Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Two-dimensional correlation spectroscopy — Biannual survey 2007-2009

NASA Astrophysics Data System (ADS)

Noda, Isao

2010-06-01

The publication activities in the field of 2D correlation spectroscopy are surveyed with the emphasis on papers published during the last two years. Pertinent review articles and conference proceedings are discussed first, followed by the examination of noteworthy developments in the theory and applications of 2D correlation spectroscopy. Specific topics of interest include Pareto scaling, analysis of randomly sampled spectra, 2D analysis of data obtained under multiple perturbations, evolution of 2D spectra along additional variables, comparison and quantitative analysis of multiple 2D spectra, orthogonal sample design to eliminate interfering cross peaks, quadrature orthogonal signal correction and other data transformation techniques, data pretreatment methods, moving window analysis, extension of kernel and global phase angle analysis, covariance and correlation coefficient mapping, variant forms of sample-sample correlation, and different display methods. Various static and dynamic perturbation methods used in 2D correlation spectroscopy, e.g., temperature, composition, chemical reactions, H/D exchange, physical phenomena like sorption, diffusion and phase transitions, optical and biological processes, are reviewed. Analytical probes used in 2D correlation spectroscopy include IR, Raman, NIR, NMR, X-ray, mass spectrometry, chromatography, and others. Application areas of 2D correlation spectroscopy are diverse, encompassing synthetic and natural polymers, liquid crystals, proteins and peptides, biomaterials, pharmaceuticals, food and agricultural products, solutions, colloids, surfaces, and the like.

The cross-correlation analysis of multi property of stock markets based on MM-DFA

NASA Astrophysics Data System (ADS)

Yang, Yujun; Li, Jianping; Yang, Yimei

2017-09-01

In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

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

Sun, Yannan; Hou, Zhangshuan; Meng, Da

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

Sensitivity Analysis of Multiple Informant Models When Data are Not Missing at Random

PubMed Central

Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae; Scaramella, Laura; Leve, Leslie; Reiss, David

2014-01-01

Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups may be retained even if only one member of a group contributes data. Statistical inference is based on the assumption that data are missing completely at random or missing at random. Importantly, whether or not data are missing is assumed to be independent of the missing data. A saturated correlates model that incorporates correlates of the missingness or the missing data into an analysis and multiple imputation that may also use such correlates offer advantages over the standard implementation of SEM when data are not missing at random because these approaches may result in a data analysis problem for which the missingness is ignorable. This paper considers these approaches in an analysis of family data to assess the sensitivity of parameter estimates to assumptions about missing data, a strategy that may be easily implemented using SEM software. PMID:25221420

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Methods for the Joint Meta-Analysis of Multiple Tests

ERIC Educational Resources Information Center

Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H.

2014-01-01

Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Atmospheric turbulence profiling with SLODAR using multiple adaptive optics wavefront sensors.

PubMed

Wang, Lianqi; Schöck, Matthias; Chanan, Gary

2008-04-10

The slope detection and ranging (SLODAR) method recovers atmospheric turbulence profiles from time averaged spatial cross correlations of wavefront slopes measured by Shack-Hartmann wavefront sensors. The Palomar multiple guide star unit (MGSU) was set up to test tomographic multiple guide star adaptive optics and provided an ideal test bed for SLODAR turbulence altitude profiling. We present the data reduction methods and SLODAR results from MGSU observations made in 2006. Wind profiling is also performed using delayed wavefront cross correlations along with SLODAR analysis. The wind profiling analysis is shown to improve the height resolution of the SLODAR method and in addition gives the wind velocities of the turbulent layers.

Correlates of Successful Aging: Are They Universal?

ERIC Educational Resources Information Center

Litwin, Howard

2005-01-01

The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

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…

Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

PubMed

Dlugonski, Deirdre; Motl, Robert W

2012-02-01

Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

Higher Education Value Added Using Multiple Outcomes

ERIC Educational Resources Information Center

Milla, Joniada; Martín, Ernesto San; Van Bellegem, Sébastien

2016-01-01

In this article we develop a methodology for the joint value added analysis of multiple outcomes that takes into account the inherent correlation between them. This is especially crucial in the analysis of higher education institutions. We use a unique Colombian database on universities, which contains scores in five domains tested in a…

The Impact of Multiple Endpoint Dependency on "Q" and "I"[superscript 2] in Meta-Analysis

ERIC Educational Resources Information Center

Thompson, Christopher Glen; Becker, Betsy Jane

2014-01-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures "Q" and…

Time-frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes

NASA Astrophysics Data System (ADS)

Abid, Fathi; Kaffel, Bilel

2018-01-01

Understanding the interrelationships of the global macro assets is crucial for global macro investing. This paper investigates the local variance and the interconnection between the stock, gold, oil, Forex and the implied volatility markets in the time/frequency domains using the wavelet methodology, including the wavelet power spectrum, the wavelet squared coherence and phase difference, the wavelet multiple correlation and cross-correlation. The univariate analysis reveals that, in some crisis periods, underlying asset markets present the same pattern in terms of the wavelet power spectrum indicating high volatility for the medium scale, and that for the other market stress periods, volatility behaves differently. Moreover, unlike the underlying asset markets, the implied volatility markets are characterized by high power regions across the entire period, even in the absence of economic events. Bivariate results show a bidirectional relationship between the underlying assets and their corresponding implied volatility indexes, and a steady co-movement between the stock index and its corresponding fear index. Multiple correlation analysis indicates a strong correlation between markets at high scales with evidence of a nearly perfect integration for a period longer than a year. In addition, the hedging strategies based on the volatility index lead to an increase in portfolio correlation. On the other hand, the results from multiple cross-correlations reveal that the lead-lag effect starts from the medium scale and that the VIX (stock market volatility index) index is the potential leader or follower of the other markets.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Correlative Tomography

PubMed Central

Burnett, T. L.; McDonald, S. A.; Gholinia, A.; Geurts, R.; Janus, M.; Slater, T.; Haigh, S. J.; Ornek, C.; Almuaili, F.; Engelberg, D. L.; Thompson, G. E.; Withers, P. J.

2014-01-01

Increasingly researchers are looking to bring together perspectives across multiple scales, or to combine insights from different techniques, for the same region of interest. To this end, correlative microscopy has already yielded substantial new insights in two dimensions (2D). Here we develop correlative tomography where the correlative task is somewhat more challenging because the volume of interest is typically hidden beneath the sample surface. We have threaded together x-ray computed tomography, serial section FIB-SEM tomography, electron backscatter diffraction and finally TEM elemental analysis all for the same 3D region. This has allowed observation of the competition between pitting corrosion and intergranular corrosion at multiple scales revealing the structural hierarchy, crystallography and chemistry of veiled corrosion pits in stainless steel. With automated correlative workflows and co-visualization of the multi-scale or multi-modal datasets the technique promises to provide insights across biological, geological and materials science that are impossible using either individual or multiple uncorrelated techniques. PMID:24736640

Pressures, Stresses, Anxieties, and On-Job Safety of the School Superintendent.

ERIC Educational Resources Information Center

Chand, Krishan

Identification of the causes of job stress for public school superintendents, with a focus on personal-experiential and task variables, is the purpose of this study. Methodology involved a mail survey of 1,531 randomly selected superintendents. Canonical correlation analysis (CCA) and multiple regression correlation (MCR) analysis were used to…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Physical and Cognitive-Affective Factors Associated with Fatigue in Individuals with Fibromyalgia: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Muller, Veronica; Brooks, Jessica; Tu, Wei-Mo; Moser, Erin; Lo, Chu-Ling; Chan, Fong

2015-01-01

Purpose: The main objective of this study was to determine the extent to which physical and cognitive-affective factors are associated with fibromyalgia (FM) fatigue. Method: A quantitative descriptive design using correlation techniques and multiple regression analysis. The participants consisted of 302 members of the National Fibromyalgia &…

Methods for Improving Information from ’Undesigned’ Human Factors Experiments.

DTIC Science & Technology

Human factors engineering, Information processing, Regression analysis , Experimental design, Least squares method, Analysis of variance, Correlation techniques, Matrices(Mathematics), Multiple disciplines, Mathematical prediction

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

SER Analysis of MPPM-Coded MIMO-FSO System over Uncorrelated and Correlated Gamma-Gamma Atmospheric Turbulence Channels

NASA Astrophysics Data System (ADS)

Khallaf, Haitham S.; Garrido-Balsells, José M.; Shalaby, Hossam M. H.; Sampei, Seiichi

2015-12-01

The performance of multiple-input multiple-output free space optical (MIMO-FSO) communication systems, that adopt multipulse pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived for both cases of uncorrelated and correlated channels. The effects of background noise, receiver shot-noise, and atmospheric turbulence are taken into consideration in our analysis. The random fluctuations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the widely used gamma-gamma statistical distribution. Uncorrelated MIMO channels are modeled by the α-μ distribution. A closed-form expression for the probability density function of the optical received irradiance is derived for the case of correlated MIMO channels. Using our analytical expressions, the degradation of the system performance with the increment of the correlation coefficients between MIMO channels is corroborated.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

PubMed

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

Disability-Specific Atlases of Gray Matter Loss in Relapsing-Remitting Multiple Sclerosis.

PubMed

MacKenzie-Graham, Allan; Kurth, Florian; Itoh, Yuichiro; Wang, He-Jing; Montag, Michael J; Elashoff, Robert; Voskuhl, Rhonda R

2016-08-01

Multiple sclerosis (MS) is characterized by progressive gray matter (GM) atrophy that strongly correlates with clinical disability. However, whether localized GM atrophy correlates with specific disabilities in patients with MS remains unknown. To understand the association between localized GM atrophy and clinical disability in a biology-driven analysis of MS. In this cross-sectional study, magnetic resonance images were acquired from 133 women with relapsing-remitting MS and analyzed using voxel-based morphometry and volumetry. A regression analysis was used to determine whether voxelwise GM atrophy was associated with specific clinical deficits. Data were collected from June 28, 2007, to January 9, 2014. Voxelwise correlation of GM change with clinical outcome measures (Expanded Disability Status Scale and Multiple Sclerosis Functional Composite scores). Among the 133 female patients (mean [SD] age, 37.4 [7.5] years), worse performance on the Multiple Sclerosis Functional Composite correlated with voxelwise GM volume loss in the middle cingulate cortex (P < .001) and a cluster in the precentral gyrus bilaterally (P = .004). In addition, worse performance on the Paced Auditory Serial Addition Test correlated with volume loss in the auditory and premotor cortices (P < .001), whereas worse performance on the 9-Hole Peg Test correlated with GM volume loss in Brodmann area 44 (Broca area; P = .02). Finally, voxelwise GM loss in the right paracentral lobulus correlated with bowel and bladder disability (P = .03). Thus, deficits in specific clinical test results were directly associated with localized GM loss in clinically eloquent locations. These biology-driven data indicate that specific disabilities in MS are associated with voxelwise GM loss in distinct locations. This approach may be used to develop disability-specific biomarkers for use in future clinical trials of neuroprotective treatments in MS.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

Multiple Mediation Analysis of the Relationship between Rapid Naming and Reading

ERIC Educational Resources Information Center

Poulsen, Mads; Juul, Holger; Elbro, Carsten

2015-01-01

It is well established that rapid automatised naming (RAN) correlates with reading ability. Despite several attempts, no single component process (mediator) has been identified that fully accounts for the correlation. The present paper estimated the explanatory value of several mediators for the RAN--reading correlation. One hundred and sixty-nine…

Advanced Statistics for Exotic Animal Practitioners.

PubMed

Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G

2017-09-01

Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical presentation and blood gas analysis of multiple trauma patients for prediction of standard coagulation parameters at emergency department arrival.

PubMed

Hilbert-Carius, P; Hofmann, G O; Lefering, R; Stuttmann, R; Struck, M F

2016-04-01

Trauma-induced coagulopathy (TIC) in multiple trauma patients is a potentially lethal complication. Whether quickly available laboratory parameters using point-of-care (POC) blood gas analysis (BGA) may serve as surrogate parameters for standard coagulation parameters is unknown. The present study evaluated TraumaRegister DGU® of the German Trauma Society for correlations between POC BGA parameters and standard coagulation parameters. In the setting of 197 trauma centres (172 in Germany), 86,442 patients were analysed between 2005 and 2012. Of these, 40,129 (72% men) with a mean age 46 ± 21 years underwent further analysis presenting with direct admission from the scene of the accident to a trauma centre, injury severity score (ISS) ≥ 9, complete data available for the calculation of revised injury severity classification prognosis, and blood samples with valid haemoglobin (Hb) measurements taken immediately after emergency department (ED) admission. Correlations between standard coagulation parameters and POC BGA parameters (Hb, base excess [BE], lactate) were tested using Pearson's test with a two-tailed significance level of p < 0.05. A subgroup analysis including patients with ISS > 16, ISS > 25, ISS > 16 and shock at ED admission, and patients with massive transfusion was likewise carried out. Correlations were found between Hb and prothrombin time (r = 0.497; p < 0.01), Hb and activated partial thromboplastin time (aPTT; r = -0.414; p < 0.01), and Hb and platelet count (PLT; r = 0.301; p < 0.01). Patients presenting with ISS ≥ 16 and shock (systolic blood pressure < 90 mmHg) at ED admission (n = 4,329) revealed the strongest correlations between Hb and prothrombin time (r = 0.570; p < 0.01), Hb and aPTT (r = -0.457; p < 0.01), and Hb and PLT (r = 0.412; p < 0.01). Significant correlations were also found between BE and prothrombin time (r = -0.365; p < 0.01), and BE and aPTT (r = 0.327, p < 0.01). No correlations were found between Hb, BE and lactate lactate. POC BGA parameters Hb and BE of multiple trauma patients correlated with standard coagulation parameters in a large database analysis. These correlations were particularly strong in multiple trauma patients presenting with ISS > 16 and shock at ED admission. This may be relevant for hospitals with delayed availability of coagulation studies and those without viscoelastic POC devices. Future studies may determine whether clinical presentation/BGA-oriented coagulation therapy is an appropriate tool for improving outcomes after major trauma.

[Correlation between feeding index and growth development of 6-36 month-old infants in two counties of western China by applying multiple correspondence analysis].

PubMed

Chen, Hong-da; Hao, Bo; Kang, Xiao-ping; Zhao, Geng-li; Zhou, Min

2012-06-18

To explore the correlation between feeding index and growth development status of infants from two counties of western China by applying the method of multiple correspondence analysis. Two sample counties were randomly selected from the ones that satisfied the research conditions in Shaanxi province and Chongqing in western China. In the study, 472 premature/low birth weight infants (PLBW) and 461 normal term infants (NT) of 6-36 months from the two counties were investigated from September 2010 to November 2010. The SPSS 19.0 software was applied to analyze the data using general statistical analysis and multiple correspondence analysis. In the two counties of western China, the proportion of infants with feeding index at the medium level was the highest, which was between 50% and 60%. In the PLBW group and the NT group, the proportion of low level of feeding index among 6-9 month-old infants was the highest, and the proportion was 33.3% for the PLBW group and 29.4% for the NT group. For both the PLBW group and the NT group, the distribution of feeding index among the different age groups showed significant difference (P<0.05).Among the infants with low level of feeding index, the growth development of the PLBW lay behind that of the NT. We could see a catching-up trend of the PLBW with medium or good level of feeding index, but their growth development index was still at a lower level than that of the NT with the same level of feeding condition. Through multiple correspondence analyses, the outcomes of PLBW corresponded and strongly correlated with low level of feeding index, low level of growth development index, mother's low education degree and low annual family income. And the outcomes of NT corresponded and strongly correlated with medium/good level of feeding index, medium level of growth development status, mother's medium/high education degree and medium/high level of annual family income. There are good correspondence correlations at different hierarchical levels of the infants' group, feeding index, growth development index and family factors in the two counties of western China. Multiple correspondence analysis could directly reveal the correlation among several variables, which is a suitable method for categorical data. The result can be illustrated directly through a two-dimensional graph and could provide the suggestion of feeding practice for different infants in western rural China.

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

Integrative Analysis of “-Omics” Data Using Penalty Functions

PubMed Central

Zhao, Qing; Shi, Xingjie; Huang, Jian; Liu, Jin; Li, Yang; Ma, Shuangge

2014-01-01

In the analysis of omics data, integrative analysis provides an effective way of pooling information across multiple datasets or multiple correlated responses, and can be more effective than single-dataset (response) analysis. Multiple families of integrative analysis methods have been proposed in the literature. The current review focuses on the penalization methods. Special attention is paid to sparse meta-analysis methods that pool summary statistics across datasets, and integrative analysis methods that pool raw data across datasets. We discuss their formulation and rationale. Beyond “standard” penalized selection, we also review contrasted penalization and Laplacian penalization which accommodate finer data structures. The computational aspects, including computational algorithms and tuning parameter selection, are examined. This review concludes with possible limitations and extensions. PMID:25691921

Forward-backward multiplicity fluctuation and longitudinal harmonics in high-energy nuclear collisions

DOE PAGES

Jia, Jiangyong; Radhakrishnan, Sooraj; Zhou, Mingliang

2016-04-18

In this paper, an analysis method is proposed to study the forward-backward (FB) multiplicity fluctuation in high-energy nuclear collisions, built on the earlier work of Bzdak and Teaney [Phys. Rev. C 87, 024906 (2013)]. The method allows the decomposition of the centrality dependence of average multiplicity from the dynamical event-by-event (EbyE) fluctuation of multiplicity in pseudorapidity. Application of the method to AMPT (A Multi-Phase Transport model) and HIJING (Heavy Ion Jet INteraction Generator) models shows that the long-range component of the FB correlation is captured by a few longitudinal harmonics, with the first component driven by the asymmetry in themore » number of participating nucleons in the two colliding nuclei. The higher-order longitudinal harmonics are found to be strongly damped in AMPT compared to HIJING, due to weaker short-range correlations as well as the final-state effects present in the AMPT model. Two-particle pseudorapidity correlation reveals interesting charge-dependent short-range structures that are absent in HIJING model. Lastly, the proposed method opens an avenue to elucidate the particle production mechanism and early time dynamics in heavy-ion collisions. Future analysis directions and prospects of using the pseudorapidity correlation function to understand the centrality bias in p + p, p + A, and A + A collisions are discussed.« less

Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis.

PubMed

Motta, Caterina; Palermo, Eduardo; Studer, Valeria; Germanotta, Marco; Germani, Giorgio; Centonze, Diego; Cappa, Paolo; Rossi, Silvia; Rossi, Stefano

2016-01-01

The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis.

Revealing time bunching effect in single-molecule enzyme conformational dynamics.

PubMed

Lu, H Peter

2011-04-21

In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a cross correlation analysis can be applied for each specific segment to obtain a detailed fluctuation dynamics analysis.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Clustering stocks using partial correlation coefficients

NASA Astrophysics Data System (ADS)

Jung, Sean S.; Chang, Woojin

2016-11-01

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

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

PubMed

Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

2017-01-01

Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

The clinico-radiological paradox of cognitive function and MRI burden of white matter lesions in people with multiple sclerosis: A systematic review and meta-analysis.

PubMed

Mollison, Daisy; Sellar, Robin; Bastin, Mark; Mollison, Denis; Chandran, Siddharthan; Wardlaw, Joanna; Connick, Peter

2017-01-01

Moderate correlation exists between the imaging quantification of brain white matter lesions and cognitive performance in people with multiple sclerosis (MS). This may reflect the greater importance of other features, including subvisible pathology, or methodological limitations of the primary literature. To summarise the cognitive clinico-radiological paradox and explore the potential methodological factors that could influence the assessment of this relationship. Systematic review and meta-analysis of primary research relating cognitive function to white matter lesion burden. Fifty papers met eligibility criteria for review, and meta-analysis of overall results was possible in thirty-two (2050 participants). Aggregate correlation between cognition and T2 lesion burden was r = -0.30 (95% confidence interval: -0.34, -0.26). Wide methodological variability was seen, particularly related to key factors in the cognitive data capture and image analysis techniques. Resolving the persistent clinico-radiological paradox will likely require simultaneous evaluation of multiple components of the complex pathology using optimum measurement techniques for both cognitive and MRI feature quantification. We recommend a consensus initiative to support common standards for image analysis in MS, enabling benchmarking while also supporting ongoing innovation.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

PubMed Central

2014-01-01

Background Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. Methods The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Results Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Conclusions Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately. PMID:25047164

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

PubMed Central

2012-01-01

Background ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles. Results We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately. Conclusions iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB. PMID:23194258

An Extension of Dominance Analysis to Canonical Correlation Analysis

ERIC Educational Resources Information Center

Huo, Yan; Budescu, David V.

2009-01-01

Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…

Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Testing Multiple Outcomes in Repeated Measures Designs

ERIC Educational Resources Information Center

Lix, Lisa M.; Sajobi, Tolulope

2010-01-01

This study investigates procedures for controlling the familywise error rate (FWR) when testing hypotheses about multiple, correlated outcome variables in repeated measures (RM) designs. A content analysis of RM research articles published in 4 psychology journals revealed that 3 quarters of studies tested hypotheses about 2 or more outcome…

A Bayesian Missing Data Framework for Generalized Multiple Outcome Mixed Treatment Comparisons

ERIC Educational Resources Information Center

Hong, Hwanhee; Chu, Haitao; Zhang, Jing; Carlin, Bradley P.

2016-01-01

Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular because of their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (although richer than standard meta-analysis, comparing only two…

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci.

PubMed

Rand, Kristin A; Song, Chi; Dean, Eric; Serie, Daniel J; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S; Bock, Cathryn H; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K; Conti, David V; Zimmerman, Todd; Hwang, Amie E; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L; Berndt, Sonja I; Blot, William J; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W Ryan; Stevens, Victoria L; Lieber, Michael R; Goodman, Phyllis J; Hennis, Anselm J M; Hsing, Ann W; Mehta, Jayesh; Kittles, Rick A; Kolb, Suzanne; Klein, Eric A; Leske, Cristina; Murphy, Adam B; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S; Vij, Ravi; Rybicki, Benjamin A; Stanford, Janet L; Signorello, Lisa B; Witte, John S; Ambrosone, Christine B; Bhatti, Parveen; John, Esther M; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Birmann, Brenda M; Ingles, Sue A; Press, Michael F; Atanackovic, Djordje; Glenn, Martha J; Cannon-Albright, Lisa A; Jones, Brandt; Tricot, Guido; Martin, Thomas G; Kumar, Shaji K; Wolf, Jeffrey L; Deming Halverson, Sandra L; Rothman, Nathaniel; Brooks-Wilson, Angela R; Rajkumar, S Vincent; Kolonel, Laurence N; Chanock, Stephen J; Slager, Susan L; Severson, Richard K; Janakiraman, Nalini; Terebelo, Howard R; Brown, Elizabeth E; De Roos, Anneclaire J; Mohrbacher, Ann F; Colditz, Graham A; Giles, Graham G; Spinelli, John J; Chiu, Brian C; Munshi, Nikhil C; Anderson, Kenneth C; Levy, Joan; Zonder, Jeffrey A; Orlowski, Robert Z; Lonial, Sagar; Camp, Nicola J; Vachon, Celine M; Ziv, Elad; Stram, Daniel O; Hazelett, Dennis J; Haiman, Christopher A; Cozen, Wendy

2016-12-01

Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10 -7 ) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR. ©2016 American Association for Cancer Research.

Performance Analysis of a De-correlated Modified Code Tracking Loop for Synchronous DS-CDMA System under Multiuser Environment

NASA Astrophysics Data System (ADS)

Wu, Ya-Ting; Wong, Wai-Ki; Leung, Shu-Hung; Zhu, Yue-Sheng

This paper presents the performance analysis of a De-correlated Modified Code Tracking Loop (D-MCTL) for synchronous direct-sequence code-division multiple-access (DS-CDMA) systems under multiuser environment. Previous studies have shown that the imbalance of multiple access interference (MAI) in the time lead and time lag portions of the signal causes tracking bias or instability problem in the traditional correlating tracking loop like delay lock loop (DLL) or modified code tracking loop (MCTL). In this paper, we exploit the de-correlating technique to combat the MAI at the on-time code position of the MCTL. Unlike applying the same technique to DLL which requires an extensive search algorithm to compensate the noise imbalance which may introduce small tracking bias under low signal-to-noise ratio (SNR), the proposed D-MCTL has much lower computational complexity and exhibits zero tracking bias for the whole range of SNR, regardless of the number of interfering users. Furthermore, performance analysis and simulations based on Gold codes show that the proposed scheme has better mean square tracking error, mean-time-to-lose-lock and near-far resistance than the other tracking schemes, including traditional DLL (T-DLL), traditional MCTL (T-MCTL) and modified de-correlated DLL (MD-DLL).

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

Comparison of Rotor Structural Loads Calculated using Comprehensive Analysis

NASA Technical Reports Server (NTRS)

Johnson, Wayne; Yeo, Hyeonsoo

2005-01-01

Blade flap and chord bending and torsion moments are investigated for six rotors operating at transition and high speed: H-34 in flight and wind tunnel, SA 330 (research Puma), SA 349/2, UH-60A full-scale, and BO- 105 model (HART-I). The measured data from flight and wind tunnel tests are compared with calculations obtained using the comprehensive analysis CAMRAD II. The calculations were made using two free wake models: rolled-up and multiple-trailer with consolidation models. At transition speed, there is fair to good agreement for the flap and chord bending moments between the test data and analysis for the H-34, research Puma, and SA 349/2. Torsion moment correlation, in general, is fair to good for all the rotors investigated. Better flap bending and torsion moment correlation is obtained for the UH-60A and BO-105 rotors by using the multiple-trailer with consolidation wake model. In the high speed condition, the analysis shows generally better correlation in magnitude than in phase for the flap bending and torsion moments. However, a significant underprediction of chord bending moment is observed for the research Puma and UH-60A. The poor chord bending moment correlation appears to be caused by the airloads model, not the structural dynamics.

Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

PubMed

Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

2012-01-01

The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

Vectorized data acquisition and fast triple-correlation integrals for Fluorescence Triple Correlation Spectroscopy

PubMed Central

Ridgeway, William K; Millar, David P; Williamson, James R

2013-01-01

Fluorescence Correlation Spectroscopy (FCS) is widely used to quantitate reaction rates and concentrations of molecules in vitro and in vivo. We recently reported Fluorescence Triple Correlation Spectroscopy (F3CS), which correlates three signals together instead of two. F3CS can analyze the stoichiometries of complex mixtures and detect irreversible processes by identifying time-reversal asymmetries. Here we report the computational developments that were required for the realization of F3CS and present the results as the Triple Correlation Toolbox suite of programs. Triple Correlation Toolbox is a complete data analysis pipeline capable of acquiring, correlating and fitting large data sets. Each segment of the pipeline handles error estimates for accurate error-weighted global fitting. Data acquisition was accelerated with a combination of off-the-shelf counter-timer chips and vectorized operations on 128-bit registers. This allows desktop computers with inexpensive data acquisition cards to acquire hours of multiple-channel data with sub-microsecond time resolution. Off-line correlation integrals were implemented as a two delay time multiple-tau scheme that scales efficiently with multiple processors and provides an unprecedented view of linked dynamics. Global fitting routines are provided to fit FCS and F3CS data to models containing up to ten species. Triple Correlation Toolbox is a complete package that enables F3CS to be performed on existing microscopes. PMID:23525193

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2005-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Latino and African American seniors enrolled at 17 doctoral/research universities. Satisfaction with the overall quality of instruction and social involvement were the…

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2004-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Hispanic and African American seniors enrolled at 17 research-extensive universities. Satisfaction with the overall quality of instruction and social involvement were…

Noninvasive deep Raman detection with 2D correlation analysis

NASA Astrophysics Data System (ADS)

Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug

2014-07-01

The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.

Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis

PubMed Central

Motta, Caterina; Palermo, Eduardo; Studer, Valeria; Germanotta, Marco; Germani, Giorgio; Centonze, Diego; Cappa, Paolo

2016-01-01

Background The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. Objective To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. Methods A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. Results We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Conclusions Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis. PMID:26863109

Multiple perspective vulnerability analysis of the power network

NASA Astrophysics Data System (ADS)

Wang, Shuliang; Zhang, Jianhua; Duan, Na

2018-02-01

To understand the vulnerability of the power network from multiple perspectives, multi-angle and multi-dimensional vulnerability analysis as well as community based vulnerability analysis are proposed in this paper. Taking into account of central China power grid as an example, correlation analysis of different vulnerability models is discussed. Then, vulnerabilities produced by different vulnerability metrics under the given vulnerability models and failure scenarios are analyzed. At last, applying the community detecting approach, critical areas of central China power grid are identified, Vulnerable and robust communities on both topological and functional perspective are acquired and analyzed. The approach introduced in this paper can be used to help decision makers develop optimal protection strategies. It will be also useful to give a multiple vulnerability analysis of the other infrastructure systems.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Physical Activity and Depressive Symptoms in Four Ethnic Groups of Midlife Women

PubMed Central

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2014-01-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic-groups of midlife women in the U.S. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women; and the Kaiser Physical Activity Survey. The data were analyzed using chi-square tests, the ANOVA, twoway ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. PMID:24879749

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Analysis of dynamic multiplicity fluctuations at PHOBOS

NASA Astrophysics Data System (ADS)

Chai, Zhengwei; PHOBOS Collaboration; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Holynski, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Skulski, W.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J. L.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Verdier, R.; Wolfs, F. L. H.; Wosiek, B.; Wozniak, K.; Wuosmaa, A. H.; Wyslouch, B.

2005-01-01

This paper presents the analysis of the dynamic fluctuations in the inclusive charged particle multiplicity measured by PHOBOS for Au+Au collisions at surdsNN = 200GeV within the pseudo-rapidity range of -3 < η < 3. First the definition of the fluctuations observables used in this analysis is presented, together with the discussion of their physics meaning. Then the procedure for the extraction of dynamic fluctuations is described. Some preliminary results are included to illustrate the correlation features of the fluctuation observable. New dynamic fluctuations results will be available in a later publication.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

"TNOs are Cool": A survey of the trans-Neptunian region. XIII. Statistical analysis of multiple trans-Neptunian objects observed with Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Kovalenko, I. D.; Doressoundiram, A.; Lellouch, E.; Vilenius, E.; Müller, T.; Stansberry, J.

2017-11-01

Context. Gravitationally bound multiple systems provide an opportunity to estimate the mean bulk density of the objects, whereas this characteristic is not available for single objects. Being a primitive population of the outer solar system, binary and multiple trans-Neptunian objects (TNOs) provide unique information about bulk density and internal structure, improving our understanding of their formation and evolution. Aims: The goal of this work is to analyse parameters of multiple trans-Neptunian systems, observed with Herschel and Spitzer space telescopes. Particularly, statistical analysis is done for radiometric size and geometric albedo, obtained from photometric observations, and for estimated bulk density. Methods: We use Monte Carlo simulation to estimate the real size distribution of TNOs. For this purpose, we expand the dataset of diameters by adopting the Minor Planet Center database list with available values of the absolute magnitude therein, and the albedo distribution derived from Herschel radiometric measurements. We use the 2-sample Anderson-Darling non-parametric statistical method for testing whether two samples of diameters, for binary and single TNOs, come from the same distribution. Additionally, we use the Spearman's coefficient as a measure of rank correlations between parameters. Uncertainties of estimated parameters together with lack of data are taken into account. Conclusions about correlations between parameters are based on statistical hypothesis testing. Results: We have found that the difference in size distributions of multiple and single TNOs is biased by small objects. The test on correlations between parameters shows that the effective diameter of binary TNOs strongly correlates with heliocentric orbital inclination and with magnitude difference between components of binary system. The correlation between diameter and magnitude difference implies that small and large binaries are formed by different mechanisms. Furthermore, the statistical test indicates, although not significant with the sample size, that a moderately strong correlation exists between diameter and bulk density. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

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…

Visual Acuity Is Correlated with the Area of the Foveal Avascular Zone in Diabetic Retinopathy and Retinal Vein Occlusion.

PubMed

Balaratnasingam, Chandrakumar; Inoue, Maiko; Ahn, Seungjun; McCann, Jesse; Dhrami-Gavazi, Elona; Yannuzzi, Lawrence A; Freund, K Bailey

2016-11-01

To determine if the area of the foveal avascular zone (FAZ) is correlated with visual acuity (VA) in diabetic retinopathy (DR) and retinal vein occlusion (RVO). Cross-sectional study. Ninety-five eyes of 66 subjects with DR (65 eyes), branch retinal vein occlusion (19 eyes), and central retinal vein occlusion (11 eyes). Structural optical coherence tomography (OCT; Spectralis, Heidelberg Engineering) and OCT angiography (OCTA; Avanti, Optovue RTVue XR) data from a single visit were analyzed. FAZ area, point thickness of central fovea, central 1-mm subfield thickness, the occurrence of intraretinal cysts, ellipsoid zone disruption, and disorganization of retinal inner layers (DRIL) length were measured. VA was also recorded. Correlations between FAZ area and VA were explored using regression models. Main outcome measure was VA. Mean age was 62.9±13.2 years. There was no difference in demographic and OCT-derived anatomic measurements between branch retinal vein occlusion and central retinal vein occlusion groups (all P ≥ 0.058); therefore, data from the 2 groups were pooled together to a single RVO group for further statistical comparisons. Univariate and multiple regression analysis showed that the area of the FAZ was significantly correlated with VA in DR and RVO (all P ≤ 0.003). The relationship between FAZ area and VA varied with age (P = 0.026) such that for a constant FAZ area, an increase in patient age was associated with poorer vision (rise in logarithm of the minimum angle of resolution visual acuity). Disruption of the ellipsoid zone was significantly correlated with VA in univariate and multiple regression analysis (both P < 0.001). Occurrence of intraretinal cysts, DRIL length, and lens status were significantly correlated with VA in the univariate regression analysis (P ≤ 0.018) but not the multiple regression analysis (P ≥ 0.210). Remaining variables evaluated in this study were not predictive of VA (all P ≥ 0.225). The area of the FAZ is significantly correlated with VA in DR and RVO and this relationship is modulated by patient age. Further study about FAZ area and VA correlations during the natural course of retinal vascular diseases and following treatment is warranted. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Multiple Intelligences Patterns of Students at King Saud University and Its Relationship with Mathematics' Achievement

ERIC Educational Resources Information Center

Kandeel, Refat A. A.

2016-01-01

The purpose of this study was to determine the multiple intelligences patterns of students at King Saud University and its relationship with academic achievement for the courses of Mathematics. The study sample consisted of 917 students were selected a stratified random manner, the descriptive analysis method and Pearson correlation were used, the…

Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data.

PubMed

Gomes, Manuel; Hatfield, Laura; Normand, Sharon-Lise

2016-09-20

Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between-study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta-analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter-defibrillator devices alone to implantable cardioverter-defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Joint cross-correlation analysis reveals complex, time-dependent functional relationship between cortical neurons and arm electromyograms

PubMed Central

Zhuang, Katie Z.; Lebedev, Mikhail A.

2014-01-01

Correlation between cortical activity and electromyographic (EMG) activity of limb muscles has long been a subject of neurophysiological studies, especially in terms of corticospinal connectivity. Interest in this issue has recently increased due to the development of brain-machine interfaces with output signals that mimic muscle force. For this study, three monkeys were implanted with multielectrode arrays in multiple cortical areas. One monkey performed self-timed touch pad presses, whereas the other two executed arm reaching movements. We analyzed the dynamic relationship between cortical neuronal activity and arm EMGs using a joint cross-correlation (JCC) analysis that evaluated trial-by-trial correlation as a function of time intervals within a trial. JCCs revealed transient correlations between the EMGs of multiple muscles and neural activity in motor, premotor and somatosensory cortical areas. Matching results were obtained using spike-triggered averages corrected by subtracting trial-shuffled data. Compared with spike-triggered averages, JCCs more readily revealed dynamic changes in cortico-EMG correlations. JCCs showed that correlation peaks often sharpened around movement times and broadened during delay intervals. Furthermore, JCC patterns were directionally selective for the arm-reaching task. We propose that such highly dynamic, task-dependent and distributed relationships between cortical activity and EMGs should be taken into consideration for future brain-machine interfaces that generate EMG-like signals. PMID:25210153

A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis.

PubMed

Richter, Craig G; Thompson, William H; Bosman, Conrado A; Fries, Pascal

2015-07-01

The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations. Copyright © 2015. Published by Elsevier Inc.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets.

PubMed

Sornborger, Andrew; Broder, Josef; Majumder, Anirban; Srinivasamoorthy, Ganesh; Porter, Erika; Reagin, Sean S; Keith, Charles; Lauderdale, James D

2008-09-01

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.

Frontiers of Two-Dimensional Correlation Spectroscopy. Part 1. New concepts and noteworthy developments

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

A comprehensive survey review of new and noteworthy developments, which are advancing forward the frontiers in the field of 2D correlation spectroscopy during the last four years, is compiled. This review covers books, proceedings, and review articles published on 2D correlation spectroscopy, a number of significant conceptual developments in the field, data pretreatment methods and other pertinent topics, as well as patent and publication trends and citation activities. Developments discussed include projection 2D correlation analysis, concatenated 2D correlation, and correlation under multiple perturbation effects, as well as orthogonal sample design, predicting 2D correlation spectra, manipulating and comparing 2D spectra, correlation strategy based on segmented data blocks, such as moving-window analysis, features like determination of sequential order and enhanced spectral resolution, statistical 2D spectroscopy using covariance and other statistical metrics, hetero-correlation analysis, and sample-sample correlation technique. Data pretreatment operations prior to 2D correlation analysis are discussed, including the correction for physical effects, background and baseline subtraction, selection of reference spectrum, normalization and scaling of data, derivatives spectra and deconvolution technique, and smoothing and noise reduction. Other pertinent topics include chemometrics and statistical considerations, peak position shift phenomena, variable sampling increments, computation and software, display schemes, such as color coded format, slice and power spectra, tabulation, and other schemes.

Assessment of Neutrophil Function in Patients with Septic Shock: Comparison of Methods

PubMed Central

Wenisch, C.; Fladerer, P.; Patruta, S.; Krause, R.; Hörl, W.

2001-01-01

Patients with septic shock are shown to have decreased neutrophil phagocytic function by multiple assays, and their assessment by whole-blood assays (fluorescence-activated cell sorter analysis) correlates with assays requiring isolated neutrophils (microscopic and spectrophotometric assays). For patients with similar underlying conditions but without septic shock, this correlation does not occur. PMID:11139215

Functional importance of different patterns of correlation between adjacent cassette exons in human and mouse.

PubMed

Peng, Tao; Xue, Chenghai; Bi, Jianning; Li, Tingting; Wang, Xiaowo; Zhang, Xuegong; Li, Yanda

2008-04-26

Alternative splicing expands transcriptome diversity and plays an important role in regulation of gene expression. Previous studies focus on the regulation of a single cassette exon, but recent experiments indicate that multiple cassette exons within a gene may interact with each other. This interaction can increase the potential to generate various transcripts and adds an extra layer of complexity to gene regulation. Several cases of exon interaction have been discovered. However, the extent to which the cassette exons coordinate with each other remains unknown. Based on EST data, we employed a metric of correlation coefficients to describe the interaction between two adjacent cassette exons and then categorized these exon pairs into three different groups by their interaction (correlation) patterns. Sequence analysis demonstrates that strongly-correlated groups are more conserved and contain a higher proportion of pairs with reading frame preservation in a combinatorial manner. Multiple genome comparison further indicates that different groups of correlated pairs have different evolutionary courses: (1) The vast majority of positively-correlated pairs are old, (2) most of the weakly-correlated pairs are relatively young, and (3) negatively-correlated pairs are a mixture of old and young events. We performed a large-scale analysis of interactions between adjacent cassette exons. Compared with weakly-correlated pairs, the strongly-correlated pairs, including both the positively and negatively correlated ones, show more evidence that they are under delicate splicing control and tend to be functionally important. Additionally, the positively-correlated pairs bear strong resemblance to constitutive exons, which suggests that they may evolve from ancient constitutive exons, while negatively and weakly correlated pairs are more likely to contain newly emerging exons.

Correlation between Volume of Apical Periodontitis Determined by Cone-beam Computed Tomography Analysis and Endotoxin Levels Found in Primary Root Canal Infection.

PubMed

Cardoso, Flávia G R; Ferreira, Nádia S; Martinho, Frederico C; Nascimento, Gustavo G; Manhães, Luiz R C; Rocco, Marco A; Carvalho, Cláudio A T; Valera, Marcia C

2015-07-01

This clinical study was conducted to correlate the levels of endotoxins and bacterial counts found in primary endodontic infection with the volume of periapical bone destruction determined by cone-beam computed tomography (CBCT) analysis. Moreover, the levels of bacteria and endotoxins were correlated with the development of clinical features. Twenty-four root canals with primary endodontic disease and apical periodontitis were selected. Clinical features such as pain on palpation, pain on percussion, and previous episode of pain were recorded. The volume (cubic millimeters) of periapical bone destruction was determined by CBCT analysis. Endotoxins and bacterial samplings were collected by using sterile/apyrogenic paper points. Endotoxins were quantified by using limulus amebocyte lysate assay (KQCL test), and bacterial count (colony-forming units [CFU]/mL) was determined by using anaerobic culture techniques. Data were analyzed by Pearson correlation and multiple logistic regression (P < .05). Endotoxins and bacteria were detected in 100% of the root canal samples (24 of 24), with median values of 10.92 endotoxin units (EU)/mL (1.75-128 EU/mL) and 7.5 × 10(5) CFU/mL (3.20 × 10(5)-8.16 × 10(6) CFU/mL), respectively. The median volume of bone destruction determined by CBCT analysis was 100 mm(3) (10-450 mm(3)). The multiple regression analysis revealed a positive correlation between higher levels of endotoxins present in root canal infection and larger volume of bone destruction (P < .05). Moreover, higher levels of endotoxins were also correlated with the presence of previous pain (P < .05). Our findings revealed that the levels of endotoxins found in root canal infection are related to the volume of periapical bone destruction determined by CBCT analysis. Moreover, the levels of endotoxin are related to the presence of previous pain. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

[Correlation of retinol binding protein 4 with 
metabolic indexes of glucose and 
lipid, bile cholesterol saturation index].

PubMed

Wang, Wen; Li, Nianfeng

2015-06-01

To measure retinol binding protein 4 (RBP4) levels in serum and bile and to analyze their relationship with insulin resistance, dyslipidemia or cholesterol saturation index (CSI).
 A total of 60 patients with gallstone were divided into a diabetes group (n=30) and a control group (n=30). The concentrations of RBP4 in serum and bile were detected by enzyme-linked immunosorbent assay (ELISA). Enzyme colorimetric method was used to measure the concentration of biliary cholesterol, bile acid and phospholipid. Biliary CSI was calculated by Carey table. Partial correlation and multiple linear regression analysis were used to evaluate the correlation between the RBP4 levels in serum or bile and the above indexes.
 The RBP4 concentrations in serum and bile in the diabetes group were significantly elevated compared with those in the control group (both P<0.01). There was no significant difference in the serum total bile acid (TBA), serum triglyceride (TG), serum high-density lipoprotein (HDL), bile TBA, bile total cholesterol (TC) , bile phospholipids and bile CSI between the 2 groups (all P>0.05); but the serum TC, low density lipoprotein (LDL), fasting blood glucose (FBG), fasting insulin (FINS), and homeostasis model assessment for insulin resistance (HOMA-IR) in the diabetes group were significantly increased compared to those in the control group (all P<0.05). The partial correlation analysis, which was adjusted by age, showed that the bile RBP4 was positively correlated with body mass index (BMI), waist circumference (WC), FINS, FBG, TC, LDL and HOMA-IR (r=0.283, 0.405, 0.685, 0.667, 0.553, 0.424 and 0.735, respectively), and the serum RBP4 was also positively correlated with the WC, FINS, FBG, TC, LDL and HOMA-IR (r=0.317, 0.734, 0.609, 0.528, 0.386 and 0.751, respectively). Stepwise multivariate linear regression analysis suggested that the HOMA-IR, BMI and WC were independently correlated with the level of bile RBP4 (multiple regression equation: Ybile RBP4=2.372XHOMA-IR+0.420XBMI+0.178XWC-26.813), and the serum RBP4 level was correlated with the HOMA-IR and WC independently (multiple regression equation: Yserum RBP4=2.832XHOMA-IR +0.235XWC-20.128). Multiple regression equations showed that HOMA-IR was the strongest correlation factor with RBP4.
 RBP4 concentrations in serum and bile in the diabetes group are significantly higher than those in the control group. HOMA-IR, BMI and WC are independently correlated with the level of bile RBP4. HOMA-IR and WC are independently correlated with the serum RBP4 level. HOMA-IR is the strongest correlation factor with RBP4. RBP4 might play an important role in the course of gallstone formation in Type 2 diabetes mellitus.

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition.

PubMed

Yamasaki, Tomoko; Ogawa, Akitoshi; Osada, Takahiro; Jimura, Koji; Konishi, Seiki

2018-01-01

Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT). Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Physical activity and depressive symptoms in four ethnic groups of midlife women.

PubMed

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2015-06-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic groups of midlife women in the United States. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women (DIMW); and the Kaiser Physical Activity Survey (KPAS). The data were analyzed using chi-square tests, the ANOVA, two-way ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. © The Author(s) 2014.

[Long-term outcome following multiple trauma in working age : A prospective study in a Swiss trauma center].

PubMed

Gross, T; Amsler, F

2016-11-01

Given the lack of data in the available literature, we were interested in the disability rate and corresponding insurance costs following multiple trauma in Switzerland. The possible impact of demographic, traumatic and hospital process factors as well as subjective and objective longer-term outcome variables on insurance data acquired were examined. Following multiple trauma the clinical and socioeconomic parameters in 145 survivors of working age were investigated over 2 and 4 years post-injury at a Swiss trauma center (University Hospital Basel). The correlation with the corresponding data provided by the largest Swiss accident insurance company (Suva, n = 63) was tested by univariate and multivariate analysis and patients insured at Suva were compared with those insured elsewhere (n = 82). The mean level of disability in this cohort of multiple trauma patients insured at Suva was 43 %. The insurer expected costs of more than 1 million Swiss Francs per multiply injured patient. In univariate analysis, only discrete correlations (maximum r = 0.37) were found with resulting disability, but significant correlations were found in subsequent multivariate testing most of all for age and the sequential organ failure assessment (SOFA 11 % and 15 % predictive capacity, p = 0.001; corrected R 2  = 0.26). Among variables of longer-term outcome the Euro Quality of Life Group health-related quality of life in five dimensions (EQ-5D) correlated almost as highly with the objective extent of disability as did the reduced capacity to work declared by the patients (0.64 and 0.7, respectively). The estimation of long-term disability following multiple trauma based on primary data following injury appears to be possible only to a limited extent. Given the clinical and socioeconomic relevance, comparable analyses are necessary by including all insurance providers involved.

Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

PubMed

Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

2018-02-16

Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits

PubMed Central

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands. PMID:28680397

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits.

PubMed

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

Novel Index (Hepatic Receptor: IHR) to Evaluate Hepatic Functional Reserve Using (99m)Tc-GSA Scintigraphy.

PubMed

Hasegawa, Daisuke; Onishi, Hideo; Matsutomo, Norikazu

2016-02-01

This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

Medication Adherence, Work Performance and Self-Esteem among Psychiatric Patients Attending Psychosocial Rehabilitation Services at Bangalore, India.

PubMed

Gandhi, Sailaxmi; Pavalur, Rajitha; Thanapal, Sivakumar; Parathasarathy, Nirmala B; Desai, Geetha; Bhola, Poornima; Philip, Mariamma; Chaturvedi, Santosh K

2014-10-01

Work benefits mental health in innumerable ways. Vocational rehabilitation can enhance self-esteem. Medication adherence can improve work performance and thereby the individuals' self-esteem. To test the hypothesis that there would be a significant correlation between medication adherence, work performance and self-esteem. A quantitative, descriptive correlational research design was adopted to invite patients attending psychiatric rehabilitation services to participate in the research. Data was collected from a convenience sample of 60 subjects using the 'Medication Adherence Rating scale', 'Griffiths work behaviour scale' and the 'Rosenberg's Self-esteem scale'. Analysis was done using spss18 with descriptive statistics, Pearsons correlation coefficient and multiple regression analysis. There were 36 males and 24 females who participated in this study. The subjects had good mean medication adherence of 8.4 ± 1.5 with median of 9.00, high mean self-esteem of 17.65 ± 2.97 with median of 18.0 and good mean work performance of 88.62 ± 22.56 with median of 93.0. Although weak and not significant, there was a positive correlation (r = 0.22, P = 0.103) between medication adherence and work performance; positive correlation between (r = 0.25, P = 0.067) medication adherence and self-esteem; positive correlation between (r = 0.136, P = 0.299) work performance and self-esteem. Multiple regression analysis showed no significant predictors for medication adherence, work performance and self-esteem among patients with psychiatric illness. Medication monitoring and strengthening of work habit can improve self-esteem thereby, strengthening hope of recovery from illness.

Inverse Association between Air Pressure and Rheumatoid Arthritis Synovitis

PubMed Central

Furu, Moritoshi; Nakabo, Shuichiro; Ohmura, Koichiro; Nakashima, Ran; Imura, Yoshitaka; Yukawa, Naoichiro; Yoshifuji, Hajime; Matsuda, Fumihiko; Ito, Hiromu; Fujii, Takao; Mimori, Tsuneyo

2014-01-01

Rheumatoid arthritis (RA) is a bone destructive autoimmune disease. Many patients with RA recognize fluctuations of their joint synovitis according to changes of air pressure, but the correlations between them have never been addressed in large-scale association studies. To address this point we recruited large-scale assessments of RA activity in a Japanese population, and performed an association analysis. Here, a total of 23,064 assessments of RA activity from 2,131 patients were obtained from the KURAMA (Kyoto University Rheumatoid Arthritis Management Alliance) database. Detailed correlations between air pressure and joint swelling or tenderness were analyzed separately for each of the 326 patients with more than 20 assessments to regulate intra-patient correlations. Association studies were also performed for seven consecutive days to identify the strongest correlations. Standardized multiple linear regression analysis was performed to evaluate independent influences from other meteorological factors. As a result, components of composite measures for RA disease activity revealed suggestive negative associations with air pressure. The 326 patients displayed significant negative mean correlations between air pressure and swellings or the sum of swellings and tenderness (p = 0.00068 and 0.00011, respectively). Among the seven consecutive days, the most significant mean negative correlations were observed for air pressure three days before evaluations of RA synovitis (p = 1.7×10−7, 0.00027, and 8.3×10−8, for swellings, tenderness and the sum of them, respectively). Standardized multiple linear regression analysis revealed these associations were independent from humidity and temperature. Our findings suggest that air pressure is inversely associated with synovitis in patients with RA. PMID:24454853

Mathematical and Statistical Software Index.

DTIC Science & Technology

1986-08-01

geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis

New sesquiterpenes from Euonymus europaeus (Celastraceae).

PubMed

Descoins, Charles; Bazzocchi, Isabel López; Ravelo, Angel Gutiérrez

2002-02-01

A new sesquiterpene evoninate alkaloid (1), and two sesquiterpenes (2, 3) with a dihydro-beta-agarofuran skeleton, along with three known sesquiterpenes (4-6), were isolated from the seeds of Euonymus europaeus. Their structures were elucidated by high resolution mass analysis, and one- and two-dimensional (1D and 2D) NMR spectroscopy, including homonuclear and heteronuclear correlation [correlation spectroscopy (COSY), rotating frame Overhauser enhancement spectroscopy (ROESY), heteronuclear single quantum coherence (HSQC), and heteronuclear multiple bond correlation (HMBC)] experiments.

Assessment of gait parameters and fatigue in MS patients during inpatient rehabilitation: a pilot trial.

PubMed

Sacco, Rosaria; Bussman, Rita; Oesch, Peter; Kesselring, Jürg; Beer, Serafin

2011-05-01

Gait impairment and fatigue are common and disabling problems in multiple sclerosis (MS). Characterisation of abnormal gait in MS patients has been done mainly using observational studies and simple walking tests providing only limited quantitative and no qualitative data, or using intricate and time-consuming assessment procedures. In addition, the correlation of gait impairments with fatigue is largely unknown. The aim of this study was to characterise spatio-temporal gait parameters by a simple and easy-to-use gait analysis system (GAITRite®) in MS patients compared with healthy controls, and to analyse changes and correlation with fatigue during inpatient rehabilitation. Twenty-four MS patients (EDSS <6.5) admitted for inpatient rehabilitation and 19 healthy subjects were evaluated using the GAITRite® Functional Ambulation System. Between-group differences and changes of gait parameters during inpatient rehabilitation were analysed, and correlation with fatigue, using the Wurzburg Fatigue Inventory for Multiple Sclerosis (WEIMuS), was determined. Compared to healthy controls MS patients showed significant impairments in different spatio-temporal gait parameters, which showed a significant improvement during inpatient rehabilitation. Different gait parameters were correlated with fatigue physical score, and change of gait parameters was correlated with improvement of fatigue. Spatio-temporal gait analysis is helpful to assess specific walking impairments in MS patients and subtle changes during rehabilitation. Correlation with fatigue may indicate a possible negative impact of fatigue on rehabilitation outcome.

White Blood Cells, Neutrophils, and Reactive Oxygen Metabolites among Asymptomatic Subjects.

PubMed

Kotani, Kazuhiko; Sakane, Naoki

2012-06-01

Chronic inflammation and oxidative stress are associated with health and the disease status. The objective of the present study was to investigate the association among white blood cell (WBC) counts, neutrophil counts as a WBC subpopulation, and diacron reactive oxygen metabolites (d-ROMs) levels in an asymptomatic population. The clinical data, including general cardiovascular risk variables and high-sensitivity C-reactive protein (hs-CRP), were collected from 100 female subjects (mean age, 62 years) in outpatient clinics. The correlation of the d-ROMs with hs-CRP, WBC, and neutrophil counts was examined. The mean/median levels were WBC counts 5.9 × 10(9)/L, neutrophil counts 3.6 × 10(9)/L, hs-CRP 0.06 mg/dL, and d-ROMs 359 CURR U. A simple correlation analysis showed a significant positive correlation of the d-ROMs with the WBC counts, neutrophil counts, or hs-CRP levels. The correlation between d-ROMs and neutrophil counts (β = 0.22, P < 0.05), as well as that between d-ROMs and hs-CRP (β = 0.28, P < 0.01), remained significant and independent in a multiple linear regression analysis adjusted for other variables. A multiple linear regression analysis showed that WBC counts had only a positive correlation tendency to the d-ROMs. Neutrophils may be slightly but more involved in the oxidative stress status, as assessed by d-ROMs, in comparison to the overall WBC. Further studies are needed to clarify the biologic mechanism(s) of the observed relationship.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students.

PubMed

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-03-01

The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

PubMed Central

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-01-01

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students. PMID:26838568

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Coherent light depolarization by multiple scattering media and tissues: some fundamentals and applications

NASA Astrophysics Data System (ADS)

Zimnyakov, Dmitry A.; Tuchin, Valery V.; Yodh, Arjun G.; Mishin, Alexey A.; Peretochkin, Igor S.

1998-04-01

Relationships between decorrelation and depolarization of coherent light scattered by disordered media are examined by using the conception of the photon paths distribution functions. Analysis of behavior of the autocorrelation functions of the scattered field fluctuations and their polarization properties allows us to introduce generalized parameter of scattering media such as specific correlation time. Determination of specific correlation time has been carried out for phantom scattering media (water suspensions of polystyrene spheres). Results of statistical, correlation and polarization analysis of static and dynamic speckle patterns carried out in the experiments with human sclera with artificially controlled optical transmittance are presented. Some possibilities of applications of such polarization- correlation technique for monitoring and visualization of non- single scattering tissue structures are discussed.

Performance Analysis of a New Coded TH-CDMA Scheme in Dispersive Infrared Channel with Additive Gaussian Noise

NASA Astrophysics Data System (ADS)

Hamdi, Mazda; Kenari, Masoumeh Nasiri

2013-06-01

We consider a time-hopping based multiple access scheme introduced in [1] for communication over dispersive infrared links, and evaluate its performance for correlator and matched filter receivers. In the investigated time-hopping code division multiple access (TH-CDMA) method, the transmitter benefits a low rate convolutional encoder. In this method, the bit interval is divided into Nc chips and the output of the encoder along with a PN sequence assigned to the user determines the position of the chip in which the optical pulse is transmitted. We evaluate the multiple access performance of the system for correlation receiver considering background noise which is modeled as White Gaussian noise due to its large intensity. For the correlation receiver, the results show that for a fixed processing gain, at high transmit power, where the multiple access interference has the dominant effect, the performance improves by the coding gain. But at low transmit power, in which the increase of coding gain leads to the decrease of the chip time, and consequently, to more corruption due to the channel dispersion, there exists an optimum value for the coding gain. However, for the matched filter, the performance always improves by the coding gain. The results show that the matched filter receiver outperforms the correlation receiver in the considered cases. Our results show that, for the same bandwidth and bit rate, the proposed system excels other multiple access techniques, like conventional CDMA and time hopping scheme.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

PubMed

Wang, Lan; Zhu, Jiang; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Xiao-Wei; Xia, Wei; Xie, Fang-Fei; He, Pei; Bing, Peng-Fei; Qiu, Ying-Hua; Lin, Xiang; Lu, Xin; Zhang, Lei; Yi, Neng-Jun; Zhang, Yong-Hong; Lei, Shu-Feng

2018-02-01

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3'-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA-mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA-mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA-mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA-mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (P < 0.05) and ~70% were negative. The correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA-mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

Time-localized wavelet multiple regression and correlation

NASA Astrophysics Data System (ADS)

Fernández-Macho, Javier

2018-02-01

This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

Measuring the impact of multiple sclerosis on psychosocial functioning: the development of a new self-efficacy scale.

PubMed

Airlie, J; Baker, G A; Smith, S J; Young, C A

2001-06-01

To develop a scale to measure self-efficacy in neurologically impaired patients with multiple sclerosis and to assess the scale's psychometric properties. Cross-sectional questionnaire study in a clinical setting, the retest questionnaire returned by mail after completion at home. Regional multiple sclerosis (MS) outpatient clinic or the Clinical Trials Unit (CTU) at a large neuroscience centre in the UK. One hundred persons with MS attending the Walton Centre for Neurology and Neurosurgery and Clatterbridge Hospital, Wirral, as outpatients. Cognitively impaired patients were excluded at an initial clinic assessment. Patients were asked to provide demographic data and complete the self-efficacy scale along with the following validated scales: Hospital Anxiety and Depression Scale, Rosenberg Self-Esteem Scale, Impact, Stigma and Mastery and Rankin Scales. The Rankin Scale and Barthel Index were also assessed by the physician. A new 11-item self-efficacy scale was constructed consisting of two domains of control and personal agency. The validity of the scale was confirmed using Cronbach's alpha analysis of internal consistency (alpha = 0.81). The test-retest reliability of the scale over two weeks was acceptable with an intraclass correlation coefficient of 0.79. Construct validity was investigated using Pearson's product moment correlation coefficient resulting in significant correlations with depression (r= -0.52) anxiety (r =-0.50) and mastery (r= 0.73). Multiple regression analysis demonstrated that these factors accounted for 70% of the variance of scores on the self-efficacy scale, with scores on mastery, anxiety and perceived disability being independently significant. Assessment of the psychometric properties of this new self-efficacy scale suggest that it possesses good validity and reliability in patients with multiple sclerosis.

Charge-dependent azimuthal correlations in pPb collisions with CMS experiment

NASA Astrophysics Data System (ADS)

Tu, Zhoudunming; CMS Collaboration

2017-11-01

Charge-dependent azimuthal correlations relative to the event plane in AA collisions have been suggested as providing evidence for the chiral magnetic effect (CME) caused by local strong parity violation. However, the observation of the CME remains inconclusive because of several possible sources of background correlations that may account for part or all of the observed signals. This talk will present the first application of three-particle, charge-dependent azimuthal correlation analysis in proton-nucleus collisions, using pPb data collected with the CMS experiment at the LHC at √{sNN} = 5.02 TeV. The differences found in comparing same and opposite sign correlations are studied as a function of event multiplicity and the pseudorapidity gap between two of the particles detected in the CMS tracker detector. After selecting events with comparable charge-particle multiplicities, the results for pPb collisions are found to be similar to those for PbPb collisions collected at the same collision energy. With a reduced magnetic field strength and a random field orientation in high multiplicity pPb events, the CME contribution to any charge separation signal is expected to be much smaller than found in peripheral PbPb events. These results pose a challenge for the interpretation of charge-dependent azimuthal correlations in heavy ion collisions in terms of the chiral magnetic effect.

Two-pion femtoscopy in p -Pb collisions at s N N = 5.02 TeV

DOE PAGES

Adam, J.; Adamová, D.; Aggarwal, M. M.; ...

2015-03-24

Here, we report the results of the femtoscopic analysis of pairs of identical pions measured in p-Pb collisions at √s NN = 5.02 TeV. Femtoscopic radii are determined as a function of event multiplicity and pair momentum in three spatial dimensions. As in the pp collision system, the analysis is complicated by the presence of sizable background correlation structures in addition to the femtoscopic signal. The radii increase with event multiplicity and decrease with pair transverse momentum. When taken at comparable multiplicity, the radii measured in p-Pb collisions, at high multiplicity and low pair transverse momentum, are 10%–20% higher thanmore » those observed in pp collisions but below those observed in A–A collisions. The results are compared to hydrodynamic predictions at large event multiplicity as well as discussed in the context of calculations based on gluon saturation.« less

Revisiting adverse effects of cross-hybridization in Affymetrix gene expression data: do they matter for correlation analysis?

PubMed

Klebanov, Lev; Chen, Linlin; Yakovlev, Andrei

2007-11-07

This work was undertaken in response to a recently published paper by Okoniewski and Miller (BMC Bioinformatics 2006, 7: Article 276). The authors of that paper came to the conclusion that the process of multiple targeting in short oligonucleotide microarrays induces spurious correlations and this effect may deteriorate the inference on correlation coefficients. The design of their study and supporting simulations cast serious doubt upon the validity of this conclusion. The work by Okoniewski and Miller drove us to revisit the issue by means of experimentation with biological data and probabilistic modeling of cross-hybridization effects. We have identified two serious flaws in the study by Okoniewski and Miller: (1) The data used in their paper are not amenable to correlation analysis; (2) The proposed simulation model is inadequate for studying the effects of cross-hybridization. Using two other data sets, we have shown that removing multiply targeted probe sets does not lead to a shift in the histogram of sample correlation coefficients towards smaller values. A more realistic approach to mathematical modeling of cross-hybridization demonstrates that this process is by far more complex than the simplistic model considered by the authors. A diversity of correlation effects (such as the induction of positive or negative correlations) caused by cross-hybridization can be expected in theory but there are natural limitations on the ability to provide quantitative insights into such effects due to the fact that they are not directly observable. The proposed stochastic model is instrumental in studying general regularities in hybridization interaction between probe sets in microarray data. As the problem stands now, there is no compelling reason to believe that multiple targeting causes a large-scale effect on the correlation structure of Affymetrix gene expression data. Our analysis suggests that the observed long-range correlations in microarray data are of a biological nature rather than a technological flaw.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Dietary intake of nutrients and its correlation with fatigue in multiple sclerosis patients

PubMed Central

Bitarafan, Sama; Harirchian, Mohammad-Hossein; Nafissi, Shahriar; Sahraian, Mohammad-Ali; Togha, Mansoureh; Siassi, Fereydoun; Saedisomeolia, Ahmad; Alipour, Elham; Mohammadpour, Nakisa; Chamary, Maryam; Honarvar, Niyaz Mohammadzadeh

2014-01-01

Background The role of nutrition in the progression of multiple sclerosis (MS) and related complications such as fatigue has been reported by several studies. The aim of this study is the assessment of nutritional status and its relationship with fatigue in multiple sclerosis patients. Methods This is a cross-sectional study, in which 101 relapsing-remitting MS patients were enrolled. The fatigue status was determined using the validated Persian version of of the Modified Fatigue Impact Scale (MFIS). Dietary intake was assessed using a 3-day food record questionnaire and compared to dietary reference intake (DRI) values. Association between variables was determined using Pearson Correlation Coefficient. Results In the preset study, 25 men and 76 women (total = 101) were enrolled. Analysis of dietary intake showed that daily intake of vitamin D, folate, calcium, and magnesium were significantly lower than DRI in all of patients. In men, zinc intake was significantly lower than DRI; while, in women, iron was significantly below the DRI level. After adjusting for energy, MFIS and its physical subscale were highly correlated with intake of folate and magnesium. Conclusion Our findings support that lower magnesium and folate diets are correlated with higher fatigue scores in MS patients. PMID:24800044

Mapping Diffusion in a Living Cell via the Phasor Approach

PubMed Central

Ranjit, Suman; Lanzano, Luca; Gratton, Enrico

2014-01-01

Diffusion of a fluorescent protein within a cell has been measured using either fluctuation-based techniques (fluorescence correlation spectroscopy (FCS) or raster-scan image correlation spectroscopy) or particle tracking. However, none of these methods enables us to measure the diffusion of the fluorescent particle at each pixel of the image. Measurement using conventional single-point FCS at every individual pixel results in continuous long exposure of the cell to the laser and eventual bleaching of the sample. To overcome this limitation, we have developed what we believe to be a new method of scanning with simultaneous construction of a fluorescent image of the cell. In this believed new method of modified raster scanning, as it acquires the image, the laser scans each individual line multiple times before moving to the next line. This continues until the entire area is scanned. This is different from the original raster-scan image correlation spectroscopy approach, where data are acquired by scanning each frame once and then scanning the image multiple times. The total time of data acquisition needed for this method is much shorter than the time required for traditional FCS analysis at each pixel. However, at a single pixel, the acquired intensity time sequence is short; requiring nonconventional analysis of the correlation function to extract information about the diffusion. These correlation data have been analyzed using the phasor approach, a fit-free method that was originally developed for analysis of FLIM images. Analysis using this method results in an estimation of the average diffusion coefficient of the fluorescent species at each pixel of an image, and thus, a detailed diffusion map of the cell can be created. PMID:25517145

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Relationships among multiple aspects of agriculture's environmental impact and productivity: a meta-analysis to guide sustainable agriculture.

PubMed

German, Richard N; Thompson, Catherine E; Benton, Tim G

2017-05-01

Given the pressures on land to produce ever more food, doing it 'sustainably' is growing in importance. However, 'sustainable agriculture' is complex to define, not least because agriculture impacts in many different ways and it is not clear how different aspects of sustainability may be in synergy or trade off against each other. We conducted a meta-analysis to assess the relationships between multiple measures of sustainability using novel analytical methods, based around defining the efficiency frontier in the relationship between variables, as well as using correlation analysis. We define 20 grouped variables of agriculture's impact (e.g. on soil, greenhouse gas, water, biodiversity) and find evidence of both strong positive and negative correlations between them. Analysis based on the efficiency frontier suggests that trade-offs can be 'softened' by exploiting the natural between-study variation that arises from a combination of farming best practice and context. Nonetheless, the literature provides strong evidence of the relationship between yields and the negative externalities created by farming across a range of measures. © 2016 Cambridge Philosophical Society.

Correlation between skin-prick testing, individual specific IgE tests, and a multiallergen IgE assay for allergy detection in patients with chronic rhinitis.

PubMed

Cho, Jae Hoon; Suh, Jeffrey D; Kim, Jin Kook; Hong, Seok-Chan; Park, Il-Ho; Lee, Heung-Man

2014-01-01

Allergy test results can differ based on the method used. The most common tests include skin-prick testing (SPT) and in vitro tests to detect allergen-specific IgE. This study was designed to assess allergy test results using SPT, individual specific IgE tests, and a multiallergen IgE assay (multiple allergen simultaneous test) in patients with chronic rhinitis and controls. One hundred forty total patients were prospectively enrolled in the study, including 100 patients with chronic rhinitis and 40 control patients without atopy. All eligible patients underwent SPT, serum analysis using individual specific IgE test, and multiple allergen simultaneous test against 10 common allergens. Allergy test results were then compared to identify correlation and interest agreement. There was an 81-97% agreement between SPT and individual specific IgE test in allergen detection and an 80-98% agreement between SPT and multiple allergen simultaneous test. Individual specific IgE test and multiple allergen simultaneous test allergy detection prevalence was generally similar to SPT in patients with chronic rhinitis. All control patients had negative SPT (0/40), but low positive results were found with both individual specific IgE test (5-12.5%) and multiple allergen simultaneous test (2.5-7.5%) to some allergens, especially cockroach, Dermatophagoides farina, and ragweed. Agreement and correlation between individual specific IgE test and multiple allergen simultaneous test were good to excellent for a majority of tested allergens. This study shows good agreement and correlation between SPT with individual specific IgE test and multiple allergen simultaneous test on a majority of the tested allergens for patients with chronic rhinitis. Comparing the two in vitro tests, individual specific IgE test agrees with SPT better than multiple allergen simultaneous test.

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

On the equivalence of the RTI and SVM approaches to time correlated analysis

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

Croft, S.; Favalli, A.; Henzlova, D.

2014-11-21

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could alsomore » use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.« less

[Keys to preventing accidents in children in the school context].

PubMed

Gabari Gambarte, M Inés; Sáenz Mendía, Raquel

2016-11-02

To learn about children's perception of the causes and prevention strategies involved in school accidents. The sample included 584 school children aged 8-9 years from Navarra. A mixed design was chosen by questionnaire with three open-response questions and one multiple-choice assessment. Analysis was performed in two phases: 1) qualitative development of categories and dimensions of the responses of narrative content, and 2) quantitative variables for recoding correlational analysis. 22 categories emerged, which make up three perceptual dimensions: 1) attribution of causality (5), 2) identification of mechanisms of avoidance (11), and 3) development of coping strategies (6). The correlation intra-variables portray varying degrees: on the one hand, moderate positive numbers (r>0.5) in allocating and identifying causality avoidance mechanisms and, on the other hand, high positive correlation values (r>0.7) referred to developing coping strategies. Children are able to identify accidents as a health problem. They question the multiplicity of elements involved and relate the origin and kind of accident to prevention and support mechanisms. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Modelling the impact of correlations between condom use and sexual contact pattern on the dynamics of sexually transmitted infections.

PubMed

Yamamoto, Nao; Ejima, Keisuke; Nishiura, Hiroshi

2018-05-31

It is believed that sexually active people, i.e. people having multiple or concurrent sexual partners, are at a high risk of sexually transmitted infections (STI), but they are likely to be more aware of the risk and may exhibit greater fraction of the use of condom. The purpose of the present study is to examine the correlation between condom use and sexual contact pattern and clarify its impact on the transmission dynamics of STIs using a mathematical model. The definition of sexual contact pattern can be broad, but we focus on two specific aspects: (i) type of partnership (i.e. steady or casual partnership) and (ii) existence of concurrency (i.e. with single or multiple partners). Systematic review and meta-analysis of published studies are performed, analysing literature that epidemiologically examined the relationship between condom use and sexual contact pattern. Subsequently, we employ an epidemiological model and compute the reproduction number that accounts for with and without concurrency so that the corresponding coverage of condom use and its correlation with existence of concurrency can be explicitly investigated using the mathematical model. Combining the model with parameters estimated from the meta-analysis along with other assumed parameters, the impact of varying the proportion of population with multiple partners on the reproduction number is examined. Based on systematic review, we show that a greater number of people used condoms during sexual contact with casual partners than with steady partners. Furthermore, people with multiple partners use condoms more frequently than people with a single partner alone. Our mathematical model revealed a positive relationship between the effective reproduction number and the proportion of people with multiple partners. Nevertheless, the association was reversed to be negative by employing a slightly greater value of the relative risk of condom use for people with multiple partners than that empirically estimated. Depending on the correlation between condom use and the existence of concurrency, association between the proportion of people with multiple partners and the reproduction number can be reversed, suggesting the sexually active population is not necessary a primary target population to encourage condom use (i.e., sexually less active individuals could equivalently be a target in some cases).

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Dichotomous-noise-induced pattern formation in a reaction-diffusion system

NASA Astrophysics Data System (ADS)

Das, Debojyoti; Ray, Deb Shankar

2013-06-01

We consider a generic reaction-diffusion system in which one of the parameters is subjected to dichotomous noise by controlling the flow of one of the reacting species in a continuous-flow-stirred-tank reactor (CSTR) -membrane reactor. The linear stability analysis in an extended phase space is carried out by invoking Furutzu-Novikov procedure for exponentially correlated multiplicative noise to derive the instability condition in the plane of the noise parameters (correlation time and strength of the noise). We demonstrate that depending on the correlation time an optimal strength of noise governs the self-organization. Our theoretical analysis is corroborated by numerical simulations on pattern formation in a chlorine-dioxide-iodine-malonic acid reaction-diffusion system.

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Systematic characterization of Bacillus Genetic Stock Center Bacillus thuringiensis strains using Multi-Locus Sequence Typing.

PubMed

Wang, Kui; Shu, Changlong; Soberón, Mario; Bravo, Alejandra; Zhang, Jie

2018-04-30

The goal of this work was to perform a systematic characterization of Bacillus thuringiensis (Bt) strains from the Bacillus Genetic Stock Center (BGSC) collection using Multi-Locus Sequence Typing (MLST). Different genetic markers of 158 Bacillus thuringiensis (Bt) strains from 73 different serovars stored in the BGSC, that represented 92% of the different Bt serovars of the BGSC were analyzed, the 8% that were not analyzed were not available. In addition, we analyzed 72 Bt strains from 18 serovars available at the pubMLST bcereus database, and Bt strains G03, HBF18 and Bt185, with no H serovars provided by our laboratory. We performed a systematic MLST analysis using seven housekeeping genes (glpF, gmK, ilvD, pta, pur, pycA and tpi) and analyzed correlation of the results of this analysis with strain serovars. The 233 Bt strains analyzed were assigned to 119 STs from which 19 STs were new. Genetic relationships were established by phylogenetic analysis and showed that STs could be grouped in two major Clusters containing 21 sub-groups. We found that a significant number of STs (101 in total) correlated with specific serovars, such as ST13 that corresponded to nine Bt isolates from B. thuringiensis serovar kenyae. However, other serovars showed high genetic variability and correlated with multiple STs; for example, B. thuringiensis serovar morrisoni correlated with 11 different STs. In addition, we found that 16 different STs correlated with multiple serovars (2-4 different serovars); for example, ST12 correlated with B. thuringiensis serovar alesti, dakota, palmanyolensis and sotto/dendrolimus. These data indicated that only partial correspondence between MLST and serotyping can be established. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-02-01

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

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

The use of dwell time cross-correlation functions to study single-ion channel gating kinetics.

PubMed Central

Ball, F G; Kerry, C J; Ramsey, R L; Sansom, M S; Usherwood, P N

1988-01-01

The derivation of cross-correlation functions from single-channel dwell (open and closed) times is described. Simulation of single-channel data for simple gating models, alongside theoretical treatment, is used to demonstrate the relationship of cross-correlation functions to underlying gating mechanisms. It is shown that time irreversibility of gating kinetics may be revealed in cross-correlation functions. Application of cross-correlation function analysis to data derived from the locust muscle glutamate receptor-channel provides evidence for multiple gateway states and time reversibility of gating. A model for the gating of this channel is used to show the effect of omission of brief channel events on cross-correlation functions. PMID:2462924

100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers.

PubMed

Kawada, Tomoyuki; Yamada, Natsuki

2012-01-01

Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Exciton multiplication from first principles.

PubMed

Jaeger, Heather M; Hyeon-Deuk, Kim; Prezhdo, Oleg V

2013-06-18

Third-generation photovolatics require demanding cost and power conversion efficiency standards, which may be achieved through efficient exciton multiplication. Therefore, generating more than one electron-hole pair from the absorption of a single photon has vast ramifications on solar power conversion technology. Unlike their bulk counterparts, irradiated semiconductor quantum dots exhibit efficient exciton multiplication, due to confinement-enhanced Coulomb interactions and slower nonradiative losses. The exact characterization of the complicated photoexcited processes within quantum-dot photovoltaics is a work in progress. In this Account, we focus on the photophysics of nanocrystals and investigate three constituent processes of exciton multiplication, including photoexcitation, phonon-induced dephasing, and impact ionization. We quantify the role of each process in exciton multiplication through ab initio computation and analysis of many-electron wave functions. The probability of observing a multiple exciton in a photoexcited state is proportional to the magnitude of electron correlation, where correlated electrons can be simultaneously promoted across the band gap. Energies of multiple excitons are determined directly from the excited state wave functions, defining the threshold for multiple exciton generation. This threshold is strongly perturbed in the presence of surface defects, dopants, and ionization. Within a few femtoseconds following photoexcitation, the quantum state loses coherence through interactions with the vibrating atomic lattice. The phase relationship between single excitons and multiple excitons dissipates first, followed by multiple exciton fission. Single excitons are coupled to multiple excitons through Coulomb and electron-phonon interactions, and as a consequence, single excitons convert to multiple excitons and vice versa. Here, exciton multiplication depends on the initial energy and coupling magnitude and competes with electron-phonon energy relaxation. Multiple excitons are generated through impact ionization within picoseconds. The basis of exciton multiplication in quantum dots is the collective result of photoexcitation, dephasing, and nonadiabatic evolution. Each process is characterized by a distinct time-scale, and the overall multiple exciton generation dynamics is complete by about 10 ps. Without relying on semiempirical parameters, we computed quantum mechanical probabilities of multiple excitons for small model systems. Because exciton correlations and coherences are microscopic, quantum properties, results for small model systems can be extrapolated to larger, realistic quantum dots.

Study of the peculiarities of multiparticle production via event-by-event analysis in asymmetric nucleus-nucleus interactions

NASA Astrophysics Data System (ADS)

Fedosimova, Anastasiya; Gaitinov, Adigam; Grushevskaya, Ekaterina; Lebedev, Igor

2017-06-01

In this work the study on the peculiarities of multiparticle production in interactions of asymmetric nuclei to search for unusual features of such interactions, is performed. A research of long-range and short-range multiparticle correlations in the pseudorapidity distribution of secondary particles on the basis of analysis of individual interactions of nuclei of 197 Au at energy 10.7 AGeV with photoemulsion nuclei, is carried out. Events with long-range multiparticle correlations (LC), short-range multiparticle correlations (SC) and mixed type (MT) in pseudorapidity distribution of secondary particles, are selected by the Hurst method in accordance with Hurst curve behavior. These types have significantly different characteristics. At first, they have different fragmentation parameters. Events of LC type are processes of full destruction of the projectile nucleus, in which multicharge fragments are absent. In events of mixed type several multicharge fragments of projectile nucleus are discovered. Secondly, these two types have significantly different multiplicity distribution. The mean multiplicity of LC type events is significantly more than in mixed type events. On the basis of research of the dependence of multiplicity versus target-nuclei fragments number for events of various types it is revealed, that the most considerable multiparticle correlations are observed in interactions of the mixed type, which correspond to the central collisions of gold nuclei and nuclei of CNO-group, i.e. nuclei with strongly asymmetric volume, nuclear mass, charge, etc. Such events are characterised by full destruction of the target-nucleus and the disintegration of the projectile-nucleus on several multi-charged fragments.

Analysis on the correlation between temperature and discharge characteristic of cloud-to-ground lightning discharge plasma with multiple return strokes

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

Qu Haiyan; Chang Zhengshi; Yuan Ping

2011-01-15

The spectra of cloud-to-ground lightning with multiple return strokes have been obtained by using a slitless spectrograph on the Chinese Tibet plateau. Combining the spectra with synchronous electrical information, the correlation among spectral properties, channel temperatures and discharge characteristics, and thermal effects of current is discussed for the first time. The results show that the channel plasma temperature varies significantly from stroke to stroke within a given flash, and the total intensity of spectra is directly proportional to the amplitude of electric field change. Moreover, the positive correlation has been confirmed between the channel plasma temperature and the thermal effectmore » which shows the effect of the electric current accumulation. It is inferred that the total intensity of the spectra should be directly proportional to the intensity of discharge current, and channel temperature is correlated positively with the energy transmission in one return stroke.« less

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Study of the propensity for hemorrhage in Hispanic Americans with stroke.

PubMed

Frey, James L; Jahnke, Heidi K; Goslar, Pamela W

2008-01-01

Multiple sources document a higher proportion of intraparenchymal hemorrhage (HEM) in Hispanic (HIS) than white (WHI) patients with stroke. We sought an explanation for this phenomenon through analysis of multiple variables in our hospital-based stroke population. We performed univariate and multivariate analysis of risk factors in our HIS and WHI patients with stroke to identify differences that might account for a greater propensity for HEM in HIS patients. Multivariate analysis disclosed that the risk of HEM correlated significantly with untreated hypertension (HTN), HIS ethnicity, and heavy alcohol intake. A negative correlation was found for hyperlipidemia and diabetes. Our HIS patients with stroke had a greater prevalence of untreated HTN and heavy alcohol intake, with HIS men being at greatest risk. HIS patients with stroke in our hospital-based population appear relatively more prone to HEM than do WHI patients. This risk correlates with a greater likelihood of having untreated HTN and heavy alcohol intake, more so for HIS men. The explanation appears to be a relative lack of health awareness and involvement in our health care system. The possibility that HIS ethnicity itself constitutes a biological risk factor for HEM remains a matter of speculation. Validation of this work with community data should lead to remediation through a community-based effort.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

PubMed

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.

PubMed

Gritsenko, Valeriya; Hardesty, Russell L; Boots, Mathew T; Yakovenko, Sergiy

2016-01-01

Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

Correlative multiple porosimetries for reservoir sandstones with adoption of a new reference-sample-guided computed-tomographic method.

PubMed

Jin, Jae Hwa; Kim, Junho; Lee, Jeong-Yil; Oh, Young Min

2016-07-22

One of the main interests in petroleum geology and reservoir engineering is to quantify the porosity of reservoir beds as accurately as possible. A variety of direct measurements, including methods of mercury intrusion, helium injection and petrographic image analysis, have been developed; however, their application frequently yields equivocal results because these methods are different in theoretical bases, means of measurement, and causes of measurement errors. Here, we present a set of porosities measured in Berea Sandstone samples by the multiple methods, in particular with adoption of a new method using computed tomography and reference samples. The multiple porosimetric data show a marked correlativeness among different methods, suggesting that these methods are compatible with each other. The new method of reference-sample-guided computed tomography is more effective than the previous methods when the accompanied merits such as experimental conveniences are taken into account.

Correlative multiple porosimetries for reservoir sandstones with adoption of a new reference-sample-guided computed-tomographic method

PubMed Central

Jin, Jae Hwa; Kim, Junho; Lee, Jeong-Yil; Oh, Young Min

2016-01-01

One of the main interests in petroleum geology and reservoir engineering is to quantify the porosity of reservoir beds as accurately as possible. A variety of direct measurements, including methods of mercury intrusion, helium injection and petrographic image analysis, have been developed; however, their application frequently yields equivocal results because these methods are different in theoretical bases, means of measurement, and causes of measurement errors. Here, we present a set of porosities measured in Berea Sandstone samples by the multiple methods, in particular with adoption of a new method using computed tomography and reference samples. The multiple porosimetric data show a marked correlativeness among different methods, suggesting that these methods are compatible with each other. The new method of reference-sample-guided computed tomography is more effective than the previous methods when the accompanied merits such as experimental conveniences are taken into account. PMID:27445105

Neural Correlates of Alerting and Orienting Impairment in Multiple Sclerosis Patients

PubMed Central

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J.; Hidalgo-Muñoz, Antonio R.; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

Background A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. Results After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Conclusions Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients. PMID:24820333

Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

PubMed

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J; Hidalgo-Muñoz, Antonio R; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

Aging effects on DNA methylation modules in human brain and blood tissue

PubMed Central

2012-01-01

Background Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues. Results We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained. Conclusions Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles. PMID:23034122

Analysis of quality of life and influencing factors in 197 Chinese patients with port-wine stains

PubMed Central

Wang, Juan; Zhu, Yu-you; Wang, Zhong-ying; Yao, Xiu-hua; Zhang, Lan-fang; Lv, Hong; Zhang, Si-ping; Hu, Bai

2017-01-01

Abstract Port-wine stains (PWS) are congenital capillary malformations, usually occurring on the face, neck, and other exposed parts of the skin, that have serious psychological and social impact on the patient. Most researchers focus on the treatment of PWS, but the quality of life (QoL) of PWS patients is seldom researched. The objective of this study is to evaluate the QoL of patients with PWS on exposed parts and explore the factors influencing the QoL of PWS patients. The QoL of 197 cases with PWS on exposed parts were prospectively studied using the Dermatology Life Quality Index questionnaire (DLQI), and the factors influencing the patients’ QoL were analyzed by single-factor analysis and multiple-factor logistic regression analysis. The reliability and validity of the QoL of PWS patients were then assessed by DLQI. A total of 197 valid questionnaires were collected. The DLQI scores in PWS cases ranged from 2 to 16, with 2 to 5 in 52.29% (103/197), 6 to 10 in 42.13% (83/197), and 11 to 20 in 5.58% (11/197). The main score elements of the DLQI focused on symptoms and feelings, daily activities, and social entertainment. Single-factor analysis and multiple-factor logistic regression analysis showed that the main influencing factors were female sex, skin hypertrophy, and lesion area >30 cm2. The inter-item correlation averaged 47.46% and the Cronbach α was 0.740, indicating high internal consistency. Correlation of the 6 dimensions of the DLQI questionnaires with the total scores showed that the Spearman correlation coefficient r ranged from 0.550 to 0.782 (P < .001), with symptoms and feelings having a correlation coefficient of 0.782 and a high correlation with total scores. This study shows that PWS has mild to moderate influence on the QoL of most patients, mainly on daily activities, social entertainment, and feelings. PMID:29390578

Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.

PubMed

Iwasawa, Tae; Kanauchi, Tetsu; Hoshi, Toshiko; Ogura, Takashi; Baba, Tomohisa; Gotoh, Toshiyuki; Oba, Mari S

2016-01-01

To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.

Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover

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

Wolfrum, E. J.; Lorenz, A. J.; deLeon, N.

There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determinemore » whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.« less

Bullying Victimization and Perpetration and Their Correlates in Adolescents Clinically Diagnosed With ADHD.

PubMed

Chou, Wen-Jiun; Liu, Tai-Ling; Yang, Pinchen; Yen, Cheng-Fang; Hu, Huei-Fan

2018-01-01

To examine the prevalence rates of bullying involvement and their correlates in adolescents diagnosed with ADHD in Taiwan. Bullying involvement, family and ADHD characteristics, the levels of behavioral inhibition system (BIS) and behavioral approach system (BAS), and psychiatric comorbidity were assessed in 287 adolescents with ADHD. The multiple regression analysis was used to examine the correlate of bullying victimization and perpetration. The prevalence rates of the pure victims, pure perpetrators, and victim-perpetrators were 14.6%, 8.4%, and 5.6%, respectively. Young age, a high BIS score, autism spectrum disorders, and low satisfaction with family relationships were associated with severe bullying victimization. A high score of fun seeking on the BAS and low satisfaction with family relationships were associated with severe bullying perpetration. A high proportion of adolescents with ADHD are involved in bullying. Multiple factors are associated with bullying involvement in adolescents with ADHD.

DGCA: A comprehensive R package for Differential Gene Correlation Analysis.

PubMed

McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min; Wang, Minghui; Zhang, Bin

2016-11-15

Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC). DGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells.

PubMed

Xie, Fang-Fei; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Hong; Wu, Jian; Guo, Yu-Fan; Zeng, Ke-Qin; Wang, Ming-Jun; Zhu, Xiao-Wei; Xia, Wei; Wang, Lan; He, Pei; Bing, Peng-Fei; Lu, Xin; Zhang, Yong-Hong; Lei, Shu-Feng

2018-01-01

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (r T1 ) between methylation level and mRNA is moderate (-0.63-0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at P < 0.05 and more than 5.96% genes presented very strong correlation (R T4  > 0.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

A meta-analysis of multiple myeloma risk regions in African and European ancestry populations identifies putatively functional loci

PubMed Central

Rand, Kristin A.; Song, Chi; Dean, Eric; Serie, Daniel J.; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H.; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S.; Bock, Cathryn H.; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K.; V.Conti, David; Zimmerman, Todd; Hwang, Amie E.; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L.; Berndt, Sonja I.; Blot, William J.; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W. Ryan; Stevens, Victoria L.; Lieber, Michael R.; Goodman, Phyllis J.; Hennis, Anselm J.M.; Hsing, Ann W.; Mehta, Jayesh; Kittles, Rick A.; Kolb, Suzanne; Klein, Eric A.; Leske, Cristina; Murphy, Adam B.; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S.; Vij, Ravi; Rybicki, Benjamin A.; Stanford, Janet L.; Signorello, Lisa B.; Witte, John S.; Ambrosone, Christine B.; Bhatti, Parveen; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F.; Hu, Jennifer J.; Ziegler, Regina G.; Nyante, Sarah J.; Bandera, Elisa V.; Birmann, Brenda M.; Ingles, Sue A.; Press, Michael F.; Atanackovic, Djordje; Glenn, Martha J.; Cannon-Albright, Lisa A.; Jones, Brandt; Tricot, Guido; Martin, Thomas G.; Kumar, Shaji K.; Wolf, Jeffrey L.; Deming, Sandra L.; Rothman, Nathaniel; Brooks-Wilson, Angela R.; Rajkumar, S. Vincent; Kolonel, Laurence N.; Chanock, Stephen J.; Slager, Susan L.; Severson, Richard K.; Janakiraman, Nalini; Terebelo, Howard R.; Brown, Elizabeth E.; De Roos, Anneclaire J.; Mohrbacher, Ann F.; Colditz, Graham A.; Giles, Graham G.; Spinelli, John J.; Chiu, Brian C.; Munshi, Nikhil C.; Anderson, Kenneth C.; Levy, Joan; Zonder, Jeffrey A.; Orlowski, Robert Z.; Lonial, Sagar; Camp, Nicola J.; Vachon, Celine M.; Ziv, Elad; Stram, Daniel O.; Hazelett, Dennis J.; Haiman, Christopher A.; Cozen, Wendy

2017-01-01

Background Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM). Methods We performed association testing of common variation in eight regions in 1,264 MM patients and 1,479 controls of European ancestry (EA) and 1,305 MM patients and 7,078 controls of African ancestry (AA) and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (p<0.05) associated with MM risk in AAs and EAs and the variant in 3p22.1 was associated in EAs only. In a combined AA-EA meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically signficantly associated with MM risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR=1.32, p=2.93×10−7) in TNFRSF13B, encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions We found that reported MM susceptibility regions contain risk variants important across populations supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact A subset of reported risk loci for multiple myeloma have consistent affects across populations and are likely to be functional. PMID:27587788

Relationships between locus of control and paranormal beliefs.

PubMed

Newby, Robert W; Davis, Jessica Boyette

2004-06-01

The present study investigated the associations between scores on paranormal beliefs, locus of control, and certain psychological processes such as affect and cognitions as measured by the Linguistic Inquiry and Word Count. Analysis yielded significant correlations between scores on Locus of Control and two subscales of Tobacyk's (1988) Revised Paranormal Beliefs Scale, New Age Philosophy and Traditional Paranormal Beliefs. A step-wise multiple regression analysis indicated that Locus of Control was significantly related to New Age Philosophy. Other correlations were found between Tobacyk's subscales, Locus of Control, and three processes measured by the Linguistic Inquiry and Word Count.

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Performance analysis of multiple PRF technique for ambiguity resolution

NASA Technical Reports Server (NTRS)

Chang, C. Y.; Curlander, J. C.

1992-01-01

For short wavelength spaceborne synthetic aperture radar (SAR), ambiguity in Doppler centroid estimation occurs when the azimuth squint angle uncertainty is larger than the azimuth antenna beamwidth. Multiple pulse recurrence frequency (PRF) hopping is a technique developed to resolve the ambiguity by operating the radar in different PRF's in the pre-imaging sequence. Performance analysis results of the multiple PRF technique are presented, given the constraints of the attitude bound, the drift rate uncertainty, and the arbitrary numerical values of PRF's. The algorithm performance is derived in terms of the probability of correct ambiguity resolution. Examples, using the Shuttle Imaging Radar-C (SIR-C) and X-SAR parameters, demonstrate that the probability of correct ambiguity resolution obtained by the multiple PRF technique is greater than 95 percent and 80 percent for the SIR-C and X-SAR applications, respectively. The success rate is significantly higher than that achieved by the range cross correlation technique.

Development and validation of a patient self-assessed questionnaire on satisfaction with communication of the multiple sclerosis diagnosis.

PubMed

Solari, A; Mattarozzi, K; Vignatelli, L; Giordano, A; Russo, P M; Uccelli, M Messmer; D'Alessandro, R

2010-10-01

We describe the development and clinical validation of a patient self-administered tool assessing the quality of multiple sclerosis diagnosis disclosure. A multiple sclerosis expert panel generated questionnaire items from the Doctor's Interpersonal Skills Questionnaire, literature review, and interviews with neurology inpatients. The resulting 19-item Comunicazione medico-paziente nella Sclerosi Multipla (COSM) was pilot tested/debriefed on seven patients with multiple sclerosis and administered to 80 patients newly diagnosed with multiple sclerosis. The resulting revised 20-item version (COSM-R) was debriefed on five patients with multiple sclerosis, field tested/debriefed on multiple sclerosis patients, and field tested on 105 patients newly diagnosed with multiple sclerosis participating in a clinical trial on an information aid. The hypothesized monofactorial structure of COSM-R section 2 was tested on the latter two groups. The questionnaire was well accepted. Scaling assumptions were satisfactory in terms of score distributions, item-total correlations and internal consistency. Factor analysis confirmed section 2's monofactorial structure, which was also test-retest reliable (intraclass correlation coefficient [ICC] 0.73; 95% CI 0.54-0.85). Section 1 had only fair test-retest reliability (ICC 0.45; 95% CI 0.12-0.69), and three items had 8-21% missed responses. COSM-R is a brief, easy-to-interpret MS-specific questionnaire for use as a health care indicator.

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Spiritual Well-Being and Its Relationship with Mindfulness, Self-Compassion and Satisfaction with Life in Baccalaureate Nursing Students: A Correlation Study.

PubMed

Mathad, Monali D; Rajesh, S K; Pradhan, Balaram

2017-12-06

The present study aimed to explore the correlates and predictors of spiritual well-being among nursing students. One hundred and forty-five BSc nursing students were recruited from three nursing colleges in Bangalore, Karnataka, India. Data were collected using SHALOM, FMI, SCS-SF and SWLS questionnaires and analysed by the Pearson correlation test and multiple regression analysis. The results of our study revealed a significant correlation between variables, and a considerable amount of variance was explained by self-compassion, mindfulness and satisfaction with life on personal, communal, environmental and transcendental domains of spiritual well-being.

Monte Carlo simulation of parameter confidence intervals for non-linear regression analysis of biological data using Microsoft Excel.

PubMed

Lambert, Ronald J W; Mytilinaios, Ioannis; Maitland, Luke; Brown, Angus M

2012-08-01

This study describes a method to obtain parameter confidence intervals from the fitting of non-linear functions to experimental data, using the SOLVER and Analysis ToolPaK Add-In of the Microsoft Excel spreadsheet. Previously we have shown that Excel can fit complex multiple functions to biological data, obtaining values equivalent to those returned by more specialized statistical or mathematical software. However, a disadvantage of using the Excel method was the inability to return confidence intervals for the computed parameters or the correlations between them. Using a simple Monte-Carlo procedure within the Excel spreadsheet (without recourse to programming), SOLVER can provide parameter estimates (up to 200 at a time) for multiple 'virtual' data sets, from which the required confidence intervals and correlation coefficients can be obtained. The general utility of the method is exemplified by applying it to the analysis of the growth of Listeria monocytogenes, the growth inhibition of Pseudomonas aeruginosa by chlorhexidine and the further analysis of the electrophysiological data from the compound action potential of the rodent optic nerve. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed

Palmer, M; Belch, A; Hanson, J; Brox, L

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed Central

Palmer, M.; Belch, A.; Hanson, J.; Brox, L.

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose. PMID:2757916

The relationship between vascular endothelial dysfunction and treatment frequency in neovascular age-related macular degeneration.

PubMed

Ueda-Consolvo, Tomoko; Hayashi, Atsushi; Ozaki, Mayumi; Nakamura, Tomoko; Yagou, Takaaki; Abe, Shinya

2017-07-01

To assess the correlation between endothelial dysfunction and frequency of antivascular endothelial growth factor (anti-VEGF) treatment for neovascular age-related macular degeneration (nAMD). We examined 64 consecutive patients with nAMD who were evaluated for endothelial function by use of peripheral arterial tonometry (EndoPAT 2000; Itamar Medical, Caesarea, Israel) at Toyama University Hospital from January 2015. We tallied the number of anti-VEGF treatments between January 2014 and December 2015 and determined the correlation between the number of anti-VEGF injections and endothelial function expressed as the reactive hyperemia index (RHI). Multiple regression analysis was also performed to identify the independent predictors of a larger number of injections. The mean number of anti-VEGF injections was 8.2 ± 3.3. The mean lnRHI was 0.47 ± 0.17. The lnRHI correlated with the number of anti-VEGF injections (r = -0.56; P = 0.030). The multiple regression analysis revealed that endothelial function, neovascular subtypes, and treatment regimens were associated with the number of injections. Endothelial dysfunction may affect the efficacy of anti-VEGF therapy. Neovascular subtypes may also predict a larger number of injections.

Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis

PubMed Central

2017-01-01

Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models. PMID:29392175

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

Alteration of Multiple Leukocyte Gene Expression Networks is Linked with Magnetic Resonance Markers of Prognosis After Acute ST-Elevation Myocardial Infarction.

PubMed

Teren, A; Kirsten, H; Beutner, F; Scholz, M; Holdt, L M; Teupser, D; Gutberlet, M; Thiery, J; Schuler, G; Eitel, I

2017-02-03

Prognostic relevant pathways of leukocyte involvement in human myocardial ischemic-reperfusion injury are largely unknown. We enrolled 136 patients with ST-elevation myocardial infarction (STEMI) after primary angioplasty within 12 h after onset of symptoms. Following reperfusion, whole blood was collected within a median time interval of 20 h (interquartile range: 15-25 h) for genome-wide gene expression analysis. Subsequent CMR scans were performed using a standard protocol to determine infarct size (IS), area at risk (AAR), myocardial salvage index (MSI) and the extent of late microvascular obstruction (lateMO). We found 398 genes associated with lateMO and two genes with IS. Neither AAR, nor MSI showed significant correlations with gene expression. Genes correlating with lateMO were strongly related to several canonical pathways, including positive regulation of T-cell activation (p = 3.44 × 10 -5 ), and regulation of inflammatory response (p = 1.86 × 10 -3 ). Network analysis of multiple gene expression alterations associated with larger lateMO identified the following functional consequences: facilitated utilisation and decreased concentration of free fatty acid, repressed cell differentiation, enhanced phagocyte movement, increased cell death, vascular disease and compensatory vasculogenesis. In conclusion, the extent of lateMO after acute, reperfused STEMI correlated with altered activation of multiple genes related to fatty acid utilisation, lymphocyte differentiation, phagocyte mobilisation, cell survival, and vascular dysfunction.

Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P

2017-03-01

The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous measurement of cerebral blood flow and mRNA signals: pixel-based inter-modality correlational analysis.

PubMed

Zhao, W; Busto, R; Truettner, J; Ginsberg, M D

2001-07-30

The analysis of pixel-based relationships between local cerebral blood flow (LCBF) and mRNA expression can reveal important insights into brain function. Traditionally, LCBF and in situ hybridization studies for genes of interest have been analyzed in separate series. To overcome this limitation and to increase the power of statistical analysis, this study focused on developing a double-label method to measure local cerebral blood flow (LCBF) and gene expressions simultaneously by means of a dual-autoradiography procedure. A 14C-iodoantipyrine autoradiographic LCBF study was first performed. Serial brain sections (12 in this study) were obtained at multiple coronal levels and were processed in the conventional manner to yield quantitative LCBF images. Two replicate sections at each bregma level were then used for in situ hybridization. To eliminate the 14C-iodoantipyrine from these sections, a chloroform-washout procedure was first performed. The sections were then processed for in situ hybridization autoradiography for the probes of interest. This method was tested in Wistar rats subjected to 12 min of global forebrain ischemia by two-vessel occlusion plus hypotension, followed by 2 or 6 h of reperfusion (n=4-6 per group). LCBF and in situ hybridization images for heat shock protein 70 (HSP70) were generated for each rat, aligned by disparity analysis, and analyzed on a pixel-by-pixel basis. This method yielded detailed inter-modality correlation between LCBF and HSP70 mRNA expressions. The advantages of this method include reducing the number of experimental animals by one-half; and providing accurate pixel-based correlations between different modalities in the same animals, thus enabling paired statistical analyses. This method can be extended to permit correlation of LCBF with the expression of multiple genes of interest.

Regional gray matter atrophy in relapsing remitting multiple sclerosis: baseline analysis of multi-center data.

PubMed

Datta, Sushmita; Staewen, Terrell D; Cofield, Stacy S; Cutter, Gary R; Lublin, Fred D; Wolinsky, Jerry S; Narayana, Ponnada A

2015-03-01

Regional gray matter (GM) atrophy in multiple sclerosis (MS) at disease onset and its temporal variation can provide objective information regarding disease evolution. An automated pipeline for estimating atrophy of various GM structures was developed using tensor based morphometry (TBM) and implemented on a multi-center sub-cohort of 1008 relapsing remitting MS (RRMS) patients enrolled in a Phase 3 clinical trial. Four hundred age and gender matched healthy controls were used for comparison. Using the analysis of covariance, atrophy differences between MS patients and healthy controls were assessed on a voxel-by-voxel analysis. Regional GM atrophy was observed in a number of deep GM structures that included thalamus, caudate nucleus, putamen, and cortical GM regions. General linear regression analysis was performed to analyze the effects of age, gender, and scanner field strength, and imaging sequence on the regional atrophy. Correlations between regional GM volumes and expanded disability status scale (EDSS) scores, disease duration (DD), T2 lesion load (T2 LL), T1 lesion load (T1 LL), and normalized cerebrospinal fluid (nCSF) were analyzed using Pearson׳s correlation coefficient. Thalamic atrophy observed in MS patients compared to healthy controls remained consistent within subgroups based on gender and scanner field strength. Weak correlations between thalamic volume and EDSS (r=-0.133; p<0.001) and DD (r=-0.098; p=0.003) were observed. Of all the structures, thalamic volume moderately correlated with T2 LL (r=-0.492; P-value<0.001), T1 LL (r=-0.473; P-value<0.001) and nCSF (r=-0.367; P-value<0.001). Copyright © 2015 Elsevier B.V. All rights reserved.

A reduced factor structure for the PROQOL-HIV questionnaire provided reliable indicators of health-related quality of life.

PubMed

Lalanne, Christophe; Chassany, Olivier; Carrieri, Patrizia; Marcellin, Fabienne; Armstrong, Andrew R; Lert, France; Spire, Bruno; Dray-Spira, Rosemary; Duracinsky, Martin

2016-04-01

To identify a simplified factor structure for the PROQOL-human immunodeficiency virus (HIV) questionnaire to improve the measurement of the health-related quality of life (HRQL) of HIV-positive patients in clinical care and research settings. HRQL data were collected using the eight-dimension PROQOL-HIV questionnaire from 2,537 patients (VESPA2 study). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) validated a simpler four-factor structure and assessed measurement invariance (MI). Multigroup analysis assessed the effect of sex, age, and antiretroviral therapy (ART) on the resulting factor scores. Correlations with symptom and Short Form (SF)-12 self-reports assessed convergent validity. Item analysis, EFA, and CFAs confirmed the validity [comparative fit index (CFI), 0.948; root mean square error of approximation, 0.064] and reliability (α's ≥ 0.8) of four dimensions: physical health and symptoms, health concerns and mental distress, social and intimate relationships, and treatment-related impact. Strong MI was demonstrated across sex and age (decrease in CFI <0.01). A multiple-cause multiple-indicator model indicated that HRQL correlated as expected with sex, age, and the ART status. Correlations of HRQL, symptom reports, and SF-12 scores evidenced convergent validity criterion. The simplified factor structure and scoring scheme for PROQOL-HIV will allow clinicians to monitor with greater reliability the HRQL of patients in clinical care and research settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

PubMed

Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

2018-07-01

Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whereas MMSE at threshold <25/30 appeared to have the best true negative rate. The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Multiple heteroatom substitution to graphene nanoribbon

PubMed Central

Meyer, Ernst

2018-01-01

Substituting heteroatoms into nanostructured graphene elements, such as graphene nanoribbons, offers the possibility for atomic engineering of electronic properties. To characterize these substitutions, functionalized atomic force microscopy (AFM)—a tool to directly resolve chemical structures—is one of the most promising tools, yet the chemical analysis of heteroatoms has been rarely performed. We synthesized multiple heteroatom-substituted graphene nanoribbons and showed that AFM can directly resolve elemental differences and can be correlated to the van der Waals radii, as well as the modulated local electron density caused by the substitution. This elemental-sensitive measurement takes an important step in the analysis of functionalized two-dimensional carbon materials. PMID:29662955

Quality of life among people with multiple sclerosis: Replication of a three-factor prediction model.

PubMed

Bishop, Malachy; Rumrill, Phillip D; Roessler, Richard T

2015-01-01

This article presents a replication of Rumrill, Roessler, and Fitzgerald's 2004 analysis of a three-factor model of the impact of multiple sclerosis (MS) on quality of life (QOL). The three factors in the original model included illness-related, employment-related, and psychosocial adjustment factors. To test hypothesized relationships between QOL and illness-related, employment-related, and psychosocial variables using data from a survey of the employment concerns of Americans with MS (N = 1,839). An ex post facto, multiple correlational design was employed incorporating correlational and multiple regression analyses. QOL was positively related to educational level, employment status, job satisfaction, and job-match, and negatively related to number of symptoms, severity of symptoms, and perceived stress level. The three-factor model explained approximately 37 percent of the variance in QOL scores. The results of this replication confirm the continuing value of the three-factor model for predicting the QOL of adults with MS, and demonstrate the importance of medical, mental health, and vocational rehabilitation interventions and services in promoting QOL.

Science Teaching Efficacy of Preservice Elementary Teachers: Examination of the Multiple Factors Reported as Influential

NASA Astrophysics Data System (ADS)

Taştan Kırık, Özgecan

2013-12-01

This study explores the science teaching efficacy beliefs of pr-service elementary teachers and the relationship between efficacy beliefs and multiple factors such as antecedent factors (participation in extracurricular activities and number of science and science teaching methods courses taken), conceptual understanding, classroom management beliefs and science teaching attitudes. Science education majors ( n = 71) and elementary education majors ( n = 262) were compared with respect to these variables. Finally, the predictors of two constructs of science teaching efficacy beliefs, personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE), were examined by multiple linear regression analysis. According to the results, participation in extracurricular activities has a significant but low correlation with science concept knowledge, science teaching attitudes, PSTE and STOE. In addition, there is a small but significant correlation between science concept knowledge and outcome expectancy, which leads the idea that preservice elementary teachers' conceptual understanding in science contributes to their science teaching self-efficacy. This study reveals a moderate correlation between science teaching attitudes and STOE and a high correlation between science teaching attitudes and PSTE. Additionally, although the correlation coefficient is low, the number of methodology courses was found to be one of the correlates of science teaching attitudes. Furthermore, students of both majors generally had positive self-efficacy beliefs on both the STOE and PSTE. Specifically, science education majors had higher science teaching self-efficacy than elementary education majors. Regression results showed that science teaching attitude is the major factor in predicting both PSTE and STOE for both groups.

Which symptoms contribute the most to patients' perception of health in multiple sclerosis?

PubMed

Green, Rivka; Cutter, Gary; Friendly, Michael; Kister, Ilya

2017-01-01

Multiple sclerosis is a polysymptomatic disease. Little is known about relative contributions of the different multiple sclerosis symptoms to self-perception of health. To investigate the relationship between symptom severity in 11 domains affected by multiple sclerosis and self-rated health. Multiple sclerosis patients in two multiple sclerosis centers assessed self-rated health with a validated instrument and symptom burden with symptoMScreen, a validated battery of Likert scales for 11 domains commonly affected by multiple sclerosis. Pearson correlations and multivariate linear regressions were used to investigate the relationship between symptoMScreen scores and self-rated health. Among 1865 multiple sclerosis outpatients (68% women, 78% with relapsing-remitting multiple sclerosis, mean age 46.38 ± 12.47 years, disease duration 13.43 ± 10.04 years), average self-rated health score was 2.30 ('moderate to good'). Symptom burden (composite symptoMScreen score) highly correlated with self-rated health ( r  = 0.68, P  < 0.0001) as did each of the symptoMScreen domain subscores. In regression analysis, pain ( t  = 7.00), ambulation ( t  = 6.91), and fatigue ( t  = 5.85) contributed the highest amount of variance in self-rated health ( P  < 0.001). Pain contributed the most to multiple sclerosis outpatients' perception of health, followed by gait dysfunction and fatigue. These findings suggest that 'invisible disability' may be more important to patients' sense of wellbeing than physical disability, and challenge the notion that physical disability should be the primary outcome measure in multiple sclerosis.

Assessment of Comprehensive Analysis Calculation of Airloads on Helicopter Rotors

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Johnson, Wayne

2004-01-01

Blade section normal force and pitching moment were investigated for six rotors operating at transition and high speeds: H-34 in flight and wind tunnel, SA 330 (research Puma), SA 349/2, UH-60A full-scale and BO-105 model (HART-I). The measured data from flight and wind tunnel tests were compared with calculations obtained using the comprehensive analysis CAMRAD II. The calculations were made using two free wake models: rolled-up and multiple-trailer with consolidation models. At transition speed, there is fair to good agreement for the blade section normal force between the test data and analysis for the H-34, research Puma, and SA 349/2 with the rolled-up wake. The calculated airloads differ significantly from the measurements for the UH-60A and BO-105. Better correlation is obtained for the UH-60A and BO-105 by using the multiple-trailer with consolidation wake model. In the high speed condition, the analysis shows generally good agreement with the research Puma flight data in both magnitude and phase. However, poor agreement is obtained for the other rotors examined. The analysis shows that the aerodynamic tip design (chord length and quarter chord location) of the Puma has an important influence on the phase correlation.

Improvement of the air quality in student health centers with chlorine dioxide.

PubMed

Hsu, Ching-Shan; Huang, Da-Ji; Lu, Ming-Chun

2010-04-01

This study aims to monitor bioaerosol levels of a local campus of a student health center in Taiwan and then to perform disinfection by applying chlorine dioxide. First, air samples were taken and evaluated in the six areas of the center. The average background bioaerosol levels were 714 +/- 1706 CFU/m(3) for bacterium and 802 +/- 633 CFU/m(3) for fungi. Then, chlorine dioxide was applied through three different procedures: single, multiple and regular disinfections. The results indicated that both multiple and regular disinfections can achieve efficiency levels higher than 59.0%. The regression analysis on bioaerosol levels showed that the number of people present correlating to the number of persons entering the room per door-opening, had a correlation of p < 0.05. Utilizing this analysis result, an empirical model was developed to predict indoor bioaerosol concentrations. It can be inferred that for indoor human activity of health centers, regular disinfection is a very effective process.

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.

Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

2016-11-01

Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

The correlation between symptomatic fatigue to definite measures of gait in people with multiple sclerosis.

PubMed

Kalron, Alon

2016-02-01

There is a general consensus relating to the multidimensional aspects of fatigue in people with multiple sclerosis (PwMS), however, the exact impact of this symptom on gait is not fully understood. Our primary aim was to examine the relationship between definite parameters of gait with self-reported symptomatic fatigue in PwMS according to their level of neurological impairment. Spatio-temporal parameters of gait were studied using an electronic walkway. The Multiple Sclerosis Walking Scale (MSWS-12) questionnaire, a patient-rated measure of walking ability was collected. The Modified Fatigue Impact Scale (MFIS) questionnaire was used to determine the level of symptomatic fatigue. One hundred and one PwMS (61 women) were included in the study analysis. Subjects were divided into mild and moderate neurological impaired groups. Fatigue was correlated with 5 (out of 14) spatiotemporal parameters. However, correlation scores were all <0.35, thus considered as weak correlations. In the mild group, the double support period was the only variable positively correlated to fatigue (Spearman's rho=0.28, P=0.05). In the moderate group, step and stride length were solely negatively correlated to fatigue (Spearman's rho=0.32, P=0.03). In contrast to the definite gait parameters, the MSWS-12 self-questionnaire was moderately positively correlated to the level of fatigue. Scores for the total, mild and moderate groups were 0.54, 0.57 and 0.51; P<0.01, respectively. The present results indicate that modifications in spatio-temporal parameters of gait are not closely related to symptomatic fatigue in PwMS. On the contrary, the self-reported MSWS-12 questionnaire is predisposed to level of fatigue in PwMS. Copyright © 2015 Elsevier B.V. All rights reserved.

Association between retinal nerve fiber layer thickness and magnetic resonance imaging findings and intelligence in patients with multiple sclerosis.

PubMed

Ashtari, Fereshteh; Emami, Parisa; Akbari, Mojtaba

2015-01-01

Multiple Sclerosis (MS) is a neurological disease in which demyelination and axonal loss leads to progressive disability. Cognition impairment is among the most common complication. Studying axonal loss in the retina is a new marker for MS. The main goal of our study is to search for correlations between magnetic resonance imaging (MRI) findings and the retinal nerve fiber layer (RNFL) thickness at the macula and head of the optic nerve and Wechsler Adult Intelligence Scale-Revised (WAIS-R) Scores that assess multiple domains of intelligence, and to explore the relationship between changes in the RNFL thickness with intellectual and cognitive dysfunction. A prospective cross-sectional study was conducted at the University Hospital of Kashani, Isfahan, Iran, from September to December 2013. All patients were assessed with a full-scale intelligence quotient (IQ) on the WAIS-R. An optical coherence tomography study and brain MRI were performed in the same week for all the patients. Statistical analysis was conducted by using a bivariate correlation, by utilizing SPSS 20.0. A P value ≤ 0.05 was the threshold of statistical significance. Examination of a 100 patients showed a significant correlation between the average RNFL thickness of the macula and the verbal IQ (P value = 0.01) and full IQ (P value = 0.01). There was a significant correlation between brain atrophy and verbal IQ. The RNFL loss was correlated with verbal IQ and full IQ.

Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: a voxel-based analysis study.

PubMed

Mallik, Shahrukh; Muhlert, Nils; Samson, Rebecca S; Sethi, Varun; Wheeler-Kingshott, Claudia A M; Miller, David H; Chard, Declan T

2015-04-01

In multiple sclerosis (MS), demyelination and neuro-axonal loss occur in the brain grey matter (GM). We used magnetic resonance imaging (MRI) measures of GM magnetisation transfer ratio (MTR) and volume to assess the regional localisation of reduced MTR (reflecting demyelination) and atrophy (reflecting neuro-axonal loss) in relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). A total of 98 people with MS (51 RRMS, 28 SPMS, 19 PPMS) and 29 controls had T1-weighted volumetric and magnetisation transfer scans. SPM8 was used to undertake voxel-based analysis (VBA) of GM tissue volumes and MTR. MS subgroups were compared with controls, adjusting for age and gender. A voxel-by-voxel basis correlation analysis between MTR and volume within each subject group was performed, using biological parametric mapping. MTR reduction was more extensive than atrophy. RRMS and SPMS patients showed proportionately more atrophy in the deep GM. SPMS and PPMS patients showed proportionately greater cortical MTR reduction. RRMS patients demonstrated the most correlation of MTR reduction and atrophy in deep GM. In SPMS and PPMS patients, there was less extensive correlation. These results suggest that in the deep GM of RRMS patients, demyelination and neuro-axonal loss may be linked, while in SPMS and PPMS patients, neuro-axonal loss and demyelination may occur mostly independently. © The Author(s), 2014.

Decision making of heavy cannabis users on the Iowa Gambling Task: stronger association with THC of hair analysis than with personality traits of the Tridimensional Personality Questionnaire.

PubMed

Hermann, Derik; Leménager, Tagrid; Gelbke, Jan; Welzel, Helga; Skopp, Gisela; Mann, Karl

2009-01-01

It is unclear whether impairment in decision making, measured by the Iowa Gambling Task (IGT), in addiction is substance-induced or the consequence of personality structure. Analysis of the IGT, the Tridimensional Personality Questionnaire (TPQ) and cannabinoids in hair and urine were performed in 13 cannabis users and matched controls. Hair Delta(9)-tetrahydrocannabinol (THC) correlated negatively with the last subtrial (cards 80-100) of the IGT (R = -0.67). In all participants (n = 26) the TPQ dimension, harm avoidance, correlated negatively with the total IGT score (R = -0.46). The last IGT-subtrial correlated with adventure seeking (R = 0.43), harm avoidance (R = -0.39) and reward dependence (R = -0.44). The last subtrial gives information on whether a participant has learned the IGT strategy. Multiple regression confirmed the impact of THC on the last subtrial, whereas TPQ personality traits did not additionally explain variance. Former indications of the IGT performance depending on the amount of cannabis consumed were replicated with an objective measurement of chronic cannabis consumption (hair THC). Multiple regression analysis argues for a stronger impact of chronic THC consumption than personality traits, but does not provide a causal relationship. Other factors (e.g. genetic) may also play a role. 2009 S. Karger AG, Basel.

What Influences How Patients Rate Their Hospital After Total Knee Arthroplasty?

PubMed

Chughtai, Morad; Jauregui, Julio J; Mistry, Jaydev B; Elmallah, Randa K; Diedrich, Aloise M; Bonutti, Peter M; Delanois, Ronald; Mont, Michael A

2016-04-01

There is increasing pressure from Centers for Medicare and Medicaid Services (CMS) to report quality measures for all hospitalizations. These quality measures are determined based on results from satisfaction surveys, such as Press Ganey® (PG) (Press Ganey® Performance Solutions, Wakefield, Massachusetts). Included in this particular survey element are questions regarding staff, including nurses and doctors, as well as items such as pain control. The results of these surveys will dictate the amount doctors are compensated for their services. Therefore, this study was undertaken to evaluate the effect of treating orthopaedists and nurses, as well as pain control, on PG surveys in patients who underwent total knee arthroplasty (TKA). Specifically, we aimed to ascertain the effect of these factors on how post-TKA patients perceive: 1) their orthopaedist, and 2) their overall surgical experience. We queried the Press Ganey® Database for all patients who underwent a TKA at our institution between November 2009 and January 2015. A weighted mean of question domains was utilized since each had multiple questions. In order to assess if pain management influences orthopaedist perception, a correlation analysis was performed between pain control and perception. In order to assess the influence of pain management on surgical experience, we performed a correlation analysis between pain control and overall hospital rating. A multiple regression analysis was performed using the hospital rating as the dependent variable to determine the most influential factors on surgical experience. Our analysis demonstrated a significantly positive correlation between patient perception of their pain control and their orthopaedist. There was a significant positive correlation between patient's perception of their pain control and their overall surgical experience. Multiple regression analysis using overall surgical experience as the dependent variable demonstrated a significant positive influence of perception of nurses and orthopaedists. Pain management positively influenced surgical experience; however, this was not significant. We found that perception of pain control in post-TKA patients affects perception of the treating orthopaedists, as well as their overall surgical experience. In addition, perception of orthopaedists and nurses both outweigh perception of pain control on overall surgical experience, with nurses being the most important. Orthopaedists should focus on staff education-particularly nurses-and educate them in order to optimize results on PG surveys and, ultimately, improve patient satisfaction. Further studies should correlate current standardized scoring systems and questionnaires for TKA with PG surveys in order to recognize gaps that need to be bridged to improve post-TKA patient satisfaction.

A Novel Multiple-Access Correlation-Delay-Shift-Keying

NASA Astrophysics Data System (ADS)

Duan, J. Y.; Jiang, G. P.; Yang, H.

In Correlation-Delay-Shift-Keying (CDSK), the reference signal and the information-bearing signal are added together during a certain time delay. Because the reference signal is not strictly orthogonal to the information-bearing signal, the cross-correlation between the adjacent chaotic signal (Intra-signal Interference, ISI) will be introduced into the demodulation at the receiver. Therefore, the Bit-Error Ratio (BER) of CDSK is higher than that of Differential-Chaos-Shift-Keying (DCSK). To avoid the ISI component and enhance the BER performance of CDSK in multiuser scenario, Multiple-Access CDSK with No Intra-signal Interference (MA-CDSK-NII) is proposed. By constructing the repeated chaotic generator and applying the Walsh code sequence to modulate the reference signal, in MA-CDSK-NII, the ISI component will be eliminated during the demodulation. Gaussian approximation method is adopted here to obtain the exact performance analysis of MA-CDSK-NII over additive white Gaussian noise (AWGN) channel and Rayleigh multipath fading channels. Results show that, due to no ISI component and lower transmitting power, the BER performance of MA-CDSK-NII can be better than that of multiple-access CDSK and Code-Shifted Differential-Chaos-Shift-Keying (CS-DCSK).

The effects of texting on driving performance in a driving simulator: the influence of driver age.

PubMed

Rumschlag, Gordon; Palumbo, Theresa; Martin, Amber; Head, Doreen; George, Rajiv; Commissaris, Randall L

2015-01-01

Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18-59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While 'driving' the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N=50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N=27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N=23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that 'no texting while driving' education and public service messages need to be continued, and they should be expanded to target older drivers as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

[A Correlational Study of the Recovery Process in Patients With Mental Illness].

PubMed

Huang, Yao-Hui; Lin, Yao-Yu; Lee, Shih-Kai; Lee, Ming-Feng; Lin, Ching-Lan Esther

2018-04-01

The ideology of recovery addresses the autonomy of patients with mental illness and their ability to reconstruct a normal life. Empirical knowledge of this process of recovery and related factors remains unclear. To assess the process of recovery and related factors in patients with mental illness. This cross-sectional, correlational study was conducted on a convenience sample in a psychiatric hospital. Two-hundred and fifty patients with mental illness were recruited and were assessed using 3 instruments: Questionnaire about the Process of Recovery (QPR), Perceived Psychiatric Stigma Scale (PPSS), and Personal and Social Performance Scale (PSP). Data were analyzed using descriptive statistics, χ 2 , analysis of variance, and multiple linear regression analysis. Most of the participants were male, middle-aged, unmarried, educated to the senior high school level, employed, receiving home-care treatment, and diagnosed with schizophrenia. Those who were unemployed, living in a community rehabilitative house, and living in the community, respectively, earned relatively higher recovery scores (p < .05). The total scores of QPR and the 3 subscales were negatively correlated with PPSS (p < .01) and positively correlated with PSPS (p < .01; p < .05). Multiple regression analysis indicated that the factors of education, employment, having received community rehabilitative models, and stigma, respectively, significantly explained the recovery capacity of patients with mental illness. Community psychiatric nurses should provide care to help employed patients adapt to stresses in the workplace, strengthen their stigma-coping strategies, and promote public awareness of mental health issues by increasing public knowledge and acceptance of mental illness in order to minimize patient-perceived stigma and facilitate their recovery.

Population Analysis of Disabled Children by Departments in France

NASA Astrophysics Data System (ADS)

Meidatuzzahra, Diah; Kuswanto, Heri; Pech, Nicolas; Etchegaray, Amélie

2017-06-01

In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The PCA is the best method for interpretation of the correlation between the determinants of disability (independent variable). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 classes. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 classes.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

PubMed Central

Kalva-Filho, CA; Campos, EZ; Andrade, VL; Silva, ASR; Zagatto, AM; Lima, MCS

2015-01-01

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (CANA). The CANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of CANA) and blood lactate concentration analysis (lactic anaerobic contributions of CANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s-1) and LMS (1.3±0.1 m·s-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min-1; r = 0.72) and CANA (4.7±1.5 L·O2; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, CANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance. PMID:28479663

Study of Isospin Correlation in High Energy Heavy Ion Interactions with the RHIC PHENIX. Final Report

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

Takahashi, Y.

This report describes the research work performed under the support of the DOE research grant E-FG02-97ER4108. The work is composed of three parts: (1) Visual analysis and quality control of the Micro Vertex Detector (MVD) of the PHENIX experiments carried out of Brookhaven National Laboratory. (2) Continuation of the data analysis of the EMU05/09/16 experiments for the study of the inclusive particle production spectra and multi-particle correlation. (3) Exploration of a new statistical means to study very high-multiplicity of nuclear-particle ensembles and its perspectives to apply to the higher energy experiments.

Dimensions of self-leadership: a German replication and extension.

PubMed

Müller, Güonter F

2006-10-01

In a sample of 167 German students three dimensions of self-leadership, i.e., constructive thoughts, natural reward creation, and proactive behavior, were replicated as when scale values of a German self-leadership questionnaire were subjected to confirmatory factor analysis very satisfactory fit-indices were obtained. In addition, dimensions of self-leadership correlated with entrepreneurial trait disposition (multiple R=0.46, p < .01), and entrepreneurial job orientation (multiple R=0.23, p < .05). Conclusions for further research and practical applications are discussed.

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Familial occurrence of cervical artery dissection--coincidence or sign of familial predisposition?

PubMed

Grond-Ginsbach, Caspar; de Freitas, Gabriel R; Campos, Cynthia R; Thie, Andreas; Caso, Valeria; Machetanz, Jochen; Kloss, Manja

2012-01-01

BACKGROUNDAND PURPOSE: The etiology of spontaneous cervical artery dissection (CeAD) is poorly understood in most patients. Mild cervical trauma preceding the dissection event is a common finding, but many CeAD occur spontaneously. It is likely that genetic factors may increase the risk for CeAD. However, familial cases are excedingly rare. Familial clustering of CeAD may be accidental or associated with genetic or environmental risk factors shared between affected relatives. In this explorative study, we aim to show that specific risk factors for familial CeAD exist. Age of onset, sex, affected artery and number of recurrent CeAD were documented for familial patients and compared with published findings from patients with sporadic CeAD. Concordance of age, sex and dissected artery within the families was analyzed by correlation analysis and by analysis of variance or Kruskal-Wallis testing. The study sample consisted of 9 new patients with a family history of CeAD enrolled in the Neurology Department of the University of Heidelberg or referred to Heidelberg from other centers. The study sample also included published findings from another 23 patients, in total 32 patients. The mean age of the patients with familial CeAD at their first dissections was 38.4 ± 13.3 years. Twenty (62.5%) patients were female and 12 patients (37.5%) suffered multiple dissections. Four patients (12.5%) presented with recurrent dissections after >1 year. Patients with a familial history of CeAD were younger (p = 0.023) and presented more often with multiple dissections (p = 0.024) and recurrent dissections (p = 0.018). Age at the first event (correlation analysis p = 0.026; analysis of variance p = 0.029) and site of the dissection (correlation analysis p = 0.032; Kruskal-Wallis test p = 0.018) differed between the families, and there was no concordance of gender of affected family members (correlation analysis p = 0.500; Kruskal-Wallis test p = 0.211). The high prevalence of multiple dissection events and of long-term (>1 year) recurrent dissections in patients with a familial history of CeAD indicates that a specific predisposition for familial CeAD exists. Since age of onset and affected vessel differ between families, the risk profile for familial CeAD is heterogeneous. A large-scale (whole exome) sequencing analysis of 14 patients from 7 of the analyzed families is currently being performed in order to identify causative genetic variants. Copyright © 2012 S. Karger AG, Basel.

Separating twin images and locating the center of a microparticle in dense suspensions using correlations among reconstructed fields of two parallel holograms.

PubMed

Ling, Hangjian; Katz, Joseph

2014-09-20

This paper deals with two issues affecting the application of digital holographic microscopy (DHM) for measuring the spatial distribution of particles in a dense suspension, namely discriminating between real and virtual images and accurate detection of the particle center. Previous methods to separate real and virtual fields have involved applications of multiple phase-shifted holograms, combining reconstructed fields of multiple axially displaced holograms, and analysis of intensity distributions of weakly scattering objects. Here, we introduce a simple approach based on simultaneously recording two in-line holograms, whose planes are separated by a short distance from each other. This distance is chosen to be longer than the elongated trace of the particle. During reconstruction, the real images overlap, whereas the virtual images are displaced by twice the distance between hologram planes. Data analysis is based on correlating the spatial intensity distributions of the two reconstructed fields to measure displacement between traces. This method has been implemented for both synthetic particles and a dense suspension of 2 μm particles. The correlation analysis readily discriminates between real and virtual images of a sample containing more than 1300 particles. Consequently, we can now implement DHM for three-dimensional tracking of particles when the hologram plane is located inside the sample volume. Spatial correlations within the same reconstructed field are also used to improve the detection of the axial location of the particle center, extending previously introduced procedures to suspensions of microscopic particles. For each cross section within a particle trace, we sum the correlations among intensity distributions in all planes located symmetrically on both sides of the section. This cumulative correlation has a sharp peak at the particle center. Using both synthetic and recorded particle fields, we show that the uncertainty in localizing the axial location of the center is reduced to about one particle's diameter.

Leadership Styles and Organizational Performance: A Predictive Analysis

ERIC Educational Resources Information Center

Kieu, Hung Q.

2010-01-01

Leadership is critically important because it affects the health of the organization. Research has found that leadership is one of the most significant contributors to organizational performance. Expanding and replicating previous research, and focusing on the specific telecommunications sector, this study used multiple correlation and regression…

CROSS-SCALE CORRELATIONS AND THE DESIGN AND ANALYSIS OF AVIAN HABITAT SELECTION STUDIES

EPA Science Inventory

It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large ...

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Combining Results of Multiple Search Engines in Proteomics*

PubMed Central

Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

2013-01-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

The Influence of Carbon-Carbon Multiple Bonds on the Solvolyses of Tertiary Alkyl Halides: a Grunwald-Winstein Analysis

PubMed Central

Reis, Marina C.; Elvas-Leitão, Ruben; Martins, Filomena

2008-01-01

The influence of carbon-carbon multiple bonds on the solvolyses of 3-chloro-3-methylbutyne (1), 2-chloro-2-phenylpropane (2), 2-bromo-2-methyl-1-phenylpropane (3), 4-chloro-4-methyl-2-pentyne (4) and 2-chloro-2-methylbutane (5) is critically evaluated through the extended Grunwald-Winstein equation. Substrates 1, 3 and 5 lead to correlations with unexpected negative sensitivity, h, to changes in the aromatic ring parameter, I. It is claimed that I is not a pure parameter, reflecting also some solvent nucleophilicity, NOTs, character. In substrates 2 and 4 the possibility of rearside solvation is reduced due to steric hindrance and/or cation stabilization and the best found correlations involve only the solvent ionizing power, Y, and I. PMID:19325827

A Modified Double Multiple Nonlinear Regression Constitutive Equation for Modeling and Prediction of High Temperature Flow Behavior of BFe10-1-2 Alloy

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Shi, Jiamin; Wang, Wen; Liu, Yingying

2018-01-01

Constitutive analysis for hot working of BFe10-1-2 alloy was carried out by using experimental stress-strain data from isothermal hot compression tests, in a wide range of temperature of 1,023 1,273 K, and strain rate range of 0.001 10 s-1. A constitutive equation based on modified double multiple nonlinear regression was proposed considering the independent effects of strain, strain rate, temperature and their interrelation. The predicted flow stress data calculated from the developed equation was compared with the experimental data. Correlation coefficient (R), average absolute relative error (AARE) and relative errors were introduced to verify the validity of the developed constitutive equation. Subsequently, a comparative study was made on the capability of strain-compensated Arrhenius-type constitutive model. The results showed that the developed constitutive equation based on modified double multiple nonlinear regression could predict flow stress of BFe10-1-2 alloy with good correlation and generalization.

A Bayesian Poisson-lognormal Model for Count Data for Multiple-Trait Multiple-Environment Genomic-Enabled Prediction

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H.; Montesinos-López, José C.; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat

2017-01-01

When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. PMID:28364037

Frontal parenchymal atrophy measures in multiple sclerosis.

PubMed

Locatelli, Laura; Zivadinov, Robert; Grop, Attilio; Zorzon, Marino

2004-10-01

The aim of this study was to establish whether, in a cross-sectional study, the normalized measures of whole and regional brain atrophy correlate better with tests assessing the cognitive function than the absolute brain atrophy measures. The neuropsychological performances and disability have been assessed in 39 patients with relapsing-remitting multiple sclerosis (MS). T1- and T2-lesion load (LL) of total brain and frontal lobes (FLs) were measured using a reproducible semiautomated technique. The whole brain volume and the regional brain parenchymal volume (RBPV) of FLs were obtained using a computerized interactive program, which incorporates semiautomated and automated segmentation processes. Normalized measures of brain atrophy, i.e., brain parenchymal fraction (BPF) and regional brain parenchymal fraction (RBPF) of FLs, were calculated. The scan-rescan, inter- and intrarater coefficient of variation (COV) and intraclass correlation coefficient (ICC) have been estimated. The RBPF of FLs showed an acceptable level of reproducibility which ranged from 1.7% for intrarater variability to 3.2% for scan-rescan variability. The mean ICC was 0.88 (CI 0.82-0.93). The RBPF of FLs demonstrated stronger magnitudes of correlation with neuropsychological functioning, disability and quantitative MRI lesion measures than RBPV. These differences were statistically significant: P<0.001 for Stroop Color Word Interference test, P<0.001 for Paced Auditory Serial Addition Test, P=0.04 for Standard Raven Progressive Matrices, P=0.049 for Expanded Disability Status Scale, P=0.01 for T2-LL of FLs and P<0.001 for T1-LL of FLs. BPF demonstrated significant correlations with tests assessing cognitive functions, whereas BPAV did not. The correlation analysis results were supported by the results of multiple regression analysis which showed that only the normalized brain atrophy measures were associated with tests exploring the cognitive functions. These data suggest that RBPF is a reproducible and sensitive method for measuring frontal parenchymal atrophy. The normalized measures of whole and regional brain parenchymal atrophy should be preferred to absolute measures in future studies that correlate neuropsychological performances and brain atrophy measures in patients with MS.

Global Terrestrial Water Storage Changes and Connections to ENSO Events

NASA Astrophysics Data System (ADS)

Ni, Shengnan; Chen, Jianli; Wilson, Clark R.; Li, Jin; Hu, Xiaogong; Fu, Rong

2018-01-01

Improved data quality of extended record of the Gravity Recovery and Climate Experiment (GRACE) satellite gravity solutions enables better understanding of terrestrial water storage (TWS) variations. Connections of TWS and climate change are critical to investigate regional and global water cycles. In this study, we provide a comprehensive analysis of global connections between interannual TWS changes and El Niño Southern Oscillation (ENSO) events, using multiple sources of data, including GRACE measurements, land surface model (LSM) predictions and precipitation observations. We use cross-correlation and coherence spectrum analysis to examine global connections between interannual TWS changes and the Niño 3.4 index, and select four river basins (Amazon, Orinoco, Colorado, and Lena) for more detailed analysis. The results indicate that interannual TWS changes are strongly correlated with ENSO over much of the globe, with maximum cross-correlation coefficients up to 0.70, well above the 95% significance level ( 0.29) derived by the Monte Carlo experiments. The strongest correlations are found in tropical and subtropical regions, especially in the Amazon, Orinoco, and La Plata basins. While both GRACE and LSM TWS estimates show reasonably good correlations with ENSO and generally consistent spatial correlation patterns, notably higher correlations are found between GRACE TWS and ENSO. The existence of significant correlations in middle-high latitudes shows the large-scale impact of ENSO on the global water cycle.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Data Analysis Techniques for Physical Scientists

NASA Astrophysics Data System (ADS)

Pruneau, Claude A.

2017-10-01

Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.

The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom.

PubMed

Krüger, Melanie; Straube, Andreas; Eggert, Thomas

2017-01-01

In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.

Combining ultrasonography and noncontrast helical computerized tomography to evaluate Holmium laser lithotripsy

PubMed Central

Mi, Jia; Li, Jie; Zhang, Qinglu; Wang, Xing; Liu, Hongyu; Cao, Yanlu; Liu, Xiaoyan; Sun, Xiao; Shang, Mengmeng; Liu, Qing

2016-01-01

Abstract The purpose of the study was to establish a mathematical model for correlating the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) with the total energy of Holmium laser lithotripsy. In this study, from March 2013 to February 2014, 180 patients with single urinary calculus were examined using ultrasonography and NCHCT before Holmium laser lithotripsy. The calculus location and size, acoustic shadowing (AS) level, twinkling artifact intensity (TAI), and CT value were all documented. The total energy of lithotripsy (TEL) and the calculus composition were also recorded postoperatively. Data were analyzed using Spearman's rank correlation coefficient, with the SPSS 17.0 software package. Multiple linear regression was also used for further statistical analysis. A significant difference in the TEL was observed between renal calculi and ureteral calculi (r = –0.565, P < 0.001), and there was a strong correlation between the calculus size and the TEL (r = 0.675, P < 0.001). The difference in the TEL between the calculi with and without AS was highly significant (r = 0.325, P < 0.001). The CT value of the calculi was significantly correlated with the TEL (r = 0.386, P < 0.001). A correlation between the TAI and TEL was also observed (r = 0.391, P < 0.001). Multiple linear regression analysis revealed that the location, size, and TAI of the calculi were related to the TEL, and the location and size were statistically significant predictors (adjusted r2 = 0.498, P < 0.001). A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. PMID:27930563

A retrospective study: correlation of histologic inflammation in biopsy specimens of Chinese men undergoing surgery for benign prostatic hyperplasia with serum prostate-specific antigen.

PubMed

Song, Lingmin; Zhu, Yuchun; Han, Ping; Chen, Ni; Lin, Dao; Lai, Jianyu; Wei, Qiang

2011-03-01

To reveal the correlation between benign prostatic hyperplasia (BPH) histologic inflammation and serum prostate-specific antigen (sPSA) concentrations, and the possible mechanism. Patients underwent surgery at the Urology Department of West China Hospital of Sichuan University were retrospectively studied. Preoperative sPSA and transrectal ultrasonography were measured. According to the histopathological classification system for chronic prostatic inflammation proposed by the Chronic Prostatitis Collaborative Research Network (CPCRN) and the International Prostatitis Collaborative Network (IPCN), we classified the histologic sections of prostatic biopsy into glandular, periglandular, and stromal inflammation by the anatomical location of inflammatory infiltration. The glandular inflammation was graded according to the inflammatory aggressiveness. The periglandular and stromal inflammation were graded according to the inflammatory density. The correlation between histologic inflammation and sPSA was studied by a multiple regression model in conjunction with age and total prostatic volume. A total of 454 patients with exclusively BPH were analyzed. The periglandular inflammatory infiltration was the most common pattern (95.6%). Single regression analysis revealed that total prostatic volume, the aggressiveness of glandular inflammation, and the intensity of periglandular and stromal inflammation were correlated with sPSA. However, the multiple regression analysis revealed that only the total prostatic volume and the aggressiveness of glandular inflammation were correlated significantly with sPSA (R = .389, 0.289; P = .000). The aggressiveness of glandular inflammatory infiltration in BPH is a significant contributor to elevated sPSA levels. The theory of leakage may be the most reasonable mechanism to reveal the correlation morphologically. We should take inflammation into consideration when interpreting the abnormal elevating of sPSA levels. Copyright © 2011 Elsevier Inc. All rights reserved.

Adding Personality to Gifted Identification: Relationships among Traditional and Personality-Based Constructs

ERIC Educational Resources Information Center

Carman, Carol A.

2011-01-01

One of the underutilized tools in gifted identification is personality-based measures. A multiple confirmatory factor analysis was utilized to examine the relationships between traditional identification methods and personality-based measures. The pattern of correlations indicated this model could be measuring two constructs, one related to…

Reexamining the Correlates of Adolescent Violent Victimization: The Importance of Exposure, Guardianship, and Target Characteristics

ERIC Educational Resources Information Center

Tillyer, Marie Skubak; Tillyer, Rob; Miller, Holly Ventura; Pangrac, Rebekah

2011-01-01

The present study examines the relative contributions of various theoretical constructs to violent victimization by operationalizing multiple measures of exposure to motivated offenders, guardianship, and target characteristics. Using a nationally representative sample of American adolescents, we conducted principal components factor analysis and…

Gender-Role Conditioning and Women's Self-Concept.

ERIC Educational Resources Information Center

Long, Vonda O.

While current research is beginning to suggest that it is masculinity that correlates with mental health, results are inconclusive and studies have primarily focused on limited measures of mental health. This study incorporated multiple measures of self-concept in an analysis of the relationship between sex-role orientation and mental health of…

Predicting Student Engagement in Online High Schools

ERIC Educational Resources Information Center

Vieira, Christopher James

2013-01-01

The purpose of this study was to analyze student engagement in online high schools based on demographic information of high school students using a mixed methods research design. Key findings through a multiple regression analysis and Pearson correlation coefficient suggest that although the majority of participants in the study are highly engaged…

Psychosocial and demographic predictors of fruit, juice and vegetable consumption among 11-14-year-old Boy Scouts

USDA-ARS?s Scientific Manuscript database

Psychosocial and demographic correlates of fruit, juice, and vegetable (FJV) consumption were investigated to guide how to increase FJV intake. Experimental design consisted of hierarchical multiple regression analysis of FJV consumption on demographics and psychosocial variables. Subjects were boys...

Environmental factors affecting understory diversity in second-growth deciduous forests

Treesearch

Cynthia D. Huebner; J.C. Randolph; G.R. Parker

1995-01-01

The purpose of this study was to determine the most important nonanthropogenic factors affecting understory (herbs, shrubs and low-growing vines) diversity in forested landscapes of southern Indiana. Fourteen environmental variables were measured for 46 sites. Multiple regression analysis showed significant positive correlation between understory diversity and tree...

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

2017-01-01

High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Vectorized data acquisition and fast triple-correlation integrals for Fluorescence Triple Correlation Spectroscopy

NASA Astrophysics Data System (ADS)

Ridgeway, William K.; Millar, David P.; Williamson, James R.

2013-04-01

Fluorescence Correlation Spectroscopy (FCS) is widely used to quantify reaction rates and concentrations of molecules in vitro and in vivo. We recently reported Fluorescence Triple Correlation Spectroscopy (F3CS), which correlates three signals together instead of two. F3CS can analyze the stoichiometries of complex mixtures and detect irreversible processes by identifying time-reversal asymmetries. Here we report the computational developments that were required for the realization of F3CS and present the results as the Triple Correlation Toolbox suite of programs. Triple Correlation Toolbox is a complete data analysis pipeline capable of acquiring, correlating and fitting large data sets. Each segment of the pipeline handles error estimates for accurate error-weighted global fitting. Data acquisition was accelerated with a combination of off-the-shelf counter-timer chips and vectorized operations on 128-bit registers. This allows desktop computers with inexpensive data acquisition cards to acquire hours of multiple-channel data with sub-microsecond time resolution. Off-line correlation integrals were implemented as a two delay time multiple-tau scheme that scales efficiently with multiple processors and provides an unprecedented view of linked dynamics. Global fitting routines are provided to fit FCS and F3CS data to models containing up to ten species. Triple Correlation Toolbox is a complete package that enables F3CS to be performed on existing microscopes. Catalogue identifier: AEOP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOP_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 50189 No. of bytes in distributed program, including test data, etc.: 6135283 Distribution format: tar.gz Programming language: C/Assembly. Computer: Any with GCC and library support. Operating system: Linux and OS X (data acq. for Linux only due to library availability), not tested on Windows. RAM: ≥512 MB. Classification: 16.4. External routines: NIDAQmx (National Instruments), Gnu Scientific Library, GTK+, PLplot (optional) Nature of problem: Fluorescence Triple Correlation Spectroscopy required three things: data acquisition at faster speeds than were possible without expensive custom hardware, triple-correlation routines that could process 1/2 TB data sets rapidly, and fitting routines capable of handling several to a hundred fit parameters and 14,000 + data points, each with error estimates. Solution method: A novel data acquisition concept mixed signal processing with off-the-shelf hardware and data-parallel processing using 128-bit registers found in desktop CPUs. Correlation algorithms used fractal data structures and multithreading to reduce data analysis times. Global fitting was implemented with robust minimization routines and provides feedback that allows the user to critically inspect initial guesses and fits. Restrictions: Data acquisition only requires a National Instruments data acquisition card (it was tested on Linux using card PCIe-6251) and a simple home-built circuit. Unusual features: Hand-coded ×86-64 assembly for data acquisition loops (platform-independent C code also provided). Additional comments: A complete collection of tools to perform Fluorescence Triple Correlation Spectroscopy-from data acquisition to two-tau correlation of large data sets, to model fitting. Running time: 1-5 h of data analysis per hour of data collected. Varies depending on data-acquisition length, time resolution, data density and number of cores used for correlation integrals.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether patients will hear well with cochlear implants. It could also be used to predict whether cochlear implants will provide good speech recognition benefits to candidates, even if their speech discrimination is poor. This FMD index could become a useful predictive tool for candidates with poor speech discrimination to determine the efficacy of CI before surgery.

Multiple fingerprinting analyses in quality control of Cassiae Semen polysaccharides.

PubMed

Cheng, Jing; He, Siyu; Wan, Qiang; Jing, Pu

2018-03-01

Quality control issue overshadows potential health benefits of Cassiae Semen due to the analytic limitations. In this study, multiple-fingerprint analysis integrated with several chemometrics was performed to assess the polysaccharide quality of Cassiae Semen harvested from different locations. FT-IR, HPLC, and GC fingerprints of polysaccharide extracts from the authentic source were established as standard profiles, applying to assess the quality of foreign sources. Analyses of FT-IR fingerprints of polysaccharide extracts using either Pearson correlation analysis or principal component analysis (PCA), or HPLC fingerprints of partially hydrolyzed polysaccharides with PCA, distinguished the foreign sources from the authentic source. However, HPLC or GC fingerprints of completely hydrolyzed polysaccharides couldn't identify all foreign sources and the methodology using GC is quite limited in determining the monosaccharide composition. This indicates that FT-IR/HPLC fingerprints of non/partially-hydrolyzed polysaccharides, respectively, accompanied by multiple chemometrics methods, might be potentially applied in detecting and differentiating sources of Cassiae Semen. Copyright © 2018 Elsevier B.V. All rights reserved.

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

Abdominal girth, vertebral column length, and spread of spinal anesthesia in 30 minutes after plain bupivacaine 5 mg/mL.

PubMed

Zhou, Qing-he; Xiao, Wang-pin; Shen, Ying-yan

2014-07-01

The spread of spinal anesthesia is highly unpredictable. In patients with increased abdominal girth and short stature, a greater cephalad spread after a fixed amount of subarachnoidally administered plain bupivacaine is often observed. We hypothesized that there is a strong correlation between abdominal girth/vertebral column length and cephalad spread. Age, weight, height, body mass index, abdominal girth, and vertebral column length were recorded for 114 patients. The L3-L4 interspace was entered, and 3 mL of 0.5% plain bupivacaine was injected into the subarachnoid space. The cephalad spread (loss of temperature sensation and loss of pinprick discrimination) was assessed 30 minutes after intrathecal injection. Linear regression analysis was performed for age, weight, height, body mass index, abdominal girth, vertebral column length, and the spread of spinal anesthesia, and the combined linear contribution of age up to 55 years, weight, height, abdominal girth, and vertebral column length was tested by multiple regression analysis. Linear regression analysis showed that there was a significant univariate correlation among all 6 patient characteristics evaluated and the spread of spinal anesthesia (all P < 0.039) except for age and loss of temperature sensation (P > 0.068). Multiple regression analysis showed that abdominal girth and the vertebral column length were the key determinants for spinal anesthesia spread (both P < 0.0001), whereas age, weight, and height could be omitted without changing the results (all P > 0.059, all 95% confidence limits < 0.372). Multiple regression analysis revealed that the combination of a patient's 5 general characteristics, especially abdominal girth and vertebral column length, had a high predictive value for the spread of spinal anesthesia after a given dose of plain bupivacaine.

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationships between Lifestyle, Living Environments, and Incidence of Hypertension in Japan (in Men): Based on Participant’s Data from the Nationwide Medical Check-Up

PubMed Central

Oka, Mayumi; Yamamoto, Mio; Mure, Kanae; Takeshita, Tatsuya; Arita, Mikio

2016-01-01

This study aims to investigate factors that contribute to the differences in incidence of hypertension between different regions in Japan, by accounting for not only individual lifestyles, but also their living environments. The target participants of this survey were individuals who received medical treatment for hypertension, as well as hypertension patients who have not received any treatment. The objective variable for analysis was the incidence of hypertension as data aggregated per prefecture. We used data (in men) including obesity, salt intake, vegetable intake, habitual alcohol consumption, habitual smoking, and number of steps walked per day. The variables within living environment included number of rail stations, standard/light vehicle usage, and slope of habitable land. In addition, we analyzed data for the variables related to medical environment including, participation rate in medical check-ups and number of hospitals. We performed multiple stepwise regression analyses to elucidate the correlation of these variables by using hypertension incidence as the objective variable. Hypertension incidence showed a significant negative correlation with walking and medical check-ups, and a significant positive correlation with light-vehicle usage and slope. Between the number of steps and variables related to the living environment, number of rail stations showed a significant positive correlation, while, standard- and light-vehicle usage showed significant negative correlation. Moreover, with stepwise multiple regression analysis, walking showed the strongest effect. The differences in daily walking based on living environment were associated with the disparities in the hypertension incidence in Japan. PMID:27788198

Higher HOMA-IR index and correlated factors of insulin resistance in patients with IgA nephropathy.

PubMed

Yang, Yue; Wei, Ri-Bao; Wang, Yuan-da; Zhang, Xue-Guang; Rong, Na; Tang, Li; Chen, Xiang-Mei

2012-11-01

To investigate the index of homeostasis model of insulin resistance (HOMA-IR) in IgA nephropathy (IgAN) patients, and to explore the possible correlated factors contributing to insulin resistance (IR) within these patients. There were 255 IgAN patients and 45 membranous nephropathy (MN) patients in our database. We identified 89 IgAN subjects and 21 MN subjects without diabetes and undergoing glucocorticoid therapy for at least 6 months. Data regarding physical examination, blood chemistry and renal pathology were collected from 89 IgAN subjects and 21 MN subjects. Then 62 IgAN patients and 19 MN patients with chronic kidney disease (CKD) Stage 1 - 2 were selected for the comparison of HOMA-IR index, 89 IgAN patients were selected for multiple regression analysis to test for correlated factors of HOMA-IR index with IgAN patients. Comparison between IgAN and MN show that HOMA-IR index was significantly higher in IgAN patients with CKD Stage 1 - 2. After logarithmic transformation with urine protein (UPr), Ln(UPr) (b = 0.186, p = 0.008), eGFR (b = -0.005, p = 0.014), > 50% of glomeruli with mesangial hypercellularity (b = 0.285, p = 0.027) and body mass index (BMI) (b = 0.039, p = 0.008) were correlated factors of HOMA-IR index in the multiple regression analysis. IgAN patients had higher HOMA-IR index compared with MN in the stages of CKD 1 - 2. For IgAN patients, more UPr, lower eGFR, > 50% of glomeruli with mesangial hypercellularity and higher BMI were correlated with IR.

Pulmonary hypertension and computed tomography measurement of small pulmonary vessels in severe emphysema.

PubMed

Matsuoka, Shin; Washko, George R; Yamashiro, Tsuneo; Estepar, Raul San Jose; Diaz, Alejandro; Silverman, Edwin K; Hoffman, Eric; Fessler, Henry E; Criner, Gerard J; Marchetti, Nathaniel; Scharf, Steven M; Martinez, Fernando J; Reilly, John J; Hatabu, Hiroto

2010-02-01

Vascular alteration of small pulmonary vessels is one of the characteristic features of pulmonary hypertension in chronic obstructive pulmonary disease. The in vivo relationship between pulmonary hypertension and morphological alteration of the small pulmonary vessels has not been assessed in patients with severe emphysema. We evaluated the correlation of total cross-sectional area of small pulmonary vessels (CSA) assessed on computed tomography (CT) scans with the degree of pulmonary hypertension estimated by right heart catheterization. In 79 patients with severe emphysema enrolled in the National Emphysema Treatment Trial (NETT), we measured CSA less than 5 mm(2) (CSA(<5)) and 5 to 10 mm(2) (CSA(5-10)), and calculated the percentage of total CSA for the lung area (%CSA(<5) and %CSA(5-10), respectively). The correlations of %CSA(<5) and %CSA(5-10) with pulmonary arterial mean pressure (Ppa) obtained by right heart catheterization were evaluated. Multiple linear regression analysis using Ppa as the dependent outcome was also performed. The %CSA(<5) had a significant negative correlation with Ppa (r = -0.512, P < 0.0001), whereas the correlation between %CSA(5-10) and Ppa did not reach statistical significance (r = -0.196, P = 0.083). Multiple linear regression analysis showed that %CSA(<5) and diffusing capacity of carbon monoxide (DL(CO)) % predicted were independent predictors of Ppa (r(2) = 0.541): %CSA (<5) (P < 0.0001), and DL(CO) % predicted (P = 0.022). The %CSA(<5) measured on CT images is significantly correlated to Ppa in severe emphysema and can estimate the degree of pulmonary hypertension.

Treatment Results of Postoperative Radiotherapy on Squamous Cell Carcinoma of the Oral Cavity: Coexistence of Multiple Minor Risk Factors Results in Higher Recurrence Rates

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

Fan, Kang-Hsing; Taipei Chang Gung Head and Neck Oncology Group, Chang Gung Memorial Hospital, Taiwan; Graduate Institute of Clinical Medical Sciences, Taiwan

2010-07-15

Purpose: The aim of this study was to investigate the treatment results of postoperative radiotherapy (PORT) on squamous cell carcinoma of the oral cavity (OSCC). Materials and Methods: This study included 302 OSCC patients who were treated by radical surgery and PORT. Indications for PORT include Stage III or IV OSCC according to the 2002 criteria of the American Joint Committee on Cancer, the presence of perineural invasion or lymphatic invasion, the depth of tumor invasion, or a close surgical margin. Patients with major risk factors, such as multiple nodal metastases, a positive surgical margin, or extracapsular spreading, were excluded.more » The prescribed dose of PORT ranged from 59.4 to 66.6Gy (median, 63Gy). Results: The 3-year overall and recurrence-free survival rates were 73% and 70%, respectively. Univariate analysis revealed that differentiation, perineural invasion, lymphatic invasion, bone invasion, location (hard palate and retromolar trigone), invasion depths {>=}10mm, and margin distances {<=}4mm were significant prognostic factors. The presence of multiple significant factors of univariate analysis correlated with disease recurrence. The 3-year recurrence-free survival rates were 82%, 76%, and 45% for patients with no risk factors, one or two risk factors, and three or more risk factors, respectively. After multivariate analysis, the number of risk factors and lymphatic invasion were significant prognostic factors. Conclusion: PORT may be an adequate adjuvant therapy for OSCC patients with one or two risk factors of recurrence. The presence of multiple risk factors and lymphatic invasion correlated with poor prognosis, and more aggressive treatment may need to be considered.« less

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

Canonical correlation analysis (CCA) is a widely used multivariate method for assessing the association between two sets of variables. However, when the number of variables far exceeds the number of subjects, such in the case of large-scale genomic studies, the traditional CCA method is not appropriate. In addition, when the variables are highly correlated the sample covariance matrices become unstable or undefined. To overcome these two issues, sparse canonical correlation analysis (SCCA) for multiple data sets has been proposed using a Lasso type of penalty. However, these methods do not have direct control over sparsity of solution. An additional step that uses Bayesian Information Criterion (BIC) has also been suggested to further filter out unimportant features. In this paper, a comparison of four penalty functions (Lasso, Elastic-net, SCAD and Hard-threshold) for SCCA with and without the BIC filtering step have been carried out using both real and simulated genotypic and mRNA expression data. This study indicates that the SCAD penalty with BIC filter would be a preferable penalty function for application of SCCA to genomic data. PMID:21984855

Satellite remote sensing of fine particulate air pollutants over Indian mega cities

NASA Astrophysics Data System (ADS)

Sreekanth, V.; Mahesh, B.; Niranjan, K.

2017-11-01

In the backdrop of the need for high spatio-temporal resolution data on PM2.5 mass concentrations for health and epidemiological studies over India, empirical relations between Aerosol Optical Depth (AOD) and PM2.5 mass concentrations are established over five Indian mega cities. These relations are sought to predict the surface PM2.5 mass concentrations from high resolution columnar AOD datasets. Current study utilizes multi-city public domain PM2.5 data (from US Consulate and Embassy's air monitoring program) and MODIS AOD, spanning for almost four years. PM2.5 is found to be positively correlated with AOD. Station-wise linear regression analysis has shown spatially varying regression coefficients. Similar analysis has been repeated by eliminating data from the elevated aerosol prone seasons, which has improved the correlation coefficient. The impact of the day to day variability in the local meteorological conditions on the AOD-PM2.5 relationship has been explored by performing a multiple regression analysis. A cross-validation approach for the multiple regression analysis considering three years of data as training dataset and one-year data as validation dataset yielded an R value of ∼0.63. The study was concluded by discussing the factors which can improve the relationship.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis.

PubMed

Ko, Fang-Yuan; Yang, Albert C; Tsai, Shih-Jen; Zhou, Yang; Xu, Lie-Ming

2013-01-22

Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis

PubMed Central

2013-01-01

Background Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. Methods A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Results Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Conclusions Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression. PMID:23339829

Modulation of brain activity by multiple lexical and word form variables in visual word recognition: A parametric fMRI study.

PubMed

Hauk, Olaf; Davis, Matthew H; Pulvermüller, Friedemann

2008-09-01

Psycholinguistic research has documented a range of variables that influence visual word recognition performance. Many of these variables are highly intercorrelated. Most previous studies have used factorial designs, which do not exploit the full range of values available for continuous variables, and are prone to skewed stimulus selection as well as to effects of the baseline (e.g. when contrasting words with pseudowords). In our study, we used a parametric approach to study the effects of several psycholinguistic variables on brain activation. We focussed on the variable word frequency, which has been used in numerous previous behavioural, electrophysiological and neuroimaging studies, in order to investigate the neuronal network underlying visual word processing. Furthermore, we investigated the variable orthographic typicality as well as a combined variable for word length and orthographic neighbourhood size (N), for which neuroimaging results are still either scarce or inconsistent. Data were analysed using multiple linear regression analysis of event-related fMRI data acquired from 21 subjects in a silent reading paradigm. The frequency variable correlated negatively with activation in left fusiform gyrus, bilateral inferior frontal gyri and bilateral insulae, indicating that word frequency can affect multiple aspects of word processing. N correlated positively with brain activity in left and right middle temporal gyri as well as right inferior frontal gyrus. Thus, our analysis revealed multiple distinct brain areas involved in visual word processing within one data set.

Maternal Factors Predicting Cognitive and Behavioral Characteristics of Children with Fetal Alcohol Spectrum Disorders

PubMed Central

May, Philip A.; Tabachnick, Barbara G.; Gossage, J. Phillip; Kalberg, Wendy O.; Marais, Anna-Susan; Robinson, Luther K.; Manning, Melanie A.; Blankenship, Jason; Buckley, David; Hoyme, H. Eugene; Adnams, Colleen M.

2013-01-01

Objective To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASD). Method Multivariate correlation techniques were employed with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and employed in structural equation models (SEM) to assess correlates of child intelligence (verbal and non-verbal) and behavior. Results A first SEM utilizing only seven maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05), but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status (SES), and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model, and were overpowered by SES and maternal physical traits. Conclusions While other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly-controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD. PMID:23751886

Is there a link between the hospital-acquired injurious fall rates in US acute care hospitals and these institutions' implementation levels of computerized systems?

PubMed

Tzeng, Huey-Ming; Hu, Hsou Mei; Yin, Chang-Yi

2011-12-01

Medicare no longer reimburses acute care hospitals for the costs of additional care required due to hospital-acquired injuries. Consequently, this study explored the effective computerized systems to inform practice for better interventions to reduce fall risk. It provided a correlation between type of computerized system and hospital-acquired injurious fall rates at acute care hospitals in California, Florida, and New York. It used multiple publicly available data sets, with the hospital as the unit of analysis. Descriptive and Pearson correlation analyses were used. The analysis included 462 hospitals. Significant correlations could be categorized into two groups: (1) meaningful computerized systems that were associated with lower injurious fall rates: the decision support systems for drug allergy alerts, drug-drug interaction alerts, and drug-laboratory interaction alerts; and (2) computerized systems that were associated with higher injurious fall rates: the decision support system for drug-drug interaction alerts and the computerized provider order entry system for radiology tests. Future research may include additional states, multiple years of data, and patient-level data to validate this study's findings. This effort may further inform policy makers and the public about effective clinical computerized systems provided to clinicians to improve their practice decisions and care outcomes.

Chromium (VI) induced oxidative damage to DNA: increase of urinary 8-hydroxydeoxyguanosine concentrations (8-OHdG) among electroplating workers

PubMed Central

Kuo, H; Chang, S; Wu, K; Wu, F

2003-01-01

Aims: To investigate the concentration of urinary 8-hydroxydeoxyguanosine (8-OHdG) among electroplating workers in Taiwan. Methods: Fifty workers were selected from five chromium (Cr) electroplating plants in central Taiwan. The 20 control subjects were office workers with no previous exposure to Cr. Urinary 8-OHdG concentrations were determined using high performance liquid chromatography with electrochemical detection. Results: Urinary 8-OHdG concentrations among Cr workers (1149.5 pmol/kg/day) were higher than those in the control group (730.2 pmol/kg/day). There was a positive correlation between urinary 8-OHdG concentrations and urinary Cr concentration (r = 0.447, p < 0.01), and urinary 8-OHdG correlated positively with airborne Cr concentration (r = 0.285). Using multiple regression analysis, the factors that affected urinary 8-OHdG concentrations were alcohol, the common cold, and high urinary Cr concentration. There was a high correlation of urinary 8-OHdG with both smoking and drinking, but multiple regression analysis showed that smoking was not a significant factor. Age and gender were also non-significant factors. Conclusion: 8-OHdG, which is an indicator of oxidative DNA damage, was a sensitive biomarker for Cr exposure. PMID:12883020

Multivariate analysis of scale-dependent associations between bats and landscape structure

USGS Publications Warehouse

Gorresen, P.M.; Willig, M.R.; Strauss, R.E.

2005-01-01

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix-simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time. ?? 2005 by the Ecological Society of America.

Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics

PubMed Central

Kong, Xiangrong; Wang, Mei-Cheng; Gray, Ronald

2014-01-01

We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence. PMID:26195849

Relation between trinucleotide GAA repeat length and sensory neuropathy in Friedreich's ataxia.

PubMed

Santoro, L; De Michele, G; Perretti, A; Crisci, C; Cocozza, S; Cavalcanti, F; Ragno, M; Monticelli, A; Filla, A; Caruso, G

1999-01-01

To verify if GAA expansion size in Friedreich's ataxia could account for the severity of sensory neuropathy. Retrospective study of 56 patients with Friedreich's ataxia selected according to homozygosity for GAA expansion and availability of electrophysiological findings. Orthodromic sensory conduction velocity in the median nerve was available in all patients and that of the tibial nerve in 46 of them. Data of sural nerve biopsy and of a morphometric analysis were available in 12 of the selected patients. The sensory action potential amplitude at the wrist (wSAP) and at the medial malleolus (m mal SAP) and the percentage of myelinated fibres with diameter larger than 7, 9, and 11 microm in the sural nerve were correlated with disease duration and GAA expansion size on the shorter (GAA1) and larger (GAA2) expanded allele in each pair. Pearson's correlation test and stepwise multiple regression were used for statistical analysis. A significant inverse correlation between GAA1 size and wSAP, m mal SAP, and percentage of myelinated fibres was found. Stepwise multiple regression showed that GAA1 size significantly affects electrophysiological and morphometric data, whereas duration of disease has no effect. The data suggest that the severity of the sensory neuropathy is probably genetically determined and that it is not progressive.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Methods for meta-analysis of multiple traits using GWAS summary statistics.

PubMed

Ray, Debashree; Boehnke, Michael

2018-03-01

Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.

A cyber-event correlation framework and metrics

NASA Astrophysics Data System (ADS)

Kang, Myong H.; Mayfield, Terry

2003-08-01

In this paper, we propose a cyber-event fusion, correlation, and situation assessment framework that, when instantiated, will allow cyber defenders to better understand the local, regional, and global cyber-situation. This framework, with associated metrics, can be used to guide assessment of our existing cyber-defense capabilities, and to help evaluate the state of cyber-event correlation research and where we must focus our future cyber-event correlation research. The framework, based on the cyber-event gathering activities and analysis functions, consists of five operational steps, each of which provides a richer set of contextual information to support greater situational understanding. The first three steps are categorically depicted as increasingly richer and broader-scoped contexts achieved through correlation activity, while in the final two steps, these richer contexts are achieved through analytical activities (situation assessment, and threat analysis & prediction). Category 1 Correlation focuses on the detection of suspicious activities and the correlation of events from a single cyber-event source. Category 2 Correlation clusters the same or similar events from multiple detectors that are located at close proximity and prioritizes them. Finally, the events from different time periods and event sources at different location/regions are correlated at Category 3 to recognize the relationship among different events. This is the category that focuses on the detection of large-scale and coordinated attacks. The situation assessment step (Category 4) focuses on the assessment of cyber asset damage and the analysis of the impact on missions. The threat analysis and prediction step (Category 5) analyzes attacks based on attack traces and predicts the next steps. Metrics that can distinguish correlation and cyber-situation assessment tools for each category are also proposed.

Multi-frequency local wavenumber analysis and ply correlation of delamination damage.

PubMed

Juarez, Peter D; Leckey, Cara A C

2015-09-01

Wavenumber domain analysis through use of scanning laser Doppler vibrometry has been shown to be effective for non-contact inspection of damage in composites. Qualitative and semi-quantitative local wavenumber analysis of realistic delamination damage and quantitative analysis of idealized damage scenarios (Teflon inserts) have been performed previously in the literature. This paper presents a new methodology based on multi-frequency local wavenumber analysis for quantitative assessment of multi-ply delamination damage in carbon fiber reinforced polymer (CFRP) composite specimens. The methodology is presented and applied to a real world damage scenario (impact damage in an aerospace CFRP composite). The methodology yields delamination size and also correlates local wavenumber results from multiple excitation frequencies to theoretical dispersion curves in order to robustly determine the delamination ply depth. Results from the wavenumber based technique are validated against a traditional nondestructive evaluation method. Published by Elsevier B.V.

Statistical research using the multiple regression analysis in areas of the cast hipereutectoid steel rolls manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Alexa, V.; Serban, S.; Rackov, M.; Čavić, M.

2018-01-01

The cast hipereutectoid steel (usually named Adamite) is a roll manufacturing destined material, having mechanical, chemical properties and Carbon [C] content of which stands between steelandiron, along-withitsalloyelements such as Nickel [Ni], Chrome [Cr], Molybdenum [Mo] and/or other alloy elements. Adamite Rolls are basically alloy steel rolls (a kind of high carbon steel) having hardness ranging from 40 to 55 degrees Shore C, with Carbon [C] percentage ranging from 1.35% until to 2% (usually between 1.2˜2.3%), the extra Carbon [C] and the special alloying element giving an extra wear resistance and strength. First of all the Adamite roll’s prominent feature is the small variation in hardness of the working surface, and has a good abrasion resistance and bite performance. This paper reviews key aspects of roll material properties and presents an analysis of the influences of chemical composition upon the mechanical properties (hardness) of the cast hipereutectoid steel rolls (Adamite). Using the multiple regression analysis (the double and triple regression equations), some mathematical correlations between the cast hipereutectoid steel rolls’ chemical composition and the obtained hardness are presented. In this work several results and evidence obtained by actual experiments are presented. Thus, several variation boundaries for the chemical composition of cast hipereutectoid steel rolls, in view the obtaining the proper values of the hardness, are revealed. For the multiple regression equations, correlation coefficients and graphical representations the software Matlab was used.

Clinical correlates and prognostic value of different metastatic sites in patients with malignant melanoma of the skin: a SEER database analysis.

PubMed

Abdel-Rahman, Omar

2018-03-01

Population-based data on the clinical correlates and prognostic value of the pattern of metastases among patients with cutaneous melanoma are needed. Surveillance, Epidemiology and End Results (SEER) database (2010-2013) has been explored through SEER*Stat program. For each of six distant metastatic sites (bone, brain, liver, lung, distant lymph nodes, and skin/subcutaneous), relevant correlation with baseline characteristics were reported. Survival analysis has been conducted through Kaplan-Meier analysis, and multivariate analysis has been conducted through a Cox proportional hazard model. A total of 2691 patients with metastatic cutaneous melanoma were identified in the period from 2010 to 2013. Patients with isolated skin/subcutaneous metastases have the best overall and melanoma-specific survival (MSS) followed by patients with isolated distant lymph node metastases followed by patients with isolated lung metastases. Patients with isolated liver, bone, or brain metastases have the worst overall and MSS (p < .0001 for both end points). Multivariate analysis revealed that age more than 70 at diagnosis (p = .012); multiple sites of metastases (p <.0001), no surgery to the primary tumor (p <.0001), and no surgery to the metastatic disease (p < .0001) were associated with worse overall survival (OS). For MSS, nodal positivity (p = .038), multiple sites of metastases (p < .0001), no surgery to the primary tumor (p < .0001), and no surgery to the metastatic disease (p < .0001) were associated with worse survival. The prognosis of metastatic cutaneous melanoma patients differs considerably according to the site of distant metastases. Further prospective studies are required to evaluate the role of local treatment in the management of metastatic disease.

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Validating the performance of correlated fission multiplicity implementation in radiation transport codes with subcritical neutron multiplication benchmark experiments

DOE PAGES

Arthur, Jennifer; Bahran, Rian; Hutchinson, Jesson; ...

2018-06-14

Historically, radiation transport codes have uncorrelated fission emissions. In reality, the particles emitted by both spontaneous and induced fissions are correlated in time, energy, angle, and multiplicity. This work validates the performance of various current Monte Carlo codes that take into account the underlying correlated physics of fission neutrons, specifically neutron multiplicity distributions. The performance of 4 Monte Carlo codes - MCNP®6.2, MCNP®6.2/FREYA, MCNP®6.2/CGMF, and PoliMi - was assessed using neutron multiplicity benchmark experiments. In addition, MCNP®6.2 simulations were run using JEFF-3.2 and JENDL-4.0, rather than ENDF/B-VII.1, data for 239Pu and 240Pu. The sensitive benchmark parameters that in this workmore » represent the performance of each correlated fission multiplicity Monte Carlo code include the singles rate, the doubles rate, leakage multiplication, and Feynman histograms. Although it is difficult to determine which radiation transport code shows the best overall performance in simulating subcritical neutron multiplication inference benchmark measurements, it is clear that correlations exist between the underlying nuclear data utilized by (or generated by) the various codes, and the correlated neutron observables of interest. This could prove useful in nuclear data validation and evaluation applications, in which a particular moment of the neutron multiplicity distribution is of more interest than the other moments. It is also quite clear that, because transport is handled by MCNP®6.2 in 3 of the 4 codes, with the 4th code (PoliMi) being based on an older version of MCNP®, the differences in correlated neutron observables of interest are most likely due to the treatment of fission event generation in each of the different codes, as opposed to the radiation transport.« less

Validating the performance of correlated fission multiplicity implementation in radiation transport codes with subcritical neutron multiplication benchmark experiments

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

Arthur, Jennifer; Bahran, Rian; Hutchinson, Jesson

Historically, radiation transport codes have uncorrelated fission emissions. In reality, the particles emitted by both spontaneous and induced fissions are correlated in time, energy, angle, and multiplicity. This work validates the performance of various current Monte Carlo codes that take into account the underlying correlated physics of fission neutrons, specifically neutron multiplicity distributions. The performance of 4 Monte Carlo codes - MCNP®6.2, MCNP®6.2/FREYA, MCNP®6.2/CGMF, and PoliMi - was assessed using neutron multiplicity benchmark experiments. In addition, MCNP®6.2 simulations were run using JEFF-3.2 and JENDL-4.0, rather than ENDF/B-VII.1, data for 239Pu and 240Pu. The sensitive benchmark parameters that in this workmore » represent the performance of each correlated fission multiplicity Monte Carlo code include the singles rate, the doubles rate, leakage multiplication, and Feynman histograms. Although it is difficult to determine which radiation transport code shows the best overall performance in simulating subcritical neutron multiplication inference benchmark measurements, it is clear that correlations exist between the underlying nuclear data utilized by (or generated by) the various codes, and the correlated neutron observables of interest. This could prove useful in nuclear data validation and evaluation applications, in which a particular moment of the neutron multiplicity distribution is of more interest than the other moments. It is also quite clear that, because transport is handled by MCNP®6.2 in 3 of the 4 codes, with the 4th code (PoliMi) being based on an older version of MCNP®, the differences in correlated neutron observables of interest are most likely due to the treatment of fission event generation in each of the different codes, as opposed to the radiation transport.« less

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

PubMed

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Effect of knee osteoarthritis on the perception of quality of life in Venezuelan patients.

PubMed

Chacón, José G; González, Nancy E; Véliz, Aleida; Losada, Benito R; Paul, Hernando; Santiago, Luís G; Antúnez, Ana; Finol, Yelitza; González, María E; Granados, Isabel; Maldonado, Irama; Maldonado, Teolinda; Marín, Francisco; Zambrano, Gisela; Rodríguez, Martín A

2004-06-15

To measure the perception of quality of life in Venezuelan patients with knee osteoarthritis and to identify those variables that may influence it. A multicenter, cross-sectional study of 126 mestizo patients with knee osteoarthritis recruited from 8 rheumatology centers in Venezuela. We used a Spanish-translated version of the Arthritis Impact Measurement Scales (AIMS), as adapted in Venezuela. One-way analysis of variance was used to compare the AIMS mean total score among subgroups of knee pain, anatomic stage, and socioeconomic status (SES); a post-hoc test was performed to identify significant intragroup differences. Pearson's correlation coefficient was used to examine correlations between age, body mass index (BMI), disease duration, knee pain, and AIMS score. Associations between radiologic stage, SES, and AIMS scores were examined using Spearman's rank correlation. Multiple regression analysis was used to estimate predictor factors of AIMS scores. A significant correlation was found between total AIMS scores and knee pain, age, and socioeconomic status, but not with BMI, disease duration, or anatomic stage. Patients with severe knee pain differed from those with mild and moderate pain, and the highest AIMS mean total score was seen in patients within the severe knee pain subset. Patients in the highest socioeconomic levels differed from those within lowest categories. Patients classified as being at the levels of relative and critical poverty showed the highest AIMS scores. Multiple regression analysis showed that knee pain was the only variable that exerted an independent effect on the quality of life in our patients. The perception of quality of life is negatively affected by increasing levels of joint pain, old age, and low socioeconomic status in Venezuelan patients with knee osteoarthritis. Our study supports the need for an early and vigorous approach to treat pain in this group of patients.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Mesenchymal stem cells can modulate longitudinal changes in cortical thickness and its related cognitive decline in patients with multiple system atrophy

PubMed Central

Sunwoo, Mun Kyung; Yun, Hyuk Jin; Song, Sook K.; Ham, Ji Hyun; Hong, Jin Yong; Lee, Ji E.; Lee, Hye S.; Sohn, Young H.; Lee, Jong-Min; Lee, Phil Hyu

2014-01-01

Multiple system atrophy (MSA) is an adult-onset, sporadic neurodegenerative disease. Because the prognosis of MSA is fatal, neuroprotective or regenerative strategies may be invaluable in MSA treatment. Previously, we obtained clinical and imaging evidence that mesenchymal stem cell (MSC) treatment could have a neuroprotective role in MSA patients. In the present study, we evaluated the effects of MSC therapy on longitudinal changes in subcortical deep gray matter volumes and cortical thickness and their association with cognitive performance. Clinical and imaging data were obtained from our previous randomized trial of autologous MSC in MSA patients. During 1-year follow-up, we assessed longitudinal differences in automatic segmentation-based subcortical deep gray matter volumes and vertex-wise cortical thickness between placebo (n = 15) and MSC groups (n = 11). Next, we performed correlation analysis between the changes in cortical thickness and changes in the Korean version of the Montreal Cognitive Assessment (MoCA) scores and cognitive performance of each cognitive subdomain using a multiple, comparison correction. There were no significant differences in age at baseline, age at disease onset, gender ratio, disease duration, clinical severity, MoCA score, or education level between the groups. The automated subcortical volumetric analysis revealed that the changes in subcortical deep gray matter volumes of the caudate, putamen, and thalamus did not differ significantly between the groups. The areas of cortical thinning over time in the placebo group were more extensive, including the frontal, temporal, and parietal areas, whereas these areas in the MSC group were less extensive. Correlation analysis indicated that declines in MoCA scores and phonemic fluency during the follow-up period were significantly correlated with cortical thinning of the frontal and posterior temporal areas and anterior temporal areas in MSA patients, respectively. In contrast, no significant correlations were observed in the MSC group. These results suggest that MSC treatment in patients with MSA may modulate cortical thinning over time and related cognitive performance, inferring a future therapeutic candidate for cognitive disorders. PMID:24982631

Multiple scaling behaviour and nonlinear traits in music scores

PubMed Central

Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-01-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece. PMID:29308256

Multiple scaling behaviour and nonlinear traits in music scores

NASA Astrophysics Data System (ADS)

González-Espinoza, Alfredo; Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-12-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece.

The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders

PubMed Central

Scarella, Timothy M.; Laferton, Johannes A. C.; Ahern, David K.; Fallon, Brian A.; Barsky, Arthur

2015-01-01

Background Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric co-morbidity in hypochondriasis and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Methods Data were collected as part of a clinical trial on treatment methods for hypochondriasis. 194 participants meeting criteria for DSM-IV hypochondriasis were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Results The majority of individuals with hypochondriasis had co-morbid psychiatric illness; the mean number of co-morbid diagnoses was 1.4, and 35.1% had hypochondriasis as their only diagnosis. Participants were more likely to have only co-morbid anxiety disorders than only co-morbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Conclusion Our findings suggest that the entity of health anxiety (Hypochondriasis in DSM-IV, Illness Anxiety Disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of co-morbidity patterns and continuous measures of symptoms suggest its appropriate classification is with anxiety rather than somatoform or mood disorders. PMID:26785798

Matsuda-DeFronzo insulin sensitivity index is a better predictor than HOMA-IR of hypertension in Japanese: the Tanno-Sobetsu study.

PubMed

Furugen, M; Saitoh, S; Ohnishi, H; Akasaka, H; Mitsumata, K; Chiba, M; Furukawa, T; Miyazaki, Y; Shimamoto, K; Miura, T

2012-05-01

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.

Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: A voxel-based analysis study

PubMed Central

Muhlert, Nils; Samson, Rebecca S; Sethi, Varun; Wheeler-Kingshott, Claudia AM; Miller, David H; Chard, Declan T

2015-01-01

Background: In multiple sclerosis (MS), demyelination and neuro-axonal loss occur in the brain grey matter (GM). We used magnetic resonance imaging (MRI) measures of GM magnetisation transfer ratio (MTR) and volume to assess the regional localisation of reduced MTR (reflecting demyelination) and atrophy (reflecting neuro-axonal loss) in relapsing–remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). Methods: A total of 98 people with MS (51 RRMS, 28 SPMS, 19 PPMS) and 29 controls had T1-weighted volumetric and magnetisation transfer scans. SPM8 was used to undertake voxel-based analysis (VBA) of GM tissue volumes and MTR. MS subgroups were compared with controls, adjusting for age and gender. A voxel-by-voxel basis correlation analysis between MTR and volume within each subject group was performed, using biological parametric mapping. Results: MTR reduction was more extensive than atrophy. RRMS and SPMS patients showed proportionately more atrophy in the deep GM. SPMS and PPMS patients showed proportionately greater cortical MTR reduction. RRMS patients demonstrated the most correlation of MTR reduction and atrophy in deep GM. In SPMS and PPMS patients, there was less extensive correlation. Conclusions: These results suggest that in the deep GM of RRMS patients, demyelination and neuro-axonal loss may be linked, while in SPMS and PPMS patients, neuro-axonal loss and demyelination may occur mostly independently. PMID:25145689

Optimized "detectors" for dynamics analysis in solid-state NMR

NASA Astrophysics Data System (ADS)

Smith, Albert A.; Ernst, Matthias; Meier, Beat H.

2018-01-01

Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.

A combined post-mortem magnetic resonance imaging and quantitative histological study of multiple sclerosis pathology

PubMed Central

Kolasinski, James; Chance, Steven A.; DeLuca, Gabriele C.; Esiri, Margaret M.; Chang, Eun-Hyuk; Palace, Jacqueline A.; McNab, Jennifer A.; Jenkinson, Mark; Miller, Karla L.; Johansen-Berg, Heidi

2012-01-01

Multiple sclerosis is a chronic inflammatory neurological condition characterized by focal and diffuse neurodegeneration and demyelination throughout the central nervous system. Factors influencing the progression of pathology are poorly understood. One hypothesis is that anatomical connectivity influences the spread of neurodegeneration. This predicts that measures of neurodegeneration will correlate most strongly between interconnected structures. However, such patterns have been difficult to quantify through post-mortem neuropathology or in vivo scanning alone. In this study, we used the complementary approaches of whole brain post-mortem magnetic resonance imaging and quantitative histology to assess patterns of multiple sclerosis pathology. Two thalamo-cortical projection systems were considered based on their distinct neuroanatomy and their documented involvement in multiple sclerosis: lateral geniculate nucleus to primary visual cortex and mediodorsal nucleus of the thalamus to prefrontal cortex. Within the anatomically distinct thalamo-cortical projection systems, magnetic resonance imaging derived cortical thickness was correlated significantly with both a measure of myelination in the connected tract and a measure of connected thalamic nucleus cell density. Such correlations did not exist between these markers of neurodegeneration across different thalamo-cortical systems. Magnetic resonance imaging lesion analysis depicted clearly demarcated subcortical lesions impinging on the white matter tracts of interest; however, quantitation of the extent of lesion-tract overlap failed to demonstrate any appreciable association with the severity of markers of diffuse pathology within each thalamo-cortical projection system. Diffusion-weighted magnetic resonance imaging metrics in both white matter tracts were correlated significantly with a histologically derived measure of tract myelination. These data demonstrate for the first time the relevance of functional anatomical connectivity to the spread of multiple sclerosis pathology in a ‘tract-specific’ pattern. Furthermore, the persisting relationship between metrics from post-mortem diffusion-weighted magnetic resonance imaging and histological measures from fixed tissue further validates the potential of imaging for future neuropathological studies. PMID:23065787

Some environmental and attitudinal characteristics as predictors of mathematical creativity

NASA Astrophysics Data System (ADS)

Kanhai, Abhishek; Singh, Bhoodev

2017-04-01

There are many things which can be made more useful and interesting through the application of creativity. Self-concept in mathematics and some school environmental factors such as resource adequacy, teachers' support to the students, teachers' classroom control, creative stimulation by the teachers, etc. were selected in the study. The sample of the study comprised 770 seventh grade students. Pearson correlation, multiple correlation, regression equation and multiple discriminant function analyses of variance were used to analyse the data. The result of the study showed that the relationship between mathematical creativity and each attitudinal and environmental characteristic was found to be positive and significant. Index of forecasting efficiency reveals that mathematical creativity may be best predicted by self-concept in mathematics. Environmental factors, resource adequacy and creative stimulation by the teachers' are found to be the most important factors for predicting mathematical creativity, while social-intellectual involvement among students and educational administration of the schools are to be suppressive factors. The multiple correlation between mathematical creativity and attitudinal and school environmental characteristic suggests that the combined contribution of these variables plays a significant role in the development of mathematical creativity. Mahalanobis analysis indicates that self-concept in mathematics and total school environment were found to be contributing significantly to the development of mathematical creativity.

Children's environmental chemical exposures in the USA, NHANES 2003-2012.

PubMed

Hendryx, Michael; Luo, Juhua

2018-02-01

Children are vulnerable to environmental chemical exposures, but little is known about the extent of multiple chemical exposures among children. We analyzed biomonitoring data from five cycles (2003-2012) of the National Health and Nutrition Examination Survey (NHANES) to describe multiple chemical exposures in US children, examine levels of chemical concentrations present over time, and examine differences in chemical exposures by selected demographic groups. We analyzed data for 36 chemical analytes across five chemical classes in a sample of 4299 children aged 6-18. Classes included metals, pesticides, phthalates, phenols, and polycyclic aromatic hydrocarbons. We calculated the number and percent of chemicals detected and tested for secular trends over time in chemical concentrations. We compared log concentrations among groups defined by age, sex, race/ethnicity, and poverty using multiple linear regression models and report adjusted geometric means. Among a smaller subgroup of 733 children with data across chemical classes, we calculated the linear correlations within and between classes and conducted a principal component analysis. The percentage of children with detectable concentrations of an individual chemical ranged from 26 to 100%; the average was 93%, and 29 of 36 were detected in more than 90% of children. Concentrations of most tested chemicals were either unchanged or declined from earlier to more recent years. Many differences in concentrations were present by age, sex, poverty, and race/ethnicity categories. Within and between class correlations were all significant and positive, and the principal component analysis suggested a one factor solution, indicating that children exposed to higher levels of one chemical were exposed to higher levels of other chemicals. In conclusion, children in the USA are exposed to multiple simultaneous chemicals at uneven risk across socioeconomic and demographic groups. Further efforts to understand the effects of multiple exposures on child health and development are warranted.

Bose-Einstein correlations in pp and PbPb collisions with ALICE at the LHC

ScienceCinema

Kisiel, Adam

2018-05-14

We report on the results of identical pion femtoscopy at the LHC. The Bose-Einstein correlation analysis was performed on the large-statistics ALICE p+p at sqrt{s}= 0.9 TeV and 7 TeV datasets collected during 2010 LHC running and the first Pb+Pb dataset at sqrt{s_NN}= 2.76 TeV. Detailed pion femtoscopy studies in heavy-ion collisions have shown that emission region sizes ("HBT radii") decrease with increasing pair momentum, which is understood as a manifestation of the collective behavior of matter. 3D radii were also found to universally scale with event multiplicity. In p+p collisions at 7 TeV one measures multiplicities which are comparable with those registered in peripheral AuAu and CuCu collisions at RHIC, so direct comparisons and tests of scaling laws are now possible. We show the results of double-differential 3D pion HBT analysis, as a function of multiplicity and pair momentum. The results for two collision energies are compared to results obtained in the heavy-ion collisions at similar multiplicity and p+p collisions at lower energy. We identify the relevant scaling variables for the femtoscopic radii and discuss the similarities and differences to results from heavy-ions. The observed trends give insight into the soft particle production mechanism in p+p collisions and suggest that a self-interacting collective system may be created in sufficiently high multiplicity events. First results for the central Pb+Pb collisions are also shown. A significant increase of the reaction zone volume and lifetime in comparison to RHIC is observed. Signatures of collective hydrodynamics-like behavior of the system are also apparent, and are compared to model predictions.

Multiple-trait multiple-country genetic evaluation of Holstein bulls for female fertility and milk production traits.

PubMed

Nilforooshan, M A; Jakobsen, J H; Fikse, W F; Berglund, B; Jorjani, H

2014-06-01

The aim of this study was to investigate the effect of including milk yield data in the international genetic evaluation of female fertility traits to reduce or eliminate a possible bias because of across-country selection for milk yield. Data included two female fertility traits from Great Britain, Italy and the Netherlands, together with milk yield data from the same countries and from the United States, because the genetic trends in other countries may be influenced by selection decisions on bulls in the United States. Potentially, female fertility data had been corrected nationally for within-country selection and management biases for milk yield. Using a multiple-trait multiple across-country evaluation (MT-MACE) for the analysis of female fertility traits with milk yield, across-country selection patterns both for female fertility and milk yield can be considered simultaneously. Four analyses were performed; one single-trait multiple across-country evaluation analysis including only milk yield data, one MT-MACE analysis including only female fertility traits, and one MT-MACE analysis including both female fertility and milk yield traits. An additional MT-MACE analysis was performed including both female fertility and milk yield traits, but excluding the United States. By including milk yield traits to the analysis, female fertility reliabilities increased, but not for all bulls in all the countries by trait combinations. The presence of milk yield traits in the analysis did not considerably change the genetic correlations, genetic trends or bull rankings of female fertility traits. Even though the predicted genetic merits of female fertility traits hardly changed by including milk yield traits to the analysis, the change was not equally distributed to the whole data. The number of bulls in common between the two sets of Top 100 bulls for each trait in the two analyses of female fertility traits, with and without the four milk yield traits and their rank correlations were low, not necessarily because of the absence of the US milk yield data. The joint international genetic evaluation of female fertility traits with milk yield is recommended to make use of information on several female fertility traits from different countries simultaneously, to consider selection decisions for milk yield in the genetic evaluation of female fertility traits for obtaining more accurate estimating breeding values (EBV) and to acquire female fertility EBV for bulls evaluated for milk yield, but not for female fertility.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

PubMed

Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

Achromatical Optical Correlator

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Liu, Hua-Kuang

1989-01-01

Signal-to-noise ratio exceeds that of monochromatic correlator. Achromatical optical correlator uses multiple-pinhole diffraction of dispersed white light to form superposed multiple correlations of input and reference images in output plane. Set of matched spatial filters made by multiple-exposure holographic process, each exposure using suitably-scaled input image and suitable angle of reference beam. Recording-aperture mask translated to appropriate horizontal position for each exposure. Noncoherent illumination suitable for applications involving recognition of color and determination of scale. When fully developed achromatical correlators will be useful for recognition of patterns; for example, in industrial inspection and search for selected features in aerial photographs.

Progress on Ultra-Dense Quantum Communication Using Integrated Photonic Architecture

DTIC Science & Technology

2013-01-01

entanglement based quantum key distribution . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Extended dispersive-optics QKD (DO-QKD) protocol...2 2.3 Analysis of non-local correlations of entangled photon pairs for arbitrary dis- persion...Section 3). 2 Protocol Development 2.1 Achieving multiple secure bits per coincidence in time-energy entanglement based quantum key distribution High

Student Characteristics and Collegiate Environments That Contribute to the Overall Satisfaction with Academic Advising among College Students

ERIC Educational Resources Information Center

DeLaRosby, Hal R.

2017-01-01

Academic advising satisfaction is highly correlated with retention in higher education. Thriving Quotient survey responses were collected from undergraduate students at a private, liberal arts college in the Pacific Northwest. Using a multiple regression analysis, this study examined what "student characteristics" and "collegiate…

Quantification of the effects of quality investment on the Cost of Poor Quality: A quasi-experimental study

NASA Astrophysics Data System (ADS)

Tamimi, Abdallah Ibrahim

Quality management is a fundamental challenge facing businesses. This research attempted to quantify the effect of quality investment on the Cost of Poor Quality (COPQ) in an aerospace company utilizing 3 years of quality data at United Launch Alliance, a Boeing -- Lockheed Martin Joint Venture Company. Statistical analysis tools, like multiple regressions, were used to quantify the relationship between quality investments and COPQ. Strong correlations were evident by the high correlation coefficient R2 and very small p-values in multiple regression analysis. The models in the study helped produce an Excel macro that based on preset constraints, optimized the level of quality spending to minimize COPQ. The study confirmed that as quality investments were increased, the COPQ decreased steadily until a point of diminishing return was reached. The findings may be used to develop an approach to reduce the COPQ and enhance product performance. Achieving superior quality in rocket launching enhances the accuracy, reliability, and mission success of delivering satellites to their precise orbits in pursuit of knowledge, peace, and freedom while assuring safety for the end user.

Considerations for multiple hypothesis correlation on tactical platforms

NASA Astrophysics Data System (ADS)

Thomas, Alan M.; Turpen, James E.

2013-05-01

Tactical platforms benefit greatly from the fusion of tracks from multiple sources in terms of increased situation awareness. As a necessary precursor to this track fusion, track-to-track association, or correlation, must first be performed. The related measurement-to-track fusion problem has been well studied with multiple hypothesis tracking and multiple frame assignment methods showing the most success. The track-to-track problem differs from this one in that measurements themselves are not available but rather track state update reports from the measuring sensors. Multiple hypothesis, multiple frame correlation systems have previously been considered; however, their practical implementation under the constraints imposed by tactical platforms is daunting. The situation is further exacerbated by the inconvenient nature of reports from legacy sensor systems on bandwidth- limited communications networks. In this paper, consideration is given to the special difficulties encountered when attempting the correlation of tracks from legacy sensors on tactical aircraft. Those difficulties include the following: covariance information from reporting sensors is frequently absent or incomplete; system latencies can create temporal uncertainty in data; and computational processing is severely limited by hardware and architecture. Moreover, consideration is given to practical solutions for dealing with these problems in a multiple hypothesis correlator.

Comparisons of Office and 24-Hour Ambulatory Blood Pressure Monitoring in Children with Obstructive Sleep Apnea.

PubMed

Kang, Kun-Tai; Chiu, Shuenn-Nan; Weng, Wen-Chin; Lee, Pei-Lin; Hsu, Wei-Chung

2017-03-01

To compare office blood pressure (BP) and 24-hour ambulatory BP (ABP) monitoring to facilitate the diagnosis and management of hypertension in children with obstructive sleep apnea (OSA). Children aged 4-16 years with OSA-related symptoms were recruited from a tertiary referral medical center. All children underwent overnight polysomnography, office BP, and 24-hour ABP studies. Multiple linear regression analyses were applied to elucidate the association between the apnea-hypopnea index and BP. Correlation and consistency between office BP and 24-hour ABP were measured by Pearson correlation, intraclass correlation, and Bland-Altman analyses. In the 163 children enrolled (mean age, 8.2 ± 3.3 years; 67% male). The prevalence of systolic hypertension at night was significantly higher in children with moderate-to-severe OSA than in those with primary snoring (44.9% vs 16.1%, P = .006). Pearson correlation and intraclass correlation analyses revealed associations between office BP and 24-hour BP, and Bland-Altman analysis indicated an agreement between office and 24-hour BP measurements. However, multiple linear regression analyses demonstrated that 24-hour BP (nighttime systolic BP and mean arterial pressure), unlike office BP, was independently associated with the apnea-hypopnea index, after adjustment for adiposity variables. Twenty-four-hour ABP is more strongly correlated with OSA in children, compared with office BP. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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

PubMed

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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.

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

NASA Astrophysics Data System (ADS)

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. 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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. 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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.; CMS Collaboration

2018-03-01

The azimuthal anisotropy Fourier coefficients (vn) 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 p p and PbPb collisions. Using a four-particle cumulant technique, vn correlations are measured for the first time in p p and p +Pb collisions. The v2 and v4 coefficients are found to be positively correlated in all collision systems. For high-multiplicity p +Pb collisions, an anticorrelation of v2 and v3 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.

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

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

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

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

Do evoked potentials contribute to the functional follow-up and clinical prognosis of multiple sclerosis?

PubMed

Giffroy, Xavier; Maes, Nathalie; Albert, Adelin; Maquet, Pierre; Crielaard, Jean-Michel; Dive, Dominique

2017-03-01

The clinical variability and complexity of multiple sclerosis (MS) challenges the individual clinical course prognostication. This study aimed to find out whether multimodal evoked potentials (EP) correlate with the motor components of multiple sclerosis functional composite (MSFCm) and predict clinically relevant motor functional deterioration. One hundred MS patients were assessed at baseline (T 0 ) and about 7.5 years later (T 1 ), with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) and the MSFCm, including the 9 Hole Peg Test and the Timed 25 Foot Walk (T25FW). The Spearman correlation coefficient (r S ) was used to evaluate the cross-sectional and longitudinal relationship between EP Z scores and clinical findings. The predictive value of baseline electrophysiological data for clinical worsening (EDSS, 9-HPT, T25FW, MSFCm) during follow-up was assessed by logistic regression analysis. Unlike longitudinal correlations, cross-sectional correlations between EP Z scores and clinical outcomes were all significant and ranged between 0.22 and 0.67 (p < 0.05). The global EP Z score was systematically predictive of EDSS and MSFCm worsening over time (all p < 0.05). EP latency was a better predictor than amplitude, although weaker than latency and amplitude aggregation in the global EP Z score. The study demonstrates that EP numerical scores can be used for motor function monitoring and outcome prediction in patients with MS.

Deterioration of abstract reasoning ability in mild cognitive impairment and Alzheimer's disease: correlation with regional grey matter volume loss revealed by diffeomorphic anatomical registration through exponentiated lie algebra analysis.

PubMed

Yoshiura, Takashi; Hiwatashi, Akio; Yamashita, Koji; Ohyagi, Yasumasa; Monji, Akira; Takayama, Yukihisa; Kamano, Norihiro; Kawashima, Toshiro; Kira, Jun-Ichi; Honda, Hiroshi

2011-02-01

To determine which brain regions are relevant to deterioration in abstract reasoning as measured by Raven's Colored Progressive Matrices (CPM) in the context of dementia. MR images of 37 consecutive patients including 19 with Alzheimer's disease (AD) and 18 with amnestic mild cognitive impairment (aMCI) were retrospectively analyzed. All patients were administered the CPM. Regional grey matter (GM) volume was evaluated according to the regimens of voxel-based morphometry, during which a non-linear registration algorithm called Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra was employed. Multiple regression analyses were used to map the regions where GM volumes were correlated with CPM scores. The strongest correlation with CPM scores was seen in the left middle frontal gyrus while a region with the largest volume was identified in the left superior temporal gyrus. Significant correlations were seen in 14 additional regions in the bilateral cerebral hemispheres and right cerebellum. Deterioration of abstract reasoning ability in AD and aMCI measured by CPM is related to GM loss in multiple regions, which is in close agreement with the results of previous activation studies.

The Correlation Between Dislocations and Vacancy Defects Using Positron Annihilation Spectroscopy

NASA Astrophysics Data System (ADS)

Pang, Jinbiao; Li, Hui; Zhou, Kai; Wang, Zhu

2012-07-01

An analysis program for positron annihilation lifetime spectra is only applicable to isolated defects, but is of no use in the presence of defective correlations. Such limitations have long caused problems for positron researchers in their studies of complicated defective systems. In order to solve this problem, we aim to take a semiconductor material, for example, to achieve a credible average lifetime of single crystal silicon under plastic deformation at different temperatures using positron life time spectroscopy. By establishing reasonable positron trapping models with defective correlations and sorting out four lifetime components with multiple parameters, as well as their respective intensities, information is obtained on the positron trapping centers, such as the positron trapping rates of defects, the density of the dislocation lines and correlation between the dislocation lines, and the vacancy defects, by fitting with the average lifetime with the aid of Matlab software. These results give strong grounds for the existence of dislocation-vacancy correlation in plastically deformed silicon, and lay a theoretical foundation for the analysis of positron lifetime spectra when the positron trapping model involves dislocation-related defects.

Generalisation of the identity method for determination of high-order moments of multiplicity distributions with a software implementation

NASA Astrophysics Data System (ADS)

Maćkowiak-Pawłowska, Maja; Przybyła, Piotr

2018-05-01

The incomplete particle identification limits the experimentally-available phase space region for identified particle analysis. This problem affects ongoing fluctuation and correlation studies including the search for the critical point of strongly interacting matter performed on SPS and RHIC accelerators. In this paper we provide a procedure to obtain nth order moments of the multiplicity distribution using the identity method, generalising previously published solutions for n=2 and n=3. Moreover, we present an open source software implementation of this computation, called Idhim, that allows one to obtain the true moments of identified particle multiplicity distributions from the measured ones provided the response function of the detector is known.

Construct validity and frequency of euphoria sclerotica in multiple sclerosis.

PubMed

Fishman, Inna; Benedict, Ralph H B; Bakshi, Rohit; Priore, Roger; Weinstock-Guttman, Bianca

2004-01-01

Using the Neuropsychiatric Inventory (NPI), we studied euphoria and other behavioral changes in 75 consecutive, unselected multiple sclerosis (MS) patients and 25 healthy controls. We also assessed disease duration, clinical course, physical disability, personality, depression, insight, cognition, and caregiver distress. Factor analysis identified a cluster of symptoms--labeled euphoria/disinhibition--similar to the euphoria sclerotica syndrome originally described by Charcot and others. The euphoria/disinhibition factor score was elevated in 9% of patients and associated with secondary-progressive course, low agreeableness, poor insight, impaired cognition, and high caregiver distress. Thus, we used the NPI to validate the euphoria syndrome in multiple sclerosis (MS) and determined its frequency, and its neurological and psychological correlates.

Uterine Fibroids: Correlation of T2 Signal Intensity with Semiquantitative Perfusion MR Parameters in Patients Screened for MR-guided High-Intensity Focused Ultrasound Ablation.

PubMed

Kim, Young-Sun; Lee, Jeong-Won; Choi, Chel Hun; Kim, Byoung-Gie; Bae, Duk-Soo; Rhim, Hyunchul; Lim, Hyo Keun

2016-03-01

To evaluate the relationships between T2 signal intensity and semiquantitative perfusion magnetic resonance (MR) parameters of uterine fibroids in patients who were screened for MR-guided high-intensity focused ultrasound (HIFU) ablation. Institutional review board approval was granted, and informed consents were waived. One hundred seventy most symptom-relevant, nondegenerated uterine fibroids (mean diameter, 7.3 cm; range, 3.0-17.2 cm) in 170 women (mean age, 43.5 years; range, 24-56 years) undergoing screening MR examinations for MR-guided HIFU ablation from October 2009 to April 2014 were retrospectively analyzed. Fibroid signal intensity was assessed as the ratio of the fibroid T2 signal intensity to that of skeletal muscle. Parameters of semiquantitative perfusion MR imaging obtained during screening MR examination (peak enhancement, percentage of relative peak enhancement, time to peak [in seconds], wash-in rate [per seconds], and washout rate [per seconds]) were investigated to assess their relationships with T2 signal ratio by using multiple linear regression analysis. Correlations between T2 signal intensity and independently significant perfusion parameters were then evaluated according to fibroid type by using Spearman correlation test. Multiple linear regression analysis revealed that relative peak enhancement showed an independently significant correlation with T2 signal ratio (Β = 0.004, P < .001). Submucosal intracavitary (n = 20, ρ = 0.275, P = .240) and type III (n = 18, ρ = 0.082, P = .748) fibroids failed to show significant correlations between perfusion and T2 signal intensity, while significant correlations were found for all other fibroid types (ρ = 0.411-0.629, P < .05). In possible candidates for MR-guided HIFU ablation, the T2 signal intensity of nondegenerated uterine fibroids showed an independently significant positive correlation with relative peak enhancement in most cases, except those of submucosal intracavitary or type III fibroids.

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in telomere length will require further investigation regarding biological influence of exposure. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Modifiable Psychosocial Constructs Associated With Physical Activity Participation in People With Multiple Sclerosis: A Systematic Review and Meta-Analysis.

PubMed

Casey, Blathin; Coote, Susan; Shirazipour, Celina; Hannigan, Ailish; Motl, Robert; Martin Ginis, Kathleen; Latimer-Cheung, Amy

2017-07-01

To synthesize current knowledge of the modifiable psychosocial constructs associated with physical activity (PA) participation in people with multiple sclerosis. A search was conducted through October 2015 in 8 electronic databases: CINAHL, PubMed, SPORTDiscus, Web of Knowledge, MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and PsycINFO. Cohort and intervention studies were included if they (1) included an objective or subjective measure of PA; (2) measured at least 1 modifiable psychosocial construct; and (3) reported bivariate correlations (or these could be extracted) between the PA and psychosocial construct measures. A total of 13,867 articles were screened for inclusion, and 26 were included in the final analysis. Meta-analyses of correlations were conducted using the Hedges-Olkin method. Where a meta-analysis was not possible, results were reported descriptively. Meta-analyses indicated a pooled correlation coefficient between (1) objective PA and self-efficacy (n=7) of r=.30 (P<.0001), indicating a moderate, positive association; (2) subjective PA and self-efficacy (n=7) of r=.34 (P<.0001), indicating a moderate, positive association; (3) subjective PA and goal-setting (n=5) of r=.44 (P<.0001), indicating a moderate-to-large positive association; and 4) subjective PA and outcome expectancies (n=4) (physical: r=.13, P=.11; social: r=.19, P<.0001; self-evaluative: r=.27, P<.0001), indicating small-moderate positive associations. Other constructs such as measures of health beliefs, enjoyment, social support, and perceived benefits and barriers were reported to be significantly correlated with PA in individual studies, but the number of studies was not sufficient for a meta-analysis. Future PA interventions should continue to focus on the psychosocial constructs of self-efficacy and goal-setting. However, there is a need to explore the associations between other constructs outside those reported in this review. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Total energy expenditure in adults with cerebral palsy as assessed by doubly labeled water.

PubMed

Johnson, R K; Hildreth, H G; Contompasis, S H; Goran, M I

1997-09-01

To characterize total energy expenditure (TEE) in free-living adults with cerebral palsy (CP) using the doubly labeled water technique, and to determine those physiologic variables and characteristics of CP that were markers of TEE in adults with CP. TEE was measured using the doubly labeled water technique in 30 free-living adults with CP (12 women, 18 men). To determine the best markers of TEE, the following factors were examined: CP status, resting metabolic rate (RMR), anthropometric characteristics and body composition by means of dual-energy x-ray absorptiometry (DXA) and skinfold thickness measurements, energy cost of leisure-time activities, and oral-motor impairment. Means +/- standard deviations, t tests, Pearson product-moment correlation coefficients, Spearman rank correlation coefficients, chi 2, stepwise multiple-correlation regression analysis, and analysis of covariance were used to examine the relationships among variables of interest. TEE was highly variable in the sample (mean = 2,455 +/- 622 kcal/day for men and 1,986 +/- 363 kcal/day for women). Stepwise regression analysis showed that TEE was best predicted in the sample by RMR, percentage body fat determined by DXA, ambulation status, and sex (multiple R = .68, P = .003). When practical, easily measured variables were used, TEE was best predicted by height, ambulation status, percentage body fat by skinfold thickness measurements, and sex (multiple R = .61, P. = 018). The contribution of energy expended in physical activity to TEE was significantly higher in the ambulatory subjects than the nonambulatory subjects (25% vs 16%, respectively; P = .009). The high degree of variability in TEE, largely attributable to high interindividual variation in energy expended in physical activity, makes it difficult to provide general guidelines for energy requirements for adults with CP. Because ambulation status was an important predictor of TEE, it must be accounted for in estimating energy requirements in this population.

MR elastography in primary sclerosing cholangitis: correlating liver stiffness with bile duct strictures and parenchymal changes.

PubMed

Bookwalter, Candice A; Venkatesh, Sudhakar K; Eaton, John E; Smyrk, Thomas D; Ehman, Richard L

2018-04-07

To determine correlation of liver stiffness measured by MR Elastography (MRE) with biliary abnormalities on MR Cholangiopancreatography (MRCP) and MRI parenchymal features in patients with primary sclerosing cholangitis (PSC). Fifty-five patients with PSC who underwent MRI of the liver with MRCP and MRE were retrospectively evaluated. Two board-certified abdominal radiologists in agreement reviewed the MRI, MRCP, and MRE images. The biliary tree was evaluated for stricture, dilatation, wall enhancement, and thickening at segmental duct, right main duct, left main duct, and common bile duct levels. Liver parenchyma features including signal intensity on T2W and DWI, and hyperenhancement in arterial, portal venous, and delayed phase were evaluated in nine Couinaud liver segments. Atrophy or hypertrophy of segments, cirrhotic morphology, varices, and splenomegaly were scored as present or absent. Regions of interest were placed in each of the nine segments on stiffness maps wherever available and liver stiffness (LS) was recorded. Mean segmental LS, right lobar (V-VIII), left lobar (I-III, and IVA, IVB), and global LS (average of all segments) were calculated. Spearman rank correlation analysis was performed for significant correlation. Features with significant correlation were then analyzed for significant differences in mean LS. Multiple regression analysis of MRI and MRCP features was performed for significant correlation with elevated LS. A total of 439/495 segments were evaluated and 56 segments not included in MRE slices were excluded for correlation analysis. Mean segmental LS correlated with the presence of strictures (r = 0.18, p < 0.001), T2W hyperintensity (r = 0.38, p < 0.001), DWI hyperintensity (r = 0.30, p < 0.001), and hyperenhancement of segment in all three phases. Mean LS of atrophic and hypertrophic segments were significantly higher than normal segments (7.07 ± 3.6 and 6.67 ± 3.26 vs. 5.1 ± 3.6 kPa, p < 0.001). In multiple regression analysis, only the presence of segmental strictures (p < 0.001), T2W hyperintensity (p = 0.01), and segmental hypertrophy (p < 0.001) were significantly associated with elevated segmental LS. Only left ductal stricture correlated with left lobe LS (r = 0.41, p = 0.018). Global LS correlated significantly with CBD stricture (r = 0.31, p = 0.02), number of segmental strictures (r = 0.28, p = 0.04), splenomegaly (r = 0.56, p < 0.001), and varices (r = 0.58, p < 0.001). In PSC, there is low but positive correlation between segmental LS and segmental duct strictures. Segments with increased LS show T2 hyperintensity, DWI hyperintensity, and post-contrast hyperenhancement. Global liver stiffness shows a moderate correlation with number of segmental strictures and significantly correlates with spleen stiffness, splenomegaly, and varices.

A Bayesian Poisson-lognormal Model for Count Data for Multiple-Trait Multiple-Environment Genomic-Enabled Prediction.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H; Montesinos-López, José C; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat

2017-05-05

When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. Copyright © 2017 Montesinos-López et al.

VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

PubMed

Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

2017-10-02

Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

Comprehensive Deployment Method for Technical Characteristics Base on Multi-failure Modes Correlation Analysis

NASA Astrophysics Data System (ADS)

Zheng, W.; Gao, J. M.; Wang, R. X.; Chen, K.; Jiang, Y.

2017-12-01

This paper put forward a new method of technical characteristics deployment based on Reliability Function Deployment (RFD) by analysing the advantages and shortages of related research works on mechanical reliability design. The matrix decomposition structure of RFD was used to describe the correlative relation between failure mechanisms, soft failures and hard failures. By considering the correlation of multiple failure modes, the reliability loss of one failure mode to the whole part was defined, and a calculation and analysis model for reliability loss was presented. According to the reliability loss, the reliability index value of the whole part was allocated to each failure mode. On the basis of the deployment of reliability index value, the inverse reliability method was employed to acquire the values of technology characteristics. The feasibility and validity of proposed method were illustrated by a development case of machining centre’s transmission system.

Time irreversibility and intrinsics revealing of series with complex network approach

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Xia, Jianan; Wang, Jing

2018-06-01

In this work, we analyze time series on the basis of the visibility graph algorithm that maps the original series into a graph. By taking into account the all-round information carried by the signals, the time irreversibility and fractal behavior of series are evaluated from a complex network perspective, and considered signals are further classified from different aspects. The reliability of the proposed analysis is supported by numerical simulations on synthesized uncorrelated random noise, short-term correlated chaotic systems and long-term correlated fractal processes, and by the empirical analysis on daily closing prices of eleven worldwide stock indices. Obtained results suggest that finite size has a significant effect on the evaluation, and that there might be no direct relation between the time irreversibility and long-range correlation of series. Similarity and dissimilarity between stock indices are also indicated from respective regional and global perspectives, showing the existence of multiple features of underlying systems.

Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0

DOE PAGES

Huck, Kevin A.; Malony, Allen D.; Shende, Sameer; ...

2008-01-01

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis ofmore » individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.« less

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

PubMed

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

2017-12-01

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

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system.

PubMed

Nüesch, Corina; Roos, Elena; Pagenstert, Geert; Mündermann, Annegret

2017-05-24

Inertial sensor systems are becoming increasingly popular for gait analysis because their use is simple and time efficient. This study aimed to compare joint kinematics measured by the inertial sensor system RehaGait® with those of an optoelectronic system (Vicon®) for treadmill walking and running. Additionally, the test re-test repeatability of kinematic waveforms and discrete parameters for the RehaGait® was investigated. Twenty healthy runners participated in this study. Inertial sensors and reflective markers (PlugIn Gait) were attached according to respective guidelines. The two systems were started manually at the same time. Twenty consecutive strides for walking and running were recorded and each software calculated sagittal plane ankle, knee and hip kinematics. Measurements were repeated after 20min. Ensemble means were analyzed calculating coefficients of multiple correlation for waveforms and root mean square errors (RMSE) for waveforms and discrete parameters. After correcting the offset between waveforms, the two systems/models showed good agreement with coefficients of multiple correlation above 0.950 for walking and running. RMSE of the waveforms were below 5° for walking and below 8° for running. RMSE for ranges of motion were between 4° and 9° for walking and running. Repeatability analysis of waveforms showed very good to excellent coefficients of multiple correlation (>0.937) and RMSE of 3° for walking and 3-7° for running. These results indicate that in healthy subjects sagittal plane joint kinematics measured with the RehaGait® are comparable to those using a Vicon® system/model and that the measured kinematics have a good repeatability, especially for walking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

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

2016-02-01

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

A spatial analysis of health-related resources in three diverse metropolitan areas

PubMed Central

Smiley, Melissa J.; Diez Roux, Ana V.; Brines, Shannon J.; Brown, Daniel G.; Evenson, Kelly R.; Rodriguez, Daniel A.

2010-01-01

Few studies have investigated the spatial clustering of multiple health-related resources. We constructed 0.5-mile kernel densities of resources for census areas in New York City, NY (n=819 block groups), Baltimore, MD (n=737), and Winston-Salem, NC (n=169). Three of the four resource densities (supermarkets/produce stores, retail areas, and recreational facilities) tended to be correlated with each other, whereas park density was less consistently and sometimes negatively correlated with the others. Blacks were more likely to live in block groups with multiple low resource densities. Spatial regression models showed that block groups with higher proportions of black residents tended to have lower supermarket/produce, retail, and recreational facility densities, although these associations did not always achieve statistical significance. A measure that combined local and neighboring block group racial composition was often a stronger predictor of resources than the local measure alone. Overall, our results from three diverse U.S. cities show that health-related resources are not randomly distributed across space and that disadvantage in multiple domains often clusters with residential racial patterning. PMID:20478737

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

PubMed Central

Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

PubMed

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

2013-10-30

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

Verifying Identities of Plant-Based Multivitamins Using Phytochemical Fingerprinting in Combination with Multiple Bioassays.

PubMed

Lim, Yeni; Ahn, Yoon Hee; Yoo, Jae Keun; Park, Kyoung Sik; Kwon, Oran

2017-09-01

Sales of multivitamins have been growing rapidly and the concept of natural multivitamin, plant-based multivitamin, or both has been introduced in the market, leading consumers to anticipate additional health benefits from phytochemicals that accompany the vitamins. However, the lack of labeling requirements might lead to fraudulent claims. Therefore, the objective of this study was to develop a strategy to verify identity of plant-based multivitamins. Phytochemical fingerprinting was used to discriminate identities. In addition, multiple bioassays were performed to determine total antioxidant capacity. A statistical computation model was then used to measure contributions of phytochemicals and vitamins to antioxidant activities. Fifteen multivitamins were purchased from the local markets in Seoul, Korea and classified into three groups according to the number of plant ingredients. Pearson correlation analysis among antioxidant capacities, amount phenols, and number of plant ingredients revealed that ferric reducing antioxidant power (FRAP) and 2,2-diphenyl-1-picryhydrazyl (DPPH) assay results had the highest correlation with total phenol content. This suggests that FRAP and DPPH assays are useful for characterizing plant-derived multivitamins. Furthermore, net effect linear regression analysis confirmed that the contribution of phytochemicals to total antioxidant capacities was always relatively higher than that of vitamins. Taken together, the results suggest that phytochemical fingerprinting in combination with multiple bioassays could be used as a strategy to determine whether plant-derived multivitamins could provide additional health benefits beyond their nutritional value.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

Femoral anteversion assessment: Comparison of physical examination, gait analysis, and EOS biplanar radiography.

PubMed

Westberry, David E; Wack, Linda I; Davis, Roy B; Hardin, James W

2018-05-01

Multiple measurement methods are available to assess transverse plane alignment of the lower extremity. This study was performed to determine the extent of correlation between femoral anteversion assessment using simultaneous biplanar radiographs and three-dimensional modeling (EOS imaging), clinical hip rotation by physical examination, and dynamic hip rotation assessed by gait analysis. Seventy-seven patients with cerebral palsy (GMFCS Level I and II) and 33 neurologically typical children with torsional abnormalities completed a comprehensive gait analysis with same day biplanar anterior-posterior and lateral radiographs and three-dimensional transverse plane assessment of femoral anteversion. Correlations were determined between physical exam of hip rotation, EOS imaging of femoral anteversion, and transverse plane hip kinematics for this retrospective review study. Linear regression analysis revealed a weak relationship between physical examination measures of hip rotation and biplanar radiographic assessment of femoral anteversion. Similarly, poor correlation was found between clinical evaluation of femoral anteversion and motion assessment of dynamic hip rotation. Correlations were better in neurologically typical children with torsional abnormalities compared to children with gait dysfunction secondary to cerebral palsy. Dynamic hip rotation cannot be predicted by physical examination measures of hip range of motion or from three-dimensional assessment of femoral anteversion derived from biplanar radiographs. Copyright © 2018 Elsevier B.V. All rights reserved.

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

PubMed Central

Zhang, Juanjuan; Yan, Li; Fu, Wenlong; Yi, Jing; Chen, Yuzhi; Liu, Chuanhe; Xu, Dongqun; Wang, Qiang

2016-01-01

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = −19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = −0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China. PMID:27556031

Computerized margin and texture analyses for differentiating bacterial pneumonia and invasive mucinous adenocarcinoma presenting as consolidation.

PubMed

Koo, Hyun Jung; Kim, Mi Young; Koo, Ja Hwan; Sung, Yu Sub; Jung, Jiwon; Kim, Sung-Han; Choi, Chang-Min; Kim, Hwa Jung

2017-01-01

Radiologists have used margin characteristics based on routine visual analysis; however, the attenuation changes at the margin of the lesion on CT images have not been quantitatively assessed. We established a CT-based margin analysis method by comparing a target lesion with normal lung attenuation, drawing a slope to represent the attenuation changes. This approach was applied to patients with invasive mucinous adenocarcinoma (n = 40) or bacterial pneumonia (n = 30). Correlations among multiple regions of interest (ROIs) were obtained using intraclass correlation coefficient (ICC) values. CT visual assessment, margin and texture parameters were compared for differentiating the two disease entities. The attenuation and margin parameters in multiple ROIs showed excellent ICC values. Attenuation slopes obtained at the margins revealed a difference between invasive mucinous adenocarcinoma and pneumonia (P<0.001), and mucinous adenocarcinoma produced a sharply declining attenuation slope. On multivariable logistic regression analysis, pneumonia had an ill-defined margin (odds ratio (OR), 4.84; 95% confidence interval (CI), 1.26-18.52; P = 0.02), ground-glass opacity (OR, 8.55; 95% CI, 2.09-34.95; P = 0.003), and gradually declining attenuation at the margin (OR, 12.63; 95% CI, 2.77-57.51, P = 0.001). CT-based margin analysis method has a potential to act as an imaging parameter for differentiating invasive mucinous adenocarcinoma and bacterial pneumonia.

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors.

PubMed

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-02-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

Classification of multiple sclerosis patients by latent class analysis of magnetic resonance imaging characteristics.

PubMed

Zwemmer, J N P; Berkhof, J; Castelijns, J A; Barkhof, F; Polman, C H; Uitdehaag, B M J

2006-10-01

Disease heterogeneity is a major issue in multiple sclerosis (MS). Classification of MS patients is usually based on clinical characteristics. More recently, a pathological classification has been presented. While clinical subtypes differ by magnetic resonance imaging (MRI) signature on a group level, a classification of individual MS patients based purely on MRI characteristics has not been presented so far. To investigate whether a restricted classification of MS patients can be made based on a combination of quantitative and qualitative MRI characteristics and to test whether the resulting subgroups are associated with clinical and laboratory characteristics. MRI examinations of the brain and spinal cord of 50 patients were scored for 21 quantitative and qualitative characteristics. Using latent class analysis, subgroups were identified, for whom disease characteristics and laboratory measures were compared. Latent class analysis revealed two subgroups that mainly differed in the extent of lesion confluency and MRI correlates of neuronal loss in the brain. Demographics and disease characteristics were comparable except for cognitive deficits. No correlations with laboratory measures were found. Latent class analysis offers a feasible approach for classifying subgroups of MS patients based on the presence of MRI characteristics. The reproducibility, longitudinal evolution and further clinical or prognostic relevance of the observed classification will have to be explored in a larger and independent sample of patients.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

Spatial correlation of auroral zone geomagnetic variations

NASA Astrophysics Data System (ADS)

Jackel, B. J.; Davalos, A.

2016-12-01

Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.

Diversity in Pathways to Common Childhood Disruptive Behavior Disorders

PubMed Central

Martel, Michelle M.; Nikolas, Molly; Jernigan, Katherine; Friderici, Karen; Nigg, Joel T.

2014-01-01

Oppositional-Defiant Disorder (ODD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are highly comorbid, a phenomenon thought to be due to shared etiological factors and mechanisms. Little work has attempted to chart multiple-level-of-analysis pathways (i.e., simultaneously including biological, environmental, and trait influences) to ODD and ADHD, the goal of the present investigation. 559 children/adolescents (325 boys) between the ages of 6 and 18 participated in a multi-stage, comprehensive diagnostic procedure. 148 were classified as ODD; 309 were classified as ADHD, based on parent, teacher, and clinician ratings. Children provided buccal or salivary samples of DNA, assayed for select markers in DRD4 and 5HTT. Parents completed the Alabama Parenting Questionnaire and the California Q-Sort. Children completed the Child Perception of Interparental Conflict Scale. Correlational associations consistent with multiple-level-of-analysis pathways to ODD and ADHD emerged. For ODD, children with the short allele of the 5HTT promoter polymorphism had higher neuroticism and ODD symptoms regardless of level of self-blame in relation to inter-parental conflict, whereas children without this allele had more ODD symptoms only in the context of more self-blame for inter-parental conflict. For ADHD (and ODD), children homozygous for the long allele of DRD4 120bp insertion polymorphism had lower conscientiousness when exposed to inconsistent parenting, whereas children without this genotype were more resilient to effects of inconsistent discipline on conscientiousness. Thus, ODD and ADHD appear to demonstrate somewhat distinct correlational associations between etiological factors and mechanisms consistent with pathway models using a multiple-level-of-analysis approach. PMID:22584505

Analyses of flooding tolerance of soybean varieties at emergence and varietal differences in their proteomes.

PubMed

Nanjo, Yohei; Jang, Hee-Young; Kim, Hong-Sig; Hiraga, Susumu; Woo, Sun-Hee; Komatsu, Setsuko

2014-10-01

Flooding of fields due to heavy and/or continuous rainfall influences soybean production. To identify soybean varieties with flooding tolerance at the seedling emergence stage, 128 soybean varieties were evaluated using a flooding tolerance index, which is based on plant survival rates, the lack of apparent damage and lateral root development, and post-flooding radicle elongation rate. The soybean varieties were ranked according to their flooding tolerance index, and it was found that the tolerance levels of soybean varieties exhibit a continuum of differences between varieties. Subsequently, tolerant, moderately tolerant and sensitive varieties were selected and subjected to comparative proteomic analysis to clarify the tolerance mechanism. Proteomic analysis of the radicles, combined with correlation analysis, showed that the ratios of RNA binding/processing related proteins and flooding stress indicator proteins were significantly correlated with flooding tolerance index. The RNA binding/processing related proteins were positively correlated in untreated soybeans, whereas flooding stress indicator proteins were negatively correlated in flooded soybeans. These results suggest that flooding tolerance is regulated by mechanisms through multiple factors and is associated with abundance levels of the identified proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Deficiencies of Circulating Mucosal-associated Invariant T Cells and Natural Killer T Cells in Patients with Multiple Trauma.

PubMed

Jo, Young Goun; Choi, Hyun Jung; Kim, Jung Chul; Cho, Young Nan; Kang, Jeong Hwa; Jin, Hye Mi; Kee, Seung Jung; Park, Yong Wook

2017-05-01

Mucosal-associated invariant T (MAIT) cells and natural killer T (NKT) cells are known to play important roles in autoimmunity, infectious diseases and cancers. However, little is known about the roles of these invariant T cells in multiple trauma. The purposes of this study were to examine MAIT and NKT cell levels in patients with multiple trauma and to investigate potential relationships between these cell levels and clinical parameters. The study cohort was composed of 14 patients with multiple trauma and 22 non-injured healthy controls (HCs). Circulating MAIT and NKT cell levels in the peripheral blood were measured by flow cytometry. The severity of injury was categorised according to the scoring systems, such as Acute Physiology and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II, and Injury Severity Score (ISS). Circulating MAIT and NKT cell numbers were significantly lower in multiple trauma patients than in HCs. Linear regression analysis showed that circulating MAIT cell numbers were significantly correlated with age, APACHE II, SAPS II, ISS category, hemoglobin, and platelet count. NKT cell numbers in the peripheral blood were found to be significantly correlated with APACHE II, SAPS II, and ISS category. This study shows numerical deficiencies of circulating MAIT cells and NKT cells in multiple trauma. In addition, these invariant T cell deficiencies were found to be associated with disease severity. These findings provide important information for predicting the prognosis of multiple trauma. © 2017 The Korean Academy of Medical Sciences.

Effects of Correlated and Uncorrelated Gamma Rays on Neutron Multiplicity Counting

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

Cowles, Christian C.; Behling, Richard S.; Imel, George R.

Neutron multiplicity counting relies on time correlation between neutron events to assay the fissile mass, (α,n) to spontaneous fission neutron ratio, and neutron self-multiplication of samples. Gamma-ray sensitive neutron multiplicity counters may misidentify gamma rays as neutrons and therefore miscalculate sample characteristics. Time correlated and uncorrelated gamma-ray-like signals were added into gamma-ray free neutron multiplicity counter data to examine the effects of gamma ray signals being misidentified as neutron signals on assaying sample characteristics. Multiplicity counter measurements with and without gamma-ray-like signals were compared to determine the assay error associated with gamma-ray-like signals at various gamma-ray and neutron rates. Correlatedmore » and uncorrelated gamma-ray signals each produced consistent but different measurement errors. Correlated gamma-ray signals most strongly led to fissile mass overestimates, whereas uncorrelated gamma-ray signals most strongly lead to (α,n) neutron overestimates. Gamma-ray sensitive neutron multiplicity counters may be able to account for the effects of gamma-rays on measurements to mitigate measurement uncertainties.« less

Body mass index is an independent risk factor for the development of endometrial polyps in patients undergoing in vitro fertilization.

PubMed

Onalan, Reside; Onalan, Gogsen; Tonguc, Esra; Ozdener, Tulin; Dogan, Muammer; Mollamahmutoglu, Leyla

2009-04-01

To determine the subgroup of patients in whom office hysteroscopy should be routinely performed before an in vitro fertilization (IVF) program. Retrospective cohort analysis. Tertiary education and research hospital. Two hundred twenty-three patients who underwent a uterine evaluation by office hysteroscopy before the IVF and embryo transfer cycle. The office hysteroscopy was performed in the follicular phase of the menstrual cycle before the IVF cycle. The office findings: number of polyps, number of multiple polyps, and polyp size. Patients with polycystic ovary syndrome (PCOS) had a higher number of endometrial polyps, but the difference was not statistically significant (28.9% vs. 18.3%). When comparing the patients according to BMI, patients with BMI >or=30 had a statistically significantly higher number of endometrial polyps versus BMI <30 (52% vs. 15%). On the other hand, obesity was positively correlated with the occurrence of polyps, size of the polyps, and occurrence of multiple number of polyps in the correlation analysis. In addition, logistic regression analysis using age, obesity, duration of infertility, and estradiol levels revealed that obesity was an independent prognostic factor for the development of endometrial polyps. Office hysteroscopy should be performed in patients with BMI >or=30 because obesity may act as an initiator for the pathogenesis of endometrial polyps.

Chemometric investigation of light-shade effects on essential oil yield and morphology of Moroccan Myrtus communis L.

PubMed

Fadil, Mouhcine; Farah, Abdellah; Ihssane, Bouchaib; Haloui, Taoufik; Lebrazi, Sara; Zghari, Badreddine; Rachiq, Saâd

2016-01-01

To investigate the effect of environmental factors such as light and shade on essential oil yield and morphological traits of Moroccan Myrtus communis, a chemometric study was conducted on 20 individuals growing under two contrasting light environments. The study of individual's parameters by principal component analysis has shown that essential oil yield, altitude, and leaves thickness were positively correlated between them and negatively correlated with plants height, leaves length and leaves width. Principal component analysis and hierarchical cluster analysis have also shown that the individuals of each sampling site were grouped separately. The one-way ANOVA test has confirmed the effect of light and shade on essential oil yield and morphological parameters by showing a statistically significant difference between them from the shaded side to the sunny one. Finally, the multiple linear model containing main, interaction and quadratic terms was chosen for the modeling of essential oil yield in terms of morphological parameters. Sun plants have a small height, small leaves length and width, but they are thicker and richer in essential oil than shade plants which have shown almost the opposite. The highlighted multiple linear model can be used to predict essential oil yield in the studied area.

ECOPASS - a multivariate model used as an index of growth performance of poplar clones

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

Ceulemans, R.; Impens, I.

The model (ECOlogical PASSport) reported was constructed by principal component analysis from a combination of biochemical, anatomical/morphological and ecophysiological gas exchange parameters measured on 5 fast growing poplar clones. Productivity data were 10 selected trees in 3 plantations in Belgium and given as m.a.i.(b.a.). The model is shown to be able to reflect not only genetic origin and the relative effects of the different parameters of the clones, but also their production potential. Multiple regression analysis of the 4 principal components showed a high cumulative correlation (96%) between the 3 components related to ecophysiological, biochemical and morphological parameters, and productivity;more » the ecophysiological component alone correlated 85% with productivity.« less

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

Factor Structure of the Revised TOEIC[R] Test: A Multiple-Sample Analysis

ERIC Educational Resources Information Center

In'nami, Yo; Koizumi, Rie

2012-01-01

This study examined the factor structure of the listening and reading sections of the revised Test of English for International Communication (TOEIC[R]) test. The data from the TOEIC IP (institutional program) test taken by 569 English learners were randomly split into two samples (n = 285 vs. 284). Four models (higher-order, correlated,…

The Counseling Opportunity Structure: Examining Correlates of Four-Year College-Going Rates

ERIC Educational Resources Information Center

Engberg, Mark E.; Gilbert, Aliza J.

2014-01-01

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…

High- and Low-Achieving Fraternity Environments at a Selective Institution: Their Influence on Members' Binge Drinking and GPA

ERIC Educational Resources Information Center

Maholchic-Nelson, Suzy

2010-01-01

This correlational study tested the efficacy of the social-ecological theory (Moos, 1979) by employing the University Residential Environmental Scale and multiple regression analysis to examine the influences of personal attributes (SAT, parents' level of education, race/ethnicity, and high school drinking) and environmental factors (high/low…

Math Talk and Representations in Elementary Classrooms of Beginning Teachers: A MLM Exploratory Analysis

ERIC Educational Resources Information Center

Alnizami, Reema

2017-01-01

This study examined the math talk and the use of multiple representations in elementary classrooms of 134 beginning teachers, all in their second year of teaching. A quantitative correlational research design was employed to investigate the research questions. The data were collected using a log instrument, the Instructional Practices Log in…

Methods for Improving Information from "Undesigned" Human Factors Experiments. Technical Report No. p75-287.

ERIC Educational Resources Information Center

Simon, Charles W.

An "undesigned" experiment is one in which the predictor variables are correlated, either due to a failure to complete a design or because the investigator was unable to select or control relevant experimental conditions. The traditional method of analyzing this class of experiment--multiple regression analysis based on a least squares…

Influence of Particle Theory Conceptions on Pre-Service Science Teachers' Understanding of Osmosis and Diffusion

ERIC Educational Resources Information Center

AlHarbi, Nawaf N. S.; Treagust, David F.; Chandrasegaran, A. L.; Won, Mihye

2015-01-01

This study investigated the understanding of diffusion, osmosis and particle theory of matter concepts among 192 pre-service science teachers in Saudi Arabia using a 17-item two-tier multiple-choice diagnostic test. The data analysis showed that the pre-service teachers' understanding of osmosis and diffusion concepts was mildly correlated with…

Exploring the Impact of Undergraduate Intramural Sports on Undergraduate Students' Perceived Sense of Community: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Penland, Nathan Paul

2017-01-01

Research has shown benefits to the student experience for college students when they participate in intramural sports on university campuses. These benefits include improved physical and social health as well as academic performance. This non-experimental, predictive correlational study sought to understand if a relationship exists between the…

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

[Life satisfaction and related socio-demographic factors during female midlife].

PubMed

Cuadros, José Luis; Pérez-Roncero, Gonzalo R; López-Baena, María Teresa; Cuadros-Celorrio, Angela M; Fernández-Alonso, Ana María

2014-01-01

To assess life satisfaction and related factors in middle-aged Spanish women. This was a cross-sectional study including 235 women aged 40 to 65, living in Granada (Spain), healthy companions of patients visiting the obstetrics and gynecology clinics. They completed the Diener Satisfaction with Life Scale, the Menopause Rating Scale, the Perceived Stress Scale, the Insomnia Severity Index and a sociodemographic questionnaire containing personal and partner data. Internal consistency of each tool was also calculated. Almost two-thirds (61.3%) of the women were postmenopausal, and 43.8% had abdominal obesity, 36.6% had insomnia, 18.7% had poor menopause-related quality of life, 31.9% performed regular exercise, and 5.1% had severe financial problems. Life satisfaction showed significant positive correlations (Spearman's test) with female and male age, and inverse correlations with menopause-related quality of life, perceived stress and insomnia. In the multiple linear regression analysis, high life satisfaction is positively correlated with having a partner who performed exercise, and inversely with having work problems, perceived stress and the suspicion of partner infidelity. These factors explained 40% of the variance of the multiple regression analysis for life satisfaction in middle-aged women. Life satisfaction is a construct related to perceived stress, work problems, and having a partner, while aspects of menopause and general health had no significant influence. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Relationship between pelvic incidence and osteoarthritis of the hip

PubMed Central

Weinberg, D. S.; Bohl, M. S.; Liu, R. W.

2016-01-01

Objectives Sagittal alignment of the lumbosacral spine, and specifically pelvic incidence (PI), has been implicated in the development of spine pathology, but generally ignored with regards to diseases of the hip. We aimed to determine if increased PI is correlated with higher rates of hip osteoarthritis (HOA). The effect of PI on the development of knee osteoarthritis (KOA) was used as a negative control. Methods We studied 400 well-preserved cadaveric skeletons ranging from 50 to 79 years of age at death. Each specimen’s OA of the hip and knee were graded using a previously described method. PI was measured from standardised lateral photographs of reconstructed pelvises. Multiple regression analysis was performed to determine the relationship between age and PI with HOA and KOA. Results The mean age was 60.2 years (standard deviation (sd) 8.1), and the mean PI was 46.7° (sd 10.7°). Multiple regression analysis demonstrated a significant correlation between increased PI and HOA (standardised beta = 0.103, p = 0.017). There was no correlation between PI and KOA (standardised beta = 0.003, p = 0.912). Conclusion Higher PI in the younger individual may contribute to the development of HOA in later life. Cite this article: Dr J. J. Gebhart. Relationship between pelvic incidence and osteoarthritis of the hip. Bone Joint Res 2016;5:66–72. DOI: 10.1302/2046-3758.52.2000552. PMID:26912384

Lesion symptom map of cognitive-postural interference in multiple sclerosis.

PubMed

Ruggieri, Serena; Fanelli, Fulvia; Castelli, Letizia; Petsas, Nikolaos; De Giglio, Laura; Prosperini, Luca

2018-04-01

To investigate the disease-altered structure-function relationship underlying the cognitive-postural interference (CPI) phenomenon in multiple sclerosis (MS). We measured postural sway of 96 patients and 48 sex-/age-matched healthy controls by force platform in quiet standing (single-task (ST)) while performing the Stroop test (dual-task (DT)) to estimate the dual-task cost (DTC) of balance. In patient group, binary T2 and T1 lesion masks and their corresponding lesion volumes were obtained from magnetic resonance imaging (MRI) of brain. Normalized brain volume (NBV) was also estimated by SIENAX. Correlations between DTC and lesion location were determined by voxel-based lesion symptom mapping (VLSM) analyses. Patients had greater DTC than controls ( p < 0.001). Among whole brain MRI metrics, only T1 lesion volume correlated with DTC ( r = -0.27; p < 0.01). However, VLSM analysis did not reveal any association with DTC using T1 lesion masks. By contrast, we found clusters of T2 lesions in distinct anatomical regions (anterior and superior corona radiata, bilaterally) to be correlated with DTC ( p < 0.01 false discovery rate (FDR)-corrected). A multivariable stepwise regression model confirmed findings from VLSM analysis. NBV did not contribute to fit the model. Our findings suggest that the CPI phenomenon in MS can be explained by disconnection along specific areas implicated in task-switching abilities and divided attention.

Plasma cell quantification in bone marrow by computer-assisted image analysis.

PubMed

Went, P; Mayer, S; Oberholzer, M; Dirnhofer, S

2006-09-01

Minor and major criteria for the diagnosis of multiple meloma according to the definition of the WHO classification include different categories of the bone marrow plasma cell count: a shift from the 10-30% group to the > 30% group equals a shift from a minor to a major criterium, while the < 10% group does not contribute to the diagnosis. Plasma cell fraction in the bone marrow is therefore critical for the classification and optimal clinical management of patients with plasma cell dyscrasias. The aim of this study was (i) to establish a digital image analysis system able to quantify bone marrow plasma cells and (ii) to evaluate two quantification techniques in bone marrow trephines i.e. computer-assisted digital image analysis and conventional light-microscopic evaluation. The results were compared regarding inter-observer variation of the obtained results. Eighty-seven patients, 28 with multiple myeloma, 29 with monoclonal gammopathy of undetermined significance, and 30 with reactive plasmocytosis were included in the study. Plasma cells in H&E- and CD138-stained slides were quantified by two investigators using light-microscopic estimation and computer-assisted digital analysis. The sets of results were correlated with rank correlation coefficients. Patients were categorized according to WHO criteria addressing the plasma cell content of the bone marrow (group 1: 0-10%, group 2: 11-30%, group 3: > 30%), and the results compared by kappa statistics. The degree of agreement in CD138-stained slides was higher for results obtained using the computer-assisted image analysis system compared to light microscopic evaluation (corr.coeff. = 0.782), as was seen in the intra- (corr.coeff. = 0.960) and inter-individual results correlations (corr.coeff. = 0.899). Inter-observer agreement for categorized results (SM/PW: kappa 0.833) was in a high range. Computer-assisted image analysis demonstrated a higher reproducibility of bone marrow plasma cell quantification. This might be of critical importance for diagnosis, clinical management and prognostics when plasma cell numbers are low, which makes exact quantifications difficult.

[Resting metabolic rate estimated by bioelectrical impedance analysis and its determinants in maintenance hemodialysis patients].

PubMed

Da, J J; Peng, H Y; Lin, X; Shen, Y; Zhao, J Q; He, S; Zha, Y

2018-03-27

Objective: To explore the level of resting energy expenditure (REE) estimated by bioelectrical impedance analysis and the association of resting metabolic rate (RMR) with clinical related factors, and provide new ideas for improving protein energy wasting (PEW) in maintenance hemodialysis (MHD) patients. Methods: Seven hundred and sixty-five subjects receiving MHD between July 2015 and September 2016 in 11 hemodialysis centers in Guizhou province were enrolled in this cross-sectional study. Bioelectrical impedance analysis was used to measure RMR and body composition, such as lean body mass, fat mass and body cell mass (BCM). Baseline characteristics, routine blood test indexes and biochemical data of hemodialysis patients were collected. The level of RMR and body composition in hemodialysis patients was compared by gender grouping. Then the patients were divided into four groups according to the cutoff value of RMR quartile. Spearman correlation analysis and multiple linear regression analysis were used to analyze the relationships between RMR and clinical related factors. Results: The average age of MHD patients was (54.96±15.78) years and the duriation of dialysis was (42.3±9.0) months. The level of RMR in male patients (474 cases, 61.96%) was significantly higher than that in female patients [1 591(1 444, 1 764) kcal/d vs 1 226 (1 104, 1 354) kcal/d, P <0.001]. However, this significant difference of RMR between different genders disappeared after adjusting for lean body mass ( P =0.193). Multiple linear regression analysis showed that RMR was positively correlated with body surface area (β=0.817) and lactate dehydrogenase (LDH) (β=0.198), and negatively correlated with age (β=-0.141), all P <0.05. Conclusion: RMR levels in patients with maintenance hemodialysis are associated with lactate dehydrogenase level, which may become a new index to evaluate energy consumption.

Mapping Resting-State Brain Networks in Conscious Animals

PubMed Central

Zhang, Nanyin; Rane, Pallavi; Huang, Wei; Liang, Zhifeng; Kennedy, David; Frazier, Jean A.; King, Jean

2010-01-01

In the present study we mapped brain functional connectivity in the conscious rat at the “resting state” based on intrinsic blood-oxygenation-level dependent (BOLD) fluctuations. The conscious condition eliminated potential confounding effects of anesthetic agents on the connectivity between brain regions. Indeed, using correlational analysis we identified multiple cortical and subcortical regions that demonstrated temporally synchronous variation with anatomically well-defined regions that are crucial to cognitive and emotional information processing including the prefrontal cortex (PFC), thalamus and retrosplenial cortex. The functional connectivity maps created were stringently validated by controlling for false positive detection of correlation, the physiologic basis of the signal source, as well as quantitatively evaluating the reproducibility of maps. Taken together, the present study has demonstrated the feasibility of assessing functional connectivity in conscious animals using fMRI and thus provided a convenient and non-invasive tool to systematically investigate the connectional architecture of selected brain networks in multiple animal models. PMID:20382183

ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

NASA Astrophysics Data System (ADS)

Roberts, D. Aaron; Boller, Ryan; Rezapkin, V.; Coleman, J.; McGuire, R.; Goldstein, M.; Kalb, V.; Kulkarni, R.; Luckyanova, M.; Byrnes, J.; Kerbel, U.; Candey, R.; Holmes, C.; Chimiak, R.; Harris, B.

2018-04-01

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

EEG and MEG source localization using recursively applied (RAP) MUSIC

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

Mosher, J.C.; Leahy, R.M.

1996-12-31

The multiple signal characterization (MUSIC) algorithm locates multiple asynchronous dipolar sources from electroencephalography (EEG) and magnetoencephalography (MEG) data. A signal subspace is estimated from the data, then the algorithm scans a single dipole model through a three-dimensional head volume and computes projections onto this subspace. To locate the sources, the user must search the head volume for local peaks in the projection metric. Here we describe a novel extension of this approach which we refer to as RAP (Recursively APplied) MUSIC. This new procedure automatically extracts the locations of the sources through a recursive use of subspace projections, which usesmore » the metric of principal correlations as a multidimensional form of correlation analysis between the model subspace and the data subspace. The dipolar orientations, a form of `diverse polarization,` are easily extracted using the associated principal vectors.« less

Importance of initial and final state effects for azimuthal correlations in p + Pb collisions

DOE PAGES

Greif, Moritz; Greiner, Carsten; Schenke, Bjorn; ...

2017-11-27

In this work, we investigate the relative importance of initial and final state effects on azimuthal correlations of gluons in low and high multiplicity p+Pb collisions. To achieve this, we couple Yang-Mills dynamics of pre-equilibrium gluon fields (IP-GLASMA) to a perturbative QCD based parton cascade for the final state evolution (BAMPS) on an event-by-event basis. We find that signatures of both the initial state correlations and final state interactions are seen in azimuthal correlation observables, such as v 2 {2PC} (p T), their strength depending on the event multiplicity and transverse momentum. Initial state correlations dominate v 2 {2PC} (pmore » T) in low multiplicity events for transverse momenta p T > 2 GeV. Lastly, while final state interactions are dominant in high multiplicity events, initial state correlations affect v 2 {2PC} (p T) for p T > 2 GeV as well as the pT integrated v 2 {2PC}.« less

Importance of initial and final state effects for azimuthal correlations in p + Pb collisions

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

Greif, Moritz; Greiner, Carsten; Schenke, Bjorn

In this work, we investigate the relative importance of initial and final state effects on azimuthal correlations of gluons in low and high multiplicity p+Pb collisions. To achieve this, we couple Yang-Mills dynamics of pre-equilibrium gluon fields (IP-GLASMA) to a perturbative QCD based parton cascade for the final state evolution (BAMPS) on an event-by-event basis. We find that signatures of both the initial state correlations and final state interactions are seen in azimuthal correlation observables, such as v 2 {2PC} (p T), their strength depending on the event multiplicity and transverse momentum. Initial state correlations dominate v 2 {2PC} (pmore » T) in low multiplicity events for transverse momenta p T > 2 GeV. Lastly, while final state interactions are dominant in high multiplicity events, initial state correlations affect v 2 {2PC} (p T) for p T > 2 GeV as well as the pT integrated v 2 {2PC}.« less

Chronic atrophic gastritis in association with hair mercury level.

PubMed

Xue, Zeyun; Xue, Huiping; Jiang, Jianlan; Lin, Bing; Zeng, Si; Huang, Xiaoyun; An, Jianfu

2014-11-01

The objective of this study was to explore hair mercury level in association with chronic atrophic gastritis, a precancerous stage of gastric cancer (GC), and thus provide a brand new angle of view on the timely intervention of precancerous stage of GC. We recruited 149 healthy volunteers as controls and 152 patients suffering from chronic gastritis as cases. The controls denied upper gastrointestinal discomforts, and the cases were diagnosed as chronic superficial gastritis (n=68) or chronic atrophic gastritis (n=84). We utilized Mercury Automated Analyzer (NIC MA-3000) to detect hair mercury level of both healthy controls and cases of chronic gastritis. The statistic of measurement data was expressed as mean ± standard deviation, which was analyzed using Levene variance equality test and t test. Pearson correlation analysis was employed to determine associated factors affecting hair mercury levels, and multiple stepwise regression analysis was performed to deduce regression equations. Statistical significance is considered if p value is less than 0.05. The overall hair mercury level was 0.908949 ± 0.8844490 ng/g [mean ± standard deviation (SD)] in gastritis cases and 0.460198 ± 0.2712187 ng/g (mean±SD) in healthy controls; the former level was significantly higher than the latter one (p=0.000<0.01). The hair mercury level in chronic atrophic gastritis subgroup was 1.155220 ± 0.9470246 ng/g (mean ± SD) and that in chronic superficial gastritis subgroup was 0.604732 ± 0.6942509 ng/g (mean ± SD); the former level was significantly higher than the latter level (p<0.01). The hair mercury level in chronic superficial gastritis cases was significantly higher than that in healthy controls (p<0.05). The hair mercury level in chronic atrophic gastritis cases was significantly higher than that in healthy controls (p<0.01). Stratified analysis indicated that the hair mercury level in healthy controls with eating seafood was significantly higher than that in healthy controls without eating seafood (p<0.01) and that the hair mercury level in chronic atrophic gastritis cases was significantly higher than that in chronic superficial gastritis cases (p<0.01). Pearson correlation analysis indicated that eating seafood was most correlated with hair mercury level and positively correlated in the healthy controls and that the severity of gastritis was most correlated with hair mercury level and positively correlated in the gastritis cases. Multiple stepwise regression analysis indicated that the regression equation of hair mercury level in controls could be expressed as 0.262 multiplied the value of eating seafood plus 0.434, the model that was statistically significant (p<0.01). Multiple stepwise regression analysis also indicated that the regression equation of hair mercury level in gastritis cases could be expressed as 0.305 multiplied the severity of gastritis, the model that was also statistically significant (p<0.01). The graphs of regression standardized residual for both controls and cases conformed to normal distribution. The main positively correlated factor affecting the hair mercury level is eating seafood in healthy people whereas the predominant positively correlated factor affecting the hair mercury level is the severity of gastritis in chronic gastritis patients. That is to say, the severity of chronic gastritis is positively correlated with the level of hair mercury. The incessantly increased level of hair mercury possibly reflects the development of gastritis from normal stomach to superficial gastritis and to atrophic gastritis. The detection of hair mercury is potentially a means to predict the severity of chronic gastritis and possibly to insinuate the environmental mercury threat to human health in terms of gastritis or even carcinogenesis.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders.

PubMed

Scarella, Timothy M; Laferton, Johannes A C; Ahern, David K; Fallon, Brian A; Barsky, Arthur

2016-01-01

Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric comorbidity in hypochondriasis (HC) and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Data were collected as part of a clinical trial on treatment methods for HC. In all, 194 participants meeting criteria for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) HC were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Most of the individuals with HC had comorbid psychiatric illness; the mean number of comorbid diagnoses was 1.4, and 35.1% had HC as their only diagnosis. Participants were more likely to have only comorbid anxiety disorders than only comorbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Our findings suggest that the entity of health anxiety (HC in DSM-IV and illness anxiety disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of comorbidity patterns and continuous measures of symptoms suggest that its appropriate classification is with anxiety rather than somatoform or mood disorders. Copyright © 2016 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

The effect of orthostatic stress on multiscale entropy of heart rate and blood pressure.

PubMed

Turianikova, Zuzana; Javorka, Kamil; Baumert, Mathias; Calkovska, Andrea; Javorka, Michal

2011-09-01

Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

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.

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

PubMed Central

Kim, Dahan; Curthoys, Nikki M.; Parent, Matthew T.; Hess, Samuel T.

2015-01-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. PMID:26185614

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy.

PubMed

Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

2013-09-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined.

Tracking quasi-stationary flow of weak fluorescent signals by adaptive multi-frame correlation.

PubMed

Ji, L; Danuser, G

2005-12-01

We have developed a novel cross-correlation technique to probe quasi-stationary flow of fluorescent signals in live cells at a spatial resolution that is close to single particle tracking. By correlating image blocks between pairs of consecutive frames and integrating their correlation scores over multiple frame pairs, uncertainty in identifying a globally significant maximum in the correlation score function has been greatly reduced as compared with conventional correlation-based tracking using the signal of only two consecutive frames. This approach proves robust and very effective in analysing images with a weak, noise-perturbed signal contrast where texture characteristics cannot be matched between only a pair of frames. It can also be applied to images that lack prominent features that could be utilized for particle tracking or feature-based template matching. Furthermore, owing to the integration of correlation scores over multiple frames, the method can handle signals with substantial frame-to-frame intensity variation where conventional correlation-based tracking fails. We tested the performance of the method by tracking polymer flow in actin and microtubule cytoskeleton structures labelled at various fluorophore densities providing imagery with a broad range of signal modulation and noise. In applications to fluorescent speckle microscopy (FSM), where the fluorophore density is sufficiently low to reveal patterns of discrete fluorescent marks referred to as speckles, we combined the multi-frame correlation approach proposed above with particle tracking. This hybrid approach allowed us to follow single speckles robustly in areas of high speckle density and fast flow, where previously published FSM analysis methods were unsuccessful. Thus, we can now probe cytoskeleton polymer dynamics in living cells at an entirely new level of complexity and with unprecedented detail.

Monitoring Changes of Ecosystem Services Supply and Demand Pattern in Central and Southern Liaoning Urban Agglomerations, China Using Landsat Images

NASA Astrophysics Data System (ADS)

Li, B.; Huang, F.; Chang, S.; Qi, H.; Zhai, H.

2018-04-01

Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93 %, whereas IMESd dropped 38 %. The undersupplied area was reduced to 2. The IMESs and IMESb were mainly negatively correlated with gross domestic product (GDP), population density, foreign investment and industrial output, while GDP per capita and the number of teachers had significant positive impacts on ecosystem services supply. The positive correlation between IMESd and GDP, population density and foreign investment were found. The ecosystem services models were established. Supply and balance of multiple-ecosystem services were positively correlated with population density, but the demand was the opposite. The results can provide some reference value for the coordinately economic and ecological development in the study area.

Multivariate objective response detectors (MORD): statistical tools for multichannel EEG analysis during rhythmic stimulation.

PubMed

Felix, Leonardo Bonato; Miranda de Sá, Antonio Mauricio Ferreira Leite; Infantosi, Antonio Fernando Catelli; Yehia, Hani Camille

2007-03-01

The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).

Prediction of jump phenomena in roll-coupled maneuvers of airplanes

NASA Technical Reports Server (NTRS)

Schy, A. A.; Hannah, M. E.

1976-01-01

An easily computerized analytical method is developed for identifying critical airplane maneuvers in which nonlinear rotational coupling effects may cause sudden jumps in the response to pilot's control inputs. Fifth and ninth degree polynomials for predicting multiple pseudo-steady states of roll-coupled maneuvers are derived. The program calculates the pseudo-steady solutions and their stability. The occurrence of jump-like responses for several airplanes and a variety of maneuvers is shown to correlate well with the appearance of multiple stable solutions for critical control combinations. The analysis is extended to include aerodynamics nonlinear in angle of attack.

Teachers' Experiences with Multiple Victimization: Identifying Demographic, Cognitive, and Contextual Correlates

ERIC Educational Resources Information Center

Martinez, Andrew; McMahon, Susan D.; Espelage, Dorothy; Anderman, Eric M.; Reddy, Linda A.; Sanchez, Bernadette

2016-01-01

Extant scholarship has primarily examined demographic predictors of teacher victimization. Teacher multiple victimization, or the extent to which teachers experience multiple types of violence, has not been examined. Using social-ecological theory, we examine correlates of violence among 2,324 teachers who reported having been victimized at least…

The Correlation of Multiple Intelligences for the Achievements of Secondary Students

ERIC Educational Resources Information Center

Ahvan, Yaghoob Raissi; Pour, Hossein Zainali

2016-01-01

The present study attempts to investigate the relationship between the multiple intelligences and the academic performance achievement levels of high school students based on Gardner's multiple intelligences theory. This was a descriptive correlation study. To accomplish this purpose, 270 students of high school of Bandar Abbas selected by…

Physical inactivity, neurological disability, and cardiorespiratory fitness in multiple sclerosis.

PubMed

Motl, R W; Goldman, M

2011-02-01

We examined the associations among physical activity, neurological disability, and cardiorespiratory fitness in two studies of individuals with multiple sclerosis (MS). Study 1 included 25 women with relapsing-remitting MS (RRMS) who undertook an incremental exercise test for measuring peak oxygen (VO₂(peak) ) consumption, wore an accelerometer during a 7-day period, and completed the Godin Leisure-Time Exercise Questionnaire (GLTEQ). Study 2 was a follow-up of Study 1 and included 24 women with RRMS who completed the self-reported Expanded Disability Status Scale (EDSS), undertook an incremental exercise test, wore an accelerometer during a 7-day period, and completed the GLTEQ. Study 1 indicated that VO₂(peak) was significantly correlated with accelerometer counts (pr = 0.69) and GLTEQ scores (pr = 0.63) even after controlling for age and MS duration. Study 2 indicated that VO₂(peak) was significantly correlated with accelerometer counts (pr = 0.50), GLTEQ scores (pr = 0.59), and EDSS scores (pr = -0.43) even after controlling for age and MS duration; there was a moderate partial correlation between accelerometer counts and EDSS scores (pr = -0.43). Multiple linear regression analysis indicated that both accelerometer counts (β = 0.32) and EDSS scores (β = -0.40) had statistically significant associations with VO₂(peak). The findings indicate that physical inactivity and neurological disability might represent independent risk factors for reduced levels of cardiorespiratory fitness in this population. © 2010 John Wiley & Sons A/S.

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Intercellular adhesion molecule, plasma adiponectin and albuminuria in type 2 diabetic patients.

PubMed

Lenghel, Alina Ramona; Kacso, Ina Maria; Bondor, Cosmina Ioana; Rusu, Crina; Rahaian, Rodica; Gherman Caprioara, Mirela

2012-01-01

Our study addressed the influence of early inflammatory stages of diabetic kidney disease: leukocyte adhesion and monocyte activation (as assessed by intercellular leukocyte adhesion molecule-ICAM-1 and monocyte chemoatractant protein-MCP-1) on the degree of albuminuria. Plasma levels of adiponectin, a possible anti-inflammatory counteracting mechanism, were also studied in correlation to the above-mentioned cytokines. 79 consecutive type 2 diabetic outpatients and 46 controls were included. Routine laboratory analysis, urinary albumin to creatinine ratio (uACR), plasma adiponectin, plasma ICAM-1 and urinary MPC-1 were assessed. In multiple regression ICAM-1 (p=0.004) and adiponectin (p=0.04) were the main determinants of uACR. Plasma adiponectin positively correlated to ICAM-1 (p=0.03, r=0.24). In albuminuric patients (uACR ≥30 mg/g) plasma adiponectin was significantly higher compared to normoalbuminuric ones (uACR <30 mg/g). In albuminuric patients the main determinants of uACR were plasma ICAM-1 and adiponectin. In multiple regression ICAM-1 is the only one that retains statistical significance (p=0.02). Urinary MCP-1 did not correlate to uACR. In our type 2 diabetic patients, plasma levels of ICAM-1 and adiponectin are predictive for albuminuria. Urinary MCP-1 does not correlated to uACR. Plasma adiponectin positively correlates to adhesion molecule ICAM-1 in our cohort. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Decoding visual object categories from temporal correlations of ECoG signals.

PubMed

Majima, Kei; Matsuo, Takeshi; Kawasaki, Keisuke; Kawai, Kensuke; Saito, Nobuhito; Hasegawa, Isao; Kamitani, Yukiyasu

2014-04-15

How visual object categories are represented in the brain is one of the key questions in neuroscience. Studies on low-level visual features have shown that relative timings or phases of neural activity between multiple brain locations encode information. However, whether such temporal patterns of neural activity are used in the representation of visual objects is unknown. Here, we examined whether and how visual object categories could be predicted (or decoded) from temporal patterns of electrocorticographic (ECoG) signals from the temporal cortex in five patients with epilepsy. We used temporal correlations between electrodes as input features, and compared the decoding performance with features defined by spectral power and phase from individual electrodes. While using power or phase alone, the decoding accuracy was significantly better than chance, correlations alone or those combined with power outperformed other features. Decoding performance with correlations was degraded by shuffling the order of trials of the same category in each electrode, indicating that the relative time series between electrodes in each trial is critical. Analysis using a sliding time window revealed that decoding performance with correlations began to rise earlier than that with power. This earlier increase in performance was replicated by a model using phase differences to encode categories. These results suggest that activity patterns arising from interactions between multiple neuronal units carry additional information on visual object categories. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantifying suspended sediment flux in a mixed-land-use urbanizing watershed using a nested-scale study design.

PubMed

Zeiger, Sean; Hubbart, Jason A

2016-01-15

Suspended sediment (SS) remains the most pervasive water quality problem globally and yet, despite progress, SS process understanding remains relatively poor in watersheds with mixed-land-use practices. The main objective of the current work was to investigate relationships between suspended sediment and land use types at multiple spatial scales (n=5) using four years of suspended sediment data collected in a representative urbanized mixed-land-use (forest, agriculture, urban) watershed. Water samples were analyzed for SS using a nested-scale experimental watershed study design (n=836 samples×5 gauging sites). Kruskal-Wallis and Dunn's post-hoc multiple comparison tests were used to test for significant differences (CI=95%, p<0.05) in SS levels between gauging sites. Climate extremes (high precipitation/drought) were observed during the study period. Annual maximum SS concentrations exceeded 2387.6 mg/L. Median SS concentrations decreased by 60% from the agricultural headwaters to the rural/urban interface, and increased by 98% as urban land use increased. Multiple linear regression analysis results showed significant relationships between SS, annual total precipitation (positive correlate), forested land use (negative correlate), agricultural land use (negative correlate), and urban land use (negative correlate). Estimated annual SS yields ranged from 16.1 to 313.0 t km(-2) year(-1) mainly due to differences in annual total precipitation. Results highlight the need for additional studies, and point to the need for improved best management practices designed to reduce anthropogenic SS loading in mixed-land-use watersheds. Copyright © 2015 Elsevier B.V. All rights reserved.

Validation of walk score for estimating neighborhood walkability: an analysis of four US metropolitan areas.

PubMed

Duncan, Dustin T; Aldstadt, Jared; Whalen, John; Melly, Steven J; Gortmaker, Steven L

2011-11-01

Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score(®) for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances (i.e., 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant's residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p < 0.05). The magnitude varied by the GIS indicator of neighborhood walkability. Correlations generally became stronger with a larger spatial scale, and there were some geographic differences. Walk Score(®) is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score(®) is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.

Impact of angiogenesis-related gene expression on the tracer kinetics of 18F-FDG in colorectal tumors.

PubMed

Strauss, Ludwig G; Koczan, Dirk; Klippel, Sven; Pan, Leyun; Cheng, Caixia; Willis, Stefan; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2008-08-01

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = -0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Association of academic performance of premedical students to satisfaction and engagement in a short training program: a cross sectional study presenting gender differences

PubMed Central

2014-01-01

Background It is important that students have a high academic engagement and satisfaction in order to have good academic achievement. No study measures association of these elements in a short training program. This study aimed to measure the correlation between academic achievement, satisfaction and engagement dimensions in a short training program among premedical students. Methods We carried out a cross sectional study, in August 2013, at Cercle d’Etudiants, Ingénieurs, Médecins et Professeurs de Lycée pour le Triomphe de l’Excellence (CEMPLEX) training center, a center which prepares students for the national common entrance examination into medical schools in Cameroon. We included all students attending this training center during last examination period. They were asked to fill out a questionnaire on paper. Academic engagement was measured using three dimensions: vigor, dedication and absorption. Satisfaction to lessons, for each learning subject was collected. Academic achievement was calculated using mean of the score of all learning subjects affected with their coefficient. Pearson coefficient (r) and multiple regression models were used to measure association. A p value < 0.05 was statistically significant. Results In total, 180 students were analyzed. In univariate linear analysis, we found correlation with academic achievement for vigor (r = 0.338, p = 0.006) and dedication (r = 0.287, p = 0.021) only in male students. In multiple regression linear analysis, academic engagement and satisfaction were correlated to academic achievement only in male students (R2 = 0.159, p = 0.035). No correlation was found in female students and in all students. The independent variables (vigor, dedication, absorption and satisfaction) explained 6.8-24.3% of the variance of academic achievement. Conclusion It is only in male students that academic engagement and satisfaction to lessons are correlated to academic achievement in this short training program for premedical students and this correlation is weak. PMID:24564911

Association of academic performance of premedical students to satisfaction and engagement in a short training program: a cross sectional study presenting gender differences.

PubMed

Bigna, Jean Joel R; Fonkoue, Loic; Tchatcho, Manuela Francette F; Dongmo, Christelle N; Soh, Dorothée M; Um, Joseph Lin Lewis N; Sime, Paule Sandra D; Affana, Landry A; Woum, Albert Ruben N; Noumegni, Steve Raoul N; Tabekou, Alphonce; Wanke, Arlette M; Taffe, Herman Rhais K; Tchoukouan, Miriette Linda N; Anyope, Kevin O; Ella, Stephane Brice E; Mouaha, Berny Vanessa T; Kenne, Edgar Y; Mbessoh, Ulrich Igor K; Tchapmi, Adrienne Y; Tene, Donald F; Voufouo, Steve S; Zogo, Stephanie M; Nouebissi, Linda P; Satcho, Kevine F; Tchoumo, Wati Joel T; Basso, Moise Fabrice; Tcheutchoua, Bertrand Daryl N; Agbor, Ako A

2014-02-24

It is important that students have a high academic engagement and satisfaction in order to have good academic achievement. No study measures association of these elements in a short training program. This study aimed to measure the correlation between academic achievement, satisfaction and engagement dimensions in a short training program among premedical students. We carried out a cross sectional study, in August 2013, at Cercle d'Etudiants, Ingénieurs, Médecins et Professeurs de Lycée pour le Triomphe de l'Excellence (CEMPLEX) training center, a center which prepares students for the national common entrance examination into medical schools in Cameroon. We included all students attending this training center during last examination period. They were asked to fill out a questionnaire on paper. Academic engagement was measured using three dimensions: vigor, dedication and absorption. Satisfaction to lessons, for each learning subject was collected. Academic achievement was calculated using mean of the score of all learning subjects affected with their coefficient. Pearson coefficient (r) and multiple regression models were used to measure association. A p value < 0.05 was statistically significant. In total, 180 students were analyzed. In univariate linear analysis, we found correlation with academic achievement for vigor (r = 0.338, p = 0.006) and dedication (r = 0.287, p = 0.021) only in male students. In multiple regression linear analysis, academic engagement and satisfaction were correlated to academic achievement only in male students (R2 = 0.159, p = 0.035). No correlation was found in female students and in all students. The independent variables (vigor, dedication, absorption and satisfaction) explained 6.8-24.3% of the variance of academic achievement. It is only in male students that academic engagement and satisfaction to lessons are correlated to academic achievement in this short training program for premedical students and this correlation is weak.

Two-particle Bose–Einstein correlations in pp collisions at √s=0.9 and 7 TeV measured with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2015-10-01

The paper presents studies of Bose–Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range pT> 100 MeV and |η|< 2.5 in proton collisions at centre-of-mass energies of 0.9 and 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. The integrated luminosities are approximately 7 μb -1, 190 μb -1 and 12.4 nb -1 for 0.9 TeV, 7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. Amore » saturation effect in the multiplicity dependence of the correlation source size parameter is observed using the high-multiplicity 7 TeV data sample. In conclusion, the dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated.« less

Two-particle Bose–Einstein correlations in pp collisions at √s=0.9 and 7 TeV measured with the ATLAS detector

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

Aad, G.; Abbott, B.; Abdallah, J.

The paper presents studies of Bose–Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range pT> 100 MeV and |η|< 2.5 in proton collisions at centre-of-mass energies of 0.9 and 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. The integrated luminosities are approximately 7 μb -1, 190 μb -1 and 12.4 nb -1 for 0.9 TeV, 7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. Amore » saturation effect in the multiplicity dependence of the correlation source size parameter is observed using the high-multiplicity 7 TeV data sample. In conclusion, the dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated.« less

Study of multiplicity correlations in nucleus-nucleus interactions at high energy

NASA Astrophysics Data System (ADS)

Mohery, M.; Sultan, E. M.; Baz, Shadiah S.

2015-06-01

In the present paper, some results on the correlations of the nucleus-nucleus interactions, at high energy, between different particle multiplicities are reported. The correlations between the multiplicities of the different charged particles emitted in the interactions of 22Ne and 28Si nuclei with emulsion at (4.1-4.5)A GeV/c have been studied. The correlations of the compound multiplicity nc, defined as the sum of both numbers of the shower particles ns and grey particles ng, have been investigated. The experimental data have been compared with the corresponding theoretical ones, calculated according to the modified cascade evaporation model (MCEM). An agreement has already been fairly obtained between the experimental values and the calculated ones. The dependence of the average compound multiplicity, on the numbers of shower, grey, black and heavy particles is obvious and the values of the slope have been found to be independent of the projectile nucleus. On the other hand, the variation of the average shower, grey, black and heavy particles is found to increase linearly with the compound particles. A strong correlation has been observed between the number of produced shower particles and the number of compound particles. Moreover, the value of the average compound multiplicity is found to increase with the increase of the projectile mass. Finally, an attempt has also been made to study the scaling of the compound multiplicity distribution showing that the compound multiplicity distribution is nearly consistent with the KNO scaling behavior.

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

PubMed

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Social Cognitive Correlates of Physical Activity in Inactive Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Dlugonski, Deirdre; Wojcicki, Thomas R.; McAuley, Edward; Motl, Robert W.

2011-01-01

Persons with multiple sclerosis (MS) are often physically inactive. This observation has prompted the search for modifiable constructs derived from established theories that act as correlates of physical activity. This study investigated self efficacy, outcome expectations, impediments, and goal setting as correlates of physical activity in…

Endoscopic carpal tunnel release: a prospective analysis of factors associated with unsatisfactory results.

PubMed

Straub, T A

1999-04-01

The first 100 consecutive cases of endoscopic carpal tunnel release (ECTR) performed by the author were studied prospectively during 6 to 24 months follow-up. Various preoperative and postoperative factors were subjected to statistical analysis to determine possible associations with unsatisfactory results. Overall, 92% of hands had a satisfactory result from ECTR, although not all were rendered symptom-free. There were no significant complications. Preoperative factors associated with an increased likelihood of unsatisfactory results included hands with preoperative weakness, widened two-point discrimination, myofascial pain syndrome or fibromyalgia, involvement in litigation, multiple compressive neuropathies, or the presence of abnormal psychological factors. A trend to less satisfactory results was present in Workers' Compensation cases and patients with normal motor latencies on nerve conduction studies. Multiple postoperative factors correlated with unsatisfactory results.

Correlation between benzene and testosterone in workers exposed to urban pollution.

PubMed

Rosati, M V; Sancini, A; Tomei, F; Sacco, C; Traversini, V; De Vita, A; De Cesare, D P; Giammichele, G; De Marco, F; Pagliara, F; Massoni, F; Ricci, L; Tomei, G; Ricci, S

2017-01-01

Many studies have examined the effects of benzene on testosterone. The purpose of this study was to evaluate the possible correlation between the blood levels of benzene and the levels of testosterone. The study involved a group of 148 subjects. For every worker have been made out a blood sample for the evaluation of benzene and testosterone levels and an urine analysis for the evaluation of the levels of trans, trans-muconic acid and S-phenylmercapturic acid. We estimated the Pearson correlation coefficient between the variables in the sample and the urinary metabolites, age, length of service, gender, BMI. For the analysis of the major confounding factors it was performed a multiple linear regression. The Pearson correlation coefficiet showed: 1. a significant inverse correlation between the S-phenyl mercapturic acid and free testosterone; 2. a significant direct correlation between trans-trans muconic acid and BMI. After dividing the sample according to the median of blood benzene (161.0 ng / L), Pearson correlation coefficient showed a significant inverse correlation between the S-phenyl mercapturic acid and free testosterone in the group with values below this median. Our results, to be considered preliminary, suggest that occupational exposure to low levels of benzene, present in urban pollution, affect the blood levels of testosterone. These results need to be confirmed in future studies, with the eventual possibility of including more specific fertility tests.

A study of Solar-Enso correlation with southern Brazil tree ring index (1955- 1991)

NASA Astrophysics Data System (ADS)

Rigozo, N.; Nordemann, D.; Vieira, L.; Echer, E.

The effects of solar activity and El Niño-Southern Oscillation on tree growth in Southern Brazil were studied by correlation analysis. Trees for this study were native Araucaria (Araucaria Angustifolia)from four locations in Rio Grande do Sul State, in Southern Brazil: Canela (29o18`S, 50o51`W, 790 m asl), Nova Petropolis (29o2`S, 51o10`W, 579 m asl), Sao Francisco de Paula (29o25`S, 50o24`W, 930 m asl) and Sao Martinho da Serra (29o30`S, 53o53`W, 484 m asl). From these four sites, an average tree ring Index for this region was derived, for the period 1955-1991. Linear correlations were made on annual and 10 year running averages of this tree ring Index, of sunspot number Rz and SOI. For annual averages, the correlation coefficients were low, and the multiple regression between tree ring and SOI and Rz indicates that 20% of the variance in tree rings was explained by solar activity and ENSO variability. However, when the 10 year running averages correlations were made, the coefficient correlations were much higher. A clear anticorrelation is observed between SOI and Index (r=-0.81) whereas Rz and Index show a positive correlation (r=0.67). The multiple regression of 10 year running averages indicates that 76% of the variance in tree ring INdex was explained by solar activity and ENSO. These results indicate that the effects of solar activity and ENSO on tree rings are better seen on long timescales.

Correlative weighted stacking for seismic data in the wavelet domain

USGS Publications Warehouse

Zhang, S.; Xu, Y.; Xia, J.; ,

2004-01-01

Horizontal stacking plays a crucial role for modern seismic data processing, for it not only compresses random noise and multiple reflections, but also provides a foundational data for subsequent migration and inversion. However, a number of examples showed that random noise in adjacent traces exhibits correlation and coherence. The average stacking and weighted stacking based on the conventional correlative function all result in false events, which are caused by noise. Wavelet transform and high order statistics are very useful methods for modern signal processing. The multiresolution analysis in wavelet theory can decompose signal on difference scales, and high order correlative function can inhibit correlative noise, for which the conventional correlative function is of no use. Based on the theory of wavelet transform and high order statistics, high order correlative weighted stacking (HOCWS) technique is presented in this paper. Its essence is to stack common midpoint gathers after the normal moveout correction by weight that is calculated through high order correlative statistics in the wavelet domain. Synthetic examples demonstrate its advantages in improving the signal to noise (S/N) ration and compressing the correlative random noise.

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores.

PubMed

Haile, Sarah R; Guerra, Beniamino; Soriano, Joan B; Puhan, Milo A

2017-12-21

Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.

Principal-component analysis of two-particle azimuthal correlations in PbPb and $$p\\text{Pb}$$ collisions at CMS

DOE PAGES

Sirunyan, A.M.; et al.

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sNN=2.76TeV PbPb and sNN=5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavymore » ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Periodontal inflamed surface area as a novel numerical variable describing periodontal conditions

PubMed Central

2017-01-01

Purpose A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis (P. gingivalis) expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation. PMID:29093989

Principal-component analysis of two-particle azimuthal correlations in PbPb and pPb collisions at CMS

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

Sirunyan, Albert M; et al.

2017-08-23

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sqrt(s[NN]) = 2.76 TeV PbPb and sqrt(s[NN]) = 5.02 TeV pPb collisions collected by the CMS experiment at the LHC. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it has been shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown ofmore » flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pt over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique has also been applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Forward-backward multiplicity correlation in high-energy nucleus-nucleus interactions at a few AGeV/c

NASA Astrophysics Data System (ADS)

Bhattacharyya, Swarnapratim; Haiduc, Maria; Neagu, Alina Tania; Firu, Elena

2014-07-01

We have presented a systematic study of two-particle rapidity correlations in terms of investigating the dynamical fluctuation observable \\sigma _c^2 in the forward-backward pseudo-rapidity windows by analyzing the experimental data of {}_{}^{16} O{--}AgBr interactions at 4.5 AGeV/c, {}_{}^{22} Ne{--}AgBr interactions at 4.1 AGeV/c, {}_{}^{28} Si{--}AgBr and {}_{}^{32} S{--}AgBr interactions at 4.5 AGeV/c. The experimental results have been compared with the results obtained from the analysis of event sample simulated (MC-RAND) by generating random numbers and also with the analysis of events generated by the UrQMD and AMPT model. Our study confirms the presence of strong short-range correlations among the produced particles in the forward and the backward pseudo-rapidity region. The analysis of the simple Monte Carlo-simulated (MC-RAND) events signifies that the observed correlations are not due to mere statistics only; explanation of such correlations can be attributed to the presence of dynamical fluctuations during the production of charged pions. Comparisons of the experimental results with the results obtained from analyzing the UrQMD data sample indicate that the UrQMD model cannot reproduce the experimental findings. The AMPT model also cannot explain the experimental results satisfactorily. Comparisons of our experimental results with the results obtained from the analysis of higher energy emulsion data and with the results of the RHIC data have also been presented.

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

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

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

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

NASA Astrophysics Data System (ADS)

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.; Strauss, J.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; 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.; 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.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; 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.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; 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.; 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.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; 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. Ã.-.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; 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.; 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.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; 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.; Olschewski, M.; Padeken, K.; 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.; 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.; 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.; Placakyte, R.; 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.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, 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.; Gilbert, A.; 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.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; 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.; Bhawandeep, U.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; 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.; Sharma, V.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; 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.; Parida, 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.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; 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.; Brigliadori, L.; 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.; Guiducci, L.; Marcellini, S.; Masetti, G.; 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.; 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.; 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.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Michelotto, M.; Montecassiano, F.; Pantano, D.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Mariani, V.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; 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.; Daci, N.; Del Re, D.; 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.; 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.; Ryu, G.; 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.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, 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.; Romanowska-Rybinska, 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.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Seixas, J.; 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.; Chadeeva, M.; Popova, E.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Demiyanov, A.; Ershov, A.; Gribushin, 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.; Krychkine, V.; 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.; 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.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Álvarez Fernández, A.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Curras, E.; 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.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karacheban, O.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Krammer, M.; 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.; 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.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Verweij, M.; Wardle, N.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Bachmair, F.; 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.; Rossini, M.; Schönenberger, M.; Shchutska, L.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zagozdzinska, A.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Donato, S.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; 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.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Adiguzel, A.; Bakirci, M. 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.; 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.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; 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.; Baber, M.; 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.; Dunne, P.; Elwood, A.; Futyan, D.; 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.; Pela, J.; 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.; 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.; 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.; Pazzini, J.; 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.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; 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.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; 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.; 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.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; 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.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Perry, T.; Prosper, H.; Santra, A.; 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.; Stringer, R.; 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.; Wang, R.-J.; 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.; Benaglia, A.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; 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.; 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.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; 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.; CMS Collaboration

2017-12-01

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √{sNN}=2.76 TeV PbPb and √{sNN}=5.02 TeV p Pb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and p Pb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

DOE PAGES

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

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

The mediating effect of calling on the relationship between medical school students’ academic burnout and empathy

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Analysis of Student-Evaluation Data on the Teaching of Fundamental Physics in an Introductory Technology Course, Paying Attention to Students‧ Earnestness to Learn

NASA Astrophysics Data System (ADS)

Nishida, Masahiko

How student evaluations of the teaching of fundamental physics for engineering relate to teaching strategy from academic 2004 to 2006 has been studied, focusing on students‧ earnestness to learn. The teaching emphasized instructing theoretical concepts for 2004 and solving problems for 2005. The instruction during 2006 offered a good balance between the strategy for 2004 and that for 2005. The first and second components produced by principal-component analysis of the evaluation data have indicated the quality of instruction and the scholastic ability of students, respectively, independent of the teaching strategy. While correlation between the second component and the degree of earnestness was positive for 2004 and negative for 2005, the correlation for 2006 has been negligible, as expected. Multiple-regression analysis between the evaluation data and students‧ exam scores has shown little correlation for 2006, in contrast to that for 2004, but similar to that for 2005. Finally, we can say that the teaching strategy for 2006 would lead to educational effects similar to those in 2005 when the exam scores were notably improved.

Accelerometry in persons with multiple sclerosis: measurement of physical activity or walking mobility?

PubMed

Weikert, Madeline; Motl, Robert W; Suh, Yoojin; McAuley, Edward; Wynn, Daniel

2010-03-15

Motion sensors such as accelerometers have been recognized as an ideal measure of physical activity in persons with MS. This study examined the hypothesis that accelerometer movement counts represent a measure of both physical activity and walking mobility in individuals with MS. The sample included 269 individuals with a definite diagnosis of relapsing-remitting MS who completed the Godin Leisure-Time Exercise Questionnaire (GLTEQ), International Physical Activity Questionnaire (IPAQ), Multiple Sclerosis Walking Scale-12 (MSWS-12), Patient Determined Disease Steps (PDDS), and then wore an ActiGraph accelerometer for 7days. The data were analyzed using bivariate correlation and confirmatory factor analysis. The results indicated that (a) the GLTEQ and IPAQ scores were strongly correlated and loaded significantly on a physical activity latent variable, (b) the MSWS-12 and PDDS scores strongly correlated and loaded significantly on a walking mobility latent variable, and (c) the accelerometer movement counts correlated similarly with the scores from the four self-report questionnaires and cross-loaded on both physical activity and walking mobility latent variables. Our data suggest that accelerometers are measuring both physical activity and walking mobility in persons with MS, whereas self-report instruments are measuring either physical activity or walking mobility in this population.

Magnetic resonance imaging correlates of bee sting induced multiple organ dysfunction syndrome: A case report.

PubMed

Das, Sushant K; Zeng, Li-Chuan; Li, Bing; Niu, Xiang-Ke; Wang, Jing-Liang; Bhetuwal, Anup; Yang, Han-Feng

2014-09-28

Occasionally systemic complications with high risk of death, such as multiple organ dysfunction syndrome (MODS), can occur following multiple bee stings. This case study reports a patient who presented with MODS, i.e., acute kidney injury, hepatic and cardiac dysfunction, after multiple bee stings. The standard clinical findings were then correlated with magnetic resonance imaging (MRI) findings, which demonstrates that MRI may be utilized as a simpler tool to use than other multiple diagnostics.

Correlates and Predictors of Resilience among Baccalaureate Nursing Students.

PubMed

Mathad, Monali Devaraj; Pradhan, Balaram; Rajesh, Sasidharan K

2017-02-01

A growing body of literature recognizes the importance of resilience in the nursing profession. Both mindfulness and resilience aid in handling stress, stress increases the risk of rumination and/or worry especially in females and they are more empathetic than other healthcare students. To identify correlates and predictors of the resilience among nursing students. This is a descriptive correlation study and we have recruited 194 participants (1-4 th year B.Sc Nursing) from Government College of Nursing and NIMHANS College of Nursing in Bangalore, India. The following instruments were used to collect the data, Freiburg Mindfulness Inventory (FMI), Toronto Empathy Questionnaire (TEQ), Perseverative Thinking Questionnaire (PTQ) and Connor-Davidson Resilience Scale (CD-RISC). Data was analysed using Pearson's correlation test and multiple regression analysis. Resilience is significantly correlated with mindfulness, perseverative thinking and empathy in nursing students. Based on regression analysis this model accounted for almost 33% of variance in resilience. This result is of interest as mindfulness alone explained 23% of the variance and unproductive Repeated Negative Thinking (RNT) and RNT consuming mental capacity predicted 8% and 2% respectively. These results support the importance of resilience and mindfulness in nursing students. Hence, resilience and/or mindfulness enhancing interventions should be inculcated in nursing education.

Correlations and forecast of death tolls in the Syrian conflict.

PubMed

Fujita, Kazuki; Shinomoto, Shigeru; Rocha, Luis E C

2017-11-16

The Syrian armed conflict has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources and aid to the affected areas. In this article, we use information on the daily number of deaths to study temporal and spatial correlations in the data, and exploit this information to forecast events of deaths. We found that the number of violent deaths per day in Syria varies more widely than that in England in which non-violent deaths dominate. We have identified strong positive auto-correlations in Syrian cities and non-trivial cross-correlations across some of them. The results indicate synchronization in the number of deaths at different times and locations, suggesting respectively that local attacks are followed by more attacks at subsequent days and that coordinated attacks may also take place across different locations. Thus the analysis of high temporal resolution data across multiple cities makes it possible to infer attack strategies, warn potential occurrence of future events, and hopefully avoid further deaths.

Serum resistin is associated with the severity of microangiopathies in type 2 diabetes

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

Osawa, Haruhiko; Ochi, Masaaki; Kato, Kenichi

2007-04-06

Resistin, secreted from adipocytes, causes insulin resistance and diabetes in rodents. To determine the relation between serum resistin and diabetic microangiopathies in humans, we analyzed 238 Japanese T2DM subjects. Mean serum resistin was higher in subjects with either advanced retinopathy (preproliferative or proliferative) (P = 0.0130), advanced nephropathy (stage III or IV) (P = 0.0151), or neuropathy (P = 0.0013). Simple regression analysis showed that serum resistin was positively correlated with retinopathy stage (P = 0.0212), nephropathy stage (P = 0.0052), and neuropathy (P = 0.0013). Multiple regression analysis adjusted for age, gender, and BMI, revealed that serum resistin wasmore » correlated with retinopathy stage (P = 0.0144), nephropathy stage (P = 0.0111), and neuropathy (P = 0.0053). Serum resistin was positively correlated with the number of advanced microangiopathies, independent of age, gender, BMI, and either the duration of T2DM (P = 0.0318) or serum creatinine (P = 0.0092). Therefore, serum resistin was positively correlated with the severity of microangiopathies in T2DM.« less

Analyzing Association Mapping in Pedigree-Based GWAS Using a Penalized Multitrait Mixed Model

PubMed Central

Liu, Jin; Yang, Can; Shi, Xingjie; Li, Cong; Huang, Jian; Zhao, Hongyu; Ma, Shuangge

2017-01-01

Genome-wide association studies (GWAS) have led to the identification of many genetic variants associated with complex diseases in the past 10 years. Penalization methods, with significant numerical and statistical advantages, have been extensively adopted in analyzing GWAS. This study has been partly motivated by the analysis of Genetic Analysis Workshop (GAW) 18 data, which have two notable characteristics. First, the subjects are from a small number of pedigrees and hence related. Second, for each subject, multiple correlated traits have been measured. Most of the existing penalization methods assume independence between subjects and traits and can be suboptimal. There are a few methods in the literature based on mixed modeling that can accommodate correlations. However, they cannot fully accommodate the two types of correlations while conducting effective marker selection. In this study, we develop a penalized multitrait mixed modeling approach. It accommodates the two different types of correlations and includes several existing methods as special cases. Effective penalization is adopted for marker selection. Simulation demonstrates its satisfactory performance. The GAW 18 data are analyzed using the proposed method. PMID:27247027

Concentration, distribution and source apportionment of atmospheric polycyclic aromatic hydrocarbons in the southeast suburb of Beijing, China.

PubMed

Zhang, Shucai; Zhang, Wei; Wang, Kaiyan; Shen, Yating; Hu, Lianwu; Wang, Xuejun

2009-04-01

Total suspended particle samples and gas phase samples were collected at three representative sampling sites in the southeastern suburb of Beijing from March 2005 to January 2006. The samples were analyzed for 16 US EPA priority PAHs using GC/MS. Concentrations of Sigma PAHs in particle and gas phases were 0.21-1.18 x 10(3) ng m(-3) and 9.5 x 10(2) ng-1.03 x 10(5) ng m(-3), respectively. PAH concentrations displayed seasonal variation in the order of winter>spring>autumn>summer for particle phase, and winter>autumn>summer>spring for gas phase. Partial correlation analysis indicates that PAH concentrations in particle phase are negatively correlated with temperature and positively correlated with air pollution index of SO(2). No significant correlation is observed between gas phase PAHs and the auxiliary parameters. Sources of PAH are identified through principal component analysis, and source contributions are estimated through multiple linear regression. Major sources of atmospheric PAHs in the study area include coal combustion, coke industry, vehicular emission and natural gas combustion.

Understanding and Promoting Birth Satisfaction in New Mothers.

PubMed

Hinic, Katherine

The purpose of this study was to examine the impact of select maternal psychosocial and experiential factors on birth satisfaction of new mothers during early postpartum. This is a descriptive correlational study exploring the relationships among birth satisfaction, breastfeeding self-efficacy, and perceived stress in 107 new mothers in the first 4 days postpartum. Instruments used included the Birth Satisfaction Scale-Revised, the Perceived Stress Scale, the Breastfeeding Self-Efficacy Scale-Short Form, and a researcher-generated demographic form. Quantitative analysis included descriptive statistics, correlation, one-way Analysis of Variance, and multiple linear regression. Birth satisfaction was negatively correlated with perceived stress (r = -.299, p < .05) and positively correlated with feeling prepared for birth (rho = .243, p < .05) and breastfeeding self-efficacy (r = .226, p < .05). The predictive model for birth satisfaction was significant (R = .204, F [6, 99] = 4.225, p = .001), explaining approximately 20.4% of variance in birth satisfaction in the sample. Stress reduction and management, establishment of realistic expectations for labor and birth, and promotion of togetherness with newborn immediately after birth are nursing priorities to promote birth satisfaction.

Application of remote sensing for fishery resources assessment and monitoring. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Thermosyphon Flooding in Reduced Gravity Environments Test Results

NASA Technical Reports Server (NTRS)

Gibson, Marc A.; Jaworske, Donald A.; Sanzi, Jim; Ljubanovic, Damir

2013-01-01

The condenser flooding phenomenon associated with gravity aided two-phase thermosyphons was studied using parabolic flights to obtain the desired reduced gravity environment (RGE). The experiment was designed and built to test a total of twelve titanium water thermosyphons in multiple gravity environments with the goal of developing a model that would accurately explain the correlation between gravitational forces and the maximum axial heat transfer limit associated with condenser flooding. Results from laboratory testing and parabolic flights are included in this report as part I of a two part series. The data analysis and correlations are included in a follow on paper.

Temporal Progression of Visual Injury from Blast Exposure

DTIC Science & Technology

2017-09-01

seen throughout the duration of the study. To correlate experimental blast exposures in rodents to human blast exposures, a computational parametric...software (JMP 10.0, Cary,NC). Descriptive and univariate analyses will first be performed to identify the occurrence of delayed visual system...later). The biostatistician evaluating the retrospective data has completed the descriptive analysis and is working on the multiple regression. Table

Development and Validation of a POSIT-Short Form: Screening for Problem Behaviors among Adolescents at Risk for Substance Use.

ERIC Educational Resources Information Center

Danseco, Evangeline R.; Marques, Paul R.

2002-01-01

The Problem-Oriented Screening Instrument for Teenagers (POSIT) screens for multiple problems among adolescents at risk for substance use. A shortened version of the POSIT was developed, using factor analysis, and correlational and reliability analyses. The POSIT-SF shows potential for a reliable and cost-efficient screen for youth with substance…

Tumble Graphs: Avoiding Misleading End Point Extrapolation When Graphing Interactions From a Moderated Multiple Regression Analysis

ERIC Educational Resources Information Center

Bodner, Todd E.

2016-01-01

This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…

RELATIONS BETWEEN LIGHTNING DISCHARGES AND DIFFERENT TYPES OF MUSICAL ATMOSPHERICS,

DTIC Science & Technology

Recording cathode-ray oscillographs were used for the analysis of the lightning discharges whose relations to musical atmospherics were investigated...of the lightning discharges investigated. Through comparative harmonic analyses it was shown that lightning discharges producing musical atmospherics...followed by multiple whistlers. An investigation was made of correlations between lightning discharges and musical atmospherics of unusual and irregular

Attempted Validation of the Scores of the VARK: Learning Styles Inventory with Multitrait-Multimethod Confirmatory Factor Analysis Models

ERIC Educational Resources Information Center

Leite, Walter L.; Svinicki, Marilla; Shi, Yuying

2010-01-01

The authors examined the dimensionality of the VARK learning styles inventory. The VARK measures four perceptual preferences: visual (V), aural (A), read/write (R), and kinesthetic (K). VARK questions can be viewed as testlets because respondents can select multiple items within a question. The correlations between items within testlets are a type…

Language and hope in schizophrenia-spectrum disorders.

PubMed

Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P

2016-11-30

Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

PubMed

Lock, Eric F; Hoadley, Katherine A; Marron, J S; Nobel, Andrew B

2013-03-01

Research in several fields now requires the analysis of datasets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such datasets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data, and provides new directions for the visual exploration of joint and individual structure. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types.

Application of optical correlation techniques to particle imaging velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1988-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Correlations of neutron multiplicity and γ -ray multiplicity with fragment mass and total kinetic energy in spontaneous fission of Cf 252

DOE PAGES

Wang, Taofeng; Li, Guangwu; Zhu, Liping; ...

2016-01-08

The dependence of correlations of neutron multiplicity ν and γ-ray multiplicity M γ in spontaneous fission of 252Cf on fragment mass A* and total kinetic energy (TKE) have been investigated by employing the ratio of M γ/ν and the form of M γ(ν). We show for the first time that M γ and ν have a complex correlation for heavy fragment masses, while there is a positive dependence of Mγ for light fragment masses and for near-symmetric mass splits. The ratio M γ/ν exhibits strong shell effects for neutron magic number N=50 and near doubly magic number shell closure atmore » Z=50 and N=82. The γ-ray multiplicity Mγ has a maximum for TKE=165-170 MeV. Above 170 MeV M γ(TKE) is approximately linear, while it deviates significantly from a linear dependence at lower TKE. The correlation between the average neutron and γ-ray multiplicities can be partly reproduced by model calculations.« less

Automated analysis of flow cytometric data for measuring neutrophil CD64 expression using a multi-instrument compatible probability state model.

PubMed

Wong, Linda; Hill, Beth L; Hunsberger, Benjamin C; Bagwell, C Bruce; Curtis, Adam D; Davis, Bruce H

2015-01-01

Leuko64™ (Trillium Diagnostics) is a flow cytometric assay that measures neutrophil CD64 expression and serves as an in vitro indicator of infection/sepsis or the presence of a systemic acute inflammatory response. Leuko64 assay currently utilizes QuantiCALC, a semiautomated software that employs cluster algorithms to define cell populations. The software reduces subjective gating decisions, resulting in interanalyst variability of <5%. We evaluated a completely automated approach to measuring neutrophil CD64 expression using GemStone™ (Verity Software House) and probability state modeling (PSM). Four hundred and fifty-seven human blood samples were processed using the Leuko64 assay. Samples were analyzed on four different flow cytometer models: BD FACSCanto II, BD FACScan, BC Gallios/Navios, and BC FC500. A probability state model was designed to identify calibration beads and three leukocyte subpopulations based on differences in intensity levels of several parameters. PSM automatically calculates CD64 index values for each cell population using equations programmed into the model. GemStone software uses PSM that requires no operator intervention, thus totally automating data analysis and internal quality control flagging. Expert analysis with the predicate method (QuantiCALC) was performed. Interanalyst precision was evaluated for both methods of data analysis. PSM with GemStone correlates well with the expert manual analysis, r(2) = 0.99675 for the neutrophil CD64 index values with no intermethod bias detected. The average interanalyst imprecision for the QuantiCALC method was 1.06% (range 0.00-7.94%), which was reduced to 0.00% with the GemStone PSM. The operator-to-operator agreement in GemStone was a perfect correlation, r(2) = 1.000. Automated quantification of CD64 index values produced results that strongly correlate with expert analysis using a standard gate-based data analysis method. PSM successfully evaluated flow cytometric data generated by multiple instruments across multiple lots of the Leuko64 kit in all 457 cases. The probability-based method provides greater objectivity, higher data analysis speed, and allows for greater precision for in vitro diagnostic flow cytometric assays. © 2015 International Clinical Cytometry Society.

Forward-backward multiplicity correlations in sNN=200 GeV Au+Au collisions

NASA Astrophysics Data System (ADS)

Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Hauer, M.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Noucier, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Seals, H.; Sedykh, I.; Skulski, W.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J.-L.; Tonjes, M. B.; Trzupek, A.; Vale, C.; Nieuwenhuizen, G. J. Van; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Wenger, E.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wuosmaa, A. H.; Wysłouch, B.

2006-07-01

Forward-backward correlations of charged-particle multiplicities in symmetric bins in pseudorapidity are studied to gain insight into the underlying correlation structure of particle production in Au+Au collisions. The PHOBOS detector is used to measure integrated multiplicities in bins centered at η, defined within |η|<3, and covering intervals Δη. The variance σC2 of a suitably defined forward-backward asymmetry variable C is calculated as a function of η,Δη, and centrality. It is found to be sensitive to short-range correlations, and the concept of “clustering” is used to interpret comparisons to phenomenological models.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices

NASA Astrophysics Data System (ADS)

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices.

PubMed

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

A symmetric multivariate leakage correction for MEG connectomes

PubMed Central

Colclough, G.L.; Brookes, M.J.; Smith, S.M.; Woolrich, M.W.

2015-01-01

Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected from eight subjects, before computing the partial correlations between power envelopes of the corrected ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together with longer-range direct fronto-parietal connections. PMID:25862259

Behavioral Actions of Alcohol: Phenotypic Relations from Multivariate Analysis of Mutant Mouse Data

PubMed Central

Blednov, Yuri A.; Mayfield, R. Dayne; Belknap, John; Harris, R. Adron

2012-01-01

Behavioral studies of genetically diverse mice have proven powerful for determining relationships between phenotypes and have been widely used in alcohol research. Most of these studies rely on naturally occurring genetic polymorphisms among inbred strains and selected lines. Another approach is to introduce variation by engineering single gene mutations in mice. We have tested 37 different mutant mice and their wild type controls for a variety (31) of behaviors and have mined this dataset by K-means clustering and analysis of correlations. We found a correlation between a stress-related response (activity in a novel environment) and alcohol consumption and preference for saccharin. We confirmed several relationships detected in earlier genetic studies including positive correlation of alcohol consumption with saccharin consumption, and negative correlations with conditioned taste aversion and alcohol withdrawal severity. Introduction of single gene mutations either eliminated or greatly diminished these correlations. The three tests of alcohol consumption used (continuous two bottle choice, and two limited access tests: Drinking In the Dark and Sustained High Alcohol Consumption) share a relationship with saccharin consumption, but differ from each other in their correlation networks. We suggest that alcohol consumption is controlled by multiple physiological systems where single gene mutations can disrupt the networks of such systems. PMID:22405477

Contributed review: Review of integrated correlative light and electron microscopy.

PubMed

Timmermans, F J; Otto, C

2015-01-01

New developments in the field of microscopy enable to acquire increasing amounts of information from large sample areas and at an increased resolution. Depending on the nature of the technique, the information may reveal morphological, structural, chemical, and still other sample characteristics. In research fields, such as cell biology and materials science, there is an increasing demand to correlate these individual levels of information and in this way to obtain a better understanding of sample preparation and specific sample properties. To address this need, integrated systems were developed that combine nanometer resolution electron microscopes with optical microscopes, which produce chemically or label specific information through spectroscopy. The complementary information from electron microscopy and light microscopy presents an opportunity to investigate a broad range of sample properties in a correlated fashion. An important part of correlating the differences in information lies in bridging the different resolution and image contrast features. The trend to analyse samples using multiple correlated microscopes has resulted in a new research field. Current research is focused, for instance, on (a) the investigation of samples with nanometer scale distribution of inorganic and organic materials, (b) live cell analysis combined with electron microscopy, and (c) in situ spectroscopic and electron microscopy analysis of catalytic materials, but more areas will benefit from integrated correlative microscopy.

Validated Metrics of Quick Flow Improve Assessments of Streamflow Generation Processes at the Long-Term Sleepers River Research Site

NASA Astrophysics Data System (ADS)

Sebestyen, S. D.; Shanley, J. B.

2015-12-01

There are multiple approaches to quantify quick flow components of streamflow. Physical hydrograph separations of quick flow using recession analysis (RA) are objective, reproducible, and easily calculated for long-duration streamflow records (years to decades). However, this approach has rarely been validated to have a physical basis for interpretation. In contrast, isotopic hydrograph separation (IHS) and end member mixing analysis using multiple solutes (EMMA) have been used to identify flow components and flowpath routing through catchment soils. Nonetheless, these two approaches are limited by data from limited and isolated periods (hours to weeks) during which more-intensive grab samples were analyzed. These limitations oftentimes make IHS and EMMA difficult to generalize beyond brief windows of time. At the Sleepers River Research Watershed (SRRW) in northern Vermont, USA, we have data from multiple snowmelt events over a two decade period and from multiple nested catchments to assess relationships among RA, IHS, and EMMA. Quick flow separations were highly correlated among the three techniques, which shows links among metrics of quick flow, water sources, and flow path routing in a small (41 ha), forested catchment (W-9) The similarity in responses validates a physical interpretation for a particular RA approach (the Ekhardt recursive RA filter). This validation provides a new tool to estimate new water inputs and flowpath routing for more and longer periods when chemical or isotopic tracers may not have been measured. At three other SRRW catchments, we found similar strong correlations among the three techniques. Consistent responses across four catchments provide evidence to support other research at the SRRW that shows that runoff generation mechanisms are similar despite differences in catchment sizes and land covers.

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

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

Khachatryan, Vardan

Our results on two-particle angular correlations for charged particles produced in pp collisions at a center-of-mass energy of 13 TeV are presented. The data were taken with the CMS detector at the LHC and correspond to an integrated luminosity of about 270 nb -1. The correlations are studied over a broad range of pseudorapidity (|η| < 2.4) and over the full azimuth (Φ) as a function of charged particle multiplicity and transverse momentum (p T). In high-multiplicity events, a long-range (|Δη| > 2.0), near-side (ΔΦ≈ 0) structure emerges in the two-particle Dh–Df correlation functions. The magnitude of the correlation exhibitsmore » a pronounced maximum in the range 1.0 < p T < 2.0 GeV/c and an approximately linear increase with the charged particle multiplicity. The overall correlation strength at √s = 13 TeV is similar to that found in earlier pp data at √s = 7 TeV, but is measured up to much higher multiplicity values. We observed long-range correlations are compared to those seen in pp, pPb, and PbPb collisions at lower collision energies.« less

Relationship between symptom dimensions and white matter alterations in obsessive-compulsive disorder.

PubMed

Yagi, Michiyo; Hirano, Yoshiyuki; Nakazato, Michiko; Nemoto, Kiyotaka; Ishikawa, Kazuhiro; Sutoh, Chihiro; Miyata, Haruko; Matsumoto, Junko; Matsumoto, Koji; Masuda, Yoshitada; Obata, Takayuki; Iyo, Masaomi; Shimizu, Eiji; Nakagawa, Akiko

2017-06-01

To investigate the relationship between the severities of symptom dimensions in obsessive-compulsive disorder (OCD) and white matter alterations. We applied tract-based spatial statistics for diffusion tensor imaging (DTI) acquired by 3T magnetic resonance imaging. First, we compared fractional anisotropy (FA) between 20 OCD patients and 30 healthy controls (HC). Then, applying whole brain analysis, we searched the brain regions showing correlations between the severities of symptom dimensions assessed by Obsessive-Compulsive Inventory-Revised and FA in all participants. Finally, we calculated the correlations between the six symptom dimensions and multiple DTI measures [FA, axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD)] in a region-of-interest (ROI) analysis and explored the differences between OCD patients and HC. There were no between-group differences in FA or brain region correlations between the severities of symptom dimensions and FA in any of the participants. ROI analysis revealed negative correlations between checking severity and left inferior frontal gyrus white matter and left middle temporal gyrus white matter and a positive correlation between ordering severity and right precuneus in FA in OCD compared with HC. We also found negative correlations between ordering severity and right precuneus in RD, between obsessing severities and right supramarginal gyrus in AD and MD, and between hoarding severity and right insular gyrus in AD. Our study supported the hypothesis that the severities of respective symptom dimensions are associated with different patterns of white matter alterations.

Automated site characterization for robotic sample acquisition systems

NASA Astrophysics Data System (ADS)

Scholl, Marija S.; Eberlein, Susan J.

1993-04-01

A mobile, semiautonomous vehicle with multiple sensors and on-board intelligence is proposed for performing preliminary scientific investigations on extraterrestrial bodies prior to human exploration. Two technologies, a hybrid optical-digital computer system based on optical correlator technology and an image and instrument data analysis system, provide complementary capabilities that might be part of an instrument package for an intelligent robotic vehicle. The hybrid digital-optical vision system could perform real-time image classification tasks using an optical correlator with programmable matched filters under control of a digital microcomputer. The data analysis system would analyze visible and multiband imagery to extract mineral composition and textural information for geologic characterization. Together these technologies would support the site characterization needs of a robotic vehicle for both navigational and scientific purposes.

Statistical analysis of trypanosomes' motility

NASA Astrophysics Data System (ADS)

Zaburdaev, Vasily; Uppaluri, Sravanti; Pfohl, Thomas; Engstler, Markus; Stark, Holger; Friedrich, Rudolf

2010-03-01

Trypanosome is a parasite causing the sleeping sickness. The way it moves in the blood stream and penetrates various obstacles is the area of active research. Our goal was to investigate a free trypanosomes' motion in the planar geometry. Our analysis of trypanosomes' trajectories reveals that there are two correlation times - one is associated with a fast motion of its body and the second one with a slower rotational diffusion of the trypanosome as a point object. We propose a system of Langevin equations to model such motion. One of its peculiarities is the presence of multiplicative noise predicting higher level of noise for higher velocity of the trypanosome. Theoretical and numerical results give a comprehensive description of the experimental data such as the mean squared displacement, velocity distribution and auto-correlation function.

Multiple sclerosis-associated retrovirus, Epstein-Barr virus, and vitamin D status in patients with relapsing remitting multiple sclerosis.

PubMed

Mostafa, Aliehossadat; Jalilvand, Somayeh; Shoja, Zabihollah; Nejati, Ahmad; Shahmahmoodi, Shohreh; Sahraian, Mohammad Ali; Marashi, Sayed Mahdi

2017-07-01

The relationship between infections and autoimmune diseases is complex and there are several reports highlighting the role of human endogenous retroviruses (HERVs) in these patients. The levels of multiple sclerosis-associated retrovirus (MSRV)-type DNA of Env gene was measured in peripheral blood mononuclear cells from 52 patients with relapsing-remitting multiple sclerosis (RRMS) and 40 healthy controls using specific quantitative PCR (qPCR) analysis. Furthermore, we analyzed the status of HERV-W/MSRV in these patients with regards to both EBV (DNA load and anti-EBNA1 IgG antibody) and vitamin D concentration. MSRV DNA copy number were significantly higher in RRMS patients than healthy controls (P < 0.0001). Interestingly, an inverse correlation was found between MSRV DNA copy number and serum vitamin D concentration (P < 0.01), but not for EBV load or anti-EBNA-1 IgG antibody. © 2017 Wiley Periodicals, Inc.

Bon-EV: an improved multiple testing procedure for controlling false discovery rates.

PubMed

Li, Dongmei; Xie, Zidian; Zand, Martin; Fogg, Thomas; Dye, Timothy

2017-01-03

Stability of multiple testing procedures, defined as the standard deviation of total number of discoveries, can be used as an indicator of variability of multiple testing procedures. Improving stability of multiple testing procedures can help to increase the consistency of findings from replicated experiments. Benjamini-Hochberg's and Storey's q-value procedures are two commonly used multiple testing procedures for controlling false discoveries in genomic studies. Storey's q-value procedure has higher power and lower stability than Benjamini-Hochberg's procedure. To improve upon the stability of Storey's q-value procedure and maintain its high power in genomic data analysis, we propose a new multiple testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni's approach. Simulation studies show that our proposed Bon-EV procedure can maintain the high power of the Storey's q-value procedure and also result in better FDR control and higher stability than Storey's q-value procedure for samples of large size(30 in each group) and medium size (15 in each group) for either independent, somewhat correlated, or highly correlated test statistics. When sample size is small (5 in each group), our proposed Bon-EV procedure has performance between the Benjamini-Hochberg procedure and the Storey's q-value procedure. Examples using RNA-Seq data show that the Bon-EV procedure has higher stability than the Storey's q-value procedure while maintaining equivalent power, and higher power than the Benjamini-Hochberg's procedure. For medium or large sample sizes, the Bon-EV procedure has improved FDR control and stability compared with the Storey's q-value procedure and improved power compared with the Benjamini-Hochberg procedure. The Bon-EV multiple testing procedure is available as the BonEV package in R for download at https://CRAN.R-project.org/package=BonEV .

The High Prevalence of the Varicella Zoster Virus in Patients With Relapsing-Remitting Multiple Sclerosis: A Case-Control Study in the North of Iran

PubMed Central

Najafi, Saeideh; Ghane, Masood; Yousefzadeh-Chabok, Shahrokh; Amiri, Mehdi

2016-01-01

Background Multiple sclerosis (MS) is the most common neurological autoimmune disease, characterized by multifocal areas of inflammatory demyelination within the central nervous system. It has been hypothesized that the stimulation of the immune system by viral infections is the leading cause of MS among susceptible individuals. Objectives The aim of this study was to investigate the prevalence of the varicella zoster virus (VZV) in patients with relapsing-remitting multiple sclerosis. Patients and Methods Plasma and peripheral blood mononuclear cells (PBMCs) collected from MS patients (n = 82) and controls (n = 89) were screened for the presence of anti-VZV antibodies and VZV DNA by the ELISA and PCR methods. DNA was extracted from all samples, and VZV infection was examined by the PCR technique. Statistical analysis was used to investigate the frequency of the virus in MS patients and a healthy control group. Results Of all the MS patients, 78 (95.1%) and 21 (25.6%) were positive for anti-VZV and VZV DNA, respectively. Statistical analysis of the PCR results showed a significant correlation between the abundance of VZV and MS disease (P < 0.001). However, there was no significant correlation between the abundance of anti-VZV antibodies and MS disease by the ELISA method. Conclusions These results support the hypothesis that VZV may contribute to MS in establishing a systemic infection process and inducing an immune response. PMID:27226879

Isovolumic relaxation period as an index of left ventricular relaxation under different afterload conditions--comparison with the time constant of left ventricular pressure decay in the dog.

PubMed

Ochi, H; Ikuma, I; Toda, H; Shimada, T; Morioka, S; Moriyama, K

1989-12-01

In order to determine whether isovolumic relaxation period (IRP) reflects left ventricular relaxation under different afterload conditions, 17 anesthetized, open chest dogs were studied, and the left ventricular pressure decay time constant (T) was calculated. In 12 dogs, angiotensin II and nitroprusside were administered, with the heart rate constant at 90 beats/min. Multiple linear regression analysis showed that the aortic dicrotic notch pressure (AoDNP) and T were major determinants of IRP, while left ventricular end-diastolic pressure was a minor determinant. Multiple linear regression analysis, correlating T with IRP and AoDNP, did not further improve the correlation coefficient compared with that between T and IRP. We concluded that correction of the IRP by AoDNP is not necessary to predict T from additional multiple linear regression. The effects of ascending aortic constriction or angiotensin II on IRP were examined in five dogs, after pretreatment with propranolol. Aortic constriction caused a significant decrease in IRP and T, while angiotensin II produced a significant increase in IRP and T. IRP was affected by the change of afterload. However, the IRP and T values were always altered in the same direction. These results demonstrate that IRP is substituted for T and it reflects left ventricular relaxation even in different afterload conditions. We conclude that IRP is a simple parameter easily used to evaluate left ventricular relaxation in clinical situations.

The Correlates of Body Composition with Heart Rate Recovery after Step Test: An Exploratory Study of Malaysian Adolescents

PubMed Central

Abu Hanifah, Redzal; Mohamed, Mohd. Nahar Azmi; Jaafar, Zulkarnain; Abdul Mohsein, Nabilla Al-Sadat; Jalaludin, Muhammad Yazid; Abdul Majid, Hazreen; Murray, Liam; Cantwell, Marie; Su, Tin Tin

2013-01-01

Background In adults, heart rate recovery is a predictor of mortality, while in adolescents it is associated with cardio-metabolic risk factors. The aim of this study was to examine the relationship between body composition measures and heart rate recovery (HRR) after step test in Malaysian secondary school students. Methods In the Malaysian Health and Adolescents Longitudinal Research Team (MyHEART) study, 1071 healthy secondary school students, aged 13 years old, participated in the step test. Parameters for body composition measures were body mass index z-score, body fat percentage, waist circumference, and waist height ratio. The step test was conducted by using a modified Harvard step test. Heart rate recovery of 1 minute (HRR1min) and heart rate recovery of 2 minutes (HRR2min) were calculated by the difference between the peak pulse rate during exercise and the resting pulse rate at 1 and 2 minutes, respectively. Analysis was done separately based on gender. Pearson correlation analysis was used to determine the association between the HRR parameters with body composition measures, while multiple regression analysis was used to determine which body composition measures was the strongest predictor for HRR. Results For both gender groups, all body composition measures were inversely correlated with HRR1min. In girls, all body composition measures were inversely correlated with HRR2min, while in boys all body composition measures, except BMI z-score, were associated with HRR2min. In multiple regression, only waist circumference was inversely associated with HRR2min (p=0.024) in boys, while in girls it was body fat percentage for HRR2min (p=0.008). Conclusion There was an inverse association between body composition measurements and HRR among apparently healthy adolescents. Therefore, it is important to identify cardio-metabolic risk factors in adolescent as an early prevention of consequent adulthood morbidity. This reiterates the importance of healthy living which should start from young. PMID:24349388

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers.

PubMed

Rai, Alex J; Stemmer, Paul M; Zhang, Zhen; Adam, Bao-Ling; Morgan, William T; Caffrey, Rebecca E; Podust, Vladimir N; Patel, Manisha; Lim, Lih-Yin; Shipulina, Natalia V; Chan, Daniel W; Semmes, O John; Leung, Hon-Chiu Eastwood

2005-08-01

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.

The Challenges of Measuring Glycemic Variability

PubMed Central

Rodbard, David

2012-01-01

This commentary reviews several of the challenges encountered when attempting to quantify glycemic variability and correlate it with risk of diabetes complications. These challenges include (1) immaturity of the field, including problems of data accuracy, precision, reliability, cost, and availability; (2) larger relative error in the estimates of glycemic variability than in the estimates of the mean glucose; (3) high correlation between glycemic variability and mean glucose level; (4) multiplicity of measures; (5) correlation of the multiple measures; (6) duplication or reinvention of methods; (7) confusion of measures of glycemic variability with measures of quality of glycemic control; (8) the problem of multiple comparisons when assessing relationships among multiple measures of variability and multiple clinical end points; and (9) differing needs for routine clinical practice and clinical research applications. PMID:22768904

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Relationships and redundancies of selected hemodynamic and structural parameters for characterizing virtual treatment of cerebral aneurysms with flow diverter devices.

PubMed

Karmonik, C; Anderson, J R; Beilner, J; Ge, J J; Partovi, S; Klucznik, R P; Diaz, O; Zhang, Y J; Britz, G W; Grossman, R G; Lv, N; Huang, Q

2016-07-26

To quantify the relationship and to demonstrate redundancies between hemodynamic and structural parameters before and after virtual treatment with a flow diverter device (FDD) in cerebral aneurysms. Steady computational fluid dynamics (CFD) simulations were performed for 10 cerebral aneurysms where FDD treatment with the SILK device was simulated by virtually reducing the porosity at the aneurysm ostium. Velocity and pressure values proximal and distal to and at the aneurysm ostium as well as inside the aneurysm were quantified. In addition, dome-to-neck ratios and size ratios were determined. Multiple correlation analysis (MCA) and hierarchical cluster analysis (HCA) were conducted to demonstrate dependencies between both structural and hemodynamic parameters. Velocities in the aneurysm were reduced by 0.14m/s on average and correlated significantly (p<0.05) with velocity values in the parent artery (average correlation coefficient: 0.70). Pressure changes in the aneurysm correlated significantly with pressure values in the parent artery and aneurysm (average correlation coefficient: 0.87). MCA found statistically significant correlations between velocity values and between pressure values, respectively. HCA sorted velocity parameters, pressure parameters and structural parameters into different hierarchical clusters. HCA of aneurysms based on the parameter values yielded similar results by either including all (n=22) or only non-redundant parameters (n=2, 3 and 4). Hemodynamic and structural parameters before and after virtual FDD treatment show strong inter-correlations. Redundancy of parameters was demonstrated with hierarchical cluster analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model for predicting the injury severity score.

PubMed

Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

2015-07-01

To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  < 0.05. To select objective variables, the stepwise method was used. A total of 122 patients were included in this study. The formula for predicting the injury severity score (ISS) was as follows: ISS = 13.252-0.078(mean blood pressure) + 0.12(fibrin degradation products). The P -value of this formula from analysis of variance was <0.001, and the multiple correlation coefficient (R) was 0.739 (R 2  = 0.546). The multiple correlation coefficient adjusted for the degrees of freedom was 0.538. The Durbin-Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

Bayesian wavelet PCA methodology for turbomachinery damage diagnosis under uncertainty

NASA Astrophysics Data System (ADS)

Xu, Shengli; Jiang, Xiaomo; Huang, Jinzhi; Yang, Shuhua; Wang, Xiaofang

2016-12-01

Centrifugal compressor often suffers various defects such as impeller cracking, resulting in forced outage of the total plant. Damage diagnostics and condition monitoring of such a turbomachinery system has become an increasingly important and powerful tool to prevent potential failure in components and reduce unplanned forced outage and further maintenance costs, while improving reliability, availability and maintainability of a turbomachinery system. This paper presents a probabilistic signal processing methodology for damage diagnostics using multiple time history data collected from different locations of a turbomachine, considering data uncertainty and multivariate correlation. The proposed methodology is based on the integration of three advanced state-of-the-art data mining techniques: discrete wavelet packet transform, Bayesian hypothesis testing, and probabilistic principal component analysis. The multiresolution wavelet analysis approach is employed to decompose a time series signal into different levels of wavelet coefficients. These coefficients represent multiple time-frequency resolutions of a signal. Bayesian hypothesis testing is then applied to each level of wavelet coefficient to remove possible imperfections. The ratio of posterior odds Bayesian approach provides a direct means to assess whether there is imperfection in the decomposed coefficients, thus avoiding over-denoising. Power spectral density estimated by the Welch method is utilized to evaluate the effectiveness of Bayesian wavelet cleansing method. Furthermore, the probabilistic principal component analysis approach is developed to reduce dimensionality of multiple time series and to address multivariate correlation and data uncertainty for damage diagnostics. The proposed methodology and generalized framework is demonstrated with a set of sensor data collected from a real-world centrifugal compressor with impeller cracks, through both time series and contour analyses of vibration signal and principal components.

Urinary excretion of uric acid is negatively associated with albuminuria in patients with chronic kidney disease: a cross-sectional study.

PubMed

Li, Fengqin; Guo, Hui; Zou, Jianan; Chen, Weijun; Lu, Yijun; Zhang, Xiaoli; Fu, Chensheng; Xiao, Jing; Ye, Zhibin

2018-04-24

Increasing evidence has shown that albuminuria is related to serum uric acid. Little is known about whether this association may be interrelated via renal handling of uric acid. Therefore, we aim to study urinary uric acid excretion and its association with albuminuria in patients with chronic kidney disease (CKD). A cross-sectional study of 200 Chinese CKD patients recruited from department of nephrology of Huadong hospital was conducted. Levels of 24 h urinary excretion of uric acid (24-h Uur), fractional excretion of uric acid (FEur) and uric acid clearance rate (Cur) according to gender, CKD stages, hypertension and albuminuria status were compared by a multivariate analysis. Pearson and Spearman correlation and multiple regression analyses were used to study the correlation of 24-h Uur, FEur and Cur with urinary albumin to creatinine ratio (UACR). The multivariate analysis showed that 24-h Uur and Cur were lower and FEur was higher in the hypertension group, stage 3-5 CKD and macro-albuminuria group (UACR> 30 mg/mmol) than those in the normotensive group, stage 1 CKD group and the normo-albuminuria group (UACR< 3 mg/mmol) (all P < 0.05). Moreover, males had higher 24-h Uur and lower FEur than females (both P < 0.05). Multiple linear regression analysis showed that UACR was negatively associated with 24-h Uur and Cur (P = 0.021, P = 0.007, respectively), but not with FEur (P = 0.759), after adjusting for multiple confounding factors. Our findings suggested that urinary excretion of uric acid is negatively associated with albuminuria in patients with CKD. This phenomenon may help to explain the association between albuminuria and serum uric acid.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Two-particle Bose-Einstein correlations in pp collisions at [Formula: see text] 0.9 and 7 TeV measured with the ATLAS detector.

PubMed

Aad, G; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimoto, G; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Allbrooke, B M M; Allison, L J; Allport, P P; Almond, J; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Araque, J P; Arce, A T H; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Auerbach, B; Augsten, K; Aurousseau, M; Avolio, G; Azuelos, G; Azuma, Y; Baak, M A; Baas, A E; Bacci, C; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Backus Mayes, J; Badescu, E; Bagiacchi, P; Bagnaia, P; Bai, Y; Bain, T; Baines, J T; Baker, O K; Balek, P; Balli, F; Banas, E; Banerjee, Sw; Bannoura, A A E; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Barnovska, Z; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Bartsch, V; Bassalat, A; Basye, A; Bates, R L; Batley, J R; Battaglia, M; Battistin, M; Bauer, F; Bawa, H S; Beattie, M D; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, K; Becker, S; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Beringer, J; Bernard, C; Bernat, P; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertsche, C; Bertsche, D; Besana, M I; Besjes, G J; Bessidskaia Bylund, O; Bessner, M; Besson, N; Betancourt, C; 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Werner, P; Wessels, M; Wetter, J; Whalen, K; White, A; White, M J; White, R; White, S; Whiteson, D; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilkens, H G; Will, J Z; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, A; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winter, B T; Wittgen, M; Wittig, T; Wittkowski, J; Wollstadt, S J; Wolter, M W; Wolters, H; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wright, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wyatt, T R; Wynne, B M; Xella, S; Xiao, M; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamada, M; Yamaguchi, H; Yamaguchi, Y; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, U K; Yang, Y; Yanush, S; Yao, L; Yao, W-M; Yasu, Y; Yatsenko, E; Yau Wong, K H; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yurkewicz, A; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zevi Della Porta, G; Zhang, D; Zhang, F; Zhang, H; Zhang, J; Zhang, L; Zhang, X; Zhang, Z; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, L; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, R; Zimmermann, S; Zimmermann, S; Zinonos, Z; Ziolkowski, M; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zutshi, V; Zwalinski, L

The paper presents studies of Bose-Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range [Formula: see text] 100 MeV and [Formula: see text] 2.5 in proton collisions at centre-of-mass energies of 0.9 and 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. The integrated luminosities are approximately 7 [Formula: see text]b[Formula: see text], 190 [Formula: see text]b[Formula: see text] and 12.4 nb[Formula: see text] for 0.9 TeV, 7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. A saturation effect in the multiplicity dependence of the correlation source size parameter is observed using the high-multiplicity 7 TeV data sample. The dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated.

Cultural adaptation and validation of a peninsular Spanish version of the MSTCQ© (Multiple Sclerosis Treatment Concerns Questionnaire).

PubMed

Muntéis Olivas, E; Navarro Mascarell, G; Meca Lallana, J; Maestre Martínez, A; Pérez Sempere, Á; Gracia Gil, J; Pato Pato, A

Although subcutaneous treatments for multiple sclerosis (MS) have been shown to be effective, adverse reactions and pain may adversely affect treatment satisfaction and adherence. This study presents an adapted and validated Spanish version of the Multiple Sclerosis Treatment Concerns Questionnaire © (MSTCQ), which evaluates satisfaction with the injection device (ID) across 4 domains: injection system (A), side effects (B) (flu-like symptoms, reactions, and satisfaction), experience with treatment (C) and benefits (D). Two study phases: 1) Cultural adaptation process with input from experts (n=6) and patients (n=30). 2) Validation obtained by means of an observational, cross-sectional, multi-centre study evaluating 143 adult MS patients using an ID. Tools employed: MSTCQ © , Patient-Reported Indices for Multiple Sclerosis (PRIMUS © ), and Treatment Satisfaction Questionnaire for Medication (TSQM © ). Psychometric properties: Feasibility (percentage of valid cases and floor/ceiling effects); Reliability (Cronbach α) and test-retest correlation (n=41, intraclass correlation coefficient, ICC); and construct validity (factor analysis of domains A and B) and convergent validity (Spearman rank-order correlation for MSTCQ © vs TSQM © ). Mean age (SD) was 41.94 (10.47) years, 63% of the group were women, and 88.11% presented relapsing-remitting MS. Mean (SD) EDSS score was 2.68 (1.82) points. MSTCQ © completion was high (0%-2.80% missing data). Internal consistency was high at α=0.89 for the total score (A+B) and α=0.76, 0.89, and 0.92 for domains A, B, and C, respectively. The version demonstrated excellent test-retest reliability for the total (ICC=0.98) and for domains A, B, and C: ICC=0.82, 0.97, and 0.89, respectively. Factor analysis corroborated the internal structure of the original questionnaire. The association between total and domain scores on both the MSTCQ © and the TSQM © was moderately strong (Rho=0.42-0.74) and significant (P<.05 and P<.01). The Spanish version of MSTCQ © demonstrates appropriate psychometric properties. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Flare rates and the McIntosh active-region classifications

NASA Technical Reports Server (NTRS)

Bornmann, P. L.; Shaw, D.

1994-01-01

Multiple linear regression analysis was used to derive the effective solar flare contributions of each of the McIntosh classification parameters. The best fits to the combined average number of M- and X-class X-ray flares per day were found when the flare contributions were assumed to be multiplicative rather than additive. This suggests that nonlinear processes may amplify the effects of the following different active-region properties encoded in the McIntosh classifications: the length of the sunspot group, the size and shape of the largest spot, and the distribution of spots within the group. Since many of these active-region properties are correlated with magnetic field strengths and fluxes, we suggest that the derived correlations reflect a more fundamental relationship between flare production and the magnetic properties of the region. The derived flare contributions for the individual McIntosh parameters can be used to derive a flare rate for each of the three-parameter McIntosh classes. These derived flare rates can be interpreted as smoothed values that may provide better estimates of an active region's expected flare rate when rare classes are reported or when the multiple observing sites report slightly different classifications.

A novel approach to analyzing lung cancer mortality disparities: Using the exposome and a graph-theoretical toolchain

PubMed Central

Juarez, Paul D; Hood, Darryl B; Rogers, Gary L; Baktash, Suzanne H; Saxton, Arnold M; Matthews-Juarez, Patricia; Im, Wansoo; Cifuentes, Myriam Patricia; Phillips, Charles A; Lichtveld, Maureen Y; Langston, Michael A

2017-01-01

Objectives The aim is to identify exposures associated with lung cancer mortality and mortality disparities by race and gender using an exposome database coupled to a graph theoretical toolchain. Methods Graph theoretical algorithms were employed to extract paracliques from correlation graphs using associations between 2162 environmental exposures and lung cancer mortality rates in 2067 counties, with clique doubling applied to compute an absolute threshold of significance. Factor analysis and multiple linear regressions then were used to analyze differences in exposures associated with lung cancer mortality and mortality disparities by race and gender. Results While cigarette consumption was highly correlated with rates of lung cancer mortality for both white men and women, previously unidentified novel exposures were more closely associated with lung cancer mortality and mortality disparities for blacks, particularly black women. Conclusions Exposures beyond smoking moderate lung cancer mortality and mortality disparities by race and gender. Policy Implications An exposome approach and database coupled with scalable combinatorial analytics provides a powerful new approach for analyzing relationships between multiple environmental exposures, pathways and health outcomes. An assessment of multiple exposures is needed to appropriately translate research findings into environmental public health practice and policy. PMID:29152601

Student perception and post-exam analysis of one best MCQs and one correct MCQs: A comparative study.

PubMed

Adhi, Mohammad Idrees; Aly, Syed Moyn

2018-04-01

To find differences between One-Correct and One-Best multiple-choice questions with relation to student scores, post-exam item analyses results and student perception. This comparative cross-sectional study was conducted at the Dow University of Health Sciences, Karachi, from November 2010 to April 2011, and comprised medical students. Data was analysed using SPSS 18. Of the 207 participants, 16(7.7%) were boys and 191(92.3%) were girls. The mean score in Paper I was 18.62±4.7, while in Paper II it was 19.58±6.1. One-Best multiple-choice questions performed better than One-Correct. There was no statistically significant difference in the mean scores of the two papers or in the difficulty indices. Difficulty and discrimination indices correlated well in both papers. Cronbach's alpha of paper I was 0.584 and that of paper II was 0.696. Point-biserial values were better for paper II than for paper I. Most students expressed dissatisfaction with paper II. One-Best multiple-choice questions showed better scores, higher reliability, better item performance and correlation values.

Correlation analysis of motor current and chatter vibration in grinding using complex continuous wavelet coherence

NASA Astrophysics Data System (ADS)

Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei

2016-11-01

Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively.

A Review on Spectral Amplitude Coding Optical Code Division Multiple Access

NASA Astrophysics Data System (ADS)

Kaur, Navpreet; Goyal, Rakesh; Rani, Monika

2017-06-01

This manuscript deals with analysis of Spectral Amplitude Coding Optical Code Division Multiple Access (SACOCDMA) system. The major noise source in optical CDMA is co-channel interference from other users known as multiple access interference (MAI). The system performance in terms of bit error rate (BER) degrades as a result of increased MAI. It is perceived that number of users and type of codes used for optical system directly decide the performance of system. MAI can be restricted by efficient designing of optical codes and implementing them with unique architecture to accommodate more number of users. Hence, it is a necessity to design a technique like spectral direct detection (SDD) technique with modified double weight code, which can provide better cardinality and good correlation property.

What variables can influence clinical reasoning?

PubMed

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

Correlation of the rates of solvolysis of α-bromoisobutyrophenone using both simple and extended forms of the Grunwald-Winstein equation and the application of correlation analysis to related studies.

PubMed

Kevill, Dennis Neil; Kim, Chang-Bae; D'Souza, Malcolm John

2018-03-01

A Grunwald-Winstein treatment of the specific rates of solvolysis of α-bromoisobutyrophenone in 100% methanol and in several aqueous ethanol, methanol, acetone, 2,2,2-trifluoroethanol (TFE), and 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) mixtures gives a good logarithmic correlation against a linear combination of N T (solvent nucleophilicity) and Y Br (solvent ionizing power) values. The l and m sensitivity values are compared to those previously reported for α-bromoacetophenone and to those obtained from parallel treatments of literature specific rate values for the solvolyses of several tertiary mesylates containing a C(=O)R group attached at the α-carbon. Kinetic data obtained earlier by Pasto and Sevenair for the solvolyses of the same substrate in 75% aqueous ethanol (by weight) in the presence of silver perchlorate and perchloric acid are analyzed using multiple regression analysis.

The predictors of chemistry achievement of 12th grade students in secondary schools in the United Arab Emirates

NASA Astrophysics Data System (ADS)

Khalaf, Ali Khalfan

2000-10-01

The purpose of this study is to explore variables related to chemistry achievement of 12th grade science students in the United Arab Emirates (UAE). The focus is to identify student, teacher, and school variables that predict chemistry achievement. The analysis sample included 204 males and 252 females in 66 classes in 60 schools from 10 districts or bureaus of education in the UAE. Thirty-two male and 33 female chemistry teachers and 60 school principals were included. The Khalaf Chemistry Achievement Test, GALT, the Student Questionnaire, Teacher Questionnaire, and School Information Questionnaire were administered. Descriptive statistics, correlations, analyses of variance, factor analysis, and stepwise multiple linear regression analyses were done. The results indicate that demographic, home environment, prior knowledge, scholastic ability, attitudes and perceptions related to chemistry and science, and student perception of instructional practices variables correlated with student chemistry achievement. The amount of help teachers received from the supervisor, class size, and courses in geology were teacher variables that correlated with class chemistry achievement. Nine school variables involving school, division, and class sizes correlated with school chemistry achievement. Analyses of variance revealed significant interaction effects: district by school size and district by student gender. In two districts, students in small schools achieved better than those in large schools. Generally female students achieved equal to or better than males. Three factors from the factor analysis: School Size, Prior Student Achievement, and Student Perception of Teacher Effectiveness, correlated with school chemistry achievement. The results of the multiple linear regression indicated that the factors of Prior Student Achievement, Student Perception of Teacher Effectiveness, and Teacher Experience and Expertise accounted for 45% of the variance in school chemistry achievement. Results indicate that the strongest predictors of chemistry achievement are prior achievement in science, Arabic language, and mathematics; student perception of teacher effectiveness; and teacher experience and expertise. Females tend to achieve better in chemistry than males. No nationality differences were found and the relationship of school size to chemistry achievement was inconclusive. Recommendations related to chemistry and science are presented. These include curriculum, school practice, teacher professional development, and future research.

Multiparticle azimuthal correlations in p -Pb and Pb-Pb collisions at the CERN Large Hadron Collider

DOE PAGES

Abelev, B.; Adam, J.; Adamová, D.; ...

2014-11-03

Our measurements of multiparticle azimuthal correlations (cumulants) for charged particles in p-Pb at √s NN=5.02 TeV and Pb-Pb at √s NN=2.76 TeV collisions are presented. They help address the question of whether there is evidence for global, flowlike, azimuthal correlations in the p-Pb system. These comparisons are made to measurements from the larger Pb-Pb system, where such evidence is established. In particular, the second harmonic two-particle cumulants are found to decrease with multiplicity, characteristic of a dominance of few-particle correlations in p-Pb collisions. However, when a |Δη| gap is placed to suppress such correlations, the two-particle cumulants begin to risemore » at high multiplicity, indicating the presence of global azimuthal correlations. The Pb-Pb values are higher than the p-Pb values at similar multiplicities. In both systems, the second harmonic four-particle cumulants exhibit a transition from positive to negative values when the multiplicity increases. Furthermore, the negative values allow for a measurement of v 2{4} to be made, which is found to be higher in Pb-Pb collisions at similar multiplicities. The second harmonic six-particle cumulants are also found to be higher in Pb-Pb collisions. In Pb-Pb collisions, we generally find v 2{4}≃v 2{6}≠0 which is indicative of a Bessel-Gaussian function for the v 2 distribution. For very high-multiplicity Pb-Pb collisions, we observe that the four- and six-particle cumulants become consistent with 0. Finally, third harmonic two-particle cumulants in p-Pb and Pb-Pb are measured. These are found to be similar for overlapping multiplicities, when a |Δη|>1.4 gap is placed.« less

Multiparticle azimuthal correlations in p -Pb and Pb-Pb collisions at the CERN Large Hadron Collider

NASA Astrophysics Data System (ADS)

Abelev, B.; Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agostinelli, A.; Agrawal, N.; Ahammed, Z.; Ahmad, N.; Ahmed, I.; Ahn, S. U.; Ahn, S. A.; Aimo, I.; Aiola, S.; Ajaz, M.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Armesto, N.; Arnaldi, R.; Aronsson, T.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Awes, T. C.; Azmi, M. D.; Bach, M.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Baltasar Dos Santos Pedrosa, F.; Baral, R. C.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartke, J.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Baumann, C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bellwied, R.; Belmont-Moreno, E.; Belmont, R.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Berger, M. E.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Bjelogrlic, S.; Blanco, F.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Bogolyubsky, M.; Böhmer, F. V.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Bossú, F.; Botje, M.; Botta, E.; Böttger, S.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Castillo Castellanos, J.; Casula, E. A. R.; Catanescu, V.; Cavicchioli, C.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Chang, B.; Chapeland, S.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Chochula, P.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa Del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortese, P.; Cortés Maldonado, I.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dainese, A.; Dang, R.; Danu, A.; Das, D.; Das, I.; Das, K.; Das, S.; Dash, A.; Dash, S.; de, S.; Delagrange, H.; Deloff, A.; Dénes, E.; D'Erasmo, G.; de Caro, A.; de Cataldo, G.; de Cuveland, J.; de Falco, A.; de Gruttola, D.; De Marco, N.; de Pasquale, S.; de Rooij, R.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; di Bari, D.; di Liberto, S.; di Mauro, A.; di Nezza, P.; Djuvsland, Ø.; Dobrin, A.; Dobrowolski, T.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Dørheim, S.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Dutta Majumdar, A. K.; Hilden, T. E.; Ehlers, R. J.; Elia, D.; Engel, H.; Erazmus, B.; Erdal, H. A.; Eschweiler, D.; Espagnon, B.; Esposito, M.; Estienne, M.; Esumi, S.; Evans, D.; Evdokimov, S.; Fabris, D.; Faivre, J.; Falchieri, D.; Fantoni, A.; Fasel, M.; Fehlker, D.; Feldkamp, L.; Felea, D.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Floratos, E.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Garishvili, I.; Gerhard, J.; Germain, M.; Gheata, A.; Gheata, M.; Ghidini, B.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Gladysz-Dziadus, E.; Glässel, P.; Gomez Ramirez, A.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Graczykowski, L. K.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Guilbaud, M.; Gulbrandsen, K.; Gulkanyan, H.; Gumbo, M.; Gunji, T.; Gupta, A.; Gupta, R.; Khan, K. H.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hanratty, L. D.; Hansen, A.; Harris, J. W.; Hartmann, H.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hippolyte, B.; Hladky, J.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Ilkiv, I.; Inaba, M.; Innocenti, G. M.; Ionita, C.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Jachołkowski, A.; Jacobs, P. M.; Jahnke, C.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kadyshevskiy, V.; Kalcher, S.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil Svn, M.; Khan, M. M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, B.; Kim, D. W.; Kim, D. J.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, J.; Klein-Bösing, C.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Köhler, M. K.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Konevskikh, A.; Kovalenko, V.; Kowalski, M.; Kox, S.; Koyithatta Meethaleveedu, G.; Kral, J.; Králik, I.; Kravčáková, A.; Krelina, M.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kučera, V.; Kucheriaev, Y.; Kugathasan, T.; Kuhn, C.; Kuijer, P. G.; Kulakov, I.; Kumar, J.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; La Pointe, S. L.; La Rocca, P.; Lea, R.; Leardini, L.; Lee, G. R.; Legrand, I.; Lehnert, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; Leoncino, M.; León Monzón, I.; Lévai, P.; Li, S.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loggins, V. R.; Loginov, V.; Lohner, D.; Loizides, C.; Lopez, X.; López Torres, E.; Lu, X.-G.; Luettig, P.; Lunardon, M.; Luparello, G.; Ma, R.; Maevskaya, A.; Mager, M.; Mahapatra, D. P.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manceau, L.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Marín, A.; Markert, C.; Marquard, M.; Martashvili, I.; Martin, N. A.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martin Blanco, J.; Martynov, Y.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Meddi, F.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mlynarz, J.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Morando, M.; Moreira de Godoy, D. A.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Müller, H.; Munhoz, M. G.; Murray, S.; Musa, L.; Musinsky, J.; Nandi, B. K.; Nania, R.; Nappi, E.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nicassio, M.; Niculescu, M.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Nilsen, B. S.; Noferini, F.; Nomokonov, P.; Nooren, G.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Okatan, A.; Olah, L.; Oleniacz, J.; Oliveira da Silva, A. C.; Onderwaater, J.; Oppedisano, C.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Sahoo, P.; Pachmayer, Y.; Pachr, M.; Pagano, P.; Paić, G.; Painke, F.; Pajares, C.; Pal, S. K.; Palmeri, A.; Pant, D.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Patalakha, D. I.; Paticchio, V.; Paul, B.; Pawlak, T.; Peitzmann, T.; Pereira da Costa, H.; Pereira de Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Pesci, A.; Peskov, V.; Pestov, Y.; Petráček, V.; Petran, M.; Petris, M.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Pohjoisaho, E. H. O.; Polichtchouk, B.; Poljak, N.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Potukuchi, B.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Rauf, A. W.; Razazi, V.; Read, K. F.; Real, J. S.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reicher, M.; Reidt, F.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Rettig, F.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Rivetti, A.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohni, S.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, R.; Sahu, P. K.; Saini, J.; Sakai, S.; Salgado, C. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sanchez Castro, X.; Sánchez Rodríguez, F. J.; Šándor, L.; Sandoval, A.; Sano, M.; Santagati, G.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Segato, G.; Seger, J. E.; Sekiguchi, Y.; Selyuzhenkov, I.; Seo, J.; Serradilla, E.; Sevcenco, A.; Shabetai, A.; Shabratova, G.; Shahoyan, R.; Shangaraev, A.; Sharma, N.; Sharma, S.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Skjerdal, K.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Søgaard, C.; Soltz, R.; Song, J.; Song, M.; Soramel, F.; Sorensen, S.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stefanek, G.; Steinpreis, M.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Stolpovskiy, M.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Sultanov, R.; Šumbera, M.; Susa, T.; Symons, T. J. M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Takahashi, J.; Tangaro, M. A.; Tapia Takaki, J. D.; Tarantola Peloni, A.; Tarazona Martinez, A.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terrevoli, C.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Vande Vyvre, P.; van der Maarel, J.; van Hoorne, J. W.; van Leeuwen, M.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vechernin, V.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wagner, V.; Wang, M.; Wang, Y.; Watanabe, D.; Weber, M.; Wessels, J. P.; Westerhoff, U.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yamaguchi, Y.; Yang, H.; Yang, P.; Yang, S.; Yano, S.; Yasnopolskiy, S.; Yi, J.; Yin, Z.; Yoo, I.-K.; Yushmanov, I.; Zaccolo, V.; Zach, C.; Zaman, A.; Zampolli, C.; Zaporozhets, S.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, F.; Zhou, Y.; Zhou, Zhuo; Zhu, H.; Zhu, J.; Zhu, X.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zoccarato, Y.; Zyzak, M.; Alice Collaboration

2014-11-01

Measurements of multiparticle azimuthal correlations (cumulants) for charged particles in p -Pb at √{sNN}=5.02 TeV and Pb-Pb at √{sNN}=2.76 TeV collisions are presented. They help address the question of whether there is evidence for global, flowlike, azimuthal correlations in the p -Pb system. Comparisons are made to measurements from the larger Pb-Pb system, where such evidence is established. In particular, the second harmonic two-particle cumulants are found to decrease with multiplicity, characteristic of a dominance of few-particle correlations in p -Pb collisions. However, when a |Δ η | gap is placed to suppress such correlations, the two-particle cumulants begin to rise at high multiplicity, indicating the presence of global azimuthal correlations. The Pb-Pb values are higher than the p -Pb values at similar multiplicities. In both systems, the second harmonic four-particle cumulants exhibit a transition from positive to negative values when the multiplicity increases. The negative values allow for a measurement of v2{4 } to be made, which is found to be higher in Pb-Pb collisions at similar multiplicities. The second harmonic six-particle cumulants are also found to be higher in Pb-Pb collisions. In Pb-Pb collisions, we generally find v2{4 } ≃v2{6 } ≠0 which is indicative of a Bessel-Gaussian function for the v2 distribution. For very high-multiplicity Pb-Pb collisions, we observe that the four- and six-particle cumulants become consistent with 0. Finally, third harmonic two-particle cumulants in p -Pb and Pb-Pb are measured. These are found to be similar for overlapping multiplicities, when a |Δ η |>1.4 gap is placed.

Inflammatory responses and intestinal injury development during acute Trypanosoma cruzi infection are associated with the parasite load.

PubMed

Vazquez, Bruna Perez; Vazquez, Thaís Perez; Miguel, Camila Botelho; Rodrigues, Wellington Francisco; Mendes, Maria Tays; de Oliveira, Carlo José Freire; Chica, Javier Emílio Lazo

2015-04-03

Chagas disease is caused by the protozoan Trypanosoma cruzi and is characterized by cardiac, gastrointestinal, and nervous system disorders. Although much about the pathophysiological process of Chagas disease is already known, the influence of the parasite burden on the inflammatory process and disease progression remains uncertain. We used an acute experimental disease model to evaluate the effect of T. cruzi on intestinal lesions and assessed correlations between parasite load and inflammation and intestinal injury at 7 and 14 days post-infection. Low (3 × 10(2)), medium (3 × 10(3)), and high (3 × 10(4)) parasite loads were generated by infecting C57BL/6 mice with "Y"-strain trypomastigotes. Statistical analysis was performed using analysis of variance with Tukey's multiple comparison post-test, Kruskal-Wallis test with Dunn's multiple comparison, χ2 test and Spearman correlation. High parasite load-bearing mice more rapidly and strongly developed parasitemia. Increased colon width, inflammatory infiltration, myositis, periganglionitis, ganglionitis, pro-inflammatory cytokines (e.g., TNF-α, INF-γ, IL-2, IL-17, IL-6), and intestinal amastigote nests were more pronounced in high parasite load-bearing animals. These results were remarkable because a positive correlation was observed between parasite load, inflammatory infiltrate, amastigote nests, and investigated cytokines. These experimental data support the idea that the parasite load considerably influences the T. cruzi-induced intestinal inflammatory response and contributes to the development of the digestive form of the disease.

Latin Hypercube Sampling (LHS) UNIX Library/Standalone

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

2004-05-13

The LHS UNIX Library/Standalone software provides the capability to draw random samples from over 30 distribution types. It performs the sampling by a stratified sampling method called Latin Hypercube Sampling (LHS). Multiple distributions can be sampled simultaneously, with user-specified correlations amongst the input distributions, LHS UNIX Library/ Standalone provides a way to generate multi-variate samples. The LHS samples can be generated either as a callable library (e.g., from within the DAKOTA software framework) or as a standalone capability. LHS UNIX Library/Standalone uses the Latin Hypercube Sampling method (LHS) to generate samples. LHS is a constrained Monte Carlo sampling scheme. Inmore » LHS, the range of each variable is divided into non-overlapping intervals on the basis of equal probability. A sample is selected at random with respect to the probability density in each interval, If multiple variables are sampled simultaneously, then values obtained for each are paired in a random manner with the n values of the other variables. In some cases, the pairing is restricted to obtain specified correlations amongst the input variables. Many simulation codes have input parameters that are uncertain and can be specified by a distribution, To perform uncertainty analysis and sensitivity analysis, random values are drawn from the input parameter distributions, and the simulation is run with these values to obtain output values. If this is done repeatedly, with many input samples drawn, one can build up a distribution of the output as well as examine correlations between input and output variables.« less

The influence of daily stress and resilience on successful ageing.

PubMed

Byun, J; Jung, D

2016-09-01

The aim of this study was to identify the effects of daily stress and resilience on successful ageing among community-dwelling older adults. Ageing can be a positive experience if there is good adaptation to ageing processes. Positive ageing needs to be a basis of nursing care, health promotion and education within community settings. Data were collected in March and April of 2014 from 262 older adults living in Seoul and Jeju, South Korea. We used a four-part survey consisting of demographic data, daily stress, resilience and successful ageing scales, in total 91 items. Data were analysed using descriptive statistics, t-test, one-way ANOVA, Tukey HSD test, Pearson's correlation coefficient and hierarchical multiple regression analysis to identify the influence of variables on successful ageing. Successful ageing had a significant negative correlation with daily stress and a positive correlation with resilience. Daily stress had a negative correlation with resilience. Findings of hierarchical multiple regression analysis indicated that resilience and subjective economic status had an effect on successful ageing. Furthermore, these variables accounted for 41.6% of the variance in successful ageing. Data were collected in only two cities of Korea based on convenience sampling. The findings of the study suggest that daily stress and resilience have a statistically significant relationship with successful ageing. Furthermore, resilience is an important influential factor and a much-needed personal characteristic for one's successful ageing. Nurses can advocate joining with health and social policy makers to implement policies on healthy ageing, including evaluation of stress, education programmes and implementation of self-help groups to enhance resilience in older people. © 2016 International Council of Nurses.

Does the utilization of dental services associate with masticatory performance in a Japanese urban population?: the Suita study

PubMed Central

Kikui, Miki; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Yoshimuta, Yoko; Yasui, Sakae; Nokubi, Takashi; Maeda, Yoshinobu; Kokubo, Yoshihiro; Watanabe, Makoto; Miyamoto, Yoshihiro

2015-01-01

Abstract There are numerous reports on the relationship between regular utilization of dental care services and oral health, but most are based on questionnaires and subjective evaluation. Few have objectively evaluated masticatory performance and its relationship to utilization of dental care services. The purpose of this study was to identify the effect of regular utilization of dental services on masticatory performance. The subjects consisted of 1804 general residents of Suita City, Osaka Prefecture (760 men and 1044 women, mean age 66.5 ± 7.9 years). Regular utilization of dental services and oral hygiene habits (frequency of toothbrushing and use of interdental aids) was surveyed, and periodontal status, occlusal support, and masticatory performance were measured. Masticatory performance was evaluated by a chewing test using gummy jelly. The correlation between age, sex, regular dental utilization, oral hygiene habits, periodontal status or occlusal support, and masticatory performance was analyzed using Spearman's correlation test and t‐test. In addition, multiple linear regression analysis was carried out to investigate the relationship of regular dental utilization with masticatory performance after controlling for other factors. Masticatory performance was significantly correlated to age when using Spearman's correlation test, and to regular dental utilization, periodontal status, or occlusal support with t‐test. Multiple linear regression analysis showed that regular utilization of dental services was significantly related to masticatory performance even after adjusting for age, sex, oral hygiene habits, periodontal status, and occlusal support (standardized partial regression coefficient β = 0.055). These findings suggested that the regular utilization of dental care services is an important factor influencing masticatory performance in a Japanese urban population. PMID:29744141

Does the utilization of dental services associate with masticatory performance in a Japanese urban population?: the Suita study.

PubMed

Kikui, Miki; Ono, Takahiro; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Yoshimuta, Yoko; Yasui, Sakae; Nokubi, Takashi; Maeda, Yoshinobu; Kokubo, Yoshihiro; Watanabe, Makoto; Miyamoto, Yoshihiro

2015-12-01

There are numerous reports on the relationship between regular utilization of dental care services and oral health, but most are based on questionnaires and subjective evaluation. Few have objectively evaluated masticatory performance and its relationship to utilization of dental care services. The purpose of this study was to identify the effect of regular utilization of dental services on masticatory performance. The subjects consisted of 1804 general residents of Suita City, Osaka Prefecture (760 men and 1044 women, mean age 66.5 ± 7.9 years). Regular utilization of dental services and oral hygiene habits (frequency of toothbrushing and use of interdental aids) was surveyed, and periodontal status, occlusal support, and masticatory performance were measured. Masticatory performance was evaluated by a chewing test using gummy jelly. The correlation between age, sex, regular dental utilization, oral hygiene habits, periodontal status or occlusal support, and masticatory performance was analyzed using Spearman's correlation test and t -test. In addition, multiple linear regression analysis was carried out to investigate the relationship of regular dental utilization with masticatory performance after controlling for other factors. Masticatory performance was significantly correlated to age when using Spearman's correlation test, and to regular dental utilization, periodontal status, or occlusal support with t -test. Multiple linear regression analysis showed that regular utilization of dental services was significantly related to masticatory performance even after adjusting for age, sex, oral hygiene habits, periodontal status, and occlusal support (standardized partial regression coefficient β  = 0.055). These findings suggested that the regular utilization of dental care services is an important factor influencing masticatory performance in a Japanese urban population.

Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys.

PubMed

Jalili, Majid; Nazem, Farzad; Sazvar, Akbar; Ranjbar, Kamal

2018-05-14

To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m ) - (0.732 × body mass index kg/m2 ) (R 2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R 2 p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings. Copyright © 2018 Elsevier Inc. All rights reserved.

Z-Scan Analysis: a New Method to Determine the Oxidative State of Low-Density Lipoprotein and Its Association with Multiple Cardiometabolic Biomarkers

NASA Astrophysics Data System (ADS)

de Freitas, Maria Camila Pruper; Figueiredo Neto, Antonio Martins; Giampaoli, Viviane; da Conceição Quintaneiro Aubin, Elisete; de Araújo Lima Barbosa, Milena Maria; Damasceno, Nágila Raquel Teixeira

2016-04-01

The great atherogenic potential of oxidized low-density lipoprotein has been widely described in the literature. The objective of this study was to investigate whether the state of oxidized low-density lipoprotein in human plasma measured by the Z-scan technique has an association with different cardiometabolic biomarkers. Total cholesterol, high-density lipoprotein cholesterol, triacylglycerols, apolipoprotein A-I and apolipoprotein B, paraoxonase-1, and glucose were analyzed using standard commercial kits, and low-density lipoprotein cholesterol was estimated using the Friedewald equation. A sandwich enzyme-linked immunosorbent assay was used to detect electronegative low-density lipoprotein. Low-density lipoprotein and high-density lipoprotein sizes were determined by Lipoprint® system. The Z-scan technique was used to measure the non-linear optical response of low-density lipoprotein solution. Principal component analysis and correlations were used respectively to resize the data from the sample and test association between the θ parameter, measured with the Z-scan technique, and the principal component. A total of 63 individuals, from both sexes, with mean age 52 years (±11), being overweight and having high levels of total cholesterol and low levels of high-density lipoprotein cholesterol, were enrolled in this study. A positive correlation between the θ parameter and more anti-atherogenic pattern for cardiometabolic biomarkers together with a negative correlation for an atherogenic pattern was found. Regarding the parameters related with an atherogenic low-density lipoprotein profile, the θ parameter was negatively correlated with a more atherogenic pattern. By using Z-scan measurements, we were able to find an association between oxidized low-density lipoprotein state and multiple cardiometabolic biomarkers in samples from individuals with different cardiovascular risk factors.

Correlates of willingness to engage in residential gardening: implications for health optimization in ibadan, Nigeria.

PubMed

Motunrayo Ibrahim, Fausat

2013-01-01

Gardening is a worthwhile adventure which engenders health op-timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar-dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Socio-psychological characteristics and being married are very rele-vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population.

Correlates of Willingness to Engage in Residential Gardening: Implications for Health Optimization in Ibadan, Nigeria

PubMed Central

Motunrayo Ibrahim, Fausat

2013-01-01

Background: Gardening is a worthwhile adventure which engenders health op­timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. Methods: In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar­dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Conclusion: Socio-psychological characteristics and being married are very rele­vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population. PMID:24688974

Reexamining the Validity and Dimensionality of the Moorong Self-Efficacy Scale: Improving Its Clinical Utility.

PubMed

Middleton, James W; Tran, Yvonne; Lo, Charles; Craig, Ashley

2016-12-01

To improve the clinical utility of the Moorong Self-Efficacy Scale (MSES) by reexamining its factor structure and comparing its performance against a measure of general self-efficacy in persons with spinal cord injury (SCI). Cross-sectional survey design. Community. Adults with SCI (N=161; 118 men and 43 women) recruited from Australia (n=82) and the United States (n=79), including 86 with paraplegia and 75 with tetraplegia. None. Confirmatory factor analysis deriving fit indices on reported 1-, 2-, and 3-factor structures for the MSES. Exploratory factor analysis of MSES using principal component analysis with promax oblique rotation and structure validation, with correlations and multiple regression using cross-sectional data from the Sherer General Self-Efficacy Scale and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The MSES was confirmed to have a 3-factor structure, explaining 61% of variance. Two of the factors, labeled social function self-efficacy and personal function self-efficacy, were SCI condition-specific, whereas the other factor (accounting for 9.7% of variance) represented general self-efficacy, correlating most strongly with the Sherer General Self-Efficacy Scale. Correlations and multiple regression analyses between MSES factors, Sherer General Self-Efficacy Scale total score, SF-36 Physical and Mental Component Summary scores, and SF-36 domain scores support validity of this MSES factor structure. No significant cross-cultural differences existed between Australia and the United States in total MSES or factor scores. The findings support a 3-factor structure encompassing general and SCI domain-specific self-efficacy beliefs and better position the MSES to assist SCI rehabilitation assessment, planning, and research. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

Choosing the best image processing method for masticatory performance assessment when using two-coloured specimens.

PubMed

Vaccaro, G; Pelaez, J I; Gil, J A

2016-07-01

Objective masticatory performance assessment using two-coloured specimens relies on image processing techniques; however, just a few approaches have been tested and no comparative studies are reported. The aim of this study was to present a selection procedure of the optimal image analysis method for masticatory performance assessment with a given two-coloured chewing gum. Dentate participants (n = 250; 25 ± 6·3 years) chewed red-white chewing gums for 3, 6, 9, 12, 15, 18, 21 and 25 cycles (2000 samples). Digitalised images of retrieved specimens were analysed using 122 image processing methods (IPMs) based on feature extraction algorithms (pixel values and histogram analysis). All IPMs were tested following the criteria of: normality of measurements (Kolmogorov-Smirnov), ability to detect differences among mixing states (anova corrected with post hoc Bonferroni) and moderate-to-high correlation with the number of cycles (Spearman's Rho). The optimal IPM was chosen using multiple criteria decision analysis (MCDA). Measurements provided by all IPMs proved to be normally distributed (P < 0·05), 116 proved sensible to mixing states (P < 0·05), and 35 showed moderate-to-high correlation with the number of cycles (|ρ| > 0·5; P < 0·05). The variance of the histogram of the Hue showed the highest correlation with the number of cycles (ρ = 0·792; P < 0·0001) and the highest MCDA score (optimal). The proposed procedure proved to be reliable and able to select the optimal approach among multiple IPMs. This experiment may be reproduced to identify the optimal approach for each case of locally available test foods. © 2016 John Wiley & Sons Ltd.

Skin autofluorescence is associated with renal function and cardiovascular diseases in pre-dialysis chronic kidney disease patients.

PubMed

Tanaka, Kenichi; Tani, Yoshihiro; Asai, Jun; Nemoto, Fumihiko; Kusano, Yuki; Suzuki, Hodaka; Hayashi, Yoshimitsu; Asahi, Koichi; Katoh, Tetsuo; Miyata, Toshio; Watanabe, Tsuyoshi

2011-01-01

Tissue accumulation of advanced glycation end-products (AGE) is thought to be a contributing factor to the progression of cardiovascular disease (CVD). Skin autofluorescence, a non-invasive measure of AGE accumulation using autofluorescence of the skin under ultraviolet light, has shown associations with CVD in haemodialysis patients. The present study aimed to evaluate relationships of skin autofluorescence to renal function as well as CVD in pre-dialysis patients with chronic kidney disease (CKD). Subjects in this cross-sectional analysis comprised 304 pre-dialysis CKD patients [median age, 62.0 years; median estimated glomerular filtration rate (eGFR), 54.3 mL/min/1.73 m(2); diabetes, n = 81 (26.6%)]. AGE accumulation in skin was assessed by skin autofluorescence using an autofluorescence reader. Relationships between skin autofluorescence, eGFR, CVD history and other parameters were evaluated. Skin autofluorescence correlated negatively with eGFR (r = -0.42, P < 0.01) and increased as CKD stage advanced. Multiple regression analysis revealed significant correlations of skin autofluorescence with age, presence of diabetes, eGFR and CVD history in CKD patients (R(2) = 30%). Age, male gender, smoking history, skin autofluorescence and eGFR were significantly correlated with CVD history, and multiple logistic regression analysis identified age [odds ratio (OR), 1.09; 95% confidence interval (CI), 1.03-1.15; P < 0.01], history of smoking (OR, 6.50; 95%CI, 1.94-21.83; P < 0.01) and skin autofluorescence (OR, 3.74; 95%CI, 1.54-9.24; P < 0.01) as independent factors. Tissue AGE accumulation measured as skin autofluorescence increased as GFR decreased and was related to CVD history in CKD patients. Non-invasive autofluorescence readers may provide potential markers for clinical risk assessment in pre-dialysis CKD patients.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

Correlation between static radiographic measurements and intersegmental angular measurements during gait using a multisegment foot model.

PubMed

Lee, Dong Yeon; Seo, Sang Gyo; Kim, Eo Jin; Kim, Sung Ju; Lee, Kyoung Min; Farber, Daniel C; Chung, Chin Youb; Choi, In Ho

2015-01-01

Radiographic examination is a widely used evaluation method in the orthopedic clinic. However, conventional radiography alone does not reflect the dynamic changes between foot and ankle segments during gait. Multiple 3-dimensional multisegment foot models (3D MFMs) have been introduced to evaluate intersegmental motion of the foot. In this study, we evaluated the correlation between static radiographic indices and intersegmental foot motion indices. One hundred twenty-five females were tested. Static radiographs of full-leg and anteroposterior (AP) and lateral foot views were performed. For hindfoot evaluation, we measured the AP tibiotalar angle (TiTA), talar tilt (TT), calcaneal pitch, lateral tibiocalcaneal angle, and lateral talcocalcaneal angle. For the midfoot segment, naviculocuboid overlap and talonavicular coverage angle were calculated. AP and lateral talo-first metatarsal angles and metatarsal stacking angle (MSA) were measured to assess the forefoot. Hallux valgus angle (HVA) and hallux interphalangeal angle were measured. In gait analysis by 3D MFM, intersegmental angle (ISA) measurements of each segment (hallux, forefoot, hindfoot, arch) were recorded. ISAs at midstance phase were most highly correlated with radiography. Significant correlations were observed between ISA measurements using MFM and static radiographic measurements in the same segment. In the hindfoot, coronal plane ISA was correlated with AP TiTA (P < .001) and TT (P = .018). In the hallux, HVA was strongly correlated with transverse ISA of the hallux (P < .001). The segmental foot motion indices at midstance phase during gait measured by 3D MFM gait analysis were correlated with the conventional radiographic indices. The observed correlation between MFM measurements at midstance phase during gait and static radiographic measurements supports the fundamental basis for the use of MFM in analysis of dynamic motion of foot segment during gait. © The Author(s) 2014.

Spectral density mapping at multiple magnetic fields suitable for 13C NMR relaxation studies

NASA Astrophysics Data System (ADS)

Kadeřávek, Pavel; Zapletal, Vojtěch; Fiala, Radovan; Srb, Pavel; Padrta, Petr; Přecechtělová, Jana Pavlíková; Šoltésová, Mária; Kowalewski, Jozef; Widmalm, Göran; Chmelík, Josef; Sklenář, Vladimír; Žídek, Lukáš

2016-05-01

Standard spectral density mapping protocols, well suited for the analysis of 15N relaxation rates, introduce significant systematic errors when applied to 13C relaxation data, especially if the dynamics is dominated by motions with short correlation times (small molecules, dynamic residues of macromolecules). A possibility to improve the accuracy by employing cross-correlated relaxation rates and on measurements taken at several magnetic fields has been examined. A suite of protocols for analyzing such data has been developed and their performance tested. Applicability of the proposed protocols is documented in two case studies, spectral density mapping of a uniformly labeled RNA hairpin and of a selectively labeled disaccharide exhibiting highly anisotropic tumbling. Combination of auto- and cross-correlated relaxation data acquired at three magnetic fields was applied in the former case in order to separate effects of fast motions and conformational or chemical exchange. An approach using auto-correlated relaxation rates acquired at five magnetic fields, applicable to anisotropically moving molecules, was used in the latter case. The results were compared with a more advanced analysis of data obtained by interpolation of auto-correlated relaxation rates measured at seven magnetic fields, and with the spectral density mapping of cross-correlated relaxation rates. The results showed that sufficiently accurate values of auto- and cross-correlated spectral density functions at zero and 13C frequencies can be obtained from data acquired at three magnetic fields for uniformly 13C -labeled molecules with a moderate anisotropy of the rotational diffusion tensor. Analysis of auto-correlated relaxation rates at five magnetic fields represents an alternative for molecules undergoing highly anisotropic motions.

Forward-backward multiplicity correlations in pp collisions at $$\\sqrt{s}$$ = 0.9, 2.76 and 7 TeV

DOE PAGES

Adam, J.; Adamová, D.; Aggarwal, M. M.; ...

2015-05-20

The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions atmore » $$\\sqrt{s}$$ = 0.9, 2.76 and 7 TeV. The measurement is performed in the central pseudorapidity region (|η| < 0.8) for the transverse momentum p T > 0.3 GeV/c. Two separate pseudorapidity windows of width ($$\\delta$$η) ranging from 0.2 to 0.8 are chosen symmetrically around η = 0. The multiplicity correlation strength (b corr) is studied as a function of the pseudorapidity gap (η gap) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing η gap and shows a non-linear increase with $$\\delta$$η. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the symmetric FB η-windows. Two different contributions, the short-range (SR) and the long-range (LR), are observed. The energy dependence of b corr is found to be weak for the SR component while it is strong for the LR component. Moreover, the correlation coefficient is studied for particles belonging to various transverse momentum intervals chosen to have the same mean multiplicity. Both SR and LR contributions to b corr are found to increase with p T in this case. Results are compared to PYTHIA and PHOJET event generators and to a string-based phenomenological model. In conclusion, the observed dependencies of b corr add new constraints on phenomenological models.« less

Forward-backward multiplicity correlations in pp collisions at = 0.9, 2.76 and 7 TeV

NASA Astrophysics Data System (ADS)

Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmed, I.; Ahn, S. U.; Aimo, I.; Aiola, S.; Ajaz, M.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Armesto, N.; Arnaldi, R.; Aronsson, T.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Bach, M.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baltasar Dos Santos Pedrosa, F.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biswas, S.; Bjelogrlic, S.; Blanco, F.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botje, M.; Botta, E.; Böttger, S.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Cavicchioli, C.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deloff, A.; Dénes, E.; D'Erasmo, G.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Dobrowolski, T.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Erazmus, B.; Erdal, H. A.; Eschweiler, D.; Espagnon, B.; Esposito, M.; Estienne, M.; Esumi, S.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Felea, D.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Germain, M.; Gheata, A.; Gheata, M.; Ghidini, B.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Gomez Ramirez, A.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gulkanyan, H.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hanratty, L. D.; Hansen, A.; Harris, J. W.; Hartmann, H.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hilden, T. E.; Hillemanns, H.; Hippolyte, B.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Ilkiv, I.; Inaba, M.; Ionita, C.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Jacholkowski, A.; Jacobs, P. M.; Jahnke, C.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, K. H.; Khan, M. M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, B.; Kim, D. W.; Kim, D. J.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Köhler, M. K.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kovalenko, V.; Kowalski, M.; Kox, S.; Koyithatta Meethaleveedu, G.; Kral, J.; Králik, I.; Kravčáková, A.; Krelina, M.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kucheriaev, Y.; Kugathasan, T.; Kuhn, C.; Kuijer, P. G.; Kulakov, I.; Kumar, J.; Kumar, L.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Legrand, I.; Lehnert, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loggins, V. R.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Lu, X.-G.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manceau, L.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martashvili, I.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martynov, Y.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Morando, M.; Moreira De Godoy, D. A.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Müller, H.; Mulligan, J. D.; Munhoz, M. G.; Murray, S.; Musa, L.; Musinsky, J.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Nilsen, B. S.; Noferini, F.; Nomokonov, P.; Nooren, G.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Onderwaater, J.; Oppedisano, C.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pajares, C.; Pal, S. K.; Pan, J.; Pandey, A. K.; Pant, D.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Patalakha, D. I.; Paticchio, V.; Paul, B.; Pawlak, T.; Peitzmann, T.; Pereira Da Costa, H.; Pereira De Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Rauf, A. W.; Razazi, V.; Read, K. F.; Real, J. S.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reicher, M.; Reidt, F.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Rettig, F.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rivetti, A.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salgado, C. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sanchez Castro, X.; Šándor, L.; Sandoval, A.; Sano, M.; Santagati, G.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Seeder, K. S.; Segato, G.; Seger, J. E.; Sekiguchi, Y.; Selyuzhenkov, I.; Senosi, K.; Seo, J.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Skjerdal, K.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Soltz, R.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stefanek, G.; Steinpreis, M.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Sultanov, R.; Šumbera, M.; Symons, T. J. M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Takahashi, J.; Tanaka, N.; Tangaro, M. A.; Tapia Takaki, J. D.; Tarantola Peloni, A.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Wang, Y.; Watanabe, D.; Weber, M.; Weber, S. G.; Wessels, J. P.; Westerhoff, U.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yamaguchi, Y.; Yang, H.; Yang, P.; Yano, S.; Yasnopolskiy, S.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zhu, X.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

2015-05-01

The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at = 0 .9, 2 .76 and 7 TeV. The measurement is performed in the central pseudorapidity region (| η| < 0 .8) for the transverse momentum p T > 0 .3 GeV /c. Two separate pseudorapidity windows of width ( δη) ranging from 0.2 to 0.8 are chosen symmetrically around η = 0. The multiplicity correlation strength ( b corr) is studied as a function of the pseudorapidity gap ( η gap) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing η gap and shows a non-linear increase with δη. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the symmetric FB η-windows. Two different contributions, the short-range (SR) and the long-range (LR), are observed. The energy dependence of b corr is found to be weak for the SR component while it is strong for the LR component. Moreover, the correlation coefficient is studied for particles belonging to various transverse momentum intervals chosen to have the same mean multiplicity. Both SR and LR contributions to b corr are found to increase with p T in this case. Results are compared to PYTHIA and PHOJET event generators and to a string-based phenomenological model. The observed dependencies of b corr add new constraints on phenomenological models. [Figure not available: see fulltext.

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach

PubMed Central

Shi, Xingjie; Zhao, Qing; Huang, Jian; Xie, Yang; Ma, Shuangge

2015-01-01

Motivation: Both gene expression levels (GEs) and copy number alterations (CNAs) have important biological implications. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The regulation analysis is challenging with one gene expression possibly regulated by multiple CNAs and one CNA potentially regulating the expressions of multiple genes. The correlations among GEs and among CNAs make the analysis even more complicated. The existing methods have limitations and cannot comprehensively describe the regulation. Results: A sparse double Laplacian shrinkage method is developed. It jointly models the effects of multiple CNAs on multiple GEs. Penalization is adopted to achieve sparsity and identify the regulation relationships. Network adjacency is computed to describe the interconnections among GEs and among CNAs. Two Laplacian shrinkage penalties are imposed to accommodate the network adjacency measures. Simulation shows that the proposed method outperforms the competing alternatives with more accurate marker identification. The Cancer Genome Atlas data are analysed to further demonstrate advantages of the proposed method. Availability and implementation: R code is available at http://works.bepress.com/shuangge/49/ Contact: shuangge.ma@yale.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26342102

Interventional effects for mediation analysis with multiple mediators

PubMed Central

Vansteelandt, Stijn; Daniel, Rhian M.

2016-01-01

The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator–outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins21 introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal in order to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when – as often – the structural dependence between the multiple mediators is unknown; for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators. PMID:27922534

Interventional Effects for Mediation Analysis with Multiple Mediators.

PubMed

Vansteelandt, Stijn; Daniel, Rhian M

2017-03-01

The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator-outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when-as often-the structural dependence between the multiple mediators is unknown, for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators.

Two- and Multi-particle Azimuthal Correlations in Small Collision Systems with the ATLAS Detector

NASA Astrophysics Data System (ADS)

Trzupek, Adam; Atlas Collaboration

2017-11-01

The recent ATLAS results on two- and multi-particle azimuthal correlations of charged particles are presented for √{ s} = 5.02 TeV and 13 TeV pp, √{sNN} = 5.02 TeV p + Pb and √{sNN} = 2.76 TeV low-multiplicity Pb + Pb collisions. To suppress the "non-flow" contribution from the correlations, a template fitting procedure is used in the two-particle correlations (2PC) measurements, while for multi-particle correlations the cumulant method is applied. The correlations are expressed in the form of Fourier harmonics vn (n = 2 , 3 , 4) measuring the global azimuthal anisotropy of produced particles. The measurements presented hereafter confirm the evidence for collective phenomena in high-multiplicity p + Pb and low-multiplicity Pb + Pb collisions. For pp collisions the results on four-particle cumulants do not demonstrate a similar collective behaviour.

The Negative Correlation between Fiber Color and Quality Traits Revealed by QTL Analysis.

PubMed

Feng, Hongjie; Guo, Lixue; Wang, Gaskin; Sun, Junling; Pan, Zhaoe; He, Shoupu; Zhu, Heqin; Sun, Jie; Du, Xiongming

2015-01-01

Naturally existing colored cotton was far from perfection due to having genetic factors for lower yield, poor fiber quality and monotonous color. These factors posed a challenge to colored cotton breeding and innovation. To identify novel quantitative trait loci (QTL) for fiber color along with understanding of correlation between fiber color and quality in colored cotton, a RIL and two F2 populations were generated from crosses among Zong128 (Brown fiber cotton) and two white fiber cotton lines which were then analyzed in four environments. Two stable and major QTLs (qLC-7-1, qFC-7-1) for fiber lint and fuzz color were detected accounting for 16.01%-59.85% of the phenotypic variation across multiple generations and environments. Meanwhile, some minor QTLs were also identified on chromosomes 5, 14, 21 and 24 providing low phenotypic variation (<5%) from only F2 populations, not from the RILs population. Especially, a multiple-effect locus for fiber color and quality has been detected between flanking markers NAU1043 and NAU3654 on chromosome 7 (A genome) over multiple environments. Of which, qLC-7-1, qFC-7-1 were responsible for positive effects and improved fiber color in offsprings. Meanwhile, the QTLs (qFL-7-1, qFU-7-1, qFF-7-1, qFE-7-1, and qFS-7-1) for fiber quality had negative effects and explained 2.19%-8.78% of the phenotypic variation. This multiple-effect locus for fiber color and quality may reveal the negative correlation between the two types of above traits, so paving the way towards cotton genetic improvement.

Stratigraphic framework for Pliocene paleoclimate reconstruction: The correlation conundrum

USGS Publications Warehouse

Dowsett, H.J.; Robinson, M.M.

2006-01-01

Pre-Holocene paleoclimate reconstructions face a correlation conundrum because complications inherent in the stratigraphic record impede the development of synchronous reconstruction. The Pliocene Research, Interpretation and Synoptic Mapping (PRISM) paleoenvironmental reconstructions have carefully balanced temporal resolution and paleoclimate proxy data to achieve a useful and reliable product and are the most comprehensive pre-Pleistocene data sets available for analysis of warmer-than-present climate and for climate modeling experiments. This paper documents the stratigraphic framework for the mid-Pliocene sea surface temperature (SST) reconstruction of the North Atlantic and explores the relationship between stratigraphic/temporal resolution and various paleoceanographic estimates of SST. The magnetobiostratigraphic framework for the PRISM North Atlantic region is constructed from planktic foraminifer, calcareous nannofossil and paleomagnetic reversal events recorded in deep-sea cores and calibrated to age. Planktic foraminifer census data from multiple samples within the mid-Pliocene yield multiple SST estimates for each site. Extracting a single SST value at each site from multiple estimates, given the limitations of the material and stratigraphic resolution, is problematic but necessary for climate model experiments. The PRISM reconstruction, unprecedented in its integration of many different types of data at a focused stratigraphic interval, utilizes a time slab approach and is based on warm peak average temperatures. A greater understanding of the dynamics of the climate system and significant advances in models now mandate more precise, globally distributed yet temporally synchronous SST estimates than are available through averaging techniques. Regardless of the precision used to correlate between sequences within the midd-Pliocene, a truly synoptic reconstruction in the temporal sense is unlikely. SST estimates from multiple proxies promise to further refine paleoclimate reconstructions but must consider the complications associated with each method, what each proxy actually records, and how these different proxies compare in time-averaged samples.

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

[Analysis of HIV/AIDS related risk behaviors and their impact factors among out-of-school adolescents in outflow areas].

PubMed

Sun, Xiao; Zhu, Guang-rong; Ji, Cheng-ye; Wang, Zhen-zhen

2012-06-18

To analyze HIV/AIDS related risk behaviors among unmarried outside school adolescents and the impact factors in outflow areas, in order to provide basis for related health education. Using cluster sampling method, we investigated a vocational training center for all 15- to 24-year-old unmarried outside school youths in one county. The structured questionnaire based on the Theory of Reasoned Action was anonymous, which filled envelopes on the spot. A total of 1 800 questionnaires were recovered, and 1 712 questionnaires were valid. Epidata 3.0 was used for establishing a database and SPSS 13.0 for statistical analysis. (1) The incidence of HIV/AIDS risk behaviors of the outside school adolescents was high: 18.0% of the respondents had sexual behavior, 27.3% had never used condom when sexed in the past three months, 31.0% had multiple sexual partners, and 9.7% had drug abuse experience; the rate of HIV/AIDS-related knowledge was only 25.1%; peer environment of respondents was poor. (2) The use of condoms was correlated with those who had higher score of AIDS knowledge, and who could talk about condoms in sexual intercourse; The multiple sexual partners' behavior was correlated with age, friends who were themselves multiple sexual partners, high score of the attitude, and the subjective norm; The commercial sex was correlated with the family address, high score of the HIV/AIDS-related knowledge, friends who had commercial sex, the subjective norm and the intention of behavior, The drug abuse behavior was correlated with age, high score of the HIV/AIDS-related knowledge, drug abuse among their friends, the subjective norm, and the intention of behavior. (3) Subjective norms and behavioral intentions could better predict the occurrence of HIV/AIDS risk behaviors. The outside school adolescents are at risk in lack of HIV/AIDS-related knowledge and coping skills of negative peer pressure, so providing the related health education before they go and work outside their home is the "critical period".