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

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

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

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

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

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

A comparison of two indices for the intraclass correlation coefficient.

PubMed

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.

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

PubMed

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

2008-06-18

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

Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

NASA Technical Reports Server (NTRS)

Frenkiel, Francois N.

1958-01-01

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

Generalization of Clustering Coefficients to Signed Correlation Networks

PubMed Central

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

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

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

Inferential Procedures for Correlation Coefficients Corrected for Attenuation.

ERIC Educational Resources Information Center

Hakstian, A. Ralph; And Others

1988-01-01

A model and computation procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Delta and Monte Carlo method applications are discussed. A power analysis revealed no serious loss in efficiency resulting from correction for attentuation. (TJH)

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

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.

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

PubMed

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

2007-09-01

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

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

PubMed

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

2018-04-01

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

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Supersymmetric contributions to weak decay correlation coefficients

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

Profumo, S.; Ramsey-Musolf, M. J.; Tulin, S.

2007-04-01

We study supersymmetric contributions to correlation coefficients that characterize the spectral shape and angular distribution for polarized {mu}- and {beta}-decays. In the minimal supersymmetric standard model (MSSM), one-loop box graphs containing superpartners can give rise to non-(V-Ax(V-A) four-fermion operators in the presence of left-right or flavor mixing between sfermions. We analyze the present phenomenological constraints on such mixing and determine the range of allowed contributions to the weak decay correlation coefficients. We discuss the prospective implications for future {mu}- and {beta}-decay experiments, and argue that they may provide unique probes of left-right mixing in the first generation scalar fermion sector.

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

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

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

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

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

The Evolution of Pearson's Correlation Coefficient

ERIC Educational Resources Information Center

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…

Choosing the best index for the average score intraclass correlation coefficient.

PubMed

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.

Zero Pearson coefficient for strongly correlated growing trees

NASA Astrophysics Data System (ADS)

Dorogovtsev, S. N.; Ferreira, A. L.; Goltsev, A. V.; Mendes, J. F. F.

2010-03-01

We obtained Pearson’s coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1) . If the number of connections of new vertices exceeds one (m>1) , then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent γ does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson’s coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Zero Pearson coefficient for strongly correlated growing trees.

PubMed

Dorogovtsev, S N; Ferreira, A L; Goltsev, A V; Mendes, J F F

2010-03-01

We obtained Pearson's coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1). If the number of connections of new vertices exceeds one (m>1), then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent gamma does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson's coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality.

PubMed

Bishara, Anthony J; Hittner, James B

2015-10-01

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 with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box-Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples ( n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

PubMed Central

Hittner, James B.

2014-01-01

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 with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box–Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples (n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated. PMID:29795841

Correlation tests of the engine performance parameter by using the detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

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

PubMed

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

2017-07-01

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

Negative Correlation between the Diffusion Coefficient and Transcriptional Activity of the Glucocorticoid Receptor.

PubMed

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.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

PubMed

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.

Highlighting material structure with transmission electron diffraction correlation coefficient maps.

PubMed

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.

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

PubMed

Rastegar, Seyed Omid; Gu, Tingyue

2017-03-24

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

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

A Method for Approximating the Bivariate Normal Correlation Coefficient.

ERIC Educational Resources Information Center

Kirk, David B.

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

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

PubMed

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

2016-06-01

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

Modeling Concordance Correlation Coefficient for Longitudinal Study Data

ERIC Educational Resources Information Center

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…

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

PubMed

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.

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

PubMed Central

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

2017-01-01

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. PMID:29035341

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

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

Statistical analysis on multifractal detrended cross-correlation coefficient for return interval by oriented percolation

NASA Astrophysics Data System (ADS)

Deng, Wei; Wang, Jun

2015-06-01

We investigate and quantify the multifractal detrended cross-correlation of return interval series for Chinese stock markets and a proposed price model, the price model is established by oriented percolation. The return interval describes the waiting time between two successive price volatilities which are above some threshold, the present work is an attempt to quantify the level of multifractal detrended cross-correlation for the return intervals. Further, the concept of MF-DCCA coefficient of return intervals is introduced, and the corresponding empirical research is performed. The empirical results show that the return intervals of SSE and SZSE are weakly positive multifractal power-law cross-correlated, and exhibit the fluctuation patterns of MF-DCCA coefficients. The similar behaviors of return intervals for the price model is also demonstrated.

Statistical test for ΔρDCCA cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Guedes, E. F.; Brito, A. A.; Oliveira Filho, F. M.; Fernandez, B. F.; de Castro, A. P. N.; da Silva Filho, A. M.; Zebende, G. F.

2018-07-01

In this paper we propose a new statistical test for ΔρDCCA, Detrended Cross-Correlation Coefficient Difference, a tool to measure contagion/interdependence effect in time series of size N at different time scale n. For this proposition we analyzed simulated and real time series. The results showed that the statistical significance of ΔρDCCA depends on the size N and the time scale n, and we can define a critical value for this dependency in 90%, 95%, and 99% of confidence level, as will be shown in this paper.

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

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

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

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

PubMed

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.

PubMed

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.

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

PubMed

Szczerbik, Ewa; Krawczyk, Maciej; Syczewska, Małgorzata

2014-01-01

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

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

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

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

Observations of copolar correlation coefficient through a bright band at vertical incidence

NASA Technical Reports Server (NTRS)

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.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

PubMed

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).

Gender and Age Analyses of NIRS/STAI Pearson Correlation Coefficients at Resting State.

PubMed

Matsumoto, T; Fuchita, Y; Ichikawa, K; Fukuda, Y; Takemura, N; Sakatani, K

2016-01-01

According to the valence asymmetry hypothesis, the left/right asymmetry of PFC activity is correlated with specific emotional responses to mental stress and personality traits. In a previous study we measured spontaneous oscillation of oxy-Hb concentrations in the bilateral PFC at rest in normal adults employing two-channel portable NIRS and computed the laterality index at rest (LIR). We investigated the Pearson correlation coefficient between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that subjects with right-dominant activity at rest showed higher STAI scores, while those with left dominant oxy-Hb changes at rest showed lower STAI scores such that the Pearson correlation coefficient between LIR and STAI was positive. This study performed Bootstrap analysis on the data and showed the following statistics of the target correlation coefficient: mean=0.4925 and lower confidence limit=0.177 with confidence level 0.05. Using the KS-test, we demonstrated that the correlation did not depend on age, whereas it did depend on gender.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

PubMed

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.

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated

Correlation time and diffusion coefficient imaging: application to a granular flow system.

PubMed

Caprihan, A; Seymour, J D

2000-05-01

A parametric method for spatially resolved measurements for velocity autocorrelation functions, R(u)(tau) = , expressed as a sum of exponentials, is presented. The method is applied to a granular flow system of 2-mm oil-filled spheres rotated in a half-filled horizontal cylinder, which is an Ornstein-Uhlenbeck process with velocity autocorrelation function R(u)(tau) = e(- ||tau ||/tau(c)), where tau(c) is the correlation time and D = tau(c) is the diffusion coefficient. The pulsed-field-gradient NMR method consists of applying three different gradient pulse sequences of varying motion sensitivity to distinguish the range of correlation times present for particle motion. Time-dependent apparent diffusion coefficients are measured for these three sequences and tau(c) and D are then calculated from the apparent diffusion coefficient images. For the cylinder rotation rate of 2.3 rad/s, the axial diffusion coefficient at the top center of the free surface was 5.5 x 10(-6) m(2)/s, the correlation time was 3 ms, and the velocity fluctuation or granular temperature was 1.8 x 10(-3) m(2)/s(2). This method is also applicable to study transport in systems involving turbulence and porous media flows. Copyright 2000 Academic Press.

Anthropometry of Women of the U.S. Army--1977. Report Number 4. Correlation Coefficients

DTIC Science & Technology

1980-02-01

S.... •, 0 76 x:. ADo5 //64 ! TECHNICAL REPORT NATICK/TR-80/016 (/ II ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY-1977 Report No. 4 Correlation...NUMBER NATICK/TR-80/016 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY--1977 Technical Report REPORT NO... Anthropometry Survey(s) Coefficients of correlation Measurement(s) U.S. Army Correlation coefficients Body size Military personnel Equation(s) Sizes

Correlation Revelation: The Search for Meaning in Pearson's Coefficient

ERIC Educational Resources Information Center

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…

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

ERIC Educational Resources Information Center

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…

Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Fan, Jie; Gao, You

2015-12-01

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

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith

Robust Approximations to the Non-Null Distribution of the Product Moment Correlation Coefficient I: The Phi Coefficient.

ERIC Educational Resources Information Center

Edwards, Lynne K.; Meyers, Sarah A.

Correlation coefficients are frequently reported in educational and psychological research. The robustness properties and optimality among practical approximations when phi does not equal 0 with moderate sample sizes are not well documented. Three major approximations and their variations are examined: (1) a normal approximation of Fisher's Z,…

Thermal expansion coefficient determination of polylactic acid using digital image correlation

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Li, Cun-Yu; Wu, Xin; Gu, Jia-Mei; Li, Hong-Yang; Peng, Guo-Ping

2018-04-01

Based on the molecular sieving and solution-diffusion effect in nanofiltration separation, the correlation between initial concentration and mass transfer coefficient of three typical phenolic acids from Salvia miltiorrhiza was fitted to analyze the relationship among mass transfer coefficient, molecular weight and concentration. The experiment showed a linear relationship between operation pressure and membrane flux. Meanwhile, the membrane flux was gradually decayed with the increase of solute concentration. On the basis of the molecular sieving and solution-diffusion effect, the mass transfer coefficient and initial concentration of three phenolic acids showed a power function relationship, and the regression coefficients were all greater than 0.9. The mass transfer coefficient and molecular weight of three phenolic acids were negatively correlated with each other, and the order from high to low is protocatechualdehyde >rosmarinic acid> salvianolic acid B. The separation mechanism of nanofiltration for phenolic acids was further clarified through the analysis of the correlation of molecular weight and nanofiltration mass transfer coefficient. The findings provide references for nanofiltration separation, especially for traditional Chinese medicine with phenolic acids. Copyright© by the Chinese Pharmaceutical Association.

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

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

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

Threshold network of a financial market using the P-value of correlation coefficients

NASA Astrophysics Data System (ADS)

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.

The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

ERIC Educational Resources Information Center

Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.

2010-01-01

In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

NASA Astrophysics Data System (ADS)

Zhao, Jinping; Cao, Yong; Wang, Xin

2018-06-01

In order to study the temporal variations of correlations between two time series, a running correlation coefficient (RCC) could be used. An RCC is calculated for a given time window, and the window is then moved sequentially through time. The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient, calculated with the data within the time window, which we call the local running correlation coefficient (LRCC). The LRCC is calculated via the two anomalies corresponding to the two local means, meanwhile, the local means also vary. It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means. To address this problem, two unchanged means obtained from all available data are adopted to calculate an RCC, which is called the synthetic running correlation coefficient (SRCC). When the anomaly variations are dominant, the two RCCs are similar. However, when the variations of the means are dominant, the difference between the two RCCs becomes obvious. The SRCC reflects the correlations of both the anomaly variations and the variations of the means. Therefore, the SRCCs from different time points are intercomparable. A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data. The SRCC always meets this criterion, while the LRCC sometimes fails. Therefore, the SRCC is better than the LRCC for running correlations. We suggest using the SRCC to calculate the RCCs.

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

ERIC Educational Resources Information Center

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)

Correlation Between Geometric Similarity of Ice Shapes and the Resulting Aerodynamic Performance Degradation: A Preliminary Investigation Using WIND

NASA Technical Reports Server (NTRS)

Wright, William B.; Chung, James

1999-01-01

Aerodynamic performance calculations were performed using WIND on ten experimental ice shapes and the corresponding ten ice shapes predicted by LEWICE 2.0. The resulting data for lift coefficient and drag coefficient are presented. The difference in aerodynamic results between the experimental ice shapes and the LEWICE ice shapes were compared to the quantitative difference in ice shape geometry presented in an earlier report. Correlations were generated to determine the geometric features which have the most effect on performance degradation. Results show that maximum lift and stall angle can be correlated to the upper horn angle and the leading edge minimum thickness. Drag coefficient can be correlated to the upper horn angle and the frequency-weighted average of the Fourier coefficients. Pitching moment correlated with the upper horn angle and to a much lesser extent to the upper and lower horn thicknesses.

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

ERIC Educational Resources Information Center

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…

Correcting Coefficient Alpha for Correlated Errors: Is [alpha][K]a Lower Bound to Reliability?

ERIC Educational Resources Information Center

Rae, Gordon

2006-01-01

When errors of measurement are positively correlated, coefficient alpha may overestimate the "true" reliability of a composite. To reduce this inflation bias, Komaroff (1997) has proposed an adjusted alpha coefficient, ak. This article shows that ak is only guaranteed to be a lower bound to reliability if the latter does not include correlated…

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

A comparison of confidence interval methods for the concordance correlation coefficient and intraclass correlation coefficient with small number of raters.

PubMed

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.

[Correlation coefficient-based principle and method for the classification of jump degree in hydrological time series].

PubMed

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.

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

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

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

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Asymptotic properties of Pearson's rank-variate correlation coefficient under contaminated Gaussian model.

PubMed

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.

A short note on jackknifing the concordance correlation coefficient.

PubMed

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.

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

PubMed

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

2016-04-01

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

Initial Ship Design Using a Pearson Correlation Coefficient and Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Moon, Byung Young; Kim, Soo Young; Kang, Gyung Ju

In this paper we analyzed correlation between geometrical character and resistance, and effective horse power by using Pearson correlation coefficient which is one of the data mining methods. Also we made input data to ship's geometrical character which has strong correlation with output data. We calculated effective horse power and resistance by using Neuro-Fuzzy system. To verify the calculation, 9 of 11 container ships' data were improved as data of Neuro-Fuzzy system and the others were improved as verification data. After analyzing rate of error between existing data and calculation data, we concluded that calculation data have sound agreement with existing data.

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

PubMed Central

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

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 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. PMID:29097924

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

PubMed

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 < 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.

Measuring the diffusion coefficient of ganglioside on cell membrane by fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Dong, Shiqing; You, Minghai; Chen, Jianling; Zhou, Jie; Xie, Shusen; Yang, Hongqin

2017-06-01

The fluidity of proteins and lipids on cell membrane plays an important role in cell’s physiological functions. Fluorescence correlation spectroscopy (FCS) is an effective technique to detect the rapid dynamic behaviors of proteins and/or lipids in living cells. In this study, we used the rhodamine6G solution to optimize the FCS system. And, cholera toxin B subunit (CT-B) was used to label ganglioside on living Hela cell membranes. The diffusion time and coefficients of ganglioside can be obtained through fitting the autocorrelation curve based on the model of two-dimensional cell membrane. The results showed that the diffusion coefficients of ganglioside distributed within a wide range. It revealed the lateral diffusion of lipids on cell membrane was inhomogeneous, which was due to different microstructures of cytoplasmic membrane. The study provides a helpful method for further studying the dynamic characteristics of proteins and lipids molecules on living cell membrane.

Confidence Intervals and "F" Tests for Intraclass Correlation Coefficients Based on Three-Way Mixed Effects Models

ERIC Educational Resources Information Center

Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.

2011-01-01

Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

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

Lu, Fengbin, E-mail: fblu@amss.ac.cn

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 relationsmore » 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.« less

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

PubMed

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 © 2016 Elsevier Ltd. All rights reserved.

The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis.

PubMed

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 (P<0.001). After the sensitivity analysis, two studies were excluded, and the pooled r was -0.61 (95% CI: -0.66, -0.56) and was not significantly heterogeneous (P = 0.127). Regarding tumor type subgroup analysis, there were sufficient data to support a strong negative correlation 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.

An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

NASA Astrophysics Data System (ADS)

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.

Correlation-coefficient-based fast template matching through partial elimination.

PubMed

Mahmood, Arif; Khan, Sohaib

2012-04-01

Partial computation elimination techniques are often used for fast template matching. At a particular search location, computations are prematurely terminated as soon as it is found that this location cannot compete with an already known best match location. Due to the nonmonotonic growth pattern of the correlation-based similarity measures, partial computation elimination techniques have been traditionally considered inapplicable to speed up these measures. In this paper, we show that partial elimination techniques may be applied to a correlation coefficient by using a monotonic formulation, and we propose basic-mode and extended-mode partial correlation elimination algorithms for fast template matching. The basic-mode algorithm is more efficient on small template sizes, whereas the extended mode is faster on medium and larger templates. We also propose a strategy to decide which algorithm to use for a given data set. To achieve a high speedup, elimination algorithms require an initial guess of the peak correlation value. We propose two initialization schemes including a coarse-to-fine scheme for larger templates and a two-stage technique for small- and medium-sized templates. Our proposed algorithms are exact, i.e., having exhaustive equivalent accuracy, and are compared with the existing fast techniques using real image data sets on a wide variety of template sizes. While the actual speedups are data dependent, in most cases, our proposed algorithms have been found to be significantly faster than the other algorithms.

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

NASA Astrophysics Data System (ADS)

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.

Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

PubMed

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.

Statistical functions and relevant correlation coefficients of clearness index

NASA Astrophysics Data System (ADS)

Pavanello, Diego; Zaaiman, Willem; Colli, Alessandra; Heiser, John; Smith, Scott

2015-08-01

This article presents a statistical analysis of the sky conditions, during years from 2010 to 2012, for three different locations: the Joint Research Centre site in Ispra (Italy, European Solar Test Installation - ESTI laboratories), the site of National Renewable Energy Laboratory in Golden (Colorado, USA) and the site of Brookhaven National Laboratories in Upton (New York, USA). The key parameter is the clearness index kT, a dimensionless expression of the global irradiance impinging upon a horizontal surface at a given instant of time. In the first part, the sky conditions are characterized using daily averages, giving a general overview of the three sites. In the second part the analysis is performed using data sets with a short-term resolution of 1 sample per minute, demonstrating remarkable properties of the statistical distributions of the clearness index, reinforced by a proof using fuzzy logic methods. Successively some time-dependent correlations between different meteorological variables are presented in terms of Pearson and Spearman correlation coefficients, and introducing a new one.

Apparent Diffusion Coefficient and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Pancreatic Cancer: Characteristics and Correlation With Histopathologic Parameters.

PubMed

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.

Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

ERIC Educational Resources Information Center

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…

Ghost imaging based on Pearson correlation coefficients

NASA Astrophysics Data System (ADS)

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

2015-05-01

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. Project supported by the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2013YQ030595) and the National High Technology Research and Development Program of China (Grant No. 2013AA122902).

Correlation Between the Field Line and Particle Diffusion Coefficients in the Stochastic Fields of a Tokamak

NASA Astrophysics Data System (ADS)

Calvin, Mark; Punjabi, Alkesh

1996-11-01

We use the method of quasi-magnetic surfaces to calculate the correlation between the field line and particle diffusion coefficients. The magnetic topology of a tokamak is perturbed by a spectrum of neighboring resonant resistive modes. The Hamiltonian equations of motion for the field line are integrated numerically. Poincare plots of the quasi-magnetic surfaces are generated initially and after the field line has traversed a considerable distance. From the areas of the quasi-magnetic surfaces and the field line distance, we estimate the field line diffusion coefficient. We start plasma particles on the initial quasi-surface, and calculate the particle diffusion coefficient from our Monte Carlo method (Punjabi A., Boozer A., Lam M., Kim H. and Burke K., J. Plasma Phys.), 44, 405 (1990). We then estimate the correlation between the particle and field diffusion as the strength of the resistive modes is varied.

Correlation between mass transfer coefficient kLa and relevant operating parameters in cylindrical disposable shaken bioreactors on a bench-to-pilot scale

PubMed Central

2013-01-01

Background 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. Results 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. Conclusion 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. PMID:24289110

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

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.

Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis.

PubMed

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]).

Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

PubMed

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.

Correlation Between Timed Barium Esophagogram and Esophageal Transit Scintigraphy Results in Achalasia.

PubMed

Park, Yoo Mi; Jeon, Han Ho; Park, Jae Jun; Kim, Jie-Hyun; Youn, Young Hoon; Park, Hyojin

2015-08-01

Timed barium esophagogram (TBE) and esophageal transit scintigraphy (ETS) have been adopted as useful ways to evaluate achalasia patients. TBE has merit as a simple, non-invasive, and convenient method. The study sought to compare the results of these two tests and verify their usefulness in evaluating treatment response. In addition, we assessed whether TBE could effectively replace ETS through correlation analysis. The medical records of 50 achalasia patients treated between September 2011 and June 2014 were reviewed retrospectively. The height and width of the barium column at 1, 2, and 5 min were measured by TBE. Half-life (T 1/2, min) and R 30 (percentage of remaining radioactivity 30 s after radioisotope ingestion) were measured by ETS. Both tests were performed before and after treatment, and the tests were carried out 1 and 2 days after procedures. And we analyzed the correlation between the parameters from the two tests. The parameters of TBE and ETS were improved after treatment (p < 0.05). Before treatment, the height and width results at 5 min from TBE positively correlated with the T 1/2 parameter from ETS (correlation coefficients of 0.59 and 0.75, respectively). After treatment, the correlation coefficients between the 5-min height and width of the barium column by TBE and T 1/2 by ETS were 0.55 and 0.46, respectively. Both TBE and ETS are useful modalities in assessing esophageal emptying and response to achalasia treatment. TBE and ETS results have a statistically significant correlation both pre- and post-treatment. We suggest that TBE could effectively replace ETS for the assessment of achalasia.

A robust bayesian estimate of the concordance correlation coefficient.

PubMed

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.

On the relationship between cumulative correlation coefficients and the quality of crystallographic data sets.

PubMed

Wang, Jimin; Brudvig, Gary W; Batista, Victor S; Moore, Peter B

2017-12-01

In 2012, Karplus and Diederichs demonstrated that the Pearson correlation coefficient CC 1/2 is a far better indicator of the quality and resolution of crystallographic data sets than more traditional measures like merging R-factor or signal-to-noise ratio. More specifically, they proposed that CC 1/2 be computed for data sets in thin shells of increasing resolution so that the resolution dependence of that quantity can be examined. Recently, however, the CC 1/2 values of entire data sets, i.e., cumulative correlation coefficients, have been used as a measure of data quality. Here, we show that the difference in cumulative CC 1/2 value between a data set that has been accurately measured and a data set that has not is likely to be small. Furthermore, structures obtained by molecular replacement from poorly measured data sets are likely to suffer from extreme model bias. © 2017 The Protein Society.

Correlation between mass transfer coefficient kLa and relevant operating parameters in cylindrical disposable shaken bioreactors on a bench-to-pilot scale.

PubMed

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.

aCORN: An experiment to measure the electron-antineutrino correlation coefficient in free neutron decay.

PubMed

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.

Experimental rotordynamic coefficient results for honeycomb seals

NASA Technical Reports Server (NTRS)

Elrod, David A.; Childs, Dara W.

1988-01-01

Test results (leakage and rotordynamic coefficients) are presented for seven honeycomb-stator smooth-rotor seals. Tests were carried out with air at rotor speeds up to 16,000 cpm and supply pressures up to 8.2 bars. Test results for the seven seals are compared, and the most stable configuration is identified based on the whirl frequency ratio. Results from tests of a smooth-rotor/smooth-stator seal, a teeth-on-stator labyrinth seal, and the most stable honeycomb seal are compared.

Partition coefficients of organic compounds in lipid-water systems and correlations with fish bioconcentration factors

USGS Publications Warehouse

Chiou, C.T.

1985-01-01

Triolein-water partition coefficients (KtW) have been determined for 38 slightly water-soluble organic compounds, and their magnitudes have been compared with the corresponding octanol-water partition coefficients (KOW). In the absence of major solvent-solute interaction effects in the organic solvent phase, the conventional treatment (based on Raoult's law) predicts sharply lower partition coefficients for most of the solutes in triolein because of its considerably higher molecular weight, whereas the Flory-Huggins treatment predicts higher partition coefficients with triolein. The data are in much better agreement with the Flory-Huggins model. As expected from the similarity in the partition coefficients, the water solubility (which was previously found to be the major determinant of the KOW) is also the major determinant for the Ktw. When the published BCF values (bioconcentration factors) of organic compounds in fish are based on the lipid content rather than on total mass, they are approximately equal to the Ktw, which suggests at least near equilibrium for solute partitioning between water and fish lipid. The close correlation between Ktw and Kow suggests that Kow is also a good predictor for lipid-water partition coefficients and bioconcentration factors.

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

PubMed

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.

Virial Coefficients for the Liquid Argon

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

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

Effects of soot absorption coefficient-Planck function correlation on radiative heat transfer in oxygen-enriched propane turbulent diffusion flame

NASA Astrophysics Data System (ADS)

Consalvi, J. L.; Nmira, F.

2016-03-01

The main objective of this article is to quantify the influence of the soot absorption coefficient-Planck function correlation on radiative loss and flame structure in an oxygen-enhanced propane turbulent diffusion flame. Calculations were run with and without accounting for this correlation by using a standard k-ε model and the steady laminar flamelet model (SLF) coupled to a joint Probability Density Function (PDF) of mixture fraction, enthalpy defect, scalar dissipation rate, and soot quantities. The PDF transport equation is solved by using a Stochastic Eulerian Field (SEF) method. The modeling of soot production is carried out by using a flamelet-based semi-empirical acetylene/benzene soot model. Radiative heat transfer is modeled by using a wide band correlated-k model and turbulent radiation interactions (TRI) are accounted for by using the Optically-Thin Fluctuation Approximation (OTFA). Predicted soot volume fraction, radiant wall heat flux distribution and radiant fraction are in good agreement with the available experimental data. Model results show that soot absorption coefficient and Planck function are negatively correlated in the region of intense soot emission. Neglecting this correlation is found to increase significantly the radiative loss leading to a substantial impact on flame structure in terms of mean and rms values of temperature. In addition mean and rms values of soot volume fraction are found to be less sensitive to the correlation than temperature since soot formation occurs mainly in a region where its influence is low.

aCORN: An experiment to measure the electron-antineutrino correlation coefficient in free neutron decay

DOE PAGES

Collett, B.; Bateman, F.; Bauder, W. K.; ...

2017-08-01

Here, we describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. This 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. We present details of the method, apparatus, detectors, data acquisition, and data reduction scheme, along with a discussion of the important systematic effects.

aCORN: An experiment to measure the electron-antineutrino correlation coefficient in free neutron decay

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

Collett, B.; Bateman, F.; Bauder, W. K.

Here, we describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. This 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. We present details of the method, apparatus, detectors, data acquisition, and data reduction scheme, along with a discussion of the important systematic effects.

SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.

PubMed

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.

Technical characterization of dialysis fluid flow and mass transfer rate in dialyzers with various filtration coefficients using dimensionless correlation equation.

PubMed

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.

Simultaneous characterization of lateral lipid and prothrombin diffusion coefficients by z-scan fluorescence correlation spectroscopy.

PubMed

Stefl, Martin; Kułakowska, Anna; Hof, Martin

2009-08-05

A new (to our knowledge) robust approach for the determination of lateral diffusion coefficients of weakly bound proteins is applied for the phosphatidylserine specific membrane interaction of bovine prothrombin. It is shown that z-scan fluorescence correlation spectroscopy in combination with pulsed interleaved dual excitation allows simultaneous monitoring of the lateral diffusion of labeled protein and phospholipids. Moreover, from the dependencies of the particle numbers on the axial sample positions at different protein concentrations phosphatidylserine-dependent equilibrium dissociation constants are derived confirming literature values. Increasing the amount of membrane-bound prothrombin retards the lateral protein and lipid diffusion, indicating coupling of both processes. The lateral diffusion coefficients of labeled lipids are considerably larger than the simultaneously determined lateral diffusion coefficients of prothrombin, which contradicts findings reported for the isolated N-terminus of prothrombin.

AN EMPIRICAL INVESTIGATION OF THE EFFECTS OF NONNORMALITY UPON THE SAMPLING DISTRIBUTION OF THE PROJECT MOMENT CORRELATION COEFFICIENT.

ERIC Educational Resources Information Center

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

PubMed Central

Alajmi, Mahdi; Shalwan, Abdullah

2015-01-01

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. PMID:28793431

Correlation between Mechanical Properties with Specific Wear Rate and the Coefficient of Friction of Graphite/Epoxy Composites.

PubMed

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.

Robust spectral-domain optical coherence tomography speckle model and its cross-correlation coefficient analysis

PubMed Central

Liu, Xuan; Ramella-Roman, Jessica C.; Huang, Yong; Guo, Yuan; Kang, Jin U.

2013-01-01

In this study, we proposed a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validated our model and used the simulation method to study the statistical properties of cross-correlation coefficients (XCC) between Ascans which have been recently applied in transverse motion analysis by our group. The results of simulation show that over sampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an under estimate of motion which can be corrected; lateral heterogeneity of sample leads to an over estimate of motion for a few pixels corresponding to the structural boundary. PMID:23456001

Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data.

PubMed

de Winter, Joost C F; Gosling, Samuel D; Potter, Jeff

2016-09-01

The Pearson product–moment correlation coefficient ( r p ) and the Spearman rank correlation coefficient ( r s ) are widely used in psychological research. We compare r p and r s on 3 criteria: variability, bias with respect to the population value, and robustness to an outlier. Using simulations across low (N = 5) to high (N = 1,000) sample sizes we show that, for normally distributed variables, r p and r s have similar expected values but r s is more variable, especially when the correlation is strong. However, when the variables have high kurtosis, r p is more variable than r s . Next, we conducted a sampling study of a psychometric dataset featuring symmetrically distributed data with light tails, and of 2 Likert-type survey datasets, 1 with light-tailed and the other with heavy-tailed distributions. Consistent with the simulations, r p had lower variability than r s in the psychometric dataset. In the survey datasets with heavy-tailed variables in particular, r s had lower variability than r p , and often corresponded more accurately to the population Pearson correlation coefficient ( R p ) than r p did. The simulations and the sampling studies showed that variability in terms of standard deviations can be reduced by about 20% by choosing r s instead of r p . In comparison, increasing the sample size by a factor of 2 results in a 41% reduction of the standard deviations of r s and r p . In conclusion, r p is suitable for light-tailed distributions, whereas r s is preferable when variables feature heavy-tailed distributions or when outliers are present, as is often the case in psychological research. PsycINFO Database Record (c) 2016 APA, all rights reserved

CORRELATION BETWEEN METAL-CERAMIC BOND STRENGTH AND COEFFICIENT OF LINEAR THERMAL EXPANSION DIFFERENCE

PubMed Central

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 °C-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. PMID:19274398

Correlation of heat transfer coefficient in quenching process using ABAQUS

NASA Astrophysics Data System (ADS)

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.

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

ERIC Educational Resources Information Center

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…

Application of Cross-Correlation Greens Function Along With FDTD for Fast Computation of Envelope Correlation Coefficient Over Wideband for MIMO Antennas

NASA Astrophysics Data System (ADS)

Sarkar, Debdeep; Srivastava, Kumar Vaibhav

2017-02-01

In this paper, the concept of cross-correlation Green's functions (CGF) is used in conjunction with the finite difference time domain (FDTD) technique for calculation of envelope correlation coefficient (ECC) of any arbitrary MIMO antenna system over wide frequency band. Both frequency-domain (FD) and time-domain (TD) post-processing techniques are proposed for possible application with this FDTD-CGF scheme. The FDTD-CGF time-domain (FDTD-CGF-TD) scheme utilizes time-domain signal processing methods and exhibits significant reduction in ECC computation time as compared to the FDTD-CGF frequency domain (FDTD-CGF-FD) scheme, for high frequency-resolution requirements. The proposed FDTD-CGF based schemes can be applied for accurate and fast prediction of wideband ECC response, instead of the conventional scattering parameter based techniques which have several limitations. Numerical examples of the proposed FDTD-CGF techniques are provided for two-element MIMO systems involving thin-wire half-wavelength dipoles in parallel side-by-side as well as orthogonal arrangements. The results obtained from the FDTD-CGF techniques are compared with results from commercial electromagnetic solver Ansys HFSS, to verify the validity of proposed approach.

Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

PubMed

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.

PubMed

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.

Heritabilities and genetic correlations of economic traits in Iranian native fowl and estimated genetic trend and inbreeding coefficients.

PubMed

Kamali, M A; Ghorbani, S H; Sharbabak, M Moradi; Zamiri, M J

2007-08-01

1. Genetic parameters were estimated in a base population of a closed experimental strain of fowl. Data were obtained on 21 245 Iranian native hens (breeding centre for Fars province) subject to 8 successive generations of selection. This population had been selected for body weight at 12 weeks of age (BW12) and egg number during the first 12 weeks of the laying period (EN), mean egg weight (EW) at weeks 28, 30 and 32, and age at sexual maturity (ASM). 2. The method of multi-traits restricted maximum likelihood with an animal model was used to estimate genetic parameters. Resulting heritabilities for BW12, EN, EW and ASM were 0.68 +/- 0.02, 0.40 +/- 0.02, 0.64 +/- 0.02 and 0.49 +/- 0.02, respectively. 3. Genetic correlations between BW12 and EN, EW and ASM were 0.11 +/- 0.33, 0.54 +/- 0.21 and -0.12 +/- 0.03, respectively. Genetic correlations between EN and EW and ASM were -0.09 +/- 0.03 and -0.85 +/- 0.01, respectively, while between EW and ASM, it was 0.05 +/- 0.03. 4. The overall predicted genetic gains, after 7 generations of selection, estimated by the regression coefficients of the breeding value on generation number were equal to 22.7, 0.17, 0.04 and -1.38, for BW12, EN, EW and ASM, respectively. 5. A pedigree file of 21 245 female and male birds was used to calculate inbreeding coefficients and their influence on production and reproduction traits. Average inbreeding coefficients for all birds, inbred birds, female birds and male birds were 0.048, 0.673, 0.055 and 0.047%, respectively. Regression coefficients of BW12, ASM, EN and EW on inbreeding coefficient for all birds were equal to 0.51 +/- 0.001, 0.31 +/- 0.003, -0.51 +/- 0.003 and 0.03 +/- 0.001, respectively.

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

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

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

Correlation dependence of the volumetric thermal expansion coefficient of metallic aluminum on its heat capacity

NASA Astrophysics Data System (ADS)

Bodryakov, V. Yu.; Bykov, A. A.

2016-05-01

The correlation between the volumetric thermal expansion coefficient β( T) and the heat capacity C( T) of aluminum is considered in detail. It is shown that a clear correlation is observed in a significantly wider temperature range, up to the melting temperature of the metal, along with the low-temperature range where it is linear. The significant deviation of dependence β( C) from the low-temperature linear behavior is observed up to the point where the heat capacity achieves the classical Dulong-Petit limit of 3 R ( R is the universal gas constant).

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

PubMed

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.

Spaced antenna diversity in temperate latitude meteor burst systems operating near 40 MHz - Variation of signal cross-correlation coefficients with antenna separation

NASA Astrophysics Data System (ADS)

Cannon, Paul S.; Shukla, Anil K.; Lester, Mark

1993-04-01

We have studied 37-MHz signals received over an 800-km temperate latitude path using 400-W continuous wave transmissions. Signals collected during a 9-day period in February 1990 on two antennas at separations of 5, 10, and 20 lambda were analyzed. Three signal categories were identified (overdense, underdense, and not known (NK)) and cross-correlation coefficients between the signals received by the two antennas were calculated for each signal category. No spatial variation, and in particular no decrease, in average cross-correlation coefficient was observed for underdense or NK signals as the antenna spacing was increased from 5 to 20 lambda. At each antenna separation the cross-correlation coefficients of these two categories were strongly dependent on time. Overdense signals, however, showed no cross-correlation time dependency at 5 and 10 lambda, but there was a strong time dependency at 20 lambda. Recommendations are made in regard to the optimum antenna spacing for a meteor burst communication system using spaced antenna diversity.

Gene interference regulates aquaporin-4 expression in swollen tissue of rats with cerebral ischemic edema: Correlation with variation in apparent diffusion coefficient.

PubMed

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 < 0.01). These findings suggest that upregulated aquaporin-4 expression is likely to be the main molecular mechanism of intracellular edema and may be the molecular basis for decreased relative apparent diffusion coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time

The Effect of a Fluorophore Photo-Physics on the Lipid Vesicle Diffusion Coefficient Studied by Fluorescence Correlation Spectroscopy.

PubMed

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.

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

NASA Astrophysics Data System (ADS)

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.

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

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

PubMed

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.

Correlation of standardized uptake value and apparent diffusion coefficient in integrated whole-body PET/MRI of primary and recurrent cervical cancer.

PubMed

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 < 0.05). When subdivided in primary and recurrent tumors, primary tumors and associated primary lymph node metastases revealed a significant and strong inverse correlation between SUVmax and ADCmin (R = -0.692, p < 0.001), whereas recurrent cancer lesions did not show a significant 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.

Nuclear Overhauser Enhancement Imaging of Glioblastoma at 7 Tesla: Region Specific Correlation with Apparent Diffusion Coefficient and Histology

PubMed Central

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

Objective 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. Patients and Methods 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. Results Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation 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 (rSp patient3 = 0.69 and rSp patient15 = 0.87, p<0.05), while the correlation of ADC and cellularity was heterogeneous (rSp patient3 = 0.545 (p = 0.067), rSp patient4 = -0.021 (p = 0.948), rSp patient15 = -0.755 (p = 0.005)). Discussion NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell

Python Waveform Cross-Correlation

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

Templeton, Dennise

PyWCC is a tool to compute seismic waveform cross-correlation coefficients on single-component or multiple-component seismic data across a network of seismic sensors. PyWCC compares waveform data templates with continuous seismic data, associates the resulting detections, identifies the template with the highest cross-correlation coefficient, and outputs a catalog of detections above a user-defined absolute cross-correlation threshold value.

Spectral regression and correlation coefficients of some benzaldimines and salicylaldimines in different solvents

NASA Astrophysics Data System (ADS)

Hammud, Hassan H.; Ghannoum, Amer; Masoud, Mamdouh S.

2006-02-01

Sixteen Schiff bases obtained from the condensation of benzaldehyde or salicylaldehyde with various amines (aniline, 4-carboxyaniline, phenylhydrazine, 2,4-dinitrophenylhydrazine, ethylenediamine, hydrazine, o-phenylenediamine and 2,6-pyridinediamine) are studied with UV-vis spectroscopy to observe the effect of solvents, substituents and other structural factors on the spectra. The bands involving different electronic transitions are interpreted. Computerized analysis and multiple regression techniques were applied to calculate the regression and correlation coefficients based on the equation that relates peak position λmax to the solvent parameters that depend on the H-bonding ability, refractive index and dielectric constant of solvents.

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

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

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

An agreement coefficient for image comparison

USGS Publications Warehouse

Ji, Lei; Gallo, Kevin

2006-01-01

Combination of datasets acquired from different sensor systems is necessary to construct a long time-series dataset for remotely sensed land-surface variables. Assessment of the agreement of the data derived from various sources is an important issue in understanding the data continuity through the time-series. Some traditional measures, including correlation coefficient, coefficient of determination, mean absolute error, and root mean square error, are not always optimal for evaluating the data agreement. For this reason, we developed a new agreement coefficient for comparing two different images. The agreement coefficient has the following properties: non-dimensional, bounded, symmetric, and distinguishable between systematic and unsystematic differences. The paper provides examples of agreement analyses for hypothetical data and actual remotely sensed data. The results demonstrate that the agreement coefficient does include the above properties, and therefore is a useful tool for image comparison.

Endometrial cancer: correlation of apparent diffusion coefficient (ADC) with tumor cellularity and tumor grade.

PubMed

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.

Drag Coefficient Estimation in Orbit Determination

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

PubMed Central

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

Correlation of the apparent diffusion coefficient and the standardized uptake value in neoplastic lesions: a meta-analysis.

PubMed

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%, P<0.001), which indicated a relatively weak negative correlation. 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 Bayesian Framework for Estimating the Concordance Correlation Coefficient Using Skew-elliptical Distributions.

PubMed

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.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations

PubMed Central

Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2016-01-01

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. PMID:27886393

Correlation between tissue metabolism and cellularity assessed by standardized uptake value and apparent diffusion coefficient in peritoneal metastasis.

PubMed

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.

PubMed

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).

Complex versus Simple Modeling for DIF Detection: When the Intraclass Correlation Coefficient (?) of the Studied Item Is Less Than the ? of the Total Score

ERIC Educational Resources Information Center

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…

Building Area Extraction from Polarimetric SAR Data via Stationarity Detection and Circular-Pol Correlation Coefficient

NASA Astrophysics Data System (ADS)

Xiang, Deliang; Su, Yi; Ban, Yifeng

2015-04-01

Since the buildings have complex geometries and may be misclassified as forests or mountains with volume scattering due to the significant cross-pol backscatter and lack reflection symmetry, especially the slant-oriented buildings, building area extraction is a challenging problem. In this paper, the time-frequency decomposition technique is adopted to acquire subaperture images, which correspond to the same scene responses under different azimuthal look angles. Stationarity detection approach with polarimetric G0 distribution is proposed to extract ortho-orientedbuildings and the circular polarization correlation coefficient is optimal in characterizing slant-oriented buildings. We test the aforementioned method using ESAR image with L-band. The results demonstrate that the proposed method can effectively extract both ortho-oriented and slant-oriented buildings and the overall detection accuracy as well as kappa value is 10%-20% higher than the compared methods.

Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

PubMed

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.

A Performance Comparison on the Probability Plot Correlation Coefficient Test using Several Plotting Positions for GEV Distribution.

NASA Astrophysics Data System (ADS)

Ahn, Hyunjun; Jung, Younghun; Om, Ju-Seong; Heo, Jun-Haeng

2014-05-01

It is very important to select the probability distribution in Statistical hydrology. Goodness of fit test is a statistical method that selects an appropriate probability model for a given data. The probability plot correlation coefficient (PPCC) test as one of the goodness of fit tests was originally developed for normal distribution. Since then, this test has been widely applied to other probability models. The PPCC test is known as one of the best goodness of fit test because it shows higher rejection powers among them. In this study, we focus on the PPCC tests for the GEV distribution which is widely used in the world. For the GEV model, several plotting position formulas are suggested. However, the PPCC statistics are derived only for the plotting position formulas (Goel and De, In-na and Nguyen, and Kim et al.) in which the skewness coefficient (or shape parameter) are included. And then the regression equations are derived as a function of the shape parameter and sample size for a given significance level. In addition, the rejection powers of these formulas are compared using Monte-Carlo simulation. Keywords: Goodness-of-fit test, Probability plot correlation coefficient test, Plotting position, Monte-Carlo Simulation ACKNOWLEDGEMENTS This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Common pediatric cerebellar tumors: correlation between cell densities and apparent diffusion coefficient metrics.

PubMed

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 < .05) and minimum tumor ADCs (ρ = -0.736, P < .05) of common pediatric cerebellar tumors. There was no 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 < .05). In atypical teratoid rhabdoid tumors, no 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

Investigation of two-phase heat transfer coefficients of argon-freon cryogenic mixed refrigerants

NASA Astrophysics Data System (ADS)

Baek, Seungwhan; Lee, Cheonkyu; Jeong, Sangkwon

2014-11-01

Mixed refrigerant Joule Thomson refrigerators are widely used in various kinds of cryogenic systems these days. Although heat transfer coefficient estimation for a multi-phase and multi-component fluid in the cryogenic temperature range is necessarily required in the heat exchanger design of mixed refrigerant Joule Thomson refrigerators, it has been rarely discussed so far. In this paper, condensation and evaporation heat transfer coefficients of argon-freon mixed refrigerant are measured in a microchannel heat exchanger. A Printed Circuit Heat Exchanger (PCHE) with 340 μm hydraulic diameter has been developed as a compact microchannel heat exchanger and utilized in the experiment. Several two-phase heat transfer coefficient correlations are examined to discuss the experimental measurement results. The result of this paper shows that cryogenic two-phase mixed refrigerant heat transfer coefficients can be estimated by conventional two-phase heat transfer coefficient correlations.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

PubMed

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.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

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

2017-01-01

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

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Nuclear Overhauser Enhancement imaging of glioblastoma at 7 Tesla: region specific correlation with apparent diffusion coefficient and histology.

PubMed

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, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation 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, p<0.05), while the correlation 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

Momentum, sensible heat and CO2 correlation coefficient variability: what can we learn from 20 years of continuous eddy covariance measurements?

NASA Astrophysics Data System (ADS)

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

Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results.

PubMed

Sagiyama, Koji; Watanabe, Yuji; Kamei, Ryotaro; Hong, Sungtak; Kawanami, Satoshi; Matsumoto, Yoshihiro; Honda, Hiroshi

2017-12-01

To investigate the usefulness of voxel-based analysis of standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) for evaluating soft-tissue tumour malignancy with a PET/MR system. Thirty-five subjects with either ten low/intermediate-grade tumours or 25 high-grade tumours were prospectively enrolled. Zoomed diffusion-weighted and fluorodeoxyglucose ( 18 FDG)-PET images were acquired along with fat-suppressed T2-weighted images (FST2WIs). Regions of interest (ROIs) were drawn on FST2WIs including the tumour in all slices. ROIs were pasted onto PET and ADC-maps to measure SUVs and ADCs within tumour ROIs. Tumour volume, SUVmax, ADCminimum, the heterogeneity and the correlation coefficients of SUV and ADC were recorded. The parameters of high- and low/intermediate-grade groups were compared, and receiver operating characteristic (ROC) analysis was also performed. The mean correlation coefficient for SUV and ADC in high-grade sarcomas was lower than that of low/intermediate-grade tumours (-0.41 ± 0.25 vs. -0.08 ± 0.34, P < 0.01). Other parameters did not differ significantly. ROC analysis demonstrated that correlation coefficient showed the best diagnostic performance for differentiating the two groups (AUC 0.79, sensitivity 96.0%, specificity 60%, accuracy 85.7%). SUV and ADC determined via PET/MR may be useful for differentiating between high-grade and low/intermediate-grade soft tissue tumours. • PET/MR allows voxel-based comparison of SUVs and ADCs in soft-tissue tumours. • A comprehensive assessment of internal heterogeneity was performed with scatter plots. • SUVmax or ADCminimum could not differentiate high-grade sarcoma from low/intermediate-grade tumours. • Only the correlation coefficient between SUV and ADC differentiated the two groups. • The correlation coefficient showed the best diagnostic performance by ROC analysis.

MEASUREMENT OF THE CORRELATION COEFFICIENT Cnn AT 90 AND AN ENERGY OF 315 MEV FOR THE ELASTIC PP-SCATTERING

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

Vasilevskii, I.M.; Vishnyakov, V.V.; Iliescu, E.

1960-01-01

The spin correlation coefficient C/sub nn/ was measured for p-p scattering at 90 deg (c.m.s.) and 315 Mev and found to be 0.52 plus or minus 0.20. Calibration experiments on the polarization of protons at 640 Mev gave C/ sub nn/ = 0.7 plus or minus 0.3. (D.L.C.)

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

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.

Diabetic Erythrocytes Test by Correlation Coefficient

PubMed Central

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

Distance correlation methods for discovering associations in large astrophysical databases

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

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

2014-01-20

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

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient

PubMed Central

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

2017-01-01

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. PMID:28855260

A Bayesian estimate of the concordance correlation coefficient with skewed data.

PubMed

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.

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data.

PubMed

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.

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data

PubMed Central

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

2014-01-01

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 (6 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. PMID:25168954

Improvement of geomagnetic core field modeling with a priori information about Gauss coefficient correlations

NASA Astrophysics Data System (ADS)

Schachtschneider, R.; Rother, M.; Lesur, V.

2013-12-01

We introduce a method that enables us to account for existing correlations between Gauss coefficients in core field modelling. The information about the correlations are obtained from a highly accurate field model based on CHAMP data, e.g. the GRIMM-3 model. We compute the covariance matrices of the geomagnetic field, the secular variation, and acceleration up to degree 18 and use these in the regularization scheme of the core field inversion. For testing our method we followed two different approaches by applying it to two different synthetic satellite data sets. The first is a short data set with a time span of only three months. Here we test how the information about correlations help to obtain an accurate model when only very little information are available. The second data set is a large one covering several years. In this case, besides reducing the residuals in general, we focus on the improvement of the model near the boundaries of the data set where the accerelation is generally more difficult to handle. In both cases the obtained covariance matrices are included in the damping scheme of the regularization. That way information from scales that could otherwise not be resolved by the data can be extracted. We show that by using this technique we are able to improve the models of the field and the secular variation for both, the short and the long term data set, compared to approaches using more conventional regularization techniques.

Complementarity and Correlations

NASA Astrophysics Data System (ADS)

Maccone, Lorenzo; Bruß, Dagmar; Macchiavello, Chiara

2015-04-01

We provide an interpretation of entanglement based on classical correlations between measurement outcomes of complementary properties: States that have correlations beyond a certain threshold are entangled. The reverse is not true, however. We also show that, surprisingly, all separable nonclassical states exhibit smaller correlations for complementary observables than some strictly classical states. We use mutual information as a measure of classical correlations, but we conjecture that the first result holds also for other measures (e.g., the Pearson correlation coefficient or the sum of conditional probabilities).

Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG-fMRI recordings.

PubMed

Ji, Hong; Petro, Nathan M; Chen, Badong; Yuan, Zejian; Wang, Jianji; Zheng, Nanning; Keil, Andreas

2018-02-06

Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework. This approach accomplishes three tasks: (1) It provides a measure for testing multivariate correlation and multivariate uncorrelation of the two modalities; (2) it provides criterion for the selection of EEG features; (3) it performs a screening of relevant EEG information by grouping the EEG channels into clusters to improve efficiency and to reduce computational load when searching for the best predictors of the BOLD signal. The present report applies this approach to a data set with concurrent recordings of steady-state-visual evoked potentials (ssVEPs) and fMRI, recorded while observers viewed phase-reversing Gabor patches. We test the hypothesis that fluctuations in visuo-cortical mass potentials systematically covary with BOLD fluctuations not only in visual cortical, but also in anterior temporal and prefrontal areas. Results supported the hypothesis and showed that the xMCC-based analysis provides straightforward identification of neurophysiological plausible brain regions with EEG-fMRI covariance. Furthermore xMCC converged with other extant methods for EEG-fMRI analysis. © 2018 The Authors Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Evaluation of estimation methods for organic carbon normalized sorption coefficients

USGS Publications Warehouse

Baker, James R.; Mihelcic, James R.; Luehrs, Dean C.; Hickey, James P.

1997-01-01

A critically evaluated set of 94 soil water partition coefficients normalized to soil organic carbon content (Koc) is presented for 11 classes of organic chemicals. This data set is used to develop and evaluate Koc estimation methods using three different descriptors. The three types of descriptors used in predicting Koc were octanol/water partition coefficient (Kow), molecular connectivity (mXt) and linear solvation energy relationships (LSERs). The best results were obtained estimating Koc from Kow, though a slight improvement in the correlation coefficient was obtained by using a two-parameter regression with Kow and the third order difference term from mXt. Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than mXt but not as good as the correlation with Koc. The correlation to predict Koc from Kow was developed for 72 chemicals; log Koc = 0.903* log Kow + 0.094. This correlation accounts for 91% of the variability in the data for chemicals with log Kow ranging from 1.7 to 7.0. The expression to determine the 95% confidence interval on the estimated Koc is provided along with an example for two chemicals of different hydrophobicity showing the confidence interval of the retardation factor determined from the estimated Koc. The data showed that Koc is not likely to be applicable for chemicals with log Kow < 1.7. Finally, the Koc correlation developed using Kow as a descriptor was compared with three nonclass-specific correlations and two 'commonly used' class-specific correlations to determine which method(s) are most suitable.

[Examination of diagnosis procedure combination survey data that influence function evaluation coefficient II].

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Kobayashi, Eiji; Yokota, Kuninobu

2015-01-01

On the basis of Diagnosis Procedure Combination (DPC) survey data, the factors that increase the value of function evaluation coefficient II were considered. A total of 1,505 hospitals were divided into groups I, II, and III, and the following items were considered. 1. Significant differences in function evaluation coefficient II and DPC survey data. 2. Examination of using the Mahalanobis-Taguchi (MT) method. 3. Correlation between function evaluation coefficient II and each DPC survey data item. 1. Function evaluation coefficient II was highest in group II. Group I hospitals showed the highest bed capacity, and numbers of hospitalization days, operations, chemotherapies, radiotherapies and general anesthesia procedures. 2. Using the MT method, we found that the number of ambulance conveyances was effective factor in group I hospitals, the number of general anesthesia procedures was effective factor in group II hospitals, and the bed capacity was effective factor in group III hospitals. 3. In group I hospitals, function evaluation coefficient II significantly correlated to the numbers of ambulance conveyances and chemotherapies. In group II hospitals, function evaluation coefficient II significantly correlated to bed capacity, the numbers of ambulance conveyances, hospitalization days, operations, general anesthesia procedures, and mean hospitalization days. In group III hospitals, function evaluation coefficient II significantly correlated to all items. The factors that improve the value of function evaluation coefficient II were the increases in the numbers of ambulance conveyances, chemotherapies and radiotherapies in group I hospitals, increases in the numbers of hospitalization days, operations, ambulance conveyances and general anesthesia procedures in group II hospitals, and increases in the numbers of hospitalization days, operations and ambulance conveyances. These results indicate that the profit of a hospital will increase, which will lead to medical

Correlation of apparent diffusion coefficient ratio on 3.0 T MRI with prostate cancer Gleason score.

PubMed

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 < 0.001) demonstrated a stronger 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.

Experimental investigation of heat transfer coefficient of mini-channel PCHE (printed circuit heat exchanger)

NASA Astrophysics Data System (ADS)

Kwon, Dohoon; Jin, Lingxue; Jung, WooSeok; Jeong, Sangkwon

2018-06-01

Heat transfer coefficient of a mini-channel printed circuit heat exchanger (PCHE) with counter-flow configuration is investigated. The PCHE used in the experiments is two layered (10 channels per layer) and has the hydraulic diameter of 1.83 mm. Experiments are conducted under various cryogenic heat transfer conditions: single-phase, boiling and condensation heat transfer. Heat transfer coefficients of each experiments are presented and compared with established correlations. In the case of the single-phase experiment, empiricial correlation of modified Dittus-Boelter correlation was proposed, which predicts the experimental results with 5% error at Reynolds number range from 8500 to 17,000. In the case of the boiling experiment, film boiling phenomenon occurred dominantly due to large temperature difference between the hot side and the cold side fluids. Empirical correlation is proposed which predicts experimental results with 20% error at Reynolds number range from 2100 to 2500. In the case of the condensation experiment, empirical correlation of modified Akers correlation was proposed, which predicts experimental results with 10% error at Reynolds number range from 3100 to 6200.

Rate-coefficients and polarization results for the electron-impact excitation of Ar+ ion

NASA Astrophysics Data System (ADS)

Srivastava, Rajesh; Dipti, Dipti

2016-05-01

A fully relativistic distorted wave theory has been employed to study the electron impact excitation in Ar+ ion. Results have been obtained for the excitation cross-sections and rate-coefficients for the transitions from the ground state 3p5 (J = 3/2) to fine-structure levels of excited states 3p4 4 s, 3p4 4 p , 3p4 5 s, 3p4 5 p, 3p4 3 d and 3p4 4 d. Polarization of the radiation following the excitation has been calculated using the obtained magnetic sub-level cross-sections. Comparison of the present rate-coefficients is also done with the previously reported theoretical results for some unresolved fine structure transitions. Work is supported by DAE-BRNS Mumbai and CSIR, New Delhi.

Pancreatic neuroendocrine tumour: Correlation of apparent diffusion coefficient or WHO classification with recurrence-free survival.

PubMed

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, p<0.001 and ρ=-0.55, p=0.001 respectively). RFS was significantly associated with WHO classification (p=0.007), but not with the ADC value (p=0.569). The ADC value of pNETs is moderately correlated 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.

Precancerous esophageal epithelia are associated with significantly increased scattering coefficients

PubMed Central

Su, Jing-Wei; Lin, Yang-Hsien; Chiang, Chun-Ping; Lee, Jang-Ming; Hsieh, Chao-Mao; Hsieh, Min-Shu; Yang, Pei-Wen; Wang, Chen-Ping; Tseng, Ping-Huei; Lee, Yi-Chia; Sung, Kung-Bin

2015-01-01

The progression of epithelial precancers into cancer is accompanied by changes of tissue and cellular structures in the epithelium. Correlations between the structural changes and scattering coefficients of esophageal epithelia were investigated using quantitative phase images and the scattering-phase theorem. An ex vivo study of 14 patients demonstrated that the average scattering coefficient of precancerous epithelia was 37.8% higher than that of normal epithelia from the same patient. The scattering coefficients were highly correlated with morphological features including the cell density and the nuclear-to-cytoplasmic ratio. A high interpatient variability in scattering coefficients was observed and suggests identifying precancerous lesions based on the relative change in scattering coefficients. PMID:26504630

Information-theoretic indices usage for the prediction and calculation of octanol-water partition coefficient.

PubMed

Persona, Marek; Kutarov, Vladimir V; Kats, Boris M; Persona, Andrzej; Marczewska, Barbara

2007-01-01

The paper describes the new prediction method of octanol-water partition coefficient, which is based on molecular graph theory. The results obtained using the new method are well correlated with experimental values. These results were compared with the ones obtained by use of ten other structure correlated methods. The comparison shows that graph theory can be very useful in structure correlation research.

Correlation between electrical conductivity and apparent diffusion coefficient in breast cancer: effect of necrosis on magnetic resonance imaging.

PubMed

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.

The Free-Free Absorption Coefficients of the Negative Helium Ion

NASA Astrophysics Data System (ADS)

John, T. L.

1994-08-01

Free-free absorption coefficients of the negative helium ion are calculated by a phaseshift approximation, using continuum data that accurately account for electron-atom correlation and polarization. The approximation is considered to yield results within a few per cent of numerical values for wavelengths greater than 1 m, over the temperature range 1400-10080 K. These coefficients are expected to give the best current estimates of He - continuous absorption. Key words: atomic data - atomic processes - stars: atmospheres - infrared: general.

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.

PubMed

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.

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.

PubMed

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 (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.

Standardized uptake value and apparent diffusion coefficient of endometrial cancer evaluated with integrated whole-body PET/MR: Correlation with pathological prognostic factors.

PubMed

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 < 0.05). ADCmin was lower in tumors with higher grade, advanced stage, and cervical invasion (P < 0.05). The ratio of SUVmax to ADCmin was higher in tumors with higher grade, advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P < 0.05). SUVmax and ADCmin of endometrial cancer derived from integrated PET/MR are inversely correlated and are associated with pathological prognostic factors. © 2015 Wiley Periodicals, Inc.

Interpreting Regression Results: beta Weights and Structure Coefficients are Both Important.

ERIC Educational Resources Information Center

Thompson, Bruce

Various realizations have led to less frequent use of the "OVA" methods (analysis of variance--ANOVA--among others) and to more frequent use of general linear model approaches such as regression. However, too few researchers understand all the various coefficients produced in regression. This paper explains these coefficients and their…

Standardization of a fluconazole bioassay and correlation of results with those obtained by high-pressure liquid chromatography.

PubMed Central

Rex, J H; Hanson, L H; Amantea, M A; Stevens, D A; Bennett, J E

1991-01-01

An improved bioassay for fluconazole was developed. This assay is sensitive in the clinically relevant range (2 to 40 micrograms/ml) and analyzes plasma, serum, and cerebrospinal fluid specimens; bioassay results correlate with results obtained by high-pressure liquid chromatography (HPLC). Bioassay and HPLC analyses of spiked plasma, serum, and cerebrospinal fluid samples (run as unknowns) gave good agreement with expected values. Analysis of specimens from patients gave equivalent results by both HPLC and bioassay. HPLC had a lower within-run coefficient of variation (less than 2.5% for HPLC versus less than 11% for bioassay) and a lower between-run coefficient of variation (less than 5% versus less than 12% for bioassay) and was more sensitive (lower limit of detection, 0.1 micrograms/ml [versus 2 micrograms/ml for bioassay]). The bioassay is, however, sufficiently accurate and sensitive for clinical specimens, and its relative simplicity, low sample volume requirement, and low equipment cost should make it the technique of choice for analysis of routine clinical specimens. PMID:1854166

Correlation between incidences of self-inflicted burns and means of inbreeding coefficients, an ecologic study.

PubMed

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.

Experimental results for correlation-based wavefront sensing

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

Poyneer, L A; Palmer, D W; LaFortune, K N

2005-07-01

Correlation wave-front sensing can improve Adaptive Optics (AO) system performance in two keys areas. For point-source-based AO systems, Correlation is more accurate, more robust to changing conditions and provides lower noise than a centroiding algorithm. Experimental results from the Lick AO system and the SSHCL laser AO system confirm this. For remote imaging, Correlation enables the use of extended objects for wave-front sensing. Results from short horizontal-path experiments will show algorithm properties and requirements.

Evaluation of generalized heat-transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Evaluation of generalized heat transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Correlation between octanol/water and liposome/water distribution coefficients and drug absorption of a set of pharmacologically active compounds.

PubMed

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.

[Characteristics of high resolution diffusion weighted imaging apparent diffusion coefficient histogram and its correlations with cancer stages in patients with nasopharyngeal carcinoma].

PubMed

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 (<305 voxels, about 2 cm(3)) and large cancer group (≥2 cm(3)). The correlation between ADC 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 <0.05). There were significant differences in tumor voxels among patients with different T stages ( K =22.306, P <0.05). There were significant differences in the ADC(mean), ADC(25%), ADC(50%) among patients with different T stages in the small cancer group( K =8.409, 8.187, 8.699, all P <0.05), and the up-mentioned three indices were positively correlated with T staging ( r =0.221, 0.209, 0.235, all P <0.05). Skewness and kurtosis differed significantly between the groups with different cancer volume( t =-2.987, Z =-3.770, both P <0.05). Conclusion

Significant Differences Characterise the Correlation Coefficients between Biocide and Antibiotic Susceptibility Profiles in Staphylococcus aureus.

PubMed

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.

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

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

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

Optical scattering coefficient estimated by optical coherence tomography correlates with collagen content in ovarian tissue

NASA Astrophysics Data System (ADS)

Yang, Yi; Wang, Tianheng; Biswal, Nrusingh C.; Wang, Xiaohong; Sanders, Melinda; Brewer, Molly; Zhu, Quing

2011-09-01

Optical scattering coefficient from ex vivo unfixed normal and malignant ovarian tissue was quantitatively extracted by fitting optical coherence tomography (OCT) A-line signals to a single scattering model. 1097 average A-line measurements at a wavelength of 1310 nm were performed at 108 sites obtained from 18 ovaries. The average scattering coefficient obtained from the normal tissue group consisted of 833 measurements from 88 sites was 2.41 mm-1 (+/-0.59), while the average coefficient obtained from the malignant tissue group consisted of 264 measurements from 20 sites was 1.55 mm-1 (+/-0.46). The malignant ovarian tissue showed significant lower scattering than the normal group (p < 0.001). The amount of collagen within OCT imaging depth was analyzed from the tissue histological section stained with Sirius Red. The average collagen area fraction (CAF) obtained from the normal tissue group was 48.4% (+/-12.3%), while the average CAF obtained from the malignant tissue group was 11.4% (+/-4.7%). A statistical significance of the collagen content was found between the two groups (p < 0.001). These results demonstrated that quantitative measurements of optical scattering coefficient from OCT images could be a potential powerful method for ovarian cancer detection.

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

A comparison of experimental and theoretical results for leakage, pressure distribution, and rotordynamic coefficients for annular gas seals

NASA Technical Reports Server (NTRS)

Nicks, C. O.; Childs, D. W.

1984-01-01

The importance of seal behavior in rotordynamics is discussed and current annular seal theory is reviewed. A Nelson's analytical-computational method for determining rotordynamic coefficients for this type of compressible-flow seal is outlined. Various means for the experimental identification of the dynamic coefficients are given, and the method employed at the Texas A and M University (TAMU) test facility is explained. The TAMU test apparatus is described, and the test procedures are discussed. Experimental results, including leakage, entrance-loss coefficients, pressure distributions, and rotordynamic coefficients for a smooth and a honeycomb constant-clearance seal are presented and compared to theoretical results from Nelson's analysis. The results for both seals show little sensitivity to the running speed over the test range. Agreement between test results and theory for leakage through the seal is satisfactory. Test results for direct stiffness show a greater sensitivity to fluid pre-rotation than predicted. Results also indicate that the deliberately roughened surface of the honeycomb seal provides improved stability versus the smooth seal.

What to Do With "Moderate" Reliability and Validity Coefficients?

PubMed

Post, Marcel W

2016-07-01

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 coefficients <.70 should be considered as indicative of unreliability. Convergent validity coefficients in the .40 to .60 or .40 to .70 range should be considered as indications of validity problems, or as inconclusive at best. Studies on reliability and convergent should be designed in such a way that it is realistic to expect high reliability and validity coefficients. Multitrait multimethod approaches are preferred to study construct (convergent-divergent) validity. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

CFD Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

NASA Technical Reports Server (NTRS)

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.

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

PubMed Central

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

2016-01-01

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

Investigation of oscillating cascade aerodynamics by an experimental influence coefficient technique

NASA Technical Reports Server (NTRS)

Buffum, Daniel H.; Fleeter, Sanford

1988-01-01

Fundamental experiments are performed in the NASA Lewis Transonic Oscillating Cascade Facility to investigate the torsion mode unsteady aerodynamics of a biconvex airfoil cascade at realistic values of the reduced frequency for all interblade phase angles at a specified mean flow condition. In particular, an unsteady aerodynamic influence coefficient technique is developed and utilized in which only one airfoil in the cascade is oscillated at a time and the resulting airfoil surface unsteady pressure distribution measured on one dynamically instrumented airfoil. The unsteady aerodynamics of an equivalent cascade with all airfoils oscillating at a specified interblade phase angle are then determined through a vector summation of these data. These influence coefficient determined oscillation cascade data are correlated with data obtained in this cascade with all airfoils oscillating at several interblade phase angle values. The influence coefficients are then utilized to determine the unsteady aerodynamics of the cascade for all interblade phase angles, with these unique data subsequently correlated with predictions from a linearized unsteady cascade model.

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Vermeer, K. A.; van der Schoot, J.; Lemij, H. G.; de Boer, J. F.

2013-03-01

Recently, a method to determine the retinal nerve fiber layer (RNFL) attenuation coefficient, based on normalization on the retinal pigment epithelium, was introduced. In contrast to conventional RNFL thickness measures, this novel measure represents a scattering property of the RNFL tissue. In this paper, we compare the RNFL thickness and the RNFL attenuation coefficient on 10 normal and 8 glaucomatous eyes by analyzing the correlation coefficient and the receiver operator curves (ROCs). The thickness and attenuation coefficient showed moderate correlation (r=0.82). Smaller correlation coefficients were found within normal (r=0.55) and glaucomatous (r=0.48) eyes. The full separation between normal and glaucomatous eyes based on the RNFL attenuation coefficient yielded an area under the ROC (AROC) of 1.0. The AROC for the RNFL thickness was 0.9875. No statistically significant difference between the two measures was found by comparing the AROC. RNFL attenuation coefficients may thus replace current RNFL thickness measurements or be combined with it to improve glaucoma diagnosis.

CMS results on multijet correlations

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

Safronov, Grigory

2015-04-10

We present recent CMS measurements on multijet correlations using forward and low-p{sub T} jets, focusing on searches for BFKL and saturation phenomena. In pp collisions at √(s)=7 TeV, azimuthal correlations in dijets separated in rapidity by up to 9.4 units were measured. The results are compared to BFKL- and DGLAP-based predictions. In pp collisions at √(s)=8 TeV, cross sections for jets with p{sub T} > 21 GeV and |y| < 4.7, and for track-jets with p{sub T} > 1 GeV (minijets) are presented. The minijet results are sensitive to the bound imposed by the total inelastic cross section, and aremore » compared to various models for taming the growth of the 2 → 2 cross section at low p{sub T}.« less

Simulation data for an estimation of the maximum theoretical value and confidence interval for the correlation coefficient.

PubMed

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.

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

PubMed

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.

A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

PubMed

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.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

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.

An instrumental variable random-coefficients model for binary outcomes

PubMed Central

Chesher, Andrew; Rosen, Adam M

2014-01-01

In this paper, we study a random-coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be required for a control function approach. The model fits within the spectrum of generalized instrumental variable models, and we thus apply identification results from our previous studies of such models to the present context, demonstrating their use. Specifically, we characterize the identified set for the distribution of random coefficients in the binary response model with endogeneity via a collection of conditional moment inequalities, and we investigate the structure of these sets by way of numerical illustration. PMID:25798048

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

PubMed

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

2016-06-01

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

Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy.

PubMed

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.

Bounds for OPE coefficients on the Regge trajectory

NASA Astrophysics Data System (ADS)

Costa, Miguel S.; Hansen, Tobias; Penedones, João

2017-10-01

We consider the Regge limit of the CFT correlation functions < JJOO> and < TTOO>, where J is a vector current, T is the stress tensor and O is some scalar operator. These correlation functions are related by a type of Fourier transform to the AdS phase shift of the dual 2-to-2 scattering process. AdS unitarity was conjectured some time ago to be positivity of the imaginary part of this bulk phase shift. This condition was recently proved using purely CFT arguments. For large N CFTs we further expand on these ideas, by considering the phase shift in the Regge limit, which is dominated by the leading Regge pole with spin j( ν), where ν is a spectral parameter. We compute the phase shift as a function of the bulk impact parameter, and then use AdS unitarity to impose bounds on the analytically continued OPE coefficients {C}_JJ}j(ν )} and C TTj(ν) that describe the coupling to the leading Regge trajectory of the current J and stress tensor T. AdS unitarity implies that the OPE coefficients associated to non-minimal couplings of the bulk theory vanish at the intercept value ν = 0, for any CFT. Focusing on the case of large gap theories, this result can be used to show that the physical OPE coefficients {C}_{JJT and C TTT , associated to non-minimal bulk couplings, scale with the gap Δ g as Δ g - 2 or Δ g - 4 . Also, looking directly at the unitarity condition imposed at the OPE coefficients {C_JJT and C TTT results precisely in the known conformal collider bounds, giving a new CFT derivation of these bounds. We finish with remarks on finite N theories and show directly in the CFT that the spin function j( ν) is convex, extending this property to the continuation to complex spin.

Correlation of second virial coefficient with solubility for proteins in salt solutions.

PubMed

Mehta, Chirag M; White, Edward T; Litster, James D

2012-01-01

In this work, osmotic second virial coefficients (B(22)) were determined and correlated with the measured solubilities for the proteins, α-amylase, ovalbumin, and lysozyme. The B(22) values and solubilities were determined in similar solution conditions using two salts, sodium chloride and ammonium sulfate in an acidic pH range. An overall decrease in the solubility of the proteins (salting out) was observed at high concentrations of ammonium sulfate and sodium chloride solutions. However, for α-amylase, salting-in behavior was also observed in low concentration sodium chloride solutions. In ammonium sulfate solutions, the B(22) are small and close to zero below 2.4 M. As the ammonium sulfate concentrations were further increased, B(22) values decreased for all systems studied. The effect of sodium chloride on B(22) varies with concentration, solution pH, and the type of protein studied. Theoretical models show a reasonable fit to the experimental derived data of B(22) and solubility. B(22) is also directly proportional to the logarithm of the solubility values for individual proteins in salt solutions, so the log-linear empirical models developed in this work can also be used to rapidly predict solubility and B(22) values for given protein-salt systems. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Fluorescence correlation spectroscopy experiments to quantify free diffusion coefficients in reaction-diffusion systems: The case of Ca2 + and its dyes

NASA Astrophysics Data System (ADS)

Sigaut, Lorena; Villarruel, Cecilia; Ponce, María Laura; Ponce Dawson, Silvina

2017-06-01

Many cell signaling pathways involve the diffusion of messengers that bind and unbind to and from intracellular components. Quantifying their net transport rate under different conditions then requires having separate estimates of their free diffusion coefficient and binding or unbinding rates. In this paper, we show how performing sets of fluorescence correlation spectroscopy (FCS) experiments under different conditions, it is possible to quantify free diffusion coefficients and on and off rates of reaction-diffusion systems. We develop the theory and present a practical implementation for the case of the universal second messenger, calcium (Ca2 +) and single-wavelength dyes that increase their fluorescence upon Ca2 + binding. We validate the approach with experiments performed in aqueous solutions containing Ca2 + and Fluo4 dextran (both in its high and low affinity versions). Performing FCS experiments with tetramethylrhodamine-dextran in Xenopus laevis oocytes, we infer the corresponding free diffusion coefficients in the cytosol of these cells. Our approach can be extended to other physiologically relevant reaction-diffusion systems to quantify biophysical parameters that determine the dynamics of various variables of interest.

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

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

Automated collimation testing by determining the statistical correlation coefficient of Talbot self-images.

PubMed

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.

Prediction of soil organic carbon partition coefficients by soil column liquid chromatography.

PubMed

Guo, Rongbo; Liang, Xinmiao; Chen, Jiping; Wu, Wenzhong; Zhang, Qing; Martens, Dieter; Kettrup, Antonius

2004-04-30

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (KOC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (KOW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for KOC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (ksoil) and KOC measured by batch equilibrium method were studied. Good correlations were achieved between ksoil and KOC for three types of soils with different properties. All the square of the correlation coefficients (R2) of the linear regression between log ksoil and log KOC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of KOC from KOW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (kCN) was comparatively evaluated for the three types of soils. The results show that the prediction of KOC from kCN and KOW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the KOC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict KOC largely depends on the properties of soil concerned.

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)?

PubMed

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

2012-10-01

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). 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. 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. 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. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Removal of dissolved organic carbon by aquifer material: Correlations between column parameters, sorption isotherms and octanol-water partition coefficient.

PubMed

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.

Annular honeycomb seals: Test results for leakage and rotordynamic coefficients; comparisons to labyrinth and smooth configurations

NASA Technical Reports Server (NTRS)

Childs, Dara W.; Elrod, David; Hale, Keith

1989-01-01

Test results are presented for leakage and rotordynamic coefficients for seven honeycomb seals. All seals have the same radius, length, and clearance; however, the cell depths and diameters are varied. Rotordynamic data, which are presented, consist of the direct and cross-coupled stiffness coefficients and the direct damping coefficients. The rotordynamic-coefficient data show a considerable sensitivity to changes in cell dimensions; however, no clear trends are identifiable. Comparisons of test data for the honeycomb seals with labyrinth and smooth annular seals show the honeycomb seal had the best sealing (minimum leakage) performance, followed in order by the labyrinth and smooth seals. For prerotated fluid entering the seal, in the direction of shaft rotation, the honeycomb seal has the best rotordynamic stability followed in order by the labyrinth and smooth. For no prerotation, or fluid prerotation against shaft rotation, the labyrinth seal has the best rotordynamic stability followed in order by the smooth and honeycomb seals.

Nonlinearity of the forward-backward correlation function in the model with string fusion

NASA Astrophysics Data System (ADS)

Vechernin, Vladimir

2017-12-01

The behavior of the forward-backward correlation functions and the corresponding correlation coefficients between multiplicities and transverse momenta of particles produced in high energy hadronic interactions is analyzed by analytical and MC calculations in the models with and without string fusion. The string fusion is taking into account in simplified form by introducing the lattice in the transverse plane. The results obtained with two alternative definitions of the forward-backward correlation coefficient are compared. It is shown that the nonlinearity of correlation functions increases with the width of observation windows, leading at small string density to a strong dependence of correlation coefficient value on the definition. The results of the modeling enable qualitatively to explain the experimentally observed features in the behavior of the correlation functions between multiplicities and mean transverse momenta at small and large multiplicities.

Analysis of Manning’s and Drag Coefficients for Flexible Submerged Vegetation

NASA Astrophysics Data System (ADS)

Yusof, Khamaruzaman Wan; Mujahid Muhammad, Muhammad; Mustafa, Muhammad Raza Ul; Azazi Zakaria, Nor; Gahani, Aminuddin Ab.

2017-06-01

Accurate determination of flow resistance is of great significance in modelling of open channels that will convey water efficiently. Although, resistance or drag induced by vegetation have been systematically studied for several decades, estimating of the resistance remain as a challenge. This is because most of previous studies use artificial vegetation to investigate flow - vegetation interactions. To overcome this, the present study evaluates the vegetation resistance in terms of Manning’s roughness coefficient and drag coefficient using a natural flexible vegetation (cow grass) under submerged condition. From the experimental result obtained, it was observed that the Manning’s and drag coefficients decreased with the increasing in average velocity. Also, graphical relationship between Manning’s coefficient, n and drag coefficient, CD has been developed with R2 = 0.9465, which indicate that there exist a strong correlation between n and CD, and one can use the proposed graphical model to predict the n - values corresponding to the CD - values.

Temporal behavior of the effective diffusion coefficients for transport in heterogeneous saturated aquifers

NASA Astrophysics Data System (ADS)

Suciu, N.; Vamos, C.; Vereecken, H.; Vanderborght, J.; Hardelauf, H.

2003-04-01

When the small scale transport is modeled by a Wiener process and the large scale heterogeneity by a random velocity field, the effective coefficients, Deff, can be decomposed as sums between the local coefficient, D, a contribution of the random advection, Dadv, and a contribution of the randomness of the trajectory of plume center of mass, Dcm: Deff=D+Dadv-Dcm. The coefficient Dadv is similar to that introduced by Taylor in 1921, and more recent works associate it with the thermodynamic equilibrium. The ``ergodic hypothesis'' says that over large time intervals Dcm vanishes and the effect of the heterogeneity is described by Dadv=Deff-D. In this work we investigate numerically the long time behavior of the effective coefficients as well as the validity of the ergodic hypothesis. The transport in every realization of the velocity field is modeled with the Global Random Walk Algorithm, which is able to track as many particles as necessary to achieve a statistically reliable simulation of the process. Averages over realizations are further used to estimate mean coefficients and standard deviations. In order to remain in the frame of most of the theoretical approaches, the velocity field was generated in a linear approximation and the logarithm of the hydraulic conductivity was taken to be exponential decaying correlated with variance equal to 0.1. Our results show that even in these idealized conditions, the effective coefficients tend to asymptotic constant values only when the plume travels thousands of correlations lengths (while the first order theories usually predict Fickian behavior after tens of correlations lengths) and that the ergodicity conditions are still far from being met.

Correlation of subjective slipperiness judgements with quantitative COF (Coefficient Of Friction) measurements for structural steel

NASA Astrophysics Data System (ADS)

Purswell, Jerry L.; Schlegel, Robert E.

1988-06-01

When there is no simple or accurate procedure for measuring the coefficient of friction (COF) at a job site, workers and/or supervisors involved must make subjective judgments about the slipperiness of the walking and climbing surfaces and in turn decide whether the surface presents a safe or an unsafe condition for work. This project was designed to determine whether these subjective judgment calls did in fact agree with the COF measurements obtained using a mechanical device. It was noted that the coatings chosen for study were subject to a polishing factor by the boot soles during the trials, causing the COF values to become lower as the trials continued. Poor correlation was obtained between subjective ratings of slipperiness and the COF values measured before the trials began. A relatively high correlation was obtained between subjective ratings and the COF values measured after the trials had been completed. A difference was noted in the subjective ratings for the effects of water on a coating for column climbing, but not for walking a beam, suggesting the effects of water on a coating are related to the type of task being performed in steel erection. An increase in the measured COF was noted for all of the coatings when they were wet as compared to the dry condition. The importance of clean shoe soles was clearly demonstrated.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

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

A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

PubMed

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.

[Correlations between apparent diffusion coefficient in diffusion?weighted magnetic resonance imaging and molecular subtypes of invasive breast cancer masses].

PubMed

Shang, Liu-Tong; Yang, Jia-Fei; Lu, Jing; Wang, Ting-Ting; Zhou, Ying; Xing, Xin-Bo; Wang, Xin-Kun; Yang, Shu-Hui; Hu, Ming-Yan

2017-10-20

To study the correlation of apparent diffusion coefficient (ADC) measured by diffusion-weighted magnetic resonance imaging (MRI) with the molecular subtypes and biological prognostic factors of invasive breast cancer masses. Breast MRI data (including dynamic enhanced and diffusion-weighted imaging) were collected from 64 patients with pathologically confirmed invasive breast cancer masses (a total of 69 lesions). The mean ADC values of the lesions were calculated and their correlations were analyzed with the 5 molecular subtypes of invasive breast cancer and the biological prognostic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), and Ki-67 index. The ADC values did not differ significantly among the 5 molecular subtypes of invasive breast cancer masses (P>0.05) or among lesions with different ER, PR, or HER2 status (P>0.05). The mean ADC values were significantly higher in Ki-67-positive lesions than in the negative lesions (P=0.023 and negatively correlated with the expressions of Ki-67 (r=-0.249). ADC value can not be used to identify the molecular subtypes of invasive breast cancer masses or to evaluate the biological prognosis of the lesions, but its correlation with Ki-67 expression may help in prognostic evaluation and guiding clinical therapy of the tumors.

Explicating the Conditions Under Which Multilevel Multiple Imputation Mitigates Bias Resulting from Random Coefficient-Dependent Missing Longitudinal Data.

PubMed

Gottfredson, Nisha C; Sterba, Sonya K; Jackson, Kristina M

2017-01-01

Random coefficient-dependent (RCD) missingness is a non-ignorable mechanism through which missing data can arise in longitudinal designs. RCD, for which we cannot test, is a problematic form of missingness that occurs if subject-specific random effects correlate with propensity for missingness or dropout. Particularly when covariate missingness is a problem, investigators typically handle missing longitudinal data by using single-level multiple imputation procedures implemented with long-format data, which ignores within-person dependency entirely, or implemented with wide-format (i.e., multivariate) data, which ignores some aspects of within-person dependency. When either of these standard approaches to handling missing longitudinal data is used, RCD missingness leads to parameter bias and incorrect inference. We explain why multilevel multiple imputation (MMI) should alleviate bias induced by a RCD missing data mechanism under conditions that contribute to stronger determinacy of random coefficients. We evaluate our hypothesis with a simulation study. Three design factors are considered: intraclass correlation (ICC; ranging from .25 to .75), number of waves (ranging from 4 to 8), and percent of missing data (ranging from 20 to 50%). We find that MMI greatly outperforms the single-level wide-format (multivariate) method for imputation under a RCD mechanism. For the MMI analyses, bias was most alleviated when the ICC is high, there were more waves of data, and when there was less missing data. Practical recommendations for handling longitudinal missing data are suggested.

Thermal coefficients of the methyl groups within ubiquitin

PubMed Central

Sabo, T Michael; Bakhtiari, Davood; Walter, Korvin F A; McFeeters, Robert L; Giller, Karin; Becker, Stefan; Griesinger, Christian; Lee, Donghan

2012-01-01

Physiological processes such as protein folding and molecular recognition are intricately linked to their dynamic signature, which is reflected in their thermal coefficient. In addition, the local conformational entropy is directly related to the degrees of freedom, which each residue possesses within its conformational space. Therefore, the temperature dependence of the local conformational entropy may provide insight into understanding how local dynamics may affect the stability of proteins. Here, we analyze the temperature dependence of internal methyl group dynamics derived from the cross-correlated relaxation between dipolar couplings of two CH bonds within ubiquitin. Spanning a temperature range from 275 to 308 K, internal methyl group dynamics tend to increase with increasing temperature, which translates to a general increase in local conformational entropy. With this data measured over multiple temperatures, the thermal coefficient of the methyl group order parameter, the characteristic thermal coefficient, and the local heat capacity were obtained. By analyzing the distribution of methyl group thermal coefficients within ubiquitin, we found that the N-terminal region has relatively high thermostability. These results indicate that methyl groups contribute quite appreciably to the total heat capacity of ubiquitin through the regulation of local conformational entropy. PMID:22334336

A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

PubMed

Wang, Jianji; Zheng, Nanning

2013-09-01

Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis.

PubMed

Jones, Reese E; Mandadapu, Kranthi K

2012-04-21

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)] 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.

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis

NASA Astrophysics Data System (ADS)

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.

Size exclusion chromatography and viscometry in paper degradation studies. New Mark-Houwink coefficients for cellulose in cupri-ethylenediamine.

PubMed

Łojewski, Tomasz; Zieba, Katarzyna; Lojewska, Joanna

2010-10-15

The paper deals with the application of size exclusion chromatography (SEC) for the studies of paper degradation phenomena. The goal is to solve some of the technical problems connected with the calibration of multi-detector SEC system and to find the correlation between SEC and viscometric results of degree of polymerization of cellulose. The results gathered for the paper samples degraded by acidic air pollutant (NO(2)) are used as an example of SEC-MALLS application. From the correlation between intrinsic viscosities and absolute value of molecular masses obtained with SEC/MALLS (Multi Angle Laser Light Scattering) technique, Mark-Houwink coefficients for cellulose in cupri-ethylenediamine solution were determined. Thus obtained coefficients were used for the determination of viscometric degree of polymerization (molecular mass) of the aged samples. An excellent correlation was found between the chromatographic values of molecular masses obtained with SEC-UV/VIS detection and the viscometric ones utilizing the improved values of Mark-Houwink coefficients. Copyright © 2010 Elsevier B.V. All rights reserved.

Characterization of Skin Friction Coefficient, and Relationship to Stratum Corneum Hydration in a Normal Chinese Population

PubMed Central

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

2011-01-01

Background and Objectives 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. Methods 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. Results 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 < 0.001 and p < 0.0001, respectively). In contrast, in males, the skin friction coefficient was positively correlated with stratum corneum hydration on the forehead and the dorsal hand skin (p < 0.05 and p < 0.0001, respectively). Conclusion The skin friction coefficient varies with age, gender and body site, and positively correlates with stratum corneum hydration on some body sites. PMID:21088455

Accelerating activity coefficient calculations using multicore platforms, and profiling the energy use resulting from such calculations.

NASA Astrophysics Data System (ADS)

Topping, David; Alibay, Irfan; Bane, Michael

2017-04-01

To predict the evolving concentration, chemical composition and ability of aerosol particles to act as cloud droplets, we rely on numerical modeling. Mechanistic models attempt to account for the movement of compounds between the gaseous and condensed phases at a molecular level. This 'bottom up' approach is designed to increase our fundamental understanding. However, such models rely on predicting the properties of molecules and subsequent mixtures. For partitioning between the gaseous and condensed phases this includes: saturation vapour pressures; Henrys law coefficients; activity coefficients; diffusion coefficients and reaction rates. Current gas phase chemical mechanisms predict the existence of potentially millions of individual species. Within a dynamic ensemble model, this can often be used as justification for neglecting computationally expensive process descriptions. Indeed, on whether we can quantify the true sensitivity to uncertainties in molecular properties, even at the single aerosol particle level it has been impossible to embed fully coupled representations of process level knowledge with all possible compounds, typically relying on heavily parameterised descriptions. Relying on emerging numerical frameworks, and designed for the changing landscape of high-performance computing (HPC), in this study we focus specifically on the ability to capture activity coefficients in liquid solutions using the UNIFAC method. Activity coefficients are often neglected with the largely untested hypothesis that they are simply too computationally expensive to include in dynamic frameworks. We present results demonstrating increased computational efficiency for a range of typical scenarios, including a profiling of the energy use resulting from reliance on such computations. As the landscape of HPC changes, the latter aspect is important to consider in future applications.

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.

PubMed

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 < 0.001), as well as in the malignant (Pearson r = 0.64, P = 0.004) and benign (Pearson r = 0.52, P = 0.01) subgroup. A significant 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.

Correlation mapping for visualizing propagation of pulsatile CSF motion in intracranial space based on magnetic resonance phase contrast velocity images: preliminary results.

PubMed

Yatsushiro, Satoshi; Hirayama, Akihiro; Matsumae, Mitsunori; Kajiwara, Nao; Abdullah, Afnizanfaizal; Kuroda, Kagayaki

2014-01-01

Correlation time mapping based on magnetic resonance (MR) velocimetry has been applied to pulsatile cerebrospinal fluid (CSF) motion to visualize the pressure transmission between CSF at different locations and/or between CSF and arterial blood flow. Healthy volunteer experiments demonstrated that the technique exhibited transmitting pulsatile CSF motion from CSF space in the vicinity of blood vessels with short delay and relatively high correlation coefficients. Patient and healthy volunteer experiments indicated that the properties of CSF motion were different from the healthy volunteers. Resultant images in healthy volunteers implied that there were slight individual difference in the CSF driving source locations. Clinical interpretation for these preliminary results is required to apply the present technique for classifying status of hydrocephalus.

Discharge coefficient correlations for circular-arc venturi flowmeters at critical /sonic/ flow

NASA Technical Reports Server (NTRS)

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.

Assessment of passive muscle elongation using Diffusion Tensor MRI: Correlation between fiber length and diffusion coefficients.

PubMed

Mazzoli, Valentina; Oudeman, Jos; Nicolay, Klaas; Maas, Mario; Verdonschot, Nico; Sprengers, Andre M; Nederveen, Aart J; Froeling, Martijn; Strijkers, Gustav J

2016-12-01

In this study we investigated the changes in fiber length and diffusion parameters as a consequence of passive lengthening and stretching of the calf muscles. We hypothesized that changes in radial diffusivity (RD) are caused by changes in the muscle fiber cross sectional area (CSA) as a consequence of lengthening and shortening of the muscle. Diffusion Tensor MRI (DT-MRI) measurements were made twice in five healthy volunteers, with the foot in three different positions (30° plantarflexion, neutral position and 15° dorsiflexion). The muscles of the calf were manually segmented on co-registered high resolution anatomical scans, and maps of RD and axial diffusivity (AD) were reconstructed from the DT-MRI data. Fiber tractography was performed and mean fiber length was calculated for each muscle group. Significant negative correlations were found between the changes in RD and changes in fiber length in the dorsiflexed and plantarflexed positions, compared with the neutral foot position. Changes in AD did not correlate with changes in fiber length. Assuming a simple cylindrical model with constant volume for the muscle fiber, the changes in the muscle fiber CSA were calculated from the changes in fiber length. In line with our hypothesis, we observed a significant positive correlation of the CSA with the measured changes in RD. In conclusion, we showed that changes in diffusion coefficients induced by passive muscle stretching and lengthening can be explained by changes in muscle CSA, advancing the physiological interpretation of parameters derived from skeletal muscle DT-MRI. Copyright © 2016 John Wiley & Sons, Ltd.

Performance of intraclass correlation coefficient (ICC) as a reliability index under various distributions in scale reliability studies.

PubMed

Mehta, Shraddha; Bastero-Caballero, Rowena F; Sun, Yijun; Zhu, Ray; Murphy, Diane K; Hardas, Bhushan; Koch, Gary

2018-04-29

Many published scale validation studies determine inter-rater reliability using the intra-class correlation coefficient (ICC). However, the use of this statistic must consider its advantages, limitations, and applicability. This paper evaluates how interaction of subject distribution, sample size, and levels of rater disagreement affects ICC and provides an approach for obtaining relevant ICC estimates under suboptimal conditions. Simulation results suggest that for a fixed number of subjects, ICC from the convex distribution is smaller than ICC for the uniform distribution, which in turn is smaller than ICC for the concave distribution. The variance component estimates also show that the dissimilarity of ICC among distributions is attributed to the study design (ie, distribution of subjects) component of subject variability and not the scale quality component of rater error variability. The dependency of ICC on the distribution of subjects makes it difficult to compare results across reliability studies. Hence, it is proposed that reliability studies should be designed using a uniform distribution of subjects because of the standardization it provides for representing objective disagreement. In the absence of uniform distribution, a sampling method is proposed to reduce the non-uniformity. In addition, as expected, high levels of disagreement result in low ICC, and when the type of distribution is fixed, any increase in the number of subjects beyond a moderately large specification such as n = 80 does not have a major impact on ICC. Copyright © 2018 John Wiley & Sons, Ltd.

Optimized atom position and coefficient coding for matching pursuit-based image compression.

PubMed

Shoa, Alireza; Shirani, Shahram

2009-12-01

In this paper, we propose a new encoding algorithm for matching pursuit image coding. We show that coding performance is improved when correlations between atom positions and atom coefficients are both used in encoding. We find the optimum tradeoff between efficient atom position coding and efficient atom coefficient coding and optimize the encoder parameters. Our proposed algorithm outperforms the existing coding algorithms designed for matching pursuit image coding. Additionally, we show that our algorithm results in better rate distortion performance than JPEG 2000 at low bit rates.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Diffusion coefficients of nitric oxide in water: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Pokharel, Sunil; Pantha, Nurapati; Adhikari, N. P.

2016-09-01

Self-diffusion coefficients along with the mutual diffusion coefficients of nitric oxide (NO) and SPC/E water (H2O) as solute and solvent of the mixture, have been studied within the framework of classical molecular dynamics level of calculations using GROMACS package. The radial distribution function (RDF) of the constituent compounds are calculated to study solute-solute, solute-solvent and solvent-solvent molecular interactions as a function of temperature. A dilute solution of five NO molecules (mole fraction 0.018) and 280 H2O molecules (mole fraction 0.982) has been taken as the sample. The self-diffusion coefficient of the solvent is calculated by using mean square displacement (MSD) where as that for solute (NO) is calculated by using MSD and velocity auto-correlation function (VACF). The results are then compared with the available experimental values. The results from the present work for water come in good agreement, very precise at low temperatures, with the experimental values. The diffusion coefficients of NO, on the other hands, agree well with the available theoretical studies, and also with experiment at low temperatures (up to 310 K). The results at the higher temperatures (up to 333 K), however, deviate significantly with the experimental observations. Also, the mutual diffusion coefficients of NO in water have been calculated by using Darken’s relation. The temperature dependence of the calculated diffusion coefficients follow the Arrhenius behavior.

Correlation between apparent diffusion coefficient and histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy.

PubMed

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 < 0.001) lower than that of non-cartilaginous tumor cell necrosis without stroma disintegration (25/91, ADC =1.77 ± 0.03 × 10 -3  mm 2 /s), cartilaginous viable tumor (14/91, ADC = 2.19 ± 0.04 × 10 -3  mm 2 /s), and cystic areas including liquefied necrosis, blood space, and secondary aneurysmal bone cyst (14/91, ADC = 2.29 ± 0.05 × 10 -3  mm 2 /s). The mean ADC value of non-cartilaginous tumor cell necrosis was also significantly ( P < 0.001) smaller than those of viable cartilaginous tumor and cystic/hemorrhagic necrosis whereas the mean ADC values were not 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.

C-Depth Method to Determine Diffusion Coefficient and Partition Coefficient of PCB in Building Materials.

PubMed

Liu, Cong; Kolarik, Barbara; Gunnarsen, Lars; Zhang, Yinping

2015-10-20

Polychlorinated biphenyls (PCBs) have been found to be persistent in the environment and possibly harmful. Many buildings are characterized with high PCB concentrations. Knowledge about partitioning between primary sources and building materials is critical for exposure assessment and practical remediation of PCB contamination. This study develops a C-depth method to determine diffusion coefficient (D) and partition coefficient (K), two key parameters governing the partitioning process. For concrete, a primary material studied here, relative standard deviations of results among five data sets are 5%-22% for K and 42-66% for D. Compared with existing methods, C-depth method overcomes the inability to obtain unique estimation for nonlinear regression and does not require assumed correlations for D and K among congeners. Comparison with a more sophisticated two-term approach implies significant uncertainty for D, and smaller uncertainty for K. However, considering uncertainties associated with sampling and chemical analysis, and impact of environmental factors, the results are acceptable for engineering applications. This was supported by good agreement between model prediction and measurement. Sensitivity analysis indicated that effective diffusion distance, contacting time of materials with primary sources, and depth of measured concentrations are critical for determining D, and PCB concentration in primary sources is critical for K.

Effects of vegetation canopy on the radar backscattering coefficient

NASA Technical Reports Server (NTRS)

Mo, T.; Blanchard, B. J.; Schmugge, T. J.

1983-01-01

Airborne L- and C-band scatterometer data, taken over both vegetation-covered and bare fields, were systematically analyzed and theoretically reproduced, using a recently developed model for calculating radar backscattering coefficients of rough soil surfaces. The results show that the model can reproduce the observed angular variations of radar backscattering coefficient quite well via a least-squares fit method. Best fits to the data provide estimates of the statistical properties of the surface roughness, which is characterized by two parameters: the standard deviation of surface height, and the surface correlation length. In addition, the processes of vegetation attenuation and volume scattering require two canopy parameters, the canopy optical thickness and a volume scattering factor. Canopy parameter values for individual vegetation types, including alfalfa, milo and corn, were also determined from the best-fit results. The uncertainties in the scatterometer data were also explored.

On the solar cycle variation in the barometer coefficients of high latitude neutron monitors

NASA Technical Reports Server (NTRS)

Kusunose, M.; Ogita, N.

1985-01-01

Evaluation of barometer coefficients of neutron monitors located at high latitudes has been performed by using the results of the spherical harmonic analysis based on the records from around twenty stations for twelve years from January 1966 to December 1977. The average of data at eight stations, where continuous records are available for twelve years, show that the absolute value of barometer coefficient is in positive correlation with the cosmic ray neutron intensity. The variation rate of the barometer coefficient to the cosmic ray neutron intensity is influenced by the changes in the cutoff rigidity and in the primary spectrum.

Air sparging: Air-water mass transfer coefficients

NASA Astrophysics Data System (ADS)

Braida, Washington J.; Ong, Say Kee

1998-12-01

Experiments investigating the mass transfer of several dissolved volatile organic compounds (VOCs) across the air-water interface were conducted using a single-air- channel air-sparging system. Three different porous media were used in the study. Air velocities ranged from 0.2 cm s-1 to 2.5 cm s-1. The tortuosity factor for each porous medium and the air-water mass transfer coefficients were estimated by fitting experimental data to a one-dimensional diffusion model. The estimated mass transfer coefficients KG ranged from 1.79 × 10-3 cm min-1 to 3.85 × 10-2 cm min-1. The estimated lumped gas phase mass transfer coefficients KGa were found to be directly related to the air diffusivity of the VOC, air velocity, and particle size, and inversely related to the Henry's law constant of the VOCs. Of the four parameters investigated, the parameter that controlled or had a dominant effect on the lumped gas phase mass transfer coefficient was the air diffusivity of the VOC. Two empirical models were developed by correlating the Damkohler and the modified air phase Sherwood numbers with the air phase Peclet number, Henry's law constant, and the reduced mean particle size of porous media. The correlation developed in this study may be used to obtain better predictions of mass transfer fluxes for field conditions.

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

PubMed

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

2007-08-15

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

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are

Refinement of Global Phase-Shift Analysis for p+^3He Elastic Scattering Using Spin-Correlation Coefficients

NASA Astrophysics Data System (ADS)

Daniels, Tim; Arnold, Charles; Cesaratto, John; Clegg, Thomas; Couture, Alexander; Imig, Astrid; Karwowski, Hugon

2008-10-01

As part of an investigation of the A=4 system, we measured the spin-correlation coefficients Ayo, Aoy, Ayy, and Axx for p-^3He elastic scattering at Elab of 2.3, 2.7, 4.0, and 5.5 MeV and θlab between 30^o and 150^o. The data were taken using TUNL's atomic beam polarized ion source and our spin-exchange optical pumping polarized ^3He targetootnotetextT. Katabuchi et al., Rev. Sci. Instrum. 76, 033503 (2005). We aim to resolve ambiguities in the phase shifts of George and KnutsonootnotetextE.A. George and L.D. Knutson, Phys Rev C 67, 027001 (2003), which seem most sensitive to Axx and Ayy at the lowest of these energies. Our measurements will be shown with phase-shift-analysis solutions, as well as some discussion of systematic effects related to the steering of charged particles by the target's magnetic field.

Effect of degree correlations above the first shell on the percolation transition

NASA Astrophysics Data System (ADS)

Valdez, L. D.; Buono, C.; Braunstein, L. A.; Macri, P. A.

2011-11-01

The use of degree-degree correlations to model realistic networks which are characterized by their Pearson's coefficient, has become widespread. However the effect on how different correlation algorithms produce different results on processes on top of them, has not yet been discussed. In this letter, using different correlation algorithms to generate assortative networks, we show that for very assortative networks the behavior of the main observables in percolation processes depends on the algorithm used to build the network. The different alghoritms used here introduce different inner structures that are missed in Pearson's coefficient. We explain the different behaviors through a generalization of Pearson's coefficient that allows to study the correlations at chemical distances l from a root node. We apply our findings to real networks.

Effect of Atomic Charges on Octanol-Water Partition Coefficient Using Alchemical Free Energy Calculation.

PubMed

Ogata, Koji; Hatakeyama, Makoto; Nakamura, Shinichiro

2018-02-15

The octanol-water partition coefficient (log P ow ) is an important index for measuring solubility, membrane permeability, and bioavailability in the drug discovery field. In this paper, the log P ow values of 58 compounds were predicted by alchemical free energy calculation using molecular dynamics simulation. In free energy calculations, the atomic charges of the compounds are always fixed. However, they must be recalculated for each solvent. Therefore, three different sets of atomic charges were tested using quantum chemical calculations, taking into account vacuum, octanol, and water environments. The calculated atomic charges in the different environments do not necessarily influence the correlation between calculated and experimentally measured ∆ G water values. The largest correlation coefficient values of the solvation free energy in water and octanol were 0.93 and 0.90, respectively. On the other hand, the correlation coefficient of log P ow values calculated from free energies, the largest of which was 0.92, was sensitive to the combination of the solvation free energies calculated from the calculated atomic charges. These results reveal that the solvent assumed in the atomic charge calculation is an important factor determining the accuracy of predicted log P ow values.

A comparison of experimental and theoretical results for leakage, pressure gradients, and rotordynamic coefficients for tapered annular gas seal

NASA Technical Reports Server (NTRS)

Elrod, D. A.; Childs, D. W.

1986-01-01

A brief review of current annular seal theory and a discussion of the predicted effect on stiffness of tapering the seal stator are presented. An outline of Nelson's analytical-computational method for determining rotordynamic coefficients for annular compressible-flow seals is included. Modifications to increase the maximum rotor speed of an existing air-seal test apparatus at Texas A&M University are described. Experimental results, including leakage, entrance-loss coefficients, pressure distributions, and normalized rotordynamic coefficients, are presented for four convergent-tapered, smooth-rotor, smooth-stator seals. A comparison of the test results shows that an inlet-to-exit clearance ratio of 1.5 to 2.0 provides the maximum direct stiffness, a clearance ratio of 2.5 provides the greatest stability, and a clearance ratio of 1.0 provides the least stability. The experimental results are compared to theoretical results from Nelson's analysis with good agreement. Test results for cross-coupled stiffness show less sensitivity of fluid prerotation than predicted.

Distribution coefficients of rare earth ions in cubic zirconium dioxide

NASA Astrophysics Data System (ADS)

Romer, H.; Luther, K.-D.; Assmus, W.

1994-08-01

Cubic zirconium dioxide crystals are grown with the skull melting technique. The effective distribution coefficients for Nd(exp 3+), Sm(exp 3+) and Er(sup 3+) as dopants are determined experimentally as a function of the crystal growth velocity. With the Burton-Prim-Slichter theory, the equilibrium distribution coefficients can be calculated. The distribution coefficients of all other trivalent rare earth ions can be estimated by applying the correlation towards the ionic radii.

Diffusion and solubility coefficients determined by permeation and immersion experiments for organic solvents in HDPE geomembrane.

PubMed

Chao, Keh-Ping; Wang, Ping; Wang, Ya-Ting

2007-04-02

The chemical resistance of eight organic solvents in high density polyethylene (HDPE) geomembrane has been investigated using the ASTM F739 permeation method and the immersion test at different temperatures. The diffusion of the experimental organic solvents in HDPE geomembrane was non-Fickian kinetic, and the solubility coefficients can be consistent with the solubility parameter theory. The diffusion coefficients and solubility coefficients determined by the ASTM F739 method were significantly correlated to the immersion tests (p<0.001). The steady state permeation rates also showed a good agreement between ASTM F739 and immersion experiments (r(2)=0.973, p<0.001). Using a one-dimensional diffusion equation based on Fick's second law, the diffusion and solubility coefficients obtained by immersion test resulted in over estimates of the ASTM F739 permeation results. The modeling results indicated that the diffusion and solubility coefficients should be obtained using ASTM F739 method which closely simulates the practical application of HDPE as barriers in the field.

Calculation of thermal expansion coefficient of glasses based on topological constraint theory

NASA Astrophysics Data System (ADS)

Zeng, Huidan; Ye, Feng; Li, Xiang; Wang, Ling; Yang, Bin; Chen, Jianding; Zhang, Xianghua; Sun, Luyi

2016-10-01

In this work, the thermal expansion behavior and the structure configuration evolution of glasses were studied. Degree of freedom based on the topological constraint theory is correlated with configuration evolution; considering the chemical composition and the configuration change, the analytical equation for calculating the thermal expansion coefficient of glasses from degree of freedom was derived. The thermal expansion of typical silicate and chalcogenide glasses was examined by calculating their thermal expansion coefficients (TEC) using the approach stated above. The results showed that this approach was energetically favorable for glass materials and revealed the corresponding underlying essence from viewpoint of configuration entropy. This work establishes a configuration-based methodology to calculate the thermal expansion coefficient of glasses that, lack periodic order.

A Review of Evidence for High Life Coefficients on Propeller and Rotor Blades Under Static Thrust Conditions with Some New Experimental Results

NASA Technical Reports Server (NTRS)

Talbot, Peter D.; Meyer, Mark; Branum, Lonnie; Burks, John S. (Technical Monitor)

1994-01-01

Interest has increased recently in the thrust-producing capability of rotors at very high collective pitch angles. An early reference noted this behaviour in rotors and offered alternative models for section lift characteristics to explain it. The same phenomenon was coincidentally noted and used in a propeller code, resulting in very good correlation with static thrust data. The proposed paper will present experimental data demonstrating the pronounced persistence of thrust for propellers at increasing collective pitch angles. Comparisons with blade element/momentum theory will be made. These results are expected to point to the need to define (ultimately to explain) aerodynamic lift and drag behaviour in a rotating environment. Experimental measurements made by the U.S. Army Aeroflightdynamics Directorate at the Ames Research Center have shown that locally measured normal force coefficients along the span of a highly twisted rotor blade continue to increase at high values of collective pitch. In some cases these coefficients exceed expected values for the same type of airfoil tested under two dimensional conditions. To date no one to the authors' knowledge has defined the variation of C(n) with pitch for very high angles (to 45 deg) in a rotating environment and for a blade of reasonably high aspect ratio; however, total propeller thrust measurements support the idea that stalling does not occur in the same way as on a wing. This paper will present experimental data in the form of surface pressure distributions as well as flow visualization (microtufts) to explore the aerodynamic behavior of the rotating airfoil at high values of blade incidence. This paper also reviews experimental evidence and infers some high lift coefficient behavior from it. Comparisons between predicted thrust, utilizing modified airfoil characteristics and a blade element model, and measured thrust for both rotors and propellers that cover the extremes of collective pitch are shown and

Apparent Diffusion Coefficient Value Changes and Clinical Correlation in 90 Cases of Cytomegalovirus-Infected Fetuses with Unremarkable Fetal MRI Results.

PubMed

Kotovich, D; Guedalia, J S B; Hoffmann, C; Sze, G; Eisenkraft, A; Yaniv, G

2017-07-01

Cytomegalovirus is the leading intrauterine infection. Fetal MR imaging is an accepted tool for fetal brain evaluation, yet it still lacks the ability to accurately predict the extent of the neurodevelopmental impairment, especially in fetal MR imaging scans with unremarkable findings. Our hypothesis was that intrauterine cytomegalovirus infection causes diffusional changes in fetal brains and that those changes may correlate with the severity of neurodevelopmental deficiencies. A retrospective analysis was performed on 90 fetal MR imaging scans of cytomegalovirus-infected fetuses with unremarkable results and compared with a matched gestational age control group of 68 fetal head MR imaging scans. ADC values were measured and averaged in the frontal, parietal, occipital, and temporal lobes; basal ganglia; thalamus; and pons. For neurocognitive assessment, the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) was used on 58 children in the cytomegalovirus-infected group. ADC values were reduced for the cytomegalovirus-infected fetuses in most brain areas studied. The VABS-II showed no trend for the major domains or the composite score of the VABS-II for the cytomegalovirus-infected children compared with the healthy population distribution. Some subdomains showed an association between ADC values and VABS-II scores. Cytomegalovirus infection causes diffuse reduction in ADC values in the fetal brain even in unremarkable fetal MR imaging scans. Cytomegalovirus-infected children with unremarkable fetal MR imaging scans do not deviate from the healthy population in the VABS-II neurocognitive assessment. ADC values were not correlated with VABS-II scores. However, the lack of clinical findings, as seen in most cytomegalovirus-infected fetuses, does not eliminate the possibility of future neurodevelopmental pathology. © 2017 by American Journal of Neuroradiology.

Correlation between apparent diffusion coefficient value on diffusion-weighted MR imaging and Gleason score in prostate cancer.

PubMed

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, P<0.05), and it was lower in patients with Gleason score 3+4 than in those with Gleason score 3+3 (0.54±0.11×10 3 mm 2 /s vs. 0.64±0.12×10 -3 mm 2 /s, P<0.05). Both the nADC min and nADC mean correlated 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.

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.

PubMed

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.

Numerical simulation of transmission coefficient using c-number Langevin equation

NASA Astrophysics Data System (ADS)

Barik, Debashis; Bag, Bidhan Chandra; Ray, Deb Shankar

2003-12-01

We numerically implement the reactive flux formalism on the basis of a recently proposed c-number Langevin equation [Barik et al., J. Chem. Phys. 119, 680 (2003); Banerjee et al., Phys. Rev. E 65, 021109 (2002)] to calculate transmission coefficient. The Kramers' turnover, the T2 enhancement of the rate at low temperatures and other related features of temporal behavior of the transmission coefficient over a range of temperature down to absolute zero, noise correlation, and friction are examined for a double well potential and compared with other known results. This simple method is based on canonical quantization and Wigner quasiclassical phase space function and takes care of quantum effects due to the system order by order.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

Monitoring changes of optical attenuation coefficients of acupuncture points during laser acupuncture by optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Yimei; Yang, Hongqin; Wang, Yuhua; Zheng, Liqin; Xie, Shusen

2010-11-01

The physical properties of acupuncture point were important to discover the mechanism of acupuncture meridian. In this paper, we used an optical coherence tomography to monitor in vivo the changes of optical attenuation coefficients of Hegu acupuncture point and non-acupuncture point during laser irradiation on Yangxi acupuncture point. The optical attenuation coefficients of Hegu acupuncture point and non-acupuncture point were obtained by fitting the raw data according to the Beer-Lambert's law. The experimental results showed that the optical attenuation coefficient of Hegu acupuncture point decreased during the laser acupuncture, in contrast to a barely changed result in that of non-acupuncture point. The significant change of optical attenuation coefficient of Hegu acupuncture point indicated that there was a correlation between Hegu and Yangxi acupuncture points to some extent.

A Physical Interpretation of the Phenomenological Coefficients of Membrane Permeability

PubMed Central

Kedem, O.; Katchalsky, A.

1961-01-01

A "translation" of the phenomenological permeability coefficients into friction and distribution coefficients amenable to physical interpretation is presented. Expressions are obtained for the solute permeability coefficient ω and the reflection coefficient σ for both non-electrolytic and electrolytic permeants. An analysis of the coefficients is given for loose membranes as well as for dense natural membranes where transport may go through capillaries or by solution in the lipoid parts of the membrane. Water diffusion and filtration and the relation between these and capillary pore radius of the membrane are discussed. For the permeation of ions through the charged membranes equations are developed for the case of zero electrical current in the membrane. The correlation of σ with ω and Lp for electrolytes resembles that for non-electrolytes. In this case ω and σ depend markedly on ion concentration and on the charge density of the membrane. The reflection coefficient may assume negative values indicating anomalous osmosis. An analysis of the phenomena of anomalous osmosis was carried out for the model of Teorell and Meyer and Sievers and the results agree with the experimental data of Loeb and of Grim and Sollner. A set of equations and reference curves are presented for the evaluation of ω and σ in the transport of polyvalent ions through charged membranes. PMID:13752127

The effect of chalk on the finger-hold friction coefficient in rock climbing.

PubMed

Amca, Arif Mithat; Vigouroux, Laurent; Aritan, Serdar; Berton, Eric

2012-11-01

The main purpose of this study was to examine the effect of chalk on the friction coefficient between climber's fingers and two different rock types (sandstone and limestone). The secondary purpose was to investigate the effects of humidity and temperature on the friction coefficient and on the influence of chalk. Eleven experienced climbers took part in this study and 42 test sessions were performed. Participants hung from holds which were fixed on a specially designed hang board. The inclination of the hang board was progressively increased until the climber's hand slipped from the holds. The angle of the hang board was simultaneously recorded by using a gyroscopic sensor and the friction coefficient was calculated at the moment of slip. The results showed that there was a significant positive effect of chalk on the coefficient of friction (+18.7% on limestone and +21.6% on sandstone). Moreover sandstone had a higher coefficient of friction than limestone (+15.6% without chalk, +18.4% with chalk). These results confirmed climbers' belief that chalk enhances friction. However, no correlation with humidity/temperature and friction coefficient was noted which suggested that additional parameters should be considered in order to understand the effects of climate on finger friction in rock climbing.

Determination of corneal elasticity coefficient using the ORA database.

PubMed

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.

Second-degree Stokes coefficients from multi-satellite SLR

NASA Astrophysics Data System (ADS)

Bloßfeld, Mathis; Müller, Horst; Gerstl, Michael; Štefka, Vojtěch; Bouman, Johannes; Göttl, Franziska; Horwath, Martin

2015-09-01

The long wavelength part of the Earth's gravity field can be determined, with varying accuracy, from satellite laser ranging (SLR). In this study, we investigate the combination of up to ten geodetic SLR satellites using iterative variance component estimation. SLR observations to different satellites are combined in order to identify the impact of each satellite on the estimated Stokes coefficients. The combination of satellite-specific weekly or monthly arcs allows to reduce parameter correlations of the single-satellite solutions and leads to alternative estimates of the second-degree Stokes coefficients. This alternative time series might be helpful for assessing the uncertainty in the impact of the low-degree Stokes coefficients on geophysical investigations. In order to validate the obtained time series of second-degree Stokes coefficients, a comparison with the SLR RL05 time series of the Center of Space Research (CSR) is done. This investigation shows that all time series are comparable to the CSR time series. The precision of the weekly/monthly and coefficients is analyzed by comparing mass-related equatorial excitation functions with geophysical model results and reduced geodetic excitation functions. In case of , the annual amplitude and phase of the DGFI solution agrees better with three of four geophysical model combinations than other time series. In case of , all time series agree very well to each other. The impact of on the ice mass trend estimates for Antarctica are compared based on CSR GRACE RL05 solutions, in which different monthly time series are used for replacing. We found differences in the long-term Antarctic ice loss of Gt/year between the GRACE solutions induced by the different SLR time series of CSR and DGFI, which is about 13 % of the total ice loss of Antarctica. This result shows that Antarctic ice mass loss quantifications must be carefully interpreted.

Closure and ratio correlation analysis of lunar chemical and grain size data

NASA Technical Reports Server (NTRS)

Butler, J. C.

1976-01-01

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

Application of New Partition Coefficients to Modeling Plagioclase

NASA Technical Reports Server (NTRS)

Fagan, A. L.; Neal, C. R.; Rapp, J. F.; Draper, D. S.; Lapen, T. J.

2017-01-01

Previously, studies that determined the partition coefficient for an element, i, between plagioclase and the residual basaltic melt (Di plag) have been conducted using experimental conditions dissimilar from the Moon, and thus these values are not ideal for modeling plagioclase fractionation in a lunar system. However, recent work [1] has determined partition coefficients for plagioclase at lunar oxygen fugacities, and resulted in plagioclase with Anorthite contents =An90; these are significantly more calcic than plagioclase in previous studies, and the An content has a profound effect on partition coefficient values [2,3]. Plagioclase D-values, which are dependent on the An content of the crystal [e.g., 2-6], can be determined using published experimental data and the correlative An contents. Here, we examine new experimental data from [1] to ascertain their effect on the calculation of equilibrium liquids from Apollo 16 sample 60635,2. This sample is a coarse grained, subophitic impact melt composed of 55% plagioclase laths with An94.4-98.7 [7,8], distinctly more calcic than of previous partition coefficient studies (e.g., [3-6, 9-10]). Sample 60635,2 is notable as having several plagioclase trace element analyses containing a negative Europium anomaly (-Eu) in the rare-earth element (REE) profile, rather than the typical positive Eu anomaly (+Eu) [7-8] (Fig. 1). The expected +Eu is due to the similarity in size and charge with Ca2+, thereby allowing Eu2+ to be easily taken up by the plagioclase crystal structure, in contrast to the remaining REE3+. Some 60635,2 plagioclase crystals only have +Eu REE profiles, some only have -Eu REE profiles, and some +Eu and -Eu analyses in different areas on a single crystal [7, 8]. Moreover, there does not seem to be any core-rim association with the +Eu or -Eu analyses, nor does there appear to be a correlation between the size, shape, or location of a particular crystal within the sample and the sign of its Eu anomaly, which

Phospholipid Diffusion Coefficients of Cushioned Model Membranes determined via Z-Scan Fluorescence Correlation Spectroscopy

PubMed Central

Sterling, Sarah M.; Allgeyer, Edward S.; Fick, Jörg; Prudovsky, Igor; Mason, Michael D.; Neivandt, David J.

2013-01-01

Model cellular membranes enable the study of biological processes in a controlled environment and reduce the traditional challenges associated with live or fixed cell studies. However, model membrane systems based on the air/water or oil/solution interface do not allow for incorporation of transmembrane proteins, or for the study of protein transport mechanisms. Conversely, a phospholipid bilayer deposited via the Langmuir-Blodgett/Langmuir Schaefer method on a hydrogel layer is potentially an effective mimic of the cross-section of a biological membrane, and facilitates both protein incorporation and transport studies. Prior to application, however, such membranes must be fully characterized, particularly with respect to the phospholipid bilayer phase transition temperature. Here we present a detailed characterization of the phase transition temperature of the inner and outer leaflets of a chitosan supported model membrane system. Specifically, the lateral diffusion coefficient of each individual leaflet has been determined as a function of temperature. Measurements were performed utilizing z-scan fluorescence correlation spectroscopy (FCS), a technique that yields calibration-free diffusion information. Analysis via the method of Wawrezinieck and coworkers, revealed that phospholipid diffusion changes from raft-like to free diffusion as the temperature is increased; an insight into the dynamic behavior of hydrogel supported membranes not previously reported. PMID:23705855

Coding stimulus amplitude by correlated neural activity

NASA Astrophysics Data System (ADS)

Metzen, Michael G.; Ávila-Åkerberg, Oscar; Chacron, Maurice J.

2015-04-01

While correlated activity is observed ubiquitously in the brain, its role in neural coding has remained controversial. Recent experimental results have demonstrated that correlated but not single-neuron activity can encode the detailed time course of the instantaneous amplitude (i.e., envelope) of a stimulus. These have furthermore demonstrated that such coding required and was optimal for a nonzero level of neural variability. However, a theoretical understanding of these results is still lacking. Here we provide a comprehensive theoretical framework explaining these experimental findings. Specifically, we use linear response theory to derive an expression relating the correlation coefficient to the instantaneous stimulus amplitude, which takes into account key single-neuron properties such as firing rate and variability as quantified by the coefficient of variation. The theoretical prediction was in excellent agreement with numerical simulations of various integrate-and-fire type neuron models for various parameter values. Further, we demonstrate a form of stochastic resonance as optimal coding of stimulus variance by correlated activity occurs for a nonzero value of noise intensity. Thus, our results provide a theoretical explanation of the phenomenon by which correlated but not single-neuron activity can code for stimulus amplitude and how key single-neuron properties such as firing rate and variability influence such coding. Correlation coding by correlated but not single-neuron activity is thus predicted to be a ubiquitous feature of sensory processing for neurons responding to weak input.

Measurements of Heat-Transfer and Friction Coefficients for Helium Flowing in a Tube at Surface Temperatures up to 5900 Deg R

NASA Technical Reports Server (NTRS)

Taylor, Maynard F.; Kirchgessner, Thomas A.

1959-01-01

Measurements of average heat transfer and friction coefficients and local heat transfer coefficients were made with helium flowing through electrically heated smooth tubes with length-diameter ratios of 60 and 92 for the following range of conditions: Average surface temperature from 1457 to 4533 R, Reynolds numbe r from 3230 to 60,000, heat flux up to 583,200 Btu per hr per ft2 of heat transfer area, and exit Mach numbe r up to 1.0. The results indicate that, in the turbulent range of Reynolds number, good correlation of the local heat transfer coefficients is obtained when the physical properties and density of helium are evaluated at the surface temperature. The average heat transfer coefficients are best correlated on the basis that the coefficient varies with [1 + (L/D))(sup -0,7)] and that the physical properties and density are evaluated at the surface temperature. The average friction coefficients for the tests with no heat addition are in complete agreement with the Karman-Nikuradse line. The average friction coefficients for heat addition are in poor agreement with the accepted line.

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.

PubMed

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.

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

Computational Fluid Dynamics Based Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

NASA Technical Reports Server (NTRS)

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. The work presented under this task uses the first-principles based Computational Fluid Dynamics (CFD) technique to compute heat transfer from 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 tank wall and cryogenic propellant, and that between tank wall and ullage gas were then simulated. The results showed that 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.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Correlation of 18F-FDG PET and MRI Apparent Diffusion Coefficient Histogram Metrics with Survival in Diffuse Intrinsic Pontine Glioma: A Report from the Pediatric Brain Tumor Consortium.

PubMed

Zukotynski, Katherine A; Vajapeyam, Sridhar; Fahey, Frederic H; Kocak, Mehmet; Brown, Douglas; Ricci, Kelsey I; Onar-Thomas, Arzu; Fouladi, Maryam; Poussaint, Tina Young

2017-08-01

The purpose of this study was to describe baseline 18 F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain 18 F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. 18 F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and 18 F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [ P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [ P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [ P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [ P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher

Reconstructing networks from dynamics with correlated noise

NASA Astrophysics Data System (ADS)

Tam, H. C.; Ching, Emily S. C.; Lai, Pik-Yin

2018-07-01

Reconstructing the structure of complex networks from measurements of the nodes is a challenge in many branches of science. External influences are always present and act as a noise to the networks of interest. In this paper, we present a method for reconstructing networks from measured dynamics of the nodes subjected to correlated noise that cannot be approximated by a white noise. This method can reconstruct the links of both bidirectional and directed networks, the correlation time and strength of the noise, and also the relative coupling strength of the links when the coupling functions have certain properties. Our method is built upon theoretical relations between network structure and measurable quantities from the dynamics that we have derived for systems that have fixed point dynamics in the noise-free limit. Using these theoretical results, we can further explain the shortcomings of two common practices of inferring links for bidirectional networks using the Pearson correlation coefficient and the partial correlation coefficient.

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

PubMed Central

Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

Background In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Methods Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. Results The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). Conclusions In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends. PMID:24339927

Channel correlation of free space optical communication systems with receiver diversity in non-Kolmogorov atmospheric turbulence

NASA Astrophysics Data System (ADS)

Ma, Jing; Fu, Yulong; Tan, Liying; Yu, Siyuan; Xie, Xiaolong

2018-05-01

Spatial diversity as an effective technique to mitigate the turbulence fading has been widely utilized in free space optical (FSO) communication systems. The received signals, however, will suffer from channel correlation due to insufficient spacing between component antennas. In this paper, the new expressions of the channel correlation coefficient and specifically its components (the large- and small-scale channel correlation coefficients) for a plane wave with aperture effects are derived for horizontal link in moderate-to-strong turbulence, using a non-Kolmogorov spectrum that has a generalized power law in the range of 3-4 instead of the fixed classical Kolmogorov power law of 11/3. And then the influence of power law variations on the channel correlation coefficient and its components are analysed. The numerical results indicated that various value of the power law lead to varying effects on the channel correlation coefficient and its components. This work will help with the further investigation on the fading correlation in spatial diversity systems.

Development of stock correlation networks using mutual information and financial big data.

PubMed

Guo, Xue; Zhang, Hu; Tian, Tianhai

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices.

Development of stock correlation networks using mutual information and financial big data

PubMed Central

Guo, Xue; Zhang, Hu

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices. PMID:29668715

Estimation of soil-soil solution distribution coefficient of radiostrontium using soil properties.

PubMed

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.

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Correlations between corneal and total wavefront aberrations

NASA Astrophysics Data System (ADS)

Mrochen, Michael; Jankov, Mirko; Bueeler, Michael; Seiler, Theo

2002-06-01

Purpose: Corneal topography data expressed as corneal aberrations are frequently used to report corneal laser surgery results. However, the optical image quality at the retina depends on all optical elements of the eye such as the human lens. Thus, the aim of this study was to investigate the correlations between the corneal and total wavefront aberrations and to discuss the importance of corneal aberrations for representing corneal laser surgery results. Methods: Thirty three eyes of 22 myopic subjects were measured with a corneal topography system and a Tschernig-type wavefront analyzer after the pupils were dilated to at least 6 mm in diameter. All measurements were centered with respect to the line of sight. Corneal and total wavefront aberrations were calculated up to the 6th Zernike order in the same reference plane. Results: Statistically significant correlations (p < 0.05) between the corneal and total wavefront aberrations were found for the astigmatism (C3,C5) and all 3rd Zernike order coefficients such as coma (C7,C8). No statistically significant correlations were found for all 4th to 6th order Zernike coefficients except for the 5th order horizontal coma C18 (p equals 0.003). On average, all Zernike coefficients for the corneal aberrations were found to be larger compared to Zernike coefficients for the total wavefront aberrations. Conclusions: Corneal aberrations are only of limited use for representing the optical quality of the human eye after corneal laser surgery. This is due to the lack of correlation between corneal and total wavefront aberrations in most of the higher order aberrations. Besides this, the data present in this study yield towards an aberration balancing between corneal aberrations and the optical elements within the eye that reduces the aberration from the cornea by a certain degree. Consequently, ideal customized ablations have to take both, corneal and total wavefront aberrations, into consideration.

Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

ERIC Educational Resources Information Center

Mitchell, Mark L.

Understanding correlation coefficients is difficult for students. A free computer program that helps introductory psychology students distinguish between positive and negative correlation, and which also teaches them to understand the differences between correlation coefficients of different size is described in this paper. The program is…

Determination of blade-to-coolant heat-transfer coefficients on a forced-convection, water-cooled, single-stage turbine

NASA Technical Reports Server (NTRS)

Freche, John C; Schum, Eugene F

1951-01-01

Blade-to-coolant convective heat-transfer coefficients were obtained on a forced-convection water-cooled single-stage turbine over a large laminar flow range and over a portion of the transition range between laminar and turbulent flow. The convective coefficients were correlated by the general relation for forced-convection heat transfer with laminar flow. Natural-convection heat transfer was negligible for this turbine over the Grashof number range investigated. Comparison of turbine data with stationary tube data for the laminar flow of heated liquids showed good agreement. Calculated average midspan blade temperatures using theoretical gas-to-blade coefficients and blade-to-coolant coefficients from stationary-tube data resulted in close agreement with experimental data.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

PubMed

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

The Proper Sequence for Correcting Correlation Coefficients for Range Restriction and Unreliability.

ERIC Educational Resources Information Center

Stauffer, Joseph M.; Mendoza, Jorge L.

2001-01-01

Uses classical test theory to show that it is the nature of the range restriction, rather than the nature of the available reliability coefficient, that determines the sequence for applying corrections for range restriction and unreliability. Shows how the common rule of thumb for choosing the sequence is tenable only when the correction does not…

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

Apparent diffusion coefficients in prostate cancer: correlation with molecular markers Ki-67, HIF-1α and VEGF.

PubMed

Ma, Teng; Yang, Shaolin; Jing, Haiyan; Cong, Lin; Cao, Zhixin; Liu, Zhiling; Huang, Zhaoqin

2018-03-01

Prostate cancer (PCa) is the second most common cancer in men. The Gleason score (GS) and biomarkers play important roles in the diagnosis and treatment of patients with PCa. The purpose of this study was to investigate the relationship between the apparent diffusion coefficient (ADC) and the molecular markers Ki-67, hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) in PCa. Thirty-nine patients with 39 lesions, who had been diagnosed with PCa, were enrolled in this study. All patients underwent diffusion-weighted magnetic resonance imaging (DW-MRI) (b = 800 s/mm 2 ). The expression of Ki-67, HIF-1α and VEGF was assessed by immunohistochemistry. Statistical analysis was applied to analyze the association between ADC and prostate-specific antigen (PSA), GS and the expression of Ki-67, HIF-1α and VEGF. The group differences in ADC among different grades of Ki-67, HIF-1α and VEGF were also analyzed. The mean ± standard deviation of ADC was (0.76 ± 0.27) × 10 -3  mm 2 /s. ADC correlated negatively with PSA and GS (p < 0.05). The Ki-67 staining index (SI), HIF-1α expression and VEGF expression in PCa were correlated inversely with ADC, controlling for age (r = -0.332, p < 0.05; r = -0.662, p < 0.0005; and r = -0.714, p < 0.0005, respectively). ADC showed a significant difference among different grades of Ki-67 (F = 9.164, p = 0.005), HIF-1α (F = 40.333, p < 0.0005) and VEGF (F = 22.048, p < 0.0005). In conclusion, ADC was correlated with PSA, GS, and Ki-67, HIF-1α and VEGF expression in patients with PCa. ADC may be used to evaluate tumor proliferation, hypoxia and angiogenesis in PCa. Copyright © 2018 John Wiley & Sons, Ltd.

Correlation between national influenza surveillance data and google trends in South Korea.

PubMed

Cho, Sungjin; Sohn, Chang Hwan; Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Long sequence correlation coprocessor

NASA Astrophysics Data System (ADS)

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.

Linear Least Squares for Correlated Data

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1988-01-01

Throughout the literature authors have consistently discussed the suspicion that regression results were less than satisfactory when the independent variables were correlated. Camm, Gulledge, and Womer, and Womer and Marcotte provide excellent applied examples of these concerns. Many authors have obtained partial solutions for this problem as discussed by Womer and Marcotte and Wonnacott and Wonnacott, which result in generalized least squares algorithms to solve restrictive cases. This paper presents a simple but relatively general multivariate method for obtaining linear least squares coefficients which are free of the statistical distortion created by correlated independent variables.

Correlation and simple linear regression.

PubMed

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.

Collisional Dissociation of CO: ab initio Potential Energy Surfaces and Quasiclassical Trajectory Rate Coefficients

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Jaffe, Richard L.; Chaban, Galina M.

2016-01-01

We have generated accurate global potential energy surfaces for CO+Ar and CO+O that correlate with atom-diatom pairs in their ground electronic states based on extensive ab initio electronic structure calculations and used these potentials in quasi-classical trajectory nuclear dynamics calculations to predict the thermal dissociation rate coefficients over 5000- 35000 K. Our results are not compatible with the 20-45 year old experimental results. For CO + Ar we obtain fairly good agreement with the experimental rate coefficients of Appleton et al. (1970) and Mick and Roth (1993), but our computed rate coefficients exhibit a stronger temperature dependence. For CO + O our dissociation rate coefficient is in close agreement with the value from the Park model, which is an empirical adjustment of older experimental results. However, we find the rate coefficient for CO + O is only 1.5 to 3.3 times larger than CO + Ar over the temperature range of the shock tube experiments (8000-15,000 K). The previously accepted value for this rate coefficient ratio is 15, independent of temperature. We also computed the rate coefficient for the CO + O ex- change reaction which forms C + O2. We find this reaction is much faster than previously believed and is the dominant process in the removal of CO at temperatures up to 16,000 K. As a result, the dissociation of CO is accomplished in two steps (react to form C+O2 and then O2 dissociates) that are endothermic by 6.1 and 5.1 eV, instead of one step that requires 11.2 eV to break the CO bond.

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

NASA Astrophysics Data System (ADS)

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.

Concentration Dependence of Pool Nucleate Boiling Heat Transfer Coefficients for R134a and Polyolester Oil System

NASA Astrophysics Data System (ADS)

Sato, Tomoaki; Takaishi, Yoshinori; Oguchi, Kosei

This paper presents experimental results of the concentration dependence of heat transfer coefficients for mixtures of R134a and polyolester (POE) oil under the conditions of pool nuc1eateboiling. The experiments are conducted by means of ah horizontal platinum wire at saturation tel11peraturesof 9, 19, and 29°C and at oil concentrations from 0 to 8 mass%. The present results show that the boiling heat transfer coefficient for the system concerned decreases with increasing oil concentration as a whole but increases slightly at a low oil concentration of about 4 mass%. A correlation equation is also given as a function of heat flux, temperature and oil concentration to reproduce the experimental boiling heat transfer coefficient within an uncertainly of about±15%.

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

PubMed

Waller, Niels G

2016-01-01

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

Thermodiffusion Coefficient Analysis of n-Dodecane /n-Hexane Mixture at Different Mass Fractions and Pressure Conditions

NASA Astrophysics Data System (ADS)

Lizarraga, Ion; Bou-Ali, M. Mounir; Santamaría, C.

2018-03-01

In this study, the thermodiffusion coefficient of n-dodecane/n-hexane binary mixture at 25 ∘C mean temperature was determined for several pressure conditions and mass fractions. The experimental technique used to determine the thermodiffusion coefficient was the thermograviational column of cylindrical configuration. In turn, thermophysical properties, such as density, thermal expansion, mass expansion and dynamic viscosity up to 10 MPa were also determined. The results obtained in this work showed a linear relation between the thermophysical properties and the pressure. Thermodiffusion coefficient values confirm a linear effect when the pressure increases. Additionally, a new correlation based on the thermodiffusion coefficient for n C12/n C6 binary mixture at 25 ∘C temperature for any mass fraction and pressures, which reproduces the data within the experimental error, was proposed.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

"L"-Bivariate and "L"-Multivariate Association Coefficients. Research Report. ETS RR-08-40

ERIC Educational Resources Information Center

Kong, Nan; Lewis, Charles

2008-01-01

Given a system of multiple random variables, a new measure called the "L"-multivariate association coefficient is defined using (conditional) entropy. Unlike traditional correlation measures, the L-multivariate association coefficient measures the multiassociations or multirelations among the multiple variables in the given system; that…

[Correlations between MRI apparent diffusion coefficient and histological grade and molecular biology of breast invasive ductal carcinoma].

PubMed

Yu, Xuejuan; Liu, Shangang; Chen, Zhaoqiu; Zhang, Pinliang; Zhang, Jianbo; Xu, Liang; Liu, Zengjun; Ren, Ruimei

2014-08-01

To study the correlation between the MRI apparent diffusion coefficient (ADC) value and histological grade and molecular biology of breast invasive ductal carcinoma (IDC). This retrospective study included 125 patients with IDC verified by pathology from February 2010 to February 2013. Conventional MRI and diffusion-weighted imaging (DWI) examination were performed using a 3.0T scanner with diffusion factor of 0 and 800 s/mm(2). The region of interest (ROI) was drawn on the largest lesion and/or its two adjacent slices. The ADC value of the whole tumor was calculated as the mean ADC value. The correlation between mean ADCs and histological grade and biological factors was analyzed. The mean ADC of pathological grade I, II and III IDC was (1.152 ± 0.072)×10(-3) mm(2)/s, (1.102 ± 0.101)×10(-3) mm(2)/s, and (1.035 ± 0.107)×10(-3) mm(2)/s, respectively. There was a statistically significant difference among them (P = 0.003). Statistically a significant difference was observed between grade III and I (P = 0.034), grade III and II (P = 0.006), but not between grade I and II (P = 0.741). A significant correlation was observed between ADC value and pathological grade (r = -0.342, P < 0.001). The median ADC values were significantly higher in the ER-negative than in the ER-positive cases [(1.130 ± 0.115)×10(-3) mm(2)/s vs. (1.060 ± 0.089) ×10(-3) mm(2)/s, P < 0.001)], in PR-negative than in PR-positive cases [(1.121 ± 0.106)×10(-3) mm(2)/s vs. (1.055 ± 0.096) ×10(-3) mm(2)/s, P < 0.001)], and in Ki-67-negative than in Ki-67-positive cases [(1.153 ± 0.090)×10(-3) mm(2)/s vs. (1.063 ± 0.101) ×10(-3) mm(2)/s, P < 0.001]. A statistically significant correlation was observed between ADC value and expressions of ER, PR, and Ki-67 (r = -0.311, r = -0.317, r = -0.414, P < 0.001). ADC value of breast invasive ductal carcinoma is correlated with histological grade, and expression of ER, PR and Ki-67.

Tensor models, Kronecker coefficients and permutation centralizer algebras

NASA Astrophysics Data System (ADS)

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.

Expressions for the Evaporation and Condensation Coefficients in the Hertz-Knudsen Relation.

PubMed

Persad, Aaron H; Ward, Charles A

2016-07-27

Although the Hertz-Knudsen (HK) relation is often used to correlate evaporation data, the relation contains two empirical parameters (the evaporation and condensation coefficients) that have inexplicably been found to span 3 orders of magnitude. Explicit expressions for these coefficients have yet to be determined. This review will examine sources of error in the HK relation that have led to the coefficients' scatter. Through an examination of theoretical, experimental, and molecular dynamics simulation studies of evaporation, this review will show that the HK relation is incomplete, since it is missing an important physical concept: the coupling between the vapor and liquid phases during evaporation. The review also examines a modified HK relation, obtained from the quantum-mechanically based statistical rate theory (SRT) expression for the evaporation flux and applying a limit to it in which the thermal energy is dominant. Explicit expressions for the evaporation and condensation coefficients are defined in this limit, with the surprising result that the coefficients are not bounded by unity. An examination is made with 127 reported evaporation experiments of water and of ethanol, leading to a new physical interpretation of the coefficients. The review concludes by showing how seemingly small simplifications, such as assuming thermal equilibrium across the liquid-vapor interface during evaporation, can lead to the erroneous predictions from the HK relation that have been reported in the literature.

Correlation of laboratory and production freeze drying cycles.

PubMed

Kuu, Wei Y; Hardwick, Lisa M; Akers, Michael J

2005-09-30

The purpose of this study was to develop the correlation of cycle parameters between a laboratory and a production freeze-dryer. With the established correlation, key cycle parameters obtained using a laboratory dryer may be converted to those for a production dryer with minimal experimental efforts. In order to develop the correlation, it was important to consider the contributions from the following freeze-drying components: (1) the dryer, (2) the vial, and (3) the formulation. The critical parameters for the dryer are the shelf heat transfer coefficient and shelf surface radiation emissivity. The critical parameters for the vial are the vial bottom heat transfer coefficients (the contact parameter Kcs and separation distance lv), and vial top heat transfer coefficient. The critical parameter of the formulation is the dry layer mass transfer coefficient. The above heat and mass transfer coefficients were determined by freeze-drying experiments in conjunction with mathematical modeling. With the obtained heat and mass transfer coefficients, the maximum product temperature, Tbmax, during primary drying was simulated using a primary drying subroutine as a function of the shelf temperature and chamber pressure. The required shelf temperature and chamber pressure, in order to perform a successful cycle run without product collapse, were then simulated based on the resulting values of Tbmax. The established correlation approach was demonstrated by the primary drying of the model formulation 5% mannitol solution. The cycle runs were performed using a LyoStar dryer as the laboratory dryer and a BOC Edwards dryer as the production dryer. The determined normalized dried layer mass transfer resistance for 5% mannitol is expressed as RpN=0.7313+17.19l, where l is the receding dry layer thickness. After demonstrating the correlation approach using the model formulation 5% mannitol, a practical comparison study was performed for the actual product, the lactate dehydrogenase

Fuzzy correlation analysis with realization

NASA Astrophysics Data System (ADS)

Tang, Yue Y.; Fan, Xinrui; Zheng, Ying N.

1998-10-01

The fundamental concept of fuzzy correlation is briefly discussed. Based on the correlation coefficient of classic correlation, polarity correlation and fuzzy correlation, the relationship between the correlations are analyzed. A fuzzy correlation analysis has the merits of both rapidity and accuracy as some amplitude information of random signals has been utilized. It has broad prospects for application. The form of fuzzy correlative analyzer with NLX 112 fuzzy data correlator and single-chip microcomputer is introduced.

VIIRS thermal emissive bands on-orbit calibration coefficient performance using vicarious calibration results

NASA Astrophysics Data System (ADS)

Moyer, D.; Moeller, C.; De Luccia, F.

2013-09-01

The Visible Infrared Imager Radiometer Suite (VIIRS), a primary sensor on-board the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, was launched October 28, 2011. It has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). The TEBs cover the spectral wavelengths between 3.7 to 12 μm and have two 371 m and five 742 m spatial resolution bands. A VIIRS Key Performance Parameter (KPP) is the sea surface temperature (SST) which uses bands M12 (3.7 μm), M15 (10.8 μm) and M16's (12.0 μm) calibrated Science Data Records (SDRs). The TEB SDRs rely on pre-launch calibration coefficients used in a quadratic algorithm to convert the detector's response to calibrated radiance. This paper will evaluate the performance of these prelaunch calibration coefficients using vicarious calibration information from the Cross-track Infrared Sounder (CrIS) also onboard the SNPP spacecraft and the Infrared Atmospheric Sounding Interferometer (IASI) on-board the Meteorological Operational (MetOp) satellite. Changes to the pre-launch calibration coefficients' offset term c0 to improve the SDR's performance at cold scene temperatures will also be discussed.

Wavelet-based image compression using shuffling and bit plane correlation

NASA Astrophysics Data System (ADS)

Kim, Seungjong; Jeong, Jechang

2000-12-01

In this paper, we propose a wavelet-based image compression method using shuffling and bit plane correlation. The proposed method improves coding performance in two steps: (1) removing the sign bit plane by shuffling process on quantized coefficients, (2) choosing the arithmetic coding context according to maximum correlation direction. The experimental results are comparable or superior for some images with low correlation, to existing coders.

Semi-quantitative spectrographic analysis and rank correlation in geochemistry

USGS Publications Warehouse

Flanagan, F.J.

1957-01-01

The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

Partition Coefficients of Organics between Water and Carbon Dioxide Revisited: Correlation with Solute Molecular Descriptors and Solvent Cohesive Properties.

PubMed

Roth, Michal

2016-12-06

High-pressure phase behavior of systems containing water, carbon dioxide and organics has been important in several environment- and energy-related fields including carbon capture and storage, CO 2 sequestration and CO 2 -assisted enhanced oil recovery. Here, partition coefficients (K-factors) of organic solutes between water and supercritical carbon dioxide have been correlated with extended linear solvation energy relationships (LSERs). In addition to the Abraham molecular descriptors of the solutes, the explanatory variables also include the logarithm of solute vapor pressure, the solubility parameters of carbon dioxide and water, and the internal pressure of water. This is the first attempt to include also the properties of water as explanatory variables in LSER correlations of K-factor data in CO 2 -water-organic systems. Increasing values of the solute hydrogen bond acidity, the solute hydrogen bond basicity, the solute dipolarity/polarizability, the internal pressure of water and the solubility parameter of water all tend to reduce the K-factor, that is, to favor the solute partitioning to the water-rich phase. On the contrary, increasing values of the solute characteristic volume, the solute vapor pressure and the solubility parameter of CO 2 tend to raise the K-factor, that is, to favor the solute partitioning to the CO 2 -rich phase.

Shear wave elastography results correlate with liver fibrosis histology and liver function reserve.

PubMed

Feng, Yan-Hong; Hu, Xiang-Dong; Zhai, Lin; Liu, Ji-Bin; Qiu, Lan-Yan; Zu, Yuan; Liang, Si; Gui, Yu; Qian, Lin-Xue

2016-05-07

To evaluate the correlation of shear wave elastography (SWE) results with liver fibrosis histology and quantitative function reserve. Weekly subcutaneous injection of 60% carbon tetrachloride (1.5 mL/kg) was given to 12 canines for 24 wk to induce experimental liver fibrosis, with olive oil given to 2 control canines. At 24 wk, liver condition was evaluated using clinical biochemistry assays, SWE imaging, lidocaine metabolite monoethylglycine-xylidide (MEGX) test, and histologic fibrosis grading. Clinical biochemistry assays were performed at the institutional central laboratory for routine liver function evaluation. Liver stiffness was measured in triplicate from three different intercostal spaces and expressed as mean liver stiffness modulus (LSM). Plasma concentrations of lidocaine and its metabolite MEGX were determined using high-performance liquid chromatography repeated in duplicate. Liver biopsy samples were fixed in 10% formaldehyde, and liver fibrosis was graded using the modified histological activity index Knodell score (F0-F4). Correlations among histologic grading, LSM, and MEGX measures were analyzed with the Pearson linear correlation coefficient. At 24 wk liver fibrosis histologic grading was as follows: F0, n = 2 (control); F1, n = 0; F2, n = 3; F3, n = 7; and F4, n = 2. SWE LSM was positively correlated with histologic grading (r = 0.835, P < 0.001). Specifically, the F4 group had a significantly higher elastic modulus than the F3, F2, and F0 groups (P = 0.002, P = 0.003, and P = 0.006, respectively), and the F3 group also had a significantly higher modulus than the control F0 group (P = 0.039). LSM was negatively associated with plasma MEGX concentrations at 30 min (r = -0.642; P = 0.013) and 60 min (r = -0.651; P = 0.012), time to ½ of the maximum concentration (r = -0.538; P = 0.047), and the area under the curve (r = -0.636; P = 0.014). Multiple comparisons showed identical differences in these three measures: significantly lower with F4 (P

Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.

PubMed

Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin

2015-06-01

We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.

Aging in freely evolving granular gas with impact velocity dependent coefficient of restitution

NASA Astrophysics Data System (ADS)

Kumari, Shikha; Ahmad, Syed Rashid

2018-05-01

The evolution of granular system is governed by the concept of coefficient of restitution that gives a relationship between normal component of relative velocities before and after collision. Most of the studies consider a simplified collision model where particles interact through coefficient of restitution which is a constant while in reality, the coefficient of restitution must be a variable that depends on the impact velocity of colliding particles. In this work, we have considered the aging in the velocity autocorrelation function, A(τw, τ) for a granular gas of realistic particles interacting through coefficient of restitution that is depending on impact velocity. Molecular dynamics simulation is used to study granular gas that is evolving freely in absence of any external force. From the simulation results, we observe that A(τw, τ) depends explicitly on waiting time τw and collision time τ. Initially, the function decays exponentially but as the waiting time increases the decay of function becomes slow due to correlations that emerge in velocity field.

Test results for rotordynamic coefficients of anti-swirl self-injection seals

NASA Technical Reports Server (NTRS)

Kim, C. H.; Lee, Y. B.

1994-01-01

Test results are presented for rotordynamic coefficients and leakage for three annular seals which use anti-swirl self-injection concept to yield significant improvement in whirl frequency ratios as compared to smooth and damper seals. A new anti-swirl self-inection mechanism is achieved by deliberately machining self-injection holes inside the seal stator mechanism which is used to achieve effective reduction of the tangential flow which is considered as a prime cause of rotor instability in high performance turbomachinery. Test results show that the self-injection mechanism significantly improves whirl frequency ratios; however, the leakage performance degrades due to the introduction of the self-injection mechanism. Through a series of the test program, an optimum anti-swirl self-injection seal which uses a labyrinth stator surface with anti-axial flow injections is selected to obtain a significant improvement in the whirl frequency ratio as compared to a damper seal, while showing moderate leakage performance. Best whirl frequency ratio is achieved by an anti-swirl self-injection seal of 12 holes anti-swirl and 6 degree anti-leakage injection with a labyrinth surface configuration. When compared to a damper seal, the optimum configuration outperforms the whirl frequency ratio by a factor of 2.

Effective diffusion coefficient including the Marangoni effect

NASA Astrophysics Data System (ADS)

Kitahata, Hiroyuki; Yoshinaga, Natsuhiko

2018-04-01

Surface-active molecules supplied from a particle fixed at the water surface create a spatial gradient of the molecule concentration, resulting in Marangoni convection. Convective flow transports the molecules far from the particle, enhancing diffusion. We analytically derive the effective diffusion coefficient associated with the Marangoni convection rolls. The resulting estimated effective diffusion coefficient is consistent with our numerical results and the apparent diffusion coefficient measured in experiments.

Information Filtering via Clustering Coefficients of User-Object Bipartite Networks

NASA Astrophysics Data System (ADS)

Guo, Qiang; Leng, Rui; Shi, Kerui; Liu, Jian-Guo

The clustering coefficient of user-object bipartite networks is presented to evaluate the overlap percentage of neighbors rating lists, which could be used to measure interest correlations among neighbor sets. The collaborative filtering (CF) information filtering algorithm evaluates a given user's interests in terms of his/her friends' opinions, which has become one of the most successful technologies for recommender systems. In this paper, different from the object clustering coefficient, users' clustering coefficients of user-object bipartite networks are introduced to improve the user similarity measurement. Numerical results for MovieLens and Netflix data sets show that users' clustering effects could enhance the algorithm performance. For MovieLens data set, the algorithmic accuracy, measured by the average ranking score, can be improved by 12.0% and the diversity could be improved by 18.2% and reach 0.649 when the recommendation list equals to 50. For Netflix data set, the accuracy could be improved by 14.5% at the optimal case and the popularity could be reduced by 13.4% comparing with the standard CF algorithm. Finally, we investigate the sparsity effect on the performance. This work indicates the user clustering coefficients is an effective factor to measure the user similarity, meanwhile statistical properties of user-object bipartite networks should be investigated to estimate users' tastes.

Kubo number and magnetic field line diffusion coefficient for anisotropic magnetic turbulence.

PubMed

Pommois, P; Veltri, P; Zimbardo, G

2001-06-01

The magnetic field line diffusion coefficients Dx and D(y) are obtained by numerical simulations in the case that all the magnetic turbulence correlation lengths l(x), l(y), and l(z) are different. We find that the variety of numerical results can be organized in terms of the Kubo number, the definition of which is extended from R=(deltaB/B(0))(l(parallel)/l(perpendicular)) to R=(deltaB/B(0))(l(z)/l(x)), for l(x) > or = l(y). Here, l(parallel) (l(perpendicular)) is the correlation length along (perpendicular to) the average field B(0)=B(0)ê(z). We have anomalous, non-Gaussian transport for R less, similar 0.1, in which case the mean square deviation scales nonlinearly with time. For R greater, similar 1 we have several Gaussian regimes: an almost quasilinear regime for 0.1 less, similar R less, similar 1, an intermediate, transition regime for 1 less, similar R less, similar 10, and a percolative regime for R greater, similar 10. An analytical form of the diffusion coefficient is proposed, D(i)=D(deltaBl(z)/B(0)l(x))(mu)(l(i)/l(x))(nu)l(2)(x)/l(z), which well describes the numerical simulation results in the quasilinear, intermediate, and percolative regimes.

Non-Markovian renormalization of kinetic coefficients for drift-type turbulence in magnetized plasmas

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

Zagorodny, A.; Weiland, J.

2009-05-15

The problem of derivation of the kinetic equations for inhomogeneous plasma in an external magnetic field is considered. The Fokker-Planck-type equations with the non-Markovian kinetic coefficients are proposed. In the time-local limit (small correlation times with respect to the distribution function relaxation time) the relations obtained recover the results known from the appropriate quasilinear theory and the Dupree-Weinstock theory of plasma turbulence. Kinetic calculations of the dielectric response function are also performed with regard to the influence of turbulent fields on particle motion. The equations proposed are used to describe zonal flow generation and to estimate the diffusion coefficient formore » saturated turbulence.« less

Characterization of skin friction coefficient, and relationship to stratum corneum hydration in a normal Chinese population.

PubMed

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 < 0.001 and p < 0.0001, respectively). In contrast, in males, the skin friction coefficient was positively correlated with stratum corneum hydration on the forehead and the dorsal hand skin (p < 0.05 and p < 0.0001, respectively). The 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.

Transonic Blunt Body Aerodynamic Coefficients Computation

NASA Astrophysics Data System (ADS)

Sancho, Jorge; Vargas, M.; Gonzalez, Ezequiel; Rodriguez, Manuel

2011-05-01

In the framework of EXPERT (European Experimental Re-entry Test-bed) accurate transonic aerodynamic coefficients are of paramount importance for the correct trajectory assessment and parachute deployment. A combined CFD (Computational Fluid Dynamics) modelling and experimental campaign strategy was selected to obtain accurate coefficients. A preliminary set of coefficients were obtained by CFD Euler inviscid computation. Then experimental campaign was performed at DNW facilities at NLR. A profound review of the CFD modelling was done lighten up by WTT results, aimed to obtain reliable values of the coefficients in the future (specially the pitching moment). Study includes different turbulence modelling and mesh sensitivity analysis. Comparison with the WTT results is explored, and lessons learnt are collected.

Ecology of Floristic Quality Assessment: testing for correlations between coefficients of conservatism, species traits and mycorrhizal responsiveness.

PubMed

Bauer, Jonathan T; Koziol, Liz; Bever, James D

2018-02-01

Many plant species are limited to habitats relatively unaffected by anthropogenic disturbance, so protecting these undisturbed habitats is essential for plant conservation. Coefficients of conservatism (C values) were developed as indicators of a species' sensitivity to anthropogenic disturbance, and these values are used in Floristic Quality Assessment as a means of assessing natural areas and ecological restoration. However, assigning of these values is subjective and improved quantitative validation of C values is needed. We tested whether there are consistent differences in life histories between species with high and low C values. To do this, we grew 54 species of tallgrass prairie plants in a greenhouse and measured traits that are associated with trade-offs on the fast-slow continuum of life-history strategies. We also grew plants with and without mycorrhizal fungi as a test of these species' reliance on this mutualism. We compared these traits and mycorrhizal responsiveness to C values. We found that six of the nine traits we measured were correlated with C values, and together, traits predicted up to 50 % of the variation in C values. Traits including fast growth rates and greater investment in reproduction were associated with lower C values, and slow growth rates, long-lived leaves and high root:shoot ratios were associated with higher C values. Additionally, plants with high C values and a slow life history were more responsive to mutualisms with mycorrhizal fungi. Overall, our results connect C values with life-history trade-offs, indicating that high C value species tend to share a suite of traits associated with a slow life history.

Correlation of Space Shuttle Landing Performance with Post-Flight Cardiovascular Dysfunction

NASA Technical Reports Server (NTRS)

McCluskey, R.

2004-01-01

Introduction: Microgravity induces cardiovascular adaptations resulting in orthostatic intolerance on re-exposure to normal gravity. Orthostasis could interfere with performance of complex tasks during the re-entry phase of Shuttle landings. This study correlated measures of Shuttle landing performance with post-flight indicators of orthostatic intolerance. Methods: Relevant Shuttle landing performance parameters routinely recorded at touchdown by NASA included downrange and crossrange distances, airspeed, and vertical speed. Measures of cardiovascular changes were calculated from operational stand tests performed in the immediate post-flight period on mission commanders from STS-41 to STS-66. Stand test data analyzed included maximum standing heart rate, mean increase in maximum heart rate, minimum standing systolic blood pressure, and mean decrease in standing systolic blood pressure. Pearson correlation coefficients were calculated with the null hypothesis that there was no statistically significant linear correlation between stand test results and Shuttle landing performance. A correlation coefficient? 0.5 with a p<0.05 was considered significant. Results: There were no significant linear correlations between landing performance and measures of post-flight cardiovascular dysfunction. Discussion: There was no evidence that post-flight cardiovascular stand test data correlated with Shuttle landing performance. This implies that variations in landing performance were not due to space flight-induced orthostatic intolerance.

Behavior of lateral-deformation coefficients during elastoplastic deformation of metals

NASA Astrophysics Data System (ADS)

Zimin, B. A.; Smirnov, I. V.; Sudenkov, Yu. V.

2017-06-01

The results of investigations into variation of the coefficients of lateral deformation (the Poisson ratio) during single-axis tension of samples of steel 12Kh18N10T and St3, titanium VT1, the aluminum alloy D16AM, copper M1, and a magnesium alloy are considered. The technique developed on the basis of the optoacoustic effect and simultaneous measurements of the longitudinal and surface speeds of sound in metallic samples during the tension makes it possible to measure the rates at various stages of the deformation process. The data obtained make it possible to construct the dependences of variation of the lateral-deformation coefficients at all stages of the plastic flow. The correlation of these variations both with known processes of structural reconstructions at various stages of plastic flow and with the process of localization of plastic-shear bands in the aluminum alloy is noted.

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

Graph characterization via Ihara coefficients.

PubMed

Ren, Peng; Wilson, Richard C; Hancock, Edwin R

2011-02-01

The novel contributions of this paper are twofold. First, we demonstrate how to characterize unweighted graphs in a permutation-invariant manner using the polynomial coefficients from the Ihara zeta function, i.e., the Ihara coefficients. Second, we generalize the definition of the Ihara coefficients to edge-weighted graphs. For an unweighted graph, the Ihara zeta function is the reciprocal of a quasi characteristic polynomial of the adjacency matrix of the associated oriented line graph. Since the Ihara zeta function has poles that give rise to infinities, the most convenient numerically stable representation is to work with the coefficients of the quasi characteristic polynomial. Moreover, the polynomial coefficients are invariant to vertex order permutations and also convey information concerning the cycle structure of the graph. To generalize the representation to edge-weighted graphs, we make use of the reduced Bartholdi zeta function. We prove that the computation of the Ihara coefficients for unweighted graphs is a special case of our proposed method for unit edge weights. We also present a spectral analysis of the Ihara coefficients and indicate their advantages over other graph spectral methods. We apply the proposed graph characterization method to capturing graph-class structure and clustering graphs. Experimental results reveal that the Ihara coefficients are more effective than methods based on Laplacian spectra.

Correlations among the parameters of the spherical model for eclipsing binaries

NASA Technical Reports Server (NTRS)

Sobieski, S.; White, J. E.

1971-01-01

Correlation coefficients were computed to investigate the parameters for describing the spherical model of an eclipsing binary system. Regions in parameter hyperspace were identified where strong correlations exist and, by implication, the solution determinacy is low. The results are presented in tabular form for a large number of system configurations.

Analysis of the correlation dimension for inertial particles

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

Gustavsson, Kristian; Department of Physics, Göteborg University, 41296 Gothenburg; Mehlig, Bernhard

2015-07-15

We obtain an implicit equation for the correlation dimension which describes clustering of inertial particles in a complex flow onto a fractal measure. Our general equation involves a propagator of a nonlinear stochastic process in which the velocity gradient of the fluid appears as additive noise. When the long-time limit of the propagator is considered our equation reduces to an existing large-deviation formalism from which it is difficult to extract concrete results. In the short-time limit, however, our equation reduces to a solvability condition on a partial differential equation. In the case where the inertial particles are much denser thanmore » the fluid, we show how this approach leads to a perturbative expansion of the correlation dimension, for which the coefficients can be obtained exactly and in principle to any order. We derive the perturbation series for the correlation dimension of inertial particles suspended in three-dimensional spatially smooth random flows with white-noise time correlations, obtaining the first 33 non-zero coefficients exactly.« less

Transfer coefficients in ultracold strongly coupled plasma

NASA Astrophysics Data System (ADS)

Bobrov, A. A.; Vorob'ev, V. S.; Zelener, B. V.

2018-03-01

We use both analytical and molecular dynamic methods for electron transfer coefficients in an ultracold plasma when its temperature is small and the coupling parameter characterizing the interaction of electrons and ions exceeds unity. For these conditions, we use the approach of nearest neighbor to determine the average electron (ion) diffusion coefficient and to calculate other electron transfer coefficients (viscosity and electrical and thermal conductivities). Molecular dynamics simulations produce electronic and ionic diffusion coefficients, confirming the reliability of these results. The results compare favorably with experimental and numerical data from earlier studies.

Clinical applications of correlational vestibular autorotation test.

PubMed

Hsieh, Li-Chun; Lin, Te-Ming; Chang, Yu-Min; Kuo, Terry B J; Lee, Gho-She

2015-06-01

The correlational vestibular autorotation test (VAT) system has the advantages of good test-retest reliability and calibrations of absolute degrees of eye movement are unnecessary when acquiring a cross correlation coefficient (CCC). The approach is able to efficiently detect peripheral vestibulopathies. A VAT has some drawbacks including poor test-retest reliability and slippage of sensor. This study aimed to develop a correlational VAT system and to evaluate the reliability and applicability of this system. Twenty healthy participants and 10 vertiginous patients were enrolled. Vertical and horizontal autorotations from 0 to 3 Hz with either closed or open eyes were performed. A small sensor and a wireless transmission technique were used to acquire the electro-ocular graph and head velocity signals. The two signals were analyzed using CCCs to assess the functioning of the vestibular ocular reflex (VOR). The results showed a significantly greater CCC for open-eye versus closed-eye of head autorotations. The CCCs also increased significantly with head rotational frequencies. Moreover, the CCCs significantly correlated with the VOR gains at autorotation frequencies ≥1.0 Hz. The test-retest reliability was good (intraclass correlation coefficients ≥0.85). The vertiginous participants had significantly lower individual CCCs and overall average CCC than age- and-gender matched controls.

Correlates of anxiety and depression among patients with type 2 diabetes mellitus.

PubMed

Balhara, Yatan Pal Singh; Sagar, Rajesh

2011-07-01

Research has established the relation between diabetes and depression. Both diabetes and anxiety/depression are independently associated with increased morbidity and mortality. The present study aims at assessing the prevalence of anxiety/depression among outpatients receiving treatment for type 2 diabetes. The study was conducted in the endocrinology outpatient department of an urban tertiary care center. The instruments used included a semi-structured questionnaire, HbA1c levels, fasting blood glucose and postprandial blood glucose, Brief Patient Health Questionnaire, and Hospital Anxiety and Depression Scale (HADS). Analysis was carried out using the SPSS version 16.0. Pearson's correlation coefficient was calculated to find out the correlations. ANOVA was carried out for the in between group comparisons. There was a significant correlation between the HADS-Anxiety scale and Body Mass Index (BMI) with a correlation coefficient of 0.34 (P = 0.008). Also, a significant correlation existed between HADS-Depression scale and BMI (correlation coefficient, 0.36; P = 0.004). Significant correlation were observed between the duration of daily physical exercise and HADS-Anxiety (coefficient of correlation, -0.25; P = 0.04) scores. HADS-Anxiety scores were found to be related to HbA1c levels (correlation-coefficient, 0.41; P = 0.03) and postprandial blood glucose levels (correlation-coefficient, 0.51; P = 0.02). Monitoring of biochemical parameters like HbA1c and postprandial blood glucose levels and BMI could be a guide to development of anxiety in these patients. Also, physical exercise seems to have a protective effect on anxiety in those with type 2 diabetes mellitus.

The functional correlation between rainfall rate and extinction coefficient for frequencies from 3 to 10 GHz

NASA Technical Reports Server (NTRS)

Jameson, A. R.

1990-01-01

The relationship between the rainfall rate (R) obtained from radiometric brightness temperatures and the extinction coefficient (k sub e) is investigated by computing the values of k sub e over a wide range of rainfall rates, for frequencies from 3 to 25 GHz. The results show that the strength of the relation between the R and the k sub e values exhibits considerable variation for frequencies at this range. Practical suggestions are made concerning the selection of particular frequencies for rain measurements to minimize the error in R determinations.

Correlations among the parameters of the spherical model for eclipsing binaries.

NASA Technical Reports Server (NTRS)

Sobieski, S.; White, J.

1973-01-01

Correlation coefficients have been computed to investigate the parameters used to describe the spherical model of an eclipsing binary system. Regions in parameter hyperspace have been identified where strong correlations exist and, by implication, the solution determinacy is low. The results are presented in tabular form for a large number of system configurations.

Identifying Bearing Rotordynamic Coefficients using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

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

Identifying Bearing Rotodynamic Coefficients Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

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

An update on the correlation between the cosmic radiation intensity and the geomagnetic AA index

NASA Technical Reports Server (NTRS)

Shea, M. A.; Smart, D. F.

1985-01-01

A statistical study between the cosmic ray intensity, as observed by a neutron monitor, and of the geomagnetic aa index, as representative of perturbations in the plasma and interplanetary magnetic field in the heliosphere, has been updated to specifically exclude time periods around the reversal of the solar magnetic field. The results of this study show a strong negative correlation for the period 1960 through 1968 with a correlation coefficient of approximately -0.86. However, there is essentially no correlation between the cosmic ray intensity and the aa index for the period 1972-1979 (i.e. correlation coefficient less than 0.16). These results would appear to support the theory of preferential particle propagation into the heliosphere vis the ecliptic during the period 1960-1968 and via the solar polar regions during 1972-1979.

Sherwood correlation for dissolution of pooled NAPL in porous media

NASA Astrophysics Data System (ADS)

Aydin Sarikurt, Derya; Gokdemir, Cagri; Copty, Nadim K.

2017-11-01

The rate of interphase mass transfer from non-aqueous phase liquids (NAPLs) entrapped in the subsurface into the surrounding mobile aqueous phase is commonly expressed in terms of Sherwood (Sh) correlations that are expressed as a function of flow and porous media properties. Because of the lack of precise methods for the estimation of the interfacial area separating the NAPL and aqueous phases, most studies have opted to use modified Sherwood expressions that lump the interfacial area into the interphase mass transfer coefficient. To date, there are only two studies in the literature that have developed non-lumped Sherwood correlations; however, these correlations have undergone limited validation. In this paper controlled dissolution experiments from pooled NAPL were conducted. The immobile NAPL mass is placed at the bottom of a flow cell filled with porous media with water flowing horizontally on top. Effluent aqueous phase concentrations were measured for a wide range of aqueous phase velocities and for two different porous media. To interpret the experimental results, a two-dimensional pore network model of the NAPL dissolution kinetics and aqueous phase transport was developed. The observed effluent concentrations were then used to compute best-fit mass transfer coefficients. Comparison of the effluent concentrations computed with the two-dimensional pore network model to those estimated with one-dimensional analytical solutions indicates that the analytical model which ignores the transport in the lateral direction can lead to under-estimation of the mass transfer coefficient. Based on system parameters and the estimated mass transfer coefficients, non-lumped Sherwood correlations were developed and compared to previously published data. The developed correlations, which are a significant improvement over currently available correlations that are associated with large uncertainties, can be incorporated into future modeling studies requiring non-lumped Sh

Estimation of instantaneous heat transfer coefficients for a direct-injection stratified-charge rotary engine

NASA Technical Reports Server (NTRS)

Lee, C. M.; Addy, H. E.; Bond, T. H.; Chun, K. S.; Lu, C. Y.

1987-01-01

The main objective of this report was to derive equations to estimate heat transfer coefficients in both the combustion chamber and coolant pasage of a rotary engine. This was accomplished by making detailed temperature and pressure measurements in a direct-injection stratified-charge rotary engine under a range of conditions. For each sppecific measurement point, the local physical properties of the fluids were calculated. Then an empirical correlation of the coefficients was derived by using a multiple regression program. This correlation expresses the Nusselt number as a function of the Prandtl number and Reynolds number.

Factor Scores, Structure Coefficients, and Communality Coefficients

ERIC Educational Resources Information Center

Goodwyn, Fara

2012-01-01

This paper presents heuristic explanations of factor scores, structure coefficients, and communality coefficients. Common misconceptions regarding these topics are clarified. In addition, (a) the regression (b) Bartlett, (c) Anderson-Rubin, and (d) Thompson methods for calculating factor scores are reviewed. Syntax necessary to execute all four…

Correlations of TOMS total ozone data (Nimbus-7 satellite) with tropopause height

NASA Technical Reports Server (NTRS)

Munteanu, Marie-Jeanne

1987-01-01

Two correlation studies of Total Ozone Mapping Spectrometer (TOMS) data with tropopause height from radiosondes performed over Europe showed a correlation coefficient of 0.94 and 0.96. As a result, the rms error in the prediction of tropopause height from total ozone was found to be 20 mb. Correlation between tropopause height and TOMS data was the highest of all the other correlations with variables directly derived from radiosondes or simulated thermal radiances over the location of radiosondes. Comparing the two dimensional fields of TOMS, tropopause height from radiosondes and tropopause height field from TIROS-N retrievals, we can say that the first field is much closer to the true field from radiosondes than the third. The correlation coefficient for a ten-day study between TOMS data and tropopause height from radiosondes is between 0.85 and 0.9 for 30-70N. Tropopause analysis provided by GLA model also shows a very high correlation with TOMS data.

40 CFR Figure C-4 to Subpart C of... - Illustration of the Minimum Limits for Correlation Coefficient for PM 2.5 and PM 10-2,5 Class II...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 6 2013-07-01 2013-07-01 false Illustration of the Minimum Limits for Correlation Coefficient for PM 2.5 and PM 10-2,5 Class II and III Methods C Figure C-4 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-4 Figure C-4 to Subpart C of Part 53—Illustration...

40 CFR Figure C-4 to Subpart C of... - Illustration of the Minimum Limits for Correlation Coefficient for PM 2.5 and PM 10-2.5 Class II...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Illustration of the Minimum Limits for Correlation Coefficient for PM 2.5 and PM 10-2.5 Class II and III Methods C Figure C-4 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-4 Figure C-4 to Subpart C of Part 53—Illustration...

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

NASA Technical Reports Server (NTRS)

Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

2016-01-01

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

The Correlation Between Tropical Convection and Upper Tropospheric Momentum Flux Convergence

NASA Technical Reports Server (NTRS)

O'CStarr, David; Boehm, Matthew T.

2003-01-01

In this study, the relationship between tropical convection and the meridional convergence of zonal momentum flux in the tropical upper troposphere is investigated using NOAA interpolated outgoing longwave radiation data and NCEP-NCAR reanalysis wind data. In particular, a variety of correlation coefficients are calculated between the data sets, both of which are filtered to isolate disturbances with frequencies and wavenumbers consistent with the Madden-Julian oscillation. The results show regions of significant correlation during each season, with the magnitude and area covered by significant correlation coefficients varying with season. Furthermore, it is found that the correlation structures look very similar to theoretical calculations of the atmospheric response to a region of tropical heating. This result suggests that tropical waves, in particular mixed Rossby-gravity waves, play an important role in the meridional transport zonal momentum into the deep tropical upper troposphere. Finally, these findings have implications to the generation of rising motion near the tropical tropopause, which in turn has ramifications for vertical moisture transport and tropopause cirrus formation.

Estimating the Diffusion Coefficients of Sugars Using Diffusion Experiments in Agar-Gel and Computer Simulations.

PubMed

Miyamoto, Shuichi; Atsuyama, Kenji; Ekino, Keisuke; Shin, Takashi

2018-01-01

The isolation of useful microbes is one of the traditional approaches for the lead generation in drug discovery. As an effective technique for microbe isolation, we recently developed a multidimensional diffusion-based gradient culture system of microbes. In order to enhance the utility of the system, it is favorable to have diffusion coefficients of nutrients such as sugars in the culture medium beforehand. We have, therefore, built a simple and convenient experimental system that uses agar-gel to observe diffusion. Next, we performed computer simulations-based on random-walk concepts-of the experimental diffusion system and derived correlation formulas that relate observable diffusion data to diffusion coefficients. Finally, we applied these correlation formulas to our experimentally-determined diffusion data to estimate the diffusion coefficients of sugars. Our values for these coefficients agree reasonably well with values published in the literature. The effectiveness of our simple technique, which has elucidated the diffusion coefficients of some molecules which are rarely reported (e.g., galactose, trehalose, and glycerol) is demonstrated by the strong correspondence between the literature values and those obtained in our experiments.

Comparison of aerodynamic coefficients obtained from theoretical calculations wind tunnel tests and flight tests data reduction for the alpha jet aircraft

NASA Technical Reports Server (NTRS)

Guiot, R.; Wunnenberg, H.

1980-01-01

The methods by which aerodynamic coefficients are determined and discussed. These include: calculations, wind tunnel experiments and experiments in flight for various prototypes of the Alpha Jet. A comparison of obtained results shows good correlation between expectations and in-flight test results.

Observation of Correlated Azimuthal Anisotropy Fourier Harmonics in pp and p+Pb Collisions at the LHC.

PubMed

Sirunyan, A M; Tumasyan, A; Adam, W; Ambrogi, F; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Grossmann, J; Hrubec, J; Jeitler, M; König, A; Krammer, N; Krätschmer, I; Liko, D; Madlener, T; Mikulec, I; Pree, E; Rabady, D; Rad, N; Rohringer, H; Schieck, J; Schöfbeck, R; Spanring, M; Spitzbart, D; Waltenberger, W; Wittmann, J; Wulz, C-E; Zarucki, M; Chekhovsky, V; Mossolov, V; Suarez Gonzalez, J; De Wolf, E A; Di Croce, D; Janssen, X; Lauwers, J; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Abu Zeid, S; Blekman, F; D'Hondt, J; De Bruyn, I; De Clercq, J; Deroover, K; Flouris, G; Lontkovskyi, D; Lowette, S; Moortgat, S; Moreels, L; Python, Q; Skovpen, K; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Brun, H; Clerbaux, B; De Lentdecker, G; Delannoy, H; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Karapostoli, G; Lenzi, T; Luetic, J; Maerschalk, T; Marinov, A; Randle-Conde, A; Seva, T; Vander Velde, C; Vanlaer, P; Vannerom, D; Yonamine, R; Zenoni, F; Zhang, F; Cimmino, A; Cornelis, T; Dobur, D; Fagot, A; Gul, M; Khvastunov, I; Poyraz, D; Roskas, C; Salva, S; Tytgat, M; Verbeke, W; Zaganidis, N; Bakhshiansohi, H; Bondu, O; Brochet, S; Bruno, G; Caputo, C; Caudron, A; De Visscher, S; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Jafari, A; Komm, M; Krintiras, G; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Piotrzkowski, K; Quertenmont, L; Vidal Marono, M; Wertz, S; Beliy, N; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Melo De Almeida, M; Mora Herrera, C; Mundim, L; Nogima, H; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Torres Da Silva De Araujo, F; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Tomei, T R Fernandez Perez; Gregores, E M; Mercadante, P G; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Misheva, M; Rodozov, M; Shopova, M; Stoykova, S; Sultanov, G; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Fang, W; Gao, X; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Jiang, C H; Leggat, D; Liao, H; Liu, Z; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Yazgan, E; Zhang, H; Zhang, S; Zhao, J; Ban, Y; Chen, G; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; González Hernández, C F; Ruiz Alvarez, J D; Courbon, B; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Mesic, B; Starodumov, A; Susa, T; Ather, M W; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Finger, M; Finger, M; Carrera Jarrin, E; Assran, Y; Mahmoud, M A; Mahrous, A; Dewanjee, R K; Kadastik, M; Perrini, L; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Pekkanen, J; Voutilainen, M; Härkönen, J; Järvinen, T; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Tuominen, E; Tuominiemi, J; Tuovinen, E; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Faure, J L; Ferri, F; Ganjour, S; Ghosh, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Kucher, I; Locci, E; Machet, M; Malcles, J; Negro, G; Rander, J; Rosowsky, A; Sahin, M Ö; Titov, M; Abdulsalam, A; Amendola, C; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Charlot, C; Granier de Cassagnac, R; Jo, M; Lisniak, S; Lobanov, A; Martin Blanco, J; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Salerno, R; Sauvan, J B; Sirois, Y; Stahl Leiton, A G; Strebler, T; Yilmaz, Y; Zabi, A; Zghiche, A; Agram, J-L; Andrea, J; Bloch, D; Brom, J-M; Buttignol, M; Chabert, E C; Chanon, N; Collard, C; Conte, E; Coubez, X; Fontaine, J-C; Gelé, D; Goerlach, U; Jansová, M; Le Bihan, A-C; Tonon, N; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Finco, L; Gascon, S; Gouzevitch, M; Grenier, G; Ille, B; Lagarde, F; Laktineh, I B; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Popov, A; Sordini, V; Vander Donckt, M; Viret, S; Toriashvili, T; Tsamalaidze, Z; Autermann, C; Feld, L; Kiesel, M K; Klein, K; Lipinski, M; Preuten, M; Schomakers, C; Schulz, J; Verlage, T; Zhukov, V; Albert, A; Dietz-Laursonn, E; Duchardt, D; Endres, M; Erdmann, M; Erdweg, S; Esch, T; Fischer, R; Güth, A; Hamer, M; Hebbeker, T; Heidemann, C; Hoepfner, K; Knutzen, S; Merschmeyer, M; Meyer, A; Millet, P; Mukherjee, S; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Teyssier, D; Thüer, S; Flügge, G; Kargoll, B; Kress, T; Künsken, A; Lingemann, J; Müller, T; Nehrkorn, A; Nowack, A; Pistone, C; Pooth, O; Stahl, A; Aldaya Martin, M; Arndt, T; Asawatangtrakuldee, C; Beernaert, K; Behnke, O; Behrens, U; Bermúdez Martínez, A; Bin Anuar, A A; Borras, K; Botta, V; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Diez Pardos, C; Eckerlin, G; Eckstein, D; Eichhorn, T; Eren, E; Gallo, E; Garay Garcia, J; Geiser, A; Gizhko, A; Grados Luyando, J M; Grohsjean, A; Gunnellini, P; Guthoff, M; Harb, A; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Kasemann, M; Keaveney, J; Kleinwort, C; Korol, I; Krücker, D; Lange, W; Lelek, A; Lenz, T; Leonard, J; Lipka, K; Lohmann, W; Mankel, R; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Ntomari, E; Pitzl, D; Raspereza, A; Roland, B; Savitskyi, M; Saxena, P; Shevchenko, R; Spannagel, S; Stefaniuk, N; Van Onsem, G P; Walsh, R; Wen, Y; Wichmann, K; Wissing, C; Zenaiev, O; Bein, S; Blobel, V; Centis Vignali, M; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hinzmann, A; Hoffmann, M; Karavdina, A; Klanner, R; Kogler, R; Kovalchuk, N; Kurz, S; Lapsien, T; Marchesini, I; Marconi, D; Meyer, M; Niedziela, M; Nowatschin, D; Pantaleo, F; Peiffer, T; Perieanu, A; Scharf, C; Schleper, P; Schmidt, A; Schumann, S; Schwandt, J; Sonneveld, J; Stadie, H; Steinbrück, G; Stober, F M; Stöver, M; Tholen, H; Troendle, D; Usai, E; Vanelderen, L; Vanhoefer, A; Vormwald, B; Akbiyik, M; Barth, C; Baur, S; Butz, E; Caspart, R; Chwalek, T; Colombo, F; De Boer, W; Dierlamm, A; Freund, B; Friese, R; Giffels, M; Haitz, D; Hartmann, F; Heindl, S M; Husemann, U; Kassel, F; Kudella, S; Mildner, H; Mozer, M U; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; Schröder, M; Shvetsov, I; Sieber, G; Simonis, H J; Ulrich, R; Wayand, S; Weber, M; Weiler, T; Williamson, S; Wöhrmann, C; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Giakoumopoulou, V A; Kyriakis, A; Loukas, D; Topsis-Giotis, I; Karathanasis, G; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Kousouris, K; Evangelou, I; Foudas, C; Kokkas, P; Mallios, S; Manthos, N; Papadopoulos, I; Paradas, E; Strologas, J; Triantis, F A; Csanad, M; Filipovic, N; Pasztor, G; Veres, G I; Bencze, G; Hajdu, C; Horvath, D; Hunyadi, Á; Sikler, F; Veszpremi, V; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Makovec, A; Molnar, J; Szillasi, Z; Bartók, M; Raics, P; Trocsanyi, Z L; Ujvari, B; Choudhury, S; Komaragiri, J R; Bahinipati, S; Bhowmik, S; Mal, P; Mandal, K; Nayak, A; Sahoo, D K; Sahoo, N; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chawla, R; Dhingra, N; Kalsi, A K; Kaur, A; Kaur, M; Kumar, R; Kumari, P; Mehta, A; Singh, J B; Walia, G; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A; Chauhan, S; Choudhary, B C; Garg, R B; Keshri, S; Kumar, A; Malhotra, S; Naimuddin, M; Ranjan, K; Sharma, R; Bhardwaj, R; Bhattacharya, R; Bhattacharya, S; Bhawandeep, U; Dey, S; Dutt, S; Dutta, S; Ghosh, S; Majumdar, N; Modak, A; Mondal, K; Mukhopadhyay, S; Nandan, S; Purohit, A; Roy, A; Roy, D; Roy Chowdhury, S; Sarkar, S; Sharan, M; Thakur, S; Behera, P K; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Mohanty, A K; Netrakanti, P K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Dugad, S; Mahakud, B; Mitra, S; Mohanty, G B; Sur, N; Sutar, B; Banerjee, S; Bhattacharya, S; Chatterjee, S; Das, P; Guchait, M; Jain, Sa; Kumar, S; Maity, M; Majumder, G; Mazumdar, K; Sarkar, T; Wickramage, N; Chauhan, S; Dube, S; Hegde, V; Kapoor, A; Kothekar, K; Pandey, S; Rane, A; Sharma, S; Chenarani, S; Eskandari Tadavani, E; Etesami, S M; Khakzad, M; Mohammadi Najafabadi, M; Naseri, M; Paktinat Mehdiabadi, S; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Errico, F; Fiore, L; Iaselli, G; Lezki, S; Maggi, G; Maggi, M; Miniello, G; My, S; Nuzzo, S; Pompili, A; Pugliese, G; Radogna, R; Ranieri, A; Selvaggi, G; Sharma, A; Silvestris, L; Venditti, R; Verwilligen, P; Abbiendi, G; Battilana, C; Bonacorsi, D; Braibant-Giacomelli, S; Campanini, R; Capiluppi, P; Castro, A; Cavallo, F R; Chhibra, S S; Codispoti, G; Cuffiani, M; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Grandi, C; Guiducci, L; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Perrotta, A; Rossi, A M; Rovelli, T; Siroli, G P; Tosi, N; Albergo, S; Costa, S; Di Mattia, A; Giordano, F; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Chatterjee, K; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Lenzi, P; Meschini, M; Paoletti, S; Russo, L; Sguazzoni, G; Strom, D; Viliani, L; Benussi, L; Bianco, S; Fabbri, F; Piccolo, D; Primavera, F; Calvelli, V; Ferro, F; Robutti, E; Tosi, S; Benaglia, A; Brianza, L; Brivio, F; Ciriolo, V; Dinardo, M E; Fiorendi, S; Gennai, S; Ghezzi, A; Govoni, P; Malberti, M; Malvezzi, S; Manzoni, R A; Menasce, D; Moroni, L; Paganoni, M; Pauwels, K; Pedrini, D; Pigazzini, S; Ragazzi, S; Redaelli, N; Tabarelli de Fatis, T; Buontempo, S; Cavallo, N; Di Guida, S; Fabozzi, F; Fienga, F; Iorio, A O M; Khan, W A; Lista, L; Meola, S; Paolucci, P; Sciacca, C; Thyssen, F; Azzi, P; Bacchetta, N; Benato, L; Bisello, D; Boletti, A; Carlin, R; Carvalho Antunes De Oliveira, A; Checchia, P; De Castro Manzano, P; Dorigo, T; Dosselli, U; Gasparini, F; Gasparini, U; Gozzelino, A; Lacaprara, S; Margoni, M; Meneguzzo, A T; Pozzobon, N; Ronchese, P; Rossin, R; Simonetto, F; Torassa, E; Zanetti, M; Zotto, P; Zumerle, G; Braghieri, A; Magnani, A; Montagna, P; Ratti, S P; Re, V; Ressegotti, M; Riccardi, C; Salvini, P; Vai, I; Vitulo, P; Alunni Solestizi, L; Biasini, M; Bilei, G M; Cecchi, C; Ciangottini, D; Fanò, L; Lariccia, P; Leonardi, R; Manoni, E; Mantovani, G; Mariani, V; Menichelli, M; Rossi, A; Santocchia, A; Spiga, D; Androsov, K; Azzurri, P; Bagliesi, G; Boccali, T; Borrello, L; Castaldi, R; Ciocci, M A; Dell'Orso, R; Fedi, G; Giannini, L; Giassi, A; Grippo, M T; Ligabue, F; Lomtadze, T; Manca, E; Mandorli, G; Martini, L; Messineo, A; Palla, F; Rizzi, A; Savoy-Navarro, A; Spagnolo, P; Tenchini, R; Tonelli, G; Venturi, A; Verdini, P G; Barone, L; Cavallari, F; Cipriani, M; Del Re, D; Di Marco, E; Diemoz, M; Gelli, S; Longo, E; Margaroli, F; Marzocchi, B; Meridiani, P; Organtini, G; Paramatti, R; Preiato, F; Rahatlou, S; Rovelli, C; Santanastasio, F; Amapane, N; Arcidiacono, R; Argiro, S; Arneodo, M; Bartosik, N; Bellan, R; Biino, C; Cartiglia, N; Cenna, F; Costa, M; Covarelli, R; Degano, A; Demaria, N; Kiani, B; Mariotti, C; Maselli, S; Migliore, E; Monaco, V; Monteil, E; Monteno, M; Obertino, M M; Pacher, L; Pastrone, N; Pelliccioni, M; Pinna Angioni, G L; Ravera, F; Romero, A; Ruspa, M; Sacchi, R; Shchelina, K; Sola, V; Solano, A; Staiano, A; Traczyk, P; Belforte, S; Casarsa, M; Cossutti, F; Della Ricca, G; Zanetti, A; Kim, D H; Kim, G N; Kim, M S; Lee, J; Lee, S; Lee, S W; Moon, C S; Oh, Y D; Sekmen, S; Son, D C; Yang, Y C; Lee, A; Kim, H; Moon, D H; Oh, G; Brochero Cifuentes, J A; Goh, J; Kim, T J; Cho, S; Choi, S; Go, Y; Gyun, D; Ha, S; Hong, B; Jo, Y; Kim, Y; Lee, K; Lee, K S; Lee, S; Lim, J; Park, S K; Roh, Y; Almond, J; Kim, J; Kim, J S; Lee, H; Lee, K; Nam, K; Oh, S B; Radburn-Smith, B C; Seo, S H; Yang, U K; Yoo, H D; Yu, G B; Choi, M; Kim, H; Kim, J H; Lee, J S H; Park, I C; Choi, Y; Hwang, C; Lee, J; Yu, I; Dudenas, V; Juodagalvis, A; Vaitkus, J; Ahmed, I; Ibrahim, Z A; Md Ali, M A B; Mohamad Idris, F; Wan Abdullah, W A T; Yusli, M N; Zolkapli, Z; Reyes-Almanza, R; Ramirez-Sanchez, G; Duran-Osuna, M C; Castilla-Valdez, H; De La Cruz-Burelo, E; Heredia-De La Cruz, I; Rabadan-Trejo, R I; Lopez-Fernandez, R; Mejia Guisao, J; Sanchez-Hernandez, A; Carrillo Moreno, S; Oropeza Barrera, C; Vazquez Valencia, F; Pedraza, I; Salazar Ibarguen, H A; Uribe Estrada, C; Morelos Pineda, A; Krofcheck, D; Butler, P H; Ahmad, A; Ahmad, M; Hassan, Q; Hoorani, H R; Saddique, A; Shah, M A; Shoaib, M; Waqas, M; Bialkowska, H; Bluj, M; Boimska, B; Frueboes, T; Górski, M; Kazana, M; Nawrocki, K; Szleper, M; Zalewski, P; Bunkowski, K; Byszuk, A; Doroba, K; Kalinowski, A; Konecki, M; Krolikowski, J; Misiura, M; Olszewski, M; Pyskir, A; Walczak, M; Bargassa, P; Beirão Da Cruz E Silva, C; Di Francesco, A; Faccioli, P; Galinhas, B; Gallinaro, M; Hollar, J; Leonardo, N; Lloret Iglesias, L; Nemallapudi, M V; Seixas, J; Strong, G; Toldaiev, O; Vadruccio, D; Varela, J; Afanasiev, S; Bunin, P; Gavrilenko, M; Golutvin, I; Gorbunov, I; Kamenev, A; Karjavin, V; Lanev, A; Malakhov, A; Matveev, V; Palichik, V; Perelygin, V; Shmatov, S; Shulha, S; Skatchkov, N; Smirnov, V; Voytishin, N; Zarubin, A; Ivanov, Y; Kim, V; Kuznetsova, E; Levchenko, P; Murzin, V; Oreshkin, V; Smirnov, I; Sulimov, V; Uvarov, L; Vavilov, S; Vorobyev, A; Andreev, Yu; Dermenev, A; Gninenko, S; Golubev, N; Karneyeu, A; Kirsanov, M; Krasnikov, N; Pashenkov, A; Tlisov, D; Toropin, A; Epshteyn, V; Gavrilov, V; Lychkovskaya, N; Popov, V; Pozdnyakov, I; Safronov, G; Spiridonov, A; Stepennov, A; Toms, M; Vlasov, E; Zhokin, A; Aushev, T; Bylinkin, A; Chistov, R; Danilov, M; Parygin, P; Philippov, D; Polikarpov, S; Tarkovskii, E; Zhemchugov, E; Andreev, V; Azarkin, M; Dremin, I; Kirakosyan, M; Terkulov, A; Baskakov, A; Belyaev, A; Boos, E; Ershov, A; Gribushin, A; Kaminskiy, A; Kodolova, O; Korotkikh, V; Lokhtin, I; Miagkov, I; Obraztsov, S; Petrushanko, S; Savrin, V; Snigirev, A; Vardanyan, I; Blinov, V; Skovpen, Y; Shtol, D; Azhgirey, I; Bayshev, I; Bitioukov, S; Elumakhov, D; Kachanov, V; Kalinin, A; Konstantinov, D; Petrov, V; Ryutin, R; Sobol, A; Troshin, S; Tyurin, N; Uzunian, A; Volkov, A; Adzic, P; Cirkovic, P; Devetak, D; Dordevic, M; Milosevic, J; Rekovic, V; Stojanovic, M; Alcaraz Maestre, J; Barrio Luna, M; Cerrada, M; Colino, N; De La Cruz, B; Delgado Peris, A; Escalante Del Valle, A; Fernandez Bedoya, C; Fernández Ramos, J P; Flix, J; Fouz, M C; Garcia-Abia, P; Gonzalez Lopez, O; Goy Lopez, S; Hernandez, J M; Josa, M I; Moran, D; Pérez-Calero Yzquierdo, A; Puerta Pelayo, J; Quintario Olmeda, A; Redondo, I; Romero, L; Soares, M S; Álvarez Fernández, A; Albajar, C; de Trocóniz, J F; Missiroli, M; Cuevas, J; Erice, C; Fernandez Menendez, J; Gonzalez Caballero, I; González Fernández, J R; Palencia Cortezon, E; Sanchez Cruz, S; Vischia, P; Vizan Garcia, J M; Cabrillo, I J; Calderon, A; Chazin Quero, B; Curras, E; Duarte Campderros, J; Fernandez, M; Garcia-Ferrero, J; Gomez, G; Lopez Virto, A; Marco, J; Martinez Rivero, C; Martinez Ruiz Del Arbol, P; Matorras, F; Piedra Gomez, J; Rodrigo, T; Ruiz-Jimeno, A; Scodellaro, L; Trevisani, N; Vila, I; Vilar Cortabitarte, R; Abbaneo, D; Auffray, E; Baillon, P; Ball, A H; Barney, D; Bianco, M; Bloch, P; Bocci, A; Botta, C; Camporesi, T; Castello, R; Cepeda, M; Cerminara, G; Chapon, E; Chen, Y; d'Enterria, D; Dabrowski, A; Daponte, V; David, A; De Gruttola, M; De Roeck, A; Dobson, M; Dorney, B; du Pree, T; Dünser, M; Dupont, N; Elliott-Peisert, A; Everaerts, P; Fallavollita, F; Franzoni, G; Fulcher, J; Funk, W; Gigi, D; Gilbert, A; Gill, K; Glege, F; Gulhan, D; Harris, P; Hegeman, J; Innocente, V; Janot, P; Karacheban, O; Kieseler, J; Kirschenmann, H; Knünz, V; Kornmayer, A; Kortelainen, M J; Lange, C; Lecoq, P; Lourenço, C; Lucchini, M T; Malgeri, L; Mannelli, M; Martelli, A; Meijers, F; Merlin, J A; Mersi, S; Meschi, E; Milenovic, P; Moortgat, F; Mulders, M; Neugebauer, H; Ngadiuba, J; Orfanelli, S; Orsini, L; Pape, L; Perez, E; Peruzzi, M; Petrilli, A; Petrucciani, G; Pfeiffer, A; Pierini, M; Racz, A; Reis, T; Rolandi, G; Rovere, M; Sakulin, H; Schäfer, C; Schwick, C; Seidel, M; Selvaggi, M; Sharma, A; Silva, P; Sphicas, P; Stakia, A; Steggemann, J; Stoye, M; Tosi, M; Treille, D; Triossi, A; Tsirou, A; Veckalns, V; Verweij, M; Zeuner, W D; Bertl, W; Caminada, L; Deiters, K; Erdmann, W; Horisberger, R; Ingram, Q; Kaestli, H C; Kotlinski, D; Langenegger, U; Rohe, T; Wiederkehr, S A; Bäni, L; Berger, P; Bianchini, L; Casal, B; Dissertori, G; Dittmar, M; Donegà, M; Grab, C; Heidegger, C; Hits, D; Hoss, J; Kasieczka, G; Klijnsma, T; Lustermann, W; Mangano, B; Marionneau, M; Meinhard, M T; Meister, D; Micheli, F; Musella, P; Nessi-Tedaldi, F; Pandolfi, F; Pata, J; Pauss, F; Perrin, G; Perrozzi, L; Quittnat, M; Reichmann, M; Schönenberger, M; Shchutska, L; Tavolaro, V R; Theofilatos, K; Vesterbacka Olsson, M L; Wallny, R; Zhu, D H; Aarrestad, T K; Amsler, C; Canelli, M F; De Cosa, A; Del Burgo, R; Donato, S; Galloni, C; Hreus, T; Kilminster, B; Pinna, D; Rauco, G; Robmann, P; Salerno, D; Seitz, C; Takahashi, Y; Zucchetta, A; Candelise, V; Doan, T H; Jain, Sh; Khurana, R; Kuo, C M; Lin, W; Pozdnyakov, A; Yu, S S; Kumar, Arun; Chang, P; Chao, Y; Chen, K F; Chen, P H; Fiori, F; Hou, W-S; Hsiung, Y; Liu, Y F; Lu, R-S; Paganis, E; Psallidas, A; Steen, A; Tsai, J F; Asavapibhop, B; Kovitanggoon, K; Singh, G; Srimanobhas, N; Boran, F; Cerci, S; Damarseckin, S; Demiroglu, Z S; Dozen, C; Dumanoglu, I; Girgis, S; Gokbulut, G; Guler, Y; Hos, I; Kangal, E E; Kara, O; Kayis Topaksu, A; Kiminsu, U; Oglakci, M; Onengut, G; Ozdemir, K; Sunar Cerci, D; Tali, B; Turkcapar, S; Zorbakir, I S; Zorbilmez, C; Bilin, B; Karapinar, G; Ocalan, K; Yalvac, M; Zeyrek, M; Gülmez, E; Kaya, M; Kaya, O; Tekten, S; Yetkin, E A; Agaras, M N; Atay, S; Cakir, A; Cankocak, K; Grynyov, B; Levchuk, L; Aggleton, R; Ball, F; Beck, L; Brooke, J J; Burns, D; Clement, E; Cussans, D; Davignon, O; Flacher, H; Goldstein, J; Grimes, M; Heath, G P; Heath, H F; Jacob, J; Kreczko, L; Lucas, C; Newbold, D M; Paramesvaran, S; Poll, A; Sakuma, T; Seif El Nasr-Storey, S; Smith, D; Smith, V J; Belyaev, A; Brew, C; Brown, R M; Calligaris, L; Cieri, D; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Olaiya, E; Petyt, D; Shepherd-Themistocleous, C H; Thea, A; Tomalin, I R; Williams, T; Auzinger, G; Bainbridge, R; Breeze, S; Buchmuller, O; Bundock, A; Casasso, S; Citron, M; Colling, D; Corpe, L; Dauncey, P; Davies, G; De Wit, A; Della Negra, M; Di Maria, R; Elwood, A; Haddad, Y; Hall, G; Iles, G; James, T; Lane, R; Laner, C; Lyons, L; Magnan, A-M; Malik, S; Mastrolorenzo, L; Matsushita, T; Nash, J; Nikitenko, A; Palladino, V; Pesaresi, M; Raymond, D M; Richards, A; Rose, A; Scott, E; Seez, C; Shtipliyski, A; Summers, S; Tapper, A; Uchida, K; Vazquez Acosta, M; Virdee, T; Wardle, N; Winterbottom, D; Wright, J; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Reid, I D; Symonds, P; Teodorescu, L; Turner, M; Borzou, A; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Pastika, N; Smith, C; Bartek, R; Dominguez, A; Buccilli, A; Cooper, S I; Henderson, C; Rumerio, P; West, C; Arcaro, D; Avetisyan, A; Bose, T; Gastler, D; Rankin, D; Richardson, C; Rohlf, J; Sulak, L; Zou, D; Benelli, G; Cutts, D; Garabedian, A; Hakala, J; Heintz, U; Hogan, J M; Kwok, K H M; Laird, E; Landsberg, G; Mao, Z; Narain, M; Piperov, S; Sagir, S; Syarif, R; Yu, D; Band, R; Brainerd, C; Burns, D; Calderon De La Barca Sanchez, M; Chertok, M; Conway, J; Conway, R; Cox, P T; Erbacher, R; Flores, C; Funk, G; Gardner, M; Ko, W; Lander, R; Mclean, C; Mulhearn, M; Pellett, D; Pilot, J; Shalhout, S; Shi, M; Smith, J; Stolp, D; Tos, K; Tripathi, M; Wang, Z; Bachtis, M; Bravo, C; Cousins, R; Dasgupta, A; Florent, A; Hauser, J; Ignatenko, M; Mccoll, N; Regnard, S; Saltzberg, D; Schnaible, C; Valuev, V; Bouvier, E; Burt, K; Clare, R; Ellison, J; Gary, J W; Ghiasi Shirazi, S M A; Hanson, G; Heilman, J; Jandir, P; Kennedy, E; Lacroix, F; Long, O R; Olmedo Negrete, M; Paneva, M I; Shrinivas, A; Si, W; Wang, L; Wei, H; Wimpenny, S; Yates, B R; Branson, J G; Cittolin, S; Derdzinski, M; Hashemi, B; Holzner, A; Klein, D; Kole, G; Krutelyov, V; Letts, J; Macneill, I; Masciovecchio, M; Olivito, D; Padhi, S; Pieri, M; Sani, M; Sharma, V; Simon, S; Tadel, M; Vartak, A; Wasserbaech, S; Wood, J; Würthwein, F; Yagil, A; Zevi Della Porta, G; Amin, N; Bhandari, R; Bradmiller-Feld, J; Campagnari, C; Dishaw, A; Dutta, V; Franco Sevilla, M; George, C; Golf, F; Gouskos, L; Gran, J; Heller, R; Incandela, J; Mullin, S D; Ovcharova, A; Qu, H; Richman, J; Stuart, D; Suarez, I; Yoo, J; Anderson, D; Bendavid, J; Bornheim, A; Lawhorn, J M; Newman, H B; Nguyen, T; Pena, C; Spiropulu, M; Vlimant, J R; Xie, S; Zhang, Z; Zhu, R Y; Andrews, M B; Ferguson, T; Mudholkar, T; Paulini, M; Russ, J; Sun, M; Vogel, H; Vorobiev, I; Weinberg, M; Cumalat, J P; Ford, W T; Jensen, F; Johnson, A; Krohn, M; Leontsinis, S; Mulholland, T; Stenson, K; Wagner, S R; Alexander, J; Chaves, J; Chu, J; Dittmer, S; Mcdermott, K; Mirman, N; Patterson, J R; Rinkevicius, A; Ryd, A; Skinnari, L; Soffi, L; Tan, S M; Tao, Z; Thom, J; Tucker, J; Wittich, P; Zientek, M; Abdullin, S; Albrow, M; Apollinari, G; Apresyan, A; Apyan, A; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bolla, G; Burkett, K; Butler, J N; Canepa, A; Cerati, G B; Cheung, H W K; Chlebana, F; Cremonesi, M; Duarte, J; Elvira, V D; Freeman, J; Gecse, Z; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Klima, B; Kreis, B; Lammel, S; Lincoln, D; Lipton, R; Liu, M; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Magini, N; Marraffino, J M; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mrenna, S; Nahn, S; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Ristori, L; Schneider, B; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Stoynev, S; Strait, J; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Wang, M; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Brinkerhoff, A; Carnes, A; Carver, M; Curry, D; Field, R D; Furic, I K; Konigsberg, J; Korytov, A; Kotov, K; Ma, P; Matchev, K; Mei, H; Mitselmakher, G; Rank, D; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Joshi, Y R; Linn, S; Markowitz, P; Rodriguez, J L; Ackert, A; Adams, T; Askew, A; Hagopian, S; Hagopian, V; Johnson, K F; Kolberg, T; Martinez, G; Perry, T; Prosper, H; Saha, A; Santra, A; Sharma, V; Yohay, R; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Cavanaugh, R; Chen, X; Evdokimov, O; Gerber, C E; Hangal, D A; Hofman, D J; Jung, K; Kamin, J; Sandoval Gonzalez, I D; Tonjes, M B; Trauger, H; Varelas, N; Wang, H; Wu, Z; Zhang, J; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Blumenfeld, B; Cocoros, A; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Roskes, J; Sarica, U; Swartz, M; Xiao, M; You, C; Al-Bataineh, A; Baringer, P; Bean, A; Boren, S; Bowen, J; Castle, J; Khalil, S; Kropivnitskaya, A; Majumder, D; Mcbrayer, W; Murray, M; Royon, C; Sanders, S; Schmitz, E; Tapia Takaki, J D; Wang, Q; Ivanov, A; Kaadze, K; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Hadley, N J; Jabeen, S; Jeng, G Y; Kellogg, R G; Kunkle, J; Mignerey, A C; Ricci-Tam, F; Shin, Y H; Skuja, A; Tonwar, S C; Abercrombie, D; Allen, B; Azzolini, V; Barbieri, R; Baty, A; Bi, R; Brandt, S; Busza, W; Cali, I A; D'Alfonso, M; Demiragli, Z; Gomez Ceballos, G; Goncharov, M; Hsu, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Maier, B; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Tatar, K; Velicanu, D; Wang, J; Wang, T W; Wyslouch, B; Benvenuti, A C; Chatterjee, R M; Evans, A; Hansen, P; Kalafut, S; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bloom, K; Claes, D R; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Kravchenko, I; Monroy, J; Siado, J E; Snow, G R; Stieger, B; Alyari, M; Dolen, J; Godshalk, A; Harrington, C; Iashvili, I; Nguyen, D; Parker, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; Teixeira De Lima, R; Trocino, D; Wood, D; Bhattacharya, S; Charaf, O; Hahn, K A; Mucia, N; Odell, N; Pollack, B; Schmitt, M H; Sung, K; Trovato, M; Velasco, M; Dev, N; Hildreth, M; Hurtado Anampa, K; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Loukas, N; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Smith, G; Taroni, S; Wayne, M; Wolf, M; Woodard, A; Alimena, J; Antonelli, L; Bylsma, B; Durkin, L S; Flowers, S; Francis, B; Hart, A; Hill, C; Ji, W; Liu, B; Luo, W; Puigh, D; Winer, B L; Wulsin, H W; Cooperstein, S; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Higginbotham, S; Lange, D; Luo, J; Marlow, D; Mei, K; Ojalvo, I; Olsen, J; Palmer, C; Piroué, P; Stickland, D; Tully, C; Malik, S; Norberg, S; Barker, A; Barnes, V E; Das, S; Folgueras, S; Gutay, L; Jha, M K; Jones, M; Jung, A W; Khatiwada, A; Miller, D H; Neumeister, N; Peng, C C; Schulte, J F; Sun, J; Wang, F; Xie, W; Cheng, T; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Bodek, A; de Barbaro, P; Demina, R; Duh, Y T; Ferbel, T; Galanti, M; Garcia-Bellido, A; Han, J; Hindrichs, O; Khukhunaishvili, A; Lo, K H; Tan, P; Verzetti, M; Ciesielski, R; Goulianos, K; Mesropian, C; Agapitos, A; Chou, J P; Gershtein, Y; Gómez Espinosa, T A; Halkiadakis, E; Heindl, M; Hughes, E; Kaplan, S; Kunnawalkam Elayavalli, R; Kyriacou, S; Lath, A; Montalvo, R; Nash, K; Osherson, M; Saka, H; Salur, S; Schnetzer, S; Sheffield, D; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Delannoy, A G; Foerster, M; Heideman, J; Riley, G; Rose, K; Spanier, S; Thapa, K; Bouhali, O; Castaneda Hernandez, A; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Kamon, T; Mueller, R; Pakhotin, Y; Patel, R; Perloff, A; Perniè, L; Rathjens, D; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Damgov, J; De Guio, F; Dudero, P R; Faulkner, J; Gurpinar, E; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Peltola, T; Undleeb, S; Volobouev, I; Wang, Z; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Melo, A; Ni, H; Padeken, K; Sheldon, P; Tuo, S; Velkovska, J; Xu, Q; Barria, P; Cox, B; Hirosky, R; Joyce, M; Ledovskoy, A; Li, H; Neu, C; Sinthuprasith, T; Wang, Y; Wolfe, E; Xia, F; Harr, R; Karchin, P E; Sturdy, J; Zaleski, S; Brodski, M; Buchanan, J; Caillol, C; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Hussain, U; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Pierro, G A; Polese, G; Ruggles, T; Savin, A; Smith, N; Smith, W H; Taylor, D; Woods, N

2018-03-02

The azimuthal anisotropy Fourier coefficients (v_{n}) in 8.16 TeV p+Pb data are extracted via long-range two-particle correlations as a function of the event multiplicity and compared to corresponding results in pp and PbPb collisions. Using a four-particle cumulant technique, v_{n} correlations are measured for the first time in pp and p+Pb collisions. The v_{2} and v_{4} coefficients are found to be positively correlated in all collision systems. For high-multiplicity p+Pb collisions, an anticorrelation of v_{2} and v_{3} is observed, with a similar correlation strength as in PbPb data at the same multiplicity. The new correlation results strengthen the case for a common origin of the collectivity seen in p+Pb and PbPb collisions in the measured multiplicity range.

Electromechanical imitator of antilock braking modes of wheels with pneumatic tire and its application for the runways friction coefficient measurement

NASA Astrophysics Data System (ADS)

Putov, A. V.; Kopichev, M. M.; Ignatiev, K. V.; Putov, V. V.; Stotckaia, A. D.

2017-01-01

In this paper it is considered a discussion of the technique that realizes a brand new method of runway friction coefficient measurement based upon the proposed principle of measuring wheel braking control for the imitation of antilock braking modes that are close to the real braking modes of the aircraft chassis while landing that are realized by the aircraft anti-skid systems. Also here is the description of the model of towed measuring device that realizes a new technique of runway friction coefficient measuring, based upon the measuring wheel braking control principle. For increasing the repeatability accuracy of electromechanical braking imitation system the sideslip (brake) adaptive control system is proposed. Based upon the Burkhard model and additive random processes several mathematical models were created that describes the friction coefficient arrangement along the airstrip with different qualitative adjectives. Computer models of friction coefficient measuring were designed and first in the world the research of correlation between the friction coefficient measuring results and shape variations, intensity and cycle frequency of the measuring wheel antilock braking modes. The sketch engineering documentation was designed and prototype of the latest generation measuring device is ready to use. The measuring device was tested on the autonomous electromechanical examination laboratory treadmill bench. The experiments approved effectiveness of method of imitation the antilock braking modes for solving the problem of correlation of the runway friction coefficient measuring.

Ecology of Floristic Quality Assessment: testing for correlations between coefficients of conservatism, species traits and mycorrhizal responsiveness

PubMed Central

Koziol, Liz; Bever, James D

2018-01-01

Abstract Many plant species are limited to habitats relatively unaffected by anthropogenic disturbance, so protecting these undisturbed habitats is essential for plant conservation. Coefficients of conservatism (C values) were developed as indicators of a species’ sensitivity to anthropogenic disturbance, and these values are used in Floristic Quality Assessment as a means of assessing natural areas and ecological restoration. However, assigning of these values is subjective and improved quantitative validation of C values is needed. We tested whether there are consistent differences in life histories between species with high and low C values. To do this, we grew 54 species of tallgrass prairie plants in a greenhouse and measured traits that are associated with trade-offs on the fast-slow continuum of life-history strategies. We also grew plants with and without mycorrhizal fungi as a test of these species’ reliance on this mutualism. We compared these traits and mycorrhizal responsiveness to C values. We found that six of the nine traits we measured were correlated with C values, and together, traits predicted up to 50 % of the variation in C values. Traits including fast growth rates and greater investment in reproduction were associated with lower C values, and slow growth rates, long-lived leaves and high root:shoot ratios were associated with higher C values. Additionally, plants with high C values and a slow life history were more responsive to mutualisms with mycorrhizal fungi. Overall, our results connect C values with life-history trade-offs, indicating that high C value species tend to share a suite of traits associated with a slow life history. PMID:29383232

Correlations Among Ice Measurements, Impingement Rates Icing Conditions, and Drag Coefficients for Unswept NACA 65A004 Airfoil

NASA Technical Reports Server (NTRS)

Gray, Vernon H.

1958-01-01

An empirical relation has been obtained by which the change in drag coefficient caused by ice formations on an unswept NACA 65AO04 airfoil section can be determined from the following icing and operating conditions: icing time, airspeed, air total temperature, liquid-water content, cloud droplet impingement efficiencies, airfoil chord length, and angles of attack. The correlation was obtained by use of measured ice heights and ice angles. These measurements were obtained from a variety of ice formations, which were carefully photographed, cross-sectioned, and weighed. Ice weights increased at a constant rate with icing time in a rime icing condition and at progressively increasing rates in glaze icing conditions. Initial rates of ice collection agreed reasonably well with values predicted from droplet impingement data. Experimental droplet impingement rates obtained on this airfoil section agreed with previous theoretical calculations for angles of attack of 40 or less. Disagreement at higher angles of attack was attributed to flow separation from the upper surface of the experimental airfoil model.

Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China.

PubMed

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

Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China

PubMed Central

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

P-Wave to Rayleigh-wave conversion coefficients for wedge corners; model experiments

USGS Publications Warehouse

Gangi, A.F.; Wesson, R.L.

1978-01-01

An analytic solution is not available for the diffraction of elastic waves by wedges; however, numerical solutions of finite-difference type are available for selected wedge angles. The P- to Rayleigh-wave conversion coefficients at wedge tips have been measured on two-dimensional seismic models for stress-free wedges with wedge angles, ??0, of 10, 30, 60, 90 and 120??. The conversion coefficients show two broad peaks and a minimum as a function of the angle between the wedge face and the direction of the incident P-wave. The minimum occurs for the P wave incident parallel to the wedge face and one maximum is near an incidence angle of 90?? to the wedge face. The amplitude of this maximum, relative to the other, decreases as the wedge angle increases. The asymmetry of the conversion coefficients, CPR(??; ??0), relative to parallel incidence (?? = 0) increases as the wedge angle increases. The locations of the maxima and the minimum as well as the asymmetry can be explained qualitatively. The conversion coefficients are measured with an accuracy of ??5% in those regions where there are no interfering waves. A comparison of the data for the 10?? wedge with the theoretical results for a half plane (0?? wedge) shows good correlation. ?? 1978.

Comparison of rotational temperature derived from ground-based OH airglow observations with TIMED/SABER to evaluate the Einstein Coefficients

NASA Astrophysics Data System (ADS)

Liu, W.; Xu, J.; Smith, A. K.; Yuan, W.

2017-12-01

Ground-based observations of the OH(9-4, 8-3, 6-2, 5-1, 3-0) band airglows over Xinglong, China (40°24'N, 117°35'E) from December 2011 to 2014 are used to calculate rotational temperatures. The temperatures are calculated using five commonly used Einstein coefficient datasets. The kinetic temperature from TIMED/SABER is completely independent of the OH rotational temperature. SABER temperatures are weighted vertically by weighting functions calculated for each emitting vibrational state from two SABER OH volume emission rate profiles. By comparing the ground-based OH rotational temperature with SABER's, five Einstein coefficient datasets are evaluated. The results show that temporal variations of the rotational temperatures are well correlated with SABER's; the linear correlation coefficients are higher than 0.72, but the slopes of the fit between the SABER and rotational temperatures are not equal to 1. The rotational temperatures calculated using each set of Einstein coefficients produce a different bias with respect to SABER; these are evaluated over each of vibrational levels to assess the best match. It is concluded that rotational temperatures determined using any of the available Einstein coefficient datasets have systematic errors. However, of the five sets of coefficients, the rotational temperature derived with the Langhoff et al.'s (1986) set is most consistent with SABER. In order to get a set of optimal Einstein coefficients for rotational temperature derivation, we derive the relative values from ground-based OH spectra and SABER temperatures statistically using three year data. The use of a standard set of Einstein coefficients will be beneficial for comparing rotational temperatures observed at different sites.

Correlation analysis of respiratory signals by using parallel coordinate plots.

PubMed

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence in Canonical Correlation Analysis.

ERIC Educational Resources Information Center

Romanazzi, Mario

1992-01-01

The perturbation theory of the generalized eigenproblem is used to derive influence functions of each squared canonical correlation coefficient and the corresponding canonical vector pair. Three sample versions of these functions are described, and some properties are noted. Two obvious applications, multiple correlation and correspondence…

Counterion adsorption theory of dilute polyelectrolyte solutions: Apparent molecular weight, second virial coefficient, and intermolecular structure factor

PubMed Central

Muthukumar, M.

2012-01-01

Polyelectrolyte chains are well known to be strongly correlated even in extremely dilute solutions in the absence of additional strong electrolytes. Such correlations result in severe difficulties in interpreting light scattering measurements in the determination of the molecular weight, radius of gyration, and the second virial coefficient of charged macromolecules at lower ionic strengths from added strong electrolytes. By accounting for charge-regularization of the polyelectrolyte by the counterions, we present a theory of the apparent molecular weight, second virial coefficient, and the intermolecular structure factor in dilute polyelectrolyte solutions in terms of concentrations of the polymer and the added strong electrolyte. The counterion adsorption of the polyelectrolyte chains to differing levels at different concentrations of the strong electrolyte can lead to even an order of magnitude discrepancy in the molecular weight inferred from light scattering measurements. Based on counterion-mediated charge regularization, the second virial coefficient of the polyelectrolyte and the interchain structure factor are derived self-consistently. The effect of the interchain correlations, dominating at lower salt concentrations, on the inference of the radius of gyration and on molecular weight is derived. Conditions for the onset of nonmonotonic scattering wave vector dependence of scattered intensity upon lowering the electrolyte concentration and interpretation of the apparent radius of gyration are derived in terms of the counterion adsorption mechanism. PMID:22830728

Coarse-grained hydrodynamics from correlation functions

NASA Astrophysics Data System (ADS)

Palmer, Bruce

2018-02-01

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models.

PubMed

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models

NASA Astrophysics Data System (ADS)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Thermodiffusion, molecular diffusion and Soret coefficient of binary and ternary mixtures of n-hexane, n-dodecane and toluene.

PubMed

Alonso de Mezquia, David; Wang, Zilin; Lapeira, Estela; Klein, Michael; Wiegand, Simone; Mounir Bou-Ali, M

2014-11-01

In this study, the thermodiffusion, molecular diffusion, and Soret coefficients of 12 binary mixtures composed of toluene, n-hexane and n-dodecane in the whole range of concentrations at atmospheric pressure and temperatures of 298.15 K and 308.15 K have been determined. The experimental measurements have been carried out using the Thermogravitational Column, the Sliding Symmetric Tubes and the Thermal Diffusion Forced Rayleigh Scattering techniques. The results obtained using the different techniques show a maximum deviation of 9% for the thermodiffusion coefficient, 8% for the molecular diffusion coefficient and 2% for the Soret coefficient. For the first time we report a decrease of the thermodiffusion coefficient with increasing ratio of the thermal expansion coefficient and viscosity for a binary mixture of an organic ring compound with a short n-alkane. This observation is discussed in terms of interactions between the different components. Additionally, the thermogravitational technique has been used to measure the thermodiffusion coefficients of four ternary mixtures consisting of toluene, n-hexane and n-dodecane at 298.15 K. In order to complete the study, the values obtained for the molecular diffusion coefficient in binary mixtures, and the thermodiffusion coefficient of binary and ternary mixtures have been compared with recently derived correlations.

Decreased apparent diffusion coefficient in the pituitary and correlation with hypopituitarism in patients with traumatic brain injury.

PubMed

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 < 0.01). Furthermore, the mean ADC was much lower in TBI patients with hypopituitarism than in those without pituitary dysfunction (1.32 ± 0.09 vs 2.28 ± 0.17, p < 0.05). There was also a significant difference in ADC values between patients with hyperprolactinemia and those with normal prolactin levels (p < 0.05). Additionally, the receiver operating characteristic curve analysis showed that the pituitary ADC could predict hypopituitarism with a sensitivity of 90.0% and a specificity of 90.1% at the level of 1.720 (ADC value). Finally, the ADC value was positively correlated with neurological outcome at 6 months following TBI (r = 0.602, p < 0.05). Use

Mutual diffusion coefficients of heptane isomers in nitrogen: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Chae, Kyungchan; Violi, Angela

2011-01-01

The accurate knowledge of transport properties of pure and mixture fluids is essential for the design of various chemical and mechanical systems that include fluxes of mass, momentum, and energy. In this study we determine the mutual diffusion coefficients of mixtures composed of heptane isomers and nitrogen using molecular dynamics (MD) simulations with fully atomistic intermolecular potential parameters, in conjunction with the Green-Kubo formula. The computed results were compared with the values obtained using the Chapman-Enskog (C-E) equation with Lennard-Jones (LJ) potential parameters derived from the correlations of state values: MD simulations predict a maximum difference of 6% among isomers while the C-E equation presents that of 3% in the mutual diffusion coefficients in the temperature range 500-1000 K. The comparison of two approaches implies that the corresponding state principle can be applied to the models, which are only weakly affected by the anisotropy of the interaction potentials and the large uncertainty will be included in its application for complex polyatomic molecules. The MD simulations successfully address the pure effects of molecular structure among isomers on mutual diffusion coefficients by revealing that the differences of the total mutual diffusion coefficients for the six mixtures are caused mainly by heptane isomers. The cross interaction potential parameters, collision diameter σ _{12}, and potential energy well depth \\varepsilon _{12} of heptane isomers and nitrogen mixtures were also computed from the mutual diffusion coefficients.

Dynamical behavior of the correlation between meteorological factors

NASA Astrophysics Data System (ADS)

You, Cheol-Hwan; Chang, Ki-Ho; Lee, Jun-Ho; Kim, Kyungsik

2017-12-01

We study the temporal and spatial variation characteristics of meteorological factors (temperature, humidity, and wind velocity) at a meteorological tower located on Bosung-gun of South Korea. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation from data of meteorological factors. The relationships between meteorological factors are identified and quantified by using DCCA coefficients. From our results, we ascertain that the DCCA coefficient between temperature and humidity at time lag m = 24 has the smallest value at the height of 10 m of the measuring tower. Particularly, the DCCA coefficient between temperature and wind speed at time lag m = 24 has the largest value at a height of 10 m of the measuring tower

Observation of Correlated Azimuthal Anisotropy Fourier Harmonics in p p and p + Pb Collisions at the LHC

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2018-02-26

Here, the azimuthal anisotropy Fourier coefficients (v n) in 8.16 TeV p+Pb data are extracted via long-range two-particle correlations as a function of the event multiplicity and compared to corresponding results in pp and PbPb collisions. Using a four-particle cumulant technique, v n correlations are measured for the first time in pp and p+Pb collisions. The v 2 and v 4 coefficients are found to be positively correlated in all collision systems. For high-multiplicity p+Pb collisions, an anticorrelation of v 2 and v 3 is observed, with a similar correlation strength as in PbPb data at the same multiplicity. The newmore » correlation results strengthen the case for a common origin of the collectivity seen in p+Pb and PbPb collisions in the measured multiplicity range.« less