application on a yeast cell cycle gene expression data shows that our method delivers better predictions of the protein-protein interactions than the Graphic Lasso. PMID:24845967
On the Kendall Correlation Coefficient

OpenAIRE

Stepanov, Alexei

2015-01-01

In the present paper, we first discuss the Kendall rank correlation coefficient. In continuous case, we define the Kendall rank correlation coefficient in terms of the concomitants of order statistics, find the expected value of the Kendall rank correlation coefficient and show that the later is free of n. We also prove that in continuous case the Kendall correlation coefficient converges in probability to its expected value. We then propose to consider the expected value of the Kendall rank ...
Correlation coefficients in neutron β-decay

International Nuclear Information System (INIS)

Byrne, J.

1978-01-01

The various angular and polarisation coefficients in neutron decay are the principal sources of information on the β-interaction. Measurements of the electron-neutrino angular correlation coefficient (a), the neutron-spin-electron-momentum correlation coefficient (A), the neutron-spin-neutrino-momentum correlation coefficient (B), and the triple correlation coefficient D and time-reversal invariance are reviewed and the results discussed. (U.K.)
Wavelet Correlation Coefficient of 'strongly correlated' financial time series

OpenAIRE

Razdan, Ashok

2003-01-01

In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two variables. In econophysics correlation coefficient forms important input to evolve hierarchial tree and minimum spanning tree of financial data.
Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation.

Science.gov (United States)

Ha, Min Jin; Sun, Wei

2014-09-01

Motivated by the problem of construction of gene co-expression network, we propose a statistical framework for estimating high-dimensional partial correlation matrix by a three-step approach. We first obtain a penalized estimate of a partial correlation matrix using ridge penalty. Next we select the non-zero entries of the partial correlation matrix by hypothesis testing. Finally we re-estimate the partial correlation coefficients at these non-zero entries. In the second step, the null distribution of the test statistics derived from penalized partial correlation estimates has not been established. We address this challenge by estimating the null distribution from the empirical distribution of the test statistics of all the penalized partial correlation estimates. Extensive simulation studies demonstrate the good performance of our method. Application on a yeast cell cycle gene expression data shows that our method delivers better predictions of the protein-protein interactions than the Graphic Lasso. © 2014, The International Biometric Society.
Estimation of the simple correlation coefficient.

Science.gov (United States)

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.
Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

Science.gov (United States)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.
Estimating varying coefficients for partial differential equation models.

Science.gov (United States)

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2017-09-01

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.
Correlation Coefficients: Appropriate Use and Interpretation.

Science.gov (United States)

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.
A new proposal for Lagrangian correlation coefficient

International Nuclear Information System (INIS)

Altinsoy, N.; Tugrul, A.B.

2002-01-01

The statistical description of dispersion in turbulent flow was first considered by Taylor (Proc. London Math. Soc. 20 (1921) 196) and the statistical properties of the field were determined by Lagrangian correlation coefficient R L (τ). Frenkiel (Adv. Appl. Mech. 3 (1953) 61) has proposed several simple forms for R L (τ). Some workers have investigated for a proper form of the Lagrangian correlation coefficient. In this work, a new proposal for the Lagrangian correlation coefficient is proposed and discussed. It can be written in general form with the one of the Frenkiel's (Adv. Appl. Mech. 3 (1953) 61) Lagrangian correlation coefficient. There is very satisfactory agreement between the new correlation and the experiment
Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

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Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.
Temporal correlation coefficient for directed networks.

Science.gov (United States)

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.
Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

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).
Alternatives to Pearson's and Spearman's Correlation Coefficients

OpenAIRE

Smarandache, Florentin

2008-01-01

This article presents several alternatives to Pearson's correlation coefficient and many examples. In the samples where the rank in a discrete variable counts more than the variable values, the mixtures that we propose of Pearson's and Spearman's correlation coefficients give better results.

Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis

OpenAIRE

Zhao, Feng

2013-01-01

In Modern Portfolio Theory, the correlation coefficients decide the risk of a set of stocks in the portfolio. So, to understand the correlation coefficients between returns of stocks, is a challenge but is very important for the portfolio management. Usually, the stocks with small correlation coefficients or even negative correlation coefficients are preferred. One can calculate the correlation coefficients of stock returns based on the historical stock data. However, in order to control the ...
A Coefficient of Association Between Categorical Variables With Partial or Tentative Ordering of Categories

DEFF Research Database (Denmark)

Siersma, Volkert; Kreiner, Svend

2009-01-01

Goodman and Kruskal's gamma coefficient measuring monotone association and its partial variants are useful for the analysis of multiway contingency tables containing ordinal variables. When the categories of a variable are only partly ordered and the variable is treated as a nominal variable......, information in the ordering of the categories and statistical power is lost. The authors suggest a (P)gamma measure that is the maximum of the ordinary gamma coefficients obtained by permuting the categories of nominal or partially ordered variables, while leaving the partial ordering intact. When...... of the (P)gamma coefficient are investigated in a simulation study and its use illustrated in two data sets....
Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

OpenAIRE

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

Science.gov (United States)

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.
[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

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.
Object detection by correlation coefficients using azimuthally averaged reference projections.

Science.gov (United States)

Nicholson, William V

2004-11-01

A method of computing correlation coefficients for object detection that takes advantage of using azimuthally averaged reference projections is described and compared with two alternative methods-computing a cross-correlation function or a local correlation coefficient versus the azimuthally averaged reference projections. Two examples of an application from structural biology involving the detection of projection views of biological macromolecules in electron micrographs are discussed. It is found that a novel approach to computing a local correlation coefficient versus azimuthally averaged reference projections, using a rotational correlation coefficient, outperforms using a cross-correlation function and a local correlation coefficient in object detection from simulated images with a range of levels of simulated additive noise. The three approaches perform similarly in detecting macromolecular views in electron microscope images of a globular macrolecular complex (the ribosome). The rotational correlation coefficient outperforms the other methods in detection of keyhole limpet hemocyanin macromolecular views in electron micrographs.
Variable Selection via Partial Correlation.

Science.gov (United States)

Li, Runze; Liu, Jingyuan; Lou, Lejia

2017-07-01

Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper addresses two important issues related to partial correlation based variable selection method: (a) whether this method is sensitive to normality assumption, and (b) whether this method is valid when the dimension of predictor increases in an exponential rate of the sample size. To address issue (a), we systematically study this method for elliptical linear regression models. Our finding indicates that the original proposal may lead to inferior performance when the marginal kurtosis of predictor is not close to that of normal distribution. Our simulation results further confirm this finding. To ensure the superior performance of partial correlation based variable selection procedure, we propose a thresholded partial correlation (TPC) approach to select significant variables in linear regression models. We establish the selection consistency of the TPC in the presence of ultrahigh dimensional predictors. Since the TPC procedure includes the original proposal as a special case, our theoretical results address the issue (b) directly. As a by-product, the sure screening property of the first step of TPC was obtained. The numerical examples also illustrate that the TPC is competitively comparable to the commonly-used regularization methods for variable selection.
The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

Science.gov (United States)

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.
Accounting for Missing Correlation Coefficients in Fixed-Effects MASEM.

Science.gov (United States)

Jak, Suzanne; Cheung, Mike W-L

2018-01-01

Meta-analytic structural equation modeling (MASEM) is increasingly applied to advance theories by synthesizing existing findings. MASEM essentially consists of two stages. In Stage 1, a pooled correlation matrix is estimated based on the reported correlation coefficients in the individual studies. In Stage 2, a structural model (such as a path model) is fitted to explain the pooled correlations. Frequently, the individual studies do not provide all the correlation coefficients between the research variables. In this study, we modify the currently optimal MASEM-method to deal with missing correlation coefficients, and compare its performance with existing methods. This study is the first to evaluate the performance of fixed-effects MASEM methods under different levels of missing correlation coefficients. We found that the often used univariate methods performed very poorly, while the multivariate methods performed well overall.
New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models

Directory of Open Access Journals (Sweden)

Yunbei Ma

2014-01-01

Full Text Available In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.
Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

Science.gov (United States)

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

Science.gov (United States)

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
General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

OpenAIRE

WenJun Zhang; Xin Li

2015-01-01

Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...
Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

Science.gov (United States)

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.
A Note on the Correlated Random Coefficient Model

DEFF Research Database (Denmark)

Kolodziejczyk, Christophe

In this note we derive the bias of the OLS estimator for a correlated random coefficient model with one random coefficient, but which is correlated with a binary variable. We provide set-identification to the parameters of interest of the model. We also show how to reduce the bias of the estimator...
Limits of the memory coefficient in measuring correlated bursts

Science.gov (United States)

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.
Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.

Science.gov (United States)

Mejia, Amanda F; Nebel, Mary Beth; Barber, Anita D; Choe, Ann S; Pekar, James J; Caffo, Brian S; Lindquist, Martin A

2018-05-15

Reliability of subject-level resting-state functional connectivity (FC) is determined in part by the statistical techniques employed in its estimation. Methods that pool information across subjects to inform estimation of subject-level effects (e.g., Bayesian approaches) have been shown to enhance reliability of subject-level FC. However, fully Bayesian approaches are computationally demanding, while empirical Bayesian approaches typically rely on using repeated measures to estimate the variance components in the model. Here, we avoid the need for repeated measures by proposing a novel measurement error model for FC describing the different sources of variance and error, which we use to perform empirical Bayes shrinkage of subject-level FC towards the group average. In addition, since the traditional intra-class correlation coefficient (ICC) is inappropriate for biased estimates, we propose a new reliability measure denoted the mean squared error intra-class correlation coefficient (ICC MSE ) to properly assess the reliability of the resulting (biased) estimates. We apply the proposed techniques to test-retest resting-state fMRI data on 461 subjects from the Human Connectome Project to estimate connectivity between 100 regions identified through independent components analysis (ICA). We consider both correlation and partial correlation as the measure of FC and assess the benefit of shrinkage for each measure, as well as the effects of scan duration. We find that shrinkage estimates of subject-level FC exhibit substantially greater reliability than traditional estimates across various scan durations, even for the most reliable connections and regardless of connectivity measure. Additionally, we find partial correlation reliability to be highly sensitive to the choice of penalty term, and to be generally worse than that of full correlations except for certain connections and a narrow range of penalty values. This suggests that the penalty needs to be chosen carefully
Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

Science.gov (United States)

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.
Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI.

Science.gov (United States)

Rakheja, Rajan; Chandarana, Hersh; DeMello, Linda; Jackson, Kimberly; Geppert, Christian; Faul, David; Glielmi, Christopher; Friedman, Kent P

2013-11-01

The purpose of this study was to assess the correlation between standardized uptake value (SUV) and apparent diffusion coefficient (ADC) of neoplastic lesions in the use of a simultaneous PET/MRI hybrid system. Twenty-four patients with known primary malignancies underwent FDG PET/CT. They then underwent whole-body PET/MRI. Diffusion-weighted imaging was performed with free breathing and a single-shot spin-echo echo-planar imaging sequence with b values of 0, 350, and 750 s/mm(2). Regions of interest were manually drawn along the contours of neoplastic lesions larger than 1 cm, which were clearly identified on PET and diffusion-weighted images. Maximum SUV (SUVmax) on PET/MRI and PET/CT images, mean SUV (SUVmean), minimum ADC (ADCmin), and mean ADC (ADCmean) were recorded on PET/MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient. Pearson correlation coefficient was used to asses the following relations: SUVmax versus ADCmin on PET/MR and PET/CT images, SUVmean versus ADCmean, and ratio of SUVmax to mean liver SUV (SUV ratio) versus ADCmin. A subanalysis of patients with progressive disease versus partial treatment response was performed with the ratio of SUVmax to ADCmin for the most metabolically active lesion. Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. A significant inverse Pearson correlation coefficient was found between PET/MRI SUVmax and ADCmin (r = -0.21, p = 0.04), between SUVmean and ADCmean (r = -0.18, p = 0.07), and between SUV ratio and ADCmin (r = -0.27, p = 0.01). A similar inverse Pearson correlation coefficient was found between the PET/CT SUVmax and ADCmin. Twenty of 24 patients had previously undergone PET/CT; five patients had a partial treatment response, and six had progressive disease according to Response Evaluation
Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

Science.gov (United States)

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.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

Science.gov (United States)

van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

2018-06-01

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.
Partial differential equations II elements of the modern theory equations with constant coefficients

CERN Document Server

Shubin, M

1994-01-01

This book, the first printing of which was published as Volume 31 of the Encyclopaedia of Mathematical Sciences, contains a survey of the modern theory of general linear partial differential equations and a detailed review of equations with constant coefficients. Readers will be interested in an introduction to microlocal analysis and its applications including singular integral operators, pseudodifferential operators, Fourier integral operators and wavefronts, a survey of the most important results about the mixed problem for hyperbolic equations, a review of asymptotic methods including short wave asymptotics, the Maslov canonical operator and spectral asymptotics, a detailed description of the applications of distribution theory to partial differential equations with constant coefficients including numerous interesting special topics.
Pearson's correlation coefficient in the theory of networks: A comment

OpenAIRE

Ahmed, Zafar; Kumar, Sachin

2018-01-01

In statistics, the Pearson correlation coefficient $r_{x,y}$ determines the degree of linear correlation between two variables and it is known that $-1 \\le r_{x,y} \\le 1$. In the theory of networks, a curious expression proposed in [PRL {\\bf 89} 208701 (2002)] for degree-degree correlation coefficient $r_{j_i,k_i}, i\\in [1,M]$ has been in use. We realize that the suggested form is the conventional Pearson's coefficient for $\\{(j_i,k_i), (k_i,j_i)\\}$ for $2M$ data points and hence it is rightl...
Analytic posteriors for Pearson's correlation coefficient.

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Ly, Alexander; Marsman, Maarten; Wagenmakers, Eric-Jan

2018-02-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open-source software package JASP.
Analytic posteriors for Pearson's correlation coefficient

OpenAIRE

Ly, A.; Marsman, M.; Wagenmakers, E.-J.

2018-01-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open‐source software package JASP.
Correlation between factors associated with the removable partial dentures use and Candida spp. in saliva.

Science.gov (United States)

Gusmão, João Milton Rocha; Ferreira dos Santos, Silvana Soleo; Neisser, Maximiliano Piero; Jorge, Antônio Olavo Cardoso; Faria, Ms Ivan

2011-12-01

To correlate the presence and number of Candida spp. in the saliva of wearers of removable partial dentures retained with precision attachments with the proportion of metal/acrylic resin present in the dentures. Saliva samples from 40 removable partial denture wearers (test) and one paired sample of individuals, non-wearers of any type of removable denture (control) were collected, seeded, and the colony forming units of Candida counted and identified. The metal/acrylic resin proportion of each denture was quantified, using silicone plates pressed over each denture. Candida spp. was found in the saliva of 80% of the individuals in the test group and 65% of the control, with C. albicans being the most prevalent species. The test group presented with the highest number of colony forming units of Candida per ml of saliva, and there was weak correlation between this number and the metal and resin area of the denture (Pearson's coefficient of correlation). Greater prevalence and a higher number of colony forming units of Candida per ml of saliva occurred in removable partial denture wearers (p = 0.04) with a weak positive correlation between the metal and resin area and the number of colony forming units of Candida per ml of saliva. However, this correlation was more significant for the area of resin. © 2010 The Gerodontology Society and John Wiley & Sons A/S.
Partial inelasticity coefficients of negative pions produced in hadron-nucleus and nucleus-nucleus collisions at high energies

International Nuclear Information System (INIS)

OLIMOV, K.; LUTPULLAEV, S.L.; PETROV, V.I.; OLIMOV, A.K.

2015-01-01

New experimental data on the partial inelasticity coefficients of negative pions produced in "1"6Op-collisions at 3.25 A GeV/s, pC-interactions at 4.2 and 9.9 GeV/s, and d,α,C(C)-collisions at 4.2 A GeV/s are presented. It is established that the behavior of partial inelasticity coefficients of pions at intermediate energies (<10 GeV) in hadron-nucleus collisions has a transitional character, reaching the limiting value at ultrahigh energies. It is shown that the mean values of partial inelasticity coefficients of pions produced in nucleus-nucleus collisions decrease with an increase in mass number of the projectile nucleus. (authors)
Partial Coefficient System for the Design of Monolithic Vertical Breakwaters Considering Sliding and Rupture Failure of the Foundation

DEFF Research Database (Denmark)

Burcharth, Hans F.; Christiani, Erik; Sørensen, John Dalsgaard

1995-01-01

The main object is to present a set of calibrated partial coefficients for monolithic vertical breakwater failure modes. A preliminary design of the monolithic breakwater will be considered, which will be designed from existing partial coefficients, documented in Eurocode 7 (1994). From this desi...
Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

Science.gov (United States)

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.
Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

Science.gov (United States)

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…
Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

Science.gov (United States)

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.
Correlation and prediction of gaseous diffusion coefficients.

Science.gov (United States)

Marrero, T. R.; Mason, E. A.

1973-01-01

A new correlation method for binary gaseous diffusion coefficients from very low temperatures to 10,000 K is proposed based on an extended principle of corresponding states, and having greater range and accuracy than previous correlations. There are two correlation parameters that are related to other physical quantities and that are predictable in the absence of diffusion measurements. Quantum effects and composition dependence are included, but high-pressure effects are not. The results are directly applicable to multicomponent mixtures.
The Evolution of Pearson's Correlation Coefficient

Science.gov (United States)

Kader, Gary D.; Franklin, Christine A.

2008-01-01

This article describes an activity for developing the notion of association between two quantitative variables. By exploring a collection of scatter plots, the authors propose a nonstandard "intuitive" measure of association; and by examining properties of this measure, they develop the more standard measure, Pearson's Correlation Coefficient. The…
A default Bayesian hypothesis test for correlations and partial correlations

NARCIS (Netherlands)

Wetzels, R.; Wagenmakers, E.J.

2012-01-01

We propose a default Bayesian hypothesis test for the presence of a correlation or a partial correlation. The test is a direct application of Bayesian techniques for variable selection in regression models. The test is easy to apply and yields practical advantages that the standard frequentist tests
Research on partial coefficients for design of quarter-circular caisson breakwater

Science.gov (United States)

Qie, Luwen; Zhang, Xiang; Jiang, Xuelian; Qin, Yinan

2013-03-01

The quarter-circular caisson breakwater (QCB) is a new type of breakwater, and it can be applied in deepwater. The stability of QCB under wave force action can be enhanced, and the rubble mound engineering can be less than that of semi-circular breakwaters in deepwater. In order to study the wave force distribution acting on the QCB, to find wave force formula for this type of breakwater, firstly in this paper, the distribution characteristics of the horizontal force, the downward vertical force and the uplift force on the breakwater were gotten based on physical model wave flume experiments and on the analysis of the wave pressure experimental data. Based on a series of physical model tests acted by irregular waves, a kind of calculation method, which was modified by Goda formula, was proposed to carry out the wave force on the QCB. Secondly, the reliability method with correlated variables was adopted to analyze the QCB, considering the high correlation between wave forces or moments. Utilizing the observed wave data in engineering field, the reliability index and failure probability of QCB were obtained. Finally, a factor Q=0.9 is given to modify the zero pressure height above SWL of QCB, and wave force partial coefficient 1.34 to the design expressions of QCB for anti-sliding, as well as 1.67 for anti-overturning, were presented.
THE ROWWISE CORRELATION BETWEEN 2 PROXIMITY MATRICES AND THE PARTIAL ROWWISE CORRELATION

NARCIS (Netherlands)

de Vries, Han

This paper discusses rowwise matrix correlation, based on the weighted sum of correlations between all pairs of corresponding rows of two proximity matrices, which may both be square (symmetric or asymmetric) or rectangular. Using the correlation coefficients usually associated with Pearson,
A new correlation for two-phase critical discharge coefficient

International Nuclear Information System (INIS)

Park, Jong Woon; Chun, Moon Hyun

1989-01-01

A new simple correlation for subcooled and two-phase critical flow discharge coefficient has been developed by stepwise regression technique. The new discharge coefficient has three independent variables and they are length to hydraulic diameter ratio, degree of subcooling, and stagnation temperature. The new discharge coefficient is applied as a multiplier to homogeneous equilibrium model and Abauf's single phase critical mass flux calculation equation. This method has been tested for its accuracy by comparing with experimental data. Results of the comparison show that the agreement between the predictions with new correlation and the experimental data is good for pipes and nozzles with vertical upward flow for subcooled upstream condition and nozzles with horizontal configuration for two-phase upstream condition
Comparing two K-category assignments by a K-category correlation coefficient

DEFF Research Database (Denmark)

Gorodkin, Jan

2004-01-01

Predicted assignments of biological sequences are often evaluated by Matthews correlation coefficient. However, Matthews correlation coefficient applies only to cases where the assignments belong to two categories, and cases with more than two categories are often artificially forced into two...... categories by considering what belongs and what does not belong to one of the categories, leading to the loss of information. Here, an extended correlation coefficient that applies to K-categories is proposed, and this measure is shown to be highly applicable for evaluating prediction of RNA secondary...
Nonlinear perturbations of systems of partial differential equations with constant coefficients

Directory of Open Access Journals (Sweden)

Carmen J. Vanegas

2000-01-01

Full Text Available In this article, we show the existence of solutions to boundary-value problems, consisting of nonlinear systems of partial differential equations with constant coefficients. For this purpose, we use the right inverse of an associated operator and a fix point argument. As illustrations, we apply this method to Helmholtz equations and to second order systems of elliptic equations.
A comparison of two indices for the intraclass correlation coefficient.

Science.gov (United States)

Shieh, Gwowen

2012-12-01

In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.

Distributing Correlation Coefficients of Linear Structure-Activity/Property Models

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Sorana D. BOLBOACA

2011-12-01

Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.
Multi criteria decision making using correlation coefficient under rough neutrosophic environment

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Surapati Pramanik

2017-09-01

Full Text Available In this paper, we define correlation coefficient measure between any two rough neutrosophic sets. We also prove some of its basic properties.. We develop a new multiple attribute group decision making method based on the proposed correlation coefficient measure.
Detecting genuine multipartite correlations in terms of the rank of coefficient matrix

International Nuclear Information System (INIS)

Li Bo; Kwek, Leong Chuan; Fan Heng

2012-01-01

We propose a method to detect genuine quantum correlation for arbitrary quantum states in terms of the rank of coefficient matrices associated with the pure state. We then derive a necessary and sufficient condition for a quantum state to possess genuine correlation, namely that all corresponding coefficient matrices have rank larger than 1. We demonstrate an approach to decompose the genuine quantum correlated state with high rank coefficient matrix into the form of product states with no genuine quantum correlation for a pure state. (paper)
Statistical electron correlation coefficients for the five lowest states of the heliumlike ions

International Nuclear Information System (INIS)

Thakkar, A.J.; Smith, V.H. Jr.

1981-01-01

Statistical correlation coefficients were introduced by Kutzelnigg, Del Re, and Berthier to provide overall measures of the difference between the electron pair density and the product of one-electron densities in atoms and molecules. Some properties of these coefficients are discussed, and it is shown that an angular correlation coefficient is experimentally accessible. Radial and angular correlation coefficients are computed from highly accurate wave functions for the 1 1 S, 2 3 S, 2 1 S, 2 3 P, and 2 1 P states of the heliumlike ions from He through Mg 10+ . It is found that positive angular correlation coefficients occur in the 2 1 P state of the two-electron positive ions but not in neutral helium. Moreover, the angular correlation coefficients for the 2 1 S and 2 3 S states of the positively charged two-electron ions show that a previously proposed reformulation of Hund's rule is incorrect
Quantized correlation coefficient for measuring reproducibility of ChIP-chip data

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Kuroda Mitzi I

2010-07-01

Full Text Available Abstract Background 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. Results 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. Conclusions 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.
Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

Science.gov (United States)

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.
Generalization of Clustering Coefficients to Signed Correlation Networks

Science.gov (United States)

Costantini, Giulio; Perugini, Marco

2014-01-01

The recent interest in network analysis applications in personality psychology and psychopathology has put forward new methodological challenges. Personality and psychopathology networks are typically based on correlation matrices and therefore include both positive and negative edge signs. However, some applications of network analysis disregard negative edges, such as computing clustering coefficients. In this contribution, we illustrate the importance of the distinction between positive and negative edges in networks based on correlation matrices. The clustering coefficient is generalized to signed correlation networks: three new indices are introduced that take edge signs into account, each derived from an existing and widely used formula. The performances of the new indices are illustrated and compared with the performances of the unsigned indices, both on a signed simulated network and on a signed network based on actual personality psychology data. The results show that the new indices are more resistant to sample variations in correlation networks and therefore have higher convergence compared with the unsigned indices both in simulated networks and with real data. PMID:24586367
Multi criteria decision making using correlation coefficient under rough neutrosophic environment

OpenAIRE

Pramanik, Surapati; Roy, Rumi; Roy, Tapan Kumar; Smarandache, Florentin

2017-01-01

In this paper, we define correlation coefficient measure between any two rough neutrosophic sets. We also prove some of its basic properties. We develop a new multiple attribute group decision making method based on the proposed correlation coefficient measure. An illustrative example of medical diagnosis is solved to demonstrate the applicability and effecriveness of the proposed method.
Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

Science.gov (United States)

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 (pcorrelated 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 Coefficients of Probabilistic Hesitant Fuzzy Elements and Their Applications to Evaluation of the Alternatives

Directory of Open Access Journals (Sweden)

Zhong-xing Wang

2017-11-01

Full Text Available Correlation coefficient is one of the broadly use indexes in multi-criteria decision-making (MCDM processes. However, some important issues related to correlation coefficient utilization within probabilistic hesitant fuzzy environments remain to be addressed. The purpose of this study is introduced a MCDM method based on correlation coefficients utilize probabilistic hesitant fuzzy information. First, the covariance and correlation coefficient between two PHFEs is introduced, the properties of the proposed covariance and correlation coefficient are discussed. In addition, the northwest corner rule to obtain the expected mean related to the multiply of two PHFEs is introduced. Second, the weighted correlation coefficient is proposed to make the proposed MCDM method more applicable. And the properties of the proposed weighted correlation coefficient are also discussed. Finally, an illustrative example is demonstrated the practicality and effectiveness of the proposed method. An illustrative example is presented to demonstrate the correlation coefficient propose in this paper lies in the interval [−1, 1], which not only consider the strength of relationship between the PHFEs but also whether the PHFEs are positively or negatively related. The advantage of this method is it can avoid the inconsistency of the decision-making result due to the loss of information.
[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

Science.gov (United States)

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.
Octanol-Water Partition Coefficient from 3D-RISM-KH Molecular Theory of Solvation with Partial Molar Volume Correction.

Science.gov (United States)

Huang, WenJuan; Blinov, Nikolay; Kovalenko, Andriy

2015-04-30

The octanol-water partition coefficient is an important physical-chemical characteristic widely used to describe hydrophobic/hydrophilic properties of chemical compounds. The partition coefficient is related to the transfer free energy of a compound from water to octanol. Here, we introduce a new protocol for prediction of the partition coefficient based on the statistical-mechanical, 3D-RISM-KH molecular theory of solvation. It was shown recently that with the compound-solvent correlation functions obtained from the 3D-RISM-KH molecular theory of solvation, the free energy functional supplemented with the correction linearly related to the partial molar volume obtained from the Kirkwood-Buff/3D-RISM theory, also called the "universal correction" (UC), provides accurate prediction of the hydration free energy of small compounds, compared to explicit solvent molecular dynamics [ Palmer , D. S. ; J. Phys.: Condens. Matter 2010 , 22 , 492101 ]. Here we report that with the UC reparametrized accordingly this theory also provides an excellent agreement with the experimental data for the solvation free energy in nonpolar solvent (1-octanol) and so accurately predicts the octanol-water partition coefficient. The performance of the Kovalenko-Hirata (KH) and Gaussian fluctuation (GF) functionals of the solvation free energy, with and without UC, is tested on a large library of small compounds with diverse functional groups. The best agreement with the experimental data for octanol-water partition coefficients is obtained with the KH-UC solvation free energy functional.
Highlighting material structure with transmission electron diffraction correlation coefficient maps

International Nuclear Information System (INIS)

Kiss, Ákos K.; Rauch, Edgar F.; Lábár, János L.

2016-01-01

Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast. - Highlights: • We propose a novel technique to image the structure of polycrystalline TEM-samples. • Correlation coefficients maps highlights the evolution of the diffracting signal. • 3D views of grain boundaries are provided for nano-particles or polycrystals.
Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.

Science.gov (United States)

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.
Earning on Response Coefficient in Automobile and Go Public Companies

Directory of Open Access Journals (Sweden)

Lisdawati Arifin

2017-09-01

Full Text Available This study aims to analyze factors that influence earnings response coefficients (ERC, simultaneously and partially, composed of leverage, the systematic risk (beta, growth opportunities (market to book value ratio, and the size of the firm (firm size, selection of the sample in this study the author take 12 automakers and components that meet the criteria of completeness of the data from the year 2008 to 2012, entirely based on consideration of the following criteria: (1 the company's automotive and components are listed on the stock exchange, (2 have the financial statements years 2008-2012 (3 has a return data (closing price the first day after the date of issuance of the financial statements. This study uses secondary data applying multiple linear regression models to analyze and test the effect of independent variables on the dependent variable partially (t-test, simultaneous (f-test, and the goodness of fit (R-square on a research model. The result shows that leverage, beta, growth opportunities (market to book value ratio and size along with (simultaneously the effect on the dependent variable (dependent variable earnings response coefficients. Partially leverage negatively affect earnings response coefficients, partially beta negatively correlated earnings response coefficients, partially growth opportunities (market to book value ratio significant effect on earnings response coefficients, partially sized companies (firm size significantly influence earnings response coefficients.
A correlation to the heat transfer coefficient in nucleate boiling

International Nuclear Information System (INIS)

Ribatski, Gherhardt; Jabardo, Jose M. Saiz

1999-01-01

Nucleate boiling heat transfer is a complex phenomenon, making the development of a correlation for the heat transfer coefficient rather cumbersome due to the number of physical parameters involved in it. Some authors have followed a pragmatic approach to the problem by correlating the heat transfer coefficient in terms of reduced primitive properties. Two of the most knowledgeable authors who have followed this approach are Gorenflo and Cooper. Comparisons have been performed among results from the correlations proposed by these researchers and experimental results obtained elsewhere for refrigerants R-11, R-113 and R-114. These comparisons have shown that Cooper's correlation is best fitted for halocarbon refrigerants. The correlation proposed by Gorenflo ads the difficulty of including a numerical factor specific for each fluid. Leiner modified Gorenflo's correlation to determine the numerical factor as a function of known physical parameters of the fluid. In present study, the form of this function has been investigated for halocarbon refrigerants. The obtained correlation is written in terms of the following parameters: reduced pressure, eccentric and compressibility factors at the critical state, and a dimensionless specific heat of the vapor phase. The correlation compares well with experimental results. (author)
Correlation Coefficients of Extended Hesitant Fuzzy Sets and Their Applications to Decision Making

Directory of Open Access Journals (Sweden)

Na Lu

2017-03-01

Full Text Available Extended hesitant fuzzy sets (EHFSs, which allow the membership degree of an element to a set represented by several possible value-groups, can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we derive some correlation coefficients between EHFSs, which contain two cases, the correlation coefficients taking into account the length of extended hesitant fuzzy elements (EHFEs and the correlation coefficients without taking into account the length of EHFEs, as a new extension of existing correlation coefficients for hesitant fuzzy sets (HFSs and apply them to decision making under extended hesitant fuzzy environments. A real-world example based on the energy policy problem is employed to illustrate the actual need for dealing with the difference of evaluation information provided by different experts without information loss in decision making processes.
Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.

Science.gov (United States)

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.
Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

Science.gov (United States)

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.
Modeling Concordance Correlation Coefficient for Longitudinal Study Data

Science.gov (United States)

Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.

2010-01-01

Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of…

Wavelet based correlation coefficient of time series of Saudi Meteorological Data

International Nuclear Information System (INIS)

Rehman, S.; Siddiqi, A.H.

2009-01-01

In this paper, wavelet concepts are used to study a correlation between pairs of time series of meteorological parameters such as pressure, temperature, rainfall, relative humidity and wind speed. The study utilized the daily average values of meteorological parameters of nine meteorological stations of Saudi Arabia located at different strategic locations. The data used in this study cover a period of 16 years between 1990 and 2005. Besides obtaining wavelet spectra, we also computed the wavelet correlation coefficients between two same parameters from two different locations and show that strong correlation or strong anti-correlation depends on scale. The cross-correlation coefficients of meteorological parameters between two stations were also calculated using statistical function. For coastal to costal pair of stations, pressure time series was found to be strongly correlated. In general, the temperature data were found to be strongly correlated for all pairs of stations and the rainfall data the least.
Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

Science.gov (United States)

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.
On the Construction of Bivariate Exponential Distributions with an Arbitrary Correlation Coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

2010-01-01

coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase-type distribution. The latter property is partially important for the development of hypothesis testing in linear models. Finally, it is easy to simulate...
Partial Thermalization of Correlations in pA and AA collisionss

Science.gov (United States)

Gavin, Sean; Moschelli, George; Zin, Christopher

2017-09-01

Correlations born before the onset of hydrodynamic flow can leave observable traces on the final state particles. Measurement of these correlations can yield important information on the isotropization and thermalization process. Starting with Israel-Stewart hydrodynamics and Boltzmann-like kinetic theory in the presence of dynamic Langevin noise, we derive new partial differential equations for two-particle correlation functions. To illustrate how these equations can be used, we study the effect of thermalization on long range correlations. We show quite generally that two particle correlations at early times depend on S, the average probability that a parton suffers no interactions. We extract S from transverse momentum fluctuations measured in Pb+Pb collisions and predict the degree of partial thermalization in pA experiments. NSF-PHY-1207687.
Correlation factor, velocity autocorrelation function and frequency-dependent tracer diffusion coefficient

NARCIS (Netherlands)

Beijeren, H. van; Kehr, K.W.

1986-01-01

The correlation factor, defined as the ratio between the tracer diffusion coefficient in lattice gases and the diffusion coefficient for a corresponding uncorrelated random walk, is known to assume a very simple form under certain conditions. A simple derivation of this is given with the aid of
Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

Science.gov (United States)

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.…
Lipidomics study of plasma phospholipid metabolism in early type 2 diabetes rats with ancient prescription Huang-Qi-San intervention by UPLC/Q-TOF-MS and correlation coefficient.

Science.gov (United States)

Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan

2016-08-25

Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

Directory of Open Access Journals (Sweden)

Bruno Giacomini Sari

2017-09-01

Full Text Available ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.
Spatially varying cross-correlation coefficients in the presence of nugget effects

KAUST Repository

Kleiber, William; Genton, Marc G.

2012-01-01

We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.
Spatially varying cross-correlation coefficients in the presence of nugget effects

KAUST Repository

Kleiber, William

2012-11-29

We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.
Correlation of Cadmium Distribution Coefficients to Soil Characteristics

DEFF Research Database (Denmark)

Holm, Peter Engelund; Rootzen, Helle; Borggaard, Ole K.

2003-01-01

on whole soil samples have shown that pH is the main parameter controlling the distribution. To identify further the components that are important for Cd binding in soil we measured Cd distribution coefficients (K-d) at two fixed pH values and at low Cd loadings for 49 soils sampled in Denmark. The Kd...... values for Cd ranged from 5 to 3000 L kg(-1). The soils were described pedologically and characterized in detail (22 parameters) including determination of contents of the various minerals in the clay fraction. Correlating parameters were grouped and step-wise regression analysis revealed...... interlayered clay minerals [HIM], chlorite, quartz, microcline, plagioclase) were significant in explaining the Cd distribution coefficient....
Reliable Recognition of Partially Occluded Objects with Correlation Filters

Directory of Open Access Journals (Sweden)

Alexey Ruchay

2018-01-01

Full Text Available Design of conventional correlation filters requires explicit knowledge of the appearance and shape of a target object, so the performance of correlation filters is significantly affected by changes in the appearance of the object in the input scene. In particular, the performance of correlation filters worsens when objects to be recognized are partially occluded by other objects, and the input scene contains a cluttered background and noise. In this paper, we propose a new algorithm for the design of a system consisting of a set of adaptive correlation filters for recognition of partially occluded objects in noisy scenes. Since the input scene may contain different fragments of the target, false objects, and background to be rejected, the system is designed in such a manner to guarantee equally high correlation peaks corresponding to parts of the target in the scenes. The key points of the system are as follows: (i it consists of a bank of composite optimum filters, which yield the best performance for different parts of the target; (ii it includes a fragmentation of the target into a given number of parts in the training stage to provide equal intensity responses of the system for each part of the target. With the help of computer simulation, the performance of the proposed algorithm for recognition partially occluded objects is compared with that of common algorithms in terms of objective metrics.
QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

Science.gov (United States)

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.
Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

Science.gov (United States)

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.
On k-summability of formal solutions for certain partial differential operators with polynomial coefficients

Directory of Open Access Journals (Sweden)

Kunio Ichinobe

2015-01-01

Full Text Available We study the \\(k\\-summability of divergent formal solutions for the Cauchy problem of certain linear partial differential operators with coefficients which are polynomial in \\(t\\. We employ the method of successive approximation in order to construct the formal solutions and to obtain the properties of analytic continuation of the solutions of convolution equations and their exponential growth estimates.
Observations of copolar correlation coefficient through a bright band at vertical incidence

Science.gov (United States)

Zrnic, D. S.; Raghavan, R.; Chandrasekar, V.

1994-01-01

This paper discusses an application of polarimetric measurements at vertical incidence. In particular, the correlation coefficients between linear copolar components are examined, and measurements obtained with the National Severe Storms Laboratory (NSSL)'s and National Center for Atmospheric Research (NCAR)'s polarimetric radars are presented. The data are from two well-defined bright bands. A sharp decrease of the correlation coefficient, confined to a height interval of a few hundred meters, marks the bottom of the bright band.
Correlation of psychomotor findings and the ability to partially weight bear

Science.gov (United States)

2012-01-01

Background Partial weight bearing is thought to avoid excessive loading that may interfere with the healing process after surgery of the pelvis or the lower extremity. The object of this study was to investigate the relationship between the ability to partially weight bear and the patient's psychomotor skills and an additional evaluation of the possibility to predict this ability with a standardized psychomotor test. Methods 50 patients with a prescribed partial weight bearing at a target load of 15 kg following surgery were verbally instructed by a physical therapist. After the instruction and sufficient training with the physical therapist vertical ground reaction forces using matrix insoles were measured while walking with forearm crutches. Additionally, psychomotor skills were tested with the Motorische Leistungsserie (MLS). To test for correlations Spearman's Rank correlation was used. For further comparison of the two groups a Mann-Withney test was performed using Bonferroni correction. Results The patient's age and body weight significantly correlated with the ability to partially weight bear at a 15 kg target load. There were significant correlations between several subtests of the MLS and ground reaction forces measured while walking with crutches. Patients that were able to correctly perform partial weight bearing showed significant better psychomotor skills especially for those subtests where both hands had to be coordinated simultaneously. Conclusions The ability to partially weight bear is associated with psychomotor skills. The MLS seems to be a tool that helps predicting the ability to keep within the prescribed load limits. PMID:22330655
Correlation of psychomotor findings and the ability to partially weight bear

Directory of Open Access Journals (Sweden)

Ruckstuhl Thomas

2012-02-01

Full Text Available Abstract Background Partial weight bearing is thought to avoid excessive loading that may interfere with the healing process after surgery of the pelvis or the lower extremity. The object of this study was to investigate the relationship between the ability to partially weight bear and the patient's psychomotor skills and an additional evaluation of the possibility to predict this ability with a standardized psychomotor test. Methods 50 patients with a prescribed partial weight bearing at a target load of 15 kg following surgery were verbally instructed by a physical therapist. After the instruction and sufficient training with the physical therapist vertical ground reaction forces using matrix insoles were measured while walking with forearm crutches. Additionally, psychomotor skills were tested with the Motorische Leistungsserie (MLS. To test for correlations Spearman's Rank correlation was used. For further comparison of the two groups a Mann-Withney test was performed using Bonferroni correction. Results The patient's age and body weight significantly correlated with the ability to partially weight bear at a 15 kg target load. There were significant correlations between several subtests of the MLS and ground reaction forces measured while walking with crutches. Patients that were able to correctly perform partial weight bearing showed significant better psychomotor skills especially for those subtests where both hands had to be coordinated simultaneously. Conclusions The ability to partially weight bear is associated with psychomotor skills. The MLS seems to be a tool that helps predicting the ability to keep within the prescribed load limits.
Evaluation of total and partial structure factors, self-diffusion coefficients, and compressibilities of the cadmium-gallium melt

International Nuclear Information System (INIS)

Gopala Rao, R.V.; Das, R.

1988-01-01

The three partial structure factors S/sub 11/(K), S/sub 22/(K), and S/sub 12/(K) defined by Ashcroft and Langreth are computed with a square-well potential as a perturbation over a hard-sphere potential for different atomic fractions or concentrations of cadmium for Cd-Ga melt at 296 0 C. Also, the number-number, concentration-concentration, and the cross-term number-concentration structure factors due to Bhatia-Thornton have been calculated for the seven concentrations of Cd-Ga melt at that temperature. From these partial structure factors total structure factors are computed and are compared with the experimental results. The total structure factors so computed are found to be in excellent agreement with the measured values except in the long-wavelength limit of S(0). Using the partial structure factors in the long-wavelength limit the isothermal compressibilities have been calculated. From these partial structure factors and by using the linear-trajectory approximation of Helfand, the self-diffusion coefficients D/sub i/'s have also been calculated for various atomic fractions of Cd for Cd-Ga alloy at 296 0 C. From these D/sub i/'s, an estimate of the mutual diffusion coefficients has been made to a good approximation
Choosing the best index for the average score intraclass correlation coefficient.

Science.gov (United States)

Shieh, Gwowen

2016-09-01

The intraclass correlation coefficient (ICC)(2) index from a one-way random effects model is widely used to describe the reliability of mean ratings in behavioral, educational, and psychological research. Despite its apparent utility, the essential property of ICC(2) as a point estimator of the average score intraclass correlation coefficient is seldom mentioned. This article considers several potential measures and compares their performance with ICC(2). Analytical derivations and numerical examinations are presented to assess the bias and mean square error of the alternative estimators. The results suggest that more advantageous indices can be recommended over ICC(2) for their theoretical implication and computational ease.

Statistical electron angular correlation coefficients for atoms within the Hohenberg-Kohn-Sham theory

International Nuclear Information System (INIS)

Pathak, R.K.

1985-01-01

Statistical electron angular correlation coefficients tau = 2 2 He through 14 Si, within the Hohenberg-Kohn-Sham density-functional formalism. These are computed with use of the spectral sum rules obtained from the pseudoexcitation spectrum employing the recent formulation of the time-dependent Kohn-Sham theory due to Bartolotti. Various approximations to the exchange-correlation energy functional are used and for first-row atoms, a comparison is made with the highly accurate correlation coefficients recently obtained by Thakkar. The present tau values show closer agreement with those of Thakkar with increasing number of electrons
Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

Science.gov (United States)

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.
Correlation-Based Amplitude Estimation of Coincident Partials in Monaural Musical Signals

Directory of Open Access Journals (Sweden)

Jayme Garcia Arnal Barbedo

2010-01-01

Full Text Available This paper presents a method for estimating the amplitude of coincident partials generated by harmonic musical sources (instruments and vocals. It was developed as an alternative to the commonly used interpolation approach, which has several limitations in terms of performance and applicability. The strategy is based on the following observations: (a the parameters of partials vary with time; (b such a variation tends to be correlated when the partials belong to the same source; (c the presence of an interfering coincident partial reduces the correlation; and (d such a reduction is proportional to the relative amplitude of the interfering partial. Besides the improved accuracy, the proposed technique has other advantages over its predecessors: it works properly even if the sources have the same fundamental frequency, it is able to estimate the first partial (fundamental, which is not possible using the conventional interpolation method, it can estimate the amplitude of a given partial even if its neighbors suffer intense interference from other sources, it works properly under noisy conditions, and it is immune to intraframe permutation errors. Experimental results show that the strategy clearly outperforms the interpolation approach.
Variability, correlation and path coefficient analysis of seedling traits ...

African Journals Online (AJOL)

Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.
Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

Science.gov (United States)

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.
Variability, correlation and path coefficient analysis of seedling traits ...

African Journals Online (AJOL)

use

2011-12-12

Dec 12, 2011 ... Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient ...
Correlation Revelation: The Search for Meaning in Pearson's Coefficient

Science.gov (United States)

Huhn, Craig

2016-01-01

When the author was first charged with getting a group of students to understand the correlation coefficient, he did not anticipate the topic would challenge his own understanding, let alone cause him to eventually question the very nature of mathematics itself. On the surface, the idea seemed straightforward, one that millions of students across…
Correlations and fluctuations in reflection coefficients for coherent wave propagation in disordered scattering media

International Nuclear Information System (INIS)

Wang, L.; Feng, S.

1989-01-01

The relation between the reflection coefficients and the Green's function for a coherent wave propagation in a disordered elastic-scattering medium is derived. The sum rule of the reflection and transmission coefficients corresponding to probability conservation is shown rigorously for an arbitrary scattering potential. The correlation function of the reflection coefficients is then calculated by using a Feynman-diagrammatic approach in the weak-localized multiple-scattering regime (L much-gt l much-gt λ). The result is in agreement with recent experiments on the so-called ''memory effect'' in reflection coefficients. A more general condition under which the memory effect can occur is derived. Differences between the the correlation functions for reflection and that for transmission are discussed
Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

Science.gov (United States)

Bishara, Anthony J.; Hittner, James B.

2015-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Overcoming multicollinearity in multiple regression using correlation coefficient

Science.gov (United States)

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.
Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

Science.gov (United States)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.
Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis

Energy Technology Data Exchange (ETDEWEB)

Aoyagi, Tomoyoshi; Shuto, Kiyohiko; Okazumi, Shinichi; Hayano, Kohichi; Satoh, Asami; Saitoh, Hiroshige; Shimada, Hideaki; Nabeya, Yoshihiro; Matsubara, Hisahiro [Chiba University, Department of Frontier Surgery, Graduate School of Medicine, Chiba (Japan); Kazama, Toshiki [Chiba University, Department of Radiology, Graduate School of Medicine, Chiba (Japan)

2012-06-15

Because diffusion-weighted imaging (DWI) can predict the prognosis of patients with oesophageal squamous cell carcinoma (ESCC), we hypothesised that apparent diffusion coefficient (ADC) values might be correlated with the collagen content and tumour angiogenesis. The purpose of this study was to determine the correlation between ADC values of ESCC before treatment and oesophageal tumour stroma and angiogenesis. Seventeen patients with ESCC were enrolled. The ADC values were calculated from the DWI score. Seventeen patients who had undergone oesophagectomy were analysed for tumour stroma, vascular endothelial growth factor (VEGF) and CD34. Tissue collagen was stained with azocarmine and aniline blue to quantitatively analyse the extracellular matrix in cancer stroma. Tissues were stained with VEGF and CD34 to analyse the angiogenesis. The ADC values decreased with stromal collagen growth. We found a negative correlation between the tumour ADC and the amount of stromal collagen (r = -0.729, P = 0.001), i.e. the ADC values decreased with growth of VEGF. We also found a negative correlation between the ADC of the tumours and the amount of VEGF (r = 0.538, P = 0.026). Our results indicated that the ADC value may be a novel prognostic factor and contribute to the treatment of oesophageal cancer. circle Magnetic resonance apparent diffusion coefficient values inversely indicate tumour stromal collagen circle There is also negative correlation between ADCs and vascular endothelial growth factor circle ADC values may contribute to the treatment of oesophageal cancer. (orig.)
Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis

International Nuclear Information System (INIS)

Aoyagi, Tomoyoshi; Shuto, Kiyohiko; Okazumi, Shinichi; Hayano, Kohichi; Satoh, Asami; Saitoh, Hiroshige; Shimada, Hideaki; Nabeya, Yoshihiro; Matsubara, Hisahiro; Kazama, Toshiki

2012-01-01

Because diffusion-weighted imaging (DWI) can predict the prognosis of patients with oesophageal squamous cell carcinoma (ESCC), we hypothesised that apparent diffusion coefficient (ADC) values might be correlated with the collagen content and tumour angiogenesis. The purpose of this study was to determine the correlation between ADC values of ESCC before treatment and oesophageal tumour stroma and angiogenesis. Seventeen patients with ESCC were enrolled. The ADC values were calculated from the DWI score. Seventeen patients who had undergone oesophagectomy were analysed for tumour stroma, vascular endothelial growth factor (VEGF) and CD34. Tissue collagen was stained with azocarmine and aniline blue to quantitatively analyse the extracellular matrix in cancer stroma. Tissues were stained with VEGF and CD34 to analyse the angiogenesis. The ADC values decreased with stromal collagen growth. We found a negative correlation between the tumour ADC and the amount of stromal collagen (r = -0.729, P = 0.001), i.e. the ADC values decreased with growth of VEGF. We also found a negative correlation between the ADC of the tumours and the amount of VEGF (r = 0.538, P = 0.026). Our results indicated that the ADC value may be a novel prognostic factor and contribute to the treatment of oesophageal cancer. circle Magnetic resonance apparent diffusion coefficient values inversely indicate tumour stromal collagen circle There is also negative correlation between ADCs and vascular endothelial growth factor circle ADC values may contribute to the treatment of oesophageal cancer. (orig.)
Negative Correlation between the Diffusion Coefficient and Transcriptional Activity of the Glucocorticoid Receptor.

Science.gov (United States)

Mikuni, Shintaro; Yamamoto, Johtaro; Horio, Takashi; Kinjo, Masataka

2017-08-25

The glucocorticoid receptor (GR) is a transcription factor, which interacts with DNA and other cofactors to regulate gene transcription. Binding to other partners in the cell nucleus alters the diffusion properties of GR. Raster image correlation spectroscopy (RICS) was applied to quantitatively characterize the diffusion properties of EGFP labeled human GR (EGFP-hGR) and its mutants in the cell nucleus. RICS is an image correlation technique that evaluates the spatial distribution of the diffusion coefficient as a diffusion map. Interestingly, we observed that the averaged diffusion coefficient of EGFP-hGR strongly and negatively correlated with its transcriptional activities in comparison to that of EGFP-hGR wild type and mutants with various transcriptional activities. This result suggests that the decreasing of the diffusion coefficient of hGR was reflected in the high-affinity binding to DNA. Moreover, the hyper-phosphorylation of hGR can enhance the transcriptional activity by reduction of the interaction between the hGR and the nuclear corepressors.
On the misinterpretation of the correlation coefficient in pharmaceutical sciences

DEFF Research Database (Denmark)

Sonnergaard, Jørn

2006-01-01

The correlation coefficient is often used and more often misused as a universal parameter expressing the quality in linear regression analysis. The popularity of this dimensionless quantity is evident as it is easy to communicate and considered to be unproblematic to comprehend. However, illustra...
Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

Science.gov (United States)

Golmohammadi, Hassan

2009-11-30

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.
Correlation between octanol/water and liposome/water distribution coefficients and drug absorption of a set of pharmacologically active compounds.

Science.gov (United States)

Esteves, Freddy; Moutinho, Carla; Matos, Carla

2013-06-01

Absorption and consequent therapeutic action are key issues in the development of new drugs by the pharmaceutical industry. In this sense, different models can be used to simulate biological membranes to predict the absorption of a drug. This work compared the octanol/water and the liposome/water models. The parameters used to relate the two models were the distribution coefficients between liposomes and water and octanol and water and the fraction of drug orally absorbed. For this study, 66 drugs were collected from literature sources and divided into four groups according to charge and ionization degree: neutral; positively charged; negatively charged; and partially ionized/zwitterionic. The results show a satisfactory linear correlation between the octanol and liposome systems for the neutral (R²= 0.9324) and partially ionized compounds (R²= 0.9367), contrary to the positive (R²= 0.4684) and negatively charged compounds (R²= 0.1487). In the case of neutral drugs, results were similar in both models because of the high fraction orally absorbed. However, for the charged drugs (positively, negatively, and partially ionized/zwitterionic), the liposomal model has a more-appropriate correlation with absorption than the octanol model. These results show that the neutral compounds only interact with membranes through hydrophobic bonds, whereas charged drugs favor electrostatic interactions established with the liposomes. With this work, we concluded that liposomes may be a more-appropriate biomembrane model than octanol for charged compounds.
Thermal expansion coefficient determination of polylactic acid using digital image correlation

Directory of Open Access Journals (Sweden)

Botean Adrian - Ioan

2018-01-01

Full Text Available This paper aims determining the linear thermal expansion coefficient (CTE of polylactic acid (PLA using an optical method for measuring deformations called digital image correlation method (DIC. Because PLA is often used in making many pieces with 3D printing technology, it is opportune to know this coefficient to obtain a higher degree of precision in the construction of parts and to monitor deformations when these parts are subjected to a thermal gradient. Are used two PLA discs with 20 and 40% degree of filling. In parallel with this approach was determined the linear thermal expansion coefficient (CTE for the copper cylinder on the surface of which are placed the two discs of PLA.
Thermal expansion coefficient determination of polylactic acid using digital image correlation

Science.gov (United States)

Botean, Adrian-Ioan

2018-02-01

This paper aims determining the linear thermal expansion coefficient (CTE) of polylactic acid (PLA) using an optical method for measuring deformations called digital image correlation method (DIC). Because PLA is often used in making many pieces with 3D printing technology, it is opportune to know this coefficient to obtain a higher degree of precision in the construction of parts and to monitor deformations when these parts are subjected to a thermal gradient. Are used two PLA discs with 20 and 40% degree of filling. In parallel with this approach was determined the linear thermal expansion coefficient (CTE) for the copper cylinder on the surface of which are placed the two discs of PLA.
Determination and correlation of mass transfer coefficients in a stirred cell

International Nuclear Information System (INIS)

Herranz, J.; Bloxom, S.R.; Keeler, J.B.; Roth, S.R.

1975-01-01

In the proposed Molten Salt Breeder Reactor flowsheet, a fraction of the rare earth fission products is removed from the fuel salt in mass transfer cells. To obtain design parameters for this extraction, the effect of cell size, blade diameter, phase volume, and agitation rate on the mass transfer for a high density ratio system (mercury/water) in nondispersing square cross section contactors was determined. Aqueous side mass transfer coefficients were measured by polarography over a wide range of operating conditions. Correlations for the experimental mass transfer coefficients as functions of the operating parameters are presented. Several techniques for measuring mercury-side mass transfer coefficients were evaluated and a new one is recommended

[Correlation of molecular weight and nanofiltration mass transfer coefficient of phenolic acid composition from Salvia miltiorrhiza].

Science.gov (United States)

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.
The robustness of designs for trials with nested data against incorrect initial intracluster correlation coefficient estimates

NARCIS (Netherlands)

Korendijk, E.J.H.; Moerbeek, M.; Maas, C.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
Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

Science.gov (United States)

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.
An inequality between the weighted average and the rowwise correlation coefficient for proximity matrices

NARCIS (Netherlands)

Krijnen, WP

De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this
AN INEQUALITY BETWEEN THE WEIGHTED AVERAGE AND THE ROWWISE CORRELATION-COEFFICIENT FOR PROXIMITY MATRICES

NARCIS (Netherlands)

KRIJNEN, WP

De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this
Time correlation functions and transport coefficients in a dilute superfluid

International Nuclear Information System (INIS)

Kirkpatrick, T.R.; Dorfman, J.R.

1985-01-01

Time correlation functions for the transport coefficients in the linear Landau-Khalatnikov equations are derived on the basis of a formal theory. These Green--Kubo expressions are then explicitly evaluated for a dilute superfluid and the resulting transport coefficiencts are shown to be identical to those obtained previously by using a distribution function method
Correlations in a partially degenerate electron plasma

Energy Technology Data Exchange (ETDEWEB)

Chihara, Junzo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-03-01

The density-functional theory proves that an ion-electron mixture can be treated as a one-component liquid interacting only via a pairwise interaction in the evaluation of the ion-ion radial distribution function (RDF), and provides a set of integral equations: one is an integral equation for the ion-ion RDF and another for an effective ion-ion interaction, which depends on the ion-ion RDF. This formulation gives a set of integral equation to calculate plasma structures with combined use of the electron-electron correlations in a partially degenerate electron plasma. Therefore, it is important for this purpose to determine the electron-electron correlations at a arbitrary temperature. Here, they are calculated by the quantal version of the hypernetted chain (HNC) equation. On the basis of the jellium-vacancy model, the ionic and electronic structures of rubidium are calculated for the range from liquid metal to plasma states by increasing the temperature at the fixed density using the electron-correlation results. (author)
Calculation of the correlation coefficients between the numbers of counts (peak areas and backgrounds) obtained from gamma-ray spectra

International Nuclear Information System (INIS)

Korun, M.; Vodenik, B.; Zorko, B.

2016-01-01

Two simple methods for calculating the correlations between peaks appearing in gamma-ray spectra are described. We show how the areas are correlated when the peaks do not overlap, but the spectral regions used for the calculation of the background below the peaks do. When the peaks overlap, the correlation can be stronger than in the case of the non-overlapping peaks. The methods presented are simplified to the extent of allowing their implementation with manual calculations. They are intended for practitioners as additional tools to be used when the correlations between the areas of the peaks in the gamma-ray spectra are to be calculated. Also, the correlation coefficient between the number of counts in the peak and the number of counts in the continuous background below the peak is derived. - Highlights: • The correlation coefficients between areas of closely spaced peaks are assessed. • For isolated peaks the correlation arises from the common continuous background. • If peaks overlap the correlation coefficient depends on how much they overlap. • If peaks overlap also the background height affects the correlation coefficient. • The correlation coefficient between the peak area and its background is −1.
Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

Directory of Open Access Journals (Sweden)

Fengjian Shi

2017-10-01

Full Text Available In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.
Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

Science.gov (United States)

Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

2017-10-16

In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.
The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

Science.gov (United States)

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…
Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market.

Science.gov (United States)

Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel

2010-12-20

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.
A new methodology of spatial cross-correlation analysis.

Science.gov (United States)

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.
New external convective heat transfer coefficient correlations for isolated low-rise buildings

Energy Technology Data Exchange (ETDEWEB)

Emmel, M. G.; Mendes, N. [Pontifical Catholic University of Parana, PUCPR/CCET, Thermal Systems Laboratory, LST, Curitiba (Brazil); Abadie, M. O. [Pontifical Catholic University of Parana, PUCPR/CCET, Thermal Systems Laboratory, LST, Curitiba (Brazil); Laboratoire d' Etude des Phenomenes de Transfert Appliques au batiment (LEPTAB), University of La Rochelle, La Rochelle (France)

2007-07-01

Building energy analyses are very sensitive to external convective heat transfer coefficients so that some researchers have conducted sensitivity calculations and proved that depending on the choice of those coefficients, energy demands estimation values can vary from 20% to 40%. In this context, computational fluid dynamics calculations have been performed to predict convective heat transfer coefficients at the external surfaces of a simple shape low-rise building. Effects of wind velocity and orientation have been analyzed considering four surface-to-air temperature differences. Results show that the convective heat transfer coefficient value strongly depends on the wind velocity, that the wind direction has a notable effect for vertical walls and for roofs and that the surface-to-air temperature difference has a negligible effect for wind velocity higher than 2 m/s. External convective heat transfer coefficient correlations are provided as a function of the wind free stream velocity and wind-to-surface angle. (author)
The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

Science.gov (United States)

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.
Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

Science.gov (United States)

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)
Highlighting material structure with transmission electron diffraction correlation coefficient maps.

Science.gov (United States)

Kiss, Ákos K; Rauch, Edgar F; Lábár, János L

2016-04-01

Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast. Copyright © 2016 Elsevier B.V. All rights reserved.
Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

Science.gov (United States)

Raykov, Tenko

2011-01-01

Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
Speed Estimation in Geared Wind Turbines Using the Maximum Correlation Coefficient

DEFF Research Database (Denmark)

Skrimpas, Georgios Alexandros; Marhadi, Kun S.; Jensen, Bogi Bech

2015-01-01

to overcome the above mentioned issues. The high speed stage shaft angular velocity is calculated based on the maximum correlation coefficient between the 1 st gear mesh frequency of the last gearbox stage and a pure sinus tone of known frequency and phase. The proposed algorithm utilizes vibration signals...
DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

Science.gov (United States)

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.

Comparison of values of Pearson’s and Spearman’s correlation coefficient on the same sets of data

OpenAIRE

Hauke, Jan; Kossowski, Tomasz

2011-01-01

Spearman’s rank correlation coefficient is a nonparametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of an association between two variables. It is a measure of a monotone association that is used when the distribution of data makes Pearson’s correlation coefficient undesirable or misleading. Spearman’s coefficient is not a measure of the linear relationship between two variables, as some “statisticians” declare. It assesses how well an arbit...
Measurement of partial coefficients of sputtering of titanium atoms from TiC and TiN coatings

International Nuclear Information System (INIS)

Vychegzhanin, G.A.; Gribanov, Yu.A.; Dikij, N.P.; Zhmurin, P.N.; Letuchij, A.N.; Matyash, P.P.; Sidokur, P.I.; Shono, D.A.

1989-01-01

Method of laser fluorescent spectroscopy was used to measure partial coefficients of sputtering of titanium atoms from TiC and TiN coatings under irradiation by 1 keV hydrogen ions. Irradiation was conducted in a plant with reflective discharge. Investigation of damaged layer in irradiated samples was conducted. The presence of near-the-surface layer enrichment with titanium atoms was revealed both in TiC and TiN samples. 12 refs.; 4 figs
Ground reaction force analysed with correlation coefficient matrix in group of stroke patients.

Science.gov (United States)

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.
Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

Science.gov (United States)

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.
A comparison of confidence interval methods for the concordance correlation coefficient and intraclass correlation coefficient with small number of raters.

Science.gov (United States)

Feng, Dai; Svetnik, Vladimir; Coimbra, Alexandre; Baumgartner, Richard

2014-01-01

The intraclass correlation coefficient (ICC) with fixed raters or, equivalently, the concordance correlation coefficient (CCC) for continuous outcomes is a widely accepted aggregate index of agreement in settings with small number of raters. Quantifying the precision of the CCC by constructing its confidence interval (CI) is important in early drug development applications, in particular in qualification of biomarker platforms. In recent years, there have been several new methods proposed for construction of CIs for the CCC, but their comprehensive comparison has not been attempted. The methods consisted of the delta method and jackknifing with and without Fisher's Z-transformation, respectively, and Bayesian methods with vague priors. In this study, we carried out a simulation study, with data simulated from multivariate normal as well as heavier tailed distribution (t-distribution with 5 degrees of freedom), to compare the state-of-the-art methods for assigning CI to the CCC. When the data are normally distributed, the jackknifing with Fisher's Z-transformation (JZ) tended to provide superior coverage and the difference between it and the closest competitor, the Bayesian method with the Jeffreys prior was in general minimal. For the nonnormal data, the jackknife methods, especially the JZ method, provided the coverage probabilities closest to the nominal in contrast to the others which yielded overly liberal coverage. Approaches based upon the delta method and Bayesian method with conjugate prior generally provided slightly narrower intervals and larger lower bounds than others, though this was offset by their poor coverage. Finally, we illustrated the utility of the CIs for the CCC in an example of a wake after sleep onset (WASO) biomarker, which is frequently used in clinical sleep studies of drugs for treatment of insomnia.
A New Methodology of Spatial Cross-Correlation Analysis

Science.gov (United States)

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
Partial correlation analysis method in ultrarelativistic heavy-ion collisions

Science.gov (United States)

Olszewski, Adam; Broniowski, Wojciech

2017-11-01

We argue that statistical data analysis of two-particle longitudinal correlations in ultrarelativistic heavy-ion collisions may be efficiently carried out with the technique of partial covariance. In this method, the spurious event-by-event fluctuations due to imprecise centrality determination are eliminated via projecting out the component of the covariance influenced by the centrality fluctuations. We bring up the relationship of the partial covariance to the conditional covariance. Importantly, in the superposition approach, where hadrons are produced independently from a collection of sources, the framework allows us to impose centrality constraints on the number of sources rather than hadrons, that way unfolding of the trivial fluctuations from statistical hadronization and focusing better on the initial-state physics. We show, using simulated data from hydrodynamics followed with statistical hadronization, that the technique is practical and very simple to use, giving insight into the correlations generated in the initial stage. We also discuss the issues related to separation of the short- and long-range components of the correlation functions and show that in our example the short-range component from the resonance decays is largely reduced by considering pions of the same sign. We demonstrate the method explicitly on the cases where centrality is determined with a single central control bin or with two peripheral control bins.
A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

Science.gov (United States)

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.
A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

Science.gov (United States)

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.
Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

Science.gov (United States)

Wu, Panpan; Xia, Kewen; Yu, Hengyong

2016-11-01

Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient.

Science.gov (United States)

Barlow, Andrew L; Macleod, Alasdair; Noppen, Samuel; Sanderson, Jeremy; Guérin, Christopher J

2010-12-01

One of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate negative correlation. We have demonstrated that the calculation of a thresholded Pearson's correlation coefficient using only intensity values over a determined threshold in both channels produces numerical values that more accurately describe both synthetic datasets and biological examples. Its use will bring clarity and accuracy to colocalization studies using fluorescent microscopy.
A simple approximation to the bivariate normal distribution with large correlation coefficient

NARCIS (Netherlands)

Albers, Willem/Wim; Kallenberg, W.C.M.

1994-01-01

The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the
The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis.

Science.gov (United States)

Chen, Lihua; Liu, Min; Bao, Jing; Xia, Yunbao; Zhang, Jiuquan; Zhang, Lin; Huang, Xuequan; Wang, Jian

2013-01-01

To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was -0.57 (95% CI: -0.62, -0.52), indicating notable heterogeneity (Pcorrelation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.
Asymptotic properties of Pearson's rank-variate correlation coefficient under contaminated Gaussian model.

Science.gov (United States)

Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu

2014-01-01

This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.
Osmotic coefficients of alcoholic mixtures containing BMpyrDCA: Experimental determination and correlation

International Nuclear Information System (INIS)

Calvar, N.; Domínguez, Á.; Macedo, E.A.

2014-01-01

Graphical abstract: - Highlights: • Osmotic coefficients of alcohols with BMpyrDCA ionic liquid are determined. • Experimental data were correlated with Extended Pitzer model of Archer and MNRTL. • Mean molal activity coefficients and excess Gibbs free energies were calculated. • The results have been interpreted in terms of interactions. - Abstract: The vapour pressure osmometry technique (VPO) has been used to obtain the osmotic coefficients of the binary mixtures of the primary and secondary alcohols 1-propanol, 2-propanol, 1-butanol, 2-butanol and 1-pentanol with the ionic liquid 1-butyl-1-methylpyrrolidinium dicyanamide, BMpyrDCA. From these coefficients, the corresponding activity coefficients and vapour pressures of the mixtures have been also determined. The results have been discussed in terms of solute–solvent and ion–ion interactions and have been compared with those taken from literature in order to analyse the influence of the anion or cation constituting the ionic liquid. For the treatment of the experimental data, the Extended Pitzer model of Archer and the MNRTL model have been applied, obtaining standard deviations from the experimental osmotic coefficients lower than 0.015 and 0.065, respectively. From the parameters obtained with the Extended Pitzer model or Archer, the mean molal activity coefficients and the excess Gibbs free energy for the studied mixtures have been calculated
A short note on jackknifing the concordance correlation coefficient.

Science.gov (United States)

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2014-02-10

Lin's concordance correlation coefficient (CCC) is a very popular scaled index of agreement used in applied statistics. To obtain a confidence interval (CI) for the estimate of CCC, jackknifing was proposed and shown to perform well in simulation as well as in applications. However, a theoretical proof of the validity of the jackknife CI for the CCC has not been presented yet. In this note, we establish a sufficient condition for using the jackknife method to construct the CI for the CCC. Copyright © 2013 John Wiley & Sons, Ltd.
RMT Assessments of the Market Latent Information Embedded in the Stocks' Raw, Normalized, and Partial Correlations

Directory of Open Access Journals (Sweden)

Dror Y. Kenett

2009-01-01

Full Text Available We present here assessment of the latent market information embedded in the raw, affinity (normalized, and partial correlations. We compared the Zipf plot, spectrum, and distribution of the eigenvalues for each matrix with the results of the corresponding random matrix. The analysis was performed on stocks belonging to the New York and Tel Aviv Stock Exchange, for the time period of January 2000 to March 2009. Our results show that in comparison to the raw correlations, the affinity matrices highlight the dominant factors of the system, and the partial correlation matrices contain more information. We propose that significant stock market information, which cannot be captured by the raw correlations, is embedded in the affinity and partial correlations. Our results further demonstrate the differences between NY and TA markets.
Partial scan artifact reduction (PSAR) for the assessment of cardiac perfusion in dynamic phase-correlated CT.

Science.gov (United States)

Stenner, Philip; Schmidt, Bernhard; Bruder, Herbert; Allmendinger, Thomas; Haberland, Ulrike; Flohr, Thomas; Kachelriess, Marc

2009-12-01

Cardiac CT achieves its high temporal resolution by lowering the scan range from 2pi to pi plus fan angle (partial scan). This, however, introduces CT-value variations, depending on the angular position of the pi range. These partial scan artifacts are of the order of a few HU and prevent the quantitative evaluation of perfusion measurements. The authors present the new algorithm partial scan artifact reduction (PSAR) that corrects a dynamic phase-correlated scan without a priori information. In general, a full scan does not suffer from partial scan artifacts since all projections in [0, 2pi] contribute to the data. To maintain the optimum temporal resolution and the phase correlation, PSAR creates an artificial full scan pn(AF) by projectionwise averaging a set of neighboring partial scans pn(P) from the same perfusion examination (typically N approximately 30 phase-correlated partial scans distributed over 20 s and n = 1, ..., N). Corresponding to the angular range of each partial scan, the authors extract virtual partial scans pn(V) from the artificial full scan pn(AF). A standard reconstruction yields the corresponding images fn(P), fn(AF), and fn(V). Subtracting the virtual partial scan image fn(V) from the artificial full scan image fn(AF) yields an artifact image that can be used to correct the original partial scan image: fn(C) = fn(P) - fn(V) + fn(AF), where fn(C) is the corrected image. The authors evaluated the effects of scattered radiation on the partial scan artifacts using simulated and measured water phantoms and found a strong correlation. The PSAR algorithm has been validated with a simulated semianthropomorphic heart phantom and with measurements of a dynamic biological perfusion phantom. For the stationary phantoms, real full scans have been performed to provide theoretical reference values. The improvement in the root mean square errors between the full and the partial scans with respect to the errors between the full and the corrected scans is
Partial scan artifact reduction (PSAR) for the assessment of cardiac perfusion in dynamic phase-correlated CT

International Nuclear Information System (INIS)

Stenner, Philip; Schmidt, Bernhard; Bruder, Herbert; Allmendinger, Thomas; Haberland, Ulrike; Flohr, Thomas; Kachelriess, Marc

2009-01-01

Purpose: Cardiac CT achieves its high temporal resolution by lowering the scan range from 2π to π plus fan angle (partial scan). This, however, introduces CT-value variations, depending on the angular position of the π range. These partial scan artifacts are of the order of a few HU and prevent the quantitative evaluation of perfusion measurements. The authors present the new algorithm partial scan artifact reduction (PSAR) that corrects a dynamic phase-correlated scan without a priori information. Methods: In general, a full scan does not suffer from partial scan artifacts since all projections in [0, 2π] contribute to the data. To maintain the optimum temporal resolution and the phase correlation, PSAR creates an artificial full scan p n AF by projectionwise averaging a set of neighboring partial scans p n P from the same perfusion examination (typically N≅30 phase-correlated partial scans distributed over 20 s and n=1,...,N). Corresponding to the angular range of each partial scan, the authors extract virtual partial scans p n V from the artificial full scan p n AF . A standard reconstruction yields the corresponding images f n P , f n AF , and f n V . Subtracting the virtual partial scan image f n V from the artificial full scan image f n AF yields an artifact image that can be used to correct the original partial scan image: f n C =f n P -f n V +f n AF , where f n C is the corrected image. Results: The authors evaluated the effects of scattered radiation on the partial scan artifacts using simulated and measured water phantoms and found a strong correlation. The PSAR algorithm has been validated with a simulated semianthropomorphic heart phantom and with measurements of a dynamic biological perfusion phantom. For the stationary phantoms, real full scans have been performed to provide theoretical reference values. The improvement in the root mean square errors between the full and the partial scans with respect to the errors between the full and the
Ion distributions, exclusion coefficients, and separation factors of electrolytes in a charged cylindrical nanopore: a partially perturbative density functional theory study.

Science.gov (United States)

Peng, Bo; Yu, Yang-Xin

2009-10-07

The structural and thermodynamic properties for charge symmetric and asymmetric electrolytes as well as mixed electrolyte system inside a charged cylindrical nanopore are investigated using a partially perturbative density functional theory. The electrolytes are treated in the restricted primitive model and the internal surface of the cylindrical nanopore is considered to have a uniform charge density. The proposed theory is directly applicable to the arbitrary mixed electrolyte solution containing ions with the equal diameter and different valences. Large amount of simulation data for ion density distributions, separation factors, and exclusion coefficients are used to determine the range of validity of the partially perturbative density functional theory for monovalent and multivalent counterion systems. The proposed theory is found to be in good agreement with the simulations for both mono- and multivalent counterion systems. In contrast, the classical Poisson-Boltzmann equation only provides reasonable descriptions of monovalent counterion system at low bulk density, and is qualitatively and quantitatively wrong in the prediction for the multivalent counterion systems due to its neglect of the strong interionic correlations in these systems. The proposed density functional theory has also been applied to an electrolyte absorbed into a pore that is a model of the filter of a physiological calcium channel.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease.

Science.gov (United States)

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na; Zhang, Bin; Yan, Jianhua

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18 F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r -to- z transformation, correlation coefficient ( r ) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was -0.35 (95% CI: -0.42-0.28) and exhibited a notable heterogeneity ( I 2 = 78.4%; P correlation coefficients of ADC/SUV range from -0.12 (lymphoma, n = 5) to -0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.
A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

Science.gov (United States)

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
Correlation Coefficient Control For A Frequency Reconfigurable Dual-Band Compact MIMO Antenna Destined For LTE

DEFF Research Database (Denmark)

Tatomirescu, Alexandru; Buskgaard, Emil Feldborg; Pedersen, Gert Frølund

2014-01-01

. The MIMO performance is investigated in two different channel models through efficiency, branch power imbalance and envelope correlation. The proposed antennas have acceptable levels of isolation between them, even in the low-bands, while having a good efficiency. Furthermore, the correlation coefficient...
Ghost imaging based on Pearson correlation coefficients

International Nuclear Information System (INIS)

Yu Wen-Kai; Yao Xu-Ri; Liu Xue-Feng; Li Long-Zhen; Zhai Guang-Jie

2015-01-01

Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. (paper)
Partial scan artifact reduction (PSAR) for the assessment of cardiac perfusion in dynamic phase-correlated CT

Energy Technology Data Exchange (ETDEWEB)

Stenner, Philip; Schmidt, Bernhard; Bruder, Herbert; Allmendinger, Thomas; Haberland, Ulrike; Flohr, Thomas; Kachelriess, Marc [Institute of Medical Physics, Henkestrasse 91, 91052 Erlangen (Germany); Siemens AG, Healthcare Sector, Siemensstrasse 1, 91301 Forchheim (Germany); Institute of Medical Physics, Henkestrasse. 91, 91052 Erlangen (Germany)

2009-12-15

Purpose: Cardiac CT achieves its high temporal resolution by lowering the scan range from 2{pi} to {pi} plus fan angle (partial scan). This, however, introduces CT-value variations, depending on the angular position of the {pi} range. These partial scan artifacts are of the order of a few HU and prevent the quantitative evaluation of perfusion measurements. The authors present the new algorithm partial scan artifact reduction (PSAR) that corrects a dynamic phase-correlated scan without a priori information. Methods: In general, a full scan does not suffer from partial scan artifacts since all projections in [0, 2{pi}] contribute to the data. To maintain the optimum temporal resolution and the phase correlation, PSAR creates an artificial full scan p{sub n}{sup AF} by projectionwise averaging a set of neighboring partial scans p{sub n}{sup P} from the same perfusion examination (typically N{approx_equal}30 phase-correlated partial scans distributed over 20 s and n=1,...,N). Corresponding to the angular range of each partial scan, the authors extract virtual partial scans p{sub n}{sup V} from the artificial full scan p{sub n}{sup AF}. A standard reconstruction yields the corresponding images f{sub n}{sup P}, f{sub n}{sup AF}, and f{sub n}{sup V}. Subtracting the virtual partial scan image f{sub n}{sup V} from the artificial full scan image f{sub n}{sup AF} yields an artifact image that can be used to correct the original partial scan image: f{sub n}{sup C}=f{sub n}{sup P}-f{sub n}{sup V}+f{sub n}{sup AF}, where f{sub n}{sup C} is the corrected image. Results: The authors evaluated the effects of scattered radiation on the partial scan artifacts using simulated and measured water phantoms and found a strong correlation. The PSAR algorithm has been validated with a simulated semianthropomorphic heart phantom and with measurements of a dynamic biological perfusion phantom. For the stationary phantoms, real full scans have been performed to provide theoretical reference
Transformation of correlation coefficients between normal and lognormal distribution and implications for nuclear applications

International Nuclear Information System (INIS)

Žerovnik, Gašper; Trkov, Andrej; Smith, Donald L.; Capote, Roberto

2013-01-01

Inherently positive parameters with large relative uncertainties (typically ≳30%) are often considered to be governed by the lognormal distribution. This assumption has the practical benefit of avoiding the possibility of sampling negative values in stochastic applications. Furthermore, it is typically assumed that the correlation coefficients for comparable multivariate normal and lognormal distributions are equivalent. However, this ideal situation is approached only in the linear approximation which happens to be applicable just for small uncertainties. This paper derives and discusses the proper transformation of correlation coefficients between both distributions for the most general case which is applicable for arbitrary uncertainties. It is seen that for lognormal distributions with large relative uncertainties strong anti-correlations (negative correlations) are mathematically forbidden. This is due to the asymmetry that is an inherent feature of these distributions. Some implications of these results for practical nuclear applications are discussed and they are illustrated with examples in this paper. Finally, modifications to the ENDF-6 format used for representing uncertainties in evaluated nuclear data libraries are suggested, as needed to deal with this issue
Transformation of correlation coefficients between normal and lognormal distribution and implications for nuclear applications

Energy Technology Data Exchange (ETDEWEB)

Žerovnik, Gašper, E-mail: gasper.zerovnik@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Trkov, Andrej, E-mail: andrej.trkov@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Smith, Donald L., E-mail: donald.l.smith@anl.gov [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, CA 92118-3073 (United States); Capote, Roberto, E-mail: roberto.capotenoy@iaea.org [NAPC–Nuclear Data Section, International Atomic Energy Agency, PO Box 100, Vienna-A-1400 (Austria)

2013-11-01

Inherently positive parameters with large relative uncertainties (typically ≳30%) are often considered to be governed by the lognormal distribution. This assumption has the practical benefit of avoiding the possibility of sampling negative values in stochastic applications. Furthermore, it is typically assumed that the correlation coefficients for comparable multivariate normal and lognormal distributions are equivalent. However, this ideal situation is approached only in the linear approximation which happens to be applicable just for small uncertainties. This paper derives and discusses the proper transformation of correlation coefficients between both distributions for the most general case which is applicable for arbitrary uncertainties. It is seen that for lognormal distributions with large relative uncertainties strong anti-correlations (negative correlations) are mathematically forbidden. This is due to the asymmetry that is an inherent feature of these distributions. Some implications of these results for practical nuclear applications are discussed and they are illustrated with examples in this paper. Finally, modifications to the ENDF-6 format used for representing uncertainties in evaluated nuclear data libraries are suggested, as needed to deal with this issue.
Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

Directory of Open Access Journals (Sweden)

Shengming Deng

2017-01-01

Full Text Available The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC on diffusion-weighted MR and the standard uptake value (SUV of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included, EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher’s r-to-z transformation, correlation coefficient (r values were extracted from each study and 95% confidence intervals (CIs were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28 and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01. In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5 to −0.59 (pancreatic cancer, n = 2. We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.
Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

Science.gov (United States)

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Evaluation of the Correlation Coefficient of Polyethylene Glycol Treated and Direct Prolactin Results and Comparability with Different Assay System Results.

Science.gov (United States)

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.
A new method of spatio-temporal topographic mapping by correlation coefficient of K-means cluster.

Science.gov (United States)

Li, Ling; Yao, Dezhong

2007-01-01

It would be of the utmost interest to map correlated sources in the working human brain by Event-Related Potentials (ERPs). This work is to develop a new method to map correlated neural sources based on the time courses of the scalp ERPs waveforms. The ERP data are classified first by k-means cluster analysis, and then the Correlation Coefficients (CC) between the original data of each electrode channel and the time course of each cluster centroid are calculated and utilized as the mapping variable on the scalp surface. With a normalized 4-concentric-sphere head model with radius 1, the performance of the method is evaluated by simulated data. CC, between simulated four sources (s (1)-s (4)) and the estimated cluster centroids (c (1)-c (4)), and the distances (Ds), between the scalp projection points of the s (1)-s (4) and that of the c (1)-c (4), are utilized as the evaluation indexes. Applied to four sources with two of them partially correlated (with maximum mutual CC = 0.4892), CC (Ds) between s (1)-s (4) and c (1)-c (4) are larger (smaller) than 0.893 (0.108) for noise levels NSRclusters located at left, right occipital and frontal. The estimated vectors of the contra-occipital area demonstrate that attention to the stimulus location produces increased amplitude of the P1 and N1 components over the contra-occipital scalp. The estimated vector in the frontal area displays two large processing negativity waves around 100 ms and 250 ms when subjects are attentive, and there is a small negative wave around 140 ms and a P300 when subjects are unattentive. The results of simulations and real Visual Evoked Potentials (VEPs) data demonstrate the validity of the method in mapping correlated sources. This method may be an objective, heuristic and important tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.
An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

Science.gov (United States)

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant
Coordination Devices in the Refurbishment Design Process: A Partial-Correlation Approach

Directory of Open Access Journals (Sweden)

Azlan Shah Ali

2009-12-01

Full Text Available Building refurbishment is an important sector in the Malaysian construction industry. The increase the number of building renovations, alterations, extensions and extensive repair works contributed to the high demand for refurbishment projects. However, refurbishment projects are more difficult to manage compared to new-built, due to uncertainty factors inherent in the projects. Therefore, this paper identifies factors that contributed to uncertainty and shows how it affects design performance of refurbishment projects. This paper was also extended to the used of coordination devices to improve design performance from the effect of uncertainty in the projects. Partial-correlation technique was used in data analysis to check any significant moderate effects of coordination devices to control the negative effect of uncertainty on design performance of refurbishment projects. Four (4 coordination devices involved in the partial-correlation tests. The results concluded that the use of lateral relations and architect’s characteristics are most likely reducing the uncertainty of client attributes towards design completeness before work started on site.
Apparent diffusion coefficient ratio correlates significantly with prostate cancer gleason score at final pathology

DEFF Research Database (Denmark)

Boesen, Lars; Chabanova, Elizaveta; Løgager, Vibeke

2015-01-01

PURPOSE: To evaluate the correlation between apparent diffusion coefficient measurements (ADCtumor and ADCratio ) and the Gleason score from radical prostatectomy specimens. MATERIALS AND METHODS: Seventy-one patients with clinically localized prostate cancer scheduled for radical prostatectomy...... correlated with the Gleason score from the prostatectomy specimens. RESULTS: The association between ADC measurements and Gleason score showed a significant negative correlation (P ... ) and 0.90 (ADCratio ) when discriminating Gleason score ≤7(3+4) from Gleason score ≥7(4+3). CONCLUSION: ADC measurements showed a significant correlation with tumor Gleason score at final pathology. The ADCratio demonstrated the best correlation compared to the ADCtumor value and radically improved...
An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

Science.gov (United States)

Shojaeefard, Mohammad Hasan; Khalkhali, Abolfazl; Yarmohammadisatri, Sadegh

2017-06-01

The main purpose of this paper is to propose a new method for designing Macpherson suspension, based on the Sobol indices in terms of Pearson correlation which determines the importance of each member on the behaviour of vehicle suspension. The formulation of dynamic analysis of Macpherson suspension system is developed using the suspension members as the modified links in order to achieve the desired kinematic behaviour. The mechanical system is replaced with an equivalent constrained links and then kinematic laws are utilised to obtain a new modified geometry of Macpherson suspension. The equivalent mechanism of Macpherson suspension increased the speed of analysis and reduced its complexity. The ADAMS/CAR software is utilised to simulate a full vehicle, Renault Logan car, in order to analyse the accuracy of modified geometry model. An experimental 4-poster test rig is considered for validating both ADAMS/CAR simulation and analytical geometry model. Pearson correlation coefficient is applied to analyse the sensitivity of each suspension member according to vehicle objective functions such as sprung mass acceleration, etc. Besides this matter, the estimation of Pearson correlation coefficient between variables is analysed in this method. It is understood that the Pearson correlation coefficient is an efficient method for analysing the vehicle suspension which leads to a better design of Macpherson suspension system.
Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix.

Science.gov (United States)

Madar, Vered

2015-08-01

We present two novel and explicit parametrizations of Cholesky factor of a nonsingular correlation matrix. One that uses semi-partial correlation coefficients, and a second that utilizes differences between the successive ratios of two determinants. To each, we offer a useful application.
Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

Science.gov (United States)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.
Apparent Diffusion Coefficient and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Pancreatic Cancer: Characteristics and Correlation With Histopathologic Parameters.

Science.gov (United States)

Ma, Wanling; Li, Na; Zhao, Weiwei; Ren, Jing; Wei, Mengqi; Yang, Yong; Wang, Yingmei; Fu, Xin; Zhang, Zhuoli; Larson, Andrew C; Huan, Yi

2016-01-01

To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.
The relation between Pearson’s correlation coefficient r and Salton’s cosine measure

NARCIS (Netherlands)

Egghe, L.; Leydesdorff, L.

2009-01-01

The relation between Pearson's correlation coefficient and Salton's cosine measure is revealed based on the different possible values of the division of the L1-norm and the L2-norm of a vector. These different values yield a sheaf of increasingly straight lines which together form a cloud of points,
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

Science.gov (United States)

Krishnamoorthy, K.; Xia, Yanping

2008-01-01

The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…

Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients

Energy Technology Data Exchange (ETDEWEB)

Tipireddy, R.; Stinis, P.; Tartakovsky, A. M.

2017-12-01

We present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support our construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Our results show that highly accurate global solutions can be obtained with significantly reduced computational costs.
Factors associated with blood oxygen partial pressure and carbon dioxide partial pressure regulation during respiratory extracorporeal membrane oxygenation support: data from a swine model.

Science.gov (United States)

Park, Marcelo; Mendes, Pedro Vitale; Costa, Eduardo Leite Vieira; Barbosa, Edzangela Vasconcelos Santos; Hirota, Adriana Sayuri; Azevedo, Luciano Cesar Pontes

2016-01-01

The aim of this study was to explore the factors associated with blood oxygen partial pressure and carbon dioxide partial pressure. The factors associated with oxygen - and carbon dioxide regulation were investigated in an apneic pig model under veno-venous extracorporeal membrane oxygenation support. A predefined sequence of blood and sweep flows was tested. Oxygenation was mainly associated with extracorporeal membrane oxygenation blood flow (beta coefficient = 0.036mmHg/mL/min), cardiac output (beta coefficient = -11.970mmHg/L/min) and pulmonary shunting (beta coefficient = -0.232mmHg/%). Furthermore, the initial oxygen partial pressure and carbon dioxide partial pressure measurements were also associated with oxygenation, with beta coefficients of 0.160 and 0.442mmHg/mmHg, respectively. Carbon dioxide partial pressure was associated with cardiac output (beta coefficient = 3.578mmHg/L/min), sweep gas flow (beta coefficient = -2.635mmHg/L/min), temperature (beta coefficient = 4.514mmHg/ºC), initial pH (beta coefficient = -66.065mmHg/0.01 unit) and hemoglobin (beta coefficient = 6.635mmHg/g/dL). In conclusion, elevations in blood and sweep gas flows in an apneic veno-venous extracorporeal membrane oxygenation model resulted in an increase in oxygen partial pressure and a reduction in carbon dioxide partial pressure 2, respectively. Furthermore, without the possibility of causal inference, oxygen partial pressure was negatively associated with pulmonary shunting and cardiac output, and carbon dioxide partial pressure was positively associated with cardiac output, core temperature and initial hemoglobin.
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

Science.gov (United States)

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Easy measurement of diffusion coefficients of EGFP-tagged plasma membrane proteins using k-space Image Correlation Spectroscopy

DEFF Research Database (Denmark)

Christensen, Eva Arnspang; Koffman, Jennifer Skaarup; Marlar, Saw

2014-01-01

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new insights to plasma membrane protein function and regulation. Recently, k-Space Image Correlation Spectroscopy (kICS)1 was developed to enable...... routine measurements of diffusion coefficients directly from images of fluorescently tagged plasma membrane proteins, that avoided systematic biases introduced by probe photophysics. Although the theoretical basis for the analysis is complex, the method can be implemented by nonexperts using a freely...... to the correlation function yields the diffusion coefficient. This paper provides a step-by-step guide to the image analysis and measurement of diffusion coefficients via kICS. First, a high frame rate image sequence of a fluorescently labeled plasma membrane protein is acquired using a fluorescence microscope Then...
Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis.

Science.gov (United States)

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

2017-08-29

The purpose of this meta-analysis was to provide clinical evidence regarding relationship between ADC and cellularity in different tumors based on large patient data. Medline library was screened for associations between ADC and cell count in different tumors up to September 2016. Only publications in English were extracted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) was used for the research. Overall, 39 publications with 1530 patients were included into the analysis. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. The pooled correlation coefficient for all studies was ρ = -0.56 (95 % CI = [-0.62; -0.50]),. Correlation coefficients ranged from ρ =-0.25 (95 % CI = [-0.63; 0.12]) in lymphoma to ρ=-0.66 (95 % CI = [-0.85; -0.47]) in glioma. Other coefficients were as follows: ovarian cancer, ρ = -0.64 (95% CI = [-0.76; -0.52]); lung cancer, ρ = -0.63 (95 % CI = [-0.78; -0.48]); uterine cervical cancer, ρ = -0.57 (95 % CI = [-0.80; -0.34]); prostatic cancer, ρ = -0.56 (95 % CI = [-0.69; -0.42]); renal cell carcinoma, ρ = -0.53 (95 % CI = [-0.93; -0.13]); head and neck squamous cell carcinoma, ρ = -0.53 (95 % CI = [-0.74; -0.32]); breast cancer, ρ = -0.48 (95 % CI = [-0.74; -0.23]); and meningioma, ρ = -0.45 (95 % CI = [-0.73; -0.17]).
Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab; Huang, Jianhua Z.

2012-01-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric
Cationic agent contrast-enhanced computed tomography imaging of cartilage correlates with the compressive modulus and coefficient of friction.

Science.gov (United States)

Lakin, B A; Grasso, D J; Shah, S S; Stewart, R C; Bansal, P N; Freedman, J D; Grinstaff, M W; Snyder, B D

2013-01-01

The aim of this study is to evaluate whether contrast-enhanced computed tomography (CECT) attenuation, using a cationic contrast agent (CA4+), correlates with the equilibrium compressive modulus (E) and coefficient of friction (μ) of ex vivo bovine articular cartilage. Correlations between CECT attenuation and E (Group 1, n = 12) and μ (Group 2, n = 10) were determined using 7 mm diameter bovine osteochondral plugs from the stifle joints of six freshly slaughtered, skeletally mature cows. The equilibrium compressive modulus was measured using a four-step, unconfined, compressive stress-relaxation test, and the coefficients of friction were determined from a torsional friction test. Following mechanical testing, samples were immersed in CA4+, imaged using μCT, rinsed, and analyzed for glycosaminoglycan (GAG) content using the 1,9-dimethylmethylene blue (DMMB) assay. The CECT attenuation was positively correlated with the GAG content of bovine cartilage (R(2) = 0.87, P coefficients of friction: CECT vs μ(static) (R(2) = 0.71, P = 0.002), CECT vs μ(static_equilibrium) (R(2) = 0.79, P coefficient of friction. Copyright © 2012 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
A robust bayesian estimate of the concordance correlation coefficient.

Science.gov (United States)

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2015-01-01

A need for assessment of agreement arises in many situations including statistical biomarker qualification or assay or method validation. Concordance correlation coefficient (CCC) is one of the most popular scaled indices reported in evaluation of agreement. Robust methods for CCC estimation currently present an important statistical challenge. Here, we propose a novel Bayesian method of robust estimation of CCC based on multivariate Student's t-distribution and compare it with its alternatives. Furthermore, we extend the method to practically relevant settings, enabling incorporation of confounding covariates and replications. The superiority of the new approach is demonstrated using simulation as well as real datasets from biomarker application in electroencephalography (EEG). This biomarker is relevant in neuroscience for development of treatments for insomnia.
[Correlation between the inspired fraction of oxygen, maternal partial oxygen pressure, and fetal partial oxygen pressure during cesarean section of normal pregnancies].

Science.gov (United States)

Castro, Carlos Henrique Viana de; Cruvinel, Marcos Guilherme Cunha; Carneiro, Fabiano Soares; Silva, Yerkes Pereira; Cabral, Antônio Carlos Vieira; Bessa, Roberto Cardoso

2009-01-01

Despite changes in pulmonary function, maternal oxygenation is maintained during obstetric regional blocks. But in those situations, the administration of supplementary oxygen to parturients is a common practice. Good fetal oxygenation is the main justification; however, this has not been proven. The objective of this randomized, prospective study was to test the hypothesis of whether maternal hyperoxia is correlated with an increase in fetal gasometric parameters in elective cesarean sections. Arterial blood gases of 20 parturients undergoing spinal block with different inspired fractions of oxygen were evaluated and correlated with fetal arterial blood gases. An increase in maternal inspired fraction of oxygen did not show any correlation with an increase of fetal partial oxygen pressure. Induction of maternal hyperoxia by the administration of supplementary oxygen did not increase fetal partial oxygen pressure. Fetal gasometric parameters did not change even when maternal parameters changed, induced by hyperoxia, during cesarean section under spinal block.
Threshold network of a financial market using the P-value of correlation coefficients

Science.gov (United States)

Ha, Gyeong-Gyun; Lee, Jae Woo; Nobi, Ashadun

2015-06-01

Threshold methods in financial networks are important tools for obtaining important information about the financial state of a market. Previously, absolute thresholds of correlation coefficients have been used; however, they have no relation to the length of time. We assign a threshold value depending on the size of the time window by using the P-value concept of statistics. We construct a threshold network (TN) at the same threshold value for two different time window sizes in the Korean Composite Stock Price Index (KOSPI). We measure network properties, such as the edge density, clustering coefficient, assortativity coefficient, and modularity. We determine that a significant difference exists between the network properties of the two time windows at the same threshold, especially during crises. This implies that the market information depends on the length of the time window when constructing the TN. We apply the same technique to Standard and Poor's 500 (S&P500) and observe similar results.
Comparison of boiling heat transfer coefficient and pressure drop correlations for evaporators

International Nuclear Information System (INIS)

Eskin, N.; Arslan, G.

2009-01-01

Evaporator design is an important aspect for the HVAC industry. As the demand for more efficient and compact heat exchangers increase, researches on estimation of two-phase flow heat transfer and pressure drop gain importance. Due to complexity of the hydrodynamic and heat transfer of the two-phase flow, there are many experimental studies available for refrigerants int he literature. In this study, a model for boiling heat transfer in a horizontal tube has been developed and the simulation results are compared with experimental ones published in the literature. In these comparisons, heat transfer coefficient is calculated by using Kattan-Thome-Favrat (1998), Shah (1982), Kandilikar (1990), Chaddock and Brunemann (1967) correlations under different operational conditions such as saturation pressure, mass flux, the type of refrigerant and two phase flow pattern. Besides that flow pattern has also been considered in the simulation by using Thome and El Hajal (2002) model. For pressure drop Lockhart-Martinelli (1949), Mueller-Steinhagen-Hack (1986) and Groennerund (1979) correlations are used in simulations. Local vapor quality change at each experimental condition through the model is determined. Roughness is an important parameter for frictional pressure drop. Friction coefficient is determined by using Churchill (1977) model. (author)
aCORN: An experiment to measure the electron-antineutrino correlation coefficient in free neutron decay.

Science.gov (United States)

Collett, B; Bateman, F; Bauder, W K; Byrne, J; Byron, W A; Chen, W; Darius, G; DeAngelis, C; Dewey, M S; Gentile, T R; Hassan, M T; Jones, G L; Komives, A; Laptev, A; Mendenhall, M P; Nico, J S; Noid, G; Park, H; Stephenson, E J; Stern, I; Stockton, K J S; Trull, C; Wietfeldt, F E; Yerozolimsky, B G

2017-08-01

We describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. The apparatus employs a novel measurement technique in which the angular correlation is converted into a proton time-of-flight asymmetry that is counted directly, avoiding the need for proton spectroscopy. Details of the method, apparatus, detectors, data acquisition, and data reduction scheme are presented, along with a discussion of the important systematic effects.
Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients

DEFF Research Database (Denmark)

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte

2017-01-01

-derived food waste amounted to 2.21 ± 3.12% with a confidence interval of (−4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson’s correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste...... and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data......, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients....
Partial Correlation-Based Retinotopically Organized Resting-State Functional Connectivity Within and Between Areas of the Visual Cortex Reflects More Than Cortical Distance.

Science.gov (United States)

Dawson, Debra Ann; Lam, Jack; Lewis, Lindsay B; Carbonell, Felix; Mendola, Janine D; Shmuel, Amir

2016-02-01

Numerous studies have demonstrated functional magnetic resonance imaging (fMRI)-based resting-state functional connectivity (RSFC) between cortical areas. Recent evidence suggests that synchronous fluctuations in blood oxygenation level-dependent fMRI reflect functional organization at a scale finer than that of visual areas. In this study, we investigated whether RSFCs within and between lower visual areas are retinotopically organized and whether retinotopically organized RSFC merely reflects cortical distance. Subjects underwent retinotopic mapping and separately resting-state fMRI. Visual areas V1, V2, and V3, were subdivided into regions of interest (ROIs) according to quadrants and visual field eccentricity. Functional connectivity (FC) was computed based on Pearson's linear correlation (correlation), and Pearson's linear partial correlation (correlation between two time courses after the time courses from all other regions in the network are regressed out). Within a quadrant, within visual areas, all correlation and nearly all partial correlation FC measures showed statistical significance. Consistently in V1, V2, and to a lesser extent in V3, correlation decreased with increasing eccentricity separation. Consistent with previously reported monkey anatomical connectivity, correlation/partial correlation values between regions from adjacent areas (V1-V2 and V2-V3) were higher than those between nonadjacent areas (V1-V3). Within a quadrant, partial correlation showed consistent significance between regions from two different areas with the same or adjacent eccentricities. Pairs of ROIs with similar eccentricity showed higher correlation/partial correlation than pairs distant in eccentricity. Between dorsal and ventral quadrants, partial correlation between common and adjacent eccentricity regions within a visual area showed statistical significance; this extended to more distant eccentricity regions in V1. Within and between quadrants, correlation decreased
The use of photon correlation spectroscopy method for determining diffusion coefficient in brine and herring flesh

Directory of Open Access Journals (Sweden)

Shumanova M.V.

2015-03-01

Full Text Available The process fish salting has been studied by the method of photon correlation spectroscopy; the distribution of salt concentration in the solution and herring flesh with skin has been found, diffusion coefficients and salt concentrations used for creating a mathematical model of the salting technology have been worked out; the possibility of determination by this method the coefficient of dynamic viscosity of solutions and different media (minced meat etc. has been considered
Correlation between 3 T apparent diffusion coefficient values and grading of invasive breast carcinoma

Energy Technology Data Exchange (ETDEWEB)

Cipolla, Valentina, E-mail: valentina.cipolla@yahoo.it [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Santucci, Domiziana; Guerrieri, Daniele; Drudi, Francesco Maria [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Meggiorini, Maria Letizia [Department of Gynaecological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Felice, Carlo de [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy)

2014-12-15

Highlights: • Apparent diffusion coefficient is a quantitative parameter which reflects molecular water movement. • Grading is an independent prognostic factor which correlates with other histopathological features. • Apparent diffusion coefficient values were significantly different between G1 and G3 classes. - Abstract: Purpose: The aim of this study was to evaluate whether the apparent diffusion coefficient (ADC) provided by 3.0 T (3 T) magnetic resonance diffusion-weighted imaging (DWI) varied according to the grading of invasive breast carcinoma. Materials and methods: A total of 92 patients with 96 invasive breast cancer lesions were enrolled; all had undergone 3 T magnetic resonance imaging (MRI) for local staging. All lesions were confirmed by histological analysis, and tumor grade was established according to the Nottingham Grading System (NGS). MRI included both dynamic contrast-enhanced and DWI sequences, and ADC value was calculated for each lesion. ADC values were compared with NGS classification using the Mann–Whitney U and the Kruskal–Wallis H tests. Grading was considered as a comprehensive prognostic factor, and Rho Spearman test was performed to determine correlation between grading and tumor size, hormonal receptor status, HER2 expression and Ki67 index. Pearson's Chi square test was carried out to compare grading with the other prognostic factors. Results: ADC values were significantly higher in G1 than in G3 tumors. No significant difference was observed when G1 and G3 were compared with G2. Tumor size, hormonal receptor status, HER2 expression and Ki67 index correlated significantly with grading but there was a significant difference only between G1 and G3 related to the ER and PR status, HER2 expression and Ki67 index. There was no statistically significant difference in lesion size between the two groups. Conclusion: ADC values obtained on 3 T DWI correlated with low-grade (G1) and high-grade (G3) invasive breast carcinoma. 3
On bounded rank positive semidefinite matrix completions of extreme partial correlation matrices.

NARCIS (Netherlands)

M. Eisenberg-Nagy (Marianna); M. Laurent (Monique); A. Varvitsiotis (Antonios)

2012-01-01

textabstractWe study a new geometric graph parameter $egd(G)$, defined as the smallest integer $r\\ge 1$ for which any partial symmetric matrix which is completable to a correlation matrix and whose entries are specified at the positions of the edges of $G$, can be completed to a matrix in the convex
[Correlation coefficient-based principle and method for the classification of jump degree in hydrological time series].

Science.gov (United States)

Wu, Zi Yi; Xie, Ping; Sang, Yan Fang; Gu, Hai Ting

2018-04-01

The phenomenon of jump is one of the importantly external forms of hydrological variabi-lity under environmental changes, representing the adaption of hydrological nonlinear systems to the influence of external disturbances. Presently, the related studies mainly focus on the methods for identifying the jump positions and jump times in hydrological time series. In contrast, few studies have focused on the quantitative description and classification of jump degree in hydrological time series, which make it difficult to understand the environmental changes and evaluate its potential impacts. Here, we proposed a theatrically reliable and easy-to-apply method for the classification of jump degree in hydrological time series, using the correlation coefficient as a basic index. The statistical tests verified the accuracy, reasonability, and applicability of this method. The relationship between the correlation coefficient and the jump degree of series were described using mathematical equation by derivation. After that, several thresholds of correlation coefficients under different statistical significance levels were chosen, based on which the jump degree could be classified into five levels: no, weak, moderate, strong and very strong. Finally, our method was applied to five diffe-rent observed hydrological time series, with diverse geographic and hydrological conditions in China. The results of the classification of jump degrees in those series were closely accorded with their physically hydrological mechanisms, indicating the practicability of our method.
SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.

Science.gov (United States)

Weaver, Bruce; Wuensch, Karl L

2013-09-01

Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.
On bounded rank positive semidefinite matrix completions of extreme partial correlation matrices.

NARCIS (Netherlands)

M. Eisenberg-Nagy (Marianna); M. Laurent (Monique); A. Varvitsiotis (Antonios)

2012-01-01

htmlabstractWe study a new geometric graph parameter egd(G), defined as the smallest integer r ≥ 1 for which any partial symmetric matrix which is completable to a correlation matrix and whose entries are specified at the positions of the edges of G, can be completed to a matrix in the convex hull

A COMPARATIVE LOOK INTO HOW TO MEASURE THE EFFECTIVENESS OF VOCABULARY LEARNING STRATEGIES: THROUGH USING PERCENTAGES OR CORRELATION COEFFICIENTS

Directory of Open Access Journals (Sweden)

İsmail Hakkı ERTEN

2008-10-01

Full Text Available This study aims to compare the appropriateness of two statistical procedures for measuring the effectiveness of vocabulary learning strategies: percentages and correlation coefficients. To do this a group of 20 learners of English were asked to study 12 words in a written list, with their pronunciations, dictionary definitions, and example sentences. Data was collected through introspection where students were asked to verbalize their mental processes as they studied the target words. A pre-test and post-test were given to measure the task achievement. The qualitative data was transcribed verbatim and content-analysed for tokens of strategy use as well as by noting whether each use of strategies led to successful recall of the words on which they were used. To calculate the strategy effectiveness, both simple percentage calculation and correlation coefficients were employed for comparison. The findings indicated that percentage calculation can give a more realistic picture of strategy effectiveness than correlation coefficients.
Technical characterization of dialysis fluid flow and mass transfer rate in dialyzers with various filtration coefficients using dimensionless correlation equation.

Science.gov (United States)

Fukuda, Makoto; Yoshimura, Kengo; Namekawa, Koki; Sakai, Kiyotaka

2017-06-01

The objective of the present study is to evaluate the effect of filtration coefficient and internal filtration on dialysis fluid flow and mass transfer coefficient in dialyzers using dimensionless mass transfer correlation equations. Aqueous solution of vitamin B 12 clearances were obtained for REXEED-15L as a low flux dialyzer, and APS-15EA and APS-15UA as high flux dialyzers. All the other design specifications were identical for these dialyzers except for filtration coefficient. The overall mass transfer coefficient was calculated, moreover, the exponents of Reynolds number (Re) and film mass transfer coefficient of the dialysis-side fluid (k D ) for each flow rate were derived from the Wilson plot and dimensionless correlation equation. The exponents of Re were 0.4 for the low flux dialyzer whereas 0.5 for the high flux dialyzers. Dialysis fluid of the low flux dialyzer was close to laminar flow because of its low filtration coefficient. On the other hand, dialysis fluid of the high flux dialyzers was assumed to be orthogonal flow. Higher filtration coefficient was associated with higher k D influenced by mass transfer rate through diffusion and internal filtration. Higher filtration coefficient of dialyzers and internal filtration affect orthogonal flow of dialysis fluid.
AN EMPIRICAL INVESTIGATION OF THE EFFECTS OF NONNORMALITY UPON THE SAMPLING DISTRIBUTION OF THE PROJECT MOMENT CORRELATION COEFFICIENT.

Science.gov (United States)

HJELM, HOWARD; NORRIS, RAYMOND C.

THE STUDY EMPIRICALLY DETERMINED THE EFFECTS OF NONNORMALITY UPON SOME SAMPLING DISTRIBUTIONS OF THE PRODUCT MOMENT CORRELATION COEFFICIENT (PMCC). SAMPLING DISTRIBUTIONS OF THE PMCC WERE OBTAINED BY DRAWING NUMEROUS SAMPLES FROM CONTROL AND EXPERIMENTAL POPULATIONS HAVING VARIOUS DEGREES OF NONNORMALITY AND BY CALCULATING CORRELATION COEFFICIENTS…
Correlation between Mechanical Properties with Specific Wear Rate and the Coefficient of Friction of Graphite/Epoxy Composites

Directory of Open Access Journals (Sweden)

Mahdi Alajmi

2015-07-01

Full Text Available The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, wear, and friction tests were conducted for Neat Epoxy (NE, Graphite/Epoxy composites (GE, and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE. The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the specific wear rate (SWR and coefficient of friction (COF of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs, as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the specific wear rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
Correlation between Mechanical Properties with Specific Wear Rate and the Coefficient of Friction of Graphite/Epoxy Composites.

Science.gov (United States)

Alajmi, Mahdi; Shalwan, Abdullah

2015-07-08

The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, wear, and friction tests were conducted for Neat Epoxy (NE), Graphite/Epoxy composites (GE), and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE). The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the specific wear rate (SWR) and coefficient of friction (COF) of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs), as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the specific wear rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
On the construction of bivariate exponential distributions with an arbitrary correlation coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase {type distributions, The latter property is potentially important for the development hypothesis testing in linear models. Thirdly, it is very easy to simulate...
Association Between Masticatory Function and Oral Health-Related Quality of Life in Partial Maxillectomy Patients.

Science.gov (United States)

Said, Mohamed Moustafa; Otomaru, Takafumi; Aimaijiang, Yiliyaer; Li, Na; Taniguchi, Hisashi

The aim of this study was to investigate associations between objectively and subjectively measured masticatory function and oral health-related quality of life (OHRQoL) in partial maxillectomy patients wearing dentomaxillary prostheses. A sample of 32 consecutively treated patients who had undergone a partial maxillectomy were enrolled. Masticatory function was assessed using two objective measures and one subjective measure. The objective measures were masticatory performance (MP), which was estimated by measuring the glucose extracted from gummy jelly, and food mixing ability (a*), which was assessed using color-changeable chewing gum. The subjective measure was perceived chewing ability, rated as masticatory score (MS) based on the patient's responses to a food intake questionnaire. OHRQoL was assessed using the Geriatric Oral Health Assessment Index (GOHAI). Relationships between the masticatory function measures and OHRQoL were analyzed using Spearman rank correlation coefficient. The correlation coefficients (r) obtained were 0.57 (P = .001) for MS and GOHAI, 0.247 (P = .173) for MP and GOHAI, -0.173 (P = .343) for a* and GOHAI, 0.517 (P = .002) for MP and a*, 0.199 (P = .257) for MP and MS, and 0.019 (P = .919) for a* and MS. Subjective MS showed a significant positive correlation with GOHAI score, suggesting that perceived chewing ability could be an important factor in the estimation of OHRQoL in partial maxillectomy patients.
Partial Edentulism and its Correlation to Age, Gender, Socio-economic Status and Incidence of Various Kennedy's Classes- A Literature Review.

Science.gov (United States)

Jeyapalan, Vidhya; Krishnan, Chitra Shankar

2015-06-01

Partial edentulism, one or more teeth missing is an indication of healthy behaviour of dental practices in the society and attitude towards dental and oral care. The pattern of partial edentulism has been evaluated in many selected populations in different countries by different methods. Most of the studies have evaluated partial edentulism by surveying of Removable Partial Dentures (RPDs), patients visiting clinics, clinical records and population in particular locality. The objective of the study is to review the prevalence of partial edentulousness and its correlation to age,gender, arch predominance, socio economic factors and incidence of various Kennedy's Classes. Key observations drawn from the review are as below. There is no gender correlation for partial edentulism.Prevalence of partial edentulism is more common in mandibular arch than maxillary arch.Younger adults have more Class III and IV RPDs. Elders have more distal extension RPDs Class I and II.
Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

Science.gov (United States)

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…
Solving Variable Coefficient Fourth-Order Parabolic Equation by ...

African Journals Online (AJOL)

Solving Variable Coefficient Fourth-Order Parabolic Equation by Modified initial guess Variational ... variable coefficient fourth order parabolic partial differential equations. The new method shows rapid convergence to the exact solution.
Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

Directory of Open Access Journals (Sweden)

Iwan Setyawan

2011-12-01

Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.
Heat transfer coefficient correlation for convective boiling inside plain and micro fin tubes using genetic algorithms

International Nuclear Information System (INIS)

Picanco, Marco Antonio Silva; Bandarra Filho, Enio Pedone; Passos, Julio Cesar

2006-01-01

Two-phase flow heat transfer has been exhaustively studied over recent years. However, in this field several questions remain unanswered. Heat transfer coefficient prediction related to nucleate and convective boiling have been studied using different approaches, numerical, analytical and experimental. In this work, an experimental analysis, data representation and heat transfer coefficient prediction on two-phase heat transfer on nucleate and convective boiling are presented. An empirical correlation is obtained based on genetic algorithms search engine over a dimensional analysis of the two-phase flow heat transfer problem. (author)
Cross-correlations and influence in world gold markets

Science.gov (United States)

Lin, Min; Wang, Gang-Jin; Xie, Chi; Stanley, H. Eugene

2018-01-01

Using the detrended cross-correlation analysis (DCCA) coefficient and the detrended partial cross-correlation analysis (DPCCA) coefficient, we investigate cross-correlations and net cross-correlations among five major world gold markets (London, New York, Shanghai, Tokyo, and Mumbai) at different time scales. We propose multiscale influence measures for examining the influence of individual markets on other markets and on the entire system. We find (i) that the cross-correlations, net cross-correlations, and net influences among the five gold markets vary across time scales, (ii) that the cross-market correlation between London and New York at each time scale is intense and inherent, meaning that the influence of other gold markets on the London-New York market is negligible, (iii) that the remaining cross-market correlations (i.e., those other than London-New York) are greatly affected by other gold markets, and (iv) that the London gold market significantly affects the other four gold markets and dominates the world-wide gold market. Our multiscale findings give market participants and market regulators new information on cross-market linkages in the world-wide gold market.
Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

Science.gov (United States)

Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu

2017-09-01

Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

Science.gov (United States)

Ma, Chuang; Wang, Xiangfeng

2012-09-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.
The relation between Pearson’s correlation coefficient r and Salton’s cosine measure

OpenAIRE

EGGHE, Leo; Leydesdorff, L.

2009-01-01

The relation between Pearson’s correlation coefficient and Salton’s cosine measure is revealed based on the different possible values of the division of the -norm and the norm of a vector. These different values yield a sheaf of increasingly straight lines which form together a cloud of points, being the investigated relation. These theoretical results are tested against the author co-citation relations among 24 informetricians for who two matrices can be constructed, based on co-citations: t...
Comparison Study on Empirical Correlation for Mass Transfer Coefficient with Gas Hold-up and Input Power of Aeration Process

International Nuclear Information System (INIS)

Park, Sang Kyoo; Yang, Hei Cheon

2017-01-01

As stricter environmental regulation have led to an increase in the water treatment cost, it is necessary to quantitatively study the input power of the aeration process to improve the energy efficiency of the water treatment processes. The objective of this study is to propose the empirical correlations for the mass transfer coefficient with the gas hold-up and input power in order to investigate the mass transfer characteristics of the aeration process. It was found that as the input power increases, the mass transfer coefficient increases because of the decrease of gas hold-up and increase of Reynolds number, the penetration length, and dispersion of mixed flow. The correlations for the volumetric mass transfer coefficients with gas hold-up and input power were consistent with the experimental data, with the maximum deviation less than approximately ±10.0%.
Comparison Study on Empirical Correlation for Mass Transfer Coefficient with Gas Hold-up and Input Power of Aeration Process

Energy Technology Data Exchange (ETDEWEB)

Park, Sang Kyoo; Yang, Hei Cheon [Chonnam Nat’l Univ., Gwangju (Korea, Republic of)

2017-06-15

As stricter environmental regulation have led to an increase in the water treatment cost, it is necessary to quantitatively study the input power of the aeration process to improve the energy efficiency of the water treatment processes. The objective of this study is to propose the empirical correlations for the mass transfer coefficient with the gas hold-up and input power in order to investigate the mass transfer characteristics of the aeration process. It was found that as the input power increases, the mass transfer coefficient increases because of the decrease of gas hold-up and increase of Reynolds number, the penetration length, and dispersion of mixed flow. The correlations for the volumetric mass transfer coefficients with gas hold-up and input power were consistent with the experimental data, with the maximum deviation less than approximately ±10.0%.
Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

Science.gov (United States)

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.
Correlation and path coefficient analysis of quantitative characters in spine gourd (Momordica dioica Roxb.).

Science.gov (United States)

Aliya, F; Begum, H; Reddy, M T; Sivaraj, N; Pandravada, S R; Narshimulu, G

2014-05-01

Fifty genotypes of spine gourd (Momordica dioica Roxb.) were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India during kharif, 2012. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively for twelve quantitative characters namely vine length (m), number of stems per plant, days to first female flower appearance, first female flowering node, days to first fruit harvest, days to last fruit harvest, fruiting period (days), fruit length (cm), fruit width (cm), fruit weight (g), number of fruits per plant and fruit yield per plant (kg) for identification of the potential selection indices. Correlation and path coefficient analyses revealed that fruiting period and number of fruits per plant not only had positively significant correlation with fruit yield but also had positively high direct effect on it and are regarded as the main determinants of fruit yield. Days to first fruit harvest had positively moderate direct effect on fruit yield and its association was negatively significant, days to last fruit harvest had negatively high direct effect on fruit yield and its association was significant positively, hence restricted simultaneous selection can be made for days to first fruit harvest and days to last fruit harvest. The improvement in fruit yield can be effective if selection is based on days to first fruit harvest, days to last fruit harvest, fruiting period and number of fruits per plant.

Spatial correlation in 3D MIMO channels using fourier coefficients of power spectrums

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2015-03-01

In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for the standardized three-dimensional (3D) multiple-input multiple-output (MIMO) channel. This novel SCF is developed for a uniform linear array of antennas with non-isotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials to obtain a closed-form expression for the SCF for arbitrary angular distributions and antenna patterns. The resulting expression depends on the underlying angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. Numerical results validate the proposed analytical expression and study the impact of angular spreads on the correlation. The derived SCF will help evaluate the performance of correlated 3D MIMO channels in the future. © 2015 IEEE.
Probabilistic optimization of safety coefficients

International Nuclear Information System (INIS)

Marques, M.; Devictor, N.; Magistris, F. de

1999-01-01

This article describes a reliability-based method for the optimization of safety coefficients defined and used in design codes. The purpose of the optimization is to determine the partial safety coefficients which minimize an objective function for sets of components and loading situations covered by a design rule. This objective function is a sum of distances between the reliability of the components designed using the safety coefficients and a target reliability. The advantage of this method is shown on the examples of the reactor vessel, a vapour pipe and the safety injection circuit. (authors)
Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab

2012-10-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
Probability based calibration of pressure coefficients

DEFF Research Database (Denmark)

Hansen, Svend Ole; Pedersen, Marie Louise; Sørensen, John Dalsgaard

2015-01-01

Normally, a consistent basis for calculating partial factors focuses on a homogeneous reliability index neither depending on which material the structure is constructed of nor the ratio between the permanent and variable actions acting on the structure. Furthermore, the reliability index should n...... the characteristic shape coefficients are based on mean values as specified in background documents to the Eurocodes. Importance of hidden safeties judging the reliability is discussed for wind actions on low-rise structures....... not depend on the type of variable action. A probability based calibration of pressure coefficients have been carried out using pressure measurements on the standard CAARC building modelled on scale of 1:383. The extreme pressures measured on the CAARC building model in the wind tunnel have been fitted.......3, the Eurocode partial factor of 1.5 for variable actions agrees well with the inherent uncertainties of wind actions when the pressure coefficients are determined using wind tunnel test results. The increased bias and uncertainty when pressure coefficients mainly are based on structural codes lead to a larger...
Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient

OpenAIRE

Ahlgren, P.; Jarneving, B.; ROUSSEAU, Ronald

2003-01-01

Author cocitation analysis (ACA), a special type of cocitation analysis, was introduced by White and Griffith in 1981. This technique is used to analyze the intellectual structure of a given scientific field. In 1990, McCain published a technical overview that has been largely adopted as a standard. Here, McCain notes that Pearson's correlation coefficient (Pearson's r) is often used as a similarity measure in ACA and presents some advantages of its use. The present article criticizes the use...
Closed-Form Representations of the Density Function and Integer Moments of the Sample Correlation Coefficient

Directory of Open Access Journals (Sweden)

Serge B. Provost

2015-07-01

Full Text Available This paper provides a simplified representation of the exact density function of R, the sample correlation coefficient. The odd and even moments of R are also obtained in closed forms. Being expressed in terms of generalized hypergeometric functions, the resulting representations are readily computable. Some numerical examples corroborate the validity of the results derived herein.
An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

Science.gov (United States)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.
Measurement of the polarization correlation coefficient in elastic pp scattering at 610 MeV

International Nuclear Information System (INIS)

Borisov, N.S.; Glonti, L.N.; Kazarinov, M.Yu.

1977-01-01

The polarization correlation coefficient Csub(nn) for elastic pp scattering at 610+-10 MeV was measured for four scattering angles: 40, 67, 78 and 90 deg (c.m.s.). A polarized proton beam with a maximum polarization of 0.39+-0.02 and a polarized proton target of the frozen type were used. The maximum polarization of the target was 0.97+-0.04. The experimental procedure is described in detail. The Csub(nn) measured are compared with the results of a phase analysis and the findings at 575 MeV obtained elsewhere. The Csub(nn) coefficients are shown to be valuable to discriminate alternative solutions of the phase analysis. The polarized proton targets of the frozen type, no accounting the complexity of their design, are emphasized to be rather reliable and convenient devices for conducting experiments at accelerators
Partial inelasticity coefficients of negative pions in p, d, α, 12C + 12C and p, 12C + 181Ta collisions at 4.2 GeV/c per nucleon

International Nuclear Information System (INIS)

Olimov, K.K.; Olimov, K.; Gulamov, K.G.; Olimov, A.K.; Lutpullaev, S.L.; Yuldashev, B.S.; Haseeb, M.Q.

2015-01-01

The partial inelasticity coefficients of the negative pions were determined in minimum bias p, d, α, 12 C + 12 C and p, 12 C + 18 Ta collisions at 4.2A GeV/c taking into account the average number of participant nucleons of a projectile nucleus. In nucleus–nucleus collisions, the average values of partial inelasticity coefficients (〈K(π-)〉) of the negative pions did not depend on the mass numbers of projectile and target nuclei. Increase of 〈K(π - )〉 in going from p + 12 C to d, α, 12 C + 12 C collisions was due to an additional source of production of fast negative pions in nucleus–nucleus collisions — a charge exchange conversion of one or more neutrons of a projectile nucleus into a proton and π - . Linking the experimental results of the present analysis at intermediate energy with those obtained at high and ultra-high energies, it was concluded that the average values of partial inelasticity coefficients of pions in nucleon–nucleus and nucleus–nucleus collisions manifest a transitive behavior. At intermediate energies, the values of 〈K(π - )〉 were smaller by a factor of two and more as compared to those at high energies, and they increased further with increasing incident energy, reaching a plateau at E 0 > 100A GeV. (author)
On the correlation between radio and gamma-ray luminosities of active galactic nuclei

DEFF Research Database (Denmark)

Mücke, A.; Pohl, M.

1997-01-01

in flux-limited samples if intrinsic scatter does not exceed similar to 40 % of the original gamma-ray luminosity. However, if mean flux values of high variable sources are used we find the chance probability of high Spearman's correlation coefficient be significant underestimated. The analysis presented......The possibility of a correlation between the radio (cm)- and gamma-ray luminosity of variable AGN seen by EGRET is investigated. We perform Monte-Carlo simulations of typical data sets and apply different correlation techniques (partial correlation analysis, chi(2)-test applied on flux......-flux relations) in view of a truncation bias caused by sensitivity limits of the surveys. For K-corrected flux densities, we find that with the least squares method only a linear correlation can be recovered. Partial correlation analysis on the other side provides a robust tool to detect correlations even...
Correlation functions for the distribution coefficients of U(IV) and Pu(III) ions between aqueous nitric acid and 30% TBP in an aliphatic diluent

International Nuclear Information System (INIS)

Geldard, J.F.; Beyerlein, A.L.; Phillips, L.

1985-01-01

Distribution coefficient correlations for U(IV) and Pu(III) are obtained in terms of a modified form of the total nitrate ion salting strength that was successfully used to obtain distribution coefficient correlations for U(VI) and Pu(IV) in the earlier work of G.L. Richardson. The modification of salting strength was needed to account for the fact that the U(IV) distribution coefficients measured under conditions where U(VI) is present consistently fall below those obtained when it is absent. The correlations were incorporated into the mixer-settler computer model PUBG, and in the simulation of a 20-stage 1B partitioning contactor, calculated product stream concentrations were in excellent agreement with experiment. Earlier mixer-settler computer models, which failed to account for U(IV) distribution coefficients, predicted that U(IV) remained in the aqueous product stream, which is contrary to the experimental measurements
Correlation functions for the distribution coefficients of U(IV) and Pu(III) ions between aqueous nitric acid and 30% TBP in an aliphatic diluent

Energy Technology Data Exchange (ETDEWEB)

Geldard, J.F.; Beyerlein, A.L.; Phillips, L.

1985-09-01

Distribution coefficient correlations for U(IV) and Pu(III) are obtained in terms of a modified form of the total nitrate ion salting strength that was successfully used to obtain distribution coefficient correlations for U(VI) and Pu(IV) in the earlier work of G.L. Richardson. The modification of salting strength was needed to account for the fact that the U(IV) distribution coefficients measured under conditions where U(VI) is present consistently fall below those obtained when it is absent. The correlations were incorporated into the mixer-settler computer model PUBG, and in the simulation of a 20-stage 1B partitioning contactor, calculated product stream concentrations were in excellent agreement with experiment. Earlier mixer-settler computer models, which failed to account for U(IV) distribution coefficients, predicted that U(IV) remained in the aqueous product stream, which is contrary to the experimental measurements.
Prediction of friction coefficients for gases

Science.gov (United States)

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.
A principle to correlate extreme values of excess thermodynamic functions with partial molar quantities

Institute of Scientific and Technical Information of China (English)

尉志武; 刘芸; 周蕊; 薛芳渝

2001-01-01

Excess thermodynamic properties are widely used quantitatively for fluids. It was found that at constant temperature and pressure a molar excess quantity of a mutually miscible binary mixture at the extreme points equals the excess partial molar quantities of the two components, i.e.F1E = F2E = FmE , forming a triple cross point. The relationship is hold for properties such as en-thalpy, entropy, Gibbs free energy, and volume, and is applicable for excess functions with multi extreme points. Solutions at extreme points can be referred to as special mixtures. Particularly fora special mixture of Gibbs free energy, activity coefficients of the two components are identical.
Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

International Nuclear Information System (INIS)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.
Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

Energy Technology Data Exchange (ETDEWEB)

Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)

2017-01-15

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.
A principle to correlate extreme values of excess thermody-namic functions with partial molar quantities

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

Excess thermodynamic properties are widely used quantitatively for fluids. It was found that at constant temperature and pressure a molar excess quantity of a mutually miscible binary mixture at the extreme points equals the excess partial molar quantities of the two components, i.e. , forming a triple cross point. The relationship is hold for properties such as enthalpy, entropy, Gibbs free energy, and volume, and is applicable for excess functions with multi extreme points. Solutions at extreme points can be referred to as special mixtures. Particularly for a special mixture of Gibbs free energy, activity coefficients of the two components are identical.
Heat transfer coefficient for boiling carbon dioxide

DEFF Research Database (Denmark)

Knudsen, Hans Jørgen Høgaard; Jensen, Per Henrik

1998-01-01

Heat transfer coefficient and pressure drop for boiling carbon dioxide (R744) flowing in a horizontal pipe has been measured. The calculated heat transfer coeeficient has been compared with the Chart correlation of Shah. The Chart Correlation predits too low heat transfer coefficient but the ratio...... between the measured and the calculated heat transfer coefficient is nearly constant and equal 1.9. With this factor the correlation predicts the measured data within 14% (RMS). The pressure drop is of the same order as the measuring uncertainty and the pressure drop has not been compared with correlation's....
Development of the loss coefficient correlation for cross flow between graphite fuel blocks in the core of prismatic very high temperature reactor-PMR200

International Nuclear Information System (INIS)

Lee, Jeong-Hun; Cho, Hyoung-Kyu; Park, Goon-Cherl

2016-01-01

Highlights: • Cross flow experimental data are produced with wedge-shaped and parallel gaps. • The results of a CFD analysis and experimental data are in good agreement. • Pressure loss coefficient for the cross gap between fuel blocks in PMR200 is found. • A new correlation of the cross flow loss coefficient for PMR200 is proposed. - Abstract: The core of the very high temperature reactor (VHTR) PMR200 (a prismatic modular reactor rated at 200 MW of thermal power) consists of hexagonal prismatic fuel blocks and reflector blocks made of graphite. If the core bypass flow ratio increases, the coolant channel flow is decreased and can then lower the heat removal efficiency, resulting in a locally increased fuel block temperature. The coolant channels in the fuel blocks are connected to bypass gaps by the cross gap, complicating flow distribution in the VHTR core. Therefore, reliable estimation of the bypass flow is highly important for the design and safety analysis of the VHTR core. Because of the complexity of the core geometry and gap configuration, it is challenging to predict the flow distribution in the VHTR core. To analyze this flow distribution accurately, it is necessary to determine the cross flow phenomena, and the loss coefficient across the cross gap has to be evaluated to determine the flow distribution in the VHTR core when a lumped parameter code or a flow network analysis code that uses the correlation of the loss coefficient is employed. The purpose of this paper is to develop a loss coefficient correlation applicable to the cross gap in the PMR200 core. The cross flow was evaluated experimentally using the difference between the measured inlet and outlet mass flow rates. Next, the applicability of a commercial computational fluid dynamics (CFD) code, CFX 15, was confirmed by comparing the experimental data and CFD analysis results. To understand the cross flow phenomena, the loss coefficient was evaluated; in the high Reynolds number region
Development of the loss coefficient correlation for cross flow between graphite fuel blocks in the core of prismatic very high temperature reactor-PMR200

Energy Technology Data Exchange (ETDEWEB)

Lee, Jeong-Hun, E-mail: huny12@snu.ac.kr; Cho, Hyoung-Kyu, E-mail: chohk@snu.ac.kr; Park, Goon-Cherl, E-mail: parkgc@snu.ac.kr

2016-10-15

Highlights: • Cross flow experimental data are produced with wedge-shaped and parallel gaps. • The results of a CFD analysis and experimental data are in good agreement. • Pressure loss coefficient for the cross gap between fuel blocks in PMR200 is found. • A new correlation of the cross flow loss coefficient for PMR200 is proposed. - Abstract: The core of the very high temperature reactor (VHTR) PMR200 (a prismatic modular reactor rated at 200 MW of thermal power) consists of hexagonal prismatic fuel blocks and reflector blocks made of graphite. If the core bypass flow ratio increases, the coolant channel flow is decreased and can then lower the heat removal efficiency, resulting in a locally increased fuel block temperature. The coolant channels in the fuel blocks are connected to bypass gaps by the cross gap, complicating flow distribution in the VHTR core. Therefore, reliable estimation of the bypass flow is highly important for the design and safety analysis of the VHTR core. Because of the complexity of the core geometry and gap configuration, it is challenging to predict the flow distribution in the VHTR core. To analyze this flow distribution accurately, it is necessary to determine the cross flow phenomena, and the loss coefficient across the cross gap has to be evaluated to determine the flow distribution in the VHTR core when a lumped parameter code or a flow network analysis code that uses the correlation of the loss coefficient is employed. The purpose of this paper is to develop a loss coefficient correlation applicable to the cross gap in the PMR200 core. The cross flow was evaluated experimentally using the difference between the measured inlet and outlet mass flow rates. Next, the applicability of a commercial computational fluid dynamics (CFD) code, CFX 15, was confirmed by comparing the experimental data and CFD analysis results. To understand the cross flow phenomena, the loss coefficient was evaluated; in the high Reynolds number region

Correlation functions for fully or partially state-resolved reactive scattering calculations

International Nuclear Information System (INIS)

Manthe, Uwe; Welsch, Ralph

2014-01-01

Flux correlation functions and the quantum transition state concept are important tools for the accurate description of polyatomic reaction processes. Combined with the multi-configurational time-dependent Hartree approach, they facilitate rigorous full-dimensional calculations of cumulative and initial-state selected reaction probabilities for six atom reactions. In recent work [R. Welsch, F. Huarte-Larrañaga, and U. Manthe, J. Chem. Phys. 136, 064117 (2012)], an approach which allows one to calculate also state-to-state reaction probabilities within the quantum transition state concept has been introduced. This article presents further developments. Alternative generalized flux correlation functions are introduced and discussed. Equations for the calculation of fully state-resolved differential cross section using arbitrary definitions of the body fixed frame are derived. An approach for the efficient calculation of partially state-resolved observables as a function of the collision energy is introduced. Finally, numerical test studying the D + H 2 reaction illustrate important aspects of the formalism
Common pediatric cerebellar tumors: correlation between cell densities and apparent diffusion coefficient metrics.

Science.gov (United States)

Koral, Korgün; Mathis, Derek; Gimi, Barjor; Gargan, Lynn; Weprin, Bradley; Bowers, Daniel C; Margraf, Linda

2013-08-01

To test whether there is correlation between cell densities and apparent diffusion coefficient (ADC) metrics of common pediatric cerebellar tumors. This study was reviewed for issues of patient safety and confidentiality and was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center and was compliant with HIPAA. The need for informed consent was waived. Ninety-five patients who had preoperative magnetic resonance imaging and surgical pathologic findings available between January 2003 and June 2011 were included. There were 37 pilocytic astrocytomas, 34 medulloblastomas (23 classic, eight desmoplastic-nodular, two large cell, one anaplastic), 17 ependymomas (13 World Health Organization [WHO] grade II, four WHO grade III), and seven atypical teratoid rhabdoid tumors. ADCs of solid tumor components and normal cerebellum were measured. Tumor-to-normal brain ADC ratios (hereafter, ADC ratio) were calculated. The medulloblastomas and ependymomas were subcategorized according to the latest WHO classification, and tumor cellularity was calculated. Correlation was sought between cell densities and mean tumor ADCs, minimum tumor ADCs, and ADC ratio. When all tumors were considered together, negative correlation was found between cellularity and mean tumor ADCs (ρ = -0.737, P correlation between cellularity and ADC ratio. Negative correlation was found between cellularity and minimum tumor ADC in atypical teratoid rhabdoid tumors (ρ = -0.786, P correlation was found between cellularity and mean tumor ADC and ADC ratio. There was no correlation between the ADC metrics and cellularity of the pilocytic astrocytomas, medulloblastomas, and ependymomas. Negative correlation was found between cellularity and ADC metrics of common pediatric cerebellar tumors. Although ADC metrics are useful in the preoperative diagnosis of common pediatric cerebellar tumors and this utility is generally attributed to differences in cellularity of tumors
Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

Science.gov (United States)

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.
Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.

Science.gov (United States)

Chirico, Nicola; Gramatica, Paola

2011-09-26

The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.
Endometrial cancer: correlation of apparent diffusion coefficient (ADC) with tumor cellularity and tumor grade.

Science.gov (United States)

Kishimoto, Keiko; Tajima, Shinya; Maeda, Ichiro; Takagi, Masayuki; Ueno, Takahiko; Suzuki, Nao; Nakajima, Yasuo

2016-08-01

Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) are widely used for detecting uterine endometrial cancer. The relationships between ADC values and pathological features of endometrial cancer have not yet been established. To investigate whether ADC values of endometrial cancer vary according to histologic tumor cellularity and tumor grade. We retrospectively reviewed 30 pathologically confirmed endometrial cancers. All patients underwent conventional non-enhanced magnetic resonance imaging (MRI) and DWI procedures, and ADC values were calculated. Tumor cellularity was evaluated by counting cancer cells in three high-power ( × 400) fields. The correlation between ADC values and tumor cellularity was assessed using Pearson's correlation coefficient test for statistical analysis. The mean ± standard deviation (SD) ADC value ( ×10(-3) mm(2)/s) of endometrial cancer was 0.85 ± 0.22 (range, 0.55-1.71). The mean ± SD tumor cellularity was 528.36 ± 16.89 (range, 298.0-763.6). ADC values were significantly inversely correlated with tumor cellularity. No significant relationship was observed between ADC values and tumor grade (mean ADC values: G1, 0.88 ± 0.265 × 10(-3) mm(2)/s; G2, 0.80 ± 0.178 × 10(-3) mm(2)/s; G3, 0.81 ± 0.117 × 10(-3) mm(2)/s). There is a significant inverse relationship between ADC values and tumor cellularity in endometrial cancer. No significant differences in average ADC value were observed between G1, G2, and G3 tumors. However, the lower the tumor grade, the wider the SD. © The Foundation Acta Radiologica 2015.
Improvement of a new rotation function for molecular replacement by designing new scoring functions and dynamic correlation coefficient

Science.gov (United States)

Jiang, Fan; Ding, Wei

2010-10-01

A previously published new rotation function has been improved by using a dynamic correlation coefficient as well as two new scoring functions of relative entropy and mean-square-residues to make the rotation function more robust and independent of a specific set of weights for scoring and ranking. The previously described new rotation function calculates the rotation function of molecular replacement by matching the search model directly with the Patterson vector map. The signal-to-noise ratio for the correct match was increased by averaging all the matching peaks. Several matching scores were employed to evaluate the goodness of matching. These matching scores were then combined into a single total score by optimizing a set of weights using the linear regression method. It was found that there exists an optimal set of weights that can be applied to the global rotation search and the correct solution can be ranked in the top 100 or less. However, this set of optimal weights in general is dependent on the search models and the crystal structures with different space groups and cell parameters. In this work, we try to solve this problem by designing a dynamic correlation coefficient. It is shown that the dynamic correlation coefficient works for a variety of space groups and cell parameters in the global search of rotation function. We also introduce two new matching scores: relative entropy and mean-square-residues. Last but not least, we discussed a valid method for the optimization of the adjustable parameters for matching vectors.
Improvement of a new rotation function for molecular replacement by designing new scoring functions and dynamic correlation coefficient

International Nuclear Information System (INIS)

Fan, Jiang; Wei, Ding

2010-01-01

A previously published new rotation function has been improved by using a dynamic correlation coefficient as well as two new scoring functions of relative entropy and mean-square-residues to make the rotation function more robust and independent of a specific set of weights for scoring and ranking. The previously described new rotation function calculates the rotation function of molecular replacement by matching the search model directly with the Patterson vector map. The signal-to-noise ratio for the correct match was increased by averaging all the matching peaks. Several matching scores were employed to evaluate the goodness of matching. These matching scores were then combined into a single total score by optimizing a set of weights using the linear regression method. It was found that there exists an optimal set of weights that can be applied to the global rotation search and the correct solution can be ranked in the top 100 or less. However, this set of optimal weights in general is dependent on the search models and the crystal structures with different space groups and cell parameters. In this work, we try to solve this problem by designing a dynamic correlation coefficient. It is shown that the dynamic correlation coefficient works for a variety of space groups and cell parameters in the global search of rotation function. We also introduce two new matching scores: relative entropy and mean-square-residues. Last but not least, we discussed a valid method for the optimization of the adjustable parameters for matching vectors. (condensed matter: structure, thermal and mechanical properties)
Correlation between mass transfer coefficient kLa and relevant operating parameters in cylindrical disposable shaken bioreactors on a bench-to-pilot scale.

Science.gov (United States)

Klöckner, Wolf; Gacem, Riad; Anderlei, Tibor; Raven, Nicole; Schillberg, Stefan; Lattermann, Clemens; Büchs, Jochen

2013-12-02

Among disposable bioreactor systems, cylindrical orbitally shaken bioreactors show important advantages. They provide a well-defined hydrodynamic flow combined with excellent mixing and oxygen transfer for mammalian and plant cell cultivations. Since there is no known universal correlation between the volumetric mass transfer coefficient for oxygen kLa and relevant operating parameters in such bioreactor systems, the aim of this current study is to experimentally determine a universal kLa correlation. A Respiration Activity Monitoring System (RAMOS) was used to measure kLa values in cylindrical disposable shaken bioreactors and Buckingham's π-Theorem was applied to define a dimensionless equation for kLa. In this way, a scale- and volume-independent kLa correlation was developed and validated in bioreactors with volumes from 2 L to 200 L. The final correlation was used to calculate cultivation parameters at different scales to allow a sufficient oxygen supply of tobacco BY-2 cell suspension cultures. The resulting equation can be universally applied to calculate the mass transfer coefficient for any of seven relevant cultivation parameters such as the reactor diameter, the shaking frequency, the filling volume, the viscosity, the oxygen diffusion coefficient, the gravitational acceleration or the shaking diameter within an accuracy range of +/- 30%. To our knowledge, this is the first kLa correlation that has been defined and validated for the cited bioreactor system on a bench-to-pilot scale.
Permeability dependence of streaming potential coefficient in porous media

NARCIS (Netherlands)

Thanh, L.D.; Sprik, R.

2015-01-01

In theory, the streaming potential coefficient depends not only on the zeta potential but also on the permeability of the rocks that partially determines the surface conductivity of the rocks. However, in practice, it is hard to show the permeability dependence of streaming potential coefficients
Genetic Variability, Correlation Studies and Path Coefficient Analysis in Gladiolus Alatus Cultivars

International Nuclear Information System (INIS)

Ramzan, A.; Nawab, N. N.; Tariq, M. S.; Ikram, S.; Ahad, A.

2016-01-01

A study was undertaken to find out the estimates of genetic variability, genetic parameters and character association among different flower traits between three gladiolus cultivars viz: Sancerre, Fado and Advanced Red. The experiment was repeated three times by using RCBD (Randomized complete block design) at Department of Horticulture, PMAS-UAAR, Rawalpindi. The highest genotypic coefficient variation (GCV) and phenotypic coefficient variation (PCV) magnitude was observed for spike length (16.00) and number of florets per spike (14.84) followed by number of leaves (10.00). Among the traits studied the highest heritability estimates was recorded in spike length (99.5 percent) followed by number of florets/spike (99.6 percent) and lowest in plant height (98.2 percent). The genetic advance as percent of mean was ranged from 2.8 percent to 24.75 percent. Genetic advance was highest for floret breadth (24.75 percent) and lowest for plant height (2.8 percent). High heritability combined with high genetic advance was noticed for number of florets per spike, spike length and floret breadth indicating additive gene action which suggested that improvement of these traits would be effective for further selection of superior genotypes. Plant height and number of florets per spike showed highly positive and significant association with spike length, number of leaves, leaf area, floret length and floret breadth while, spike length registered positive and significant correlation with number of leaves and floret breadth. The path coefficient analysis based on spike length, as responsible variable exposed that all of the traits exerted direct positive effect except leaf area and floret length. Spike length imparted maximum positive direct effect on the number of florets per spike. Hence, spike length and number of florets per spike may be considered for further improvement. However, Floret length and floret breadth may also be considered as a criterion for selection. (author)
Relationship Between Preoperative Extrusion of the Medial Meniscus and Surgical Outcomes After Partial Meniscectomy.

Science.gov (United States)

Kim, Sung-Jae; Choi, Chong Hyuk; Chun, Yong-Min; Kim, Sung-Hwan; Lee, Su-Keon; Jang, Jinyoung; Jeong, Howon; Jung, Min

2017-07-01

No previous study has examined arthritic change after meniscectomy with regard to extrusion of the medial meniscus. (1) To determine the factors related to preoperative meniscal extrusion; (2) to investigate the relationship between medial meniscal extrusion and postoperative outcomes of partial meniscectomy, and to identify a cutoff point of meniscal extrusion that contributes to arthritic change after partial meniscectomy in nonosteoarthritic knees. Cohort study; Level of evidence, 3. A total of 208 patients who underwent partial meniscectomy of the medial meniscus between January 2000 and September 2006 were retrospectively reviewed. The extent of extrusion and severity of degeneration of the medial meniscus as shown on preoperative MRI were evaluated. The minimum follow-up duration was 7 years. Clinical function was assessed with the Lysholm knee scoring scale, the International Knee Documentation Committee (IKDC) subjective knee evaluation form, and the Tapper and Hoover grading system. Radiological evaluation was conducted by use of the IKDC radiographic assessment scale. Regression analysis was performed to identify factors affecting preoperative extrusion of the medial meniscus and factors influencing follow-up results after partial meniscectomy. Receiver operating characteristic curve was used to identify a cutoff point for the extent of meniscal extrusion that was associated with arthritic change. The mean ± SD preoperative Lysholm knee score was 65.0 ± 6.3 and the mean IKDC subjective score was 60.1 ± 7.5. The mean follow-up functional scores were 93.2 ± 5.1 ( P meniscus showed a tendency to increase as the extent of intrameniscal degeneration increased, and the medial meniscus was extruded more in patients with horizontal, horizontal flap, and complex tears. The preoperative extent of meniscal extrusion had a statistically significant correlation with follow-up Lysholm knee score (coefficient = -0.10, P = .002), IKDC subjective score (coefficient
Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

Science.gov (United States)

Ma, Chuang; Wang, Xiangfeng

2012-01-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655
Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

Science.gov (United States)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
A Bayesian Framework for Estimating the Concordance Correlation Coefficient Using Skew-elliptical Distributions.

Science.gov (United States)

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2018-04-05

The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently encountered in practice such as confounding covariates and missing data. The performance of the proposal was studied and demonstrated using simulated as well as real-life biomarker data from a clinical study of an insomnia drug. The implementation of the proposal is accessible through a package in the Comprehensive R Archive Network.
Using Generalizability Theory to Disattenuate Correlation Coefficients for Multiple Sources of Measurement Error.

Science.gov (United States)

Vispoel, Walter P; Morris, Carrie A; Kilinc, Murat

2018-05-02

Over the years, research in the social sciences has been dominated by reporting of reliability coefficients that fail to account for key sources of measurement error. Use of these coefficients, in turn, to correct for measurement error can hinder scientific progress by misrepresenting true relationships among the underlying constructs being investigated. In the research reported here, we addressed these issues using generalizability theory (G-theory) in both traditional and new ways to account for the three key sources of measurement error (random-response, specific-factor, and transient) that affect scores from objectively scored measures. Results from 20 widely used measures of personality, self-concept, and socially desirable responding showed that conventional indices consistently misrepresented reliability and relationships among psychological constructs by failing to account for key sources of measurement error and correlated transient errors within occasions. The results further revealed that G-theory served as an effective framework for remedying these problems. We discuss possible extensions in future research and provide code from the computer package R in an online supplement to enable readers to apply the procedures we demonstrate to their own research.
Correlation between tissue metabolism and cellularity assessed by standardized uptake value and apparent diffusion coefficient in peritoneal metastasis.

Science.gov (United States)

Yu, Xue; Lee, Elaine Yuen Phin; Lai, Vincent; Chan, Queenie

2014-07-01

To evaluate the correlation between standardized uptake value (SUV) (tissue metabolism) and apparent diffusion coefficient (ADC) (water diffusivity) in peritoneal metastases. Patients with peritoneal dissemination detected on (18)F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) were prospectively recruited for MRI examinations with informed consent and the study was approved by the local Institutional Review Board. FDG-PET/CT, diffusion-weighted imaging (DWI), MRI, and DWI/MRI images were independently reviewed by two radiologists based on visual analysis. SUVmax/SUVmean and ADCmin/ADCmean were obtained manually by drawing ROIs over the peritoneal metastases on FDG-PET/CT and DWI, respectively. Diagnostic characteristics of each technique were evaluated. Pearson's coefficient and McNemar and Kappa tests were used for statistical analysis. Eight patients were recruited for this prospective study and 34 peritoneal metastases were evaluated. ADCmean was significantly and negatively correlated with SUVmax (r = -0.528, P = 0.001) and SUVmean (r = -0.548, P = 0.001). ADCmin had similar correlation with SUVmax (r = -0.508, P = 0.002) and SUVmean (r = -0.513, P = 0.002). DWI/MRI had high diagnostic performance (accuracy = 98%) comparable to FDG-PET/CT, in peritoneal metastasis detection. Kappa values were excellent for all techniques. There was a significant inverse correlation between SUV and ADC. © 2013 Wiley Periodicals, Inc.
The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

Science.gov (United States)

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).
Decoherence of coupled Josephson charge qubits due to partially correlated low-frequency noise

International Nuclear Information System (INIS)

Hu, Yong; Zhou, Zheng-Wei; Cai, Jian-Ming; Guo, Guang-Can

2007-01-01

Josephson charge qubits are promising candidates for scalable quantum computing. However, their performances are strongly degraded by decoherence due to low-frequency background noise, typically with a 1/f spectrum. In this paper, we investigate the decoherence process of two Cooper pair boxes (CPBs) coupled via a capacitor. Going beyond the common and uncorrelated noise models and the Bloch-Redfield formalism of previous works, we study the coupled system's quadratic dephasing under the condition of partially correlated noise sources. Based on reported experiments and generally accepted noise mechanisms, we introduce a reasonable assumption for the noise correlation, with which the calculation of multiqubit decoherence can be simplified to a problem on the single-qubit level. For the conventional Gaussian 1/f noise case, our results demonstrate that the quadratic dephasing rates are not very sensitive to the spatial correlation of the noises. Furthermore, we discuss the feasibility and efficiency of dynamical decoupling in the coupled CPBs
Study on GPS Common-view Observation Data with Multiscale Kalman Filter Based on Correlation Structure of the Discrete Wavelet Coefficients

National Research Council Canada - National Science Library

Xiaojuan, Ou; Wei, Zhou; Jianguo, Yu

2005-01-01

In this paper, we pay our attention to the multiscale kalman algorithm based on correlation structure of the discrete wavelet coefficients for the restoration of the GPS common-view observation data...
A new methodology for determining dispersion coefficient using ordinary and partial differential transport equations.

Science.gov (United States)

Cho, Kyung Hwa; Lee, Seungwon; Ham, Young Sik; Hwang, Jin Hwan; Cha, Sung Min; Park, Yongeun; Kim, Joon Ha

2009-01-01

The present study proposes a methodology for determining the effective dispersion coefficient based on the field measurements performed in Gwangju (GJ) Creek in South Korea which is environmentally degraded by the artificial interferences such as weirs and culverts. Many previous works determining the dispersion coefficient were limited in application due to the complexity and artificial interferences in natural stream. Therefore, the sequential combination of N-Tank-In-Series (NTIS) model and Advection-Dispersion-Reaction (ADR) model was proposed for evaluating dispersion process in complex stream channel in this study. The series of water quality data were intensively monitored in the field to determine the effective dispersion coefficient of E. coli in rainy day. As a result, the suggested methodology reasonably estimates the dispersion coefficient for GJ Creek with 1.25 m(2)/s. Also, the sequential combined method provided Number of tank-Velocity-Dispersion coefficient (NVD) curves for convenient evaluation of dispersion coefficient of other rivers or streams. Comparing the previous studies, the present methodology is quite general and simple for determining the effective dispersion coefficients which are applicable for other rivers and streams.

Theoretical study to determine the heat transfer by forced convection coefficient in an empirical correlation in single phase, for annular channels

International Nuclear Information System (INIS)

Herrera A, E.

1994-01-01

In the heat transfer studies by forced convection, we have few data about behavior of the fluids in an annular channel heated by a concentric pipe, such date is necessary to know the heat transfer coefficient that establish the interchange of energy and the thermic properties of the fluid with the geometry of the flow. In this work the objective, was to compare some empirical correlations that we needed for determinate the heat transfer coefficient for annular channels, where we obtained similar at the theoretical results of an experiment made by Miller and Benforado. It is important to know such coefficients because we can determinate the heat quantity transmitted to a probe zone, in which we simulate a nuclear fuel element that developed huge heat quantity that must be dispersed in short time. We give theoretical data of the heat forced transfer convection and we analyzed the phenomena in annular channels given some empirical correlations employed by some investigators and we analyzed each one. (Author)
Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells

International Nuclear Information System (INIS)

Artursson, P.; Karlsson, J.

1991-01-01

Monolayers of a well differentiated human intestinal epithelial cell line, Caco-2, were used as a model to study passive drug absorption across the intestinal epithelium. Absorption rate constants (expressed as apparent permeability coefficients) were determined for 20 drugs and peptides with different structural properties. The permeability coefficients ranged from approximately 5 x 10 - 8 to 5 x 10 - 5 cm/s. A good correlation was obtained between data on oral absorption in humans and the results in the Caco-2 model. Drugs that are completely absorbed in humans had permeability coefficients greater than 1 x 10 - 6 cm/s. Drugs that are absorbed to greater than 1% but less than 100% had permeability coefficients of 0.1-1.0 x 10 - 6 cm/s while drugs and peptides that are absorbed to less than 1% had permeability coefficients of less than or equal to 1 x 10 - 7 cm/s. The results indicate that Caco-2 monolayers can be used as a model for studies on intestinal drug absorption
Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

Science.gov (United States)

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard

2017-11-01

Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.
Consistent Partial Least Squares Path Modeling via Regularization.

Science.gov (United States)

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.
Consistent Partial Least Squares Path Modeling via Regularization

Directory of Open Access Journals (Sweden)

Sunho Jung

2018-02-01

Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.
Texture profile analysis of yogurt as influenced by partially hydrolyzed guar gum and process variables.

Science.gov (United States)

Mudgil, Deepak; Barak, Sheweta; Khatkar, B S

2017-11-01

Effect of partially hydrolyzed guar gum (PHGG) level (1-5%), culture level (1.5-3.5%) and incubation time (4-8 h) on texture profile of yogurt was studied using response surface methodology. The fortification of partially hydrolyzed guar gum in yogurt decreased the firmness and gumminess while it increased the adhesiveness, cohesiveness and springiness of yogurt significantly at p < 0.01. The culture level did not affect the textural properties of yogurt significantly except gumminess whereas textural properties of yogurt were negatively correlated with incubation time. The coefficient of determination for hardness/hardness, adhesiveness, cohesiveness, springiness and gumminess were 0.9216, 0.9397, 0.8914, 0.8971 and 0.9156, respectively, which revealed that the models obtained were significant as coefficient of determination value was close to one. The optimum conditions obtained were PHGG level 3.37%, culture level 1.96% and incubation time 5.96 h which leads to preparation of yogurt with desired textural characteristics.
Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

Science.gov (United States)

Li, Yuxing; Li, Yaan; Chen, Xiao; Yu, Jing

2017-12-26

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.
Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient

Directory of Open Access Journals (Sweden)

Yuxing Li

2017-12-01

Full Text Available As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN, research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC. First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD; then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD combined with CC compared to EMD denoising, ensemble EMD (EEMD denoising, VMD denoising and cubic VMD (3VMD denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.
Plateau Waves of Intracranial Pressure and Partial Pressure of Cerebral Oxygen.

Science.gov (United States)

Lang, Erhard W; Kasprowicz, Magdalena; Smielewski, Peter; Pickard, John; Czosnyka, Marek

2016-01-01

This study investigates 55 intracranial pressure (ICP) plateau waves recorded in 20 patients after severe traumatic brain injury (TBI) with a focus on a moving correlation coefficient between mean arterial pressure (ABP) and ICP, called PRx, which serves as a marker of cerebrovascular reactivity, and a moving correlation coefficient between ABP and cerebral partial pressure of oxygen (pbtO2), called ORx, which serves as a marker for cerebral oxygen reactivity. ICP and ICPamplitude increased significantly during the plateau waves, whereas CPP and pbtO2 decreased significantly. ABP, ABP amplitude, and heart rate remained unchanged. In 73 % of plateau waves PRx increased during the wave. ORx showed an increase during and a decrease after the plateau waves, which was not statistically significant. Our data show profound cerebral vasoparalysis on top of the wave and, to a lesser extent, impairment of cerebral oxygen reactivity. The different behavior of the indices may be due to the different latencies of the cerebral blood flow and oxygen level control mechanisms. While cerebrovascular reactivity is a rapidly reacting mechanism, cerebral oxygen reactivity is slower.
Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

Science.gov (United States)

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.
RMT Assessments of the Market Latent Information Embedded in the Stocks' Raw, Normalized, and Partial Correlations

OpenAIRE

Kenett, Dror Y.; Shapira, Yoash; Ben-Jacob, Eshel

2009-01-01

We present here assessment of the latent market information embedded in the raw, affinity (normalized), and partial correlations. We compared the Zipf plot, spectrum, and distribution of the eigenvalues for each matrix with the results of the corresponding random matrix. The analysis was performed on stocks belonging to the New York ...
Dynamics with infinitely many derivatives: variable coefficient equations

International Nuclear Information System (INIS)

Barnaby, Neil; Kamran, Niky

2008-01-01

Infinite order differential equations have come to play an increasingly significant role in theoretical physics. Field theories with infinitely many derivatives are ubiquitous in string field theory and have attracted interest recently also from cosmologists. Crucial to any application is a firm understanding of the mathematical structure of infinite order partial differential equations. In our previous work we developed a formalism to study the initial value problem for linear infinite order equations with constant coefficients. Our approach relied on the use of a contour integral representation for the functions under consideration. In many applications, including the study of cosmological perturbations in nonlocal inflation, one must solve linearized partial differential equations about some time-dependent background. This typically leads to variable coefficient equations, in which case the contour integral methods employed previously become inappropriate. In this paper we develop the theory of a particular class of linear infinite order partial differential equations with variable coefficients. Our formalism is particularly well suited to the types of equations that arise in nonlocal cosmological perturbation theory. As an example to illustrate our formalism we compute the leading corrections to the scalar field perturbations in p-adic inflation and show explicitly that these are small on large scales.
Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China.

Science.gov (United States)

Cui, Yang; Wang, Silong; Yan, Shaokui

2016-01-01

Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai's trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution
Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

Science.gov (United States)

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Correlation of the apparent diffusion coefficient and the standardized uptake value in neoplastic lesions: a meta-analysis.

Science.gov (United States)

Shen, Guohua; Ma, Huan; Liu, Bin; Ren, Pengwei; Kuang, Anren

2017-12-01

Diffusion-weighted imaging and fluorine-18-fluorodeoxyglucose PET are increasingly being recognized as feasible oncological techniques. The apparent diffusion coefficient (ADC) measured by diffusion-weighted imaging and the standardized uptake value (SUV) from fluorine-18-fluorodeoxyglucose PET have similar clinical applications. The aim of this study was to assess the correlation between these two parameters in various cancers. Several major databases were searched for eligible studies. The correlation coefficient (ρ) values were pooled in a random-effects model. Begg's test was used to analyze the existence of publication bias and the sources of heterogeneity were explored in subgroup analyses on the basis of study design, diagnostic method, scanning modality, and tumor type. Thirty-five articles were accepted. The pooled ρ value of all of the accepted studies was -0.30 (95% confidence interval: -0.33 to -0.27), and notable heterogeneity was present (I=69.4%, Pcorrelation. The pooled ρ values were -0.26, -0.33, -0.32, and -0.33 for the SUVmax/ADCmean, SUVmax/ADCmin, SUVmean/ADCmean, and SUVmean/ADCmin relationships, respectively. The study design and diagnostic method were potential sources of heterogeneity. Lung cancer showed a stronger correlation (ρ=-0.42) than head and neck cancer (ρ=-0.27), cervical cancer (ρ=-0.21), and breast cancer (ρ=-0.23). A Begg's test indicated no significant publication bias among the accepted studies (P>0.05). The two functional parameters of ADC and SUV showed a very weak inverse correlation, which may contribute toward a sophisticated characterization of tumor biology. However, the findings require further validation with trials with large samples and different tumor types.
A partitioned correlation function interaction approach for describing electron correlation in atoms

International Nuclear Information System (INIS)

Verdebout, S; Godefroid, M; Rynkun, P; Jönsson, P; Gaigalas, G; Fischer, C Froese

2013-01-01

The traditional multiconfiguration Hartree–Fock (MCHF) and configuration interaction (CI) methods are based on a single orthonormal orbital basis. For atoms with many closed core shells, or complicated shell structures, a large orbital basis is needed to saturate the different electron correlation effects such as valence, core–valence and correlation within the core shells. The large orbital basis leads to massive configuration state function (CSF) expansions that are difficult to handle, even on large computer systems. We show that it is possible to relax the orthonormality restriction on the orbital basis and break down the originally very large calculations into a series of smaller calculations that can be run in parallel. Each calculation determines a partitioned correlation function (PCF) that accounts for a specific correlation effect. The PCFs are built on optimally localized orbital sets and are added to a zero-order multireference (MR) function to form a total wave function. The expansion coefficients of the PCFs are determined from a low dimensional generalized eigenvalue problem. The interaction and overlap matrices are computed using a biorthonormal transformation technique (Verdebout et al 2010 J. Phys. B: At. Mol. Phys. 43 074017). The new method, called partitioned correlation function interaction (PCFI), converges rapidly with respect to the orbital basis and gives total energies that are lower than the ones from ordinary MCHF and CI calculations. The PCFI method is also very flexible when it comes to targeting different electron correlation effects. Focusing our attention on neutral lithium, we show that by dedicating a PCF to the single excitations from the core, spin- and orbital-polarization effects can be captured very efficiently, leading to highly improved convergence patterns for hyperfine parameters compared with MCHF calculations based on a single orthogonal radial orbital basis. By collecting separately optimized PCFs to correct the
A partitioned correlation function interaction approach for describing electron correlation in atoms

Science.gov (United States)

Verdebout, S.; Rynkun, P.; Jönsson, P.; Gaigalas, G.; Froese Fischer, C.; Godefroid, M.

2013-04-01

The traditional multiconfiguration Hartree-Fock (MCHF) and configuration interaction (CI) methods are based on a single orthonormal orbital basis. For atoms with many closed core shells, or complicated shell structures, a large orbital basis is needed to saturate the different electron correlation effects such as valence, core-valence and correlation within the core shells. The large orbital basis leads to massive configuration state function (CSF) expansions that are difficult to handle, even on large computer systems. We show that it is possible to relax the orthonormality restriction on the orbital basis and break down the originally very large calculations into a series of smaller calculations that can be run in parallel. Each calculation determines a partitioned correlation function (PCF) that accounts for a specific correlation effect. The PCFs are built on optimally localized orbital sets and are added to a zero-order multireference (MR) function to form a total wave function. The expansion coefficients of the PCFs are determined from a low dimensional generalized eigenvalue problem. The interaction and overlap matrices are computed using a biorthonormal transformation technique (Verdebout et al 2010 J. Phys. B: At. Mol. Phys. 43 074017). The new method, called partitioned correlation function interaction (PCFI), converges rapidly with respect to the orbital basis and gives total energies that are lower than the ones from ordinary MCHF and CI calculations. The PCFI method is also very flexible when it comes to targeting different electron correlation effects. Focusing our attention on neutral lithium, we show that by dedicating a PCF to the single excitations from the core, spin- and orbital-polarization effects can be captured very efficiently, leading to highly improved convergence patterns for hyperfine parameters compared with MCHF calculations based on a single orthogonal radial orbital basis. By collecting separately optimized PCFs to correct the MR
Gene interference regulates aquaporin-4 expression in swollen tissue of rats with cerebral ischemic edema: Correlation with variation in apparent diffusion coefficient.

Science.gov (United States)

Hu, Hui; Lu, Hong; He, Zhanping; Han, Xiangjun; Chen, Jing; Tu, Rong

2012-07-25

To investigate the effects of mRNA interference on aquaporin-4 expression in swollen tissue of rats with ischemic cerebral edema, and diagnose the significance of diffusion-weighted MRI, we injected 5 μL shRNA- aquaporin-4 (control group) or siRNA- aquaporin-4 solution (1:800) (RNA interference group) into the rat right basal ganglia immediately before occlusion of the middle cerebral artery. At 0.25 hours after occlusion of the middle cerebral artery, diffusion-weighted MRI displayed a high signal; within 2 hours, the relative apparent diffusion coefficient decreased markedly, aquaporin-4 expression increased rapidly, and intracellular edema was obviously aggravated; at 4 and 6 hours, the relative apparent diffusion coefficient slowly returned to control levels, aquaporin-4 expression slightly increased, and angioedema was observed. In the RNA interference group, during 0.25-6 hours after injection of siRNA- aquaporin-4 solution, the relative apparent diffusion coefficient slightly fluctuated and aquaporin-4 expression was upregulated; during 0.5-4 hours, the relative apparent diffusion coefficient was significantly higher, while aquaporin-4 expression was significantly lower when compared with the control group, and intracellular edema was markedly reduced; at 0.25 and 6 hours, the relative apparent diffusion coefficient and aquaporin-4 expression were similar when compared with the control group; obvious angioedema remained at 6 hours. Pearson's correlation test results showed that aquaporin-4 expression was negatively correlated with the apparent diffusion coefficient (r = -0.806, P coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time-effectiveness. Moreover, diffusion-weighted MRI can accurately detect intracellular edema.
Quantum Non-Markovian Langevin Equations and Transport Coefficients

International Nuclear Information System (INIS)

Sargsyan, V.V.; Antonenko, N.V.; Kanokov, Z.; Adamian, G.G.

2005-01-01

Quantum diffusion equations featuring explicitly time-dependent transport coefficients are derived from generalized non-Markovian Langevin equations. Generalized fluctuation-dissipation relations and analytic expressions for calculating the friction and diffusion coefficients in nuclear processes are obtained. The asymptotic behavior of the transport coefficients and correlation functions for a damped harmonic oscillator that is linearly coupled in momentum to a heat bath is studied. The coupling to a heat bath in momentum is responsible for the appearance of the diffusion coefficient in coordinate. The problem of regression of correlations in quantum dissipative systems is analyzed
Virial Coefficients for the Liquid Argon

Science.gov (United States)

Korth, Micheal; Kim, Saesun

2014-03-01

We begin with a geometric model of hard colliding spheres and calculate probability densities in an iterative sequence of calculations that lead to the pair correlation function. The model is based on a kinetic theory approach developed by Shinomoto, to which we added an interatomic potential for argon based on the model from Aziz. From values of the pair correlation function at various values of density, we were able to find viral coefficients of liquid argon. The low order coefficients are in good agreement with theoretical hard sphere coefficients, but appropriate data for argon to which these results might be compared is difficult to find.

Path coefficient and correlation of yield and yield associated traits in candidate bread wheat (triticum aestivum l)lines

International Nuclear Information System (INIS)

Muhammad, T.; Haider, S.; Qureshi, M. J.; Shah, G. S.; Zamir, R.

2005-01-01

Yield and yield contributing traits were studied in candidate bread wheat lines to find out the genetic contribution of the different characters towards grain yield at NIFA, Peshawar during 2001-02. All the characteristics studied differed significantly from each other. Days to heading showed negative and significant correlation with harvest index and grain yield but was negative and non-significant with the biological yield. Days to maturity were negatively correlated at both genotypic and phenotypic levels with biological yield; harvest index and grain yield and level of correlations were significant with harvest index and grain yield. Plant height showed negative genotypic and phenotypic correlation with harvest index and grain yield. Biological yield had positive and significant genotypic and phenotypic correlations with harvest index and grain yield. Harvest index had positive and highly significant genotypic and phenotypic correlation with grain yield. Genotypic and phenotypic correlation coefficients revealed that important characters influencing grain yield are harvest index and biological yield. Path analysis showed the importance in order of harvest index, biological yield, plant height, days to maturity and days to heading with grain yield. (author)
Correlation of standardized uptake value and apparent diffusion coefficient in integrated whole-body PET/MRI of primary and recurrent cervical cancer.

Science.gov (United States)

Grueneisen, Johannes; Beiderwellen, Karsten; Heusch, Philipp; Buderath, Paul; Aktas, Bahriye; Gratz, Marcel; Forsting, Michael; Lauenstein, Thomas; Ruhlmann, Verena; Umutlu, Lale

2014-01-01

To evaluate a potential correlation of the maximum standard uptake value (SUVmax) and the minimum apparent diffusion coefficient (ADCmin) in primary and recurrent cervical cancer based on integrated PET/MRI examinations. 19 consecutive patients (mean age 51.6 years; range 30-72 years) with histopathologically confirmed primary cervical cancer (n = 9) or suspected tumor recurrence (n = 10) were prospectively enrolled for an integrated PET/MRI examination. Two radiologists performed a consensus reading in random order, using a dedicated post-processing software. Polygonal regions of interest (ROI) covering the entire tumor lesions were drawn into PET/MR images to assess SUVmax and into ADC parameter maps to determine ADCmin values. Pearson's correlation coefficients were calculated to assess a potential correlation between the mean values of ADCmin and SUVmax. In 15 out of 19 patients cervical cancer lesions (n = 12) or lymph node metastases (n = 42) were detected. Mean SUVmax (12.5 ± 6.5) and ADCmin (644.5 ± 179.7 × 10(-5) mm2/s) values for all assessed tumor lesions showed a significant but weak inverse correlation (R = -0.342, p correlation between SUVmax and ADCmin (R = -0.692, p correlation. These initial results of this emerging hybrid imaging technique demonstrate the high diagnostic potential of simultaneous PET/MR imaging for the assessment of functional biomarkers, revealing a significant and strong correlation of tumor metabolism and higher cellularity in cervical cancer lesions.
Standardized uptake value and apparent diffusion coefficient of endometrial cancer evaluated with integrated whole-body PET/MR: Correlation with pathological prognostic factors.

Science.gov (United States)

Shih, I-Lun; Yen, Ruoh-Fang; Chen, Chi-An; Chen, Bang-Bin; Wei, Shwu-Yuan; Chang, Wen-Chun; Sheu, Bor-Ching; Cheng, Wen-Fang; Tseng, Yao-Hui; Chen, Xin-Jia; Chen, Chi-Hau; Wei, Lin-Hung; Chiang, Ying-Cheng; Torng, Pao-Ling; Yen, Men-Luh; Shih, Tiffany Ting-Fang

2015-12-01

To evaluate the correlation between maximum standardized uptake value (SUVmax ) and minimum apparent diffusion coefficient (ADCmin ) of endometrial cancer derived from an integrated positron emission tomography / magnetic resonance (PET/MR) system and to determine their correlation with pathological prognostic factors. This prospective study was approved by the Institutional Review Board of the hospital, and informed consent was obtained. Between April and December 2014, 47 consecutive patients with endometrial cancer were enrolled and underwent simultaneous PET/MR examinations before surgery. Thirty-six patients with measurable tumors on PET/MR were included for image analysis. Pearson's correlation coefficient was used to evaluate the correlation between SUVmax and ADCmin of the tumors. The Mann-Whitney U-test was utilized to evaluate relationships between these two imaging biomarkers and pathological prognostic factors. The mean SUVmax and ADCmin were 14.7 ± 7.1 and 0.48 ± 0.13 × 10(-3) mm(2) /s, respectively. A significant inverse correlation was found between SUVmax and ADCmin (r = -0.53; P = 0.001). SUVmax was significantly higher in tumors with advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P correlated and are associated with pathological prognostic factors. © 2015 Wiley Periodicals, Inc.
A comparison of roughness parameters and friction coefficients of aesthetic archwires.

Science.gov (United States)

Rudge, Philippa; Sherriff, Martyn; Bister, Dirk

2015-02-01

Compare surface roughness of 'aesthetic' nickel-titanium (NiTi) archwires with their dynamic frictional properties. Archwires investigated were: four fully coated tooth coloured [Forestadent: Biocosmetic (FB) and Titanol Cosmetic (FT); TOC Tooth Tone (TT); and Hawley Russell Coated Superelastic NiTi (HRC)]; two partially coated tooth coloured [DB Euroline Microcoated (DB) and TP Aesthetic NiTi (TP)]; two rhodium coated [TOC Sentalloy (TS) and Hawley Russell Rhodium Coated Superelastic NiTi (HRR)]; and two controls: stainless steel [Forestadent Steel (FS)] and NiTi archwire [Forestadent Titanol Superelastic (FN)]. Surface roughness [profilometry (Rugosurf)] was compared with frictional coefficients for archwire/bracket/ligature combinations (n = 10). Analysis of variance, Sidak's multiple comparison of means, and Spearman's correlation coefficient were used for analysis. Roughness coefficients were from low to high: FB; FN; TT; FS; TS; HRR; FT; DB; TP; HRC. Friction coefficients were from low to high: TP; FS; FN; HRR; FT; DB; FB; HRC; TS; TT. Coated archwires generally exhibited higher friction than uncoated controls. TP had the lowest friction but this was not statistically significant (P < 0.05). Friction of tooth coloured coated archwires were significantly different for some wires. Spearman's correlation did not demonstrate consistency between surface roughness (R a) and dynamic friction. Aesthetic archwires investigated had either low surface roughness or low frictional resistance but not both properties simultaneously. Causes for friction are likely to be multifactorial and do not appear to be solely determined by surface roughness (measured by profilometry). For selecting the most appropriate aligning archwire, both surface roughness and frictional resistance need to be considered. © The Author 2014. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.
MEASUREMENT AND CORRELATION OF THE MASS TRANSFER COEFFICIENT FOR A LIQUID-LIQUID SYSTEM WITH HIGH DENSITY DIFFERENCE

Directory of Open Access Journals (Sweden)

Zhixian Huang

Full Text Available Abstract To investigate the mass transfer behavior of a liquid-liquid system with high density difference (∆ρ≈500 kg/m3, single drop experiments were performed by using the ternary chloroform-ethanol-water system. The mass transfer direction was from the dispersed phase to the continuous phase, while the aqueous phase was dispersed in chloroform to generate drops. The influences of drop diameter, initial solute concentration and temperature on the mass transfer were investigated. The effects of the drop diameter and initial solute concentration on interfacial instability of droplets hanging in the continuous phase were also observed. For the purpose of correlation, a mass transfer enhancement factor F was introduced and then correlated as a function of dimensionless variables. The modified correlation from the mass transfer coefficient model was found to fit well with the experimental values.
Determination and importance of temperature dependence of retention coefficient (RPHPLC) in QSAR model of nitrazepams' partition coefficient in bile acid micelles.

Science.gov (United States)

Posa, Mihalj; Pilipović, Ana; Lalić, Mladena; Popović, Jovan

2011-02-15

Linear dependence between temperature (t) and retention coefficient (k, reversed phase HPLC) of bile acids is obtained. Parameters (a, intercept and b, slope) of the linear function k=f(t) highly correlate with bile acids' structures. Investigated bile acids form linear congeneric groups on a principal component (calculated from k=f(t)) score plot that are in accordance with conformations of the hydroxyl and oxo groups in a bile acid steroid skeleton. Partition coefficient (K(p)) of nitrazepam in bile acids' micelles is investigated. Nitrazepam molecules incorporated in micelles show modified bioavailability (depo effect, higher permeability, etc.). Using multiple linear regression method QSAR models of nitrazepams' partition coefficient, K(p) are derived on the temperatures of 25°C and 37°C. For deriving linear regression models on both temperatures experimentally obtained lipophilicity parameters are included (PC1 from data k=f(t)) and in silico descriptors of the shape of a molecule while on the higher temperature molecular polarisation is introduced. This indicates the fact that the incorporation mechanism of nitrazepam in BA micelles changes on the higher temperatures. QSAR models are derived using partial least squares method as well. Experimental parameters k=f(t) are shown to be significant predictive variables. Both QSAR models are validated using cross validation and internal validation method. PLS models have slightly higher predictive capability than MLR models. Copyright © 2010 Elsevier B.V. All rights reserved.
Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

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Yinyin Yuan

Full Text Available Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/.
Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

KAUST Repository

Nobile, Fabio; Tempone, Raul

2009-01-01

We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.
Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

KAUST Repository

Nobile, Fabio

2009-11-05

We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.
Validity of GNRB® arthrometer compared to Telos™ in the assessment of partial anterior cruciate ligament tears.

Science.gov (United States)

Lefevre, N; Bohu, Y; Naouri, J F; Klouche, S; Herman, S

2014-02-01

The main goal of this study was to compare the results of the GNRB(®) arthrometer to those of Telos™ in the diagnosis of partial thickness tears of the anterior cruciate ligament (ACL). A prospective study performed January-December 2011 included all patients presenting with a partial or full-thickness ACL tears without ACL reconstruction and with a healthy contralateral knee. Anterior laxity was measured in all patients by the Telos™ and GNRB(®) devices. This series included 139 patients, mean age 30.7 ± 9.3 years. Arthroscopic reconstruction was performed in 109 patients, 97 for complete tears and 12 single bundle reconstructions for partial thickness tears. Conservative treatment was proposed in 30 patients with a partial thickness tear. The correlation between the two devices was evaluated by the Spearman coefficient. The optimal laxity thresholds were determined with ROC curves, and the diagnostic value of the tests was assessed by the area under the curve (AUC). The differential laxities of full and partial thickness tears were significantly different with the two tests. The correlation between the results of laxity measurement with the two devices was fair, with the strongest correlation between Telos™ 250 N and GNRB(®) 250 N (r = 0.46, p = 0.00001). Evaluation of the AUC showed that the informative value of all tests was fair with the best results with the GNRB(®) 250 N: AUC = 0.89 [95 % CI 0.83-0.94]. The optimal differential laxity threshold with the GNRB(®) 250 N was 2.5 mm (Se = 84 %, Sp = 81 %). The diagnostic value of GNRB(®) was better than Telos™ for ACL partial thickness tears.
The intraclass correlation coefficient applied for evaluation of data correction, labeling methods and rectal biopsy sampling in DNA microarray experiments

NARCIS (Netherlands)

Pellis, E.P.M.; Franssen-Hal, van N.L.W.; Burema, J.; Keijer, J.

2003-01-01

We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from
Momentum, sensible heat and CO2 correlation coefficient variability: what can we learn from 20 years of continuous eddy covariance measurements?

Science.gov (United States)

Hurdebise, Quentin; Heinesch, Bernard; De Ligne, Anne; Vincke, Caroline; Aubinet, Marc

2017-04-01

Long-term data series of carbon dioxide and other gas exchanges between terrestrial ecosystems and atmosphere become more and more numerous. Long-term analyses of such exchanges require a good understanding of measurement conditions during the investigated period. Independently of climate drivers, measurements may indeed be influenced by measurement conditions themselves subjected to long-term variability due to vegetation growth or set-up changes. The present research refers to the Vielsalm Terrestrial Observatory (VTO) an ICOS candidate site located in a mixed forest (beech, silver fir, Douglas fir, Norway spruce) in the Belgian Ardenne. Fluxes of momentum, carbon dioxide and sensible heat have been continuously measured there by eddy covariance for more than 20 years. During this period, changes in canopy height and measurement height occurred. The correlation coefficients (for momemtum, sensible heat and CO2) and the normalized standard deviations measured for the past 20 years at the Vielsalm Terrestrial Observatory (VTO) were analysed in order to define how the fluxes, independently of climate conditions, were affected by the surrounding environment evolution, including tree growth, forest thinning and tower height change. A relationship between canopy aerodynamic distance and the momentum correlation coefficient was found which is characteristic of the roughness sublayer, and suggests that momentum transport processes were affected by z-d. In contrast, no relationship was found for sensible heat and CO2 correlation coefficients, suggesting that the z-d variability observed did not affect their turbulent transport. There were strong differences in these coefficients, however, between two wind sectors, characterized by contrasted stands (height differences, homogeneity) and different hypotheses were raised to explain it. This study highlighted the importance of taking the surrounding environment variability into account in order to ensure the spatio
Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

International Nuclear Information System (INIS)

Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L.

2017-01-01

The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)
Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L., E-mail: prii.ramos@gmail.com, E-mail: camunita@ipen.br, E-mail: alapolli@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

2017-07-01

The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)
Control in the coefficients with variational crimes

DEFF Research Database (Denmark)

Evgrafov, Anton; Marhadi, Kun Saptohartyadi

2012-01-01

We study convergence of discontinuous Galerkin-type discretizations of the problems of control in the coefficients of uniformly elliptic partial differential equations (PDEs). As a model problem we use that of the optimal design of thin (Kirchhoff) plates, where the governing equations...
Masseter muscle thickness in unilateral partial edentulism: An ultrasonographic study

Directory of Open Access Journals (Sweden)

S Sathasivasubramanian

2017-01-01

Full Text Available Introduction: Teeth and facial muscles play a very important role in occlusal equilibrium and function. Occlusal derangement, seen in unilateral partially edentulous individuals, has an effect on masseter muscle anatomy and function. The present study aims to evaluate masseter muscle thickness in unilateral partial edentulism. Patients and Methods: Institutional ethics committee approval was obtained before the commencement of the study. The study involved patients who routinely visited the Department of Oral Medicine and Radiology, Sri Ramachandra University. The study sample included 27 unilateral edentulous patients (Group E and 30 controls (Group C. The masseter muscle thickness was evaluated using high-resolution ultrasound real-time scanner (linear transducer − 7.5–10 MHz at both relaxed and contracted states. Statistical Analysis Used: The results were analyzed using paired t-test and independent t-test. Duration of edentulism and muscle thickness was assessed using Pearson's correlation coefficient. Results: The study patients' age ranged between 25 and 48 years (mean – 36 years. The comparative evaluation of masseter muscle thickness between the dentulous and edentulous sides of experimental group was statistically significant (P < 0.05. However, no statistically significant difference in masseter muscle thickness was found between the dentulous side of control and experimental groups. The correlation between the duration of partial edentulism and muscle thickness was statistically insignificant. Conclusion: The study proves masseter atrophy in the edentulous side. However, since the difference is found to be marginal with the present sample, a greater sample is necessary to establish and prove the present findings as well as to correlate with the duration of edentulism. Further studies are aimed to assess the muscle morphology after prosthetic rehabilitation.
The Effect of a Fluorophore Photo-Physics on the Lipid Vesicle Diffusion Coefficient Studied by Fluorescence Correlation Spectroscopy.

Science.gov (United States)

Drabik, Dominik; Przybyło, Magda; Sikorski, Aleksander; Langner, Marek

2016-03-01

Fluorescence Correlation Spectroscopy (FCS) is a technique, which allows determination of the diffusion coefficient and concentration of fluorescent objects suspended in the solution. The measured parameter is the fluctuation of the fluorescence signal emitted by diffusing molecules. When 100 nm DOPC vesicles labeled with various fluorescent dyes (Fluorescein-PE, NBD-PE, Atto488 DOPE or βBodipy FL) were measured, different values of diffusion coefficients have been obtained. These diffusion coefficients were different from the expected values measured using the dynamic light scattering method (DLS). The FCS was initially developed for solutions containing small fluorescent molecules therefore the observed inconsistency may result from the nature of vesicle suspension itself. The duration of the fluorescence signal may depend on the following factors: the exposure time of the labeled object to the excitation beam, the photo-physical properties (e.g., stability) of a fluorophore, the theoretical model used for the calculations of the diffusion coefficient and optical properties of the vesicle suspension. The diffusion coefficients determined for differently labeled liposomes show that its dependence on vesicle size and quantity of fluorescent probed used for labeling was significant demonstrating that the fluorescence properties of the fluorophore itself (bleaching and/or blinking) were critical factors for a correct outcome of FCS experiment. The new, based on combined FCS and DLS measurements, method for the determination of the focal volume prove itself to be useful for the evaluation of a fluorescence dye with respect to its applicability for FCS experiment.
Chemical analysis of industrial scale deposits by combined use of correlation coefficients with emission line detection of laser induced breakdown spectroscopy spectra

International Nuclear Information System (INIS)

Siozos, P.; Philippidis, A.; Hadjistefanou, M.; Gounarakis, C.; Anglos, D.

2013-01-01

Laser-induced breakdown spectroscopy (LIBS) was used to determine the mineral composition of various industrial scale samples. The aim of the study has been to investigate the capacity of LIBS to provide a fast, reliable analytical tool for carrying out routine analysis of inorganic scales, potentially on site, as a means to facilitate decision making concerning scale removal procedures. LIBS spectra collected in the range of 200–660 nm conveyed information about the metal content of the minerals. Via a straightforward analysis based on linear correlation of LIBS spectra it was possible to successfully discriminate scale samples into three main groups, Fe-rich, Ca-rich and Ba-rich, on the basis of correlation coefficients. By combining correlation coefficients with spectral data collected in the NIR, 860–960 nm, where sulfur emissions are detected, it became further possible to discriminate sulfates from carbonates as confirmed by independent analysis based on Raman spectroscopy. It is emphasized that the proposed LIBS-based method successfully identifies the major mineral or minerals present in the samples classifying the scales into relevant groups hence enabling process engineers to select appropriate scale dissolution strategies. - Highlights: • LIBS was used to determine the mineral composition of industrial scale samples. • Three groups of inorganic scales were identified: Ca rich, Ba rich and Fe rich. • A method that combines correlation coefficients and line detection is proposed. • The method successfully identifies the main mineral, or minerals, in the samples. • The results were compared with results obtained by use of Raman analysis
Genetic variability, correlation and path coefficients of yield and its components analysis in pumpkin (Cucurbita moschata Duch Ex Poir

Directory of Open Access Journals (Sweden)

GM Mohsin

2017-06-01

Full Text Available Genetic variability, correlation and path coefficient were studied for yield and yield component traits in twenty one diverse genotypes of pumpkin. Highest genotypic coefficient of variation was recorded for fruit length (cm, single fruit weight (kg, Brix (% and yield per plant (kg. Heritability estimates in broad sense were higher for almost all the characters. The characters namely, fruit length, single fruit weight, yield per plant and brix% had high genotypic coefficient of variation coupled with heritability gave high genetic advance expressed as percentage of mean ranged from 76.84 to 96.06 which indicated that these characters were less influenced by environment confirming additive gene action, and therefore, selection of these characters would be more effective for yield improvement of pumpkins. Total six traits likely fruit length, fruit diameter, flesh thickness, single fruit weight and number of fruits per plant were positively and significantly associated with yield per plant. Path coefficient analysis also revealed maximum contribution of single fruit weight (0.869 to yield and this was followed by the contribution of number of fruit per plant (0.527 at genotypic level.
Classification of criticality calculations with correlation coefficient method and its application to OECD/NEA burnup credit benchmarks phase III-A and II-A

International Nuclear Information System (INIS)

Okuno, Hiroshi

2003-01-01

A method for classifying benchmark results of criticality calculations according to similarity was proposed in this paper. After formulation of the method utilizing correlation coefficients, it was applied to burnup credit criticality benchmarks Phase III-A and II-A, which were conducted by the Expert Group on Burnup Credit Criticality Safety under auspices of the Nuclear Energy Agency of the Organisation for Economic Cooperation and Development (OECD/NEA). Phase III-A benchmark was a series of criticality calculations for irradiated Boiling Water Reactor (BWR) fuel assemblies, whereas Phase II-A benchmark was a suite of criticality calculations for irradiated Pressurized Water Reactor (PWR) fuel pins. These benchmark problems and their results were summarized. The correlation coefficients were calculated and sets of benchmark calculation results were classified according to the criterion that the values of the correlation coefficients were no less than 0.15 for Phase III-A and 0.10 for Phase II-A benchmarks. When a couple of benchmark calculation results belonged to the same group, one calculation result was found predictable from the other. An example was shown for each of the Benchmarks. While the evaluated nuclear data seemed the main factor for the classification, further investigations were required for finding other factors. (author)

Correlation between metal-ceramic bond strength and coefficient of linear thermal expansion difference

Directory of Open Access Journals (Sweden)

Stella Crosara Lopes

2009-04-01

Full Text Available The purpose of this study was to evaluate the metal-ceramic bond strength (MCBS of 6 metal-ceramic pairs (2 Ni-Cr alloys and 1 Pd-Ag alloy with 2 dental ceramics and correlate the MCBS values with the differences between the coefficients of linear thermal expansion (CTEs of the metals and ceramics. Verabond (VB Ni-Cr-Be alloy, Verabond II (VB2, Ni-Cr alloy, Pors-on 4 (P, Pd-Ag alloy, and IPS (I and Duceram (D ceramics were used for the MCBS test and dilatometric test. Forty-eight ceramic rings were built around metallic rods (3.0 mm in diameter and 70.0 mm in length made from the evaluated alloys. The rods were subsequently embedded in gypsum cast in order to perform a tensile load test, which enabled calculating the CMBS. Five specimens (2.0 mm in diameter and 12.0 mm in length of each material were made for the dilatometric test. The chromel-alumel thermocouple required for the test was welded into the metal test specimens and inserted into the ceramics. ANOVA and Tukey's test revealed significant differences (p=0.01 for the MCBS test results (MPa, with PI showing higher MCBS (67.72 than the other pairs, which did not present any significant differences. The CTE (10-6 oC-1 differences were: VBI (0.54, VBD (1.33, VB2I (-0.14, VB2D (0.63, PI (1.84 and PD (2.62. Pearson's correlation test (r=0.17 was performed to evaluate of correlation between MCBS and CTE differences. Within the limitations of this study and based on the obtained results, there was no correlation between MCBS and CTE differences for the evaluated metal-ceramic pairs.
Correlation between metal-ceramic bond strength and coefficient of linear thermal expansion difference.

Science.gov (United States)

Lopes, Stella Crosara; Pagnano, Valéria Oliveira; Rollo, João Manuel Domingos de Almeida; Leal, Mônica Barbosa; Bezzon, Osvaldo Luiz

2009-01-01

The purpose of this study was to evaluate the metal-ceramic bond strength (MCBS) of 6 metal-ceramic pairs (2 Ni-Cr alloys and 1 Pd-Ag alloy with 2 dental ceramics) and correlate the MCBS values with the differences between the coefficients of linear thermal expansion (CTEs) of the metals and ceramics. Verabond (VB) Ni-Cr-Be alloy, Verabond II (VB2), Ni-Cr alloy, Pors-on 4 (P), Pd-Ag alloy, and IPS (I) and Duceram (D) ceramics were used for the MCBS test and dilatometric test. Forty-eight ceramic rings were built around metallic rods (3.0 mm in diameter and 70.0 mm in length) made from the evaluated alloys. The rods were subsequently embedded in gypsum cast in order to perform a tensile load test, which enabled calculating the CMBS. Five specimens (2.0 mm in diameter and 12.0 mm in length) of each material were made for the dilatometric test. The chromel-alumel thermocouple required for the test was welded into the metal test specimens and inserted into the ceramics. ANOVA and Tukey's test revealed significant differences (p=0.01) for the MCBS test results (MPa), with PI showing higher MCBS (67.72) than the other pairs, which did not present any significant differences. The CTE (10(-6) oC(-1)) differences were: VBI (0.54), VBD (1.33), VB2I (-0.14), VB2D (0.63), PI (1.84) and PD (2.62). Pearson's correlation test (r=0.17) was performed to evaluate of correlation between MCBS and CTE differences. Within the limitations of this study and based on the obtained results, there was no correlation between MCBS and CTE differences for the evaluated metal-ceramic pairs.
R package to estimate intracluster correlation coefficient with confidence interval for binary data.

Science.gov (United States)

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.
The electron antineutrino angular correlation coefficient a in free neutron decay. Testing the standard model with the aSPECT-spectrometer

International Nuclear Information System (INIS)

Borg, Michael

2011-01-01

The β-decay of free neutrons is a strongly over-determined process in the Standard Model (SM) of Particle Physics and is described by a multitude of observables. Some of those observables are sensitive to physics beyond the SM. For example, the correlation coefficients of the involved particles belong to them. The spectrometer aSPECT was designed to measure precisely the shape of the proton energy spectrum and to extract from it the electron anti-neutrino angular correlation coefficient a. A first test period (2005/2006) showed the ''proof-of-principles''. The limiting influence of uncontrollable background conditions in the spectrometer made it impossible to extract a reliable value for the coefficient a (published in 2008). A second measurement cycle (2007/2008) aimed to under-run the relative accuracy of previous experiments (δa)/(a)=5%. I performed the analysis of the data taken there which is the emphasis of this doctoral thesis. A central point are background studies. The systematic impact of background on a was reduced to (δa (syst.) )/(a)=0.61 %. The statistical accuracy of the analyzed measurements is (δa (stat.) )/(a)∼1.4 %. Besides, saturation effects of the detector electronics were investigated which were initially observed. These turned out not to be correctable on a sufficient level. An applicable idea how to avoid the saturation effects is discussed in the last chapter. (orig.)
Measurement of the angular correlation coefficient a between electron and antineutrino in neutron β-decay with the spectrometer aSPECT

International Nuclear Information System (INIS)

Maisonobe, Romain

2014-01-01

Neutron β-decay is parametrized by several measurable correlation coefficients which are used to determine parameters of the Standard Model and to search for new physics. The aim of the retardation spectrometer aSPECT is to measure the electron-antineutrino angular correlation coefficient a with an unprecedented accuracy of well below 1%. The coefficient is extracted from a high precision measurement of the proton energy spectrum. A central point of this PhD thesis is the analysis of the background, motivated by the observations of discharges during the beam time of 2011, and an earlier indication for a dependence on the retardation potential. During this thesis, several measurements were conducted off-line, without ionizing particles from neutron decay. An 'internal' background (X-rays and ions) was identified. It has an influence of 10 -5 to 10 -4 on Δa/a depending on the vacuum level (∼10 -9 mbar) and the spectrometer settings. Within the analysis of the data from the beam time in 2013, a model was built to correct for backgrounds present in neutron decay experiment, taking into account its time dependence. The correction is about 3% on the coefficient for standard settings and vacuum but it can reach 7% for unfavorable settings. To reduce the background, a drift electric field was applied close to the maximum of the retardation potential. Additional measurements performed during this beam time included tests of systematics, in particular the edge effect (beam profile) and different electrode settings. In order to obtain the final result, the analysis has to be extended by including the different corrections and by comparing with simulations of the systematic effects. (author)
A Bayesian estimate of the concordance correlation coefficient with skewed data.

Science.gov (United States)

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2015-01-01

Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real-life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network. Copyright © 2015 John Wiley & Sons, Ltd.
Gaussian graphical modeling reveals specific lipid correlations in glioblastoma cells

Science.gov (United States)

Mueller, Nikola S.; Krumsiek, Jan; Theis, Fabian J.; Böhm, Christian; Meyer-Bäse, Anke

2011-06-01

Advances in high-throughput measurements of biological specimens necessitate the development of biologically driven computational techniques. To understand the molecular level of many human diseases, such as cancer, lipid quantifications have been shown to offer an excellent opportunity to reveal disease-specific regulations. The data analysis of the cell lipidome, however, remains a challenging task and cannot be accomplished solely based on intuitive reasoning. We have developed a method to identify a lipid correlation network which is entirely disease-specific. A powerful method to correlate experimentally measured lipid levels across the various samples is a Gaussian Graphical Model (GGM), which is based on partial correlation coefficients. In contrast to regular Pearson correlations, partial correlations aim to identify only direct correlations while eliminating indirect associations. Conventional GGM calculations on the entire dataset can, however, not provide information on whether a correlation is truly disease-specific with respect to the disease samples and not a correlation of control samples. Thus, we implemented a novel differential GGM approach unraveling only the disease-specific correlations, and applied it to the lipidome of immortal Glioblastoma tumor cells. A large set of lipid species were measured by mass spectrometry in order to evaluate lipid remodeling as a result to a combination of perturbation of cells inducing programmed cell death, while the other perturbations served solely as biological controls. With the differential GGM, we were able to reveal Glioblastoma-specific lipid correlations to advance biomedical research on novel gene therapies.
Nuclear Overhauser Enhancement imaging of glioblastoma at 7 Tesla: region specific correlation with apparent diffusion coefficient and histology.

Science.gov (United States)

Paech, Daniel; Burth, Sina; Windschuh, Johannes; Meissner, Jan-Eric; Zaiss, Moritz; Eidel, Oliver; Kickingereder, Philipp; Nowosielski, Martha; Wiestler, Benedikt; Sahm, Felix; Floca, Ralf Omar; Neumann, Jan-Oliver; Wick, Wolfgang; Heiland, Sabine; Bendszus, Martin; Schlemmer, Heinz-Peter; Ladd, Mark Edward; Bachert, Peter; Radbruch, Alexander

2015-01-01

To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells. For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 μT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site. Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, pcorrelations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (pcorrelation between MTRasym and ADC was found in CE-T1 tumor (-0.310.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSppatient3 = 0.69 and rSppatient15 = 0.87, pcorrelation of ADC and cellularity was heterogeneous (rSppatient3 = 0.545 (p = 0.067), rSppatient4 = -0.021 (p = 0.948), rSppatient15 = -0.755 (p = 0.005)). NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes
Uranium plasma emission coefficient in the visible and near UV.

Science.gov (United States)

Mack, J. M., Jr.; Usher, J. L.; Schneider, R. T.; Campbell, H. D.

1971-01-01

Measurements of the specific emission coefficient in the near ultra-violet and visible region of a uranium arc plasma are reported. Spatial unfolding of the intensity profile is used to determine the emission coefficient in the spectral range of 2000 A to 6000 A. The uranium partial pressure is estimated to range between .001 and .01 atmosphere, and the corresponding temperature range is 5000 - 10,000 K.
The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

Science.gov (United States)

Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

2018-03-01

Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.
Application of Stochastic Partial Differential Equations to Reservoir Property Modelling

KAUST Repository

Potsepaev, R.

2010-09-06

Existing algorithms of geostatistics for stochastic modelling of reservoir parameters require a mapping (the \\'uvt-transform\\') into the parametric space and reconstruction of a stratigraphic co-ordinate system. The parametric space can be considered to represent a pre-deformed and pre-faulted depositional environment. Existing approximations of this mapping in many cases cause significant distortions to the correlation distances. In this work we propose a coordinate free approach for modelling stochastic textures through the application of stochastic partial differential equations. By avoiding the construction of a uvt-transform and stratigraphic coordinates, one can generate realizations directly in the physical space in the presence of deformations and faults. In particular the solution of the modified Helmholtz equation driven by Gaussian white noise is a zero mean Gaussian stationary random field with exponential correlation function (in 3-D). This equation can be used to generate realizations in parametric space. In order to sample in physical space we introduce a stochastic elliptic PDE with tensor coefficients, where the tensor is related to correlation anisotropy and its variation is physical space.
Prediction of Partition Coefficients of Organic Compounds for SPME/PDMS

Directory of Open Access Journals (Sweden)

Liao Hsuan-Yu

2016-01-01

Full Text Available The partition coefficients of 51 organic compounds between SPME/PDMS and gas were compiled from the literature sources in this study. The effect of physicochemical properties and descriptors on the partitioning process of partition coefficients was explicated by the correlation analysis. The PDMS-gas partition coefficients were well correlated to the molecular weight of organic compounds (r = 0.832, p < 0.05. An empirical model, consisting of the molecular weight and the polarizability, was developed to appropriately predict the partition coefficients of organic compounds. The empirical model for estimating the PDMS-gas partition coefficient will contribute to the practical applications of the SPME technique.
A drying coefficient for building materials

DEFF Research Database (Denmark)

Scheffler, Gregor Albrecht; Plagge, Rudolf

2009-01-01

coefficient is defined which can be determined based on measured drying data. The correlation of this coefficient with the water absorption and the vapour diffusion coefficient is analyzed and its additional information content is critically challenged. As result, a drying coefficient has been derived......The drying experiment is an important element of the hygrothermal characterisation of building materials. Contrary to other moisture transport experiments as the vapour diffusion and the water absorption test, it is until now not possible to derive a simple coefficient for the drying. However......, in many cases such a coefficient would be highly appreciated, e.g. in interaction of industry and research or for the distinction and selection of suitable building materials throughout design and practise. This article first highlights the importance of drying experiments for hygrothermal...
Analytic posteriors for Pearson's correlation coefficient

NARCIS (Netherlands)

Ly, A.; Marsman, M.; Wagenmakers, E.-J.

2018-01-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the
First-principles calculations of impurity diffusion coefficients in dilute Mg alloys using the 8-frequency model

International Nuclear Information System (INIS)

Ganeshan, S.; Hector, L.G.; Liu, Z.-K.

2011-01-01

Research highlights: → Implemented the eight frequency model for impurity diffusion in hexagonal metals. → Model inputs were energetics/vibrational properties from first princples. → Predicted diffusion coefficients for Al, Ca, Zn and Sn impurity diffusion in Mg. → Successful prediction of partial correlation factors and jump frequencies. → Good agreement between calculated and experimental results. - Abstract: Diffusion in dilute Mg-X alloys, where X denotes Al, Zn, Sn and Ca impurities, was investigated with first-principles density functional theory in the local density approximation. Impurity diffusion coefficients were computed as a function of temperature using the 8-frequency model which provided the relevant impurity and solvent (Mg) jump frequencies and correlation factors. Minimum energy pathways for impurity diffusion and associated saddle point structures were computed with the climbing image nudged elastic band method. Vibrational properties were obtained with the supercell (direct) method for lattice dynamics. Calculated diffusion coefficients were compared with available experimental data. For diffusion between basal planes, we find D Mg-Ca > D Mg-Zn > D Mg-Sn > D Mg-Al, where D is the diffusion coefficient. For diffusion within a basal plane, the same trend holds except that D Mg-Zn overlaps with D Mg-Al at high temperatures and D Mg-Sn at low temperatures. These trends were explored with charge density contours in selected planes of each Mg-X alloy, the variation of the activation energy for diffusion with the atomic radius of each impurity and the electronic density of states. The theoretical methodology developed herein can be applied to impurity diffusion in other hexagonal materials.
Experiments and correlations of pressure loss coefficients for hexagonal arranged rod bundles (P/D > 1.02) with helical wire spacers in laminar and turbulent flows

International Nuclear Information System (INIS)

Marten, K.; Yonekawa, S.; Hoffmann, H.

1987-05-01

Advanced pressurized water reactors as well as sodium cooled fast reactors, in their breeding and absorber elements, use tightly packed rod bundles with hexagonally arranged rods. Helical wires or helical fins serve as spacers. The pressure loss coefficients of twelve bundles with helical wires were determined systematically in water experiments. High measuring accuracy was achieved by very precise fabrication of the bundles and the shroud as well as by investigations of the proper measuring techniques. The results show a dependency of the loss coefficients on the Reynolds number and on the P/D and H/D ratios of the bundles. These results together with available systematic experimental results of investigations at P/D > 1.1 were used to develop a correlation to determine the pressure loss coefficients of tightly and widely packed hexagonally arranged rod bundles with helical wire spacers. These correlations were used to recalculate and compare results of pressure loss investigations found in the literature; good agreement was demonstrated. Hence, calculation methods exist for a broad range of applications to determine the pressure loss coefficients of hexagonally arranged rod bundles with helical wires for spacers. (orig./HP) [de
Total and Direct Correlation Function Integrals from Molecular Simulation of Binary Systems

DEFF Research Database (Denmark)

Wedberg, Nils Hejle Rasmus Ingemar; O’Connell, John P.; Peters, Günther H.J.

2011-01-01

The possibility for obtaining derivative properties for mixtures from integrals of spatial total and direct correlation functions obtained from molecular dynamics simulations is explored. Theoretically well-supported methods are examined to extend simulation radial distribution functions to long...... are consistent with an excess Helmholtz energy model fitted to available simulations. In addition, simulations of water/methanol and water/t-butanol mixtures have been carried out. The method yields results for partial molar volumes, activity coefficient derivatives, and individual correlation function integrals...... in reasonable agreement with smoothed experimental data. The proposed method for obtaining correlation function integrals is shown to perform at least as well as or better than two previously published approaches....
Solution of heat equation with variable coefficient using derive

CSIR Research Space (South Africa)

Lebelo, RS

2008-09-01

Full Text Available In this paper, the method of approximating solutions of partial differential equations with variable coefficients is studied. This is done by considering heat flow through a one-dimensional model with variable cross-sections. Two cases...
'aspect' - a new spectrometer for the measurement of the angular correlation coefficient a in neutron beta decay

CERN Document Server

Zimmer, O; Grinten, M G D; Heil, W; Glück, F

2000-01-01

The combination of the coefficient a of the antineutrino/electron angular correlation with the beta asymmetry of the neutron provides a sensitive test for scalar and tensor contributions to the electroweak Lagrangian, as well as for right-handed currents. A method is given for measuring a with high sensitivity from the proton recoil spectrum. The method is based on a magnetic spectrometer with electrostatic retardation potentials such as used for searches of the neutrino mass in tritium beta decay. The spectrometer can also be used for similar studies using radioactive nuclei.
Prediction of Partition Coefficients of Organic Compounds for SPME/PDMS

OpenAIRE

Liao Hsuan-Yu; Huang Miao-Ling; Lu Yu-Ting; Chao Keh-Ping

2016-01-01

The partition coefficients of 51 organic compounds between SPME/PDMS and gas were compiled from the literature sources in this study. The effect of physicochemical properties and descriptors on the partitioning process of partition coefficients was explicated by the correlation analysis. The PDMS-gas partition coefficients were well correlated to the molecular weight of organic compounds (r = 0.832, p < 0.05). An empirical model, consisting of the molecular weight and the polarizability, was ...

Determination of molecular diffusion coefficient in n-alkane binary mixtures: empirical correlations.

Science.gov (United States)

De Mezquia, D Alonso; Bou-Ali, M Mounir; Larrañaga, M; Madariaga, J A; Santamaría, C

2012-03-08

In this work we have measured the molecular diffusion coefficient of the n-alkane binary series nC(i)-nC(6), nC(i)-nC(10), and nC(i)-nC(12) at 298 K and 1 atm and a mass fraction of 0.5 by using the so-called sliding symmetric tubes technique. The results show that the diffusion coefficient at this concentration is proportional to the inverse viscosity of the mixture. In addition, we have also measured the diffusion coefficient of the systems nC(12)-nC(6), nC(12)-nC(7), and nC(12)-nC(8) as a function of concentration. From the data obtained, it is shown that the diffusion coefficient of the n-alkane binary mixtures at any concentration can be calculated from the molecular weight of the components and the dynamic viscosity of the corresponding mixture at 50% mass fraction.
Evidence of quantum correlations in the H/D-transfer dynamics in the hydrogen bonds in partially deuterated benzoic acid crystals

Science.gov (United States)

Takeda, Sadamu; Tsuzumitani, Akihiko; Chatzidimitriou-Dreismann, C. A.

1992-10-01

A precise investigation of spin—lattice relaxation rates for protons and deuterons of partially deuterated benzoic acid crystals showed a remarkable quenching of the transfer rate of an HD pair in hydrogen-bonded dimeric units of carboxyl groups with increasing concentration of D in the surrounding hydrogen bonds. A similar effect was also observed for partially deuterated crystals of acetylenedicarboxylic acid. This finding supports recent theoretical predictions of thermally activated protonic quantum correlation in condensed matter and proposes a new mechanism for the proton transfer in hydrogen bonds in condensed matter.
Pancreatic neuroendocrine tumour: Correlation of apparent diffusion coefficient or WHO classification with recurrence-free survival.

Science.gov (United States)

Kim, Mimi; Kang, Tae Wook; Kim, Young Kon; Kim, Seong Hyun; Kwon, Wooil; Ha, Sang Yun; Ji, Sang A

2016-03-01

To evaluate the correlation between grade of pancreatic neuroendocrine tumours (pNETs) based on the 2010 World Health Organization (WHO) classification and the apparent diffusion coefficient (ADC), and to assess whether the ADC value and WHO classification can predict recurrence-free survival (RFS) after surgery for pNETs. This retrospective study was approved by the Institutional Review Board. The requirement for informed consent was waived. Between March 2009 and November 2014, forty-nine patients who underwent magnetic resonance (MR) imaging with diffusion-weighted image and subsequent surgery for single pNETs were included. Correlations among qualitative MR imaging findings, quantitative ADC values, and WHO classifications were assessed. An ordered logistic regression test was used to control for tumour size as a confounding factor. The association between ADC value (or WHO classification) and RFS was analysed. All tumors (n=49) were classified as low- (n=29, grade 1), intermediate- (n=17, grade 2), and high-grade (n=3, grade 3), respectively. The mean ADC of pNETs was moderately negatively correlated with WHO classification before and after adjustment for tumour size (ρ=-0.64, pcorrelated with WHO tumour grade, regardless of tumour size. However, the WHO tumour classification of pNET may be more suitable for predicting RFS than the ADC value. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Partially massless fields during inflation

Science.gov (United States)

Baumann, Daniel; Goon, Garrett; Lee, Hayden; Pimentel, Guilherme L.

2018-04-01

The representation theory of de Sitter space allows for a category of partially massless particles which have no flat space analog, but could have existed during inflation. We study the couplings of these exotic particles to inflationary perturbations and determine the resulting signatures in cosmological correlators. When inflationary perturbations interact through the exchange of these fields, their correlation functions inherit scalings that cannot be mimicked by extra massive fields. We discuss in detail the squeezed limit of the tensor-scalar-scalar bispectrum, and show that certain partially massless fields can violate the tensor consistency relation of single-field inflation. We also consider the collapsed limit of the scalar trispectrum, and find that the exchange of partially massless fields enhances its magnitude, while giving no contribution to the scalar bispectrum. These characteristic signatures provide clean detection channels for partially massless fields during inflation.
Correlation between electrical conductivity and apparent diffusion coefficient in breast cancer: effect of necrosis on magnetic resonance imaging.

Science.gov (United States)

Kim, Soo-Yeon; Shin, Jaewook; Kim, Dong-Hyun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; You, Jai Kyung; Kim, Min Jung

2018-03-06

To investigate the correlation between conductivity and ADC in invasive ductal carcinoma according to the presence of necrosis on MRI. Eighty-one women with invasive ductal carcinoma ≥1 cm on T2-weighted fast spin echo sequence of preoperative MRI were included. Phase-based MR electric properties tomography was used to reconstruct conductivity. Mean ADC was measured. Necrosis was defined as an area with very high T2 signal intensity. The relationship between conductivity and ADC was examined using Spearman's correlation coefficient (r). Multiple linear regression analysis was performed to identify factors associated with conductivity or ADC. In the total group, conductivity showed negative correlation with ADC (r = -0.357, p = 0.001). This correlation was maintained in the subgroup without necrosis (n = 53, r = -0.455, p = 0.001), but not in the subgroup with necrosis (n = 28, r = -0.080, p = 0.687). The correlation between the two parameters was different according to necrosis (r = -0.455 vs -0.080, p = 0.047). HER2 enriched subtype was independently associated with conductivity (p = 0.029). Necrosis on MRI was independently associated with ADC (p = 0.027). Conductivity shows negative correlation with ADC that is abolished by the presence of necrosis on MRI. • Electric conductivity showed negative correlation with ADC • However, the correlation was abolished by the presence of necrosis on MRI • HER2-enriched subtype was independently associated with conductivity • Necrosis on MRI was independently associated with ADC.
Correlation of heat transfer coefficient in quenching process using ABAQUS

Science.gov (United States)

Davare, Sandeep Kedarnath; Balachandran, G.; Singh, R. K. P.

2018-04-01

During the heat treatment by quenching in a liquid medium the convective heat transfer coefficient plays a crucial role in the extraction of heat. The heat extraction ultimately influences the cooling rate and hence the hardness and mechanical properties. A Finite Element analysis of quenching a simple flat copper sample with different orientation of sample and with different quenchant temperatures were carried out to check and verify the results obtained from the experiments. The heat transfer coefficient (HTC) was calculated from temperature history in a simple flat copper disc sample experimentally. This HTC data was further used as input to simulation software and the cooling curves were back calculated. The results obtained from software and using experimentation shows nearly consistent values.
Correlation between apparent diffusion coefficients and HER2 status in gastric cancers: pilot study

International Nuclear Information System (INIS)

He, Jian; Shi, Hua; Zhou, Zhuping; Chen, Jun; Guan, Wenxian; Wang, Hao; Yu, Haiping; Liu, Song; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian

2015-01-01

To evaluate whether apparent diffusion coefficient (ADC) value of gastric cancer obtained from diffusion weighted imaging (DWI) correlates with the HER2 status. Forty-five patients, who had been diagnosed with gastric cancer through biopsy, were enrolled in this IRB-approved study. Each patient underwent a DWI (b values: 0 and 1,000 sec/mm 2 ) prior to surgery (curative gastrectomy or palliative resection). Postoperative microscopic findings, HER2 status by immunohistochemical analysis and fluorescence in situ hybridization (FISH) were obtained. HER2 status was compared among gastric cancers with various histopathological features using the chi square test. The ADC values of gastric cancers with positive and negative HER2 were compared using the student t test. A weak yet significant correlation was observed between the mean ADC values and HER2 status (r = 0.312, P = 0.037) and scores (r = 0.419, P = 0.004). The mean ADC value of HER2-positive gastric cancers was significantly higher than those of HER2-negative tumors (1.211 vs. 0.984 mm 2 /s, P = 0.020). The minimal ADC value of HER2-positive gastric cancers was significantly higher than those of HER2-negative tumors (1.105 vs. 0.905 × 10 −3 mm 2 /s, P = 0.036). In this pilot study, we have demonstrated that the ADC values of gastric cancer correlate with the HER2 status. Future research is warranted to see if DWI can predict HER2 status and help in tailoring therapy for gastric cancer
Correlation of Benzene, 1,1,1-Trichloroethane, and Naphthalene Distribution Coefficients to the Characteristics of Aquifer Materials With Low Organic Carbon Content

DEFF Research Database (Denmark)

Larsen, Thomas; Kjeldsen, Peter; Christensen, Thomas Højlund

1992-01-01

area of the aquifer materials as a second regression parameter did not significantly improve the correlation. Estimated Koc values were up to 3 times higher than those predicted from regression equations based on the octanol-water partition coefficient. The reason for this is not known, but may...
The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

Directory of Open Access Journals (Sweden)

Ying Peng

2018-03-01

Full Text Available Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.
Concordance-based Kendall's Correlation for Computationally-Light vs. Computationally-Heavy Centrality Metrics: Lower Bound for Correlation

Directory of Open Access Journals (Sweden)

Natarajan Meghanathan

2017-01-01

Full Text Available We identify three different levels of correlation (pair-wise relative ordering, network-wide ranking and linear regression that could be assessed between a computationally-light centrality metric and a computationally-heavy centrality metric for real-world networks. The Kendall's concordance-based correlation measure could be used to quantitatively assess how well we could consider the relative ordering of two vertices vi and vj with respect to a computationally-light centrality metric as the relative ordering of the same two vertices with respect to a computationally-heavy centrality metric. We hypothesize that the pair-wise relative ordering (concordance-based assessment of the correlation between centrality metrics is the most strictest of all the three levels of correlation and claim that the Kendall's concordance-based correlation coefficient will be lower than the correlation coefficient observed with the more relaxed levels of correlation measures (linear regression-based Pearson's product-moment correlation coefficient and the network wide ranking-based Spearman's correlation coefficient. We validate our hypothesis by evaluating the three correlation coefficients between two sets of centrality metrics: the computationally-light degree and local clustering coefficient complement-based degree centrality metrics and the computationally-heavy eigenvector centrality, betweenness centrality and closeness centrality metrics for a diverse collection of 50 real-world networks.
Kubo Formulas for Second-Order Hydrodynamic Coefficients

International Nuclear Information System (INIS)

Moore, Guy D.; Sohrabi, Kiyoumars A.

2011-01-01

At second order in gradients, conformal relativistic hydrodynamics depends on the viscosity η and on five additional ''second-order'' hydrodynamical coefficients τ Π , κ, λ 1 , λ 2 , and λ 3 . We derive Kubo relations for these coefficients, relating them to equilibrium, fully retarded three-point correlation functions of the stress tensor. We show that the coefficient λ 3 can be evaluated directly by Euclidean means and does not in general vanish.
Increased correlation coefficient between the written test score and tutors' performance test scores after training of tutors for assessment of medical students during problem-based learning course in Malaysia.

Science.gov (United States)

Jaiprakash, Heethal; Min, Aung Ko Ko; Ghosh, Sarmishtha

2016-03-01

This paper is aimed at finding if there was a change of correlation between the written test score and tutors' performance test scores in the assessment of medical students during a problem-based learning (PBL) course in Malaysia. This is a cross-sectional observational study, conducted among 264 medical students in two groups from November 2010 to November 2012. The first group's tutors did not receive tutor training; while the second group's tutors were trained in the PBL process. Each group was divided into high, middle and low achievers based on their end-of-semester exam scores. PBL scores were taken which included written test scores and tutors' performance test scores. Pearson correlation coefficient was calculated between the two kinds of scores in each group. The correlation coefficient between the written scores and tutors' scores in group 1 was 0.099 (pcorrelation coefficient in the group where tutors received the PBL training reinforces the importance of tutor training before their participation in the PBL course.
Generalised partial autocorrelations and the mutual information between past and future

DEFF Research Database (Denmark)

Proietti, Tommaso; Luati, Alessandra

the generalized partial autocorrelations as the partial autocorrelation coefficients of an auxiliary process, we derive their properties and relate them to essential features of the original process. Based on a parameterisation suggested by Barndorff-Nielsen and Schou (1973) and on Whittle likelihood, we develop...
Correlation between incidences of self-inflicted burns and means of inbreeding coefficients, an ecologic study.

Science.gov (United States)

Saadat, Mostafa; Zendeh-Boodi, Zahra

2006-09-01

The aim of the study is to obtain more insight into the possible association between consanguinity and the incidence of deliberate self-burning. Data were obtained by analysis of medical records of patients hospitalized in two referral burn centers: Chormy Burn Center (Bushehr Province, south of Iran) from March 21, 1998, through March 20, 2004, and Shahid Sadoqi Center of Burns and Injuries (Yazd Province, center of Iran) from March 21, 2000, through March 20, 2004. The incidence of suicidal burns was 6.51 and 2.32/100,000 person-years for Bushehr and Yazd Provinces, respectively. The observed sex ratio of patients in both centers indicated there was a female predominance in patients with self-inflicted burns. Using patients' home addresses, patients were sorted into 16 cities. The incidence of suicide by self-burning ranged from 0.80 (for Tabas, located in Yazd Province) to 12.60/100,000 person-years (for Dilam, located in Bushehr Province). The coefficient of inbreeding defines the probability that an individual received both alleles of a pair from an identical ancestral source. There was a significant correlation between incidences of suicidal burns and mean coefficient of inbreeding (r = 0.782, df = 14, p < 0.001). In addition to other factors, consanguineous marriage may be a risk factor that influences the incidence of suicidal burns in a population.
Moving-window bis-correlation coefficients method for visible and near-infrared spectral discriminant analysis with applications

Directory of Open Access Journals (Sweden)

Lijun Yao

2018-03-01

Full Text Available The moving-window bis-correlation coefficients (MW-BiCC was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and β-thalassemia with visible and near-infrared (Vis–NIR spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA was also conducted for comparison. A total of 306 transgenic (positive and 150 nontransgenic (negative leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG smoothing with first-order derivative (d=1, third-degree polynomial (p=3 and 25 smoothing points (m=25. The selected waveband was 736–1054nm with MW-BiCC, and the positive and negative validation recognition rates (V_REC+, V_REC− were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 β-thalassemia (positive and 148 nonthalassemia (negative of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm. The V_REC+ and V_REC− were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coefficients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing β-thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.
Significant Differences Characterise the Correlation Coefficients between Biocide and Antibiotic Susceptibility Profiles in Staphylococcus aureus.

Science.gov (United States)

Oggioni, Marco R; Coelho, Joana Rosado; Furi, Leonardo; Knight, Daniel R; Viti, Carlo; Orefici, Graziella; Martinez, Jose-Luis; Freitas, Ana Teresa; Coque, Teresa M; Morrissey, Ian

2015-01-01

There is a growing concern by regulatory authorities for the selection of antibiotic resistance caused by the use of biocidal products. We aimed to complete the detailed information on large surveys by investigating the relationship between biocide and antibiotic susceptibility profiles of a large number of Staphylococcus aureus isolates using four biocides and antibiotics commonly used in clinical practice. The minimal inhibitory concentration (MIC) for most clinically-relevant antibiotics was determined according to the standardized methodology for over 1600 clinical S. aureus isolates and compared to susceptibility profiles of benzalkonium chloride, chlorhexidine, triclosan, and sodium hypochlorite. The relationship between antibiotic and biocide susceptibility profiles was evaluated using non-linear correlations. The main outcome evidenced was an absence of any strong or moderate statistically significant correlation when susceptibilities of either triclosan or sodium hypochlorite were compared for any of the tested antibiotics. On the other hand, correlation coefficients for MICs of benzalkonium chloride and chlorhexidine were calculated above 0.4 for susceptibility to quinolones, beta-lactams, and also macrolides. Our data do not support any selective pressure for association between biocides and antibiotics resistance and furthermore do not allow for a defined risk evaluation for some of the compounds. Importantly, our data clearly indicate that there does not involve any risk of selection for antibiotic resistance for the compounds triclosan and sodium hypochlorite. These data hence infer that biocide selection for antibiotic resistance has had so far a less significant impact than feared.
Amide temperature coefficients in the protein G B1 domain

International Nuclear Information System (INIS)

Tomlinson, Jennifer H.; Williamson, Mike P.

2012-01-01

Temperature coefficients have been measured for backbone amide 1 H and 15 N nuclei in the B1 domain of protein G (GB1), using temperatures in the range 283–313 K, and pH values from 2.0 to 9.0. Many nuclei display pH-dependent coefficients, which were fitted to one or two pK a values. 1 H coefficients showed the expected behaviour, in that hydrogen-bonded amides have less negative values, but for those amides involved in strong hydrogen bonds in regular secondary structure there is a negative correlation between strength of hydrogen bond and size of temperature coefficient. The best correlation to temperature coefficient is with secondary shift, indicative of a very approximately uniform thermal expansion. The largest pH-dependent changes in coefficient are for amides in loops adjacent to sidechain hydrogen bonds rather than the amides involved directly in hydrogen bonds, indicating that the biggest determinant of the temperature coefficient is temperature-dependent loss of structure, not hydrogen bonding. Amide 15 N coefficients have no clear relationship with structure.
Increased correlation coefficient between the written test score and tutors’ performance test scores after training of tutors for assessment of medical students during problem-based learning course in Malaysia

Directory of Open Access Journals (Sweden)

Heethal Jaiprakash

2016-03-01

Full Text Available This paper is aimed at finding if there was a change of correlation between the written test score and tutors’ performance test scores in the assessment of medical students during a problem-based learning (PBL course in Malaysia. This is a cross-sectional observational study, conducted among 264 medical students in two groups from November 2010 to November 2012. The first group’s tutors did not receive tutor training; while the second group’s tutors were trained in the PBL process. Each group was divided into high, middle and low achievers based on their end-of-semester exam scores. PBL scores were taken which included written test scores and tutors’ performance test scores. Pearson correlation coefficient was calculated between the two kinds of scores in each group. The correlation coefficient between the written scores and tutors’ scores in group 1 was 0.099 (p<0.001 and for group 2 was 0.305 (p<0.001. The higher correlation coefficient in the group where tutors received the PBL training reinforces the importance of tutor training before their participation in the PBL course.
Drag Coefficient Estimation in Orbit Determination

Science.gov (United States)

McLaughlin, Craig A.; Manee, Steve; Lichtenberg, Travis

2011-07-01

Drag modeling is the greatest uncertainty in the dynamics of low Earth satellite orbits where ballistic coefficient and density errors dominate drag errors. This paper examines fitted drag coefficients found as part of a precision orbit determination process for Stella, Starlette, and the GEOSAT Follow-On satellites from 2000 to 2005. The drag coefficients for the spherical Stella and Starlette satellites are assumed to be highly correlated with density model error. The results using MSIS-86, NRLMSISE-00, and NRLMSISE-00 with dynamic calibration of the atmosphere (DCA) density corrections are compared. The DCA corrections were formulated for altitudes of 200-600 km and are found to be inappropriate when applied at 800 km. The yearly mean fitted drag coefficients are calculated for each satellite for each year studied. The yearly mean drag coefficients are higher for Starlette than Stella, where Starlette is at a higher altitude. The yearly mean fitted drag coefficients for all three satellites decrease as solar activity decreases after solar maximum.
Experimental determination of new statistical correlations for the calculation of the heat transfer coefficient by convection for flat plates, cylinders and tube banks

Directory of Open Access Journals (Sweden)

Ismael Fernando Meza Castro

2017-07-01

Full Text Available Introduction: This project carried out an experimental research with the design, assembly, and commissioning of a convection heat transfer test bench. Objective: To determine new statistical correlations that allow knowing the heat transfer coefficients by air convection with greater accuracy in applications with different heating geometry configurations. Methodology: Three geometric configurations, such as flat plate, cylinders and tube banks were studied according to their physical properties through Reynolds and Prandtl numbers, using a data transmission interface using Arduino® controllers Measured the air temperature through the duct to obtain real-time data and to relate the heat transferred from the heating element to the fluid and to perform mathematical modeling in specialized statistical software. The study was made for the three geometries mentioned, one power per heating element and two air velocities with 10 repetitions. Results: Three mathematical correlations were obtained with regression coefficients greater than 0.972, one for each heating element, obtaining prediction errors in the heat transfer convective coefficients of 7.50% for the flat plate, 2.85% for the plate Cylindrical and 1.57% for the tube bank. Conclusions: It was observed that in geometries constituted by several individual elements, a much more accurate statistical adjustment was obtained to predict the behavior of the convection heat coefficients, since each unit reaches a stability in the surface temperature profile with Greater speed, giving the geometry in general, a more precise measurement of the parameters that govern the transfer of heat, as it is in the case of the geometry of the tube bank.

Mayer coefficients in two-dimensional Coulomb systems

International Nuclear Information System (INIS)

Speer, E.R.

1986-01-01

It is shown that, for neutral systems of particles of arbitrary charges in two dimensions, with hard cores, coefficients of the Mayer series for the pressure exist in the thermodynamic limit below certain thresholds in the temperature. The methods used here apply also to correlation functions and yield bounds on the asymptotic behavior of their Mayer coefficients
Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

Science.gov (United States)

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.
Correlation between apparent diffusion coefficient and histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy.

Science.gov (United States)

Wang, Jifei; Sun, Meili; Liu, Dawei; Hu, Xiaoshu; Pui, Margaret H; Meng, Quanfei; Gao, Zhenhua

2017-08-01

Background Neoadjuvant chemotherapy has made limb-salvage surgery possible for the patients with osteosarcoma. Diffusion-weighted magnetic resonance imaging (DWI) has been used to monitor chemotherapy response. Purpose To correlate the apparent diffusion coefficient (ADC) values with histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy. Material and Methods Twelve patients with osteoblastic (n = 7), chondroblastic (n = 4), and fibroblastic (n = 1) osteosarcomas underwent post-chemotherapy DWI before limb-salvage surgery. ADCs corresponding to 127 histological tissue samples from the 12 resected specimens were compared to histological features. Results The mean ADC value of non-cartilaginous viable tumor (38/91, ADC = 1.22 ± 0.03 × 10 -3 mm 2 /s) was significantly ( P 0.05) different between viable cartilaginous tumor and cystic/hemorrhagic necrosis. Conclusion DWI allows assessment of tumor necrosis after neoadjuvant chemotherapy by ADC differences between viable tumor and necrosis in fibroblastic and osteoblastic osteosarcomas whereas viable chondroblastic osteosarcoma has high ADC and cannot be distinguished reliably from necrosis.
Canonical coordinates for partial differential equations

Science.gov (United States)

Hunt, L. R.; Villarreal, Ramiro

1988-01-01

Necessary and sufficient conditions are found under which operators of the form Sigma (m, j=1) x (2) sub j + X sub O can be made constant coefficient. In addition, necessary and sufficient conditions are derived which classify those linear partial differential operators that can be moved to the Kolmogorov type.
Canonical coordinates for partial differential equations

Science.gov (United States)

Hunt, L. R.; Villarreal, Ramiro

1987-01-01

Necessary and sufficient conditions are found under which operators of the form Sigma(m, j=1) X(2)sub j + X sub 0 can be made constant coefficient. In addition, necessary and sufficient conditions are derived which classify those linear partial differential operators that can be moved to the Kolmogorov type.
[Correlation between gaseous exchange rate, body temperature, and mitochondrial protein content in the liver of mice].

Science.gov (United States)

Muradian, Kh K; Utko, N O; Mozzhukhina, T H; Pishel', I M; Litoshenko, O Ia; Bezrukov, V V; Fraĭfel'd, V E

2002-01-01

Correlative and regressive relations between the gaseous exchange, thermoregulation and mitochondrial protein content were analyzed by two- and three-dimensional statistics in mice. It has been shown that the pair wise linear methods of analysis did not reveal any significant correlation between the parameters under exploration. However, it became evident at three-dimensional and non-linear plotting for which the coefficients of multivariable correlation reached and even exceeded 0.7-0.8. The calculations based on partial differentiation of the multivariable regression equations allow to conclude that at certain values of VO2, VCO2 and body temperature negative relations between the systems of gaseous exchange and thermoregulation become dominating.
Tomography based determination of permeability, Dupuit-Forchheimer coefficient, and interfacial heat transfer coefficient in reticulate porous ceramics

International Nuclear Information System (INIS)

Petrasch, Joerg; Meier, Fabian; Friess, Hansmartin; Steinfeld, Aldo

2008-01-01

A computer tomography based methodology is applied to determine the transport properties of fluid flow across porous media. A 3D digital representation of a 10-ppi reticulate porous ceramic (RPC) sample was generated by X-ray tomographic scans. Structural properties such as the porosity, specific interfacial surface area, pore-size distribution, mean survival time, two-point correlation function s 2 , and local geometry distribution of the RPC sample are directly extracted from the tomographic data. Reference solutions of the fluid flow governing equations are obtained for Re = 0.2-200 by applying finite volume direct pore-level numerical simulation (DPLS) using unstructured, body-fitted, tetrahedral mesh discretization. The permeability and the Dupuit-Forchheimer coefficient are determined from the reference solutions by DPLS, and compared to the values predicted by selected porous media flow models, namely: conduit-flow, hydraulic radius theory, drag models, mean survival time bound, s 2 -bound, fibrous bed correlations, and local porosity theory-based models. DPLS is further employed to determine the interfacial heat transfer coefficient and to derive a corresponding Nu-correlation, which is compared to empirical correlations
Investigation on Thrust and Moment Coefficients of a Centrifugal Turbomachine

Directory of Open Access Journals (Sweden)

Bo Hu

2018-04-01

Full Text Available In radial pumps and turbines, the centrifugal through-flow in both the front and the back chambers is quite common. It strongly impacts the core swirl ratio, pressure distribution, axial thrust and frictional torque. In order to investigate these relationships experimentally, a test rig was designed at the University of Duisburg-Essen and described in this paper. Based on both the experimental and numerical results, correlations are determined to predict the impacts of the centrifugal through-flow on the core swirl ratio, the thrust coefficient and the moment coefficient. Two correlations respectively are determined to associate the core swirl ratio with the local through-flow coefficient for both Batchelor type flow and Stewartson type flow. The correlations describing the thrust coefficient and the moment coefficient in a rotor-stator cavity with centripetal through-flow (Hu et al., 2017 are modified for the case of centrifugal through-flow. The Daily and Nece diagram distinguishing between different flow regimes in rotor-stator cavities is extended with a through-flow coordinate into 3D. The achieved results provide a comprehensive data base which is intended to support the calculation of axial thrust and moment coefficients during the design process of radial pumps and turbines in a more accurate manner.
Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

Science.gov (United States)

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulation data for an estimation of the maximum theoretical value and confidence interval for the correlation coefficient.

Science.gov (United States)

Rocco, Paolo; Cilurzo, Francesco; Minghetti, Paola; Vistoli, Giulio; Pedretti, Alessandro

2017-10-01

The data presented in this article are related to the article titled "Molecular Dynamics as a tool for in silico screening of skin permeability" (Rocco et al., 2017) [1]. Knowledge of the confidence interval and maximum theoretical value of the correlation coefficient r can prove useful to estimate the reliability of developed predictive models, in particular when there is great variability in compiled experimental datasets. In this Data in Brief article, data from purposely designed numerical simulations are presented to show how much the maximum r value is worsened by increasing the data uncertainty. The corresponding confidence interval of r is determined by using the Fisher r → Z transform.
Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

Science.gov (United States)

Satomura, Hironori; Adachi, Kohei

2013-07-01

To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions.
An Improved Heaviside Approach to Partial Fraction Expansion and Its Applications

Science.gov (United States)

Man, Yiu-Kwong

2009-01-01

In this note, we present an improved Heaviside approach to compute the partial fraction expansions of proper rational functions. This method uses synthetic divisions to determine the unknown partial fraction coefficients successively, without the need to use differentiation or to solve a system of linear equations. Examples of its applications in…
Varying coefficients model with measurement error.

Science.gov (United States)

Li, Liang; Greene, Tom

2008-06-01

We propose a semiparametric partially varying coefficient model to study the relationship between serum creatinine concentration and the glomerular filtration rate (GFR) among kidney donors and patients with chronic kidney disease. A regression model is used to relate serum creatinine to GFR and demographic factors in which coefficient of GFR is expressed as a function of age to allow its effect to be age dependent. GFR measurements obtained from the clearance of a radioactively labeled isotope are assumed to be a surrogate for the true GFR, with the relationship between measured and true GFR expressed using an additive error model. We use locally corrected score equations to estimate parameters and coefficient functions, and propose an expected generalized cross-validation (EGCV) method to select the kernel bandwidth. The performance of the proposed methods, which avoid distributional assumptions on the true GFR and residuals, is investigated by simulation. Accounting for measurement error using the proposed model reduced apparent inconsistencies in the relationship between serum creatinine and GFR among different clinical data sets derived from kidney donor and chronic kidney disease source populations.
Effect of Partial Shrouds on the Performance and Flow Field of a Low-Aspect-Ratio Axial-Flow Fan Rotor

Directory of Open Access Journals (Sweden)

N. Sitaram

2011-01-01

Full Text Available The flow field at the rotor exit of a low aspect ratio axial flow fan for different tip geometries and for different flow coefficients is measured in the present study. The following configurations are tested: (1 rotor without partial shroud, designated as rotor (wos, (2 rotor with partial shroud, designated as rotor (ws, and (3 rotor with perforated (perforations in the shape of discrete circular holes partial shroud, designated as rotor (wps. From steady state measurements, the performance of rotor (wps is found to be the best. Both the rotors with partial shrouds have stalled at a higher flow coefficient compared to that of rotor (wos. From periodic flow measurements, it is concluded that the low velocity region near the tip section is considerably reduced with the use of partial shrouds with perforations. The extent of this low velocity region for both rotor (wos and rotor (wps increases with decreasing flow coefficient due to increased stage loading. This core of low momentum fluid has moved inwards of the annulus and towards the pressure side as the flow coefficient decreases. The extent of the low momentum fluid is smaller for rotor (wps than that of rotor (wos at all flow coefficients.
Movie Popularity Classification based on Inherent Movie Attributes using C4.5, PART and Correlation Coefficient

DEFF Research Database (Denmark)

Ibnal Asad, Khalid; Ahmed, Tanvir; Rahman, Md. Saiedur

2012-01-01

Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet...... sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we...... propose classification scheme of pre-release movie popularity based on inherent attributes using C4.S and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient....
Correlated linear response calculations of the C6 dispersion coefficients of hydrogen halides

Czech Academy of Sciences Publication Activity Database

Sauer, S. P. A.; Paidarová, Ivana

2007-01-01

Roč. 3, 2-4 (2007), s. 399-421 ISSN 1574-0404 R&D Projects: GA AV ČR IAA401870702 Institutional research plan: CEZ:AV0Z40400503 Keywords : hydrogen halides * C6 dospersion coefficients * van der Waals coefficients * polarizability at imaginary frequences * SOPPA Subject RIV: CF - Physical ; Theoretical Chemistry
Monte Carlo based diffusion coefficients for LMFBR analysis

International Nuclear Information System (INIS)

Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

2010-01-01

A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)
Correlation of the octanol/water partition coefficient with clearance halftimes of intratracheally instilled aromatic hydrocarbons in rats

International Nuclear Information System (INIS)

Bond, J.A.; Baker, S.M.; Bechtold, W.E.

1985-01-01

Studies on the lung retention of polycyclic aromatic hydrocarbons (PAH) after inhalation have indicated that, in general, the PAH are rapidly cleared from the respiratory tract. Clearance of the PAH from the lungs is best described as bi-phasic, with the long-term component of the clearance curve having a half-time of greater than 24 h. The purpose of this study was to determine whether a relationship exists between the lipophilicity (as measured by the octanol/water partition coefficient, P) of various PAH and the short-term and long-term clearance half-times of PAH in rat lungs. Female F344/Crl rats were administered intratracheally 1 nmol of 14 C-labelled anthracene (AN), benz (a) anthracene (BA), 1-nitropyrene (NP), 6-nitrobenzo (a) pyrene (6-NBP), or dibenzo (c, g) carbazole (DBC). At various times after instillation rats were sacrificed and the amount of 14 C from rat lungs following instillation of the different PAH was biphasic. In all cases, greater than 85% of the initial dose instilled was cleared with a half-time of less than 1 h. The half-times for clearance of the residual 14 C (1-15% of the dose) were 26, 30, 36, 53 and 63 h for AN, NP, 6-NBP, BA and DCB, respectively. The log of the octanol-water partition coefficients for the different PAH examined ranged from 4.1 (AN) to 6.05 (DBC). Plots of the octanol/water coefficients vs. the long-term clearance half-time for the PAH indicated a linear correlation (p 2 =0.96). The results from this study indicate that the greater the lipophilicity of the PAH, the slower the long-term clearance of a small fraction (1-15%) of PAH from rat lungs. These data suggest that predictions of long-term lung clearance can be made for PAH with log octanol-water partition coefficients between 4 and 6. (author)
GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

Science.gov (United States)

Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin

2011-05-01

The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is
Efficient tracking of the cross-correlation coefficient

NARCIS (Netherlands)

Aarts, R.M.; Irwan, R.; Janssen, A.J.E.M.

2002-01-01

In many (audio) processing algorithms, involving manipulation of discrete-time signals, the performance can vary strongly over the repertoire that is used. This may be the case when the signals from the various channels are allowed to be strongly positively or negatively correlated. We propose and

[Correlation between end-tidal carbon dioxide and partial pressure of arterial carbon dioxide in ventilated newborns].

Science.gov (United States)

Feng, Jin-Xing; Liu, Xiao-Hong; Huang, Hui-Jun; Yu, Zhen-Zhu; Yang, Hui; He, Liu-Fang

2014-05-01

To study the correlation between end-tidal carbon dioxide (PetCO2) and partial pressure of arterial carbon dioxide (PaCO2) in ventilated newborns. Thirty-one ventilated newborn underwent mainstream PetCO2 monitoring; meanwhile, arterial blood gas analysis was performed. The correlation and consistency between PetCO2 and PaCO2 were assessed. A total of 85 end-tidal and arterial CO2 pairs were obtained from 31 ventilated newborns. The mean PetCO2 (41±10 mm Hg) was significantly lower than the corresponding mean PaCO2 (46±11 mm Hg) (Plimits of consistency, -3.3 to 13.6 mmHg), and 5% (4/85) of the points were beyond the 95%CI. When the oxygenation index (OI) was less than 300 mm Hg (n=48), there was a significant positive correlation between PetCO2 and PaCO2 (r=0.85, Plimits of consistency, -2.6 to 14.5 mm Hg), and 4.2% (2/48) of the points were beyond the 95%CI. When the OI was more than 300 mm Hg (n=37), there was also a significant positive correlation between PetCO2 and PaCO2 (r=0.91, Plimits of consistency, -3.9 to 12.1 mm Hg), and 5% (2/37) of the points were beyond the 95%CI. There is a good correlation and consistency between PetCO2 and PaCO2 in ventilated newborns.
Automated collimation testing by determining the statistical correlation coefficient of Talbot self-images.

Science.gov (United States)

Rana, Santosh; Dhanotia, Jitendra; Bhatia, Vimal; Prakash, Shashi

2018-04-01

In this paper, we propose a simple, fast, and accurate technique for detection of collimation position of an optical beam using the self-imaging phenomenon and correlation analysis. Herrera-Fernandez et al. [J. Opt.18, 075608 (2016)JOOPDB0150-536X10.1088/2040-8978/18/7/075608] proposed an experimental arrangement for collimation testing by comparing the period of two different self-images produced by a single diffraction grating. Following their approach, we propose a testing procedure based on correlation coefficient (CC) for efficient detection of variation in the size and fringe width of the Talbot self-images and thereby the collimation position. When the beam is collimated, the physical properties of the self-images of the grating, such as its size and fringe width, do not vary from one Talbot plane to the other and are identical; the CC is maximum in such a situation. For the de-collimated position, the size and fringe width of the self-images vary, and correspondingly the CC decreases. Hence, the magnitude of CC is a measure of degree of collimation. Using the method, we could set the collimation position to a resolution of 1 μm, which relates to ±0.25 μ radians in terms of collimation angle (for testing a collimating lens of diameter 46 mm and focal length 300 mm). In contrast to most collimation techniques reported to date, the proposed technique does not require a translation/rotation of the grating, use of complicated phase evaluation algorithms, or an intricate method for determination of period of the grating or its self-images. The technique is fully automated and provides high resolution and precision.
Coefficient αcc in design value of concrete compressive strength

Directory of Open Access Journals (Sweden)

Goleš Danica

2016-01-01

Full Text Available Coefficient αcc introduces the effects of rate and duration of loading on compressive strength of concrete. These effects may be partially or completely compensated by the increase in concrete strength over time. Selection of the value of this coefficient, in recommended range between 0.8 and 1.0, is carried out through the National Annexes to Eurocode 2. This paper presents some considerations related to the introduction of this coefficient and its value adopted in some European countries. The article considers the effect of the adoption of conservative value αcc=0.85 on design value of compressive and flexural resistance of rectangular cross-section made of normal and high strength concrete. It analyzes the influence of different values of coefficient αcc on the area of reinforcement required to achieve the desired resistance of cross-section.
Activity coefficients from molecular simulations using the OPAS method

Science.gov (United States)

Kohns, Maximilian; Horsch, Martin; Hasse, Hans

2017-10-01

A method for determining activity coefficients by molecular dynamics simulations is presented. It is an extension of the OPAS (osmotic pressure for the activity of the solvent) method in previous work for studying the solvent activity in electrolyte solutions. That method is extended here to study activities of all components in mixtures of molecular species. As an example, activity coefficients in liquid mixtures of water and methanol are calculated for 298.15 K and 323.15 K at 1 bar using molecular models from the literature. These dense and strongly interacting mixtures pose a significant challenge to existing methods for determining activity coefficients by molecular simulation. It is shown that the new method yields accurate results for the activity coefficients which are in agreement with results obtained with a thermodynamic integration technique. As the partial molar volumes are needed in the proposed method, the molar excess volume of the system water + methanol is also investigated.
Measurement and correlation of infinite dilution activity coefficients of alcohols in hexadecane and tetradecane; Hexadecane oyobi tetradecane chu no alcohol rui no mugen kishaku katsuryo keisu no sokutei narabini sokan

Energy Technology Data Exchange (ETDEWEB)

Fukuchi, K.; Miyoshi, K. [Ube National College of Technology, Yamaguchi (Japan)

1996-03-10

The infinite dilution activity coefficients of alcohols (methanol, ethanol, 1-propanol, 2-propano, 1-butanol, and 2-butanol) in heavy paraffinic hydrocarbons (hexadecane and tetradecane) were measured in the region 20-80{degree}C by a gas stripping method. The ASOG model was applied to calculate the infinite dilution activity coefficients. The infinite dilution activity coefficients can be correlated by adjusting the group interaction parameters between hydroxy and methyl groups. 8 refs., 3 figs., 4 tabs.
A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

Science.gov (United States)

Koo, Terry K; Li, Mae Y

2016-06-01

Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis. There are 10 forms of ICCs. Because each form involves distinct assumptions in their calculation and will lead to different interpretations, researchers should explicitly specify the ICC form they used in their calculation. A thorough review of the research design is needed in selecting the appropriate form of ICC to evaluate reliability. The best practice of reporting ICC should include software information, "model," "type," and "definition" selections. When coming across an article that includes ICC, readers should first check whether information about the ICC form has been reported and if an appropriate ICC form was used. Based on the 95% confident interval of the ICC estimate, values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9, and greater than 0.90 are indicative of poor, moderate, good, and excellent reliability, respectively. This article provides a practical guideline for clinical researchers to choose the correct form of ICC and suggests the best practice of reporting ICC parameters in scientific publications. This article also gives readers an appreciation for what to look for when coming across ICC while reading an article.
SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling

Science.gov (United States)

Luchko, Tyler; Blinov, Nikolay; Limon, Garrett C.; Joyce, Kevin P.; Kovalenko, Andriy

2016-11-01

Implicit solvent methods for classical molecular modeling are frequently used to provide fast, physics-based hydration free energies of macromolecules. Less commonly considered is the transferability of these methods to other solvents. The Statistical Assessment of Modeling of Proteins and Ligands 5 (SAMPL5) distribution coefficient dataset and the accompanying explicit solvent partition coefficient reference calculations provide a direct test of solvent model transferability. Here we use the 3D reference interaction site model (3D-RISM) statistical-mechanical solvation theory, with a well tested water model and a new united atom cyclohexane model, to calculate partition coefficients for the SAMPL5 dataset. The cyclohexane model performed well in training and testing (R=0.98 for amino acid neutral side chain analogues) but only if a parameterized solvation free energy correction was used. In contrast, the same protocol, using single solute conformations, performed poorly on the SAMPL5 dataset, obtaining R=0.73 compared to the reference partition coefficients, likely due to the much larger solute sizes. Including solute conformational sampling through molecular dynamics coupled with 3D-RISM (MD/3D-RISM) improved agreement with the reference calculation to R=0.93. Since our initial calculations only considered partition coefficients and not distribution coefficients, solute sampling provided little benefit comparing against experiment, where ionized and tautomer states are more important. Applying a simple pK_{ {a}} correction improved agreement with experiment from R=0.54 to R=0.66, despite a small number of outliers. Better agreement is possible by accounting for tautomers and improving the ionization correction.
SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling.

Science.gov (United States)

Luchko, Tyler; Blinov, Nikolay; Limon, Garrett C; Joyce, Kevin P; Kovalenko, Andriy

2016-11-01

Implicit solvent methods for classical molecular modeling are frequently used to provide fast, physics-based hydration free energies of macromolecules. Less commonly considered is the transferability of these methods to other solvents. The Statistical Assessment of Modeling of Proteins and Ligands 5 (SAMPL5) distribution coefficient dataset and the accompanying explicit solvent partition coefficient reference calculations provide a direct test of solvent model transferability. Here we use the 3D reference interaction site model (3D-RISM) statistical-mechanical solvation theory, with a well tested water model and a new united atom cyclohexane model, to calculate partition coefficients for the SAMPL5 dataset. The cyclohexane model performed well in training and testing ([Formula: see text] for amino acid neutral side chain analogues) but only if a parameterized solvation free energy correction was used. In contrast, the same protocol, using single solute conformations, performed poorly on the SAMPL5 dataset, obtaining [Formula: see text] compared to the reference partition coefficients, likely due to the much larger solute sizes. Including solute conformational sampling through molecular dynamics coupled with 3D-RISM (MD/3D-RISM) improved agreement with the reference calculation to [Formula: see text]. Since our initial calculations only considered partition coefficients and not distribution coefficients, solute sampling provided little benefit comparing against experiment, where ionized and tautomer states are more important. Applying a simple [Formula: see text] correction improved agreement with experiment from [Formula: see text] to [Formula: see text], despite a small number of outliers. Better agreement is possible by accounting for tautomers and improving the ionization correction.
[Characteristics of high resolution diffusion weighted imaging apparent diffusion coefficient histogram and its correlations with cancer stages in patients with nasopharyngeal carcinoma].

Science.gov (United States)

Wang, G J; Wang, Y; Ye, Y; Chen, F; Lu, Y T; Li, S L

2017-11-07

Objective: To investigate the features of apparent diffusion coefficient (ADC) histogram parameters based on entire tumor volume data in high resolution diffusion weighted imaging of nasopharyngeal carcinoma (NPC) and to evaluate its correlations with cancer stages. Methods: This retrospective study included 154 cases of NPC patients[102 males and 52 females, mean age (48±11) years]who had received readout segmentation of long variable echo trains of MRI scan before radiation therapy. The area of tumor was delineated on each section of axial ADC maps to generate ADC histogram by using Image J. ADC histogram of entire tumor along with the histogram parameters-the tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness and kurtosis were obtained by merging all sections with SPSS 22.0 software. Intra-observer repeatability was assessed by using intra-class correlation coefficients (ICC). The patients were subdivided into two groups according to cancer volume: small cancer group (histogram parameters and cancer stages was evaluated with Spearman test. Results: The ICC of measuring ADC histogram parameters of tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness, kurtosis was 0.938, 0.861, 0.885, 0.838, 0.836, 0.358 and 0.456, respectively. The tumor voxels was positively correlated with T staging ( r =0.368, P histogram (ADC(mean), ADC(25%), ADC(50%)) increases with T staging in NPC smaller than 2 cm(3).
Mutual diffusion coefficients of isopropanol + n-heptane and isobutanol + n-heptane

International Nuclear Information System (INIS)

He, Maogang; Peng, Sanguo; Zhang, Ying; Zhang, Shi; Liu, Xiangyang

2016-01-01

Graphical abstract: Mutual diffusion coefficients of isopropanol + n-heptane as a function of mass fraction of isopropanol. - Highlights: • D_1_2 of isopropanol + n-heptane and isobutanol + n-heptane were measured. • Effect of T, w and M of the solute on D_1_2 were analyzed. • A new correlation is proposed for the experimental data. - Abstract: The mutual diffusion coefficients of isopropanol + n-heptane and isobutanol + n-heptane were measured at different concentrations and in the temperature range from (283.15 to 323.15) K. The measurements were carried out using a digital holographic interferometry system. For all the mixtures investigated, the mutual diffusion coefficient increases as the temperature increases. At the same concentration and temperature, the mutual diffusion coefficients of isobutanol + n-heptane were lower than those of isopropanol + n-heptane due to the fact that the molecular weight of isobutanol is larger than that of isopropanol. A new correlation is proposed for the mutual diffusion coefficients of isopropanol + n-heptane and isobutanol + n-heptane. The absolute average relative deviation between the correlation and experiment is less than 1.90%.
Nonlinear parabolic equations with blowing-up coefficients with respect to the unknown and with soft measure data

Directory of Open Access Journals (Sweden)

Khaled Zaki

2016-12-01

Full Text Available We establish the existence of solutions for the nonlinear parabolic problem with Dirichlet homogeneous boundary conditions, $$ \\frac{\\partial u}{\\partial t} - \\sum_{i=1}^N\\frac{\\partial}{\\partial x_i} \\Big( d_i(u\\frac{\\partial u}{\\partial x_i} \\Big =\\mu,\\quad u(t=0=u_0, $$ in a bounded domain. The coefficients $d_i(s$ are continuous on an interval $]-\\infty,m[$, there exists an index p such that $d_p(u$ blows up at a finite value m of the unknown u, and $\\mu$ is a diffuse measure.
Correlation between apparent diffusion coefficient value on diffusion-weighted MR imaging and Gleason score in prostate cancer.

Science.gov (United States)

Wu, X; Reinikainen, P; Vanhanen, A; Kapanen, M; Vierikko, T; Ryymin, P; Hyödynmaa, S; Kellokumpu-Lehtinen, P-L

2017-01-01

To investigate whether diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) correlates with prostate cancer aggressiveness and further to compare the diagnostic performance of ADC and normalized ADC (nADC: normalized to non-tumor tissue). Thirty pre-treatment patients (mean age, 69years; range: 59-78years) with prostate cancer underwent magnetic resonance imaging (MRI) examination, including DWI with three b values: 50, 400, and 800s/mm 2 . Both ADC and nADC were correlated with the Gleason score obtained through transrectal ultrasound-guided biopsy. The tumor minimum ADC (ADC min : the lowest ADC value within tumor) had an inverse correlation with the Gleason score (r=-0.43, Pcorrelated with the Gleason score (r=-0.52 and r=-0.55, P<0.01; respectively), and they were lower in patients with Gleason score 3+4 than those with Gleason score 3+3 (P<0.01; respectively). Receiver operating characteristic (ROC) analysis showed that the area under the ROC curve was 0.765, 0.818, or 0.833 for the ADC min , nADC min , or nADC mean ; respectively, in differentiating between Gleason score 3+4 and 3+3 tumors. Tumor ADC min , nADC min , and nADC mean are useful markers to predict the aggressiveness of prostate cancer. Copyright © 2016 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.
Partial removal of correlated noise in thermal imagery

International Nuclear Information System (INIS)

Borel, C.C.; Cooke, B.J.; Laubscher, B.E.

1996-01-01

Correlated noise occurs in many imaging systems such as scanners and push-broom imagers. The sources of correlated noise can be from the detectors, pre-amplifiers and sampling circuits. Correlated noise appears as streaking along the scan direction of a scanner or in the along track direction of a push-broom imager. We have developed algorithms to simulate correlated noise and pre-filter to reduce the amount of streaking while not destroying the scene content. The pre- filter in the Fourier domain consists of the product of two filters. One filter models the correlated noise spectrum, the other is a windowing function e.g. Gaussian or Hanning window with variable width to block high frequency noise away from the origin of the Fourier Transform of the image data. We have optimized the filter parameters for various scenes and find improvements of the RMS error of the original minus the pre-filtered noisy image
Estimation of rank correlation for clustered data.

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Rosner, Bernard; Glynn, Robert J

2017-06-30

It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Partial discharge signal denoising with spatially adaptive wavelet thresholding and support vector machines

Energy Technology Data Exchange (ETDEWEB)

Mota, Hilton de Oliveira; Rocha, Leonardo Chaves Dutra da [Department of Computer Science, Federal University of Sao Joao del-Rei, Visconde do Rio Branco Ave., Colonia do Bengo, Sao Joao del-Rei, MG, 36301-360 (Brazil); Salles, Thiago Cunha de Moura [Department of Computer Science, Federal University of Minas Gerais, 6627 Antonio Carlos Ave., Pampulha, Belo Horizonte, MG, 31270-901 (Brazil); Vasconcelos, Flavio Henrique [Department of Electrical Engineering, Federal University of Minas Gerais, 6627 Antonio Carlos Ave., Pampulha, Belo Horizonte, MG, 31270-901 (Brazil)

2011-02-15

In this paper an improved method to denoise partial discharge (PD) signals is presented. The method is based on the wavelet transform (WT) and support vector machines (SVM) and is distinct from other WT-based denoising strategies in the sense that it exploits the high spatial correlations presented by PD wavelet decompositions as a way to identify and select the relevant coefficients. PD spatial correlations are characterized by WT modulus maxima propagation along decomposition levels (scales), which are a strong indicative of the their time-of-occurrence. Denoising is performed by identification and separation of PD-related maxima lines by an SVM pattern classifier. The results obtained confirm that this method has superior denoising capabilities when compared to other WT-based methods found in the literature for the processing of Gaussian and discrete spectral interferences. Moreover, its greatest advantages become clear when the interference has a pulsating or localized shape, situation in which traditional methods usually fail. (author)
Search for a nonzero triple-correlation coefficient and new experimental limit on T invariance in polarized-neutron beta decay

International Nuclear Information System (INIS)

Steinberg, R.I.; Liaud, P.; Vignon, B.; Hughes, V.W.

1976-01-01

A detailed description of an experimental test of time-reversal invariance in the β decay of the polarized free neutron is presented. The experiment consists of a measurement of the triple-correlation coefficient D between the neutron polarization vector and the electron and antineutrino momentum vectors. A nonzero value for this coefficient would imply T violation, since final-state interactions and other corrections may be neglected at the present level of precision. The experiment was performed using a cold-neutron beam at the High Flux Reactor of the Institut Laue-Langevin, Grenoble. A polarizing neutron guide tube yielded a beam intensity of 10 9 neutrons/sec with a polarization of 70%. Our result, based upon observation of approximately 6 x 10 6 decays, is D = (-1.1 +- 1.7) x 10 -3 , consistent with time-reversal invariance in the ΔS = 0 weak interaction. In terms of the relative phase angle between axial-vector and vector coupling constants, the result may be expressed as phi = 180.14 +- 0.22 0
Dense fluid self-diffusion coefficient calculations using perturbation theory and molecular dynamics

Directory of Open Access Journals (Sweden)

COELHO L. A. F.

1999-01-01

Full Text Available A procedure to correlate self-diffusion coefficients in dense fluids by using the perturbation theory (WCA coupled with the smooth-hard-sphere theory is presented and tested against molecular simulations and experimental data. This simple algebraic expression correlates well the self-diffusion coefficients of carbon dioxide, ethane, propane, ethylene, and sulfur hexafluoride. We have also performed canonical ensemble molecular dynamics simulations by using the Hoover-Nosé thermostat and the mean-square displacement formula to compute self-diffusion coefficients for the reference WCA intermolecular potential. The good agreement obtained from both methods, when compared with experimental data, suggests that the smooth-effective-sphere theory is a useful procedure to correlate diffusivity of pure substances.
Comparison of Treatment Outcomes in Partially Edentulous Patients with Implant-Supported Fixed Prostheses and Removable Partial Dentures.

Science.gov (United States)

Nogawa, Toshifumi; Takayama, Yoshiyuki; Ishida, Keita; Yokoyama, Atsuro

The aim of this study was to compare masticatory performance, occlusal force, and oral health-related quality of life (OHRQoL) in patients with mandibular distal-extension edentulism between those with implant-supported fixed prostheses (ISFPs) and those with removable partial dentures (RPDs), and to evaluate relationships among them. Subjects were recruited from patients using ISFPs or RPDs for mandibular distal-extension edentulism. Masticatory performance was evaluated based on the glucose extracted from chewed gummy jelly. Occlusal force was measured with a pressure-sensitive sheet, and data were subjected to computer analysis. The Japanese version of the Oral Health Impact Profile (OHIP-J) was used to evaluate OHRQoL. The masticatory performance, occlusal force, and OHIP-J scores of the ISFP and RPD groups were compared using the Wilcoxon rank-sum test. The relationships among the variables were analyzed using the Spearman rank correlation coefficient test. Multivariate logistic regression analysis was employed with the OHIP-J score as a dependent variable. Nineteen patients with ISFPs and 25 patients with RPDs participated in this study. No significant difference was observed between the two groups with regard to masticatory performance and occlusal force. The OHIP-J score was significantly lower in the ISFP group than in the RPD group. The OHIP-J score had no significant correlation with masticatory performance, but was significantly correlated with occlusal force and the prosthetic method. Multivariate logistic regression analysis showed that younger age, RPDs, and lower occlusal force were significantly associated with a higher OHIP-J summary score. The present results suggest that the difference in masticatory performance and occlusal force between ISFPs and RPDs is small, but ISFPs are superior to RPDs with regard to OHRQoL in patients with mandibular distal-extension edentulism. In addition, there appears to be a slight correlation between the OHIP
Discharge coefficient correlations for circular-arc venturi flowmeters at critical /sonic/ flow

Science.gov (United States)

Arnberg, B. T.; Britton, C. L.; Seidl, W. F.

1973-01-01

Experimental data are analyzed to support theoretical predictions for discharge coefficients in circular-arc venturi flow meters operating in the critical sonic flow regime at throat Reynolds numbers above 150 thousand. The data tend to verify the predicted 0.25% decrease in the discharge coefficient during transition from a laminar to turbulent boundary layer. Four different test gases and three flow measurement facilities were used in the experiments with 17 venturis with throat sizes from 0.15 to 1.37 in. and Beta ratios ranging from 0.014 to 0.25. Recommendations are given as to how the effectiveness of future studies in the field could be improved.
OUTLIER DETECTION IN PARTIAL ERRORS-IN-VARIABLES MODEL

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JUN ZHAO

Full Text Available The weighed total least square (WTLS estimate is very sensitive to the outliers in the partial EIV model. A new procedure for detecting outliers based on the data-snooping is presented in this paper. Firstly, a two-step iterated method of computing the WTLS estimates for the partial EIV model based on the standard LS theory is proposed. Secondly, the corresponding w-test statistics are constructed to detect outliers while the observations and coefficient matrix are contaminated with outliers, and a specific algorithm for detecting outliers is suggested. When the variance factor is unknown, it may be estimated by the least median squares (LMS method. At last, the simulated data and real data about two-dimensional affine transformation are analyzed. The numerical results show that the new test procedure is able to judge that the outliers locate in x component, y component or both components in coordinates while the observations and coefficient matrix are contaminated with outliers

Measurement of the electron antineutrino angular correlation coefficient a with the neutron decay spectrometer aSPECT

International Nuclear Information System (INIS)

Simson, Martin

2010-01-01

This thesis describes measurements with the retardation spectrometer aSPECT at the Institut Laue-Langevin in Grenoble. The goal of the measurement is to determine the angular correlation coefficient a from the form of the proton recoil spectrum in the decay of the free neutron in order to determine a precise value for the ratio of the weak axial vector and vector coupling constants of the nucleon. A big improvement was achieved with the use of a silicon drift detector which was used here for the first time to detect low energetic protons. A saturation effect of the electronics that was only discovered during the analysis of the data from neutron decay proved to be not correctable. The findings from analysis, simulations and test experiments gained in this work should allow a measurement of a with high precision in a future beamtime. (orig.)
Measurement of the electron antineutrino angular correlation coefficient a with the neutron decay spectrometer aSPECT

Energy Technology Data Exchange (ETDEWEB)

Simson, Martin

2010-09-21

This thesis describes measurements with the retardation spectrometer aSPECT at the Institut Laue-Langevin in Grenoble. The goal of the measurement is to determine the angular correlation coefficient a from the form of the proton recoil spectrum in the decay of the free neutron in order to determine a precise value for the ratio of the weak axial vector and vector coupling constants of the nucleon. A big improvement was achieved with the use of a silicon drift detector which was used here for the first time to detect low energetic protons. A saturation effect of the electronics that was only discovered during the analysis of the data from neutron decay proved to be not correctable. The findings from analysis, simulations and test experiments gained in this work should allow a measurement of a with high precision in a future beamtime. (orig.)
Complex versus Simple Modeling for DIF Detection: When the Intraclass Correlation Coefficient (?) of the Studied Item Is Less Than the ? of the Total Score

Science.gov (United States)

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

2014-01-01

Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (?) of the studied item was the same as the ? of the total score. The current study extended…
Distance correlation methods for discovering associations in large astrophysical databases

International Nuclear Information System (INIS)

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P.

2014-01-01

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, 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.
High expression of Rac1 is correlated with partial reversed cell polarity and poor prognosis in invasive ductal carcinoma of the breast.

Science.gov (United States)

Liu, Bingbing; Xiong, Jianhua; Liu, Guiqiu; Wu, Jing; Wen, Likun; Zhang, Qin; Zhang, Chuanshan

2017-07-01

The change of cell polarity is usually associated with invasion and metastasis. Partial reverse cell polarity in IDC-NOS may play a role in lymphatic tumor spread. Rac1 is a kind of polarity related protein. It plays an important role in invasion and metastasis in tumors. We here investigated the expression of Rac1 and partial reverse cell polarity status in breast cancer and evaluated their value for prognosis in breast cancer. The association of the expression of Rac1 and MUC-1 with clinicopathological parameters and prognostic significance was evaluated in 162 cases of IDC-NOS paraffin-embedded tissues by immunohistochemical method. The Rac1 messenger RNA expression was measured by real-time polymerase chain reaction in 30 breast cancer patients, which was divided into two groups of partial reverse cell polarity and no partial reverse cell polarity. We found that lymph node metastasis of partial reverse cell polarity patients was higher than no partial reverse cell polarity patients (Z = -4.030, p = 0.000). Rac1 was upregulated in partial reverse cell polarity group than no partial reverse cell polarity group (Z = -3.164, p = 0.002), and there was correlationship between the expression of Rac1 and partial reverse cell polarity status (r s = 0.249, p = 0.001). The level of Rac1 messenger RNA expression in partial reverse cell polarity group was significantly higher compared to no partial reverse cell polarity group (t = -2.527, p = 0.017). Overexpression of Rac1 and partial reverse cell polarity correlates with poor prognosis of IDC-NOS patients (p = 0.011). Partial reverse cell polarity and lymph node metastasis remained as independent predictors for poor disease-free survival of IDC-NOS (p = 0.023, p = 0.046). Our study suggests that partial reverse cell polarity may lead to poor prognosis of breast cancer. Overexpression of Rac1 may lead to polarity change in IDC-NOS of the breast. Therefore, Rac1 could be a
Non-Markovian dynamics of quantum systems: formalism, transport coefficients

International Nuclear Information System (INIS)

Kanokov, Z.; Palchikov, Yu.V.; Antonenko, N.V.; Adamian, G.G.; Kanokov, Z.; Adamian, G.G.; Scheid, W.

2004-01-01

Full text: The generalized Linbland equations with non-stationary transport coefficients are derived from the Langevin equations for the case of nonlinear non-Markovian noise [1]. The equations of motion for the collective coordinates are consistent with the generalized quantum fluctuation dissipation relations. The microscopic justification of the Linbland axiomatic approach is performed. Explicit expressions for the time-dependent transport coefficients are presented for the case of FC- and RWA-oscillators and a general linear coupling in coordinate and in momentum between the collective subsystem and heat bath. The explicit equations for the correlation functions show that the Onsanger's regression hypothesis does not hold exactly for the non-Markovian equations of motion. However, under some conditions the regression of fluctuations goes to zero in the same manner as the average values. In the low and high temperature regimes we found that the dissipation leads to long-time tails in correlation functions in the RWA-oscillator. In the case of the FC-oscillator a non-exponential power-like decay of the correlation function in coordinate is only obtained only at the low temperature limit. The calculated results depend rather weakly on the memory time in many applications. The found transient times for diffusion coefficients D pp (t), D qp (t) and D qq (t) are quite short. The value of classical diffusion coefficients in momentum underestimates the asymptotic value of quantum one D pp (t), but the asymptotic values of classical σ qq c and quantum σ qq second moments are close due to the negativity of quantum mixed diffusion coefficient D qp (t)
Correlation between apparent diffusion coefficients and standardized uptake values in hybrid {sup 18}F-FDG PET/MR: Preliminary results in rectal cancer

Energy Technology Data Exchange (ETDEWEB)

Jeong, Ju Hye [Dept. of Nuclear Medicine, Kyungpook National University Hospital, Daegu (Korea, Republic of); Cho, Ihn Ho; Chun, Kyung Ah; Kong, Eun Jung; Kwon, Sang Don; Kim, Jae Hwang [Yeungnam University Hospital, Daegu (Korea, Republic of)

2016-06-15

Fluorine-18-fluorodeoxyglucose ({sup 18}F-FDG) positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DWI) share the same role in clinical oncology and it is feasible to obtain the standardized uptake value (SUV) and apparent diffusion coefficient (ADC) simultaneously by emerging the hybrid positron emission tomography/magnetic resonance (PET/MR). This study investigated the correlation between the ADCs of rectal cancer lesions and their SUVs derived from hybrid PET/MR. Nine patients with histologically proven rectal adenocarcinoma (5 men, 4 women; mean age, 70 ± 15.91 years) underwent torso {sup 18}F-FDG PET/CT and regional hybrid {sup 18}F-FDG PET/MR sequentially. A fixed threshold value of 40 % of maximum uptake was used to determine tumor volume of interest (VOI) on PET image; SUV{sub max}, SUV{sub peak}, and SUV{sub mean} were calculated automatically. A single freehand region of interest (ROI) was drawn on high b-value (b1000) DWI image and copied to corresponding ADC map to determine the ADCmean of rectal cancer lesion. Spearman'rank correlation coefficient (ρ) was calculated to determine the correlation between SUVs and ADC values. SUV{sub max}, SUV{sub peak}, and SUV{sub mean} derived by hybrid PET/MR were 12.35 ± 4.66 (mean ± standard deviation), 9.66 ± 3.15 and 7.41 ± 2.54, respectively. The ADCmean value of rectal cancer lesions was 1.02 ± 0.08 × 10{sup -3}mm{sup 2}/s. ADCmean was significantly and inversely correlated with SUV values (SUV{sub max}, ρ = -0.95, p < 0.001; SUV{sub peak}, ρ = -0.93, p < 0.001; SUV{sub mean}, ρ = -0.91, p = 0.001). This preliminary hybrid PET/MR study demonstrates a significant inverse correlation exists between metabolic activity on {sup 18}F-FDG PET and water diffusion on DWI in rectal cancer.
Cross correlation coefficients of turbulent boundary layer with micro-bubble injection

Energy Technology Data Exchange (ETDEWEB)

Claudia del Carmen Gutierrez-Torres [LABINTHAP-SEPI-ESIME, Instituto Politecnico Nacional, U.P. Adolfo Lopez Mateos Edif. 5 3er. Piso, Col Lindavista, C.P. 07738, Mexico, D. F. (Mexico); Yassin A Hassan; Jose Alfredo Jimenez-Bernal [Texas A and M University, College Station, Tx. 77843-3133 (United States)

2005-07-01

Full text of publication follows: Injection of micro-bubbles within the turbulent boundary layer has been investigated for a several years as a method to achieve drag reduction. However, the physical mechanism of this phenomenon is not fully understood yet. Experiments in a channel flow for single phase (water) and two phase (water and micro-bubbles) flows under different void fraction conditions are reported for a Reynolds number of 5128. Particle Image Velocimetry technique is used to measure instantaneous velocity fields. Consequently the cross-correlation coefficient Ruv can be calculated along the stream-wise direction for various different y{sup +} positions and along the normal direction for the fluctuating components of the velocity obtained from the instantaneous velocity fields. The experiments were carried out in a rectangular acrylic channel, whose dimensions are 4.8 m length, 20.6 cm wide and 5.6 cm height. Water was driven trough the channel by gravity from a tank, which was located 3 m above the channel. Then, water was conducted to a lower tank; from which water was pumped to the upper thank forming a closed loop. Upper tank's water level was kept constant through the tests to ensure constant flow rate trough the channel. The velocity field in the x-y plane was obtained by particle image velocimetry (PIV) at 3.15 m downstream from the channel inlet. A Nd:YAG laser with a wavelength of 532 nm (green light) and power of 350 mJ per pulse is utilized. The particles used for seeding have a diameter that goes from 6-9 {mu}m with a specific gravity almost identical to water s specific gravity. The laser light scattered from the seeding particles was recorded using a CCD Kodak Megaplus camera, Model ES 1.0, 1008 x 1018 pixels. The viewing area was 1.28 cm{sup 2} and was located close to the channel wall. The system recorded 30 velocity fields per second. Each velocity field was obtained from a pair of consecutive images capturing the second image of
Cross correlation coefficients of turbulent boundary layer with micro-bubble injection

International Nuclear Information System (INIS)

Claudia del Carmen Gutierrez-Torres; Yassin A Hassan; Jose Alfredo Jimenez-Bernal

2005-01-01

Full text of publication follows: Injection of micro-bubbles within the turbulent boundary layer has been investigated for a several years as a method to achieve drag reduction. However, the physical mechanism of this phenomenon is not fully understood yet. Experiments in a channel flow for single phase (water) and two phase (water and micro-bubbles) flows under different void fraction conditions are reported for a Reynolds number of 5128. Particle Image Velocimetry technique is used to measure instantaneous velocity fields. Consequently the cross-correlation coefficient Ruv can be calculated along the stream-wise direction for various different y + positions and along the normal direction for the fluctuating components of the velocity obtained from the instantaneous velocity fields. The experiments were carried out in a rectangular acrylic channel, whose dimensions are 4.8 m length, 20.6 cm wide and 5.6 cm height. Water was driven trough the channel by gravity from a tank, which was located 3 m above the channel. Then, water was conducted to a lower tank; from which water was pumped to the upper thank forming a closed loop. Upper tank's water level was kept constant through the tests to ensure constant flow rate trough the channel. The velocity field in the x-y plane was obtained by particle image velocimetry (PIV) at 3.15 m downstream from the channel inlet. A Nd:YAG laser with a wavelength of 532 nm (green light) and power of 350 mJ per pulse is utilized. The particles used for seeding have a diameter that goes from 6-9 μm with a specific gravity almost identical to water s specific gravity. The laser light scattered from the seeding particles was recorded using a CCD Kodak Megaplus camera, Model ES 1.0, 1008 x 1018 pixels. The viewing area was 1.28 cm 2 and was located close to the channel wall. The system recorded 30 velocity fields per second. Each velocity field was obtained from a pair of consecutive images capturing the second image of the pair 1 ms after
A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2015-05-07

Previous studies have confirmed the adverse impact of fading correlation on the mutual information (MI) of two-dimensional (2D) multiple-input multiple-output (MIMO) systems. More recently, the trend is to enhance the system performance by exploiting the channel’s degrees of freedom in the elevation, which necessitates the derivation and characterization of three-dimensional (3D) channels in the presence of spatial correlation. In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for 3D MIMO channels. This novel SCF is developed for a uniform linear array of antennas with nonisotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. The resulting expression depends on the underlying arbitrary angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. The developed SCF determines the covariance matrices at the transmitter and the receiver that form the Kronecker channel model. In order to quantify the effects of correlation on the system performance, the information-theoretic deterministic equivalents of the MI for the Kronecker model are utilized in both mono-user and multi-user cases. Numerical results validate the proposed analytical expressions and elucidate the dependence of the system performance on azimuth and elevation angular spreads and antenna patterns. Some useful insights into the behaviour of MI as a function of downtilt angles are provided. The derived model will help evaluate the performance of correlated 3D MIMO channels in the future.
Spectral and partial-wave decomposition of time-dependent wave functions on a grid: Photoelectron spectra of H and H2+ in electromagnetic fields

International Nuclear Information System (INIS)

Nikolopoulos, L. A. A.; Kjeldsen, T. K.; Madsen, L. B.

2007-01-01

We present a method for spectral (bound and continuum) and partial-wave analysis of a three-dimensional time-dependent wave function, defined on a grid, without projecting onto the field-free eigenstates of the system. The method consists of propagating the time-dependent Schroedinger equation to obtain its autocorrelation function C(t)= after the end of the interaction, at time T, of the system with an external time-dependent field. The Fourier spectrum of this correlation function is directly related to the expansion coefficients of the wave function on the field-free bound and continuum energy eigenstates of the system. By expanding on a spherical harmonics basis we show how to calculate the contribution of the various partial waves to the total photoelectron energy spectrum
Decreased apparent diffusion coefficient in the pituitary and correlation with hypopituitarism in patients with traumatic brain injury.

Science.gov (United States)

Zheng, Ping; He, Bin; Guo, Yijun; Zeng, Jingsong; Tong, Wusong

2015-07-01

The relationship between microstructural abnormality in patients with traumatic brain injury (TBI) and hormone-secreting status remains unknown. In this study, the authors aimed to identify the role of the apparent diffusion coefficient (ADC) using a diffusion-weighted imaging (DWI) technique and to evaluate the association of such changes with hypopituitarism in patients with TBI. Diffusion-weighted images were obtained in 164 consecutive patients with TBI within 2 weeks after injury to generate the pituitary ADC as a measure of microstructural change. Patients with TBI were further grouped into those with and those without hypopituitarism based on the secretion status of pituitary hormones at 6 months postinjury. Thirty healthy individuals were enrolled in the study and underwent MRI examinations for comparison. Mean ADC values were compared between this control group, the patients with TBI and hypopituitarism, and the patients with TBI without hypopituitarism; correlational studies were also performed. Neurological outcome was assessed with the Glasgow Outcome Scale (GOS) for all TBI patients 6 months postinjury. In the TBI group, 84 patients had hypopituitarism and 80 had normal pituitary function. The pituitary ADC in TBI patients was significantly less than that in controls (1.83 ± 0.16 vs 4.13 ± 0.33, p correlated with neurological outcome at 6 months following TBI (r = 0.602, p correlated with hormone-secreting status in TBI patients. The authors suggest that pituitary ADC may be a useful biomarker to predict pituitary function in patients with TBI.
Tantrums, Emotion Reactions and Their EEG Correlates in Childhood Benign Rolandic Epilepsy vs. Complex Partial Seizures: Exploratory Observations.

Science.gov (United States)

Potegal, Michael; Drewel, Elena H; MacDonald, John T

2018-01-01

We explored associations between EEG pathophysiology and emotional/behavioral (E/B) problems of children with two types of epilepsy using standard parent questionnaires and two new indicators: tantrums recorded by parents at home and brief, emotion-eliciting situations in the laboratory. Children with Benign Rolandic epilepsy (BRE, N = 6) reportedly had shorter, more angry tantrums from which they recovered quickly. Children with Complex Partial Seizures (CPS, N = 13) had longer, sadder tantrums often followed by bad moods. More generally, BRE correlated with anger and aggression; CPS with sadness and withdrawal. Scores of a composite group of siblings ( N = 11) were generally intermediate between the BRE and CPS groups. Across all children, high voltage theta and/or interictal epileptiform discharges (IEDs) correlated with negative emotional reactions. Such EEG abnormalities in left hemisphere correlated with greater social fear, right hemisphere EEG abnormalities with greater anger. Right hemisphere localization in CPS was also associated with parent-reported problems at home. If epilepsy alters neural circuitry thereby increasing negative emotions, additional assessment of anti-epileptic drug treatment of epilepsy-related E/B problems would be warranted.
What to Do With "Moderate" Reliability and Validity Coefficients?

NARCIS (Netherlands)

Post, Marcel W

Clinimetric studies may use criteria for test-retest reliability and convergent validity such that correlation coefficients as low as .40 are supportive of reliability and validity. It can be argued that moderate (.40-.60) correlations should not be interpreted in this way and that reliability
A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data.

Science.gov (United States)

Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G; Gu, C Charles

2014-11-01

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of custom correlation coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (six genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets. © 2014 WILEY PERIODICALS, INC.
Partial resistance of carrot to Alternaria dauci correlates with in vitro cultured carrot cell resistance to fungal exudates.

Directory of Open Access Journals (Sweden)

Mickaël Lecomte

Full Text Available Although different mechanisms have been proposed in the recent years, plant pathogen partial resistance is still poorly understood. Components of the chemical warfare, including the production of plant defense compounds and plant resistance to pathogen-produced toxins, are likely to play a role. Toxins are indeed recognized as important determinants of pathogenicity in necrotrophic fungi. Partial resistance based on quantitative resistance loci and linked to a pathogen-produced toxin has never been fully described. We tested this hypothesis using the Alternaria dauci-carrot pathosystem. Alternaria dauci, causing carrot leaf blight, is a necrotrophic fungus known to produce zinniol, a compound described as a non-host selective toxin. Embryogenic cellular cultures from carrot genotypes varying in resistance against A. dauci were confronted with zinniol at different concentrations or to fungal exudates (raw, organic or aqueous extracts. The plant response was analyzed through the measurement of cytoplasmic esterase activity, as a marker of cell viability, and the differentiation of somatic embryos in cellular cultures. A differential response to toxicity was demonstrated between susceptible and partially resistant genotypes, with a good correlation noted between the resistance to the fungus at the whole plant level and resistance at the cellular level to fungal exudates from raw and organic extracts. No toxic reaction of embryogenic cultures was observed after treatment with the aqueous extract or zinniol used at physiological concentration. Moreover, we did not detect zinniol in toxic fungal extracts by UHPLC analysis. These results suggest that strong phytotoxic compounds are present in the organic extract and remain to be characterized. Our results clearly show that carrot tolerance to A. dauci toxins is one component of its partial resistance.
Effect of design and operation parameters on heat transfer coefficient in condensers

International Nuclear Information System (INIS)

Eskin, N.; Arslan, G.; Balci, T.

2009-01-01

Accurate and optimum usage of energy sources is gaining importance all over the world due to the increase of energy need and limited energy sources. Increasing condenser efficiency, reduce both the dimensions and the material usage and also the investment cost of the devices. This can be maintained by increasing the heat transfer coefficient in condensers. Generally, tubes having plain inner surfaces are mounted horizontally in serpentine type condenser applications and due to the performance loss results from the congestion in serpentine connections, vertical tube mounting is not preferred. Due to the complexity of the two-phase flow, a single set of correlation for heat transfer cannot be used. Average and local heat transfer coefficient for condensers are determined. Moreover, for each experiments flow pattern is determined and the validity of the correlations are compared according to that flow pattern. In Table 2, some of the experiments for R134a are listed. Local heat transfer coefficient is also important for condenser design. As a result, to design effective condensers the accuracy of the correlations is very important. When all the experiments are taken into account, it is seen that deviation of the correlations differs according to the refrigerant type, tube dimensions, mass flux, saturation temperature and flow pattern. For high mass flux (>400 kg/m 2 s) Traviss (1973) correlation failed. For small diameters (<3.14 mm) Tandon (1985) correlation estimate the heat transfer coefficient with a high deviation. Most accurate results are obtained for Akers et al. (1959), M.M. Shah (1978), Cavallini and Zecchlin (1974), J.R. Thome - J. El Hajal - A. Cavallini (2003) correlations. For high mass flux and annular flow, M.M. Shah (1978) correlation estimates the heat transfer coefficient with high precision. However, as the tube diameter decrease, this deviation increases. For small tube diameter such as 0.691 mm Cavallini and Zecchlin (1974) gives the most
A simple method for identifying parameter correlations in partially observed linear dynamic models.

Science.gov (United States)

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a
Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

Science.gov (United States)

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.
Simultaneous Description of Activity Coefficients and Solubility with eCPA

DEFF Research Database (Denmark)

Schlaikjer, Anders; Thomsen, Kaj; Kontogeorgis, Georgios

2017-01-01

with salt specific parameters. The focus is on accurate description of the salt solubility, and low deviation correlations are obtained for all salts investigated. The inclusion of the solubility data in the parametrization has, compared to parameters only parametrized to osmotic coefficients and activity...... coefficients, not significantly affected the deviations of the osmotic coefficients and activity coefficients. The average deviations of the activity coefficient does increase slightly and it was found that the increase in deviations was almost entirely due to reduced accuracy at high temperature and high...... molality. The model is, furthermore, compared to the activity coefficient model, Extended UNIQUAC. It is shown that the eCPA provides more accurate solubility description at higher temperatures than Extended UNIQUAC but also that Extended UNIQUAC is slightly better at describing the activity coefficients...

[Cytogenetic and molecular genetic diagnosis of a neonate with partial 13q trisomy and partial 5p monosomy].

Science.gov (United States)

Xiao, Wenjun; Gao, Zhenkui; Meng, Qian; Zhang, Man

2014-12-01

To diagnose a neonate presenting with multiple dysmorphic features, Cri-du-chat signs and hypoglycemia and to correlate the phenotype with the genotype. The patient was diagnosed with conventional cytogenetics and real-time fluorescence quantitative PCR (QF-PCR). The phenotype was then correlated with the genotype through a review of literature. The neonate was diagnosed with a partial 13q trisomy (q12 → qter) and partial 5p monosomy (p15 →pter). A rare diagnosis has been established with combined cytogenetic and molecular genetic techniques. QF-PCR has a broad application in genetic diagnosis.
Correlation of apparent diffusion coefficient ratio on 3.0 T MRI with prostate cancer Gleason score.

Science.gov (United States)

Jyoti, Rajeev; Jain, Tarun Pankaj; Haxhimolla, Hodo; Liddell, Heath; Barrett, Sean Edward

2018-01-01

The purpose was to investigate the usefulness of ADC ratio on Diffusion MRI to discriminate between benign and malignant lesions of Prostate. Images of patients who underwent in-gantry MRI guided prostate lesion biopsy were retrospectively analyzed. Prostate Cancers with 20% or more Gleason score (GS) pattern 3 + 3 = 6 in each core or any volume of higher Gleason score pattern were included. ADC ratio was calculated by two reviewers for each lesion. The ADC ratio was calculated for each lesion by dividing the lowest ADC value in a lesion and highest ADC value in normal prostate in peripheral zone (PZ). ADC ratio values were compared with the biopsy result. Data was analysed using independent samples T-test, Spearman correlation, intra-class correlation coefficient (ICC) and Receiver operating characteristic (ROC) curve. 45 lesions in 33 patients were analyzed. 12 lesions were in transitional zone (TZ) and 33 in perpheral zone PZ. All lesions demonstrated an ADC ratio of 0.45 or lower. GS demonstrated a negative correlation with both the ADC value and ADC ratio . However, ADC ratio (p correlation compared to ADC value alone (p = 0.014). There was no significant statistical difference between GS 3 + 4 and GS 4 + 3 mean ADC tumour value (p = 0.167). However when using ADC ratio , there was a significant difference (p = 0.032). ROC curve analysis demonstrated an area under the curve of 0.83 using ADC ratio and 0.76 when using ADC tumour value when discriminating Gleason 6 from Gleason ≥7 tumours. Inter-observer reliability in the calculation of ADC ratios was excellent, with ICC of 0.964. ADC ratio is a reliable and reproducible tool in quantification of diffusion restriction for clinically significant prostate cancer foci.
FDG-PET/CT and diffusion-weighted imaging for resected lung cancer: correlation of maximum standardized uptake value and apparent diffusion coefficient value with prognostic factors.

Science.gov (United States)

Usuda, Katsuo; Funasaki, Aika; Sekimura, Atsushi; Motono, Nozomu; Matoba, Munetaka; Doai, Mariko; Yamada, Sohsuke; Ueda, Yoshimichi; Uramoto, Hidetaka

2018-04-09

Diffusion-weighted magnetic resonance imaging (DWI) is useful for detecting malignant tumors and the assessment of lymph nodes, as FDG-PET/CT is. But it is not clear how DWI influences the prognosis of lung cancer patients. The focus of this study is to evaluate the correlations between maximum standardized uptake value (SUVmax) of FDG-PET/CT and apparent diffusion coefficient (ADC) value of DWI with known prognostic factors in resected lung cancer. A total of 227 patients with resected lung cancers were enrolled in this study. FEG-PET/CT and DWI were performed in each patient before surgery. There were 168 patients with adenocarcinoma, 44 patients with squamous cell carcinoma, and 15 patients with other cell types. SUVmax was a factor that was correlated to T factor, N factor, or cell differentiation. ADC of lung cancer was a factor that was not correlated to T factor, or N factor. There was a significantly weak inverse relationship between SUVmax and ADC (Correlation coefficient r = - 0.227). In analysis of survival, there were significant differences between the categories of sex, age, pT factor, pN factor, cell differentiation, cell type, and SUVmax. Univariate analysis revealed that SUVmax, pN factor, age, cell differentiation, cell type, sex, and pT factor were significant factors. Multivariate analysis revealed that SUVmax and pN factor were independent significant prognostic factors. SUVmax was a significant prognostic factor that is correlated to T factor, N factor, or cell differentiation, but ADC was not. SUVmax may be more useful for predicting the prognosis of lung cancer than ADC values.
Prediction of air-to-blood partition coefficients of volatile organic compounds using genetic algorithm and artificial neural network

International Nuclear Information System (INIS)

Konoz, Elahe; Golmohammadi, Hassan

2008-01-01

An artificial neural network (ANN) was constructed and trained for the prediction of air-to-blood partition coefficients of volatile organic compounds. The inputs of this neural network are theoretically derived descriptors that were chosen by genetic algorithm (GA) and multiple linear regression (MLR) features selection techniques. These descriptors are: R maximal autocorrelation of lag 1 weighted by atomic Sanderson electronegativities (R1E+), electron density on the most negative atom in molecule (EDNA), maximum partial charge for C atom (MXPCC), surface weighted charge partial surface area (WNSA1), fractional charge partial surface area (FNSA2) and atomic charge weighted partial positive surface area (PPSA3). The standard errors of training, test and validation sets for the ANN model are 0.095, 0.148 and 0.120, respectively. Result obtained showed that nonlinear model can simulate the relationship between structural descriptors and the partition coefficients of the molecules in data set accurately
Biostatistics Series Module 6: Correlation and Linear Regression.

Science.gov (United States)

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 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.
Diabetic Erythrocytes Test by Correlation Coefficient

Science.gov (United States)

Korol, A.M; Foresto, P; Darrigo, M; Rosso, O.A

2008-01-01

Even when a healthy individual is studied, his/her erythrocytes in capillaries continually change their shape in a synchronized erratic fashion. In this work, the problem of characterizing the cell behavior is studied from the perspective of bounded correlated random walk, based on the assumption that diffractometric data involves both deterministic and stochastic components. The photometric readings are obtained by ektacytometry over several millions of shear elongated cells, using a home-made device called Erythrodeformeter. We have only a scalar signal and no governing equations; therefore the complete behavior has to be reconstructed in an artificial phase space. To analyze dynamics we used the technique of time delay coordinates suggested by Takens, May algorithm, and Fourier transform. The results suggest that on random-walk approach the samples from healthy controls exhibit significant differences from those from diabetic patients and these could allow us to claim that we have linked mathematical nonlinear tools with clinical aspects of diabetic erythrocytes’ rheological properties. PMID:19415139
Experimental study on the minimum drag coefficient of supercritical pressure water in horizontal tubes

International Nuclear Information System (INIS)

Lei, Xianliang; Li, Huixiong; Guo, YuMeng; Zhang, Qing; Zhang, Weiqiang; Zhang, Qian

2016-01-01

Highlights: • The minimum drag coefficient phenomenon (MDC) has been observed and further investigated. • Effects of heat flux, mass flux and pressure to MDC have been discussed. • A series of comparisons between existing correlations and data have been conducted. • Two correlations of drag coefficient are proposed for isothermal and nonisothermal flow. - Abstract: Hydraulic resistance and its components are of great importance for understanding the turbulence nature of supercritical fluid and establishing prediction methods. Under supercritical pressures, the hydraulic resistance of the fluid exhibits a “pit” in the regions near its pseudo-critical point, which is hereafter called the minimum drag coefficient phenomenon. However, this special phenomenon was paid a little attention before. Hence systematical experiments have been carried out to investigate the hydraulic resistance of supercritical pressure water in both adiabatic and heated horizontal tubes. Parametric effects of heat flux, pressure and mass fluxes to drag coefficient are further compared. It is found that almost all of the existing correlations don’t agree well with the experimental data due to the insufficient consideration of thermal-properties near the pseudocritical point. Two correlations of the drag coefficients are finally proposed by introducing the new variable of the derivative of density with respect to temperature or Prandtl number, which can better predict the drag coefficient of isothermal and nonisothermal flow respectively.
Hepatic hemangioma: Correlation of enhancement types with diffusion-weighted MR findings and apparent diffusion coefficients

Energy Technology Data Exchange (ETDEWEB)

Goshima, Satoshi [Department of Radiology, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan)], E-mail: gossy@par.odn.ne.jp; Kanematsu, Masayuki [Department of Radiology, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan); Department of Radiology Services, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan); Kondo, Hiroshi [Department of Radiology, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan); Yokoyama, Ryujiro; Kajita, Kimihiro [Department of Radiology Services, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan); Tsuge, Yusuke [Department of Radiology, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194 (Japan); Shiratori, Yoshimune [Department of Medical Informatics, Gifu University School of Medicine, Gifu (Japan); Onozuka, Minoru [Department of Physiology and Neuroscience, Kanagawa Dental College, Yokosuka (Japan); Moriyama, Noriyuki [Research Center for Cancer Prevention and Screening, National Cancer Center Hospital, Tsukiji (Japan)

2009-05-15

Purpose: To correlate hepatic hemangioma enhancement types in gadolinium-enhanced magnetic resonance (MR) images with diffusion-weighted MR findings and apparent diffusion coefficients (ADCs). Materials and methods: Respiratory-triggered diffusion-weighted MR images (TR/TE, 2422/46 ms; parallel imaging factor, 2; b factor, 500 s/mm{sup 2}; number of averaging, 6) obtained in 35 patients with 44 hepatic hemangiomas diagnosed by gadolinium-enhanced MR and by follow-up imaging were retrospectively evaluated. Hemangiomas were classified into three enhancement types based on gadolinium-enhanced MR imaging findings: type I, early-enhancement type; type II, peripheral nodular enhancement type; type III, delayed enhancement type. Two blinded readers qualitatively assessed lesion sizes and signal intensities on T2-weighted turbo spin-echo and diffusion-weighted images. The ADCs of hemangiomas were also measured. Results: No significant difference was observed between the three enhancement types in terms of signal intensities on T2-weighted images. Signal intensities on diffusion-weighted images were lower in the order type I to III (P < .01), and mean ADCs were 2.18 x 10{sup -3}, 1.86 x 10{sup -3}, and 1.71 x 10{sup -3} mm{sup 2}/s for types I, II, and III, respectively (P < .01). No correlation was found between lesion sizes and ADCs. Conclusion: Hepatic hemangiomas were found to have enhancement type dependent signal intensities and ADCs on diffusion-weighted MR images. Further studies will have to substantiate that these diffusion patterns might reflect intratumoral blood flow or perfusion.
Prediction of beef marblingusing Hyperspectral Imaging (HSI and Partial Least Squares Regression (PLSR

Directory of Open Access Journals (Sweden)

Victor Aredo

2017-01-01

Full Text Available The aim of this study was to build a model to predict the beef marbling using HSI and Partial Least Squares Regression (PLSR. Totally 58 samples of longissmus dorsi muscle were scanned by a HSI system (400 - 1000 nm in reflectance mode, using 44 samples to build t he PLSR model and 14 samples to model validation. The Japanese Beef Marbling Standard (BMS was used as reference by 15 middle - trained judges for the samples evaluation. The scores were assigned as continuous values and varied from 1.2 to 5.3 BMS. The PLSR model showed a high correlation coefficient in the prediction (r = 0.95, a low Standard Error of Calibration (SEC of 0.2 BMS score, and a low Standard Error of Prediction (SEP of 0.3 BMS score.
Observability of discretized partial differential equations

Science.gov (United States)

Cohn, Stephen E.; Dee, Dick P.

1988-01-01

It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.
Electron scattering on N2O-from cross sections to diffusion coefficients

International Nuclear Information System (INIS)

Mechlinska-Drewko, J.; Wroblewski, T.; Petrovic, Z.L.; Novakovic, V.; Karwasz, G.P.

2003-01-01

Results of measurements of the ratio of transverse (D T /μ) and longitudinal (D L /μ) diffusion coefficients to mobility and drift velocity (W) as function of reduced electrical field (E/N) for electrons in nitrous oxide are presented. The coefficients D T /μ and D L /μ have been determined by applying the Townsend-Huxley method. The drift velocities were obtained by using the Bradbury-Nielsen technique. Also the deduced set of total and partial cross sections has been used to calculate the D T /μ and W
On new classes of solutions of nonlinear partial differential equations in the form of convergent special series

Science.gov (United States)

Filimonov, M. Yu.

2017-12-01

The method of special series with recursively calculated coefficients is used to solve nonlinear partial differential equations. The recurrence of finding the coefficients of the series is achieved due to a special choice of functions, in powers of which the solution is expanded in a series. We obtain a sequence of linear partial differential equations to find the coefficients of the series constructed. In many cases, one can deal with a sequence of linear ordinary differential equations. We construct classes of solutions in the form of convergent series for a certain class of nonlinear evolution equations. A new class of solutions of generalized Boussinesque equation with an arbitrary function in the form of a convergent series is constructed.
Determination of corneal elasticity coefficient using the ORA database.

Science.gov (United States)

Avetisov, Sergei E; Novikov, Ivan A; Bubnova, Irina A; Antonov, Alexei A; Siplivyi, Vladimir I

2010-07-01

To propose a new approach for the study of corneal biomechanics using the Reichert Ocular Response Analyzer (ORA) database, which is based on changes in velocity retardation in the central cornea at the peak of flattening. The ORA applanation curve was analyzed using a mathematical technique, which allowed calculation of the elasticity coefficient (Ke), which is primarily characteristic of the elastic properties of the cornea. Elasticity coefficient values were obtained in patients with presumably different biomechanical properties of the cornea: "normal" cornea (71 eyes, normal group), keratoconus (34 eyes, keratoconus group), LASIK (36 eyes, LASIK group), and glaucoma with elevated and compensated intraocular pressure (lOP) (38 eyes, glaucoma group). The mean Ke value in the normal group was 11.05 +/- 1.6, and the corneal thickness correlation coefficient r2 was 0.48. In the keratoconus group, the mean Ke value was 4.91 +/- 1.87 and the corneal thickness correlation coefficient r2 was 0.47. In the LASIK group, Ke and r2 were 5.99 +/- 1.18 and 0.39, respectively. In the glaucoma group, the same eyes that experienced a two-fold reduction in lOP developed a statistically significant reduction in the Ke (1.06 times lower), whereas their corneal hysteresis value increased 1.25 times. The elasticity coefficient calculated using the ORA applanation curve can be used in the evaluation of corneal biomechanical properties.
Dielectronic recombination rate coefficients of initially rubidium-like tungsten

International Nuclear Information System (INIS)

Wu, Z.; Zhang, Y.; Fu, Y.; Dong, C.; Surzhykov, A.; Fritzsche, S.

2015-01-01

Dielectric recombination (DR) is a dominant electron recombination process in plasmas. Tungsten ions are expected to be prominent impurities in fusion plasmas so the knowledge of DR rate coefficient of tungsten ions is important to model fusion plasmas. Ab initio calculations of DR rate coefficients of initially rubidium-like W 37+ ions have been performed for the electron temperatures from 1 eV to 5*10 4 eV, by using the Flexible Atomic Code based on the relativistic configuration-interaction method. Special attention has been paid to the partial contributions to total DR rate coefficients as associated with the excitation of individual subshells. A detailed comparison of the calculations shows that the excitation from 4p subshell dominates total DR rate coefficients followed by the excitations from 4s and 4d subshells, while the contribution of excitations from 3l (l = s, p, d) subshells becomes important only at high temperatures. Besides, it is found that the electron excitations associated with Δn = 0, 1 dominate at low-temperature plasmas, however, the excitations associated with Δn ≥ 2 become non-negligible at high-temperature ones
A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

KAUST Repository

Babuška, Ivo; Nobile, Fabio; Tempone, Raul

2010-01-01

This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables. The method consists of a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It treats easily a wide range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction of the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method. Finally, we include a section with developments posterior to the original publication of this work. There we review sparse grid stochastic collocation methods, which are effective collocation strategies for problems that depend on a moderately large number of random variables.
147 - 154 Genetic Variability, Heritability and Correlation Coefficient

African Journals Online (AJOL)

USER

twelve upland rice genotypes during 2013 main cropping season. ... spikelet per panicle, number of filled grains per panicle and biomass yield had a positive and significant correlation ... fertilizers were applied at the rate of 100 kg per hectare. ..... ultimate effect for selecting superior varieties (Ali et al., .... (Brassica napus L.).
Tantrums, Emotion Reactions and Their EEG Correlates in Childhood Benign Rolandic Epilepsy vs. Complex Partial Seizures: Exploratory Observations

Directory of Open Access Journals (Sweden)

Michael Potegal

2018-03-01

Full Text Available We explored associations between EEG pathophysiology and emotional/behavioral (E/B problems of children with two types of epilepsy using standard parent questionnaires and two new indicators: tantrums recorded by parents at home and brief, emotion-eliciting situations in the laboratory. Children with Benign Rolandic epilepsy (BRE, N = 6 reportedly had shorter, more angry tantrums from which they recovered quickly. Children with Complex Partial Seizures (CPS, N = 13 had longer, sadder tantrums often followed by bad moods. More generally, BRE correlated with anger and aggression; CPS with sadness and withdrawal. Scores of a composite group of siblings (N = 11 were generally intermediate between the BRE and CPS groups. Across all children, high voltage theta and/or interictal epileptiform discharges (IEDs correlated with negative emotional reactions. Such EEG abnormalities in left hemisphere correlated with greater social fear, right hemisphere EEG abnormalities with greater anger. Right hemisphere localization in CPS was also associated with parent-reported problems at home. If epilepsy alters neural circuitry thereby increasing negative emotions, additional assessment of anti-epileptic drug treatment of epilepsy-related E/B problems would be warranted.
Prediction of retention indices for frequently reported compounds of plant essential oils using multiple linear regression, partial least squares, and support vector machine.

Science.gov (United States)

Yan, Jun; Huang, Jian-Hua; He, Min; Lu, Hong-Bing; Yang, Rui; Kong, Bo; Xu, Qing-Song; Liang, Yi-Zeng

2013-08-01

Retention indices for frequently reported compounds of plant essential oils on three different stationary phases were investigated. Multivariate linear regression, partial least squares, and support vector machine combined with a new variable selection approach called random-frog recently proposed by our group, were employed to model quantitative structure-retention relationships. Internal and external validations were performed to ensure the stability and predictive ability. All the three methods could obtain an acceptable model, and the optimal results by support vector machine based on a small number of informative descriptors with the square of correlation coefficient for cross validation, values of 0.9726, 0.9759, and 0.9331 on the dimethylsilicone stationary phase, the dimethylsilicone phase with 5% phenyl groups, and the PEG stationary phase, respectively. The performances of two variable selection approaches, random-frog and genetic algorithm, are compared. The importance of the variables was found to be consistent when estimated from correlation coefficients in multivariate linear regression equations and selection probability in model spaces. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Evaluation of temperature coefficients of reactivity for 233U--thorium fueled HTGR lattices. Final report

International Nuclear Information System (INIS)

Newman, D.F.; Leonard, B.R. Jr.; Trapp, T.J.; Gore, B.F.; Kottwitz, D.A.; Thompson, J.K.; Purcell, W.L.; Stewart, K.B.

1977-05-01

A comparison of calculated and measured neutron multiplication factors as a function of temperature was made for three graphite-moderated lattices in the High Temperature Lattice Test Reactor (HTLTR) using 233 UO 2 --ThO 2 fuels in varying amounts and configurations. Correlation of neutronic analysis methods and cross section data with the experimental measurements forms the basis for assessing the accuracy of the methods and data and developing confidence in the ability to predict the temperature coefficient of reactivity for various High Temperature Gas-Cooled Reactor (HTGR) conditions in which 233 U and thorium are present in the fuel. The calculated values of k/sub infinity/(T) were correlated with measured values using two least-squares-fitted correlation coefficients: (1) a normalization factor, and (2) a temperature coefficient bias factor. These correlations indicate the existence of a negative (nonconservative) bias in temperature coefficients of reactivity calculated using ENDF/B-IV cross section data
The significance level and repeatability for isotope-temperature coefficient of precipitation in China

International Nuclear Information System (INIS)

Wang Dongsheng; Wang Jinglan

2003-01-01

The good linear relationship with significance level α = 0.01 exists between isotope in precipitation and surface air temperature with multi-year average in 32 stations of China, and the yearly δD-temperature coefficient = 3.1‰/1℃ and the yearly δ 18 O-temperature coefficient = 0.36‰/1℃, and its determination coefficient R 2 = 0.67 and 0.64 respectively. So the isotope-temperature coefficient with yearly average can serve as the temperature yearly measure. But the monthly average isotope-temperature coefficient in each station is variable according to both of space and time, and its repeatability is determined by the meteorological regimes. According to the monthly isotope-temperature coefficient (B) and the coefficient of determination (R 2 ) and its α, all of China can be zoned the following three belts: (1) In the North Belt, B>O, R 2 ≈ 0.3-0.65, α = 0.01, the relation between monthly isotope in precipitation and surface air temperature (RMIT) belongs to a direct correlation and is closer in 99% probability; (2) In the South Belt, Bcorrelation; (3) In the Middle Belt the RMIP is a non-correlation. The isotope-temperature coefficient with both of yearly average and monthly average and its statistical attribution is site-specific, it may be used to reconstruct past surface air temperatures or to diagnose regional climate models. (authors)

An approach for fixed coefficient RNS-based FIR filter

Science.gov (United States)

Srinivasa Reddy, Kotha; Sahoo, Subhendu Kumar

2017-08-01

In this work, an efficient new modular multiplication method for {2k-1, 2k, 2k+1-1} moduli set is proposed to implement a residue number system (RNS)-based fixed coefficient finite impulse response filter. The new multiplication approach reduces the number of partial products by using pre-loaded product block. The reduction in partial products with the proposed modular multiplication improves the clock frequency and reduces the area and power as compared with the conventional modular multiplication. Further, the present approach eliminates a binary number to residue number converter circuit, which is usually needed at the front end of RNS-based system. In this work, two fixed coefficient filter architectures with the new modular multiplication approach are proposed. The filters are implemented using Verilog hardware description language. The United Microelectronics Corporation 90 nm technology library has been used for synthesis and the results area, power and delay are obtained with the help of Cadence register transfer level compiler. The power delay product (PDP) is also considered for performance comparison among the proposed filters. One of the proposed architecture is found to improve PDP gain by 60.83% as compared with the filter implemented with conventional modular multiplier. The filters functionality is validated with the help of Altera DSP Builder.
Clinical application of calculated split renal volume using computed tomography-based renal volumetry after partial nephrectomy: Correlation with technetium-99m dimercaptosuccinic acid renal scan data.

Science.gov (United States)

Lee, Chan Ho; Park, Young Joo; Ku, Ja Yoon; Ha, Hong Koo

2017-06-01

To evaluate the clinical application of computed tomography-based measurement of renal cortical volume and split renal volume as a single tool to assess the anatomy and renal function in patients with renal tumors before and after partial nephrectomy, and to compare the findings with technetium-99m dimercaptosuccinic acid renal scan. The data of 51 patients with a unilateral renal tumor managed by partial nephrectomy were retrospectively analyzed. The renal cortical volume of tumor-bearing and contralateral kidneys was measured using ImageJ software. Split estimated glomerular filtration rate and split renal volume calculated using this renal cortical volume were compared with the split renal function measured with technetium-99m dimercaptosuccinic acid renal scan. A strong correlation between split renal function and split renal volume of the tumor-bearing kidney was observed before and after surgery (r = 0.89, P volumetry had a strong correlation with the split renal function measured using technetium-99m dimercaptosuccinic acid renal scan. Computed tomography-based split renal volume measurement before and after partial nephrectomy can be used as a single modality for anatomical and functional assessment of the tumor-bearing kidney. © 2017 The Japanese Urological Association.
Correlation model to analyze dependent failures for probabilistic risk assessment

International Nuclear Information System (INIS)

Dezfuli, H.

1985-01-01

A methodology is formulated to study the dependent (correlated) failures of various abnormal events in nuclear power plants. This methodology uses correlation analysis is a means for predicting and quantifying the dependent failures. Appropriate techniques are also developed to incorporate the dependent failure in quantifying fault trees and accident sequences. The uncertainty associated with each estimation in all of the developed techniques is addressed and quantified. To identify the relative importance of the degree of dependency (correlation) among events and to incorporate these dependencies in the quantification phase of PRA, the interdependency between a pair of events in expressed with the aid of the correlation coefficient. For the purpose of demonstrating the methodology, the data base used in the Accident Sequence Precursor Study (ASP) was adopted and simulated to obtain distributions for the correlation coefficients. A computer program entitled Correlation Coefficient Generator (CCG) was developed to generate a distribution for each correlation coefficient. The method of bootstrap technique was employed in the CCG computer code to determine confidence limits of the estimated correlation coefficients. A second computer program designated CORRELATE was also developed to obtain probability intervals for both fault trees and accident sequences with statistically correlated failure data
Lattice cell diffusion coefficients. Definitions and comparisons

International Nuclear Information System (INIS)

Hughes, R.P.

1980-01-01

Definitions of equivalent diffusion coefficients for regular lattices of heterogeneous cells have been given by several authors. The paper begins by reviewing these different definitions and the unification of their derivation. This unification makes clear how accurately each definition (together with appropriate cross-section definitions to preserve the eigenvalue) represents the individual reaction rates within the cell. The approach can be extended to include asymmetric cells and whereas before, the buckling describing the macroscopic flux shape was real, here it is found to be complex. A neutron ''drift'' coefficient as well as a diffusion coefficient is necessary to produce the macroscopic flux shape. The numerical calculation of the various different diffusion coefficients requires the solutions of equations similar to the ordinary transport equation for an infinite lattice. Traditional reactor physics codes are not sufficiently flexible to solve these equations in general. However, calculations in certain simple cases are presented and the theoretical results quantified. In difficult geometries, Monte Carlo techniques can be used to calculate an effective diffusion coefficient. These methods relate to those already described provided that correlation effects between different generations of neutrons are included. Again, these effects are quantified in certain simple cases. (author)
Effective constants for wave propagation through partially saturated porous media

International Nuclear Information System (INIS)

Berryman, J.G.; Thigpen, L.

1985-01-01

The multipole scattering coefficients for elastic wave scattering from a spherical inhomogeneity in a fluid-saturated porous medium have been calculated. These coefficients may be used to obtain estimates of the effective macroscopic constants for long-wavelength propagation of elastic waves through partially saturated media. If the volume average of the single scattering from spherical bubbles of gas and liquid is required to vanish, the resulting equations determine the effective bulk modulus, density, and viscosity of the multiphase fluid filling the pores. The formula for the effective viscosity during compressional wave excitation is apparently new
Estimation of soil-soil solution distribution coefficient of radiostrontium using soil properties.

Science.gov (United States)

Ishikawa, Nao K; Uchida, Shigeo; Tagami, Keiko

2009-02-01

We propose a new approach for estimation of soil-soil solution distribution coefficient (K(d)) of radiostrontium using some selected soil properties. We used 142 Japanese agricultural soil samples (35 Andosol, 25 Cambisol, 77 Fluvisol, and 5 others) for which Sr-K(d) values had been determined by a batch sorption test and listed in our database. Spearman's rank correlation test was carried out to investigate correlations between Sr-K(d) values and soil properties. Electrical conductivity and water soluble Ca had good correlations with Sr-K(d) values for all soil groups. Then, we found a high correlation between the ratio of exchangeable Ca to Ca concentration in water soluble fraction and Sr-K(d) values with correlation coefficient R=0.72. This pointed us toward a relatively easy way to estimate Sr-K(d) values.
HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.

Science.gov (United States)

Yang, Tao; Zhang, Feipeng; Yardımcı, Galip Gürkan; Song, Fan; Hardison, Ross C; Noble, William Stafford; Yue, Feng; Li, Qunhua

2017-11-01

Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach. © 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.
Membrane mobility and microdomain association of the dopaminetransporter studied with fluorescence correlation spectroscopy and fluorescence recovery after photobleaching

DEFF Research Database (Denmark)

Adkins, Erika; Samuvel, Devadoss; Fog, Jacob

2007-01-01

To investigate microdomain association of the dopamine transporter (DAT), we employed FCS (fluorescence correlation spectroscopy) and FRAP (fluorescence recovery after photobleaching). In non-neuronal cells (HEK293), FCS measurements revealed for the YFP-DAT (DAT tagged with yellow fluorescent...... protein) a diffusion coefficient (D) of ~3.6 × 10-9 cm2/s, consistent with a relatively freely diffusible protein. In neuronally derived cells (N2a), we were unable to perform FCS measurements on plasma membrane-associated protein due to photobleaching, suggesting partial immobilization...
SEPHIS and the distribution coefficients correlation in the IMPUREX system

International Nuclear Information System (INIS)

Andaur Iturrieta, Claudio

1997-01-01

The reprocessing of spent nuclear fuels by the IMPUREX process consists in uranium selective extraction, originally in aqueous nitric solution, by action of the tributyl phosphate (TBP) present in an organic phase that circulates at countercurrent of the aqueous one. In the study of such process, it is necessary to use the correlations that allows to predict the concentrations of the solutes in the equilibrium, both in the aqueous phase and in the organic one, given as data the ruling operation conditions (temperature, TBP concentration and acidity). A correlation of this kind is the Groenier-Rainey-Watson, which is forming part of the code of the SEPHIS simulation program. In the present work it is analyzed the behavior of this correlation contrasting the predicted values with experimental ones
Scalar meson in dynamical and partially quenched two-flavor QCD: Lattice results and chiral loops

International Nuclear Information System (INIS)

Prelovsek, S.; Dawson, C.; Izubuchi, T.; Orginos, K.; Soni, A.

2004-01-01

This is an exploratory study of the lightest nonsinglet scalar qq state on the lattice with two dynamical quarks. Domain wall fermions are used for both sea and valence quarks on a 16 3 x32 lattice with an inverse lattice spacing of 1.7 GeV. We extract the scalar meson mass 1.58±0.34 GeV from the exponential time dependence of the dynamical correlators with m val =m sea and N f =2. Since this statistical error bar from dynamical correlators is rather large, we analyze also the partially quenched lattice correlators with m val ≠m sea . They are positive for m val ≥m sea and negative for m val sea . In order to understand this striking effect of partial quenching, we derive the scalar correlator within the partially quenched chiral perturbation theory (ChPT) and find it describes lattice correlators well. The leading unphysical contribution in partially quenched ChPT comes from the exchange of the two pseudoscalar fields and is also positive for m val ≥m sea and negative for m val sea at large t. After the subtraction of this unphysical contribution from the partially quenched lattice correlators, the correlators are positive and exponentially falling. The resulting scalar meson mass 1.51±0.19 GeV from the partially quenched correlators is consistent with the dynamical result and has an appreciably smaller error bar
Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

Science.gov (United States)

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…
Determining extreme parameter correlation in ground water models

DEFF Research Database (Denmark)

Hill, Mary Cole; Østerby, Ole

2003-01-01

can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Heat transfer coefficients for particles in liquid in axially rotating cans

Science.gov (United States)

Hassan, B. H.

A theoretical analysis was carried out to determine the nondimensional parameters and corresponding correlations for the overall heat transfer coefficient (between the external steam and internal rotating liquid) and the liquid-particle film heat transfer coefficient for spherical particles in liquid in axially rotating 303 x 406 cans undergoing steam heating. The correlations were obtained from dimensional analysis of the equations of continuity, motion and energy, together with the thermal energy balances and the particle-fluid dynamics of the system. The theoretical solutions for the temperature distribution in spherical particles with a time varying boundary condition were presented.
Spatial correlation in 3D MIMO channels using fourier coefficients of power spectrums

KAUST Repository

Nadeem, Qurrat-Ul-Ain; Kammoun, Abla; Debbah, Mé rouane; Alouini, Mohamed-Slim

2015-01-01

for arbitrary angular distributions and antenna patterns. The resulting expression depends on the underlying angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty
Modulating Function-Based Method for Parameter and Source Estimation of Partial Differential Equations

KAUST Repository

Asiri, Sharefa M.

2017-01-01

Partial Differential Equations (PDEs) are commonly used to model complex systems that arise for example in biology, engineering, chemistry, and elsewhere. The parameters (or coefficients) and the source of PDE models are often unknown
Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy.

Science.gov (United States)

Meyer, Hans-Jonas; Ziemann, Oliver; Kornhuber, Malte; Emmer, Alexander; Quäschling, Ulf; Schob, Stefan; Surov, Alexey

2018-06-01

Background Magnetic resonance imaging (MRI) is widely used in several muscle disorders. Diffusion-weighted imaging (DWI) is an imaging modality, which can reflect microstructural tissue composition. The apparent diffusion coefficient (ADC) is used to quantify the random motion of water molecules in tissue. Purpose To investigate ADC values in patients with myositis and non-inflammatory myopathy and to analyze possible associations between ADC and laboratory parameters in these patients. Material and Methods Overall, 17 patients with several myositis entities, eight patients with non-inflammatory myopathies, and nine patients without muscle disorder as a control group were included in the study (mean age = 55.3 ± 14.3 years). The diagnosis was confirmed by histopathology in every case. DWI was obtained in a 1.5-T scanner using two b-values: 0 and 1000 s/mm 2 . In all patients, the blood sample was acquired within three days to the MRI. The following serological parameters were estimated: C-reactive protein, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, and myoglobine. Results The estimated mean ADC value for the myositis group was 1.89 ± 0.37 × 10 -3 mm 2 /s and for the non-inflammatory myopathy group was 1.79 ± 0.33 × 10 -3 mm 2 /s, respectively. The mean ADC values (1.15 ± 0.37 × 10 -3 mm 2 /s) were significantly higher to unaffected muscles (vs. myositis P = 0.0002 and vs. myopathy P = 0.0021). There were no significant correlations between serological parameters and ADC values. Conclusion Affected muscles showed statistically significantly higher ADC values than normal muscles. No linear correlations between ADC and serological parameters were identified.
Graphene: A partially ordered non-periodic solid

International Nuclear Information System (INIS)

Wei, Dongshan; Wang, Feng

2014-01-01

Molecular dynamics simulations were performed to study the structural features of graphene over a wide range of temperatures from 50 to 4000 K using the PPBE-G potential [D. Wei, Y. Song, and F. Wang, J. Chem. Phys. 134, 184704 (2011)]. This potential was developed by force matching the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional and has been validated previously to provide accurate potential energy surface for graphene at temperatures as high as 3000 K. Simulations with the PPBE‑G potential are the best available approximation to a direct Car-Parrinello Molecular Dynamics study of graphene. One advantage of the PBE-G potential is to allow large simulation boxes to be modeled efficiently so that properties showing strong finite size effects can be studied. Our simulation box contains more than 600 000 C atoms and is one of the largest graphene boxes ever modeled. With the PPBE-G potential, the thermal-expansion coefficient is negative up to 4000 K. With a large box and an accurate potential, the critical exponent for the scaling properties associated with the normal-normal and height-height correlation functions was confirmed to be 0.85. This exponent remains constant up to 4000 K suggesting graphene to be in the deeply cooled regime even close to the experimental melting temperature. The reduced peak heights in the radial distribution function of graphene show an inverse power law dependence to distance, which indicates that a macroscopic graphene sheet will lose long-range crystalline order as predicted by the Mermin-Wagner instability. Although graphene loses long-range translational order, it retains long range orientational order as indicated by its orientational correlation function; graphene is thus partially ordered but not periodic
Long sequence correlation coprocessor

Science.gov (United States)

Gage, Douglas W.

1994-09-01

A long sequence correlation coprocessor (LSCC) accelerates the bitwise correlation of arbitrarily long digital sequences by calculating in parallel the correlation score for 16, for example, adjacent bit alignments between two binary sequences. The LSCC integrated circuit is incorporated into a computer system with memory storage buffers and a separate general purpose computer processor which serves as its controller. Each of the LSCC's set of sequential counters simultaneously tallies a separate correlation coefficient. During each LSCC clock cycle, computer enable logic associated with each counter compares one bit of a first sequence with one bit of a second sequence to increment the counter if the bits are the same. A shift register assures that the same bit of the first sequence is simultaneously compared to different bits of the second sequence to simultaneously calculate the correlation coefficient by the different counters to represent different alignments of the two sequences.
The Investigation of the Cavitation Phenomenon in the Laval Nozzle with Full and Partial Surface Wetting

Directory of Open Access Journals (Sweden)

Jablonská Jana

2017-04-01

Full Text Available The article deals with the cavitation phenomenon affected by full and partial wetting of the wall. For the numerical computation of flow in the Laval nozzle the Schnerr-Sauer cavitation model was tested and was used for cavitation research of flow within the nozzle considering partial surface wetting. The coefficient of wetting for various materials was determined using experimental, theoretical and numerical methods of fluid flow due to partial surface wetting.
Correlation and simple linear regression.

Science.gov (United States)

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Diffusion coefficient calculations for cylindrical cells

International Nuclear Information System (INIS)

Lam-Hime, M.

1983-03-01

An accurate and general diffusion coefficient calculation for cylindrical cells is described using isotropic scattering integral transport theory. This method has been particularly applied to large regular lattices of graphite-moderated reactors with annular coolant channels. The cells are divided into homogeneous zones, and a zone-wise flux expansion is used to formulate a collision probability problem. The reflection of neutrons at the cell boundary is accounted for by the conservation of the neutron momentum. The uncorrected diffusion coefficient Benoist's definition is used, and the described formulation does not neglect any effect. Angular correlation terms, energy coupling non-uniformity and anisotropy of the classical flux are exactly taken into account. Results for gas-graphite typical cells are given showing the importance of these approximations
Partial solvation parameters and LSER molecular descriptors

International Nuclear Information System (INIS)

Panayiotou, Costas

2012-01-01

Graphical abstract: The one-to-one correspondence of LSER molecular descriptors and partial solvation parameters (PSPs) for propionic acid. Highlights: ► Quantum-mechanics based development of a new QSPR predictive method. ► One-to-one correspondence of partial solvation parameters and LSER molecular descriptors. ► Development of alternative routes for the determination of partial solvation parameters and solubility parameters. ► Expansion and enhancement of solubility parameter approach. - Abstract: The partial solvation parameters (PSP) have been defined recently, on the basis of the insight derived from modern quantum chemical calculations, in an effort to overcome some of the inherent restrictions of the original definition of solubility parameter and expand its range of applications. The present work continues along these lines and introduces two new solvation parameters, the van der Waals and the polarity/refractivity ones, which may replace both of the former dispersion and polar PSPs. Thus, one may use either the former scheme of PSPs (dispersion, polar, acidic, and basic) or, equivalently, the new scheme (van der Waals, polarity/refractivity, acidic, basic). The new definitions are made in a simple and straightforward manner and, thus, the strength and appeal of the widely accepted concept of solubility parameter is preserved. The inter-relations of the various PSPs are critically discussed and their values are tabulated for a variety of common substances. The advantage of the new scheme of PSPs is the bridge that makes with the corresponding Abraham’s LSER descriptors. With this bridge, one may exchange information between PSPs, LSER experimental scales, and quantum mechanics calculations such as via the COSMO-RS theory. The proposed scheme is a predictive one and it is applicable to, both, homo-solvated and hetero-solvated compounds. The new scheme is tested for the calculation of activity coefficients at infinite dilution, for octanol
Physiological Background of Differences in Quantitative Diffusion-Weighted Magnetic Resonance Imaging Between Acute Malignant and Benign Vertebral Body Fractures: Correlation of Apparent Diffusion Coefficient With Quantitative Perfusion Magnetic Resonance Imaging Using the 2-Compartment Exchange Model.

Science.gov (United States)

Geith, Tobias; Biffar, Andreas; Schmidt, Gerwin; Sourbron, Steven; Dietrich, Olaf; Reiser, Maximilian; Baur-Melnyk, Andrea

2015-01-01

To test the hypothesis that apparent diffusion coefficient (ADC) in vertebral bone marrow of benign and malignant fractures is related to the volume of the interstitial space, determined with dynamic contrast-enhanced (DCE) magnetic resonance imaging. Patients with acute benign (n = 24) and malignant (n = 19) vertebral body fractures were examined at 1.5 T. A diffusion-weighted single-shot turbo-spin-echo sequence (b = 100 to 600 s/mm) and DCE turbo-FLASH sequence were evaluated. Regions of interest were manually selected for each fracture. Apparent diffusion coefficient was determined with a monoexponential decay model. The DCE magnetic resonance imaging concentration-time curves were analyzed using a 2-compartment tracer-kinetic model. Apparent diffusion coefficient showed a significant positive correlation with interstitial volume in the whole study population (Pearson r = 0.66, P correlation between ADC and the permeability-surface area product could be observed when analyzing the whole study population (Spearman rs = 0.40, P = 0.008), but not when separately examining the subgroups. Plasma flow showed a significant correlation with ADC in benign fractures (Pearson r = 0.23, P = 0.03). Plasma volume did not show significant correlations with ADC. The results support the hypothesis that the ADC of a lesion is inversely correlated to its cellularity. This explains previous observations that ADC is reduced in more malignant lesions.
Membrane mobility and microdomain association of the dopamine transporter studied with fluorescence correlation spectroscopy and fluorescence recovery after photobleaching

DEFF Research Database (Denmark)

Adkins, Erika M; Samuvel, Devadoss J; Fog, Jacob U

2007-01-01

To investigate microdomain association of the dopamine transporter (DAT), we employed FCS (fluorescence correlation spectroscopy) and FRAP (fluorescence recovery after photobleaching). In non-neuronal cells (HEK293), FCS measurements revealed for the YFP-DAT (DAT tagged with yellow fluorescent...... protein) a diffusion coefficient (D) of approximately 3.6 x 10(-9) cm2/s, consistent with a relatively freely diffusible protein. In neuronally derived cells (N2a), we were unable to perform FCS measurements on plasma membrane-associated protein due to photobleaching, suggesting partial immobilization...
Characterization of skin friction coefficient, and relationship to stratum corneum hydration in a normal Chinese population.

Science.gov (United States)

Zhu, Y H; Song, S P; Luo, W; Elias, P M; Man, M Q

2011-01-01

Studies have demonstrated that some cutaneous biophysical properties vary with age, gender and body sites. However, the characteristics of the skin friction coefficient in different genders and age groups have not yet been well established. In the present study, we assess the skin friction coefficient in a larger Chinese population. A total of 633 subjects (300 males and 333 females) aged 0.15-79 years were enrolled. A Frictiometer FR 770 and Corneometer CM 825 (C&K MPA 5) were used to measure the skin friction coefficient and stratum corneum hydration, respectively, on the dorsal surface of the hand, the forehead and the canthus. In the females, the maximum skin friction coefficients on both the canthus and the dorsal hand skin were observed around the age of 40 years. In the males, the skin friction coefficient on the dorsal hand skin gradually increased from 0 to 40 years of age, and changed little afterward. Skin friction coefficients on some body sites were higher in females than in age-matched males in some age groups. On the canthus and the dorsal hand skin of females, a positive correlation was found between skin friction coefficient and stratum corneum hydration (p skin friction coefficient was positively correlated with stratum corneum hydration on the forehead and the dorsal hand skin (p skin friction coefficient varies with age, gender and body site, and positively correlates with stratum corneum hydration on some body sites. Copyright © 2010 S. Karger AG, Basel.
Lipid–water partition coefficients and correlations with uptakes by algae of organic compounds

International Nuclear Information System (INIS)

Hung, Wei-Nung; Chiou, Cary T.; Lin, Tsair-Fuh

2014-01-01

Graphical abstract: - Highlights: • Partition coefficients of contaminants with lipid triolein (K tw ) are measured. • Measured K tw values are nearly the same as the respective K ow . • Sorption of the contaminants to a dry algal powder is similarly measured. • Algal uptake of a compound occurs primarily by partition into the algal lipid. - Abstract: In view of the scarcity of the lipid–water partition coefficients (K tw ) for organic compounds, the log K tw values for many environmental contaminants were measured using ultra-pure triolein as the model lipid. Classes of compounds studied include alkyl benzenes, halogenated benzenes, short-chain chlorinated hydrocarbons, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine pesticides. In addition to log K tw determination, the uptakes of these compounds from water by a dry algal species were measured to evaluate the lipid effect on the algal uptake. The measured log K tw are closely related to their respective log K ow (octanol–water), with log K ow = 1.9 to 6.5. A significant difference is observed between the present and early measured log K tw for compounds with log K ow > ∼5, which is attributed to the presence and absence of a triolein microemulsion in water affecting the solute partitioning. The observed lipid-normalized algae–water distribution coefficients (log K aw/lipid ) are virtually identical to the respective log K tw values, which manifests the dominant lipid-partition effect of the compounds with algae
CFD Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

Science.gov (United States)

Yang, H. Q.; West, Jeff

2015-01-01

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. This study uses first-principles based CFD methodology to compute heat transfer from the tank wall to the cryogenic fluids and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between the tank wall and cryogenic propellant, and that between the tank wall and ullage gas were then simulated. The results showed that the commonly used heat transfer correlations for either vertical or horizontal plate over-predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.
Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

Science.gov (United States)

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.
Neutrosophic Correlation and Simple Linear Regression

Directory of Open Access Journals (Sweden)

A. A. Salama

2014-09-01

Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.
Extinction Coefficient of Gold Nanostars

OpenAIRE

de Puig, Helena; Tam, Justina O.; Yen, Chun-Wan; Gehrke, Lee; Hamad-Schifferli, Kimberly

2015-01-01

Gold nanostars (NStars) are highly attractive for biological applications due to their surface chemistry, facile synthesis and optical properties. Here, we synthesize NStars in HEPES buffer at different HEPES/Au ratios, producing NStars of different sizes and shapes, and therefore varying optical properties. We measure the extinction coefficient of the synthesized NStars at their maximum surface plasmon resonances (SPR), which range from 5.7 × 108 to 26.8 × 108 M−1cm−1. Measured values correl...
Diffusion weighted MRI and 18F-FDG PET/CT in non-small cell lung cancer (NSCLC): Does the apparent diffusion coefficient (ADC) correlate with tracer uptake (SUV)?

International Nuclear Information System (INIS)

Regier, M.; Derlin, T.; Schwarz, D.; Laqmani, A.; Henes, F.O.; Groth, M.; Buhk, J.-H.; Kooijman, H.; Adam, G.

2012-01-01

Introduction: To investigate the potential correlation of the apparent diffusion coefficient assessed by diffusion-weighted MRI (DWI) and glucose metabolism determined by the standardized uptake value (SUV) at 18F-FDG PET/CT in non-small cell lung cancer (NSCLC). Materials and methods: 18F-FDG PET/CT and DWI (TR/TE, 2000/66 ms; b-values, 0 and 500 s/mm 2 ) were performed in 41 consecutive patients with histologically verified NSCLC. Analysing the PET-CT data calculation of the mean (SUV mean ) and maximum (SUV max ) SUV was performed. By placing a region-of-interest (ROI) encovering the entire tumor mean (ADC mean ) and minimum ADC (ADC min ) were determined by two independent radiologists. Results of 18F-FDG PET-CT and DWI were compared on a per-patient basis. For statistical analysis Pearson's correlation coefficient, Bland–Altman and regression analysis were assessed. Results: Data analysis revealed a significant inverse correlation of the ADC min and SUV max (r = −0.46; p = 0.032). Testing the correlation of the ADC min and SUV max for each histological subtype separately revealed that the inverse correlation was good for both adenocarcinomas (r = −0.47; p = 0.03) and squamouscell carcinomas (r = −0.71; p = 0.002), respectively. No significant correlation was found for the comparison of ADC min and SUV mean (r = −0.29; p = 0.27), ADC mean vs. SUV mean (r = −0.28; p = 0.31) or ADC mean vs. SUV max (r = −0.33; p = 0.23). The κ-value of 0.88 indicated a good agreement between both observers. Conclusion: This preliminary study is the first to verify the relation between the SUV and the ADC in NSCLC. The significant inverse correlation of these two quantitative imaging approaches points out the association of metabolic activity and tumor cellularity. Therefore, DWI with ADC measurement might represent a new prognostic marker in NSCLC
Correlation Coefficient, Path Analysis and Drought Tolerance Indices for Wheat under Deficit Irrigation Conditions and Nitrogen Levels

Directory of Open Access Journals (Sweden)

A. R Tavakoli

2012-07-01

Full Text Available In order to investigate the indices of drought tolerance, correlation coefficient and path analysis at deficit irrigation and nitrogen experiment, this experiment was conducted as split plot arranged in a randomized complete block design (RCBD with three replications during 2000-2003 for wheat at Maragheh agricultural research station of DARI. The treatments were included four levels of deficit irrigation (Rainfed, 100, 160 and 220mm of water use as main plots and five nitrogen rates (0, 30, 60, 90 and 120 kg.N.ha-1 as sub plots. Grain, straw and biological yield, harvest index, productivity degree, plant height, kernel number per spike, Spike number per square meter and TKW determined from the middle of each plot. There were positive significant correlations due to grain yield with all variables: harvest index (r = 0.969 , Productivity degree (r = 0.952 , straw yield (r = 0.904 , plant height (r = 0.904 , biological yield (r = 0.824 , Spike number per square meter (r = 0.817 , kernel number per spike (r = 0.773 and TKW (r = 0.612 respectively. Results of path analysis showed that increase in grain yield was due to increase spike number per square meter and kernel number per spike respectively. On based of indices of drought tolerance (Tolerance Index, Mean Productivity, Geometric Mean Productivity and Harmonic Mean, treatment of %66full irrigation combined with 90KgN.ha-1 was substantially increased water productivity.
Correlation Structures of Correlated Binomial Models and Implied Default Distribution

OpenAIRE

S. Mori; K. Kitsukawa; M. Hisakado

2006-01-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution h...
A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

Science.gov (United States)

Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli

2017-07-01

As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.
A new correlation for convective heat transfer coefficient of water–alumina nanofluid in a square array subchannel under PWR condition

Energy Technology Data Exchange (ETDEWEB)

Shamim, Jubair A. [Department of Nuclear Engineering, Seoul National University, Seoul 08826 (Korea, Republic of); Department of Mechanical Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Bhowmik, Palash K. [Department of Nuclear Engineering, Seoul National University, Seoul 08826 (Korea, Republic of); Department of Nuclear Engineering, Missouri University of Science and Technology, 1201 N. State St., Rolla, MO 65409 (United States); Xiangyi, Chen [Department of Nuclear Engineering, Seoul National University, Seoul 08826 (Korea, Republic of); Suh, Kune Y., E-mail: kysuh@snu.ac.kr [Department of Nuclear Engineering, Seoul National University, Seoul 08826 (Korea, Republic of)

2016-11-15

Highlights: • Thermo-hydrodynamic properties of water–Al{sub 2}O{sub 3} nanofluid at PWR condition is analyzed. • Details of CFD simulation and validation procedure is outlined. • Augmented heat transfer capacity of nanofluid is governed by larger pumping power. • A new correlation for nanofluid Nusselt number in subchannel geometry is proposed. - Abstract: The computational fluid dynamic (CFD) simulation is performed to determine on the thermo- and hydrodynamic performance of the water–alumina (Al{sub 2}O{sub 3}) nanofluid in a square array subchannel featuring pitch-to-diameter ratios of 1.25 and 1.35. Two fundamental aspects of thermal hydraulics, viz. heat transfer and pressure drop, are assessed under typical pressurized water reactor (PWR) conditions at various flow rates (3 × 10{sup 5} ⩽ Re ⩽ 6 × 10{sup 5}) using pure water and differing concentrations of water–alumina nanofluid (0.5–3.0 vol.%) as coolant. Numerical results are compared against predictions made by conventional single-phase convective heat transfer and pressure loss correlations for fully developed turbulent flow. It is observed that addition of tiny nanoparticles in PWR coolant can give rise to the convective heat transfer coefficient at the expense of larger pressure drop. Nevertheless, a modified correlation as a function of nanoparticle volume fraction is proposed to estimate nanofluid Nusselt number more precisely in square array subchannel.
A new correlation for convective heat transfer coefficient of water–alumina nanofluid in a square array subchannel under PWR condition

International Nuclear Information System (INIS)

Shamim, Jubair A.; Bhowmik, Palash K.; Xiangyi, Chen; Suh, Kune Y.

2016-01-01

Highlights: • Thermo-hydrodynamic properties of water–Al_2O_3 nanofluid at PWR condition is analyzed. • Details of CFD simulation and validation procedure is outlined. • Augmented heat transfer capacity of nanofluid is governed by larger pumping power. • A new correlation for nanofluid Nusselt number in subchannel geometry is proposed. - Abstract: The computational fluid dynamic (CFD) simulation is performed to determine on the thermo- and hydrodynamic performance of the water–alumina (Al_2O_3) nanofluid in a square array subchannel featuring pitch-to-diameter ratios of 1.25 and 1.35. Two fundamental aspects of thermal hydraulics, viz. heat transfer and pressure drop, are assessed under typical pressurized water reactor (PWR) conditions at various flow rates (3 × 10"5 ⩽ Re ⩽ 6 × 10"5) using pure water and differing concentrations of water–alumina nanofluid (0.5–3.0 vol.%) as coolant. Numerical results are compared against predictions made by conventional single-phase convective heat transfer and pressure loss correlations for fully developed turbulent flow. It is observed that addition of tiny nanoparticles in PWR coolant can give rise to the convective heat transfer coefficient at the expense of larger pressure drop. Nevertheless, a modified correlation as a function of nanoparticle volume fraction is proposed to estimate nanofluid Nusselt number more precisely in square array subchannel.
How to test for partially predictable chaos.

Science.gov (United States)

Wernecke, Hendrik; Sándor, Bulcsú; Gros, Claudius

2017-04-24

For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.
Partially Decentralized Control Architectures for Satellite Formations

Science.gov (United States)

Carpenter, J. Russell; Bauer, Frank H.

2002-01-01

In a partially decentralized control architecture, more than one but less than all nodes have supervisory capability. This paper describes an approach to choosing the number of supervisors in such au architecture, based on a reliability vs. cost trade. It also considers the implications of these results for the design of navigation systems for satellite formations that could be controlled with a partially decentralized architecture. Using an assumed cost model, analytic and simulation-based results indicate that it may be cheaper to achieve a given overall system reliability with a partially decentralized architecture containing only a few supervisors, than with either fully decentralized or purely centralized architectures. Nominally, the subset of supervisors may act as centralized estimation and control nodes for corresponding subsets of the remaining subordinate nodes, and act as decentralized estimation and control peers with respect to each other. However, in the context of partially decentralized satellite formation control, the absolute positions and velocities of each spacecraft are unique, so that correlations which make estimates using only local information suboptimal only occur through common biases and process noise. Covariance and monte-carlo analysis of a simplified system show that this lack of correlation may allow simplification of the local estimators while preserving the global optimality of the maneuvers commanded by the supervisors.
Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research.

Science.gov (United States)

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.
Determining Composite Validity Coefficients for Army Jobs and Job Families

National Research Council Canada - National Science Library

Zeidner, Joseph

2002-01-01

.... These correlation coefficients are corrected, first, for unreliability of the criterion and, then, for restriction in range effects due to assignment from an Army input population to MOS samples...

Global correlation imaging of magnetic total field gradients

International Nuclear Information System (INIS)

Guo, Lianghui; Meng, Xiaohong; Shi, Lei

2012-01-01

Firstly we introduce the correlation imaging approach for the x-, y- and z-gradients of a magnetic total field anomaly for deriving the distribution of equivalent magnetic sources of the subsurface. In this approach, the subsurface space is divided into a regular grid, and then a correlation coefficient function is computed at each grid node, based on the cross-correlation between the x-gradient (or y-gradient or z-gradient) of the observed magnetic total field anomaly and the x-gradient (or y-gradient or z-gradient) of the theoretical magnetic total field anomaly due to a magnetic dipole. The resultant correlation coefficient is used to describe the probability of a magnetic dipole occurring at the node. We then define a global correlation coefficient function for comprehensively delineating the probability of an occurrence of a magnetic dipole, which takes, at each node, the maximum positive value of the corresponding correlation coefficient function of the three gradients. We finally test the approach both on synthetic data and real data from a metallic deposit area in the middle-lower reaches of the Yangtze River, China. (paper)
Correlation between thromboelastography and traditional coagulation test parameters in hospitalized dogs

Directory of Open Access Journals (Sweden)

Rubanick JV

2017-02-01

Full Text Available Jean V Rubanick, Medora B Pashmakova, Micah A Bishop, James W Barr Department of Veterinary Small Animal Clinical Sciences, Texas A&M University, College Station, TX, USA Abstract: A hospital-based, prospective cross-sectional study was used to compare kaolin-activated thromboelastography (TEG parameters with traditional coagulation tests in 29 hospitalized dogs. Cases were included if the attending clinician requested coagulation testing. Blood was obtained from each dog and coagulation (prothrombin time, partial thromboplastin time, antithrombin activity, d-dimer concentration, and fibrinogen concentration and TEG analyses were performed. Hematocrit (Hct was also measured. Traditional coagulation results were evaluated for correlation with those from kaolin-activated TEG. Spearman’s correlation was used to calculate correlation coefficients. Fibrinogen was positively correlated with maximum amplitude (Pearson r=0.72, P<0.001 and global clot strength (Pearson r=0.72, P<0.001. There was no correlation between any of the remaining coagulation variables, TEG parameters, or Hct. Results of kaolin-activated TEG and traditional coagulation tests are not interchangeable means of monitoring coagulation derangements in this intensive care unit patient population. Determination of a true outcome measure is necessary to establish TEG’s clinical relevance to veterinary medicine. Keywords: TEG, thromboelastography, coagulation, hemostasis
An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

Science.gov (United States)

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.
Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

Roč. 406 , č. 1 (2014), s. 169-175 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Grant - others:GA ČR(CZ) GAP402/11/0948 Program:GA Institutional support: RVO:67985556 Keywords : correlations * econophysics * non-stationarity Subject RIV: AH - Economics Impact factor: 1.732, year: 2014 http://library.utia.cas.cz/separaty/2014/E/kristoufek-0433529.pdf
Tensor models, Kronecker coefficients and permutation centralizer algebras

Science.gov (United States)

Geloun, Joseph Ben; Ramgoolam, Sanjaye

2017-11-01

We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.
CORRELATION COEFFICIENTS BETWEEN THE NUMBERS OF CATEGORIES TILLERS ON SIGNALGRASS PASTURE

Directory of Open Access Journals (Sweden)

Manoel Eduardo Rozalino Santos

2011-07-01

Full Text Available The understanding of relationship between the numbers of tillers categories allows the identification of compensatory mechanisms that ensure plants adaptation to grazing. Thus, this work was conducted to evaluate the associations between densities of various tillers categories in same Brachiaria decumbens pasture under continuous stocking with cattle. The tillers were measured with different growth sources, developmental stages, and defoliation and sizes levels in sites of same pasture with plants of 10, 20, 30 and 40 cm. Pearson linear correlation between the different tillers categories were estimated. The vegetative tillers number (VTN correlated positively with percentage of tillers with up to 20 cm. The response pattern opposite occurred with reproductive (RTN and dead (DTN tillers numbers. The correlations of number of leafless tillers were positive with the percentage of tillers with less than 20 cm and negative with the percentage of tillers with more than 20 cm. The VTN correlated positively with numbers of tillers with and without defoliation, and negatively with the RNT and DNT. The number of aerial tiller was positively correlated with the number of tillers without apical meristem. In B. decumbens pasture there are tradeoffs between percentage of longer tillers and VNT, between numbers of vegetative and leafless tillers, and between VNT and RNT.
Parabolic versus spherical partial cross sections for photoionization excitation of He near threshold

International Nuclear Information System (INIS)

Bouri, C.; Selles, P.; Malegat, L.; Kwato Njock, M. G.

2006-01-01

Spherical and parabolic partial cross sections and asymmetry parameters, defined in the ejected electron frame, are presented for photoionization excitation of the helium atom at 0.1 eV above its double ionization threshold. A quantitative law giving the dominant spherical partial wave l dom for each excitation level n is obtained. The parabolic partial cross sections are shown to satisfy the same approximate selection rules as the related Rydberg series of doubly excited states (K,T) n A . The analysis of radial and angular correlations reveals the close relationship between double excitation, ionization excitation, and double ionization. Opposite to a widespread belief, the observed value of the asymmetry parameter is shown to result from the interplay of radial correlations and symmetry constraints, irrespective of angular correlations. Finally, the measurement of parabolic partial cross sections is proposed as a challenge to experimentalists
Lipid–water partition coefficients and correlations with uptakes by algae of organic compounds

Energy Technology Data Exchange (ETDEWEB)

Hung, Wei-Nung [Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 30011, Taiwan (China); Chiou, Cary T., E-mail: carychio@mail.ncku.edu.tw [Department of Environmental Engineering and Sustainable Environment Research Laboratory, National Cheng Kung University, Tainan 70101, Taiwan (China); U.S. Geological Survey, Denver Federal Center, Denver, CO 80225 (United States); Lin, Tsair-Fuh, E-mail: tflin@mail.ncku.edu.tw [Department of Environmental Engineering and Sustainable Environment Research Laboratory, National Cheng Kung University, Tainan 70101, Taiwan (China)

2014-08-30

Graphical abstract: - Highlights: • Partition coefficients of contaminants with lipid triolein (K{sub tw}) are measured. • Measured K{sub tw} values are nearly the same as the respective K{sub ow}. • Sorption of the contaminants to a dry algal powder is similarly measured. • Algal uptake of a compound occurs primarily by partition into the algal lipid. - Abstract: In view of the scarcity of the lipid–water partition coefficients (K{sub tw}) for organic compounds, the log K{sub tw} values for many environmental contaminants were measured using ultra-pure triolein as the model lipid. Classes of compounds studied include alkyl benzenes, halogenated benzenes, short-chain chlorinated hydrocarbons, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine pesticides. In addition to log K{sub tw} determination, the uptakes of these compounds from water by a dry algal species were measured to evaluate the lipid effect on the algal uptake. The measured log K{sub tw} are closely related to their respective log K{sub ow} (octanol–water), with log K{sub ow} = 1.9 to 6.5. A significant difference is observed between the present and early measured log K{sub tw} for compounds with log K{sub ow} > ∼5, which is attributed to the presence and absence of a triolein microemulsion in water affecting the solute partitioning. The observed lipid-normalized algae–water distribution coefficients (log K{sub aw/lipid}) are virtually identical to the respective log K{sub tw} values, which manifests the dominant lipid-partition effect of the compounds with algae.
Darboux transformations and linear parabolic partial differential equations

International Nuclear Information System (INIS)

Arrigo, Daniel J.; Hickling, Fred

2002-01-01

Solutions for a class of linear parabolic partial differential equation are provided. These solutions are obtained by first solving a system of (n+1) nonlinear partial differential equations. This system arises as the coefficients of a Darboux transformation and is equivalent to a matrix Burgers' equation. This matrix equation is solved using a generalized Hopf-Cole transformation. The solutions for the original equation are given in terms of solutions of the heat equation. These results are applied to the (1+1)-dimensional Schroedinger equation where all bound state solutions are obtained for a 2n-parameter family of potentials. As a special case, the solutions for integral members of the regular and modified Poeschl-Teller potentials are recovered. (author). Letter-to-the-editor
THE EFFECTS OF BASIC MOTOR ABILITIES ON DRIBBLING RESULTS IN SOCCER

Directory of Open Access Journals (Sweden)

Ismail Selimović

2011-03-01

Full Text Available This study was conducted on a sample of 100 boys aged 12-14 years, members of Sarajevo soccer school teams; FK "ŽELJEZNIČAR", FK "SARAJEVO", FK "NOVI GRAD" and FK "BOSNA". As a predictive variable system, the 17 variables of basic motor skills were applied, and criteria variable was the level of motor control knowledge of ball dribble in football. The aim of this study was to determine the effect of multiple and partial basic motor abilities on the ball dribbling results. Results of regression analysis showed that the significance of mutual influence and prediction criteria system was p <0.01. Variables for general endurance assessment and variable for agility assessment showed statistically significant positive partial correlation coefficients. The explosive strength assessment variable had a statistically significant partial correlation coefficient, but a statistically significant negative partial correlation coefficient was noticed with the flexibility assessment variable
Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

International Nuclear Information System (INIS)

Liu, Song; Guan, Wenxian; Wang, Hao; Pan, Liang; Zhou, Zhuping; Yu, Haiping; Liu, Tian; Yang, Xiaofeng; He, Jian; Zhou, Zhengyang

2014-01-01

Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm 2 ). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and Lauren
Spin correlation parameters A{sub xx} and A{sub yy} measurements in p-p scattering from 11 to 26 MeV; Mesure des coefficients de correlation de spins A{sub xx} et A{sub yy} dans la diffusion p-p de 11 a 26 MeV

Energy Technology Data Exchange (ETDEWEB)

Catillon, Ph; Chapellier, M; Garreta, D [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1967-07-01

The A{sub xx} and A{sub yy} spin correlation coefficients of the proton-proton scattering have been measured at the laboratory energies of 11,40 - 19,15 - 23,45 and 26,50 MeV for the center of mass scattering angle 90 degrees. These measurements have been made by scattering a polarized proton beam on a polarized proton target. (authors) [French] Les coefficients de correlation de spins A{sub xx} et A{sub yy} de la diffusion proton-proton ont ete mesures aux energies laboratoire de 11,40 - 19,15 - 23,45 et 26,50 MeV pour un angle de diffusion dans le centre de masse egal a 90 degres. Ces mesures ont ete effectuees par la diffusion d'un faisceau de protons polarises sur une cible de protons polarises. (auteur)
Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

Science.gov (United States)

Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.
Estimating nonlinear selection gradients using quadratic regression coefficients: double or nothing?

Science.gov (United States)

Stinchcombe, John R; Agrawal, Aneil F; Hohenlohe, Paul A; Arnold, Stevan J; Blows, Mark W

2008-09-01

The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 papers published in Evolution between 2002 and 2007, at least 78% of papers have not doubled quadratic regression coefficients, leading to an appreciable underestimate of the strength of stabilizing and disruptive selection. Proper treatment of quadratic regression coefficients is necessary for estimation of fitness surfaces and contour plots, canonical analysis of the gamma matrix, and modeling the evolution of populations on an adaptive landscape.
Measurements of total and tropospheric ozone from IASI: comparison with correlative satellite, ground-based and ozonesonde observations

Directory of Open Access Journals (Sweden)

A. Boynard

2009-08-01

Full Text Available In this paper, we present measurements of total and tropospheric ozone, retrieved from infrared radiance spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI, which was launched on board the MetOp-A European satellite in October 2006. We compare IASI total ozone columns to Global Ozone Monitoring Experiment-2 (GOME-2 observations and ground-based measurements from the Dobson and Brewer network for one full year of observations (2008. The IASI total ozone columns are shown to be in good agreement with both GOME-2 and ground-based data, with correlation coefficients of about 0.9 and 0.85, respectively. On average, IASI ozone retrievals exhibit a positive bias of about 9 DU (3.3% compared to both GOME-2 and ground-based measurements. In addition to total ozone columns, the good spectral resolution of IASI enables the retrieval of tropospheric ozone concentrations. Comparisons of IASI tropospheric columns to 490 collocated ozone soundings available from several stations around the globe have been performed for the period of June 2007–August 2008. IASI tropospheric ozone columns compare well with sonde observations, with correlation coefficients of 0.95 and 0.77 for the [surface–6 km] and [surface–12 km] partial columns, respectively. IASI retrievals tend to overestimate the tropospheric ozone columns in comparison with ozonesonde measurements. Positive average biases of 0.15 DU (1.2% and 3 DU (11% are found for the [surface–6 km] and for the [surface–12 km] partial columns respectively.
Understanding deterministic diffusion by correlated random walks

International Nuclear Information System (INIS)

Klages, R.; Korabel, N.

2002-01-01

Low-dimensional periodic arrays of scatterers with a moving point particle are ideal models for studying deterministic diffusion. For such systems the diffusion coefficient is typically an irregular function under variation of a control parameter. Here we propose a systematic scheme of how to approximate deterministic diffusion coefficients of this kind in terms of correlated random walks. We apply this approach to two simple examples which are a one-dimensional map on the line and the periodic Lorentz gas. Starting from suitable Green-Kubo formulae we evaluate hierarchies of approximations for their parameter-dependent diffusion coefficients. These approximations converge exactly yielding a straightforward interpretation of the structure of these irregular diffusion coefficients in terms of dynamical correlations. (author)
Removal of dissolved organic carbon by aquifer material: Correlations between column parameters, sorption isotherms and octanol-water partition coefficient.

Science.gov (United States)

Pradhan, Snigdhendubala; Boernick, Hilmar; Kumar, Pradeep; Mehrotra, Indu

2016-07-15

The correlation between octanol-water partition coefficient (KOW) and the transport of aqueous samples containing single organic compound is well documented. The concept of the KOW of river water containing the mixture of organics was evolved by Pradhan et al. (2015). The present study aims at determining the KOW and sorption parameters of synthetic aqueous samples and river water to finding out the correlation, if any. The laboratory scale columns packed with aquifer materials were fed with synthetic and river water samples. Under the operating conditions, the compounds in the samples did not separate, and all the samples that contain more than one organic compound yielded a single breakthrough curve. Breakthrough curves simulated from sorption isotherms were compared with those from the column runs. The sorption parameters such as retardation factor (Rf), height of mass transfer zone (HMTZ), rate of mass transfer zone (RMTZ), breakpoint column capacity (qb) and maximum column capacity (qx) estimated from column runs, sorption isotherms and models developed by Yoon-Nelson, Bohart-Adam and Thomas were in agreement. The empirical correlations were found between the KOW and sorption parameters. The transport of the organics measured as dissolved organic carbon (DOC) through the aquifer can be predicted from the KOW of the river water and other water samples. The novelty of the study is to measure KOW and to envisage the fate of the DOC of the river water, particularly during riverbank filtration. Statistical analysis of the results revealed a fair agreement between the observed and computed values. Copyright © 2016 Elsevier Ltd. All rights reserved.
Angular correlation methods

International Nuclear Information System (INIS)

Ferguson, A.J.

1974-01-01

An outline of the theory of angular correlations is presented, and the difference between the modern density matrix method and the traditional wave function method is stressed. Comments are offered on particular angular correlation theoretical techniques. A brief discussion is given of recent studies of gamma ray angular correlations of reaction products recoiling with high velocity into vacuum. Two methods for optimization to obtain the most accurate expansion coefficients of the correlation are discussed. (1 figure, 53 references) (U.S.)
DETERMINATION OF HEAT TRANSFER COEFFICIENTS FOR FRENCH PLASTIC SEMEN STRAW SUSPENDED IN STATIC NITROGEN VAPOR OVER LIQUID NITROGEN.

Science.gov (United States)

Santo, M V; Sansinena, M; Chirife, J; Zaritzky, N

2015-01-01

The use of mathematical models describing heat transfer during the freezing process is useful for the improvement of cryopreservation protocols. A widespread practice for cryopreservation of spermatozoa of domestic animal species consists of suspending plastic straws in nitrogen vapor before plunging into liquid nitrogen. Knowledge of surface heat transfer coefficient (h) is mandatory for computational modelling; however, h values for nitrogen vapor are not available. In the present study, surface heat transfer coefficients for plastic French straws immersed in nitrogen vapor over liquid nitrogen was determined; vertical and horizontal positions were considered. Heat transfer coefficients were determined from the measurement of time-temperature curves and from numerical solution of heat transfer partial differential equation under transient conditions using finite elements. The h values experimentally obtained for horizontal and vertically placed straws were compared to those calculated using correlations based on the Nusselt number for natural convection. For horizontal straws the average obtained value was h=12.5 ± 1.2 W m(2) K and in the case of vertical straws h=16 ± 2.48 W m(2) K. The numerical simulation validated against experimental measurements, combined with accurate h values provides a reliable tool for the prediction of freezing curves of semen-filled straws immersed in nitrogen vapor. The present study contributes to the understanding of the cryopreservation techniques for sperm freezing based on engineering concepts, improving the cooling protocols and the manipulation of the straws.
Horizontal-Longitudinal Correlations of Acoustic Field in Deep Water

International Nuclear Information System (INIS)

Li Jun; Li Zheng-Lin; Ren Yun; Li Wen; Zhang Ren-He

2015-01-01

The horizontal-longitudinal correlations of the acoustic field in deep water are investigated based on the experimental data obtained in the South China Sea. It is shown that the horizontal-longitudinal correlation coefficients in the convergence zone are high, and the correlation length is consistent with the convergence zone width, which depends on the receiver depth and range. The horizontal-longitudinal correlation coefficients in the convergence zone also have a division structure for the deeper receiver. The signals from the second part of the convergence zone are still correlated with the reference signal in the first part. The horizontal-longitudinal correlation coefficients in the shadow zone are lower than that in the convergence zone, and the correlation length in the shadow zone is also much shorter than that in the convergence zone. The numerical simulation results by using the normal modes theory are qualitatively consistent with the experimental results. (paper)

Assessment of the crossflow loss coefficient in Very High Temperature Reactor core - 15338

International Nuclear Information System (INIS)

Lee, S.N.; Tak, N.I.; Kim, M.H.; Noh, J.M.

2015-01-01

The Very High Temperature Reactor (VHTR) is a helium gas cooled and graphite moderated reactor. It was chosen as one of the Gen-4 reactors owing to its inherent safety. Various researches for prismatic gas-cooled reactors have been conducted for efficient and safe use. The prismatic VHTR consists of vertically stacked fuel blocks. Between the vertical fuel blocks, there is cross gap because of manufacturing tolerance or graphite change during the operation. This cross gap changes the coolant flow path, called a crossflow, which may affect the fuel temperature. Various tests and numerical studies have been conducted to predict the crossflow and loss coefficient. In the present study, the CFD calculation is conducted to draw the loss coefficient, and compared with Groehn, Kaburaki and General Atomics (GA) correlations. The results of the Groehn and Kaburaki correlations tend to decrease as the gap size increases, whereas the data of GA show the opposite. The loss coefficient given by the CFD calculation tends to maintain the regular value without regard to the gap size for the standard fuel block, like the Groehn correlation. However, the loss coefficient of the control fuel block increases as the gap size widens, like the GA results
Study of oxygen mass transfer coefficient and oxygen uptake rate in a stirred tank reactor for uranium ore bioleaching

International Nuclear Information System (INIS)

Zokaei-Kadijani, S.; Safdari, J.; Mousavian, M.A.; Rashidi, A.

2013-01-01

Highlights: ► Mass transfer coefficient does not depend on biomass concentration. ► The pulp density has a negative effect on mass transfer coefficient. ► The pulp density is the unique factor that affects maximum OUR. ► In this work, Neale’s correlation is corrected for prediction of mass transfer coefficient. ► Biochemical reaction is a limiting factor in the uranium bioleaching process. - Abstract: In this work, the volumetric oxygen mass transfer coefficient and the oxygen uptake rate (OUR) were studied for uranium ore bioleaching process by Acidthiobacillus ferrooxidans in a stirred tank reactor. The Box-Bohnken design method was used to study the effect of operating parameters on the oxygen mass transfer coefficient. The investigated factors were agitation speed (rpm), aeration rate (vvm) and pulp density (% weight/volume) of the stirred tank reactor. Analysis of experimental results showed that the oxygen mass transfer coefficient had low dependence on biomass concentration but had higher dependence on the agitation speed, aeration rate and pulp density. The obtained biological enhancement factors were equal to ones in experiments. On the other hand, the obtained values for Damkohler number (Da < 0.468) indicated that the process was limited by the biochemical reaction rate. Experimental results obtained for oxygen mass transfer coefficient were correlated with the empirical relations proposed by Garcia-Ochoa and Gomez (2009) and Neale and Pinches (1994). Due to the high relative error in the correlation of Neale and Pinches, that correlation was corrected and the coefficient of determination was calculated to be 89%. The modified correlation has been obtained based on a wide range of operating conditions, which can be used to determine the mass transfer coefficient in a bioreactor
Correlation and prediction of osmotic coefficient and water activity of aqueous electrolyte solutions by a two-ionic parameter model

International Nuclear Information System (INIS)

Pazuki, G.R.

2005-01-01

In this study, osmotic coefficients and water activities in aqueous solutions have been modeled using a new approach based on the Pitzer model. This model contains two physically significant ionic parameters regarding ionic solvation and the closest distance of approach between ions in a solution. The proposed model was evaluated by estimating the osmotic coefficients of nine electrolytes in aqueous solutions. The obtained results showed that the model is suitable for predicting the osmotic coefficients in aqueous electrolyte solutions. Using adjustable parameters, which have been calculated from regression between the experimental osmotic coefficient and the results of this model, the water activity coefficients of aqueous solutions were calculated. The average absolute relative deviations of the osmotic coefficients between the experimental data and the calculated results were in agreement
Spectral methods for time dependent partial differential equations

Science.gov (United States)

Gottlieb, D.; Turkel, E.

1983-01-01

The theory of spectral methods for time dependent partial differential equations is reviewed. When the domain is periodic Fourier methods are presented while for nonperiodic problems both Chebyshev and Legendre methods are discussed. The theory is presented for both hyperbolic and parabolic systems using both Galerkin and collocation procedures. While most of the review considers problems with constant coefficients the extension to nonlinear problems is also discussed. Some results for problems with shocks are presented.
Covariate-adjusted Spearman's rank correlation with probability-scale residuals.

Science.gov (United States)

Liu, Qi; Li, Chun; Wanga, Valentine; Shepherd, Bryan E

2018-06-01

It is desirable to adjust Spearman's rank correlation for covariates, yet existing approaches have limitations. For example, the traditionally defined partial Spearman's correlation does not have a sensible population parameter, and the conditional Spearman's correlation defined with copulas cannot be easily generalized to discrete variables. We define population parameters for both partial and conditional Spearman's correlation through concordance-discordance probabilities. The definitions are natural extensions of Spearman's rank correlation in the presence of covariates and are general for any orderable random variables. We show that they can be neatly expressed using probability-scale residuals (PSRs). This connection allows us to derive simple estimators. Our partial estimator for Spearman's correlation between X and Y adjusted for Z is the correlation of PSRs from models of X on Z and of Y on Z, which is analogous to the partial Pearson's correlation derived as the correlation of observed-minus-expected residuals. Our conditional estimator is the conditional correlation of PSRs. We describe estimation and inference, and highlight the use of semiparametric cumulative probability models, which allow preservation of the rank-based nature of Spearman's correlation. We conduct simulations to evaluate the performance of our estimators and compare them with other popular measures of association, demonstrating their robustness and efficiency. We illustrate our method in two applications, a biomarker study and a large survey. © 2017, The International Biometric Society.
Stochastic partial differential equations an introduction

CERN Document Server

Liu, Wei

2015-01-01

This book provides an introduction to the theory of stochastic partial differential equations (SPDEs) of evolutionary type. SPDEs are one of the main research directions in probability theory with several wide ranging applications. Many types of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. The theory of SPDEs is based both on the theory of deterministic partial differential equations, as well as on modern stochastic analysis. Whilst this volume mainly follows the ‘variational approach’, it also contains a short account on the ‘semigroup (or mild solution) approach’. In particular, the volume contains a complete presentation of the main existence and uniqueness results in the case of locally monotone coefficients. Various types of generalized coercivity conditions are shown to guarantee non-explosion, but also a systematic approach to treat SPDEs with explosion in finite time is developed. It is, so far, the only book where the latter and t...
INTERPRETING THE DISTANCE CORRELATION RESULTS FOR THE COMBO-17 SURVEY

International Nuclear Information System (INIS)

Richards, Mercedes T.; Richards, Donald St. P.; Martínez-Gómez, Elizabeth

2014-01-01

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be enhanced through a new statistical measure of association and correlation, called the distance correlation coefficient, which has more statistical power to detect associations than does the classical Pearson measure of linear relationships between two variables. The distance correlation measure offers a more precise alternative to the classical measure since it is capable of detecting nonlinear relationships that may appear in astrophysical applications. We showed recently that the comparison between the distance and Pearson correlation coefficients can be used effectively to isolate potential outliers in various galaxy data sets, and this comparison has the ability to confirm the level of accuracy associated with the data. In this work, we elucidate the advantages of distance correlation when applied to large databases. We illustrate how the distance correlation measure can be used effectively as a tool to confirm nonlinear relationships between various variables in the COMBO-17 database, including the lengths of the major and minor axes, and the alternative redshift distribution. For these outlier pairs, the distance correlation coefficient is routinely higher than the Pearson coefficient since it is easier to detect nonlinear relationships with distance correlation. The V-shaped scatter plots of Pearson versus distance correlation coefficients also reveal the patterns with increasing redshift and the contributions of different galaxy types within each redshift range
Correlation Structures of Correlated Binomial Models and Implied Default Distribution

Science.gov (United States)

Mori, Shintaro; Kitsukawa, Kenji; Hisakado, Masato

2008-11-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.
New design procedure development of future reactor critical power estimation. (1) Practical design-by-analysis method for BWR critical power design correlation

International Nuclear Information System (INIS)

Yamamoto, Yasushi; Mitsutake, Toru

2007-01-01

For present BWR fuels, the full mock-up thermal-hydraulic test, such as the critical power measurement test, pressure drop measurement test and so on, has been needed. However, the full mock-up test required the high costs and large-scale test facility. At present, there are only a few test facilities to perform the full mock-up thermal-hydraulic test in the world. Moreover, for future BWR, the bundle size tends to be larger, because of reducing the plant construction costs and minimizing the routine check period. For instance, AB1600, improved ABWR, was proposed from Toshiba, whose bundle size was 1.2 times larger than the conventional BWR fuel size. It is too expensive and far from realistic to perform the full mock-up thermal-hydraulic test for such a large size fuel bundle. The new design procedure is required to realize the large scale bundle design development, especially for the future reactor. Therefore, the new design procedure, Practical Design-by-Analysis (PDBA) method, has been developed. This new procedure consists of the partial mock-up test and numerical analysis. At present, the subchannel analysis method based on three-fluid two-phase flow model only is a realistic choice. Firstly, the partial mock-up test is performed, for instance, the 1/4 partial mock-up bundle. Then, the first-step critical power correlation coefficients are evaluated with the measured data. The input data, such as the spacer effect model coefficient, on the subchannel analysis are also estimated with the data. Next, the radial power effect on the critical power of the full-bundle size was estimated with the subchannel analysis. Finally, the critical power correlation is modified by the subchannel analysis results. In the present study, the critical power correlation of the conventional 8x8 BWR fuel was developed with the PDBA method by 4x4 partial mock-up tests and the subchannel analysis code. The accuracy of the estimated critical power was 3.8%. The several themes remain to
Vapour pressures and osmotic coefficients of binary mixtures containing alcohol and pyrrolidinium-based ionic liquids

International Nuclear Information System (INIS)

Calvar, N.; Domínguez, Á.; Macedo, E.A.

2013-01-01

Highlights: • Osmotic coefficients of alcohols with pyrrolidinium ILs are determined. • Experimental data were correlated with extended Pitzer model of Archer and MNRTL. • Mean molal activity coefficients and excess Gibbs free energies were calculated. • The results have been interpreted in terms of interactions. -- Abstract: The osmotic and activity coefficients and vapour pressures of mixtures containing primary (1-propanol, 1-butanol and 1-pentanol) and secondary (2-propanol and 2-butanol) alcohols with pyrrolidinium-based ionic liquids (1-butyl-1-methyl pyrrolidinium bis(trifluoromethylsulfonyl)imide, C 4 MpyrNTf 2 , and 1-butyl-1-methyl pyrrolidinium trifluoromethanesulfonate, C 4 MpyrTFO) have been experimentally determined at T = 323.15 K. For the experimental measurements, the vapour pressure osmometry technique has been used. The results on the influence of the structure of the alcohol and of the anion of the ionic liquid on the determined properties have been discussed and compared with literature data. For the correlation of the osmotic coefficients obtained, the Extended Pitzer model of Archer and the Modified Non-Random Two Liquids model were applied. The mean molal activity coefficients and the excess Gibbs energy for the studied mixtures were calculated from the parameters obtained in the correlation
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series

DEFF Research Database (Denmark)

Johansen, Søren

), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population...... values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient......Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Influence of N2 partial pressure on structural and microhardness properties of TiN/ZrN multilayers deposited by Ar/N2 vacuum arc discharge

Science.gov (United States)

Naddaf, M.; Abdallah, B.; Ahmad, M.; A-Kharroub, M.

2016-08-01

The influence of N2 partial pressure on structural, mechanical and wetting properties of multilayered TiN/ZrN thin films deposited on silicon substrates by vacuum arc discharge of (N2 + Ar) gas mixtures is investigated. X-ray diffraction (XRD) results show that the average texturing coefficient of (1 1 1) orientation and the grain size of both TiN and ZrN individual layers increase with increasing the N2 partial pressure. The Rutherford back scattering (RBS) measurements and analysis reveal that incorporation of the nitrogen in the film increases with increasing the N2 partial pressure and both TiN and ZrN individual layers have a nitrogen over-stoichiometry for N2 partial pressure ⩾50%. The change in the film micro-hardness is correlated to the changes in crystallographic texture, grain size, stoichiometry and the residual stress in the film as a function of the N2 partial pressure. In particular, stoichiometry of ZrN and TiN individual is found to play the vital role in determining the multilayer hardness. The multilayer film deposited at N2 partial pressure of 25% has the best stoichiometric ratio of both TiN and ZrN layers and the highest micro-hardness of about 32 GPa. In addition, water contact angle (WCA) measurements and analysis show a decrease in the work of adhesion on increasing the N2 partial pressure.
Influence of N_2 partial pressure on structural and microhardness properties of TiN/ZrN multilayers deposited by Ar/N_2 vacuum arc discharge

International Nuclear Information System (INIS)

Naddaf, M.; Abdallah, B.; Ahmad, M.; A-Kharroub, M.

2016-01-01

The influence of N_2 partial pressure on structural, mechanical and wetting properties of multilayered TiN/ZrN thin films deposited on silicon substrates by vacuum arc discharge of (N_2 + Ar) gas mixtures is investigated. X-ray diffraction (XRD) results show that the average texturing coefficient of (1 1 1) orientation and the grain size of both TiN and ZrN individual layers increase with increasing the N_2 partial pressure. The Rutherford back scattering (RBS) measurements and analysis reveal that incorporation of the nitrogen in the film increases with increasing the N_2 partial pressure and both TiN and ZrN individual layers have a nitrogen over-stoichiometry for N_2 partial pressure ⩾50%. The change in the film micro-hardness is correlated to the changes in crystallographic texture, grain size, stoichiometry and the residual stress in the film as a function of the N_2 partial pressure. In particular, stoichiometry of ZrN and TiN individual is found to play the vital role in determining the multilayer hardness. The multilayer film deposited at N_2 partial pressure of 25% has the best stoichiometric ratio of both TiN and ZrN layers and the highest micro-hardness of about 32 GPa. In addition, water contact angle (WCA) measurements and analysis show a decrease in the work of adhesion on increasing the N_2 partial pressure.
Sustained frictional instabilities on nanodomed surfaces: Stick-slip amplitude coefficient

DEFF Research Database (Denmark)

Quignon, Benoit; Pilkington, Georgia A.; Thormann, Esben

2013-01-01

to sustained frictional instabilities, effectively with no contact frictional sliding. The amplitude of the stick-slip oscillations, σf, was found to correlate with the topographic properties of the surfaces and scale linearly with the applied load. In line with the friction coefficient, we define the slope......-defined nanodomes comprising densely packed prolate spheroids, of diameters ranging from tens to hundreds of nanometers. Our results show that the average lateral force varied linearly with applied load, as described by Amontons' first law of friction, although no direct correlation between the sample topographic...... properties and their measured friction coefficients was identified. Furthermore, all the nanodomed textures exhibited pronounced oscillations in the shear traces, similar to the classic stick-slip behavior, under all the shear velocities and load regimes studied. That is, the nanotextured topography led...
Strength and Biot's coefficient for high-porosity oil- or water-saturated chalk

DEFF Research Database (Denmark)

Andreassen, Katrine Alling

. The Biot coefficient states the degree of cementation or how the pore pressure contributes to the strain resulting from an external load for a porous material. It is here calculated from dynamic measurements and correlated with the strength of outcrop chalk characterized by the onset of pore collapse...... during hydrostatic loading. The hypothesis is that the Biot coefficient and the theory of poroelasticity may cover the fluid effect by including the increased fluid bulk modulus from oil to water. A high number of test results for both oil- and water-saturated high-porosity outcrop chalk show correlation......In the petroleum industry it is relevant to know the Biot coefficient for establishing the effective stresses present in both the overburden and for the reservoir interval. When depleting a reservoir it is important to estimate the settlement through the strain imposed by the effective stress. Also...
Activity coefficients at infinite dilution of organic solutes in 1-hexyl-3-methylimidazolium trifluoroacetate and influence of interfacial adsorption using gas–liquid chromatography

International Nuclear Information System (INIS)

Jiang, Lin-Kun; Wang, Li-Sheng; Du, Chao-Jun; Wang, Xue-Yuan

2014-01-01

Highlights: • Activity coefficients at infinite dilution of organic solutes in [HMIM][TFA] were determined. • The contribution of interfacial adsorption to the retention mechanism was estimated. • The partial molar excess enthalpies and the solubility parameters of [HMIM][TFA] were calculated. -- Abstract: Activity coefficients at infinite dilution for a series of organic solutes in the ionic liquid 1-hexyl-3-methylimidazolium trifluoroacetate ([HMIM][TFA]) have been determined by gas–liquid chromatography at the temperature range from (303.15 to 363.15) K. The contribution of interfacial adsorption to the retention mechanism was estimated by changing the loading of ionic liquid in stationary phase. The partial molar excess enthalpies at infinite dilution and the solubility parameters of ionic liquid were also calculated from the experimental values of activity coefficients at infinite dilution
development of dual purpose sorghum: correlation and path

African Journals Online (AJOL)

ACSS

(Table 3). Grain yield and stem sugar traits. The correlation coefficients between grain yield and. T. ABLE 2. Correlation coefficients between grain yield and stem sugar content with selected agronomic traits in sorghum. SBX. GY. SBW. DT50F. HDL. SJS. NLP. PHT. Stem brix (SBX). 1.000. Grain yield (GY). 0.071**. 1.000.
Analysis of Satellite Drag Coefficient Based on Wavelet Transform

Science.gov (United States)

Liu, Wei; Wang, Ronglan; Liu, Siqing

Abstract: Drag coefficient sequence was obtained by solving Tiangong1 continuous 55days GPS orbit data with different arc length. The same period solar flux f10.7 and geomagnetic index Ap ap series were high and low frequency multi-wavelet decomposition. Statistical analysis results of the layers sliding correlation between space environmental parameters and decomposition of Cd, showed that the satellite drag coefficient sequence after wavelet decomposition and the corresponding level of f10.7 Ap sequence with good lag correlation. It also verified that the Cd prediction is feasible. Prediction residuals of Cd with different regression models and different sample length were analysed. The results showed that the case was best when setting sample length 20 days and f10.7 regression model were used. It also showed that NRLMSIS-00 model's response in the region of 350km (Tiangong's altitude) and low-middle latitude (Tiangong's inclination) is excessive in ascent stage of geomagnetic activity Ap and is inadequate during fall off segment. Additionally, the low-frequency decomposition components NRLMSIS-00 model's response is appropriate in f10.7 rising segment. High frequency decomposition section, Showed NRLMSIS-00 model's response is small-scale inadequate during f10.7 ascent segment and is reverse in decline of f10.7. Finally, the potential use of a summary and outlook were listed; This method has an important reference value to improve the spacecraft orbit prediction accuracy. Key words: wavelet transform; drag coefficient; lag correlation; Tiangong1;space environment
Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

Science.gov (United States)

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis

Science.gov (United States)

Jones, Reese E.; Mandadapu, Kranthi K.

2012-04-01

We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.

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