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.

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.

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

ERIC Educational Resources Information Center

Krishnamoorthy, K.; Xia, Yanping

2008-01-01

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

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

An Automated Parallel Image Registration Technique Based on the Correlation of Wavelet Features

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Campbell, William J.; Cromp, Robert F.; Zukor, Dorothy (Technical Monitor)

2001-01-01

With the increasing importance of multiple platform/multiple remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Our work utilizes maxima of wavelet coefficients to form the basic features of a correlation-based automatic registration algorithm. Our wavelet-based registration algorithm is tested successfully with data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Landsat/Thematic Mapper(TM), which differ by translation and/or rotation. By the choice of high-frequency wavelet features, this method is similar to an edge-based correlation method, but by exploiting the multi-resolution nature of a wavelet decomposition, our method achieves higher computational speeds for comparable accuracies. This algorithm has been implemented on a Single Instruction Multiple Data (SIMD) massively parallel computer, the MasPar MP-2, as well as on the CrayT3D, the Cray T3E and a Beowulf cluster of Pentium workstations.

Two methods for parameter estimation using multiple-trait models and beef cattle field data.

PubMed

Bertrand, J K; Kriese, L A

1990-08-01

Two methods are presented for estimating variances and covariances from beef cattle field data using multiple-trait sire models. Both methods require that the first trait have no missing records and that the contemporary groups for the second trait be subsets of the contemporary groups for the first trait; however, the second trait may have missing records. One method uses pseudo expectations involving quadratics composed of the solutions and the right-hand sides of the mixed model equations. The other method is an extension of Henderson's Simple Method to the multiple trait case. Neither of these methods requires any inversions of large matrices in the computation of the parameters; therefore, both methods can handle very large sets of data. Four simulated data sets were generated to evaluate the methods. In general, both methods estimated genetic correlations and heritabilities that were close to the Restricted Maximum Likelihood estimates and the true data set values, even when selection within contemporary groups was practiced. The estimates of residual correlations by both methods, however, were biased by selection. These two methods can be useful in estimating variances and covariances from multiple-trait models in large populations that have undergone a minimal amount of selection within contemporary groups.

Local denoising of digital speckle pattern interferometry fringes by multiplicative correlation and weighted smoothing splines.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2005-05-10

We evaluate the use of smoothing splines with a weighted roughness measure for local denoising of the correlation fringes produced in digital speckle pattern interferometry. In particular, we also evaluate the performance of the multiplicative correlation operation between two speckle patterns that is proposed as an alternative procedure to generate the correlation fringes. It is shown that the application of a normalization algorithm to the smoothed correlation fringes reduces the excessive bias generated in the previous filtering stage. The evaluation is carried out by use of computer-simulated fringes that are generated for different average speckle sizes and intensities of the reference beam, including decorrelation effects. A comparison with filtering methods based on the continuous wavelet transform is also presented. Finally, the performance of the smoothing method in processing experimental data is illustrated.

Multivariate meta-analysis using individual participant data

PubMed Central

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

2016-01-01

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 that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Method and apparatus for fiber optic multiple scattering suppression

NASA Technical Reports Server (NTRS)

Ackerson, Bruce J. (Inventor)

2000-01-01

The instant invention provides a method and apparatus for use in laser induced dynamic light scattering which attenuates the multiple scattering component in favor of the single scattering component. The preferred apparatus utilizes two light detectors that are spatially and/or angularly separated and which simultaneously record the speckle pattern from a single sample. The recorded patterns from the two detectors are then cross correlated in time to produce one point on a composite single/multiple scattering function curve. By collecting and analyzing cross correlation measurements that have been taken at a plurality of different spatial/angular positions, the signal representative of single scattering may be differentiated from the signal representative of multiple scattering, and a near optimum detector separation angle for use in taking future measurements may be determined.

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.

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.

Strong correlation in incremental full configuration interaction

NASA Astrophysics Data System (ADS)

Zimmerman, Paul M.

2017-06-01

Incremental Full Configuration Interaction (iFCI) reaches high accuracy electronic energies via a many-body expansion of the correlation energy. In this work, the Perfect Pairing (PP) ansatz replaces the Hartree-Fock reference of the original iFCI method. This substitution captures a large amount of correlation at zero-order, which allows iFCI to recover the remaining correlation energy with low-order increments. The resulting approach, PP-iFCI, is size consistent, size extensive, and systematically improvable with increasing order of incremental expansion. Tests on multiple single bond, multiple double bond, and triple bond dissociations of main group polyatomics using double and triple zeta basis sets demonstrate the power of the method for handling strong correlation. The smooth dissociation profiles that result from PP-iFCI show that FCI-quality ground state computations are now within reach for systems with up to about 10 heavy atoms.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

NASA Astrophysics Data System (ADS)

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai

2015-05-01

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiport nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

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

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai, E-mail: jtjing@phy.ecnu.edu.cn

2015-05-25

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiportmore » nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.« less

Multiplication and Presence of Shielding Material from Time-Correlated Pulse-Height Measurements of Subcritical Plutonium Assemblies

DOE PAGES

Monterial, Mateusz; Marleau, Peter; Paff, Marc; ...

2017-01-20

Here, we present the results from the first measurements of the Time-Correlated Pulse-Height (TCPH) distributions from 4.5 kg sphere of α-phase weapons-grade plutonium metal in five configurations: bare, reflected by 1.27 cm and 2.54 cm of tungsten, and 2.54 cm and 7.62 cm of polyethylene. A new method for characterizing source multiplication and shielding configuration is also demonstrated. The method relies on solving for the underlying fission chain timing distribution that drives the spreading of the measured TCPH distribution. We found that a gamma distribution fits the fission chain timing distribution well and that the fit parameters correlate with bothmore » multiplication (rate parameter) and shielding material types (shape parameter). The source-to-detector distance was another free parameter that we were able to optimize, and proved to be the most well constrained parameter. MCNPX-PoliMi simulations were used to complement the measurements and help illustrate trends in these parameters and their relation to multiplication and the amount and type of material coupled to the subcritical assembly.« less

Multiplication and Presence of Shielding Material from Time-Correlated Pulse-Height Measurements of Subcritical Plutonium Assemblies

NASA Astrophysics Data System (ADS)

Monterial, Mateusz; Marleau, Peter; Paff, Marc; Clarke, Shaun; Pozzi, Sara

2017-04-01

We present the results from the first measurements of the Time-Correlated Pulse-Height (TCPH) distributions from 4.5 kg sphere of α-phase weapons-grade plutonium metal in five configurations: bare, reflected by 1.27 cm and 2.54 cm of tungsten, and 2.54 cm and 7.62 cm of polyethylene. A new method for characterizing source multiplication and shielding configuration is also demonstrated. The method relies on solving for the underlying fission chain timing distribution that drives the spreading of the measured TCPH distribution. We found that a gamma distribution fits the fission chain timing distribution well and that the fit parameters correlate with both multiplication (rate parameter) and shielding material types (shape parameter). The source-to-detector distance was another free parameter that we were able to optimize, and proved to be the most well constrained parameter. MCNPX-PoliMi simulations were used to complement the measurements and help illustrate trends in these parameters and their relation to multiplication and the amount and type of material coupled to the subcritical assembly.

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-04

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. Copyright © 2018 Montesinos-Lopez et al.

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C.; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-01

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. PMID:29097376

Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method

PubMed Central

Zhou, Sujuan; Liu, Bo; Meng, Jiang

2017-01-01

Background: Raw Moutan cortex (RMC) is an important Chinese herbal medicine. Comprehensive and objective quality evaluation of Chinese herbal medicine has been one of the most important issues in the modern herbs development. Objective: To evaluate and compare the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Materials and Methods: The percentage composition of gallic acid, catechin, oxypaeoniflorin, paeoniflorin, quercetin, benzoylpaeoniflorin, paeonol in different batches of RMC was determined, and then adopting MATLAB programming to construct the gray correlation-TOPSIS assessment model for quality evaluation of RMC. Results: The quality evaluation results of model evaluation and objective evaluation were consistent, reliable, and stable. Conclusion: The model of gray correlation-TOPSIS can be well applied to the quality evaluation of traditional Chinese medicine with multiple components and has broad prospect in application. SUMMARY The experiment tries to construct a model to evaluate the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Results show the model is reliable and provide a feasible way in evaluating quality of traditional Chinese medicine with multiple components. PMID:28839384

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.

On dealing with multiple correlation peaks in PIV

NASA Astrophysics Data System (ADS)

Masullo, A.; Theunissen, R.

2018-05-01

A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

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.

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.

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'…

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

Multilabel learning via random label selection for protein subcellular multilocations prediction.

PubMed

Wang, Xiao; Li, Guo-Zheng

2013-01-01

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multilocation proteins to multiple proteins with single location, which does not take correlations among different subcellular locations into account. In this paper, a novel method named random label selection (RALS) (multilabel learning via RALS), which extends the simple binary relevance (BR) method, is proposed to learn from multilocation proteins in an effective and efficient way. RALS does not explicitly find the correlations among labels, but rather implicitly attempts to learn the label correlations from data by augmenting original feature space with randomly selected labels as its additional input features. Through the fivefold cross-validation test on a benchmark data set, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark data sets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multilocations of proteins. The prediction web server is available at >http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

NASA Astrophysics Data System (ADS)

Gan, Luping; Li, Yan-Feng; Zhu, Shun-Peng; Yang, Yuan-Jian; Huang, Hong-Zhong

2014-06-01

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.

The Development of the CMS Zero Degree Calorimeters to Derive the Centrality of AA Collisions

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

Wood, Jeffrey Scott

The centrality of РЬРЬ collisions is derived using correlations from the zero degree calorimeter (ZDC) signal and pixel multiplicity at the Compact Muon Solenoid (CMS) Experiment using data from the heavy ion run in 2010. The method to derive the centrality takes the two-dimensional correlation between the ZDC and pixels and linearizes it for sorting events. The initial method for deriving the centrality at CMS uses the energy deposit in the HF detector, and it is compared to the centrality derived Ьу the correlations in ZDC and pixel multiplicity. This comparison highlights the similarities between the results of both methodsmore » in central collisions, as expected, and deviations in the results in peripheral collisions. The ZDC signals in peripheral collisions are selected Ьу low pixel multiplicity to oЬtain а ZDC neutron spectrum, which is used to effectively gain match both sides of the ZDC« less

Development and evaluation of modified envelope correlation method for deep tectonic tremor

NASA Astrophysics Data System (ADS)

Mizuno, N.; Ide, S.

2017-12-01

We develop a new location method for deep tectonic tremors, as an improvement of widely used envelope correlation method, and applied it to construct a tremor catalog in western Japan. Using the cross-correlation functions as objective functions and weighting components of data by the inverse of error variances, the envelope cross-correlation method is redefined as a maximum likelihood method. This method is also capable of multiple source detection, because when several events occur almost simultaneously, they appear as local maxima of likelihood.The average of weighted cross-correlation functions, defined as ACC, is a nonlinear function whose variable is a position of deep tectonic tremor. The optimization method has two steps. First, we fix the source depth to 30 km and use a grid search with 0.2 degree intervals to find the maxima of ACC, which are candidate event locations. Then, using each of the candidate locations as initial values, we apply a gradient method to determine horizontal and vertical components of a hypocenter. Sometimes, several source locations are determined in a time window of 5 minutes. We estimate the resolution, which is defined as a distance of sources to be detected separately by the location method, is about 100 km. The validity of this estimation is confirmed by a numerical test using synthetic waveforms. Applying to continuous seismograms in western Japan for over 10 years, the new method detected 27% more tremors than a previous method, owing to the multiple detection and improvement of accuracy by appropriate weighting scheme.

Multiple Testing with Modified Bonferroni Methods.

ERIC Educational Resources Information Center

Li, Jianmin; And Others

This paper discusses the issue of multiple testing and overall Type I error rates in contexts other than multiple comparisons of means. It demonstrates, using a 5 x 5 correlation matrix, the application of 5 recently developed modified Bonferroni procedures developed by the following authors: (1) Y. Hochberg (1988); (2) B. S. Holland and M. D.…

Optimization of OT-MACH Filter Generation for Target Recognition

NASA Technical Reports Server (NTRS)

Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

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.

Approximation of reliabilities for multiple-trait model with maternal effects.

PubMed

Strabel, T; Misztal, I; Bertrand, J K

2001-04-01

Reliabilities for a multiple-trait maternal model were obtained by combining reliabilities obtained from single-trait models. Single-trait reliabilities were obtained using an approximation that supported models with additive and permanent environmental effects. For the direct effect, the maternal and permanent environmental variances were assigned to the residual. For the maternal effect, variance of the direct effect was assigned to the residual. Data included 10,550 birth weight, 11,819 weaning weight, and 3,617 postweaning gain records of Senepol cattle. Reliabilities were obtained by generalized inversion and by using single-trait and multiple-trait approximation methods. Some reliabilities obtained by inversion were negative because inbreeding was ignored in calculating the inverse of the relationship matrix. The multiple-trait approximation method reduced the bias of approximation when compared with the single-trait method. The correlations between reliabilities obtained by inversion and by multiple-trait procedures for the direct effect were 0.85 for birth weight, 0.94 for weaning weight, and 0.96 for postweaning gain. Correlations for maternal effects for birth weight and weaning weight were 0.96 to 0.98 for both approximations. Further improvements can be achieved by refining the single-trait procedures.

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Simultaneously measuring multiple protein interactions and their correlations in a cell by Protein-interactome Footprinting

PubMed Central

Luo, Si-Wei; Liang, Zhi; Wu, Jia-Rui

2017-01-01

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerization of the target proteins fused with DNA-binding domains. The interaction intensity of each target protein is quantified as the copy number of the specific DNA sequences bound by each fusion protein dimers. Using PiF, we quantitatively reveal dynamic patterns of PPIs and their correlation network in E. coli two-component systems. PMID:28338015

Fuzzy neural network technique for system state forecasting.

PubMed

Li, Dezhi; Wang, Wilson; Ismail, Fathy

2013-10-01

In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.

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.

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

Psychophysical Reverse Correlation with Multiple Response Alternatives

PubMed Central

Dai, Huanping; Micheyl, Christophe

2011-01-01

Psychophysical reverse-correlation methods such as the “classification image” technique provide a unique tool to uncover the internal representations and decision strategies of individual participants in perceptual tasks. Over the last thirty years, these techniques have gained increasing popularity among both visual and auditory psychophysicists. However, thus far, principled applications of the psychophysical reverse-correlation approach have been almost exclusively limited to two-alternative decision (detection or discrimination) tasks. Whether and how reverse-correlation methods can be applied to uncover perceptual templates and decision strategies in situations involving more than just two response alternatives remains largely unclear. Here, the authors consider the problem of estimating perceptual templates and decision strategies in stimulus identification tasks with multiple response alternatives. They describe a modified correlational approach, which can be used to solve this problem. The approach is evaluated under a variety of simulated conditions, including different ratios of internal-to-external noise, different degrees of correlations between the sensory observations, and various statistical distributions of stimulus perturbations. The results indicate that the proposed approach is reasonably robust, suggesting that it could be used in future empirical studies. PMID:20695712

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Graphical correlation of gaging-station records

USGS Publications Warehouse

Searcy, James K.

1960-01-01

A gaging-station record is a sample of the rate of flow of a stream at a given site. This sample can be used to estimate the magnitude and distribution of future flows if the record is long enough to be representative of the long-term flow of the stream. The reliability of a short-term record for estimating future flow characteristics can be improved through correlation with a long-term record. Correlation can be either numerical or graphical, but graphical correlation of gaging-station records has several advantages. The graphical correlation method is described in a step-by-step procedure with an illustrative problem of simple correlation, illustrative problems of three examples of multiple correlation--removing seasonal effect--and two examples of correlation of one record with two other records. Except in the problem on removal of seasonal effect, the same group of stations is used in the illustrative problems. The purpose of the problems is to illustrate the method--not to show the improvement that can result from multiple correlation as compared with simple correlation. Hydrologic factors determine whether a usable relation exists between gaging-station records. Statistics is only a tool for evaluating and using an existing relation, and the investigator must be guided by a knowledge of hydrology.

Resampling-based Methods in Single and Multiple Testing for Equality of Covariance/Correlation Matrices

PubMed Central

Yang, Yang; DeGruttola, Victor

2016-01-01

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients. PMID:22740584

Resampling-based methods in single and multiple testing for equality of covariance/correlation matrices.

PubMed

Yang, Yang; DeGruttola, Victor

2012-06-22

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.

Integrating Multiple Criteria in Selection Procedures for Improving Student Quality and Reducing Cost Per Graduate. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Jones, Gerald L.; Westen, Risdon J.

The multivariate approach of canonical correlation was used to assess selection procedures of the Air Force Academy. It was felt that improved student selection methods might reduce the number of dropouts while maintaining or improving the quality of graduates. The method of canonical correlation was designed to maximize prediction of academic…

The separate universe approach to soft limits

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

Kenton, Zachary; Mulryne, David J., E-mail: z.a.kenton@qmul.ac.uk, E-mail: d.mulryne@qmul.ac.uk

We develop a formalism for calculating soft limits of n -point inflationary correlation functions using separate universe techniques. Our method naturally allows for multiple fields and leads to an elegant diagrammatic approach. As an application we focus on the trispectrum produced by inflation with multiple light fields, giving explicit formulae for all possible single- and double-soft limits. We also investigate consistency relations and present an infinite tower of inequalities between soft correlation functions which generalise the Suyama-Yamaguchi inequality.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method.

PubMed

Leung, Denis H Y; Wang, You-Gan; Zhu, Min

2009-07-01

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Characterization of Fissile Assemblies Using Low-Efficiency Detection Systems

DOE PAGES

Chapline, George F.; Verbeke, Jerome M.

2017-02-02

Here, we have investigated the possibility that the amount, chemical form, multiplication, and shape of the fissile material in an assembly can be passively assayed using scintillator detection systems by only measuring the fast neutron pulse height distribution and distribution of time intervals Δt between fast neutrons. We have previously demonstrated that the alpha-ratio can be obtained from the observed pulse height distribution for fast neutrons. In this paper we report that we report that when the distribution of time intervals is plotted as a function of logΔt, the position of the correlated neutron peak is nearly independent of detectormore » efficiency and determines the internal relaxation rate for fast neutrons. If this information is combined with knowledge of the alpha-ratio, then the position of the minimum between the correlated and uncorrelated peaks can be used to rapidly estimate the mass, multiplication, and shape of fissile material. This method does not require a priori knowledge of either the efficiency for neutron detection or the alpha-ratio. Although our method neglects 3-neutron correlations, we have used previously obtained experimental data for metallic and oxide forms of Pu to demonstrate that our method yields good estimates for multiplications as large as 2, and that the only constraint on detector efficiency/observation time is that a peak in the interval time distribution due to correlated neutrons is visible.« less

Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

PubMed

Wang, Xiao; Li, Guo-Zheng

2013-03-12

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

Measuring the scale dependence of intrinsic alignments using multiple shear estimates

NASA Astrophysics Data System (ADS)

Leonard, C. Danielle; Mandelbaum, Rachel

2018-06-01

We present a new method for measuring the scale dependence of the intrinsic alignment (IA) contamination to the galaxy-galaxy lensing signal, which takes advantage of multiple shear estimation methods applied to the same source galaxy sample. By exploiting the resulting correlation of both shape noise and cosmic variance, our method can provide an increase in the signal-to-noise of the measured IA signal as compared to methods which rely on the difference of the lensing signal from multiple photometric redshift bins. For a galaxy-galaxy lensing measurement which uses LSST sources and DESI lenses, the signal-to-noise on the IA signal from our method is predicted to improve by a factor of ˜2 relative to the method of Blazek et al. (2012), for pairs of shear estimates which yield substantially different measured IA amplitudes and highly correlated shape noise terms. We show that statistical error necessarily dominates the measurement of intrinsic alignments using our method. We also consider a physically motivated extension of the Blazek et al. (2012) method which assumes that all nearby galaxy pairs, rather than only excess pairs, are subject to IA. In this case, the signal-to-noise of the method of Blazek et al. (2012) is improved.

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

NASA Technical Reports Server (NTRS)

Park, Han G. (Inventor); Zak, Michail (Inventor); James, Mark L. (Inventor); Mackey, Ryan M. E. (Inventor)

2003-01-01

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

Multibin long-range correlations

NASA Astrophysics Data System (ADS)

Bialas, A.; Zalewski, K.

2011-06-01

A new method to study the long-range correlations in multiparticle production is developed. It is proposed to measure the joint factorial moments or cumulants of multiplicity distribution in several (more than two) bins. It is shown that this step dramatically increases the discriminative power of data.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Combined action of time-delay and colored cross-associated multiplicative and additive noises on stability and stochastic resonance for a stochastic metapopulation system

NASA Astrophysics Data System (ADS)

Wang, Kang-Kang; Zong, De-Cai; Wang, Ya-Jun; Li, Sheng-Hong

2016-05-01

In this paper, the transition between the stable state of a big density and the extinction state and stochastic resonance (SR) for a time-delayed metapopulation system disturbed by colored cross-correlated noises are investigated. By applying the fast descent method, the small time-delay approximation and McNamara and Wiesenfeld's SR theory, we investigate the impacts of time-delay, the multiplicative, additive noises and colored cross-correlated noise on the SNR and the shift between the two states of the system. Numerical results show that the multiplicative, additive noises and time-delay can all speed up the transition from the stable state to the extinction state, while the correlation noise and its correlation time can slow down the extinction process of the population system. With respect to SNR, the multiplicative noise always weakens the SR effect, while noise correlation time plays a dual role in motivating the SR phenomenon. Meanwhile, time-delay mainly plays a negative role in stimulating the SR phenomenon. Conversely, it could motivate the SR effect to increase the strength of the cross-correlation noise in the SNR-β plot, while the increase of additive noise intensity will firstly excite SR, and then suppress the SR effect.

Magnetic resonance spectroscopy of normal appearing white matter in early relapsing-remitting multiple sclerosis: correlations between disability and spectroscopy

PubMed Central

Ruiz-Peña, Juan Luis; Piñero, Pilar; Sellers, Guillermo; Argente, Joaquín; Casado, Alfredo; Foronda, Jesus; Uclés, Antonio; Izquierdo, Guillermo

2004-01-01

Background What currently appears to be irreversible axonal loss in normal appearing white matter, measured by proton magnetic resonance spectroscopy is of great interest in the study of Multiple Sclerosis. Our aim is to determine the axonal damage in normal appearing white matter measured by magnetic resonance spectroscopy and to correlate this with the functional disability measured by Multiple Sclerosis Functional Composite scale, Neurological Rating Scale, Ambulation Index scale, and Expanded Disability Scale Score. Methods Thirty one patients (9 male and 22 female) with relapsing remitting Multiple Sclerosis and a Kurtzke Expanded Disability Scale Score of 0–5.5 were recruited from four hospitals in Andalusia, Spain and included in the study. Magnetic resonance spectroscopy scans and neurological disability assessments were performed the same day. Results A statistically significant correlation was found (r = -0.38 p < 0.05) between disability (measured by Expanded Disability Scale Score) and N-Acetyl Aspartate (NAA/Cr ratio) levels in normal appearing white matter in these patients. No correlation was found between the NAA/Cr ratio and disability measured by any of the other disability assessment scales. Conclusions There is correlation between disability (measured by Expanded Disability Scale Score) and the NAA/Cr ratio in normal appearing white matter. The lack of correlation between the NAA/Cr ratio and the Multiple Sclerosis Functional Composite score indicates that the Multiple Sclerosis Functional Composite is not able to measure irreversible disability and would be more useful as a marker in stages where axonal damage is not a predominant factor. PMID:15191618

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Intensity ratio to improve black hole assessment in multiple sclerosis.

PubMed

Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H

2018-01-01

Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Psychophysical Reverse Correlation with Multiple Response Alternatives

ERIC Educational Resources Information Center

Dai, Huanping; Micheyl, Christophe

2010-01-01

Psychophysical reverse-correlation methods such as the "classification image" technique provide a unique tool to uncover the internal representations and decision strategies of individual participants in perceptual tasks. Over the past 30 years, these techniques have gained increasing popularity among both visual and auditory psychophysicists.…

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

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.

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…

How Should Colleges Treat Multiple Admissions Test Scores? ACT Working Paper 2017-4

ERIC Educational Resources Information Center

Mattern, Krista; Radunzel, Justine; Bertling, Maria; Ho, Andrew

2017-01-01

The percentage of students retaking college admissions tests is rising (Harmston & Crouse, 2016). Researchers and college admissions offices currently use a variety of methods for summarizing these multiple scores. Testing companies, interested in validity evidence like correlations with college first-year grade-point averages (FYGPA), often…

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

Fast determination of total ginsenosides content in ginseng powder by near infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Hua-cai; Chen, Xing-dan; Lu, Yong-jun; Cao, Zhi-qiang

2006-01-01

Near infrared (NIR) reflectance spectroscopy was used to develop a fast determination method for total ginsenosides in Ginseng (Panax Ginseng) powder. The spectra were analyzed with multiplicative signal correction (MSC) correlation method. The best correlative spectra region with the total ginsenosides content was 1660 nm~1880 nm and 2230nm~2380 nm. The NIR calibration models of ginsenosides were built with multiple linear regression (MLR), principle component regression (PCR) and partial least squares (PLS) regression respectively. The results showed that the calibration model built with PLS combined with MSC and the optimal spectrum region was the best one. The correlation coefficient and the root mean square error of correction validation (RMSEC) of the best calibration model were 0.98 and 0.15% respectively. The optimal spectrum region for calibration was 1204nm~2014nm. The result suggested that using NIR to rapidly determinate the total ginsenosides content in ginseng powder were feasible.

Improved Characterization of Far-Regional and Near-Teleseismic Phases Observed in Central Asia

DTIC Science & Technology

2010-07-02

Pn/P travel-time residuals as a function of epicentral distance. To generate this figure, we retrieved International Seismic Centre (ISC) bulletins...spectral frequency-wave number methods (e.g., Capon, 1969), multiple signal characteristic ( MUSIC ; Stoica and Nehorai, 1989), cross-correlation (Tibuleac...root and cross-correlation implementations. Methods such as MUSIC do not suffer these limitations and can perform well on far-regional arrivals

Cross-Informant Symptoms from CBCL, TRF, and YSR : Trait and Method Variance in a Normative Sample of Russian Youths

ERIC Educational Resources Information Center

Grigorenko, Elena L.; Geiser, Christian; Slobodskaya, Helena R.; Francis, David J.

2010-01-01

A large community-based sample of Russian youths (n = 841, age M = 13.17 years, SD = 2.51) was assessed with the Child Behavior Checklist (mothers and fathers separately), Teacher's Report Form, and Youth Self-Report. The multiple indicator-version of the correlated trait-correlated method minus one, or CT-C(M-1), model was applied to analyze (a)…

Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Greg C.; Alexander, Brian; Jiang, Steve B.

2007-02-01

For gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. We have previously investigated and demonstrated the feasibility of generating gating signals using the correlation scores between the reference template image and the fluoroscopic images acquired during the treatment. In this paper, we present an in-depth study, aiming at the improvement of robustness of the algorithm and its validation using multiple sets of patient data. Three different template generating and matching methods have been developed and evaluated: (1) single template method, (2) multiple template method, and (3) template clustering method. Using the fluoroscopic data acquired during patient setup before each fraction of treatment, reference templates are built that represent the tumour position and shape in the gating window, which is assumed to be at the end-of-exhale phase. For the single template method, all the setup images within the gating window are averaged to generate a composite template. For the multiple template method, each setup image in the gating window is considered as a reference template and used to generate an ensemble of correlation scores. All the scores are then combined to generate the gating signal. For the template clustering method, clustering (grouping of similar objects together) is performed to reduce the large number of reference templates into a few representative ones. Each of these methods has been evaluated against the reference gating signal as manually determined by a radiation oncologist. Five patient datasets were used for evaluation. In each case, gated treatments were simulated at both 35% and 50% duty cycles. False positive, negative and total error rates were computed. Experiments show that the single template method is sensitive to noise; the multiple template and clustering methods are more robust to noise due to the smoothing effect of aggregation of correlation scores; and the clustering method results in the best performance in terms of computational efficiency and accuracy.

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.

Use of ultrasonic array method for positioning multiple partial discharge sources in transformer oil.

PubMed

Xie, Qing; Tao, Junhan; Wang, Yongqiang; Geng, Jianghai; Cheng, Shuyi; Lü, Fangcheng

2014-08-01

Fast and accurate positioning of partial discharge (PD) sources in transformer oil is very important for the safe, stable operation of power systems because it allows timely elimination of insulation faults. There is usually more than one PD source once an insulation fault occurs in the transformer oil. This study, which has both theoretical and practical significance, proposes a method of identifying multiple PD sources in the transformer oil. The method combines the two-sided correlation transformation algorithm in the broadband signal focusing and the modified Gerschgorin disk estimator. The method of classification of multiple signals is used to determine the directions of arrival of signals from multiple PD sources. The ultrasonic array positioning method is based on the multi-platform direction finding and the global optimization searching. Both the 4 × 4 square planar ultrasonic sensor array and the ultrasonic array detection platform are built to test the method of identifying and positioning multiple PD sources. The obtained results verify the validity and the engineering practicability of this method.

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

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Integrated optics to improve resolution on multiple configuration

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Guo, Chunjie; Zhou, Liwei

2015-04-01

Inspired to in order to reveal the structure to improve imaging resolution, further technical requirement is proposed in some areas of the function and influence on the development of multiple configuration. To breakthrough diffraction limit, smart structures are recommended as the most efficient and economical method, while by used to improve the system performance, especially on signal to noise ratio and resolution. Integrated optics were considered in the selection, with which typical multiple configuration, by use the method of simulation experiment. Methodology can change traditional design concept and to develop the application space. Our calculations using multiple matrix transfer method, also the correlative algorithm and full calculations, show the expected beam shaping through system and, in particular, the experimental results will support our argument, which will be reported in the presentation.

Do sampling methods differ in their utility for ecological monitoring? Comparison of line-point intercept, grid-point intercept, and ocular estimate methods

USDA-ARS?s Scientific Manuscript database

This study compared the utility of three sampling methods for ecological monitoring based on: interchangeability of data (rank correlations), precision (coefficient of variation), cost (minutes/transect), and potential of each method to generate multiple indicators. Species richness and foliar cover...

Pulse transmission receiver with higher-order time derivative pulse correlator

DOEpatents

Dress, Jr., William B.; Smith, Stephen F.

2003-09-16

Systems and methods for pulse-transmission low-power communication modes are disclosed. A pulse transmission receiver includes: a higher-order time derivative pulse correlator; a demodulation decoder coupled to the higher-order time derivative pulse correlator; a clock coupled to the demodulation decoder; and a pseudorandom polynomial generator coupled to both the higher-order time derivative pulse correlator and the clock. The systems and methods significantly reduce lower-frequency emissions from pulse transmission spread-spectrum communication modes, which reduces potentially harmful interference to existing radio frequency services and users and also simultaneously permit transmission of multiple data bits by utilizing specific pulse shapes.

Method and apparatus for the simultaneous display and correlation of independently generated images

DOEpatents

Vaitekunas, Jeffrey J.; Roberts, Ronald A.

1991-01-01

An apparatus and method for location by location correlation of multiple images from Non-Destructive Evaluation (NDE) and other sources. Multiple images of a material specimen are displayed on one or more monitors of an interactive graphics system. Specimen landmarks are located in each image and mapping functions from a reference image to each other image are calcuated using the landmark locations. A location selected by positioning a cursor in the reference image is mapped to the other images and location identifiers are simultaneously displayed in those images. Movement of the cursor in the reference image causes simultaneous movement of the location identifiers in the other images to positions corresponding to the location of the reference image cursor.

The correlation structure of several popular pseudorandom number generators

NASA Technical Reports Server (NTRS)

Neuman, F.; Merrick, R.; Martin, C. F.

1973-01-01

One of the desirable properties of a pseudorandom number generator is that the sequence of numbers it generates should have very low autocorrelation for all shifts except for zero shift and those that are multiples of its cycle length. Due to the simple methods of constructing random numbers, the ideal is often not quite fulfilled. A simple method of examining any random generator for previously unsuspected regularities is discussed. Once they are discovered it is often easy to derive the mathematical relationships, which describe the mathematical relationships, which describe the regular behavior. As examples, it is shown that high correlation exists in mixed and multiplicative congruential random number generators and prime moduli Lehmer generators for shifts a fraction of their cycle lengths.

New decoding methods of interleaved burst error-correcting codes

NASA Astrophysics Data System (ADS)

Nakano, Y.; Kasahara, M.; Namekawa, T.

1983-04-01

A probabilistic method of single burst error correction, using the syndrome correlation of subcodes which constitute the interleaved code, is presented. This method makes it possible to realize a high capability of burst error correction with less decoding delay. By generalizing this method it is possible to obtain probabilistic method of multiple (m-fold) burst error correction. After estimating the burst error positions using syndrome correlation of subcodes which are interleaved m-fold burst error detecting codes, this second method corrects erasure errors in each subcode and m-fold burst errors. The performance of these two methods is analyzed via computer simulation, and their effectiveness is demonstrated.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

Preliminary Evidence that Self-Efficacy Predicts Physical Activity in Multiple Sclerosis

ERIC Educational Resources Information Center

Motl, Robert W.; McAuley, Edward; Doerksen, Shawna; Hu, Liang; Morris, Katherine S.

2009-01-01

Individuals with multiple sclerosis (MS) are less physically active than nondiseased people. One method for increasing physical activity levels involves the identification of factors that correlate with physical activity and that are modifiable by a well designed intervention. This study examined two types of self-efficacy as cross-sectional and…

The strange and charm quark contributions to the anomalous magnetic moment of the muon from lattice QCD

NASA Astrophysics Data System (ADS)

Koponen, Jonna; Chakraborty, Bipasha; Davies, Christine T. H.; Donald, Gordon; Dowdall, Rachel; Gonçalves de Oliveira, Pedro; Lepage, G. Peter; Teubner, Thomas

2016-04-01

We describe a new technique (published in [1]) to determine the contribution to the anomalous magnetic moment of the muon coming from the hadronic vacuum polarisation using lattice QCD. Our method uses Padé approximants to reconstruct the Adler function from its derivatives at q2 = 0. These are obtained simply and accurately from time-moments of the vector current-current correlator at zero spatial momentum. We test the method using strange quark correlators calculated on MILC Collaboration's nf = 2 + 1 + 1 HISQ ensembles at multiple values of the lattice spacing, multiple volumes and multiple light sea quark masses (including physical pion mass configurations). We find the (connected) contribution to the anomalous moment from the strange quark vacuum polarisation to be aμs = 53.41 (59) ×10-10, and the contribution from charm quarks to be aμc = 14.42 (39) ×10-10 - 1% accuracy is achieved for the strange quark contribution. The extension of our method to the light quark contribution and to that from the quark-line disconnected diagram is straightforward.

Multiplicity and transverse momentum dependence of two- and four-particle correlations in pPb and PbPb collisions

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

2013-07-01

Measurements of two- and four-particle angular correlations for charged particles emitted in pPb collisions are presented over a wide range in pseudorapidity and full azimuth. The data, corresponding to an integrated luminosity of approximately 31 inverse nanobarns, were collected during the 2013 LHC pPb run at a nucleon-nucleon center-of-mass energy of 5.02 TeV by the CMS experiment. The results are compared to 2.76 TeV semi-peripheral PbPb collision data, collected during the 2011 PbPb run, covering a similar range of particle multiplicities. The observed correlations are characterized by the near-side (abs(Delta(phi)~0) associated pair yields and the azimuthal anisotropy Fourier harmonics (v[n]).more » The second-order (v[2]) and third-order (v[3]) anisotropy harmonics are extracted using the two-particle azimuthal correlation technique. A four-particle correlation method is also applied to obtain the value of v[2] and further explore the multi-particle nature of the correlations. Both associated pair yields and anisotropy harmonics are studied as a function of particle multiplicity and transverse momentum. The associated pair yields, the four-particle v[2], and the v[3] become apparent at about the same multiplicity. A remarkable similarity in the v[3] signal as a function of multiplicity is observed between the pPb and PbPb systems. Predictions based on the color glass condensate and hydrodynamic models are compared to the experimental results.« less

Noise reduction methods for nucleic acid and macromolecule sequencing

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

Schuller, Ivan K.; Di Ventra, Massimiliano; Balatsky, Alexander

Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.

Relations between Brain Structure and Attentional Function in Spina Bifida: Utilization of Robust Statistical Approaches

PubMed Central

Kulesz, Paulina A.; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M.; Francis, David J.

2015-01-01

Objective Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Method Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product moment correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator Results All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Conclusions Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PMID:25495830

"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.

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Aggregation of carbon dioxide sequestration storage assessment units

USGS Publications Warehouse

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

2013-01-01

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

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.

Diffusion-weighted magnetic resonance imaging in the characterization of testicular germ cell neoplasms: Effect of ROI methods on apparent diffusion coefficient values and interobserver variability.

PubMed

Tsili, Athina C; Ntorkou, Alexandra; Astrakas, Loukas; Xydis, Vasilis; Tsampalas, Stavros; Sofikitis, Nikolaos; Argyropoulou, Maria I

2017-04-01

To evaluate the difference in apparent diffusion coefficient (ADC) measurements at diffusion-weighted (DW) magnetic resonance imaging of differently shaped regions-of-interest (ROIs) in testicular germ cell neoplasms (TGCNS), the diagnostic ability of differently shaped ROIs in differentiating seminomas from nonseminomatous germ cell neoplasms (NSGCNs) and the interobserver variability. Thirty-three TGCNs were retrospectively evaluated. Patients underwent MR examinations, including DWI on a 1.5-T MR system. Two observers measured mean tumor ADCs using four distinct ROI methods: round, square, freehand and multiple small, round ROIs. The interclass correlation coefficient was analyzed to assess interobserver variability. Statistical analysis was used to compare mean ADC measurements among observers, methods and histologic types. All ROI methods showed excellent interobserver agreement, with excellent correlation (P<0.001). Multiple, small ROIs provided the lower mean ADC in TGCNs. Seminomas had lower mean ADC compared to NSGCNs for each ROI method (P<0.001). Round ROI proved the most accurate method in characterizing TGCNS. Interobserver variability in ADC measurement is excellent, irrespective of the ROI shape. Multiple, small round ROIs and round ROI proved the more accurate methods for ADC measurement in the characterization of TGCNs and in the differentiation between seminomas and NSGCNs, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Relationships between World Health Organization "International Classification of Functioning, Disability and Health" Constructs and Participation in Adults with Severe Mental Illness

ERIC Educational Resources Information Center

Sánchez, Jennifer; Rosenthal, David A.; Chan, Fong; Brooks, Jessica; Bezyak, Jill L.

2016-01-01

Purpose: To examine the World Health Organization "International Classification of Functioning, Disability and Health" (ICF) constructs as correlates of community participation of people with severe mental illnesses (SMI). Methods: Quantitative descriptive research design using multiple regression and correlational techniques was used to…

Local Field Response Method Phenomenologically Introducing Spin Correlations

NASA Astrophysics Data System (ADS)

Tomaru, Tatsuya

2018-03-01

The local field response (LFR) method is a way of searching for the ground state in a similar manner to quantum annealing. However, the LFR method operates on a classical machine, and quantum effects are introduced through a priori information and through phenomenological means reflecting the states during the computations. The LFR method has been treated with a one-body approximation, and therefore, the effect of entanglement has not been sufficiently taken into account. In this report, spin correlations are phenomenologically introduced as one of the effects of entanglement, by which multiple tunneling at anticrossing points is taken into account. As a result, the accuracy of solutions for a 128-bit system increases by 31% compared with that without spin correlations.

Exploring effective multiplicity in multichannel functional near-infrared spectroscopy using eigenvalues of correlation matrices

PubMed Central

Uga, Minako; Dan, Ippeita; Dan, Haruka; Kyutoku, Yasushi; Taguchi, Y-h; Watanabe, Eiju

2015-01-01

Abstract. Recent advances in multichannel functional near-infrared spectroscopy (fNIRS) allow wide coverage of cortical areas while entailing the necessity to control family-wise errors (FWEs) due to increased multiplicity. Conventionally, the Bonferroni method has been used to control FWE. While Type I errors (false positives) can be strictly controlled, the application of a large number of channel settings may inflate the chance of Type II errors (false negatives). The Bonferroni-based methods are especially stringent in controlling Type I errors of the most activated channel with the smallest p value. To maintain a balance between Types I and II errors, effective multiplicity (Meff) derived from the eigenvalues of correlation matrices is a method that has been introduced in genetic studies. Thus, we explored its feasibility in multichannel fNIRS studies. Applying the Meff method to three kinds of experimental data with different activation profiles, we performed resampling simulations and found that Meff was controlled at 10 to 15 in a 44-channel setting. Consequently, the number of significantly activated channels remained almost constant regardless of the number of measured channels. We demonstrated that the Meff approach can be an effective alternative to Bonferroni-based methods for multichannel fNIRS studies. PMID:26157982

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

Validity and reliability of the multidimensional assessment of fatigue scale in Iranian patients with relapsing-remitting subtype of multiple sclerosis.

PubMed

Behrangrad, Shabnam; Kordi Yoosefinejad, Amin

2018-03-01

The purpose of this study is to investigate the validity and reliability of the Persian version of the Multidimensional Assessment of Fatigue Scale (MAFS) in an Iranian population with multiple sclerosis. A self-reported survey on fatigue including the MAFS, Fatigue Impact Scale and demographic measures was completed by 130 patients with multiple sclerosis and 60 healthy persons sampled with a convenience method. Test-retest reliability and validity were evaluated 3 days apart. Construct validity of the MAFS was assessed with the Fatigue Impact Scale. The MAFS had high internal consistency (Cronbach's alpha >0.9) and 3-d test-retest reliability (intraclass correlation coefficient = 0.99). Correlation between the Fatigue Impact Scale and MAFS was high (r = 0.99). Correlation between MAFS scores and the Expanded Disability Status Scale was also strong (r = 0.85). Questionnaire items showed acceptable item-scale correlation (0.968-0.993). The Persian version of the MAFS appears to be a valid and reliable questionnaire. It is an appropriate short multidimensional instrument to assess fatigue in patients with multiple sclerosis in clinical practice and research. Implications for Rehabilitation The Persian version of Multidimensional Assessment of Fatigue is a valid and reliable instrument for the assessment and monitoring the fatigue in Persian-language patients with multiple sclerosis. It is very easy to administer and a time efficient scale in comparison to other instruments evaluating fatigue in patients with multiple sclerosis.

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

PubMed

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

2017-07-01

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

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 &…

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…

Potential use of multiple surveillance data in the forecast of hospital admissions

PubMed Central

Lau, Eric H.Y.; Ip, Dennis K.M.; Cowling, Benjamin J.

2013-01-01

Objective This paper describes the potential use of multiple influenza surveillance data to forecast hospital admissions for respiratory diseases. Introduction A sudden surge in hospital admissions in public hospital during influenza peak season has been a challenge to healthcare and manpower planning. In Hong Kong, the timing of influenza peak seasons are variable and early short-term indication of possible surge may facilitate preparedness which could be translated into strategies such as early discharge or reallocation of extra hospital beds. In this study we explore the potential use of multiple routinely collected syndromic data in the forecast of hospital admissions. Methods A multivariate dynamic linear time series model was fitted to multiple syndromic data including influenza-like illness (ILI) rates among networks of public and private general practitioners (GP), and school absenteeism rates, plus drop-in fever count data from designated flu clinics (DFC) that were created during the pandemic. The latent process derived from the model has been used as a measure of the influenza activity [1]. We compare the cross-correlations between estimated influenza level based on multiple surveillance data and GP ILI data, versus accident and emergency hospital admissions with principal diagnoses of respiratory diseases and pneumonia & influenza (P&I). Results The estimated influenza activity has higher cross-correlation with respiratory and P&I admissions (ρ=0.66 and 0.73 respectively) compared to that of GP ILI rates (Table 1). Cross correlations drop distinctly after lag 2 for both estimated influenza activity and GP ILI rates. Conclusions The use of a multivariate method to integrate information from multiple sources of influenza surveillance data may have the potential to improve forecasting of admission surge of respiratory diseases.

Multiple description distributed image coding with side information for mobile wireless transmission

NASA Astrophysics Data System (ADS)

Wu, Min; Song, Daewon; Chen, Chang Wen

2005-03-01

Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions, and then transmitting them over different channels in packet network or error-prone wireless environment to achieve graceful degradation if parts of descriptions are lost at the receiver. In this paper, we proposed a multiple description distributed wavelet zero tree image coding system for mobile wireless transmission. We provide two innovations to achieve an excellent error resilient capability. First, when MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. We consider using such a correlation as well as potentially error corrupted description as side information in the decoding to formulate the MDC decoding as a Wyner Ziv decoding problem. If only part of descriptions is lost, however, their correlation information is still available, the proposed Wyner Ziv decoder can recover the description by using the correlation information and the error corrupted description as side information. Secondly, in each description, single bitstream wavelet zero tree coding is very vulnerable to the channel errors. The first bit error may cause the decoder to discard all subsequent bits whether or not the subsequent bits are correctly received. Therefore, we integrate the multiple description scalar quantization (MDSQ) with the multiple wavelet tree image coding method to reduce error propagation. We first group wavelet coefficients into multiple trees according to parent-child relationship and then code them separately by SPIHT algorithm to form multiple bitstreams. Such decomposition is able to reduce error propagation and therefore improve the error correcting capability of Wyner Ziv decoder. Experimental results show that the proposed scheme not only exhibits an excellent error resilient performance but also demonstrates graceful degradation over the packet loss rate.

Multiple exposure photographic (MEP) technique: an objective assessment of sperm motility in infertility management.

PubMed

Adetoro, O O

1988-06-01

Multiple exposure photography (MEP), an objective technique, was used in determining the percentage of motile sperms in the semen samples from 41 males being investigated for infertility. This technique was compared with the conventional subjective ordinary microscopy method of spermatozoal motility assessment. A satisfactory correlation was observed in percentage sperm motility assessment using the two methods but the MEP estimation was more consistent and reliable. The value of this technique of sperm motility study in the developing world is discussed.

Assessment of curing behavior of light-activated dental composites using intensity correlation based multiple reference optical coherence tomography.

PubMed

Dsouza, Roshan; Subhash, Hrebesh; Neuhaus, Kai; Kantamneni, Ramakrishna; McNamara, Paul M; Hogan, Josh; Wilson, Carol; Leahy, Martin

2016-01-01

Monitoring the curing kinetics of light-activated resin is a key area of research. These resins are used in restorative applications and particularly in dental applications. They can undergo volumetric shrinkage due to poor control of the depth dependent curing process, modulated by the intensity and duration of the curing light source. This often results in the formation of marginal gaps, causing pain and damage to the restoration site. In this study, we demonstrate the capabilities of a correlation method applied using a multiple references optical coherence tomography (MR-OCT) architecture to monitor the curing of the resin. A MR-OCT system is used in this study to monitor the curing of the resin. The system operates at the center wavelength of 1310 nm with an A-scan rate of 1200 A-scans per second. The axial and lateral resolution of the system is ∼13 μm and ∼27 μm. The method to determine the intensity correlation between adjacent B-frames is based on the Pearson correlation coefficient for a region of interest. Calculating the correlation coefficient for multiple B-frames related to the first B-frame at regular spaced time points, shows for a noncured resin a reduction of the correlation coefficient over time due to Brownian motion. The time constant of the reduction of the correlation value is a measure for the progress of the polymerization during LED light irradiation of the resin. The proposed approach is potentially a low-cost, powerful and unique optical imaging modality for measuring the curing behavior of dental resin and other resins, coatings, and adhesives in medical and industrial applications. To demonstrate the proposed method to monitor the curing process, a light-activated resin composite from GRADIA DIRECT ANTERIOR (GC Corporation, Japan) is studied. The curing time of resin was measured and monitored as a function of depth. The correlation coefficient method is highly sensitive to Brownian motion. The process of curing results in a change in intensity as measured by the MR-OCT signal and hence can be monitored using this method. These results show that MR-OCT has the potential to measure the curing time and monitor the curing process as a function of depth. Moreover, MR-OCT as a product has potential to be compact, low-cost and to fit into a smartphone. Using such a device for monitoring the curing of the resin will be suitable for dentists in stationary and mobile clinical settings. © 2015 Wiley Periodicals, Inc.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

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.

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

The Nature, Prevalence and Correlates of Generativity among Men in Middle Career

ERIC Educational Resources Information Center

Clark, Mike; Arnold, John

2008-01-01

Multiple methods were used to explore the character, contexts, and correlates of generativity among 41 men aged 45-55. Generativity in the role of worker was unrelated to generativity in men's roles as father, citizen and "leisurite". Individuals who were generative in their work reported greater job satisfaction and subjective career success.…

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.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

Accounting for multiple climate components when estimating climate change exposure and velocity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

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.

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

PubMed Central

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-01-01

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

PubMed

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

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.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

A Monte Carlo Evaluation of Estimated Parameters of Five Shrinkage Estimate Formuli.

ERIC Educational Resources Information Center

Newman, Isadore; And Others

A Monte Carlo study was conducted to estimate the efficiency of and the relationship between five equations and the use of cross validation as methods for estimating shrinkage in multiple correlations. Two of the methods were intended to estimate shrinkage to population values and the other methods were intended to estimate shrinkage from sample…

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program

PubMed Central

Tejada, Frederick R.; Lang, Lynn A.; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-01-01

Objective. To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Methods. Statistical analyses included two sample t tests, multiple regression and Pearson’s correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. Results. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Conclusion. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion. PMID:26430273

Assessing assay agreement estimation for multiple left-censored data: a multiple imputation approach.

PubMed

Lapidus, Nathanael; Chevret, Sylvie; Resche-Rigon, Matthieu

2014-12-30

Agreement between two assays is usually based on the concordance correlation coefficient (CCC), estimated from the means, standard deviations, and correlation coefficient of these assays. However, such data will often suffer from left-censoring because of lower limits of detection of these assays. To handle such data, we propose to extend a multiple imputation approach by chained equations (MICE) developed in a close setting of one left-censored assay. The performance of this two-step approach is compared with that of a previously published maximum likelihood estimation through a simulation study. Results show close estimates of the CCC by both methods, although the coverage is improved by our MICE proposal. An application to cytomegalovirus quantification data is provided. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates

PubMed Central

2012-01-01

Background Presented is the method “Detection and Outline Error Estimates” (DOEE) for assessing rater agreement in the delineation of multiple sclerosis (MS) lesions. The DOEE method divides operator or rater assessment into two parts: 1) Detection Error (DE) -- rater agreement in detecting the same regions to mark, and 2) Outline Error (OE) -- agreement of the raters in outlining of the same lesion. Methods DE, OE and Similarity Index (SI) values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR) images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA) of the raters' Region of Interests (ROIs). Results When correlated with MTA, neither DE (ρ = .056, p=.83) nor the ratio of OE to MTA (ρ = .23, p=.37), referred to as Outline Error Rate (OER), exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p < .001). Furthermore, DE and OER values can be used to model the variation in SI with MTA. Conclusions The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement. PMID:22812697

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

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.

Relations between volumetric measures of brain structure and attentional function in spina bifida: utilization of robust statistical approaches.

PubMed

Kulesz, Paulina A; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M; Francis, David J

2015-03-01

Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product-moment correlation was compared with 4 robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator. All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

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

Multiple-3D-object secure information system based on phase shifting method and single interference.

PubMed

Li, Wei-Na; Shi, Chen-Xiao; Piao, Mei-Lan; Kim, Nam

2016-05-20

We propose a multiple-3D-object secure information system for encrypting multiple three-dimensional (3D) objects based on the three-step phase shifting method. During the decryption procedure, five phase functions (PFs) are decreased to three PFs, in comparison with our previous method, which implies that one cross beam splitter is utilized to implement the single decryption interference. Moreover, the advantages of the proposed scheme also include: each 3D object can be decrypted discretionarily without decrypting a series of other objects earlier; the quality of the decrypted slice image of each object is high according to the correlation coefficient values, none of which is lower than 0.95; no iterative algorithm is involved. The feasibility of the proposed scheme is demonstrated by computer simulation results.

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

PubMed

Lang, Dean H; Sharkey, Neil A; Lionikas, Arimantas; Mack, Holly A; Larsson, Lars; Vogler, George P; Vandenbergh, David J; Blizard, David A; Stout, Joseph T; Stitt, Joseph P; McClearn, Gerald E

2005-05-01

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health.

A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs.

PubMed

Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

2015-12-26

This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

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

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.

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'.

Women's Voices on Recovery: A Multi-Method Study of the Complexity of Recovery from Child Sexual Abuse

ERIC Educational Resources Information Center

Banyard, Victoria L.; Williams, Linda M.

2007-01-01

Objective: The current study was exploratory and used multiple methods to examine patterns of stability and change in resilient functioning across 7 years of early adulthood. Second, qualitative data were used to examine in greater detail survivors' own narratives about correlates of healing. Method: This study was longitudinal and used both…

A method of solving tilt illumination for multiple distance phase retrieval

NASA Astrophysics Data System (ADS)

Guo, Cheng; Li, Qiang; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-07-01

Multiple distance phase retrieval is a technique of using a series of intensity patterns to reconstruct a complex-valued image of object. However, tilt illumination originating from the off-axis displacement of incident light significantly impairs its imaging quality. To eliminate this affection, we use cross-correlation calibration to estimate oblique angle of incident light and a Fourier-based strategy to correct tilted illumination effect. Compared to other methods, binary and biological object are both stably reconstructed in simulation and experiment. This work provides a simple but beneficial method to solve the problem of tilt illumination for lens-free multi-distance system.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

PubMed

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

PubMed Central

Chichilnisky, E. J.; Simoncelli, Eero P.

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583

Ability, Demography, Learning Style, and Personality Trait Correlates of Student Preference for Assessment Method

ERIC Educational Resources Information Center

Furnham, Adrian; Christopher, Andrew; Garwood, Jeanette; Martin, Neil G.

2008-01-01

More than 400 students from four universities in America and Britain completed measures of learning style preference, general knowledge (as a proxy for intelligence), and preference for examination method. Learning style was consistently associated with preferences: surface learners preferred multiple choice and group work options, and viewed…

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

Semi-automated surface mapping via unsupervised classification

NASA Astrophysics Data System (ADS)

D'Amore, M.; Le Scaon, R.; Helbert, J.; Maturilli, A.

2017-09-01

Due to the increasing volume of the returned data from space mission, the human search for correlation and identification of interesting features becomes more and more unfeasible. Statistical extraction of features via machine learning methods will increase the scientific output of remote sensing missions and aid the discovery of yet unknown feature hidden in dataset. Those methods exploit algorithm trained on features from multiple instrument, returning classification maps that explore intra-dataset correlation, allowing for the discovery of unknown features. We present two applications, one for Mercury and one for Vesta.

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 use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

A double-correlation tremor-location method

NASA Astrophysics Data System (ADS)

Li, Ka Lok; Sgattoni, Giulia; Sadeghisorkhani, Hamzeh; Roberts, Roland; Gudmundsson, Olafur

2017-02-01

A double-correlation method is introduced to locate tremor sources based on stacks of complex, doubly-correlated tremor records of multiple triplets of seismographs back projected to hypothetical source locations in a geographic grid. Peaks in the resulting stack of moduli are inferred source locations. The stack of the moduli is a robust measure of energy radiated from a point source or point sources even when the velocity information is imprecise. Application to real data shows how double correlation focuses the source mapping compared to the common single correlation approach. Synthetic tests demonstrate the robustness of the method and its resolution limitations which are controlled by the station geometry, the finite frequency of the signal, the quality of the used velocity information and noise level. Both random noise and signal or noise correlated at time shifts that are inconsistent with the assumed velocity structure can be effectively suppressed. Assuming a surface wave velocity, we can constrain the source location even if the surface wave component does not dominate. The method can also in principle be used with body waves in 3-D, although this requires more data and seismographs placed near the source for depth resolution.

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.

Effects of cross correlation on the relaxation time of a bistable system driven by cross-correlated noise

NASA Astrophysics Data System (ADS)

Mei, Dongcheng; Xie, Chongwei; Zhang, Li

2003-11-01

We study the effects of correlations between additive and multiplicative noise on relaxation time in a bistable system driven by cross-correlated noise. Using the projection-operator method, we derived an analytic expression for the relaxation time Tc of the system, which is the function of additive (α) and multiplicative (D) noise intensities, correlation intensity λ of noise, and correlation time τ of noise. After introducing a noise intensity ratio and a dimensionless parameter R=D/α, and then performing numerical computations, we find the following: (i) For the case of R<1, the relaxation time Tc increases as R increases. (ii) For the cases of R⩾1, there is a one-peak structure on the Tc-R plot and the effects of cross-correlated noise on the relaxation time are very notable. (iii) For the case of R<1, Tc almost does not change with both λ and τ, and for the cases of R⩾1, Tc decreases as λ increases, however Tc increases as τ increases. λ and τ play opposite roles in Tc, i.e., λ enhances the fluctuation decay of dynamical variable and τ slows down the fluctuation decay of dynamical variable.

Alternative methods for CYP2D6 phenotyping: comparison of dextromethorphan metabolic ratios from AUC, single point plasma, and urine.

PubMed

Chen, Rui; Wang, Haotian; Shi, Jun; Hu, Pei

2016-05-01

CYP2D6 is a high polymorphic enzyme. Determining its phenotype before CYP2D6 substrate treatment can avoid dose-dependent adverse events or therapeutic failures. Alternative phenotyping methods of CYP2D6 were compared to aluate the appropriate and precise time points for phenotyping after single-dose and ultiple-dose of 30-mg controlled-release (CR) dextromethorphan (DM) and to explore the antimodes for potential sampling methods. This was an open-label, single and multiple-dose study. 21 subjects were assigned to receive a single dose of CR DM 30 mg orally, followed by a 3-day washout period prior to oral administration of CR DM 30 mg every 12 hours for 6 days. Metabolic ratios (MRs) from AUC∞ after single dosing and from AUC0-12h at steady state were taken as the gold standard. The correlations of metabolic ratios of DM to dextrorphan (MRDM/DX) values based on different phenotyping methods were assessed. Linear regression formulas were derived to calculate the antimodes for potential sample methods. In the single-dose part of the study statistically significant correlations were found between MRDM/DX from AUC∞ and from serial plasma points from 1 to 30 hours or from urine (all p-values < 0.001). In the multiple-dose part, statistically significant correlations were found between MRDM/DX from AUC0-12h on day 6 and MRDM/DX from serial plasma points from 0 to 36 hours after the last dosing (all p-values < 0.001). Based on reported urinary antimode and linear regression analysis, the antimodes of AUC and plasma points were derived to profile the trend of antimodes as the drug concentrations changed. MRDM/DX from plasma points had good correlations with MRDM/DX from AUC. Plasma points from 1 to 30 hours after single dose of 30-mg CR DM and any plasma point at steady state after multiple doses of CR DM could potentially be used for phenotyping of CYP2D6.

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.

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

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies

PubMed Central

Zhang, Yu; Liu, Jun S.

2011-01-01

Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online. PMID:22140288

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.

A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs

PubMed Central

Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

2015-01-01

This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB. PMID:26712765

Predicting MHC-II binding affinity using multiple instance regression

PubMed Central

EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2011-01-01

Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923

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.

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…

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.

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar

PubMed Central

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-01-01

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar.

PubMed

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-12-14

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method

PubMed Central

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-01-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity. PMID:28468308

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method.

PubMed

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-05-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity.

Geophysical methods in Geology. Second edition

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

Sharma, P.V.

This book presents an introduction to the methods of geophysics and their application to geological problems. The text emphasizes the broader aspects of geophysics, including the way in which geophysical methods help solve structural, correlational, and geochromological problems. Stress is laid on the principles and applications of methods rather than on instrumental techniques. This edition includes coverage of recent developments in geophysics and geology. New topics are introduced, including paleomagnetic methods, electromagnetic methods, microplate tectronics, and the use of multiple geophysical techniques.

Covariance Matrix Estimation for Massive MIMO

NASA Astrophysics Data System (ADS)

Upadhya, Karthik; Vorobyov, Sergiy A.

2018-04-01

We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.

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.

Differential correlation for sequencing data.

PubMed

Siska, Charlotte; Kechris, Katerina

2017-01-19

Several methods have been developed to identify differential correlation (DC) between pairs of molecular features from -omics studies. Most DC methods have only been tested with microarrays and other platforms producing continuous and Gaussian-like data. Sequencing data is in the form of counts, often modeled with a negative binomial distribution making it difficult to apply standard correlation metrics. We have developed an R package for identifying DC called Discordant which uses mixture models for correlations between features and the Expectation Maximization (EM) algorithm for fitting parameters of the mixture model. Several correlation metrics for sequencing data are provided and tested using simulations. Other extensions in the Discordant package include additional modeling for different types of differential correlation, and faster implementation, using a subsampling routine to reduce run-time and address the assumption of independence between molecular feature pairs. With simulations and breast cancer miRNA-Seq and RNA-Seq data, we find that Spearman's correlation has the best performance among the tested correlation methods for identifying differential correlation. Application of Spearman's correlation in the Discordant method demonstrated the most power in ROC curves and sensitivity/specificity plots, and improved ability to identify experimentally validated breast cancer miRNA. We also considered including additional types of differential correlation, which showed a slight reduction in power due to the additional parameters that need to be estimated, but more versatility in applications. Finally, subsampling within the EM algorithm considerably decreased run-time with negligible effect on performance. A new method and R package called Discordant is presented for identifying differential correlation with sequencing data. Based on comparisons with different correlation metrics, this study suggests Spearman's correlation is appropriate for sequencing data, but other correlation metrics are available to the user depending on the application and data type. The Discordant method can also be extended to investigate additional DC types and subsampling with the EM algorithm is now available for reduced run-time. These extensions to the R package make Discordant more robust and versatile for multiple -omics studies.

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.

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.

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

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

PubMed

Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang

2018-03-27

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

An Intuitionistic Multiplicative ORESTE Method for Patients’ Prioritization of Hospitalization

PubMed Central

Zhang, Cheng; Wu, Xingli; Wu, Di; Luo, Li; Herrera-Viedma, Enrique

2018-01-01

The tension brought about by sickbeds is a common and intractable issue in public hospitals in China due to the large population. Assigning the order of hospitalization of patients is difficult because of complex patient information such as disease type, emergency degree, and severity. It is critical to rank the patients taking full account of various factors. However, most of the evaluation criteria for hospitalization are qualitative, and the classical ranking method cannot derive the detailed relations between patients based on these criteria. Motivated by this, a comprehensive multiple criteria decision making method named the intuitionistic multiplicative ORESTE (organísation, rangement et Synthèse dedonnées relarionnelles, in French) was proposed to handle the problem. The subjective and objective weights of criteria were considered in the proposed method. To do so, first, considering the vagueness of human perceptions towards the alternatives, an intuitionistic multiplicative preference relation model is applied to represent the experts’ preferences over the pairwise alternatives with respect to the predetermined criteria. Then, a correlation coefficient-based weight determining method is developed to derive the objective weights of criteria. This method can overcome the biased results caused by highly-related criteria. Afterwards, we improved the general ranking method, ORESTE, by introducing a new score function which considers both the subjective and objective weights of criteria. An intuitionistic multiplicative ORESTE method was then developed and further highlighted by a case study concerning the patients’ prioritization. PMID:29673212

[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.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

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

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

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.

Determination of dipole coupling constants using heteronuclear multiple quantum NMR

NASA Astrophysics Data System (ADS)

Weitekamp, D. P.; Garbow, J. R.; Pines, A.

1982-09-01

The problem of extracting dipole couplings from a system of N spins I = 1/2 and one spin S by NMR techniques is analyzed. The resolution attainable using a variety of single quantum methods is reviewed. The theory of heteronuclear multiple quantum (HMQ) NMR is developed, with particular emphasis being placed on the superior resolution available in HMQ spectra. Several novel pulse sequences are introduced, including a two-step method for the excitation of HMQ coherence. Experiments on partially oriented [1-13C] benzene demonstrate the excitation of the necessary HMQ coherence and illustrate the calculation of relative line intensities. Spectra of high order HMQ coherence under several different effective Hamiltonians achievable by multiple pulse sequences are discussed. A new effective Hamiltonian, scalar heteronuclear recoupled interactions by multiple pulse (SHRIMP), achieved by the simultaneous irradiation of both spin species with the same multiple pulse sequence, is introduced. Experiments are described which allow heteronuclear couplings to be correlated with an S-spin spreading parameter in spectra free of inhomogeneous broadening.

Monitoring multiple components in vinegar fermentation using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Soykut, Esra Acar; Boyaci, Ismail Hakki; Topcu, Ali

2013-12-15

In this study, the utility of Raman spectroscopy (RS) with chemometric methods for quantification of multiple components in the fermentation process was investigated. Vinegar, the product of a two stage fermentation, was used as a model and glucose and fructose consumption, ethanol production and consumption and acetic acid production were followed using RS and the partial least squares (PLS) method. Calibration of the PLS method was performed using model solutions. The prediction capability of the method was then investigated with both model and real samples. HPLC was used as a reference method. The results from comparing RS-PLS and HPLC with each other showed good correlations were obtained between predicted and actual sample values for glucose (R(2)=0.973), fructose (R(2)=0.988), ethanol (R(2)=0.996) and acetic acid (R(2)=0.983). In conclusion, a combination of RS with chemometric methods can be applied to monitor multiple components of the fermentation process from start to finish with a single measurement in a short time. Copyright © 2013 Elsevier Ltd. All rights reserved.

A KST framework for correlation network construction from time series signals

NASA Astrophysics Data System (ADS)

Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

2018-04-01

A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

Correlation complementarity yields bell monogamy relations.

PubMed

Kurzyński, P; Paterek, T; Ramanathan, R; Laskowski, W; Kaszlikowski, D

2011-05-06

We present a method to derive Bell monogamy relations by connecting the complementarity principle with quantum nonlocality. The resulting monogamy relations are stronger than those obtained from the no-signaling principle alone. In many cases, they yield tight quantum bounds on the amount of violation of single and multiple qubit correlation Bell inequalities. In contrast with the two-qubit case, a rich structure of possible violation patterns is shown to exist in the multipartite scenario.

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.

A real-time method for autonomous passive acoustic detection-classification of humpback whales.

PubMed

Abbot, Ted A; Premus, Vincent E; Abbot, Philip A

2010-05-01

This paper describes a method for real-time, autonomous, joint detection-classification of humpback whale vocalizations. The approach adapts the spectrogram correlation method used by Mellinger and Clark [J. Acoust. Soc. Am. 107, 3518-3529 (2000)] for bowhead whale endnote detection to the humpback whale problem. The objective is the implementation of a system to determine the presence or absence of humpback whales with passive acoustic methods and to perform this classification with low false alarm rate in real time. Multiple correlation kernels are used due to the diversity of humpback song. The approach also takes advantage of the fact that humpbacks tend to vocalize repeatedly for extended periods of time, and identification is declared only when multiple song units are detected within a fixed time interval. Humpback whale vocalizations from Alaska, Hawaii, and Stellwagen Bank were used to train the algorithm. It was then tested on independent data obtained off Kaena Point, Hawaii in February and March of 2009. Results show that the algorithm successfully classified humpback whales autonomously in real time, with a measured probability of correct classification in excess of 74% and a measured probability of false alarm below 1%.

Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies

PubMed Central

Geiser, Christian; Burns, G. Leonard; Servera, Mateu

2014-01-01

Models of confirmatory factor analysis (CFA) are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM) investigations. We show that interesting incremental information about method effects can be gained from including mean structures and tests of MI across methods in MTMM models. We present a modeling framework for testing MI in the first step of a CFA-MTMM analysis. We also discuss the relevance of MI in the context of four more complex CFA-MTMM models with method factors. We focus on three recently developed multiple-indicator CFA-MTMM models for structurally different methods [the correlated traits-correlated (methods – 1), latent difference, and latent means models; Geiser et al., 2014a; Pohl and Steyer, 2010; Pohl et al., 2008] and one model for interchangeable methods (Eid et al., 2008). We demonstrate that some of these models require or imply MI by definition for a proper interpretation of trait or method factors, whereas others do not, and explain why MI may or may not be required in each model. We show that in the model for interchangeable methods, testing for MI is critical for determining whether methods can truly be seen as interchangeable. We illustrate the theoretical issues in an empirical application to an MTMM study of attention deficit and hyperactivity disorder (ADHD) with mother, father, and teacher ratings as methods. PMID:25400603

Correlated components of ongoing EEG point to emotionally laden attention - a possible marker of engagement?

PubMed

Dmochowski, Jacek P; Sajda, Paul; Dias, Joao; Parra, Lucas C

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.

Correlated Components of Ongoing EEG Point to Emotionally Laden Attention – A Possible Marker of Engagement?

PubMed Central

Dmochowski, Jacek P.; Sajda, Paul; Dias, Joao; Parra, Lucas C.

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity. PMID:22623915

The utility of gravity and water-level monitoring at alluvial aquifer wells in southern Arizona

USGS Publications Warehouse

Pool, D.R.

2008-01-01

Coincident monitoring of gravity and water levels at 39 wells in southern Arizona indicate that water-level change might not be a reliable indicator of aquifer-storage change for alluvial aquifer systems. One reason is that water levels in wells that are screened across single or multiple aquifers might not represent the hydraulic head and storage change in a local unconfined aquifer. Gravity estimates of aquifer-storage change can be approximated as a one-dimensional feature except near some withdrawal wells and recharge sources. The aquifer storage coefficient is estimated by the linear regression slope of storage change (estimated using gravity methods) and water-level change. Nonaquifer storage change that does not percolate to the aquifer can be significant, greater than 3 ??Gal, when water is held in the root zone during brief periods following extreme rates of precipitation. Monitor-ing of storage change using gravity methods at wells also can improve understanding of local hydrogeologic conditions. In the study area, confined aquifer conditions are likely at three wells where large water-level variations were accompanied by little gravity change. Unconfined conditions were indicated at 15 wells where significant water-level and gravity change were positively linearly correlated. Good positive linear correlations resulted in extremely large specific-yield values, greater than 0.35, at seven wells where it is likely that significant ephemeral streamflow infiltration resulted in unsaturated storage change. Poor or negative linear correlations indicate the occurrence of confined, multiple, or perched aquifers. Monitoring of a multiple compressible aquifer system at one well resulted in negative correlation of rising water levels and subsidence-corrected gravity change, which suggests that water-level trends at the well are not a good indicatior of overall storage change. ?? 2008 Society of Exploration Geophysicists. All rights reserved.

Silanols, a New Class of Antimicrobial Agent

DTIC Science & Technology

2006-04-01

carbinols against the four bacteria was log (1/MLC) = 0.670 log P + 0.0035 ∆ν -1.836, n = 282, r = 0.96, s = 0.22. This equation and a significantly...activity relationship of antimicrobial agents by means of equations [8] based on a method proposed by Hansch and Fujita in 1964 [1]. This multiple...correlation equations between their antimicrobial activities and structural properties, log P and H-bond acidity, were created by a multiple regression

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

Disentangling the Correlates of Drug Use in a Clinic and Community Sample: A Regression Analysis of the Associations between Drug Use, Years-of-School, Impulsivity, IQ, Working Memory, and Psychiatric Symptoms.

PubMed

Heyman, Gene M; Dunn, Brian J; Mignone, Jason

2014-01-01

Years-of-school is negatively correlated with illicit drug use. However, educational attainment is positively correlated with IQ and negatively correlated with impulsivity, two traits that are also correlated with drug use. Thus, the negative correlation between education and drug use may reflect the correlates of schooling, not schooling itself. To help disentangle these relations we obtained measures of working memory, simple memory, IQ, disposition (impulsivity and psychiatric status), years-of-school and frequency of illicit and licit drug use in methadone clinic and community drug users. We found strong zero-order correlations between all measures, including IQ, impulsivity, years-of-school, psychiatric symptoms, and drug use. However, multiple regression analyses revealed a different picture. The significant predictors of illicit drug use were gender, involvement in a methadone clinic, and years-of-school. That is, psychiatric symptoms, impulsivity, cognition, and IQ no longer predicted illicit drug use in the multiple regression analyses. Moreover, high risk subjects (low IQ and/or high impulsivity) who spent 14 or more years in school used stimulants and opiates less than did low risk subjects who had spent <14 years in school. Smoking and drinking had a different correlational structure. IQ and years-of-school predicted whether someone ever became a smoker, whereas impulsivity predicted the frequency of drinking bouts, but years-of-school did not. Many subjects reported no use of one or more drugs, resulting in a large number of "zeroes" in the data sets. Cragg's Double-Hurdle regression method proved the best approach for dealing with this problem. To our knowledge, this is the first report to show that years-of-school predicts lower levels of illicit drug use after controlling for IQ and impulsivity. This paper also highlights the advantages of Double-Hurdle regression methods for analyzing the correlates of drug use in community samples.

Modal survey of the space shuttle solid rocket motor using multiple input methods

NASA Technical Reports Server (NTRS)

Brillhart, Ralph; Hunt, David L.; Jensen, Brent M.; Mason, Donald R.

1987-01-01

The ability to accurately characterize propellant in a finite element model is a concern of engineers tasked with studying the dynamic response of the Space Shuttle Solid Rocket Motor (SRM). THe uncertainties arising from propellant characterization through specimem testing led to the decision to perform a model survey and model correlation of a single segment of the Shuttle SRM. Multiple input methods were used to excite and define case/propellant modes of both an inert segment and, later, a live propellant segment. These tests were successful at defining highly damped, flexible modes, several pairs of which occured with frequency spacing of less than two percent.

Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI.

PubMed

Lerch, Jason P; Worsley, Keith; Shaw, W Philip; Greenstein, Deanna K; Lenroot, Rhoshel K; Giedd, Jay; Evans, Alan C

2006-07-01

We introduce MACACC-Mapping Anatomical Correlations Across Cerebral Cortex-to study correlated changes within and across different cortical networks. The principal topic of investigation is whether the thickness of one area of the cortex changes in a statistically correlated fashion with changes in thickness of other cortical regions. We further extend these methods by introducing techniques to test whether different population groupings exhibit significantly varying MACACC patterns. The methods are described in detail and applied to a normal childhood development population (n = 292), and show that association cortices have the highest correlation strengths. Taking Brodmann Area (BA) 44 as a seed region revealed MACACC patterns strikingly similar to tractography maps obtained from diffusion tensor imaging. Furthermore, the MACACC map of BA 44 changed with age, older subjects featuring tighter correlations with BA 44 in the anterior portions of the superior temporal gyri. Lastly, IQ-dependent MACACC differences were investigated, revealing steeper correlations between BA 44 and multiple frontal and parietal regions for the higher IQ group, most significantly (t = 4.0) in the anterior cingulate.

Two-particle correlation function and dihadron correlation approach

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

Vechernin, V. V., E-mail: v.vechernin@spbu.ru; Ivanov, K. O.; Neverov, D. I.

It is shown that, in the case of asymmetric nuclear interactions, the application of the traditional dihadron correlation approach to determining a two-particle correlation function C may lead to a form distorted in relation to the canonical pair correlation function {sub C}{sup 2}. This result was obtained both by means of exact analytic calculations of correlation functions within a simple string model for proton–nucleus and deuteron–nucleus collisions and by means of Monte Carlo simulations based on employing the HIJING event generator. It is also shown that the method based on studying multiplicity correlations in two narrow observation windows separated inmore » rapidity makes it possible to determine correctly the canonical pair correlation function C{sub 2} for all cases, including the case where the rapidity distribution of product particles is not uniform.« less

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Are peer specialists happy on the job?

PubMed

Jenkins, Sarah; Chenneville, Tiffany; Salnaitis, Christina

2018-03-01

This study was designed to examine the impact of role clarity and job training on job satisfaction among peer specialists. A 3-part survey assessing job training, job satisfaction, and role clarity was administered online to 195 peer specialists who are members of the International Association of Peer Specialists. Data was analyzed using descriptive statistics, correlational analyses to include multiple linear regressions and analysis of variance. Self-study and online training methods were negatively correlated with job satisfaction while job shadowing was positively correlated with job satisfaction. Role clarity was positively correlated with job satisfaction and job training satisfaction as well as job shadowing and one-on-one training. The use of self-study and online training for peer specialists is contraindicated by current findings, which suggest the need to utilize job shadowing or training methods that allow for personal interaction between peer specialists and their colleagues. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

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

An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.

PubMed

Kim, Junghi; Bai, Yun; Pan, Wei

2015-12-01

We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods. © 2015 WILEY PERIODICALS, INC.

Multi-camera digital image correlation method with distributed fields of view

NASA Astrophysics Data System (ADS)

Malowany, Krzysztof; Malesa, Marcin; Kowaluk, Tomasz; Kujawinska, Malgorzata

2017-11-01

A multi-camera digital image correlation (DIC) method and system for measurements of large engineering objects with distributed, non-overlapping areas of interest are described. The data obtained with individual 3D DIC systems are stitched by an algorithm which utilizes the positions of fiducial markers determined simultaneously by Stereo-DIC units and laser tracker. The proposed calibration method enables reliable determination of transformations between local (3D DIC) and global coordinate systems. The applicability of the method was proven during in-situ measurements of a hall made of arch-shaped (18 m span) self-supporting metal-plates. The proposed method is highly recommended for 3D measurements of shape and displacements of large and complex engineering objects made from multiple directions and it provides the suitable accuracy of data for further advanced structural integrity analysis of such objects.

Associated relaxation time and the correlation function for a tumor cell growth system subjected to color noises

NASA Astrophysics Data System (ADS)

Wang, Can-Jun; Wei, Qun; Mei, Dong-Cheng

2008-03-01

The associated relaxation time T and the normalized correlation function C(s) for a tumor cell growth system subjected to color noises are investigated. Using the Novikov theorem and Fox approach, the steady probability distribution is obtained. Based on them, the expressions of T and C(s) are derived by means of projection operator method, in which the effects of the memory kernels of the correlation function are taken into account. Performing the numerical computations, it is found: (1) With the cross-correlation intensity |λ|, the additive noise intensity α and the multiplicative noise self-correlation time τ increasing, the tumor cell numbers can be restrained; And the cross-correlation time τ, the multiplicative noise intensity D can induce the tumor cell numbers increasing; However, the additive noise self-correlation time τ cannot affect the tumor cell numbers; The relaxation time T is a stochastic resonant phenomenon, and the distribution curves exhibit a single-maximum structure with D increasing. (2) The cross-correlation strength λ weakens the related activity between two states of the tumor cell numbers at different time, and enhances the stability of the tumor cell growth system in the steady state; On the contrast, τ and τ enhance the related activity between two states at different time; However, τ has no effect on the related activity between two states at different time.

Basal fire wounds on some southern Appalachian hardwoods

Treesearch

RM Nelson; IH Sims; MS. Abell

1933-01-01

Data from 317 oaks and yellow poplars wounded by a spring fire in Virginia were analyzed by means of multiple linear correlation. A method was obtained whereby the size of wound can be predicted provided the areas of discolored bark and diameters of injured trees are known. The method of prediction so far is safely applicable only to groups of trees similar to those...

Optical coherence tomography angiography retinal vascular network assessment in multiple sclerosis.

PubMed

Lanzillo, Roberta; Cennamo, Gilda; Criscuolo, Chiara; Carotenuto, Antonio; Velotti, Nunzio; Sparnelli, Federica; Cianflone, Alessandra; Moccia, Marcello; Brescia Morra, Vincenzo

2017-09-01

Optical coherence tomography (OCT) angiography is a new method to assess the density of the vascular networks. Vascular abnormalities are considered involved in multiple sclerosis (MS) pathology. To assess the presence of vascular abnormalities in MS and to evaluate their correlation to disease features. A total of 50 MS patients with and without history of optic neuritis (ON) and 46 healthy subjects were included. All underwent spectral domain (SD)-OCT and OCT angiography. Clinical history, Expanded Disability Status Scale (EDSS), Multiple Sclerosis Severity Score (MSSS) and disease duration were collected. Angio-OCT showed a vessel density reduction in eyes of MS patients when compared to controls. A statistically significant reduction in all SD-OCT and OCT angiography parameters was noticed both in eyes with and without ON when compared with control eyes. We found an inverse correlation between SD-OCT parameters and MSSS ( p = 0.003) and between vessel density parameters and EDSS ( p = 0.007). We report a vessel density reduction in retina of MS patients. We highlight the clinical correlation between vessel density and EDSS, suggesting that angio-OCT could be a good marker of disease and of disability in MS.

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).

Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients.

PubMed

Harutyunyan, Nika M; Vardanyan, Suzie; Ghermezi, Michael; Gottlieb, Jillian; Berenson, Ariana; Andreu-Vieyra, Claudia; Berenson, James R

2016-07-01

Multiple myeloma (MM) is characterized by the enhanced production of the same monoclonal immunoglobulin (M-Ig or M protein). Techniques such as serum protein electrophoresis and nephelometry are routinely used to quantify levels of this protein in the serum of MM patients. However, these methods are not without their shortcomings and problems accurately quantifying M proteins remain. Precise quantification of the types and levels of M-Ig present is critical to monitoring patient response to therapy. In this study, we investigated the ability of the HevyLite (HLC) immunoassay to correlate with clinical status based on levels of involved and uninvolved antibodies. In our cohort of MM patients, we observed that significantly higher ratios and greater differences of involved HLC levels compared to uninvolved HLC levels correlated with a worse clinical status. Similarly, higher absolute levels of involved HLC antibodies and lower levels of uninvolved HLC antibodies also correlated with a worse clinical status and a shorter progression-free survival. These findings suggest that the HLC assay is a useful and a promising tool for determining the clinical status and survival time for patients with multiple myeloma. © 2016 John Wiley & Sons Ltd.

Diffusion Tensor Imaging of the Optic Tracts in Multiple Sclerosis: Association with Retinal Thinning and Visual Disability

PubMed Central

Dasenbrock, Hormuzdiyar H.; Smith, Seth A.; Ozturk, Arzu; Farrell, Sheena K.; Calabresi, Peter A.; Reich, Daniel S.

2009-01-01

Background and purpose Visual disability is common in multiple sclerosis, but its relationship to abnormalities of the optic tracts remains unknown. Because they are only rarely affected by lesions, the optic tracts may represent a good model for assessing the imaging properties of normal-appearing white matter in multiple sclerosis. Methods Whole-brain diffusion tensor imaging was performed on 34 individuals with multiple sclerosis and 26 healthy volunteers. The optic tracts were reconstructed by tractography, and tract-specific diffusion indices were quantified. In the multiple-sclerosis group, peripapillary retinal nerve-fiber-layer thickness and total macular volume were measured by optical coherence tomography, and visual acuity at 100%, 2.5%, and 1.25% contrast was examined. Results After adjusting for age and sex, optic-tract mean and perpendicular diffusivity were higher (p=0.002) in multiple sclerosis. Lower optic-tract fractional anisotropy was correlated with retinal nerve-fiber-layer thinning (r=0.51, p=0.003) and total-macular-volume reduction (r=0.59, p=0.002). However, optic-tract diffusion indices were not specifically correlated with visual acuity or with their counterparts in the optic radiation. Conclusions Optic-tract diffusion abnormalities are associated with retinal damage, suggesting that both may be related to optic-nerve injury, but do not appear to contribute strongly to visual disability in multiple sclerosis. PMID:20331501

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Measuring and imaging diffusion with multiple scan speed image correlation spectroscopy.

PubMed

Gröner, Nadine; Capoulade, Jérémie; Cremer, Christoph; Wachsmuth, Malte

2010-09-27

The intracellular mobility of biomolecules is determined by transport and diffusion as well as molecular interactions and is crucial for many processes in living cells. Methods of fluorescence microscopy like confocal laser scanning microscopy (CLSM) can be used to characterize the intracellular distribution of fluorescently labeled biomolecules. Fluorescence correlation spectroscopy (FCS) is used to describe diffusion, transport and photo-physical processes quantitatively. As an alternative to FCS, spatially resolved measurements of mobilities can be implemented using a CLSM by utilizing the spatio-temporal information inscribed into the image by the scan process, referred to as raster image correlation spectroscopy (RICS). Here we present and discuss an extended approach, multiple scan speed image correlation spectroscopy (msICS), which benefits from the advantages of RICS, i.e. the use of widely available instrumentation and the extraction of spatially resolved mobility information, without the need of a priori knowledge of diffusion properties. In addition, msICS covers a broad dynamic range, generates correlation data comparable to FCS measurements, and allows to derive two-dimensional maps of diffusion coefficients. We show the applicability of msICS to fluorophores in solution and to free EGFP in living cells.

[High-sensitive detection of multiple allergenic proteins in infant food with high-resolution mass spectrometry].

PubMed

Wu, Ci; Chen, Xi; Liu, Jianhui; Zhang, Xiaolin; Xue, Weifeng; Liang, Zhen; Liu, Mengyao; Cui, Yan; Huang, Daliang; Zhang, Lihua

2017-10-08

A novel method of the simultaneous detection of multiple kinds of allergenic proteins in infant food with parallel reaction monitoring (PRM) mode using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was established. In this method, unique peptides with good stability and high sensibility were used to quantify the corresponding allergenic proteins. Furthermore, multiple kinds of allergenic proteins are inspected simultaneously with high sensitivity. In addition, such method was successfully used for the detection of multiple allergenic proteins in infant food. As for the sample preparation for infant food, compared with the traditional acetone precipitation strategy, the protein extraction efficiency and capacity of resisting disturbance are both higher with in-situ filter-aided sample pretreatment (i-FASP) method. All allergenic proteins gave a good linear response with the correlation coefficients ( R 2 ) ≥ 0.99, and the largest concentration range of the allergenic proteins could be four orders of magnitude, and the lowest detection limit was 0.028 mg/L, which was better than that reported in references. Finally, the method was conveniently used to detect the allergens from four imported infant food real samples. All the results demonstrate that this novel strategy is of great significance for providing a rapid and reliable analytical technique for allergen proteomics.

Unexpected flood loss correlations across Europe

NASA Astrophysics Data System (ADS)

Booth, Naomi; Boyd, Jessica

2017-04-01

Floods don't observe country borders, as highlighted by major events across Europe that resulted in heavy economic and insured losses in 1999, 2002, 2009 and 2013. Flood loss correlations between some countries occur along multi-country river systems or between neighbouring nations affected by the same weather systems. However, correlations are not so obvious and whilst flooding in multiple locations across Europe may appear independent, for a re/insurer providing cover across the continent, these unexpected correlations can lead to high loss accumulations. A consistent, continental-scale method that allows quantification and comparison of losses, and identifies correlations in loss between European countries is therefore essential. A probabilistic model for European river flooding was developed that allows estimation of potential losses to pan-European property portfolios. By combining flood hazard and exposure information in a catastrophe modelling platform, we can consider correlations between river basins across Europe rather than being restricted to country boundaries. A key feature of the model is its statistical event set based on extreme value theory. Using historical river flow data, the event set captures spatial and temporal patterns of flooding across Europe and simulates thousands of events representing a full range of possible scenarios. Some known correlations were identified, such as between neighbouring Belgium and Luxembourg where 28% of events that affect either country produce a loss in both. However, our model identified some unexpected correlations including between Austria and Poland, and Poland and France, which are geographically distant. These correlations in flood loss may be missed by traditional methods and are key for re/insurers with risks in multiple countries. The model also identified that 46% of European river flood events affect more than one country. For more extreme events with a return period higher than 200 years, all events impact more than one country. These tail events also demonstrate that it is unlikely for the market to experience an extreme event which does not affect at least five European countries.

Dynamic contrast-enhanced MR imaging of the rectum: Correlations between single-section and whole-tumor histogram analyses.

PubMed

Choi, M H; Oh, S N; Park, G E; Yeo, D-M; Jung, S E

2018-05-10

To evaluate the interobserver and intermethod correlations of histogram metrics of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters acquired by multiple readers using the single-section and whole-tumor volume methods. Four DCE parameters (K trans , K ep , V e , V p ) were evaluated in 45 patients (31 men and 14 women; mean age, 61±11 years [range, 29-83 years]) with locally advanced rectal cancer using pre-chemoradiotherapy (CRT) MRI. Ten histogram metrics were extracted using two methods of lesion selection performed by three radiologists: the whole-tumor volume method for the whole tumor on axial section-by-section images and the single-section method for the entire area of the tumor on one axial image. The interobserver and intermethod correlations were evaluated using the intraclass correlation coefficients (ICCs). The ICCs showed excellent interobserver and intermethod correlations in most of histogram metrics of the DCE parameters. The ICCs among the three readers were > 0.7 (P<0.001) for all histogram metrics, except for the minimum and maximum. The intermethod correlations for most of the histogram metrics were excellent for each radiologist, regardless of the differences in the radiologists' experience. The interobserver and intermethod correlations for most of the histogram metrics of the DCE parameters are excellent in rectal cancer. Therefore, the single-section method may be a potential alternative to the whole-tumor volume method using pre-CRT MRI, despite the fact that the high agreement between the two methods cannot be extrapolated to post-CRT MRI. Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

PubMed

Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra

2010-01-01

In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.

Hadamard multimode optical imaging transceiver

DOEpatents

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

2012-10-30

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

a Data Field Method for Urban Remotely Sensed Imagery Classification Considering Spatial Correlation

NASA Astrophysics Data System (ADS)

Zhang, Y.; Qin, K.; Zeng, C.; Zhang, E. B.; Yue, M. X.; Tong, X.

2016-06-01

Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary's C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM) for the classification of multi-features (e.g. the spectral feature and spatial correlation feature). In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.

Restoring method for missing data of spatial structural stress monitoring based on correlation

NASA Astrophysics Data System (ADS)

Zhang, Zeyu; Luo, Yaozhi

2017-07-01

Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.

Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in p p and p +Pb collisions with the ATLAS detector at the CERN Large Hadron Collider

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

Aaboud, M.; Aad, G.; Abbott, B.

A detailed study of multiparticle azimuthal correlations is presented using pp data at √s = 5.02 and 13 TeV, and p+Pb data at √ sNN = 5.02 TeV, recorded with the ATLAS detector at the CERN Large Hadron Collider. The azimuthal correlations are probed using four-particle cumulants c n {4} and flow coefficients v n {4} = (-c n{4}) 1/4 for n = 2 and 3, with the goal of extracting long-range multiparticle azimuthal correlation signals and suppressing the short-range correlations. The values of c n {4} are obtained as a function of the average number of charged particles permore » event, (N ch), using the recently proposed two-subevent and three-subevent cumulant methods, and compared with results obtained with the standard cumulant method. The standard method is found to be strongly biased by short-range correlations, which originate mostly from jets with a positive contribution to c n {4}. The three-subevent method, on the other hand, is found to be least sensitive to short-range correlations. The three-subevent method gives a negative c 2 {4}, and therefore a well-defined v 2 {4}, nearly independent of (N ch), which implies that the long-range multiparticle azimuthal correlations persist to events with low multiplicity. Furthermore, v 2 {4} is found to be smaller than the v 2 {2} measured using the two-particle correlation method, as expected for long-range collective behavior. Finally, the measured values of v 2 {4} and v 2 {2} are used to estimate the number of sources relevant for the initial eccentricity in the collision geometry. The results based on the subevent cumulant technique provide direct evidence, in small collision systems, for a long-range collectivity involving many particles distributed across a broad rapidity interval.« less

Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in p p and p +Pb collisions with the ATLAS detector at the CERN Large Hadron Collider

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

Aaboud, M.; Aad, G.; Abbott, B.

A demore » tailed study of multiparticle azimuthal correlations is presented using pp data at $$\\sqrt{s}$$=5.02 and 13 TeV, and p+Pb data at s NN =5.02 TeV, recorded with the ATLAS detector at the CERN Large Hadron Collider. The azimuthal correlations are probed using four-particle cumulants c n{4} and flow coefficients v n{4}=(-c n{4}) 1/4 for n=2 and 3, with the goal of extracting long-range multiparticle azimuthal correlation signals and suppressing the short-range correlations. The values of c n{4} are obtained as a function of the average number of charged particles per event, N ch, using the recently proposed two-subevent and three-subevent cumulant methods, and compared with results obtained with the standard cumulant method. The standard method is found to be strongly biased by short-range correlations, which originate mostly from jets with a positive contribution to cn{4}. The three-subevent method, on the other hand, is found to be least sensitive to short-range correlations. The three-subevent method gives a negative c 2{4}, and therefore a well-defined v 2{4}, nearly independent of N ch, which implies that the long-range multiparticle azimuthal correlations persist to events with low multiplicity. Furthermore, v 2{4} is found to be smaller than the v 2{2} measured using the two-particle correlation method, as expected for long-range collective behavior. Finally, the measured values of v 2{4} and v 2{2} are used to estimate the number of sources relevant for the initial eccentricity in the collision geometry. Finally, the results based on the subevent cumulant technique provide direct evidence, in small collision systems, for a long-range collectivity involving many particles distributed across a broad rapidity interval.« less

Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in p p and p +Pb collisions with the ATLAS detector at the CERN Large Hadron Collider

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2018-02-12

A demore » tailed study of multiparticle azimuthal correlations is presented using pp data at $$\\sqrt{s}$$=5.02 and 13 TeV, and p+Pb data at s NN =5.02 TeV, recorded with the ATLAS detector at the CERN Large Hadron Collider. The azimuthal correlations are probed using four-particle cumulants c n{4} and flow coefficients v n{4}=(-c n{4}) 1/4 for n=2 and 3, with the goal of extracting long-range multiparticle azimuthal correlation signals and suppressing the short-range correlations. The values of c n{4} are obtained as a function of the average number of charged particles per event, N ch, using the recently proposed two-subevent and three-subevent cumulant methods, and compared with results obtained with the standard cumulant method. The standard method is found to be strongly biased by short-range correlations, which originate mostly from jets with a positive contribution to cn{4}. The three-subevent method, on the other hand, is found to be least sensitive to short-range correlations. The three-subevent method gives a negative c 2{4}, and therefore a well-defined v 2{4}, nearly independent of N ch, which implies that the long-range multiparticle azimuthal correlations persist to events with low multiplicity. Furthermore, v 2{4} is found to be smaller than the v 2{2} measured using the two-particle correlation method, as expected for long-range collective behavior. Finally, the measured values of v 2{4} and v 2{2} are used to estimate the number of sources relevant for the initial eccentricity in the collision geometry. Finally, the results based on the subevent cumulant technique provide direct evidence, in small collision systems, for a long-range collectivity involving many particles distributed across a broad rapidity interval.« less

Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in p p and p +Pb collisions with the ATLAS detector at the CERN Large Hadron Collider

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, B. H.; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. 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G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; 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, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2018-02-01

A detailed study of multiparticle azimuthal correlations is presented using p p data at √{s }=5.02 and 13 TeV, and p +Pb data at √{sNN}=5.02 TeV, recorded with the ATLAS detector at the CERN Large Hadron Collider. The azimuthal correlations are probed using four-particle cumulants cn{4 } and flow coefficients vn{4 } =(-cn{4 } ) 1 /4 for n =2 and 3, with the goal of extracting long-range multiparticle azimuthal correlation signals and suppressing the short-range correlations. The values of cn{4 } are obtained as a function of the average number of charged particles per event, <" close=">Nch>">Nch, using the recently proposed two-subevent and three-subevent cumulant methods, and compared with results obtained with the standard cumulant method. The standard method is found to be strongly biased by short-range correlations, which originate mostly from jets with a positive contribution to cn{4 } . The three-subevent method, on the other hand, is found to be least sensitive to short-range correlations. The three-subevent method gives a negative c2{4 } , and therefore a well-defined v2{4 } , nearly independent of Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in p p and p +Pb collisions with the ATLAS detector at the CERN Large Hadron Collider

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2018-02-12

A detailed study of multiparticle azimuthal correlations is presented using pp data at √s = 5.02 and 13 TeV, and p+Pb data at √ sNN = 5.02 TeV, recorded with the ATLAS detector at the CERN Large Hadron Collider. The azimuthal correlations are probed using four-particle cumulants c n {4} and flow coefficients v n {4} = (-c n{4}) 1/4 for n = 2 and 3, with the goal of extracting long-range multiparticle azimuthal correlation signals and suppressing the short-range correlations. The values of c n {4} are obtained as a function of the average number of charged particles permore » event, (N ch), using the recently proposed two-subevent and three-subevent cumulant methods, and compared with results obtained with the standard cumulant method. The standard method is found to be strongly biased by short-range correlations, which originate mostly from jets with a positive contribution to c n {4}. The three-subevent method, on the other hand, is found to be least sensitive to short-range correlations. The three-subevent method gives a negative c 2 {4}, and therefore a well-defined v 2 {4}, nearly independent of (N ch), which implies that the long-range multiparticle azimuthal correlations persist to events with low multiplicity. Furthermore, v 2 {4} is found to be smaller than the v 2 {2} measured using the two-particle correlation method, as expected for long-range collective behavior. Finally, the measured values of v 2 {4} and v 2 {2} are used to estimate the number of sources relevant for the initial eccentricity in the collision geometry. The results based on the subevent cumulant technique provide direct evidence, in small collision systems, for a long-range collectivity involving many particles distributed across a broad rapidity interval.« less

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

PubMed Central

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-01-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder.

PubMed

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-04-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

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…

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…

Automated acoustic localization and call association for vocalizing humpback whales on the Navy's Pacific Missile Range Facility.

PubMed

Helble, Tyler A; Ierley, Glenn R; D'Spain, Gerald L; Martin, Stephen W

2015-01-01

Time difference of arrival (TDOA) methods for acoustically localizing multiple marine mammals have been applied to recorded data from the Navy's Pacific Missile Range Facility in order to localize and track humpback whales. Modifications to established methods were necessary in order to simultaneously track multiple animals on the range faster than real-time and in a fully automated way, while minimizing the number of incorrect localizations. The resulting algorithms were run with no human intervention at computational speeds faster than the data recording speed on over forty days of acoustic recordings from the range, spanning multiple years. Spatial localizations based on correlating sequences of units originating from within the range produce estimates having a standard deviation typically 10 m or less (due primarily to TDOA measurement errors), and a bias of 20 m or less (due primarily to sound speed mismatch). An automated method for associating units to individual whales is presented, enabling automated humpback song analyses to be performed.

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.

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

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Riley, Richard D; Abrams, Keith R

2016-03-30

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Time-series analysis of multiple foreign exchange rates using time-dependent pattern entropy

NASA Astrophysics Data System (ADS)

Ishizaki, Ryuji; Inoue, Masayoshi

2018-01-01

Time-dependent pattern entropy is a method that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window. We use this method to analyze the instability of daily variations in multiple foreign exchange rates. The time-dependent pattern entropy of 7 foreign exchange rates (AUD/USD, CAD/USD, CHF/USD, EUR/USD, GBP/USD, JPY/USD, and NZD/USD) was found to be high in the long period after the Lehman shock, and be low in the long period after Mar 2012. We compared the correlation matrix between exchange rates in periods of high and low of the time-dependent pattern entropy.

Link Correlation Based Transmit Sector Antenna Selection for Alamouti Coded OFDM

NASA Astrophysics Data System (ADS)

Ahn, Chang-Jun

In MIMO systems, the deployment of a multiple antenna technique can enhance the system performance. However, since the cost of RF transmitters is much higher than that of antennas, there is growing interest in techniques that use a larger number of antennas than the number of RF transmitters. These methods rely on selecting the optimal transmitter antennas and connecting them to the respective. In this case, feedback information (FBI) is required to select the optimal transmitter antenna elements. Since FBI is control overhead, the rate of the feedback is limited. This motivates the study of limited feedback techniques where only partial or quantized information from the receiver is conveyed back to the transmitter. However, in MIMO/OFDM systems, it is difficult to develop an effective FBI quantization method for choosing the space-time, space-frequency, or space-time-frequency processing due to the numerous subchannels. Moreover, MIMO/OFDM systems require antenna separation of 5 ∼ 10 wavelengths to keep the correlation coefficient below 0.7 to achieve a diversity gain. In this case, the base station requires a large space to set up multiple antennas. To reduce these problems, in this paper, we propose the link correlation based transmit sector antenna selection for Alamouti coded OFDM without FBI.

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

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

Modal smoothing for analysis of room reflections measured with spherical microphone and loudspeaker arrays.

PubMed

Morgenstern, Hai; Rafaely, Boaz

2018-02-01

Spatial analysis of room acoustics is an ongoing research topic. Microphone arrays have been employed for spatial analyses with an important objective being the estimation of the direction-of-arrival (DOA) of direct sound and early room reflections using room impulse responses (RIRs). An optimal method for DOA estimation is the multiple signal classification algorithm. When RIRs are considered, this method typically fails due to the correlation of room reflections, which leads to rank deficiency of the cross-spectrum matrix. Preprocessing methods for rank restoration, which may involve averaging over frequency, for example, have been proposed exclusively for spherical arrays. However, these methods fail in the case of reflections with equal time delays, which may arise in practice and could be of interest. In this paper, a method is proposed for systems that combine a spherical microphone array and a spherical loudspeaker array, referred to as multiple-input multiple-output systems. This method, referred to as modal smoothing, exploits the additional spatial diversity for rank restoration and succeeds where previous methods fail, as demonstrated in a simulation study. Finally, combining modal smoothing with a preprocessing method is proposed in order to increase the number of DOAs that can be estimated using low-order spherical loudspeaker arrays.

Learning style preferences and their influence on students' problem solving in kinematics observed by eye-tracking method

NASA Astrophysics Data System (ADS)

Kekule, Martina

2017-01-01

The article presents eye-tracking method and its using for observing students when they solve problems from kinematics. Particularly, multiple-choice items in TUG-K test by Robert Beichner. Moreover, student's preference for visual way of learning as a possible influential aspect is proofed and discussed. Learning Style Inventory by Dunn, Dunn&Price was administered to students in order to find out their preferences. More than 20 high school and college students about 20 years old took part in the research. Preferred visual way of learning in contrast to the other ways of learning (audio, tactile, kinesthetic) shows very slight correlation with the total score of the test, none correlation with the average fixation duration and slight correlation with average fixation count on a task and average total visit duration on a task.

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

Comparative study on treatment satisfaction and health perception in children and adolescents with type 1 diabetes mellitus on multiple daily injection of insulin, insulin pump and sensor-augmented pump therapy.

PubMed

Hussain, Tara; Akle, Mariette; Nagelkerke, Nico; Deeb, Asma

2017-01-01

Diabetes management imposes considerable demands on patients. Treatment method used has an impact on treatment satisfaction. We aim to examine the relationship between treatment satisfaction and health perception with the method used for treatment of type 1 diabetes mellitus in children and adolescents. We have interviewed patients with type 1 diabetes mellitus using questionnaires to assess treatment satisfaction and health perception. Patients were divided into three groups based on treatment used: multiple daily injection, insulin pump and sensor-augmented pump therapy. Comparison of scores was done between the groups. A total of 72 patients were enrolled (36 males). Mean age (standard deviation) was 11.4 (4.4) years and duration of diabetes of 4.9 (3.5) years. Mean (standard deviation) HbA1c was 8.1 (1.2). Median (range) duration of sensor use was 17.7 (3-30) days/month. Mean scale for treatment satisfaction and health perception questions was 25.3, 29.7 and 31.7 and 60, 79.7 and 81 for the multiple daily injection, pump and sensor-augmented pump, respectively (p = 0.00). Significant difference was seen between the multiple daily injection and both other groups. Sensor-augmented pump group scored higher than the pump group. However, the difference was not statistically significant. Duration of sensor use showed no correlation with treatment satisfaction. The method used for diabetes treatment has an impact on patients' satisfaction and health perception in children and adolescents with type 1 diabetes mellitus. Insulin pump users have a higher treatment satisfaction and better health perception than those on multiple daily injection. Augmenting pump therapy with sensor use adds value to treatment satisfaction without correlation with the duration of the sensors use.

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

PubMed

Raghunandhan, S; Ravikumar, A; Kameswaran, Mohan; Mandke, Kalyani; Ranjith, R

2014-05-01

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.

Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor

PubMed Central

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high. PMID:22438703

Hand motion classification using a multi-channel surface electromyography sensor.

PubMed

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

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.

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

PubMed Central

Wang, Shijun; Yao, Jianhua; Liu, Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

2009-01-01

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice—Once supine and once prone—to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline. PMID:20095272

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

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

Wang Shijun; Yao Jianhua; Liu Jiamin

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined bymore » the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27{+-}52.97 to 14.98 mm{+-}11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.« less

The multiple mini-interview for emergency medicine resident selection.

PubMed

Hopson, Laura R; Burkhardt, John C; Stansfield, R Brent; Vohra, Taher; Turner-Lawrence, Danielle; Losman, Eve D

2014-04-01

The Multiple Mini-Interview (MMI) uses multiple, short-structured contacts to evaluate communication and professionalism. It predicts medical school success better than the traditional interview and application. Its acceptability and utility in emergency medicine (EM) residency selection are unknown. We theorized that participants would judge the MMI equal to a traditional unstructured interview and it would provide new information for candidate assessment. Seventy-one interns from 3 programs in the first month of training completed an eight-station MMI focused on EM topics. Pre- and post-surveys assessed reactions. MMI scores were compared with application data. EM grades correlated with MMI performance (F[1, 66] = 4.18; p < 0.05) with honors students having higher scores. Higher third-year clerkship grades were associated with higher MMI performance, although this was not statistically significant. MMI performance did not correlate with match desirability and did not predict most other components of an application. There was a correlation between lower MMI scores and lower global ranking on the Standardized Letter of Recommendation. Participants preferred a traditional interview (mean difference = 1.36; p < 0.01). A mixed format (traditional interview and MMI) was preferred over a MMI alone (mean difference = 1.1; p < 0.01). MMI performance did not significantly correlate with preference for the MMI. Although the MMI alone was viewed less favorably than a traditional interview, participants were receptive to a mixed-methods interview. The MMI does correlate with performance on the EM clerkship and therefore can measure important abilities for EM success. Future work will determine whether MMI performance predicts residency performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

NASA Technical Reports Server (NTRS)

Sinclair, Kenneth; Van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; Mcgill, Matthew

2017-01-01

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

Towards the construction of high-quality mutagenesis libraries.

PubMed

Li, Heng; Li, Jing; Jin, Ruinan; Chen, Wei; Liang, Chaoning; Wu, Jieyuan; Jin, Jian-Ming; Tang, Shuang-Yan

2018-07-01

To improve the quality of mutagenesis libraries in directed evolution strategy. In the process of library transformation, transformants which have been shown to take up more than one plasmid might constitute more than 20% of the constructed library, thereby extensively impairing the quality of the library. We propose a practical transformation method to prevent the occurrence of multiple-plasmid transformants while maintaining high transformation efficiency. A visual library model containing plasmids expressing different fluorescent proteins was used. Multiple-plasmid transformants can be reduced through optimizing plasmid DNA amount used for transformation based on the positive correlation between the occurrence frequency of multiple-plasmid transformants and the logarithmic ratio of plasmid molecules to competent cells. This method provides a simple solution for a seemingly common but often neglected problem, and should be valuable for improving the quality of mutagenesis libraries to enhance the efficiency of directed evolution strategies.

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.

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

Three-Dimensional Echocardiographic Assessment of Left Heart Chamber Size and Function with Fully Automated Quantification Software in Patients with Atrial Fibrillation.

PubMed

Otani, Kyoko; Nakazono, Akemi; Salgo, Ivan S; Lang, Roberto M; Takeuchi, Masaaki

2016-10-01

Echocardiographic determination of left heart chamber volumetric parameters by using manual tracings during multiple beats is tedious in atrial fibrillation (AF). The aim of this study was to determine the usefulness of fully automated left chamber quantification software with single-beat three-dimensional transthoracic echocardiographic data sets in patients with AF. Single-beat full-volume three-dimensional transthoracic echocardiographic data sets were prospectively acquired during consecutive multiple cardiac beats (≥10 beats) in 88 patients with AF. In protocol 1, left ventricular volumes, left ventricular ejection fraction, and maximal left atrial volume were validated using automated quantification against the manual tracing method in identical beats in 10 patients. In protocol 2, automated quantification-derived averaged values from multiple beats were compared with the corresponding values obtained from the indexed beat in all patients. Excellent correlations of left chamber parameters between automated quantification and the manual method were observed (r = 0.88-0.98) in protocol 1. The time required for the analysis with the automated quantification method (5 min) was significantly less compared with the manual method (27 min) (P < .0001). In protocol 2, there were excellent linear correlations between the averaged left chamber parameters and the corresponding values obtained from the indexed beat (r = 0.94-0.99), and test-retest variability of left chamber parameters was low (3.5%-4.8%). Three-dimensional transthoracic echocardiography with fully automated quantification software is a rapid and reliable way to measure averaged values of left heart chamber parameters during multiple consecutive beats. Thus, it is a potential new approach for left chamber quantification in patients with AF in daily routine practice. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

PubMed

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M

2011-07-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.

MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

PubMed Central

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.

2011-01-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652

Simultaneous regularization method for the determination of radius distributions from experimental multiangle correlation functions

NASA Astrophysics Data System (ADS)

Buttgereit, R.; Roths, T.; Honerkamp, J.; Aberle, L. B.

2001-10-01

Dynamic light scattering experiments have become a powerful tool in order to investigate the dynamical properties of complex fluids. In many applications in both soft matter research and industry so-called ``real world'' systems are subject of great interest. Here, the dilution of the investigated system often cannot be changed without getting measurement artifacts, so that one often has to deal with highly concentrated and turbid media. The investigation of such systems requires techniques that suppress the influence of multiple scattering, e.g., cross correlation techniques. However, measurements at turbid as well as highly diluted media lead to data with low signal-to-noise ratio, which complicates data analysis and leads to unreliable results. In this article a multiangle regularization method is discussed, which copes with the difficulties arising from such samples and enhances enormously the quality of the estimated solution. In order to demonstrate the efficiency of this multiangle regularization method we applied it to cross correlation functions measured at highly turbid samples.

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

Patterns of Objective and Subjective Burden of Informal Caregivers in Multiple Sclerosis.

PubMed

Bayen, E; Papeix, C; Pradat-Diehl, P; Lubetzki, C; Joël, M E

2015-01-01

Home care for patients with Multiple Sclerosis (MS) relies largely on informal caregivers (ICs). Methods. We assessed ICs objective burden (Resource Utilization in Dementia measuring informal care time (ICT)) and ICs subjective burden (Zarit Burden Inventory (ZBI)). ICs (N = 99) were spouses (70%), mean age 52 years, assisting disabled patients with a mean EDSS (Expanded Disability Status Scale) of 5.5, with executive dysfunction (mean DEX (Dysexecutive questionnaire) of 25) and a duration of MS ranging from 1 to 44 years. burden was high (mean ICT = 6.5 hours/day), mostly consisting of supervision time. Subjective burden was moderate (mean ZBI = 27.3). Multivariate analyses showed that both burdens were positively correlated with higher levels of EDSS and DEX, whereas coresidency and IC's female gender correlated with objective burden only and IC's poor mental health status with subjective burden only. When considering MS aggressiveness, it appeared that both burdens were not correlated with a higher duration of MS but rather increased for patients with severe and early dysexecutive function and for patients classified as fast progressors according to the Multiple Sclerosis Severity Score. Evaluation of MS disability course and IC's personal situation is crucial to understand the burden process and to implement adequate interventions in MS.

Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.

PubMed

Rajan, Jeny; Veraart, Jelle; Van Audekerke, Johan; Verhoye, Marleen; Sijbers, Jan

2012-12-01

Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. Copyright © 2012 Elsevier Inc. All rights reserved.

Multiple Light Scattering Probes of Soft Materials

NASA Astrophysics Data System (ADS)

Scheffold, Frank

2007-02-01

I will discuss both static and dynamic properties of diffuse waves. In practical applications the optical properties of colloidal systems play an important role, for example in commercial products such as sunscreen lotions, food (drinks), coatings but also in medicine for example in cataract formation (eye lens turbidity). It is thus of importance to know the key parameters governing optical turbidity from the single to the multiple scattering regime. Temporal fluctuations of multiply scattered light are studied with photon correlation spectroscopy (Diffusing Wave Spectroscopy). This DWS method and its various implementations will be treated.

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.

A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation

NASA Astrophysics Data System (ADS)

Kim, Seokhyeon; Parinussa, Robert M.; Liu, Yi. Y.; Johnson, Fiona M.; Sharma, Ashish

2015-08-01

A method for combining two microwave satellite soil moisture products by maximizing the temporal correlation with a reference data set has been developed. The method was applied to two global soil moisture data sets, Japan Aerospace Exploration Agency (JAXA) and Land Parameter Retrieval Model (LPRM), retrieved from the Advanced Microwave Scanning Radiometer 2 observations for the period 2012-2014. A global comparison revealed superior results of the combined product compared to the individual products against the reference data set of ERA-Interim volumetric water content. The global mean temporal correlation coefficient of the combined product with this reference was 0.52 which outperforms the individual JAXA (0.35) as well as the LPRM (0.45) product. Additionally, the performance was evaluated against in situ observations from the International Soil Moisture Network. The combined data set showed a significant improvement in temporal correlation coefficients in the validation compared to JAXA and minor improvements for the LPRM product.

Correlates of Mental Health among Latino Farmworkers in North Carolina

ERIC Educational Resources Information Center

Crain, Rebecca; Grzywacz, Joseph G.; Schwantes, Melody; Isom, Scott; Quandt, Sara A.; Arcury, Thomas A.

2012-01-01

Purpose: Latino farmworkers are a vulnerable population who confront multiple threats to their mental health. Informed by the stress-process model of psychiatric disorder, the goal of this paper is to determine primary and context-specific stressors of poor mental health among Latino farmworkers. Methods: Structured interview data were obtained…

Determination of Habitat Requirements For Birds in Suburban Areas

Treesearch

Jack Ward Thomas; Richard M. DeGraaf; Joseph C. Mawson

1977-01-01

Songbird populations can be related to habitat components by a method that allows the simultaneous determination of habitat requirements for a variety of species . Through correlation and multiple-regression analyses, 10 bird species were studied in a suburban habitat, which was stratified according to human density. Variables used to account for bird distribution...

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.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

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

2017-01-01

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

Testing a single regression coefficient in high dimensional linear models.

PubMed

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

2016-11-01

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

Cross-Informant Symptoms from CBCL, TRF, and YSR: Trait and Method Variance in a Normative Sample of Russian Youths

PubMed Central

Grigorenko, Elena L.; Geiser, Christian; Slobodskaya, Helena R.; Francis, David J.

2015-01-01

A large community-based sample of Russian youths (n = 847, mean age = 13.17, sd = 2.51) was assessed with the Child Behavior Checklist (mothers and fathers separately), Teacher’s Report Form, and Youth Self-Report. The multiple indicator-version of the Correlated Trait-Correlated (Method Minus One) [CT-C(M-1)] model was applied to analyze (1) the convergent and divergent validity of these instruments in Russia, (2) the degree of trait-specificity of rater biases, and (3) potential predictors of rater-specific effects. As expected, based on the published results from different countries and in different languages, the convergent validity of the instruments was rather high between mother and father reports, but rather low for parent, teacher, and self reports. For self- and teacher reports, rater-specific effects were related to age and gender of the children for some traits. These results, once again, attest to the importance of incorporating information from multiple observers when psychopathological traits are evaluated in children and adolescents. PMID:21133549

A Bayesian hierarchical approach to galaxy-galaxy lensing

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Leauthaud, Alexie

2018-07-01

We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter haloes and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does not resort to stacking the weak lensing signal in bins, and thus allows for a more efficient use of the information content in the data. Our method is particularly useful for constraining scaling relations between two or more galaxy properties and dark matter halo mass, and can also be used to constrain the intrinsic scatter in these scaling relations. We show that, if observational scatter is not properly accounted for, the traditional stacking method can produce biased results when exploring correlations between multiple galaxy properties and halo mass. For example, this bias can affect studies of the joint correlation between galaxy mass, halo mass, and galaxy size, or galaxy colour. In contrast, our method easily and efficiently handles the intrinsic and observational scatter in multiple galaxy properties and halo mass. We test our method on mocks with varying degrees of complexity. We find that we can recover the mean halo mass and concentration, each with a 0.1 dex accuracy, and the intrinsic scatter in halo mass with a 0.05 dex accuracy. In its current version, our method will be most useful for studying the weak lensing signal around central galaxies in groups and clusters, as well as massive galaxies samples with log M* > 11, which have low satellite fractions.

A Bayesian Hierarchical Approach to Galaxy-Galaxy Lensing

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Leauthaud, Alexie

2018-04-01

We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter halos and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does not resort to stacking the weak lensing signal in bins, and thus allows for a more efficient use of the information content in the data. Our method is particularly useful for constraining scaling relations between two or more galaxy properties and dark matter halo mass, and can also be used to constrain the intrinsic scatter in these scaling relations. We show that, if observational scatter is not properly accounted for, the traditional stacking method can produce biased results when exploring correlations between multiple galaxy properties and halo mass. For example, this bias can affect studies of the joint correlation between galaxy mass, halo mass, and galaxy size, or galaxy colour. In contrast, our method easily and efficiently handles the intrinsic and observational scatter in multiple galaxy properties and halo mass. We test our method on mocks with varying degrees of complexity. We find that we can recover the mean halo mass and concentration, each with a 0.1 dex accuracy, and the intrinsic scatter in halo mass with a 0.05 dex accuracy. In its current version, our method will be most useful for studying the weak lensing signal around central galaxies in groups and clusters, as well as massive galaxies samples with log M* > 11, which have low satellite fractions.

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

A spatial scan statistic for compound Poisson data.

PubMed

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Self-consistent implementation of ensemble density functional theory method for multiple strongly correlated electron pairs

DOE PAGES

Filatov, Michael; Liu, Fang; Kim, Kwang S.; ...

2016-12-22

Here, the spin-restricted ensemble-referenced Kohn-Sham (REKS) method is based on an ensemble representation of the density and is capable of correctly describing the non-dynamic electron correlation stemming from (near-)degeneracy of several electronic configurations. The existing REKS methodology describes systems with two electrons in two fractionally occupied orbitals. In this work, the REKS methodology is extended to treat systems with four fractionally occupied orbitals accommodating four electrons and self-consistent implementation of the REKS(4,4) method with simultaneous optimization of the orbitals and their fractional occupation numbers is reported. The new method is applied to a number of molecular systems where simultaneous dissociationmore » of several chemical bonds takes place, as well as to the singlet ground states of organic tetraradicals 2,4-didehydrometaxylylene and 1,4,6,9-spiro[4.4]nonatetrayl.« less

Ultrasonography of the biliary tract - up to date. The importance of correlation between imaging methods and patients' signs and symptoms.

PubMed

Badea, Radu; Zaro, Răzvan; Tanțău, Marcel; Chiorean, Liliana

2015-09-01

Ultrasonography is generally accepted and performed as a first choice imaging technique in patients with jaundice. The method allows the discrimination between cholestatic and mechanical jaundice. The existing procedures are multiple: gray scale, Doppler, i.v. contrast enhancement, elastography, tridimensional ultrasonography, each of these with different contribution to the positive and differential diagnosis regarding the nature of the jaundice. The final diagnosis is a multimodal one and the efficiency is dependent on the level of the available technology, the examiner's experience, the degree and modality of integration of the data within the clinical context, as well as on the portfolio of available imaging procedures. This review shows the main ultrasonographic methods consecrated in the evaluation of the biliary tree. It also underlines the integrated character of the procedures, as well as the necessity to correlate with other imaging methods and the clinical situation.

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.

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.

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

Sirunyan, A M; Tumasyan, A; Adam, W; Ambrogi, F; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Grossmann, J; Hrubec, J; Jeitler, M; König, A; Krammer, N; Krätschmer, I; Liko, D; Madlener, T; Mikulec, I; Pree, E; Rabady, D; Rad, N; Rohringer, H; Schieck, J; Schöfbeck, R; Spanring, M; Spitzbart, D; Waltenberger, W; Wittmann, J; Wulz, C-E; Zarucki, M; Chekhovsky, V; Mossolov, V; Suarez Gonzalez, J; De Wolf, E A; Di Croce, D; Janssen, X; Lauwers, J; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Abu Zeid, S; Blekman, F; D'Hondt, J; De Bruyn, I; De Clercq, J; Deroover, K; Flouris, G; Lontkovskyi, D; Lowette, S; Moortgat, S; Moreels, L; Python, Q; Skovpen, K; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Brun, H; Clerbaux, B; De Lentdecker, G; Delannoy, H; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Karapostoli, G; Lenzi, T; Luetic, J; Maerschalk, T; Marinov, A; Randle-Conde, A; Seva, T; Vander Velde, C; Vanlaer, P; Vannerom, D; Yonamine, R; Zenoni, F; Zhang, F; Cimmino, A; Cornelis, T; Dobur, D; Fagot, A; Gul, M; Khvastunov, I; Poyraz, D; Roskas, C; Salva, S; Tytgat, M; Verbeke, W; Zaganidis, N; Bakhshiansohi, H; Bondu, O; Brochet, S; Bruno, G; Caputo, C; Caudron, A; De Visscher, S; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Jafari, A; Komm, M; Krintiras, G; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Piotrzkowski, K; Quertenmont, L; Vidal Marono, M; Wertz, S; Beliy, N; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Melo De Almeida, M; Mora Herrera, C; Mundim, L; Nogima, H; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Torres Da Silva De Araujo, F; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Tomei, T R Fernandez Perez; Gregores, E M; Mercadante, P G; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Misheva, M; Rodozov, M; Shopova, M; Stoykova, S; Sultanov, G; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Fang, W; Gao, X; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Jiang, C H; Leggat, D; Liao, H; Liu, Z; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Yazgan, E; Zhang, H; Zhang, S; Zhao, J; Ban, Y; Chen, G; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; González Hernández, C F; Ruiz Alvarez, J D; Courbon, B; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Mesic, B; Starodumov, A; Susa, T; Ather, M W; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Finger, M; Finger, M; Carrera Jarrin, E; Assran, Y; Mahmoud, M A; Mahrous, A; Dewanjee, R K; Kadastik, M; Perrini, L; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Pekkanen, J; Voutilainen, M; Härkönen, J; Järvinen, T; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Tuominen, E; Tuominiemi, J; Tuovinen, E; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Faure, J L; Ferri, F; Ganjour, S; Ghosh, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Kucher, I; Locci, E; Machet, M; Malcles, J; Negro, G; Rander, J; Rosowsky, A; Sahin, M Ö; Titov, M; Abdulsalam, A; Amendola, C; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Charlot, C; Granier de Cassagnac, R; Jo, M; Lisniak, S; Lobanov, A; Martin Blanco, J; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Salerno, R; Sauvan, J B; Sirois, Y; Stahl Leiton, A G; Strebler, T; Yilmaz, Y; Zabi, A; Zghiche, A; Agram, J-L; Andrea, J; Bloch, D; Brom, J-M; Buttignol, M; Chabert, E C; Chanon, N; Collard, C; Conte, E; Coubez, X; Fontaine, J-C; Gelé, D; Goerlach, U; Jansová, M; Le Bihan, A-C; Tonon, N; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Finco, L; Gascon, S; Gouzevitch, M; Grenier, G; Ille, B; Lagarde, F; Laktineh, I B; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Popov, A; Sordini, V; Vander Donckt, M; Viret, S; Toriashvili, T; Tsamalaidze, Z; Autermann, C; Feld, L; Kiesel, M K; Klein, K; Lipinski, M; Preuten, M; Schomakers, C; Schulz, J; Verlage, T; Zhukov, V; Albert, A; Dietz-Laursonn, E; Duchardt, D; Endres, M; Erdmann, M; Erdweg, S; Esch, T; Fischer, R; Güth, A; Hamer, M; Hebbeker, T; Heidemann, C; Hoepfner, K; Knutzen, S; Merschmeyer, M; Meyer, A; Millet, P; Mukherjee, S; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Teyssier, D; Thüer, S; Flügge, G; Kargoll, B; Kress, T; Künsken, A; Lingemann, J; Müller, T; Nehrkorn, A; Nowack, A; Pistone, C; Pooth, O; Stahl, A; Aldaya Martin, M; Arndt, T; Asawatangtrakuldee, C; Beernaert, K; Behnke, O; Behrens, U; Bermúdez Martínez, A; Bin Anuar, A A; Borras, K; Botta, V; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Diez Pardos, C; Eckerlin, G; Eckstein, D; Eichhorn, T; Eren, E; Gallo, E; Garay Garcia, J; Geiser, A; Gizhko, A; Grados Luyando, J M; Grohsjean, A; Gunnellini, P; Guthoff, M; Harb, A; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Kasemann, M; Keaveney, J; Kleinwort, C; Korol, I; Krücker, D; Lange, W; Lelek, A; Lenz, T; Leonard, J; Lipka, K; Lohmann, W; Mankel, R; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Ntomari, E; Pitzl, D; Raspereza, A; Roland, B; Savitskyi, M; Saxena, P; Shevchenko, R; Spannagel, S; Stefaniuk, N; Van Onsem, G P; Walsh, R; Wen, Y; Wichmann, K; Wissing, C; Zenaiev, O; Bein, S; Blobel, V; Centis Vignali, M; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hinzmann, A; Hoffmann, M; Karavdina, A; Klanner, R; Kogler, R; Kovalchuk, N; Kurz, S; Lapsien, T; Marchesini, I; 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Filipovic, N; Pasztor, G; Veres, G I; Bencze, G; Hajdu, C; Horvath, D; Hunyadi, Á; Sikler, F; Veszpremi, V; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Makovec, A; Molnar, J; Szillasi, Z; Bartók, M; Raics, P; Trocsanyi, Z L; Ujvari, B; Choudhury, S; Komaragiri, J R; Bahinipati, S; Bhowmik, S; Mal, P; Mandal, K; Nayak, A; Sahoo, D K; Sahoo, N; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chawla, R; Dhingra, N; Kalsi, A K; Kaur, A; Kaur, M; Kumar, R; Kumari, P; Mehta, A; Singh, J B; Walia, G; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A; Chauhan, S; Choudhary, B C; Garg, R B; Keshri, S; Kumar, A; Malhotra, S; Naimuddin, M; Ranjan, K; Sharma, R; Bhardwaj, R; Bhattacharya, R; Bhattacharya, S; Bhawandeep, U; Dey, S; Dutt, S; Dutta, S; Ghosh, S; Majumdar, N; Modak, A; Mondal, K; Mukhopadhyay, S; Nandan, S; Purohit, A; Roy, A; Roy, D; Roy Chowdhury, S; Sarkar, S; Sharan, M; Thakur, S; Behera, P K; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Mohanty, A K; Netrakanti, P K; Pant, L M; Shukla, P; 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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. 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I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. 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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. I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Galinhas, B.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Seixas, J.; Strong, G.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Stepennov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chistov, R.; Danilov, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Tarkovskii, E.; Zhemchugov, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Ershov, A.; Gribushin, A.; Kaminskiy, A.; Kodolova, O.; Korotkikh, V.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Vardanyan, I.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Stojanovic, M.; Alcaraz Maestre, J.; Barrio Luna, M.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Álvarez Fernández, A.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Curras, E.; Duarte Campderros, J.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bianco, M.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fallavollita, F.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gilbert, A.; Gill, K.; Glege, F.; Gulhan, D.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karacheban, O.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Neugebauer, H.; Ngadiuba, J.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Bäni, L.; Berger, P.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Klijnsma, T.; Lustermann, W.; Mangano, B.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. 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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

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.

Correlation of Diffusion and Metabolic Alterations in Different Clinical Forms of Multiple Sclerosis

PubMed Central

Hannoun, Salem; Bagory, Matthieu; Durand-Dubief, Francoise; Ibarrola, Danielle; Comte, Jean-Christophe; Confavreux, Christian; Cotton, Francois; Sappey-Marinier, Dominique

2012-01-01

Diffusion tensor imaging (DTI) and MR spectroscopic imaging (MRSI) provide greater sensitivity than conventional MRI to detect diffuse alterations in normal appearing white matter (NAWM) of Multiple Sclerosis (MS) patients with different clinical forms. Therefore, the goal of this study is to combine DTI and MRSI measurements to analyze the relation between diffusion and metabolic markers, T2-weighted lesion load (T2-LL) and the patients clinical status. The sensitivity and specificity of both methods were then compared in terms of MS clinical forms differentiation. MR examination was performed on 71 MS patients (27 relapsing remitting (RR), 26 secondary progressive (SP) and 18 primary progressive (PP)) and 24 control subjects. DTI and MRSI measurements were obtained from two identical regions of interest selected in left and right centrum semioval (CSO) WM. DTI metrics and metabolic contents were significantly altered in MS patients with the exception of N-acetyl-aspartate (NAA) and NAA/Choline (Cho) ratio in RR patients. Significant correlations were observed between diffusion and metabolic measures to various degrees in every MS patients group. Most DTI metrics were significantly correlated with the T2-LL while only NAA/Cr ratio was correlated in RR patients. A comparison analysis of MR methods efficiency demonstrated a better sensitivity/specificity of DTI over MRSI. Nevertheless, NAA/Cr ratio could distinguish all MS and SP patients groups from controls, while NAA/Cho ratio differentiated PP patients from controls. This study demonstrated that diffusivity changes related to microstructural alterations were correlated with metabolic changes and provided a better sensitivity to detect early changes, particularly in RR patients who are more subject to inflammatory processes. In contrast, the better specificity of metabolic ratios to detect axonal damage and demyelination may provide a better index for identification of PP patients. PMID:22479330

The preferred magnetic resonance imaging planes in quantifying visceral adipose tissue and evaluating cardiovascular risk.

PubMed

Liu, K H; Chan, Y L; Chan, J C N; Chan, W B; Kong, M O; Poon, M Y

2005-09-01

Magnetic Resonance Imaging (MRI) is a well-accepted non-invasive method in the quantification of visceral adipose tissue. However, a standard method of measurement has not yet been universally agreed. The objectives of the present study were 2-fold, firstly, to identify the imaging plane in the Chinese population which gives the best correlation with total visceral adipose tissue volume and cardiovascular risk factors; and secondly to compare the correlations between single-slice and multiple-slice approach with cardiovascular risk factors. Thirty-seven Chinese subjects with no known medical history underwent MRI examination for quantifying total visceral adipose tissue volume. The visceral adipose tissue area at five axial imaging levels within abdomen and pelvis were determined. All subjects had blood pressure measured and fasting blood taken for analysis of cardiovascular risk factors. Framingham risk score for each subject was calculated. The imaging plane at the level of 'lower costal margin' (LCM) in both men and women had the highest correlation with total visceral adipose tissue volume (r = 0.97 and 0.99 respectively). The visceral adipose tissue area at specific imaging levels showed higher correlations with various cardiovascular risk factors and Framingham risk score than total visceral adipose tissue volume. The visceral adipose tissue area at 'umbilicus' (UMB) level in men (r = 0.88) and LCM level in women (r = 0.70) showed the best correlation with Framingham risk score. The imaging plane at the level of LCM is preferred for reflecting total visceral adipose tissue volume in Chinese subjects. For investigating the association of cardiovascular risk with visceral adipose tissue in MRI-obesity research, the single-slice approach is superior to the multiple-slice approach, with the level of UMB in men and LCM in women as the preferred imaging planes.

Prediction of beta-turns and beta-turn types by a novel bidirectional Elman-type recurrent neural network with multiple output layers (MOLEBRNN).

PubMed

Kirschner, Andreas; Frishman, Dmitrij

2008-10-01

Prediction of beta-turns from amino acid sequences has long been recognized as an important problem in structural bioinformatics due to their frequent occurrence as well as their structural and functional significance. Because various structural features of proteins are intercorrelated, secondary structure information has been often employed as an additional input for machine learning algorithms while predicting beta-turns. Here we present a novel bidirectional Elman-type recurrent neural network with multiple output layers (MOLEBRNN) capable of predicting multiple mutually dependent structural motifs and demonstrate its efficiency in recognizing three aspects of protein structure: beta-turns, beta-turn types, and secondary structure. The advantage of our method compared to other predictors is that it does not require any external input except for sequence profiles because interdependencies between different structural features are taken into account implicitly during the learning process. In a sevenfold cross-validation experiment on a standard test dataset our method exhibits the total prediction accuracy of 77.9% and the Mathew's Correlation Coefficient of 0.45, the highest performance reported so far. It also outperforms other known methods in delineating individual turn types. We demonstrate how simultaneous prediction of multiple targets influences prediction performance on single targets. The MOLEBRNN presented here is a generic method applicable in a variety of research fields where multiple mutually depending target classes need to be predicted. http://webclu.bio.wzw.tum.de/predator-web/.

Clinical Variables Correlated with Numbers of Intra-arterial Nimodipine Infusion in Patients with Medically Refractory Cerebral Vasospasm

PubMed Central

Kim, Sang-Young; Kim, Ki-Hong; Cho, Jae-Hoon

2015-01-01

Objective The objective of this study was to find out the clinical variables correlated with repeated intra-arterial (IA) nimodipine infusions in patients with medically refractory cerebral vasospasm (CV) following subarachnoid hemorrhage (SAH). Materials and Methods During the 36 months between January 2011 and December 2013, 275 patients were treated at our institute for SAH due to a ruptured intracranial aneurysm. Of the 275 patients, 26 patients (9.5%) met the inclusion criteria. For each patient, a retrospective review of their medical records was conducted. Results Eleven patients underwent a single IA nimodipine infusion and 15 patients underwent more than two IA nimodipine infusions. Multiple IA nimodipine infusion patients had poor improvement (2 of 15 patients, 13.3%) in Glasgow coma scale (GCS) scores after the first IA nimodipine infusion compared to patients of single IA nimodipine infusion (6 of 11 patients, 54.6%) (p = 0.038). The mean middle cerebral artery (MCA) Lindegaard ratio of multiple IA nimodipine infusion patients was 4.3 ± 1.1 after the first IA nimodipine infusion (p = 0.039). In multiple IA nimodipine infusion patients, CV occurred more often bilaterally (p = 0.035) and distally (p = 0.001). More vessel segments were affected in multiple IA nimodipine infusion patients (3.1 ± 1.0) (p < 0.001). Conclusion The following factors correlated with multiple IA nimodipine infusions: 1) no improvement in GCS after the IA nimodipine infusion; 2) no decrease of MCA velocity on transcranial doppler over 50 cm/s or Lindegaard ratio over 4.3 after the IA nimodipine infusion; 3) distal, bilateral, or diffuse involvement of CV. PMID:26523251

Multiple-Event Seismic Location Using the Markov-Chain Monte Carlo Technique

NASA Astrophysics Data System (ADS)

Myers, S. C.; Johannesson, G.; Hanley, W.

2005-12-01

We develop a new multiple-event location algorithm (MCMCloc) that utilizes the Markov-Chain Monte Carlo (MCMC) method. Unlike most inverse methods, the MCMC approach produces a suite of solutions, each of which is consistent with observations and prior estimates of data and model uncertainties. Model parameters in MCMCloc consist of event hypocenters, and travel-time predictions. Data are arrival time measurements and phase assignments. Posteriori estimates of event locations, path corrections, pick errors, and phase assignments are made through analysis of the posteriori suite of acceptable solutions. Prior uncertainty estimates include correlations between travel-time predictions, correlations between measurement errors, the probability of misidentifying one phase for another, and the probability of spurious data. Inclusion of prior constraints on location accuracy allows direct utilization of ground-truth locations or well-constrained location parameters (e.g. from InSAR) that aid in the accuracy of the solution. Implementation of a correlation structure for travel-time predictions allows MCMCloc to operate over arbitrarily large geographic areas. Transition in behavior between a multiple-event locator for tightly clustered events and a single-event locator for solitary events is controlled by the spatial correlation of travel-time predictions. We test the MCMC locator on a regional data set of Nevada Test Site nuclear explosions. Event locations and origin times are known for these events, allowing us to test the features of MCMCloc using a high-quality ground truth data set. Preliminary tests suggest that MCMCloc provides excellent relative locations, often outperforming traditional multiple-event location algorithms, and excellent absolute locations are attained when constraints from one or more ground truth event are included. When phase assignments are switched, we find that MCMCloc properly corrects the error when predicted arrival times are separated by several seconds. In cases where the predicted arrival times are within the combined uncertainty of prediction and measurement errors, MCMCloc determines the probability of one or the other phase assignment and propagates this uncertainty into all model parameters. We find that MCMCloc is a promising method for simultaneously locating large, geographically distributed data sets. Because we incorporate prior knowledge on many parameters, MCMCloc is ideal for combining trusted data with data of unknown reliability. This work was performed under the auspices of the U.S. Department of Energy by the University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48, Contribution UCRL-ABS-215048

In vivo 1D and 2D correlation MR spectroscopy of the soleus muscle at 7T

PubMed Central

Ramadan, Saadallah; Ratai, Eva-Maria; Wald, Lawrence L.; Mountford, Carolyn E.

2013-01-01

Aim This study aims to (1) undertake and analyse 1D and 2D MR correlation spectroscopy from human soleus muscle in vivo at 7T, and (2) determine T1 and T2 relaxation time constants at 7T field strength due to their importance in sequence design and spectral quantitation. Method Six healthy, male volunteers were consented and scanned on a 7T whole-body scanner (Siemens AG, Erlangen, Germany). Experiments were undertaken using a 28 cm diameter detunable birdcage coil for signal excitation and an 8.5 cm diameter surface coil for signal reception. The relaxation time constants, T1 and T2 were recorded using a STEAM sequence, using the ‘progressive saturation’ method for the T1 and multiple echo times for T2. The 2D L-Correlated SpectroscopY (L-COSY) method was employed with 64 increments (0.4 ms increment size) and eight averages per scan, with a total time of 17 min. Results T1 and T2 values for the metabolites of interest were determined. The L-COSY spectra obtained from the soleus muscle provided information on lipid content and chemical structure not available, in vivo, at lower field strengths. All molecular fragments within multiple lipid compartments were chemically shifted by 0.20–0.26 ppm at this field strength. 1D and 2D L-COSY spectra were assigned and proton connectivities were confirmed with the 2D method. Conclusion In vivo 1D and 2D spectroscopic examination of muscle can be successfully recorded at 7T and is now available to assess lipid alterations as well as other metabolites present with disease. T1 and T2 values were also determined in soleus muscle of male healthy volunteers. PMID:20206561

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.

Prognostic score–based balance measures for propensity score methods in comparative effectiveness research

PubMed Central

Stuart, Elizabeth A.; Lee, Brian K.; Leacy, Finbarr P.

2013-01-01

Objective Examining covariate balance is the prescribed method for determining when propensity score methods are successful at reducing bias. This study assessed the performance of various balance measures, including a proposed balance measure based on the prognostic score (also known as the disease-risk score), to determine which balance measures best correlate with bias in the treatment effect estimate. Study Design and Setting The correlations of multiple common balance measures with bias in the treatment effect estimate produced by weighting by the odds, subclassification on the propensity score, and full matching on the propensity score were calculated. Simulated data were used, based on realistic data settings. Settings included both continuous and binary covariates and continuous covariates only. Results The standardized mean difference in prognostic scores, the mean standardized mean difference, and the mean t-statistic all had high correlations with bias in the effect estimate. Overall, prognostic scores displayed the highest correlations of all the balance measures considered. Prognostic score measure performance was generally not affected by model misspecification and performed well under a variety of scenarios. Conclusion Researchers should consider using prognostic score–based balance measures for assessing the performance of propensity score methods for reducing bias in non-experimental studies. PMID:23849158

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

PubMed

Lujan, J Luis; Crago, Patrick E

2009-01-01

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

[Non-linear canonical correlation analysis between anthropometric indicators and multiple metabolic abnormalities].

PubMed

Fu, Xiaoli; Liu, Li; Ping, Zhiguang; Li, Linlin

2013-09-01

To define the general correlation between anthropometric indicators and multiple metabolic abnormalities, and to put forward some particular suggestions for the prevention of multiple metabolic abnormalities. A random cluster sampling was carried out in one county of Henan Province. Questionnaire, physical examination and biochemical tests were admitted to the adult inhabitants. Non-linear canonical correlation analysis (NLCCA) was applied with OVERALS of SPSS 13.0. The coefficients of canonical correlation and multiple correlation were calculated. The plot of centroids labeled by variables showed the correlation among various indicators. In total, 2,914 objects were investigated. It included 1,134 (38.9%) males and 1,780 (61.1%) females (60.0%). The average age was (50.58 +/- 13.70) years old. The fitting result of NLCCA were as follows: the loss of 0.577 accounting for 28.8% of the total variation was relatively small, and indicated that the two sets of variables of this study, namely sets of biochemical indicators (including serum total cholesterol, total triglyceride, high-density lipoprotein cholesterol, low density lipoprotein cholesterol and fasting plasma glucose) and sets of others (including gender, BMI and waist circumference) were closely related and often changed synchronously. Multivariate correlation coefficient showed that internal indicators of the above two sets were closely related respectively and often showed the multiple anomalies of the same set. The diagram of the center of gravity of the association of various indicators showed that the symptoms of metabolic abnormalities increased with age. Women were more liable to have metabolic abnormalities. Overweight and obese people often suffer multiple metabolic disorders. Waist circumference was positively correlated with metabolic abnormalities. (1) Biochemical indicators and anthropometric often change in combination. (2) Much attention should be paid to older people especially middle-aged or older men and older women in primary prevention. (3) Overweight and abdominal obesity can be considered the sensitive predictive indicator of multiple metabolic abnormalities. (4) Nonlinear canonical correlation and center of gravity Figure had the advantage of analyze the correlation between multiple sets of variables.

Joint channel/frequency offset estimation and correction for coherent optical FBMC/OQAM system

NASA Astrophysics Data System (ADS)

Wang, Daobin; Yuan, Lihua; Lei, Jingli; wu, Gang; Li, Suoping; Ding, Runqi; Wang, Dongye

2017-12-01

In this paper, we focus on analysis of the preamble-based joint estimation for channel and laser-frequency offset (LFO) in coherent optical filter bank multicarrier systems with offset quadrature amplitude modulation (CO-FBMC/OQAM). In order to reduce the noise impact on the estimation accuracy, we proposed an estimation method based on inter-frame averaging. This method averages the cross-correlation function of real-valued pilots within multiple FBMC frames. The laser-frequency offset is estimated according to the phase of this average. After correcting LFO, the final channel response is also acquired by averaging channel estimation results within multiple frames. The principle of the proposed method is analyzed theoretically, and the preamble structure is thoroughly designed and optimized to suppress the impact of inherent imaginary interference (IMI). The effectiveness of our method is demonstrated numerically using different fiber and LFO values. The obtained results show that the proposed method can improve transmission performance significantly.

Strainrange partitioning behavior of the nickel-base superalloys, Rene' 80 and in 100

NASA Technical Reports Server (NTRS)

Halford, G. R.; Nachtigall, A. J.

1978-01-01

A study was made to assess the ability of the method of Strainrange Partitioning (SRP) to both correlate and predict high-temperature, low cycle fatigue lives of nickel base superalloys for gas turbine applications. The partitioned strainrange versus life relationships for uncoated Rene' 80 and cast IN 100 were also determined from the ductility normalized-Strainrange Partitioning equations. These were used to predict the cyclic lives of the baseline tests. The life predictability of the method was verified for cast IN 100 by applying the baseline results to the cyclic life prediction of a series of complex strain cycling tests with multiple hold periods at constant strain. It was concluded that the method of SRP can correlate and predict the cyclic lives of laboratory specimens of the nickel base superalloys evaluated in this program.

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.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering

PubMed Central

Almeida, Fernando R.; Brayner, Angelo; Rodrigues, Joel J. P. C.; Maia, Jose E. Bessa

2017-01-01

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering. To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE). PMID:28590450

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

PubMed

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Target-based calibration method for multifields of view measurement using multiple stereo digital image correlation systems

NASA Astrophysics Data System (ADS)

Dong, Shuai; Yu, Shanshan; Huang, Zheng; Song, Shoutan; Shao, Xinxing; Kang, Xin; He, Xiaoyuan

2017-12-01

Multiple digital image correlation (DIC) systems can enlarge the measurement field without losing effective resolution in the area of interest (AOI). However, the results calculated in substereo DIC systems are located in its local coordinate system in most cases. To stitch the data obtained by each individual system, a data merging algorithm is presented in this paper for global measurement of multiple stereo DIC systems. A set of encoded targets is employed to assist the extrinsic calibration, of which the three-dimensional (3-D) coordinates are reconstructed via digital close range photogrammetry. Combining the 3-D targets with precalibrated intrinsic parameters of all cameras, the extrinsic calibration is significantly simplified. After calculating in substereo DIC systems, all data can be merged into a universal coordinate system based on the extrinsic calibration. Four stereo DIC systems are applied to a four point bending experiment of a steel reinforced concrete beam structure. Results demonstrate high accuracy for the displacement data merging in the overlapping field of views (FOVs) and show feasibility for the distributed FOVs measurement.

A resampling procedure for generating conditioned daily weather sequences

USGS Publications Warehouse

Clark, Martyn P.; Gangopadhyay, Subhrendu; Brandon, David; Werner, Kevin; Hay, Lauren E.; Rajagopalan, Balaji; Yates, David

2004-01-01

A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record “nens” times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Niño 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8°N, 109.9°W), where El Niño and La Niña conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.

Sequential Superresolution Imaging of Multiple Targets Using a Single Fluorophore

PubMed Central

Lidke, Diane S.; Lidke, Keith A.

2015-01-01

Fluorescence superresolution (SR) microscopy, or fluorescence nanoscopy, provides nanometer scale detail of cellular structures and allows for imaging of biological processes at the molecular level. Specific SR imaging methods, such as localization-based imaging, rely on stochastic transitions between on (fluorescent) and off (dark) states of fluorophores. Imaging multiple cellular structures using multi-color imaging is complicated and limited by the differing properties of various organic dyes including their fluorescent state duty cycle, photons per switching event, number of fluorescent cycles before irreversible photobleaching, and overall sensitivity to buffer conditions. In addition, multiple color imaging requires consideration of multiple optical paths or chromatic aberration that can lead to differential aberrations that are important at the nanometer scale. Here, we report a method for sequential labeling and imaging that allows for SR imaging of multiple targets using a single fluorophore with negligible cross-talk between images. Using brightfield image correlation to register and overlay multiple image acquisitions with ~10 nm overlay precision in the x-y imaging plane, we have exploited the optimal properties of AlexaFluor647 for dSTORM to image four distinct cellular proteins. We also visualize the changes in co-localization of the epidermal growth factor (EGF) receptor and clathrin upon EGF addition that are consistent with clathrin-mediated endocytosis. These results are the first to demonstrate sequential SR (s-SR) imaging using direct stochastic reconstruction microscopy (dSTORM), and this method for sequential imaging can be applied to any superresolution technique. PMID:25860558

Development of a multiple immunoaffinity column for simultaneous determination of multiple mycotoxins in feeds using UPLC-MS/MS.

PubMed

Hu, Xiaofeng; Hu, Rui; Zhang, Zhaowei; Li, Peiwu; Zhang, Qi; Wang, Min

2016-09-01

A sensitive and specific immunoaffinity column to clean up and isolate multiple mycotoxins was developed along with a rapid one-step sample preparation procedure for ultra-performance liquid chromatography-tandem mass spectrometry analysis. Monoclonal antibodies against aflatoxin B1, aflatoxin B2, aflatoxin G1, aflatoxin G2, zearalenone, ochratoxin A, sterigmatocystin, and T-2 toxin were coupled to microbeads for mycotoxin purification. We optimized a homogenization and extraction procedure as well as column loading and elution conditions to maximize recoveries from complex feed matrices. This method allowed rapid, simple, and simultaneous determination of mycotoxins in feeds with a single chromatographic run. Detection limits for these toxins ranged from 0.006 to 0.12 ng mL(-1), and quantitation limits ranged from 0.06 to 0.75 ng mL(-1). Concentration curves were linear from 0.12 to 40 μg kg(-1) with correlation coefficients of R (2) > 0.99. Intra-assay and inter-assay comparisons indicated excellent repeatability and reproducibility of the multiple immunoaffinity columns. As a proof of principle, 80 feed samples were tested and several contained multiple mycotoxins. This method is sensitive, rapid, and durable enough for multiple mycotoxin determinations that fulfill European Union and Chinese testing criteria.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Combining matched and unmatched control groups in case-control studies.

PubMed

le Cessie, Saskia; Nagelkerke, Nico; Rosendaal, Frits R; van Stralen, Karlijn J; Pomp, Elisabeth R; van Houwelingen, Hans C

2008-11-15

Multiple control groups in case-control studies are used to control for different sources of confounding. For example, cases can be contrasted with matched controls to adjust for multiple genetic or unknown lifestyle factors and simultaneously contrasted with an unmatched population-based control group. Inclusion of different control groups for a single exposure analysis yields several estimates of the odds ratio, all using only part of the data. Here the authors introduce an easy way to combine odds ratios from several case-control analyses with the same cases. The approach is based upon methods used for meta-analysis but takes into account the fact that the same cases are used and that the estimated odds ratios are therefore correlated. Two ways of estimating this correlation are discussed: sandwich methodology and the bootstrap. Confidence intervals for the pooled estimates and a test for checking whether the odds ratios in the separate case-control studies differ significantly are derived. The performance of the method is studied by simulation and by applying the methods to a large study on risk factors for thrombosis, the MEGA Study (1999-2004), wherein cases with first venous thrombosis were included with a matched control group of partners and an unmatched population-based control group.

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking

PubMed Central

Chargé, Pascal; Bazzi, Oussama; Ding, Yuehua

2018-01-01

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods. PMID:29734797

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking.

PubMed

Mohydeen, Ali; Chargé, Pascal; Wang, Yide; Bazzi, Oussama; Ding, Yuehua

2018-05-06

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit⁻receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit⁻receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit⁻receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.

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.

Development and Validation of a Modified Multiple Errands Test for Adults with Intellectual Disabilities

ERIC Educational Resources Information Center

Steverson, Tom; Adlam, Anna-Lynne R.; Langdon, Peter E.

2017-01-01

Background: The aims of the current study were to adapt a version of the MET for people with intellectual disabilities and assess its ecological and construct validity. Material and Methods: Using a correlational design, 40 participants with intellectual disabilities were invited to complete a battery of neuropsychological assessments and the…

The Effects of Social Capital Elements on Job Satisfaction and Motivation Levels of Teachers

ERIC Educational Resources Information Center

Boydak Özan, Mukadder; Yavuz Özdemir, Tuncay; Yaras, Zübeyde

2017-01-01

The purpose of this study is to examine the effects of social capital elements' on job satisfaction and motivation levels of teachers. The mixed method was used in the study. The quantitative data were analyzed through Correlation and Multiple Regression analyses. An interview form developed by the researchers was used for analyzing the…

Methods to Find the Number of Latent Skills

ERIC Educational Resources Information Center

Beheshti, Behzad; Desmarais, Michel C.; Naceur, Rhouma

2012-01-01

Identifying the skills that determine the success or failure to exercises and question items is a difficult task. Multiple skills may be involved at various degree of importance, and skills may overlap and correlate. In an effort towards the goal of finding the skills behind a set of items, we investigate two techniques to determine the number of…

Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring

ERIC Educational Resources Information Center

de la Torre, Jimmy; Patz, Richard J.

2005-01-01

This article proposes a practical method that capitalizes on the availability of information from multiple tests measuring correlated abilities given in a single test administration. By simultaneously estimating different abilities with the use of a hierarchical Bayesian framework, more precise estimates for each ability dimension are obtained.…

Is Tobacco Use Associated with Academic Failure among Government School Students in Urban India?

ERIC Educational Resources Information Center

Dhavan, Poonam; Stigler, Melissa H.; Perry, Cheryl L.; Arora, Monika; Reddy, K. Srinath

2010-01-01

Background: Not much is known about the academic correlates of tobacco use among students in developing countries. This study investigated associations between multiple forms of tobacco use, psychosocial risk factors, and academic failure among 10- to 16-year-old government school students in Delhi and Chennai, India. Methods: This study was a…

The grey matter correlates of impaired decision-making in multiple sclerosis

PubMed Central

Muhlert, Nils; Sethi, Varun; Cipolotti, Lisa; Haroon, Hamied; Parker, Geoff J M; Yousry, Tarek; Wheeler-Kingshott, Claudia; Miller, David; Ron, Maria; Chard, Declan

2015-01-01

Objective People with multiple sclerosis (MS) have difficulties with decision-making but it is unclear if this is due to changes in impulsivity, risk taking, deliberation or risk adjustment, and how this relates to brain pathology. Methods We assessed these aspects of decision-making in 105 people with MS and 43 healthy controls. We used a novel diffusion MRI method, diffusion orientational complexity (DOC), as an index of grey matter pathology in regions associated with decision-making and also measured grey matter tissue volumes and white matter lesion volumes. Results People with MS showed less adjustment to risk and slower decision-making than controls. Moreover, impaired decision-making correlated with reduced executive function, memory and processing speed. Decision-making impairments were most prevalent in people with secondary progressive MS. They were seen in patients with cognitive impairment and those without cognitive impairment. On diffusion MRI, people with MS showed DOC changes in all regions except the occipital cortex, relative to controls. Risk adjustment correlated with DOC in the hippocampi and deliberation time with DOC in the medial prefrontal, middle frontal gyrus, anterior cingulate and caudate parcellations and with white matter lesion volumes. Conclusions These data clarify the features of decision-making deficits in MS, and provide the first evidence that they relate to grey and white matter abnormalities seen using MRI. PMID:25006208

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

Application of a high-throughput relative chemical stability assay to screen therapeutic protein formulations by assessment of conformational stability and correlation to aggregation propensity.

PubMed

Rizzo, Joseph M; Shi, Shuai; Li, Yunsong; Semple, Andrew; Esposito, Jessica J; Yu, Shenjiang; Richardson, Daisy; Antochshuk, Valentyn; Shameem, Mohammed

2015-05-01

In this study, an automated high-throughput relative chemical stability (RCS) assay was developed in which various therapeutic proteins were assessed to determine stability based on the resistance to denaturation post introduction to a chaotrope titration. Detection mechanisms of both intrinsic fluorescence and near UV circular dichroism (near-UV CD) are demonstrated. Assay robustness was investigated by comparing multiple independent assays and achieving r(2) values >0.95 for curve overlays. The complete reversibility of the assay was demonstrated by intrinsic fluorescence, near-UV CD, and biologic potency. To highlight the method utility, we compared the RCS assay with differential scanning calorimetry and dynamic scanning fluorimetry methodologies. Utilizing C1/2 values obtained from the RCS assay, formulation rank-ordering of 12 different mAb formulations was performed. The prediction of long-term stability on protein aggregation is obtained by demonstrating a good correlation with an r(2) of 0.83 between RCS and empirical aggregation propensity data. RCS promises to be an extremely useful tool to aid in candidate formulation development efforts based on the complete reversibility of the method to allow for multiple assessments without protein loss and the strong correlation between the C1/2 data obtained and accelerated stability under stressed conditions. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Dietary quality varies according to data collection instrument: a comparison between a food frequency questionnaire and 24-hour recall.

PubMed

Rodrigues, Paulo Rogério Melo; de Souza, Rita Adriana Gomes; De Cnop, Mara Lima; Monteiro, Luana Silva; Coura, Camila Pinheiro; Brito, Alessandra Page; Pereira, Rosangela Alves

2016-02-01

The objective of this study was to assess the agreement between the Brazilian Healthy Eating Index - Revised (BHEI-R), estimated by a food frequency questionnaire (FFQ) and multiple 24-hour recalls (24h-R). The Wilcoxon paired test, partial correlations (PC), intraclass correlation coefficient (ICC), and Bland-Altman method were used. The total BHEI-R scores and its components ("total fruits", "whole fruits", "total vegetables", "integral cereals", "saturated fat", "sodium", and "energy intake derived from solid fat, added sugar, and alcoholic beverages") were statistically different, with the ICC and PC indicating poor concordance and correlation. The mean concordance estimated for the total BHEI-R and its components varied from 68% for "integral cereals" to 147% for "whole fruits". The suitable concordance limits were violated for most of the components of the BHEI-R. Poor concordance was observed between the BHEI-R estimated by the FFQ and by multiple 24h-R, which indicated a strong reliability of the BHEI-R on the instrument used to collect information on food consumption.

Estimating False Discovery Proportion Under Arbitrary Covariance Dependence*

PubMed Central

Fan, Jianqing; Han, Xu; Gu, Weijie

2012-01-01

Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are performed simultaneously to find if any SNPs are associated with some traits and those tests are correlated. When test statistics are correlated, false discovery control becomes very challenging under arbitrary dependence. In the current paper, we propose a novel method based on principal factor approximation, which successfully subtracts the common dependence and weakens significantly the correlation structure, to deal with an arbitrary dependence structure. We derive an approximate expression for false discovery proportion (FDP) in large scale multiple testing when a common threshold is used and provide a consistent estimate of realized FDP. This result has important applications in controlling FDR and FDP. Our estimate of realized FDP compares favorably with Efron (2007)’s approach, as demonstrated in the simulated examples. Our approach is further illustrated by some real data applications. We also propose a dependence-adjusted procedure, which is more powerful than the fixed threshold procedure. PMID:24729644

Region-Based Prediction for Image Compression in the Cloud.

PubMed

Begaint, Jean; Thoreau, Dominique; Guillotel, Philippe; Guillemot, Christine

2018-04-01

Thanks to the increasing number of images stored in the cloud, external image similarities can be leveraged to efficiently compress images by exploiting inter-images correlations. In this paper, we propose a novel image prediction scheme for cloud storage. Unlike current state-of-the-art methods, we use a semi-local approach to exploit inter-image correlation. The reference image is first segmented into multiple planar regions determined from matched local features and super-pixels. The geometric and photometric disparities between the matched regions of the reference image and the current image are then compensated. Finally, multiple references are generated from the estimated compensation models and organized in a pseudo-sequence to differentially encode the input image using classical video coding tools. Experimental results demonstrate that the proposed approach yields significant rate-distortion performance improvements compared with the current image inter-coding solutions such as high efficiency video coding.

Quantification of right ventricular volumes and function by real time three-dimensional echocardiographic longitudinal axial plane method: validation in the clinical setting.

PubMed

Endo, Yuka; Maddukuri, Prasad V; Vieira, Marcelo L C; Pandian, Natesa G; Patel, Ayan R

2006-11-01

Measurement of right ventricular (RV) volumes and right ventricular ejection fraction (RVEF) by three-dimensional echocardiographic (3DE) short-axis disc summation method has been validated in multiple studies. However, in some patients, short-axis images are of insufficient quality for accurate tracing of the RV endocardial border. This study examined the accuracy of long-axis analysis in multiple planes (longitudinal axial plane method) for assessment of RV volumes and RVEF. 3DE images were analyzed in 40 subjects with a broad range of RV function. RV end-diastolic (RVEDV) and end-systolic volumes (RVESV) and RVEF were calculated by both short-axis disc summation method and longitudinal axial plane method. Excellent correlation was obtained between the two methods for RVEDV, RVESV, and RVEF (r = 0.99, 0.99, 0.94, respectively; P < 0.0001 for all comparisons). 3DE longitudinal-axis analysis is a promising technique for the evaluation of RV function, and may provide an alternative method of assessment in patients with suboptimal short-axis images.

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

NASA Astrophysics Data System (ADS)

O'Neill, George C.; Barratt, Eleanor L.; Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Brookes, Matthew J.

2015-11-01

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5 mm) spatial resolution and excellent (~1 ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including (i) projection of MEG data into source space, (ii) removing confounds introduced by the MEG inverse problem and (iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease.

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

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar

2012-06-01

Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.

Cosmological perturbation theory using the FFTLog: formalism and connection to QFT loop integrals

NASA Astrophysics Data System (ADS)

Simonović, Marko; Baldauf, Tobias; Zaldarriaga, Matias; Carrasco, John Joseph; Kollmeier, Juna A.

2018-04-01

We present a new method for calculating loops in cosmological perturbation theory. This method is based on approximating a ΛCDM-like cosmology as a finite sum of complex power-law universes. The decomposition is naturally achieved using an FFTLog algorithm. For power-law cosmologies, all loop integrals are formally equivalent to loop integrals of massless quantum field theory. These integrals have analytic solutions in terms of generalized hypergeometric functions. We provide explicit formulae for the one-loop and the two-loop power spectrum and the one-loop bispectrum. A chief advantage of our approach is that the difficult part of the calculation is cosmology independent, need be done only once, and can be recycled for any relevant predictions. Evaluation of standard loop diagrams then boils down to a simple matrix multiplication. We demonstrate the promise of this method for applications to higher multiplicity/loop correlation functions.

Random matrices and condensation into multiple states

NASA Astrophysics Data System (ADS)

Sadeghi, Sina; Engel, Andreas

2018-03-01

In the present work, we employ methods from statistical mechanics of disordered systems to investigate static properties of condensation into multiple states in a general framework. We aim at showing how typical properties of random interaction matrices play a vital role in manifesting the statistics of condensate states. In particular, an analytical expression for the fraction of condensate states in the thermodynamic limit is provided that confirms the result of the mean number of coexisting species in a random tournament game. We also study the interplay between the condensation problem and zero-sum games with correlated random payoff matrices.

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

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.

Comparing solutions to the expectancy-value muddle in the theory of planned behaviour.

PubMed

O' Sullivan, B; McGee, H; Keegan, O

2008-11-01

The authors of the Theories of Reasoned Action (TRA) and Planned Behaviour (TPB) recommended a method for statistically analysing the relationship between the indirect belief-based measures and the direct measures of attitude, subjective norm, and perceived behavioural control (PBC). However, there is a growing awareness that this yields statistically uninterpretable results. This study's objective was to compare two solutions to what has been called the 'expectancy-value muddle'. These solutions were (i) optimal scoring of modal beliefs and (ii) individual beliefs without multiplicative composites. Cross-sectional data were collected by telephone interview. Participants were 110 first-degree relatives (FDRs) of patients diagnosed with colorectal cancer (CRC), who were offered CRC screening in the study hospital (83% response rate). Participants were asked to rate the TPB constructs in relation to attending for CRC screening. There was no significant difference in the correlation between behavioural beliefs and attitude for rescaled modal and individual beliefs. This was also the case for control beliefs and PBC. By contrast, there was a large correlation between rescaled modal normative beliefs and subjective norm, whereas individual normative beliefs did not correlate with subjective norm. Using individual beliefs without multiplicative composites allows for a fairly unproblematic interpretation of the relationship between the indirect and direct TPB constructs (French & Hankins, 2003). Therefore, it is recommended that future studies consider using individual measures of behavioural and control beliefs without multiplicative composites and examine a different way of measuring individual normative beliefs without multiplicative composites to that used in this study.

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

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

Marshall, William BJ J; Rearden, Bradley T

The validation of neutron transport methods used in nuclear criticality safety analyses is required by consensus American National Standards Institute/American Nuclear Society (ANSI/ANS) standards. In the last decade, there has been an increased interest in correlations among critical experiments used in validation that have shared physical attributes and which impact the independence of each measurement. The statistical methods included in many of the frequently cited guidance documents on performing validation calculations incorporate the assumption that all individual measurements are independent, so little guidance is available to practitioners on the topic. Typical guidance includes recommendations to select experiments from multiple facilitiesmore » and experiment series in an attempt to minimize the impact of correlations or common-cause errors in experiments. Recent efforts have been made both to determine the magnitude of such correlations between experiments and to develop and apply methods for adjusting the bias and bias uncertainty to account for the correlations. This paper describes recent work performed at Oak Ridge National Laboratory using the Sampler sequence from the SCALE code system to develop experimental correlations using a Monte Carlo sampling technique. Sampler will be available for the first time with the release of SCALE 6.2, and a brief introduction to the methods used to calculate experiment correlations within this new sequence is presented in this paper. Techniques to utilize these correlations in the establishment of upper subcritical limits are the subject of a companion paper and will not be discussed here. Example experimental uncertainties and correlation coefficients are presented for a variety of low-enriched uranium water-moderated lattice experiments selected for use in a benchmark exercise by the Working Party on Nuclear Criticality Safety Subgroup on Uncertainty Analysis in Criticality Safety Analyses. The results include studies on the effect of fuel rod pitch on the correlations, and some observations are also made regarding difficulties in determining experimental correlations using the Monte Carlo sampling technique.« less

Enhance-Synergism and Suppression Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, W. Michael

2004-01-01

Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

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.

Correlation of Simulation Examination to Written Test Scores for Advanced Cardiac Life Support Testing: Prospective Cohort Study.

PubMed

Strom, Suzanne L; Anderson, Craig L; Yang, Luanna; Canales, Cecilia; Amin, Alpesh; Lotfipour, Shahram; McCoy, C Eric; Osborn, Megan Boysen; Langdorf, Mark I

2015-11-01

Traditional Advanced Cardiac Life Support (ACLS) courses are evaluated using written multiple-choice tests. High-fidelity simulation is a widely used adjunct to didactic content, and has been used in many specialties as a training resource as well as an evaluative tool. There are no data to our knowledge that compare simulation examination scores with written test scores for ACLS courses. To compare and correlate a novel high-fidelity simulation-based evaluation with traditional written testing for senior medical students in an ACLS course. We performed a prospective cohort study to determine the correlation between simulation-based evaluation and traditional written testing in a medical school simulation center. Students were tested on a standard acute coronary syndrome/ventricular fibrillation cardiac arrest scenario. Our primary outcome measure was correlation of exam results for 19 volunteer fourth-year medical students after a 32-hour ACLS-based Resuscitation Boot Camp course. Our secondary outcome was comparison of simulation-based vs. written outcome scores. The composite average score on the written evaluation was substantially higher (93.6%) than the simulation performance score (81.3%, absolute difference 12.3%, 95% CI [10.6-14.0%], p<0.00005). We found a statistically significant moderate correlation between simulation scenario test performance and traditional written testing (Pearson r=0.48, p=0.04), validating the new evaluation method. Simulation-based ACLS evaluation methods correlate with traditional written testing and demonstrate resuscitation knowledge and skills. Simulation may be a more discriminating and challenging testing method, as students scored higher on written evaluation methods compared to simulation.

Dynamical properties of a tumor growth system in the presence of immunization and colored cross-correlated noises

NASA Astrophysics Data System (ADS)

Jia, Zheng-Lin; Mei, Dong-Cheng

2010-05-01

We investigate the effects of the noise parameters and immunization strength β on the dynamical properties of a tumor growth system with both immunization and colored cross-correlated noises. The analytical expressions for the associated relaxation time TC and the normalized correlation function C(s) are derived by means of the projection operator method. The results indicate that: (i) TC as a function of the multiplicative noise intensity α shows resonance-like behavior, i.e. the curves of TC versus α exhibit a single-peak structure and its peak position changes with increasing correlation strength between noises λ, the autocorrelation time of multiplicative noise τ1, the autocorrelation time of additive noise τ2 and the cross-correlation time τ3. This behavior can be understood in terms of the noise-enhanced stability effect and the influence of the memory effects on it. (ii) The increasing λ, τ1, τ2 and the additive noise intensity D slow down the fluctuation decay of the tumor population, whereas the increasing τ3 and β speed it up. (iii) C(s) increases as λ, τ1, τ2 and β increase, while it decreases with τ3 increasing. Our study shows that the effects of some noise parameters on tumor growth can be modified due to the presence of the immunization effect.

Identifying intervals of temporally invariant field-aligned currents from Swarm: Assessing the validity of single-spacecraft methods

NASA Astrophysics Data System (ADS)

Forsyth, C.; Rae, I. J.; Mann, I. R.; Pakhotin, I. P.

2017-03-01

Field-aligned currents (FACs) are a fundamental component of coupled solar wind-magnetosphere-ionosphere. By assuming that FACs can be approximated by stationary infinite current sheets that do not change on the spacecraft crossing time, single-spacecraft magnetic field measurements can be used to estimate the currents flowing in space. By combining data from multiple spacecraft on similar orbits, these stationarity assumptions can be tested. In this technical report, we present a new technique that combines cross correlation and linear fitting of multiple spacecraft measurements to determine the reliability of the FAC estimates. We show that this technique can identify those intervals in which the currents estimated from single-spacecraft techniques are both well correlated and have similar amplitudes, thus meeting the spatial and temporal stationarity requirements. Using data from European Space Agency's Swarm mission from 2014 to 2015, we show that larger-scale currents (>450 km) are well correlated and have a one-to-one fit up to 50% of the time, whereas small-scale (<50 km) currents show similar amplitudes only 1% of the time despite there being a good correlation 18% of the time. It is thus imperative to examine both the correlation and amplitude of the calculated FACs in order to assess both the validity of the underlying assumptions and hence ultimately the reliability of such single-spacecraft FAC estimates.

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.

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.

Temporal evolution of the Green's function reconstruction in the seismic coda

NASA Astrophysics Data System (ADS)

Clerc, V.; Roux, P.; Campillo, M.

2013-12-01

In presence of multiple scattering, the wavefield evolves towards an equipartitioned state, equivalent to ambient noise. CAMPILLO and PAUL (2003) reconstructed the surface wave part of the Green's function between three pairs of stations in Mexico. The data indicate that the time asymmetry between causal and acausal part of the Green's function is less pronounced when the correlation is performed in the later windows of the coda. These results on the correlation of diffuse waves provide another perspective on the reconstruction of Green function which is independent of the source distribution and which suggests that if the time of observation is long enough, a single source could be sufficient. The paper by ROUX et al. (2005) provides a theoretical frame for the reconstruction of the Green's function in a homogeneous middle. In a multiple scattering medium with a single source, scatterers behave as secondary sources according to the Huygens principle. Coda waves are relevant to multiple scattering, a regime which can be approximated by diffusion for long lapse times. We express the temporal evolution of the correlation function between two receivers as a function of the secondary sources. We are able to predict the effect of the persistence of the net flux of energy observed by CAMPILLO and PAUL (2003) in numerical simulations. This method is also effective in order to retrieve the scattering mean free path. We perform a partial reconstruction of the Green's function in a strongly scattering medium in numerical simulations. The prediction of the flux asymmetry allows defining the parts of the coda providing the same information as ambient noise cross correlation.

Accurate Simulation and Detection of Coevolution Signals in Multiple Sequence Alignments

PubMed Central

Ackerman, Sharon H.; Tillier, Elisabeth R.; Gatti, Domenico L.

2012-01-01

Background While the conserved positions of a multiple sequence alignment (MSA) are clearly of interest, non-conserved positions can also be important because, for example, destabilizing effects at one position can be compensated by stabilizing effects at another position. Different methods have been developed to recognize the evolutionary relationship between amino acid sites, and to disentangle functional/structural dependencies from historical/phylogenetic ones. Methodology/Principal Findings We have used two complementary approaches to test the efficacy of these methods. In the first approach, we have used a new program, MSAvolve, for the in silico evolution of MSAs, which records a detailed history of all covarying positions, and builds a global coevolution matrix as the accumulated sum of individual matrices for the positions forced to co-vary, the recombinant coevolution, and the stochastic coevolution. We have simulated over 1600 MSAs for 8 protein families, which reflect sequences of different sizes and proteins with widely different functions. The calculated coevolution matrices were compared with the coevolution matrices obtained for the same evolved MSAs with different coevolution detection methods. In a second approach we have evaluated the capacity of the different methods to predict close contacts in the representative X-ray structures of an additional 150 protein families using only experimental MSAs. Conclusions/Significance Methods based on the identification of global correlations between pairs were found to be generally superior to methods based only on local correlations in their capacity to identify coevolving residues using either simulated or experimental MSAs. However, the significant variability in the performance of different methods with different proteins suggests that the simulation of MSAs that replicate the statistical properties of the experimental MSA can be a valuable tool to identify the coevolution detection method that is most effective in each case. PMID:23091608

Rapid Chemometric Filtering of Spectral Data

NASA Technical Reports Server (NTRS)

Beaman, Gregory; Pelletier, Michael; Seshadri, Suresh

2004-01-01

A method of rapid, programmable filtering of spectral transmittance, reflectance, or fluorescence data to measure the concentrations of chemical species has been proposed. By programmable is meant that a variety of spectral analyses can readily be performed and modified in software, firmware, and/or electronic hardware, without need to change optical filters or other optical hardware of the associated spectrometers. The method is intended to enable real-time identification of single or multiple target chemical species in applications that involve high-throughput screening of multiple samples. Examples of such applications include (but are not limited to) combinatorial chemistry, flow cytometry, bead assays, testing drugs, remote sensing, and identification of targets. The basic concept of the proposed method is to perform real-time crosscorrelations of a measured spectrum with one or more analytical function(s) of wavelength that could be, for example, the known spectra of target species. Assuming that measured spectral intensities are proportional to concentrations of target species plus background spectral intensities, then after subtraction of background levels, it should be possible to determine target species concentrations from cross-correlation values. Of course, the problem of determining the concentrations is more complex when spectra of different species overlap, but the problem can be solved by use of multiple analytical functions in combination with computational techniques that have been developed previously for analyses of this type. The method is applicable to the design and operation of a spectrometer in which spectrally dispersed light is measured by means of an active-pixel sensor (APS) array. The row or column dimension of such an array is generally chosen to be aligned along the spectral-dispersion dimension, so that each pixel intercepts light in a narrow spectral band centered on a wavelength that is a known function of the pixel position. The proposed method admits of two hardware implementations for computing cross-correlations in real time.

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

PubMed Central

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-01-01

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. PMID:27420066

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms.

PubMed

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-07-12

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

DISCO: Distance and Spectrum Correlation Optimization Alignment for Two Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-based Metabolomics

PubMed Central

Wang, Bing; Fang, Aiqin; Heim, John; Bogdanov, Bogdan; Pugh, Scott; Libardoni, Mark; Zhang, Xiang

2010-01-01

A novel peak alignment algorithm using a distance and spectrum correlation optimization (DISCO) method has been developed for two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) based metabolomics. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson’s correlation coefficient. A local linear fitting method is employed in the original two-dimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity. The effectiveness of the DISCO algorithm is demonstrated using data sets acquired under different experiment conditions and a spiked-in experiment. PMID:20476746

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…

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.

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.

Separating Spike Count Correlation from Firing Rate Correlation

PubMed Central

Vinci, Giuseppe; Ventura, Valérie; Smith, Matthew A.; Kass, Robert E.

2016-01-01

Populations of cortical neurons exhibit shared fluctuations in spiking activity over time. When measured for a pair of neurons over multiple repetitions of an identical stimulus, this phenomenon emerges as correlated trial-to-trial response variability via spike count correlation (SCC). However, spike counts can be viewed as noisy versions of firing rates, which can vary from trial to trial. From this perspective, the SCC for a pair of neurons becomes a noisy version of the corresponding firing-rate correlation (FRC). Furthermore, the magnitude of the SCC is generally smaller than that of the FRC, and is likely to be less sensitive to experimental manipulation. We provide statistical methods for disambiguating time-averaged drive from within-trial noise, thereby separating FRC from SCC. We study these methods to document their reliability, and we apply them to neurons recorded in vivo from area V4, in an alert animal. We show how the various effects we describe are reflected in the data: within-trial effects are largely negligible, while attenuation due to trial-to-trial variation dominates, and frequently produces comparisons in SCC that, because of noise, do not accurately reflect those based on the underlying FRC. PMID:26942746

Multiple window spatial registration error of a gamma camera: 133Ba point source as a replacement of the NEMA procedure.

PubMed

Bergmann, Helmar; Minear, Gregory; Raith, Maria; Schaffarich, Peter M

2008-12-09

The accuracy of multiple window spatial resolution characterises the performance of a gamma camera for dual isotope imaging. In the present study we investigate an alternative method to the standard NEMA procedure for measuring this performance parameter. A long-lived 133Ba point source with gamma energies close to 67Ga and a single bore lead collimator were used to measure the multiple window spatial registration error. Calculation of the positions of the point source in the images used the NEMA algorithm. The results were validated against the values obtained by the standard NEMA procedure which uses a liquid 67Ga source with collimation. Of the source-collimator configurations under investigation an optimum collimator geometry, consisting of a 5 mm thick lead disk with a diameter of 46 mm and a 5 mm central bore, was selected. The multiple window spatial registration errors obtained by the 133Ba method showed excellent reproducibility (standard deviation < 0.07 mm). The values were compared with the results from the NEMA procedure obtained at the same locations and showed small differences with a correlation coefficient of 0.51 (p < 0.05). In addition, the 133Ba point source method proved to be much easier to use. A Bland-Altman analysis showed that the 133Ba and the 67Ga Method can be used interchangeably. The 133Ba point source method measures the multiple window spatial registration error with essentially the same accuracy as the NEMA-recommended procedure, but is easier and safer to use and has the potential to replace the current standard procedure.

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

Online blind source separation using incremental nonnegative matrix factorization with volume constraint.

PubMed

Zhou, Guoxu; Yang, Zuyuan; Xie, Shengli; Yang, Jun-Mei

2011-04-01

Online blind source separation (BSS) is proposed to overcome the high computational cost problem, which limits the practical applications of traditional batch BSS algorithms. However, the existing online BSS methods are mainly used to separate independent or uncorrelated sources. Recently, nonnegative matrix factorization (NMF) shows great potential to separate the correlative sources, where some constraints are often imposed to overcome the non-uniqueness of the factorization. In this paper, an incremental NMF with volume constraint is derived and utilized for solving online BSS. The volume constraint to the mixing matrix enhances the identifiability of the sources, while the incremental learning mode reduces the computational cost. The proposed method takes advantage of the natural gradient based multiplication updating rule, and it performs especially well in the recovery of dependent sources. Simulations in BSS for dual-energy X-ray images, online encrypted speech signals, and high correlative face images show the validity of the proposed method.

Neutron-fragment and Neutron-neutron Correlations in Low-energy Fission

NASA Astrophysics Data System (ADS)

Lestone, J. P.

2016-01-01

A computational method has been developed to simulate neutron emission from thermal-neutron induced fission of 235U and from spontaneous fission of 252Cf. Measured pre-emission mass-yield curves, average total kinetic energies and their variances, both as functions of mass split, are used to obtain a representation of the distribution of fragment velocities. Measured average neutron multiplicities as a function of mass split and their dependence on total kinetic energy are used. Simulations can be made to reproduce measured factorial moments of neutron-multiplicity distributions with only minor empirical adjustments to some experimental inputs. The neutron-emission spectra in the rest-frame of the fragments are highly constrained by ENDF/B-VII.1 prompt-fission neutron-spectra evaluations. The n-f correlation measurements of Vorobyev et al. (2010) are consistent with predictions where all neutrons are assumed to be evaporated isotropically from the rest frame of fully accelerated fragments. Measured n-f and n-n correlations of others are a little weaker than the predictions presented here. These weaker correlations could be used to infer a weak scission-neutron source. However, the effect of neutron scattering on the experimental results must be studied in detail before moving away from a null hypothesis that all neutrons are evaporated from the fragments.

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

PubMed

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

2010-07-01

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

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

Unusual interactions above 100 TeV: A review of cosmic ray experiments with emulsion chambers

NASA Technical Reports Server (NTRS)

Yodh, D. B.

1977-01-01

A method is given for analyzing the space correlated collection of jets (gamma ray families) with energies greater than 100 TeV in Pb or Fe absorber sampled by photosensitive layers in an emulsion chamber. Events analyzed indicate large multiplicities of particles in the primary hadron-air interaction, and a marked absence of neutral pions.

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.

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

A Multiple-Label Guided Clustering Algorithm for Historical Document Dating and Localization.

PubMed

He, Sheng; Samara, Petros; Burgers, Jan; Schomaker, Lambert

2016-11-01

It is of essential importance for historians to know the date and place of origin of the documents they study. It would be a huge advancement for historical scholars if it would be possible to automatically estimate the geographical and temporal provenance of a handwritten document by inferring them from the handwriting style of such a document. We propose a multiple-label guided clustering algorithm to discover the correlations between the concrete low-level visual elements in historical documents and abstract labels, such as date and location. First, a novel descriptor, called histogram of orientations of handwritten strokes, is proposed to extract and describe the visual elements, which is built on a scale-invariant polar-feature space. In addition, the multi-label self-organizing map (MLSOM) is proposed to discover the correlations between the low-level visual elements and their labels in a single framework. Our proposed MLSOM can be used to predict the labels directly. Moreover, the MLSOM can also be considered as a pre-structured clustering method to build a codebook, which contains more discriminative information on date and geography. The experimental results on the medieval paleographic scale data set demonstrate that our method achieves state-of-the-art results.

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…

Measures of health sciences journal use: a comparison of vendor, link-resolver, and local citation statistics*

PubMed Central

De Groote, Sandra L.; Blecic, Deborah D.; Martin, Kristin

2013-01-01

Objective: Libraries require efficient and reliable methods to assess journal use. Vendors provide complete counts of articles retrieved from their platforms. However, if a journal is available on multiple platforms, several sets of statistics must be merged. Link-resolver reports merge data from all platforms into one report but only record partial use because users can access library subscriptions from other paths. Citation data are limited to publication use. Vendor, link-resolver, and local citation data were examined to determine correlation. Because link-resolver statistics are easy to obtain, the study library especially wanted to know if they correlate highly with the other measures. Methods: Vendor, link-resolver, and local citation statistics for the study institution were gathered for health sciences journals. Spearman rank-order correlation coefficients were calculated. Results: There was a high positive correlation between all three data sets, with vendor data commonly showing the highest use. However, a small percentage of titles showed anomalous results. Discussion and Conclusions: Link-resolver data correlate well with vendor and citation data, but due to anomalies, low link-resolver data would best be used to suggest titles for further evaluation using vendor data. Citation data may not be needed as it correlates highly with other measures. PMID:23646026

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.

The use of multiple imputation for the accurate measurements of individual feed intake by electronic feeders.

PubMed

Jiao, S; Tiezzi, F; Huang, Y; Gray, K A; Maltecca, C

2016-02-01

Obtaining accurate individual feed intake records is the key first step in achieving genetic progress toward more efficient nutrient utilization in pigs. Feed intake records collected by electronic feeding systems contain errors (erroneous and abnormal values exceeding certain cutoff criteria), which are due to feeder malfunction or animal-feeder interaction. In this study, we examined the use of a novel data-editing strategy involving multiple imputation to minimize the impact of errors and missing values on the quality of feed intake data collected by an electronic feeding system. Accuracy of feed intake data adjustment obtained from the conventional linear mixed model (LMM) approach was compared with 2 alternative implementations of multiple imputation by chained equation, denoted as MI (multiple imputation) and MICE (multiple imputation by chained equation). The 3 methods were compared under 3 scenarios, where 5, 10, and 20% feed intake error rates were simulated. Each of the scenarios was replicated 5 times. Accuracy of the alternative error adjustment was measured as the correlation between the true daily feed intake (DFI; daily feed intake in the testing period) or true ADFI (the mean DFI across testing period) and the adjusted DFI or adjusted ADFI. In the editing process, error cutoff criteria are used to define if a feed intake visit contains errors. To investigate the possibility that the error cutoff criteria may affect any of the 3 methods, the simulation was repeated with 2 alternative error cutoff values. Multiple imputation methods outperformed the LMM approach in all scenarios with mean accuracies of 96.7, 93.5, and 90.2% obtained with MI and 96.8, 94.4, and 90.1% obtained with MICE compared with 91.0, 82.6, and 68.7% using LMM for DFI. Similar results were obtained for ADFI. Furthermore, multiple imputation methods consistently performed better than LMM regardless of the cutoff criteria applied to define errors. In conclusion, multiple imputation is proposed as a more accurate and flexible method for error adjustments in feed intake data collected by electronic feeders.

Stability conditions for exact-exchange Kohn-Sham methods and their relation to correlation energies from the adiabatic-connection fluctuation-dissipation theorem.

PubMed

Bleiziffer, Patrick; Schmidtel, Daniel; Görling, Andreas

2014-11-28

The occurrence of instabilities, in particular singlet-triplet and singlet-singlet instabilities, in the exact-exchange (EXX) Kohn-Sham method is investigated. Hessian matrices of the EXX electronic energy with respect to the expansion coefficients of the EXX effective Kohn-Sham potential in an auxiliary basis set are derived. The eigenvalues of these Hessian matrices determine whether or not instabilities are present. Similar as in the corresponding Hartree-Fock case instabilities in the EXX method are related to symmetry breaking of the Hamiltonian operator for the EXX orbitals. In the EXX methods symmetry breaking can easily be visualized by displaying the local multiplicative exchange potential. Examples (N2, O2, and the polyyne C10H2) for instabilities and symmetry breaking are discussed. The relation of the stability conditions for EXX methods to approaches calculating the Kohn-Sham correlation energy via the adiabatic-connection fluctuation-dissipation (ACFD) theorem is discussed. The existence or nonexistence of singlet-singlet instabilities in an EXX calculation is shown to indicate whether or not the frequency-integration in the evaluation of the correlation energy is singular in the EXX-ACFD method. This method calculates the Kohn-Sham correlation energy through the ACFD theorem theorem employing besides the Coulomb kernel also the full frequency-dependent exchange kernel and yields highly accurate electronic energies. For the case of singular frequency-integrands in the EXX-ACFD method a regularization is suggested. Finally, we present examples of molecular systems for which the self-consistent field procedure of the EXX as well as the Hartree-Fock method can converge to more than one local minimum depending on the initial conditions.

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Optical multiple-image authentication based on cascaded phase filtering structure

NASA Astrophysics Data System (ADS)

Wang, Q.; Alfalou, A.; Brosseau, C.

2016-10-01

In this study, we report on the recent developments of optical image authentication algorithms. Compared with conventional optical encryption, optical image authentication achieves more security strength because such methods do not need to recover information of plaintext totally during the decryption period. Several recently proposed authentication systems are briefly introduced. We also propose a novel multiple-image authentication system, where multiple original images are encoded into a photon-limited encoded image by using a triple-plane based phase retrieval algorithm and photon counting imaging (PCI) technique. One can only recover a noise-like image using correct keys. To check authority of multiple images, a nonlinear fractional correlation is employed to recognize the original information hidden in the decrypted results. The proposal can be implemented optically using a cascaded phase filtering configuration. Computer simulation results are presented to evaluate the performance of this proposal and its effectiveness.

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

USArray Receiver Function Imaging of Multiple-Layer Crustal Structure of the Contiguous United States

NASA Astrophysics Data System (ADS)

Ma, X.; Lowry, A. R.; Ravat, D.

2014-12-01

Thickness andseismic velocity of crustal layers are useful for understanding the history and evolution of continental lithosphere. Lowry and Pérez-Gussinyé (2011) observed that low bulk crustal seismic velocity ratio, Vp/Vs, strongly correlates with high geothermal gradient and active deformation, indicating quartz (to which Vp/Vs is most sensitive) plays a role in these processes. The lower crust (where ductile flow occurs which might explain the relationship) is commonly thought to be quartz-poor. However, layering of the crust may represent changes in either lithology or the phase of quartz. Laboratory strain-stress experiments on quartz indicate that near the a- to b-quartz phase transition, both Vp and Vp/Vs initially drop dramatically but then increase relative to the a-quartz regime because Young's modulus initially decreases by 30% before increasing by a net ~20%. Shear modulus varies only ~3% across the transition. Crustal structure is commonly represented by an upper, mid- and lower layer (e.g., Crust1.0) and conceptualized as primarily reflecting a change to more mafic lithology at greater depth, but estimates of Moho temperature indicate a quartz phase transition should be present in much of the western and central U.S. We have imaged multiple layering of the contiguous U.S. by applying a new cross-correlation and stacking method to USArray receiver functions. Synthetic models of a multiple layer crust indicate 'splitting' of converted-phase arrivals would be expected if a quartz phase transition were responsible. Preliminary imaging using cross-correlation of observed receiver functions with multiple layer synthetics demonstrates a marked improvement in correlation coefficients relative to a single-layer crust. In this presentation we will examine observational evidence for possible a- to b- phase transition layering (indicating quartz at depth) and compare with depths predicted for the quartz phase transition based on Pn-derived Moho temperatures and estimates of magnetic Curie depths.

The use of a combination of instrumental methods to assess change in sensory crispness during storage of a "Honeycrisp" apple breeding family.

PubMed

Chang, Hsueh-Yuan; Vickers, Zata M; Tong, Cindy B S

2018-04-01

Loss of crispness in apple fruit during storage reduces the fruit's fresh sensation and consumer acceptance. Apple varieties that maintain crispness thus have higher potential for longer-term consumer appeal. To efficiently phenotype crispness, several instrumental methods have been tested, but variable results were obtained when different apple varieties were assayed. To extend these studies, we assessed the extent to which instrumental measurements correlate to and predict sensory crispness, with a focus on crispness maintenance. We used an apple breeding family derived from a cross between "Honeycrisp" and "MN1764," which segregates for crispness maintenance. Three types of instrumental measurements (puncture, snapping, and mechanical-acoustic tests) and sensory evaluation were performed on fruit at harvest and after 8 weeks of cold storage. Overall, 20 genotypes from the family and the 2 parents were characterized by 19 force and acoustic measures. In general, crispness was more related to force than to acoustic measures. Force linear distance and maximum force as measured by the mechanical-acoustic test were best correlated with sensory crispness and change in crispness, respectively. The correlations varied by apple genotype. The best multiple linear regression model to predict change in sensory crispness between harvest and storage of fruit of this breeding family incorporated both force and acoustic measures. This work compared the abilities of instrumental tests to predict sensory crispness maintenance of apple fruit. The use of an instrumental method that is highly correlated to sensory crispness evaluation can enhance the efficiency and reduce the cost of measuring crispness for breeding purposes. This study showed that sensory crispness and change in crispness after storage of an apple breeding family were reliably predicted with a combination of instrumental measurements and multiple variable analyses. The strategy potentially can be applied to other apple varieties for more accurate interpretation of crispness maintenance measured instrumentally. © 2018 Wiley Periodicals, Inc.

Safety training priorities

NASA Astrophysics Data System (ADS)

Thompson, N. A.; Ruck, H. W.

1984-04-01

The Air Force is interested in identifying potentially hazardous tasks and prevention of accidents. This effort proposes four methods for determining safety training priorities for job tasks in three enlisted specialties. These methods can be used to design training aimed at avoiding loss of people, time, materials, and money associated with on-the-job accidents. Job tasks performed by airmen were measured using task and job factor ratings. Combining accident reports and job inventories, subject-matter experts identified tasks associated with accidents over a 3-year period. Applying correlational, multiple regression, and cost-benefit analysis, four methods were developed for ordering hazardous tasks to determine safety training priorities.

Electronic Structures of Anti-Ferromagnetic Tetraradicals: Ab Initio and Semi-Empirical Studies.

PubMed

Zhang, Dawei; Liu, Chungen

2016-04-12

The energy relationships and electronic structures of the lowest-lying spin states in several anti-ferromagnetic tetraradical model systems are studied with high-level ab initio and semi-empirical methods. The Full-CI method (FCI), the complete active space second-order perturbation theory (CASPT2), and the n-electron valence state perturbation theory (NEVPT2) are employed to obtain reference results. By comparing the energy relationships predicted from the Heisenberg and Hubbard models with ab initio benchmarks, the accuracy of the widely used Heisenberg model for anti-ferromagnetic spin-coupling in low-spin polyradicals is cautiously tested in this work. It is found that the strength of electron correlation (|U/t|) concerning anti-ferromagnetically coupled radical centers could range widely from strong to moderate correlation regimes and could become another degree of freedom besides the spin multiplicity. Accordingly, the Heisenberg-type model works well in the regime of strong correlation, which reproduces well the energy relationships along with the wave functions of all the spin states. In moderately spin-correlated tetraradicals, the results of the prototype Heisenberg model deviate severely from those of multi-reference electron correlation ab initio methods, while the extended Heisenberg model, containing four-body terms, can introduce reasonable corrections and maintains its accuracy in this condition. In the weak correlation regime, both the prototype Heisenberg model and its extended forms containing higher-order correction terms will encounter difficulties. Meanwhile, the Hubbard model shows balanced accuracy from strong to weak correlation cases and can reproduce qualitatively correct electronic structures, which makes it more suitable for the study of anti-ferromagnetic coupling in polyradical systems.

One lens optical correlation: application to face recognition.

PubMed

Jridi, Maher; Napoléon, Thibault; Alfalou, Ayman

2018-03-20

Despite its extensive use, the traditional 4f Vander Lugt Correlator optical setup can be further simplified. We propose a lightweight correlation scheme where the decision is taken in the Fourier plane. For this purpose, the Fourier plane is adapted and used as a decision plane. Then, the offline phase and the decision metric are re-examined in order to keep a reasonable recognition rate. The benefits of the proposed approach are numerous: (1) it overcomes the constraints related to the use of a second lens; (2) the optical correlation setup is simplified; (3) the multiplication with the correlation filter can be done digitally, which offers a higher adaptability according to the application. Moreover, the digital counterpart of the correlation scheme is lightened since with the proposed scheme we get rid of the inverse Fourier transform (IFT) calculation (i.e., decision directly in the Fourier domain without resorting to IFT). To assess the performance of the proposed approach, an insight into digital hardware resources saving is provided. The proposed method involves nearly 100 times fewer arithmetic operators. Moreover, from experimental results in the context of face verification-based correlation, we demonstrate that the proposed scheme provides comparable or better accuracy than the traditional method. One interesting feature of the proposed scheme is that it could greatly outperform the traditional scheme for face identification application in terms of sensitivity to face orientation. The proposed method is found to be digital/optical implementation-friendly, which facilitates its integration on a very broad range of scenarios.

Defining the optimal method for reporting prostate cancer grade and tumor extent on magnetic resonance/ultrasound fusion-targeted biopsies.

PubMed

Gordetsky, Jennifer B; Schultz, Luciana; Porter, Kristin K; Nix, Jeffrey W; Thomas, John V; Del Carmen Rodriguez Pena, Maria; Rais-Bahrami, Soroush

2018-06-01

Magnetic resonance (MR)/ultrasound fusion-targeted biopsy (TB) routinely samples multiple cores from each MR lesion of interest. Pathologists can evaluate the extent of cancer involvement and grade using an individual core (IC) or aggregate (AG) method, which could potentially lead to differences in reporting. We reviewed patients who underwent TB followed by radical prostatectomy (RP). TB cores were evaluated for grade and tumor extent by 2 methods. In the IC method, the grade for each TB lesion was based on the core with the highest Gleason score. Tumor extent for each TB was based on the core with the highest percent of tumor involvement. In the AG method, the tumor from all cores within each TB lesion was aggregated to determine the final composite grade and percentage of tumor involvement. Each method was compared with MR lesional volume, MR lesional density (lesion volume/prostate volume), and RP. Fifty-five patients underwent TB followed by RP. Extent of tumor by the AG method showed a better correlation with target lesion volume (r= 0.27,P= .022) and lesional density (r = 0.32, P = .008) than did the IC method (r= 0.19 [P = .103] andr= 0.22 [P = .062]), respectively. Extent of tumor on TB was associated with extraprostatic extension on RP by the AG method (P= .04), but not by the IC method. This association was significantly higher in patients with a grade group (GG) of 3 or higher (P= .03). A change in cancer grade occurred in 3 patients when comparing methods (2 downgraded GG3 to GG2, 1 downgraded GG4 to GG3 by the AG method). For multiple cores obtained via TB, the AG method better correlates with target lesion volume, lesional density, and extraprostatic extension. Copyright © 2018 Elsevier Inc. All rights reserved.

Centrality and transverse momentum dependence of dihadron correlations in a hydrodynamic model

NASA Astrophysics Data System (ADS)

Castilho, Wagner M.; Qian, Wei-Liang

2018-06-01

In this work, we study the centrality as well as transverse momentum dependence of the dihadron correlation for Au+Au collisions at 200A GeV. The numerical simulations are carried out by using a hydrodynamical code NeXSPheRIO, where the initial conditions are obtained from a Regge-Gribov based microscopic model, NeXuS. In our calculations, the centrality windows are evaluated regarding multiplicity. The final correlations are obtained by the background subtraction via ZYAM methods, where higher harmonics are considered explicitly. The correlations are evaluated for the 0-20%, 20%-40% and 60%-92% centrality windows. Also, the transverse momentum dependence of the dihadron correlations is investigated. The obtained results are compared with experimental data. It is observed that the centrality dependence of the "ridge" and "double shoulder" structures is in consistency with the data. Based on specific set of parameters employed in the present study, it is found that different ZYAM subtraction schemes might lead to different features in the resultant correlations.

Image analysis of pubic bone for age estimation in a computed tomography sample.

PubMed

López-Alcaraz, Manuel; González, Pedro Manuel Garamendi; Aguilera, Inmaculada Alemán; López, Miguel Botella

2015-03-01

Radiology has demonstrated great utility for age estimation, but most of the studies are based on metrical and morphological methods in order to perform an identification profile. A simple image analysis-based method is presented, aimed to correlate the bony tissue ultrastructure with several variables obtained from the grey-level histogram (GLH) of computed tomography (CT) sagittal sections of the pubic symphysis surface and the pubic body, and relating them with age. The CT sample consisted of 169 hospital Digital Imaging and Communications in Medicine (DICOM) archives of known sex and age. The calculated multiple regression models showed a maximum R (2) of 0.533 for females and 0.726 for males, with a high intra- and inter-observer agreement. The method suggested is considered not only useful for performing an identification profile during virtopsy, but also for application in further studies in order to attach a quantitative correlation for tissue ultrastructure characteristics, without complex and expensive methods beyond image analysis.

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.

[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.

Multiple resolution chirp reflectometry for fault localization and diagnosis in a high voltage cable in automotive electronics

NASA Astrophysics Data System (ADS)

Chang, Seung Jin; Lee, Chun Ku; Shin, Yong-June; Park, Jin Bae

2016-12-01

A multiple chirp reflectometry system with a fault estimation process is proposed to obtain multiple resolution and to measure the degree of fault in a target cable. A multiple resolution algorithm has the ability to localize faults, regardless of fault location. The time delay information, which is derived from the normalized cross-correlation between the incident signal and bandpass filtered reflected signals, is converted to a fault location and cable length. The in-phase and quadrature components are obtained by lowpass filtering of the mixed signal of the incident signal and the reflected signal. Based on in-phase and quadrature components, the reflection coefficient is estimated by the proposed fault estimation process including the mixing and filtering procedure. Also, the measurement uncertainty for this experiment is analyzed according to the Guide to the Expression of Uncertainty in Measurement. To verify the performance of the proposed method, we conduct comparative experiments to detect and measure faults under different conditions. Considering the installation environment of the high voltage cable used in an actual vehicle, target cable length and fault position are designed. To simulate the degree of fault, the variety of termination impedance (10 Ω , 30 Ω , 50 Ω , and 1 \\text{k} Ω ) are used and estimated by the proposed method in this experiment. The proposed method demonstrates advantages in that it has multiple resolution to overcome the blind spot problem, and can assess the state of the fault.

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

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Direct and simultaneous detection of organic and inorganic ingredients in herbal powder preparations by Fourier transform infrared microspectroscopic imaging

NASA Astrophysics Data System (ADS)

Chen, Jian-bo; Sun, Su-qin; Tang, Xu-dong; Zhang, Jing-zhao; Zhou, Qun

2016-08-01

Herbal powder preparation is a kind of widely-used herbal product in the form of powder mixture of herbal ingredients. Identification of herbal ingredients is the first and foremost step in assuring the quality, safety and efficacy of herbal powder preparations. In this research, Fourier transform infrared (FT-IR) microspectroscopic identification method is proposed for the direct and simultaneous recognition of multiple organic and inorganic ingredients in herbal powder preparations. First, the reference spectrum of characteristic particles of each herbal ingredient is assigned according to FT-IR results and other available information. Next, a statistical correlation threshold is determined as the lower limit of correlation coefficients between the reference spectrum and a larger number of calibration characteristic particles. After validation, the reference spectrum and correlation threshold can be used to identify herbal ingredient in mixture preparations. A herbal ingredient is supposed to be present if correlation coefficients between the reference spectrum and some sample particles are above the threshold. Using this method, all kinds of herbal materials in powder preparation Kouqiang Kuiyang San are identified successfully. This research shows the potential of FT-IR microspectroscopic identification method for the accurate and quick identification of ingredients in herbal powder preparations.

The correlation between calcaneal valgus angle and asymmetrical thoracic-lumbar rotation angles in patients with adolescent scoliosis.

PubMed

Park, Jaeyong; Lee, Sang Gil; Bae, Jongjin; Lee, Jung Chul

2015-12-01

[Purpose] This study aimed to provide a predictable evaluation method for the progression of scoliosis in adolescents based on quick and reliable measurements using the naked eye, such as the calcaneal valgus angle of the foot, which can be performed at public facilities such as schools. [Subjects and Methods] Idiopathic scoliosis patients with a Cobb's angle of 10° or more (96 females, 22 males) were included in this study. To identify relationships between factors, Pearson's product-moment correlation coefficient was computed. The degree of scoliosis was set as a dependent variable to predict thoracic and lumbar scoliosis using ankle angle and physique factors. Height, weight, and left and right calcaneal valgus angles were set as independent variables; thereafter, multiple regression analysis was performed. This study extracted variables at a significance level (α) of 0.05 by applying a stepwise method, and calculated a regression equation. [Results] Negative correlation (R=-0.266) was shown between lumbar lordosis and asymmetrical lumbar rotation angles. A correlation (R=0.281) was also demonstrated between left calcaneal valgus angles and asymmetrical thoracic rotation angles. [Conclusion] Prediction of scoliosis progress was revealed to be possible through ocular inspection of the calcaneus and Adams forward bending test and the use of a scoliometer.

Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

PubMed

Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2013-01-01

The paper addresses the automated segmentation of multiple organs in upper abdominal CT data. We propose a framework of multi-organ segmentation which is adaptable to any imaging conditions without using intensity information in manually traced training data. The features of the framework are as follows: (1) the organ correlation graph (OCG) is introduced, which encodes the spatial correlations among organs inherent in human anatomy; (2) the patient-specific organ shape and location priors obtained using OCG enable the estimation of intensity priors from only target data and optionally a number of untraced CT data of the same imaging condition as the target data. The proposed methods were evaluated through segmentation of eight abdominal organs (liver, spleen, left and right kidney, pancreas, gallbladder, aorta, and inferior vena cava) from 86 CT data obtained by four imaging conditions at two hospitals. The performance was comparable to the state-of-the-art method using intensity priors constructed from manually traced data.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

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

Visualizing Iron Deposition in Multiple Sclerosis Cadaver Brains

NASA Astrophysics Data System (ADS)

Habib, Charbel A.; Zheng, Weili; Mark Haacke, E.; Webb, Sam; Nichol, Helen

2010-07-01

Aim: To visualize and validate iron deposition in two cases of multiple sclerosis using rapid scanning X-Ray Fluorescence (RS-XRF) and Susceptibility Weighted Imaging (SWI). Material and Methods: Two (2) coronal cadaver brain slices from patients clinically diagnosed with multiple sclerosis underwent magnetic resonance imaging (MRI), specifically SWI to image iron content. To confirm the presence of iron deposits and the absence of zinc-rich myelin in lesions, iron and zinc were mapped using RS-XRF. Results: MS lesions were visualized using FLAIR and correlated with the absence of zinc by XRF. XRF and SWI showed that in the first MS case, there were large iron deposits proximal to the draining vein of the caudate nucleus as well as iron deposits associated with blood vessels throughout the globus pallidus. Less iron was seen in association with lesions than in the basal ganglia. The presence of larger amounts of iron correlated reasonably well between RS-XRF and SWI. In the second case, the basal ganglia appeared normal and acute perivascular iron deposition was absent. Conclusion: Perivascular iron deposition is seen in some but not all MS cases, giving credence to the use of SWI to assess iron involvement in MS pathology in vivo.

Anatomisation with slicing: a new privacy preservation approach for multiple sensitive attributes.

PubMed

Susan, V Shyamala; Christopher, T

2016-01-01

An enormous quantity of personal health information is available in recent decades and tampering of any part of this information imposes a great risk to the health care field. Existing anonymization methods are only apt for single sensitive and low dimensional data to keep up with privacy specifically like generalization and bucketization. In this paper, an anonymization technique is proposed that is a combination of the benefits of anatomization, and enhanced slicing approach adhering to the principle of k-anonymity and l-diversity for the purpose of dealing with high dimensional data along with multiple sensitive data. The anatomization approach dissociates the correlation observed between the quasi identifier attributes and sensitive attributes (SA) and yields two separate tables with non-overlapping attributes. In the enhanced slicing algorithm, vertical partitioning does the grouping of the correlated SA in ST together and thereby minimizes the dimensionality by employing the advanced clustering algorithm. In order to get the optimal size of buckets, tuple partitioning is conducted by MFA. The experimental outcomes indicate that the proposed method can preserve privacy of data with numerous SA. The anatomization approach minimizes the loss of information and slicing algorithm helps in the preservation of correlation and utility which in turn results in reducing the data dimensionality and information loss. The advanced clustering algorithms prove its efficiency by minimizing the time and complexity. Furthermore, this work sticks to the principle of k-anonymity, l-diversity and thus avoids privacy threats like membership, identity and attributes disclosure.

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 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

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.

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.

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.

Convergence at the faces of development workings

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

Borisenko, A.A.

1977-07-01

Since 1963 we have been carrying out investigations in pits of the Pechora coalfield to establish the general laws of roof-floor convergence in the face areas of development workings and their role in gas bursts. We also considered how various methods of working on the seam influence the amount of type of convergence. The observations were made in 20 workings in five pits of Vorkutaugol Group, cut by cutter-loaders and by drilling and blasting at depths between 350 and 600 m; the cross-sectional areas of the workings ranged frm 3.7 to 12.0 m/sup 2/. The aggregated data on daily convergencemore » values was analyzed by the multiple correlation method with the aid of a computer. The aim of the analysis was to elucidate the influence of six factors on the daily convergence values: the depth below the surface, the corrected seam strength, the cross-sectional area of the working, the initial distance from the face to the measurement prop, the daily advance, and the thickness of the seam. The combined correlation coefficient was rather low - 0.49 with a reliability of 9.13. The greatest influence on the convergence values is exerted by the cross-sectional area and by the distance from the face (the partial correlation coefficients being 0.281 and 0.310, respectively), and lesser influences are exerted by the depth below the surface and by the corrected strength of the seam (partial correlationcoefficients 0.164 and 0.178); the influences of seam thickness and daily face advance are very slight. The multiple correlation results indicate that a very great influence is exerted by disregarded factors, among which the most important are undoubtedly the properties of the surrounding rocks.« less

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.

The Capacity Gain of Orbital Angular Momentum Based Multiple-Input-Multiple-Output System

PubMed Central

Zhang, Zhuofan; Zheng, Shilie; Chen, Yiling; Jin, Xiaofeng; Chi, Hao; Zhang, Xianmin

2016-01-01

Wireless communication using electromagnetic wave carrying orbital angular momentum (OAM) has attracted increasing interest in recent years, and its potential to increase channel capacity has been explored widely. In this paper, we compare the technique of using uniform linear array consist of circular traveling-wave OAM antennas for multiplexing with the conventional multiple-in-multiple-out (MIMO) communication method, and numerical results show that the OAM based MIMO system can increase channel capacity while communication distance is long enough. An equivalent model is proposed to illustrate that the OAM multiplexing system is equivalent to a conventional MIMO system with a larger element spacing, which means OAM waves could decrease the spatial correlation of MIMO channel. In addition, the effects of some system parameters, such as OAM state interval and element spacing, on the capacity advantage of OAM based MIMO are also investigated. Our results reveal that OAM waves are complementary with MIMO method. OAM waves multiplexing is suitable for long-distance line-of-sight (LoS) communications or communications in open area where the multi-path effect is weak and can be used in massive MIMO systems as well. PMID:27146453

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Learning style and concept acquisition of community college students in introductory biology

NASA Astrophysics Data System (ADS)

Bobick, Sandra Burin

This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous multiple regression indicated that demographic variables were significant positive predictors for Methodical, Deep and Elaborative Learning Styles. Stepwise multiple regression resulted in number of credits, Read Science and gender (female) as significant predictors of learning styles. The findings of this study emphasize the importance of learning styles in conceptual understanding of the gene and the correlation of nonformal exposure to science information with learning style and conceptual understanding.

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.

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

PubMed Central

Zhu, Xuqi; Liu, Yu; Zhang, Lin

2009-01-01

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency. PMID:22408560

Implementation of false discovery rate for exploring novel paradigms and trait dimensions with ERPs.

PubMed

Crowley, Michael J; Wu, Jia; McCreary, Scott; Miller, Kelly; Mayes, Linda C

2012-01-01

False discovery rate (FDR) is a multiple comparison procedure that targets the expected proportion of false discoveries among the discoveries. Employing FDR methods in event-related potential (ERP) research provides an approach to explore new ERP paradigms and ERP-psychological trait/behavior relations. In Study 1, we examined neural responses to escape behavior from an aversive noise. In Study 2, we correlated a relatively unexplored trait dimension, ostracism, with neural response. In both situations we focused on the frontal cortical region, applying a channel by time plots to display statistically significant uncorrected data and FDR corrected data, controlling for multiple comparisons.

Disentangling formation of multiple-core holes in aminophenol molecules exposed to bright X-FEL radiation

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Kamińska, M.; Mucke, M.; Squibb, R. J.; Eland, J. H. D.; Piancastelli, M. N.; Frasinski, L. J.; Grilj, J.; Koch, M.; McFarland, B. K.; Sistrunk, E.; Gühr, M.; Coffee, R. N.; Bostedt, C.; Bozek, J. D.; Salén, P.; Meulen, P. v. d.; Linusson, P.; Thomas, R. D.; Larsson, M.; Foucar, L.; Ullrich, J.; Motomura, K.; Mondal, S.; Ueda, K.; Richter, R.; Prince, K. C.; Takahashi, O.; Osipov, T.; Fang, L.; Murphy, B. F.; Berrah, N.; Feifel, R.

2015-12-01

Competing multi-photon ionization processes, some leading to the formation of double core hole states, have been examined in 4-aminophenol. The experiments used the linac coherent light source (LCLS) x-ray free electron laser, in combination with a time-of-flight magnetic bottle electron spectrometer and the correlation analysis method of covariance mapping. The results imply that 4-aminophenol molecules exposed to the focused x-ray pulses of the LCLS sequentially absorb more than two x-ray photons, resulting in the formation of multiple core holes as well as in the sequential removal of photoelectrons and Auger electrons (so-called PAPA sequences).

Disentangling formation of multiple-core holes in aminophenol molecules exposed to bright X-FEL radiation

DOE PAGES

Zhaunerchyk, V.; Kaminska, M.; Mucke, M.; ...

2015-10-28

Competing multi-photon ionization processes, some leading to the formation of double core hole states, have been examined in 4-aminophenol. The experiments used the linac coherent light source (LCLS) x-ray free electron laser, in combination with a time-of-flight magnetic bottle electron spectrometer and the correlation analysis method of covariance mapping. Furthermore, the results imply that 4-aminophenol molecules exposed to the focused x-ray pulses of the LCLS sequentially absorb more than two x-ray photons, resulting in the formation of multiple core holes as well as in the sequential removal of photoelectrons and Auger electrons (so-called PAPA sequences).

Two-particle Bose-Einstein correlations in pp collisions at [Formula: see text] 0.9 and 7 TeV measured with the ATLAS detector.

PubMed

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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.

Drug use, mental health and problems related to crime and violence: cross-sectional study1

PubMed Central

Claro, Heloísa Garcia; de Oliveira, Márcia Aparecida Ferreira; Bourdreaux, Janet Titus; Fernandes, Ivan Filipe de Almeida Lopes; Pinho, Paula Hayasi; Tarifa, Rosana Ribeiro

2015-01-01

Objective: to investigate the correlation between disorders related to the use of alcohol and other drugs and symptoms of mental disorders, problems related to crime and violence and to age and gender. Methods: cross-sectional descriptive study carried out with 128 users of a Psychosocial Care Center for Alcohol and other Drugs, in the city of São Paulo, interviewed by means of the instrument entitled Global Appraisal of Individual Needs - Short Screener. Univariate and multiple linear regression models were used to verify the correlation between the variables. Results: using univariate regression models, internalizing and externalizing symptoms and problems related to crime/violence proved significant and were included in the multiple model, in which only the internalizing symptoms and problems related to crime and violence remained significant. Conclusions: there is a correlation between the severity of problems related to alcohol use and severity of mental health symptoms and crime and violence in the study sample. The results emphasize the need for an interdisciplinary and intersectional character of attention to users of alcohol and other drugs, since they live in a socially vulnerable environment. PMID:26626010

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

Daily sodium and potassium excretion can be estimated by scheduled spot urine collections.

PubMed

Doenyas-Barak, Keren; Beberashvili, Ilia; Bar-Chaim, Adina; Averbukh, Zhan; Vogel, Ofir; Efrati, Shai

2015-01-01

The evaluation of sodium and potassium intake is part of the optimal management of hypertension, metabolic syndrome, renal stones, and other conditions. To date, no convenient method for its evaluation exists, as the gold standard method of 24-hour urine collection is cumbersome and often incorrectly performed, and methods that use spot or shorter collections are not accurate enough to replace the gold standard. The aim of this study was to evaluate the correlation and agreement between a new method that uses multiple-scheduled spot urine collection and the gold standard method of 24-hour urine collection. The urine sodium or potassium to creatinine ratios were determined for four scheduled spot urine samples. The mean ratios of the four spot samples and the ratios of each of the single spot samples were corrected for estimated creatinine excretion and compared to the gold standard. A significant linear correlation was demonstrated between the 24-hour urinary solute excretions and estimated excretion evaluated by any of the scheduled spot urine samples. The correlation of the mean of the four spots was better than for any of the single spots. Bland-Altman plots showed that the differences between these measurements were within the limits of agreement. Four scheduled spot urine samples can be used as a convenient method for estimation of 24-hour sodium or potassium excretion. © 2015 S. Karger AG, Basel.

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.

A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations.

PubMed

Agier, Lydiane; Portengen, Lützen; Chadeau-Hyam, Marc; Basagaña, Xavier; Giorgis-Allemand, Lise; Siroux, Valérie; Robinson, Oliver; Vlaanderen, Jelle; González, Juan R; Nieuwenhuijsen, Mark J; Vineis, Paolo; Vrijheid, Martine; Slama, Rémy; Vermeulen, Roel

2016-12-01

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

Subcarrier intensity modulation for MIMO visible light communications

NASA Astrophysics Data System (ADS)

Celik, Yasin; Akan, Aydin

2018-04-01

In this paper, subcarrier intensity modulation (SIM) is investigated for multiple-input multiple-output (MIMO) visible light communication (VLC) systems. A new modulation scheme called DC-aid SIM (DCA-SIM) is proposed for the spatial modulation (SM) transmission plan. Then, DCA-SIM is extended for multiple subcarrier case which is called DC-aid Multiple Subcarrier Modulation (DCA-MSM). Bit error rate (BER) performances of the considered system are analyzed for different MIMO schemes. The power efficiencies of DCA-SIM and DCA-MSM are shown in correlated MIMO VLC channels. The upper bound BER performances of the proposed models are obtained analytically for PSK and QAM modulation types in order to validate the simulation results. Additionally, the effect of power imbalance method on the performance of SIM is studied and remarkable power gains are obtained compared to the non-power imbalanced cases. In this work, Pulse amplitude modulation (PAM) and MSM-Index are used as benchmarks for single carrier and multiple carrier cases, respectively. And the results show that the proposed schemes outperform PAM and MSM-Index for considered single carrier and multiple carrier communication scenarios.

Relationship between parent–infant attachment and parental satisfaction with supportive nursing care

PubMed Central

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Background: Parent–infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent–infant caring relationship, this study sought to investigate the relationship between mother–infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). Materials and Methods: In this descriptive–correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. Results: The results showed that the overall score of mother–infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother–infant attachment and mothers’ satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother–infant attachment) could be explained by different dimensions of mothers’ satisfaction. Conclusions: The results of the study showed that mother–infant attachment improved by increasing mothers’ satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother–infant attachment. PMID:26985225

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.

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.

Estimating small amplitude tremor sources

NASA Astrophysics Data System (ADS)

Katakami, S.; Ito, Y.; Ohta, K.

2017-12-01

Various types of slow earthquakes have been recently observed at both the updip and downdip edges of the coseismic slip areas [Obara and Kato, 2016]. Frequent occurrence of slow earthquakes may help us to reveal the physics underlying megathrust events as useful analogs. Maeda and Obara [2009] estimated spatiotemporal distribution of seismic energy radiation from low-frequency tremors. They applied their method to only the tremors, whose hypocenters had been decided with multiple station method. However, recently Katakami et al. (2016) identified a lot of continuous tremors with small amplitude that were not recorded multiple stations. These small events should be important to reveal the whole slow earthquake activity and to understand strain condition around a plate boundary in subduction zones. First, we apply the modified frequency scanning method (mFSM) at a single station to NIED Hi-net data in the southwestern Japan to understand whole tremor activity which were included weak signal tremors. Second, we developed a method to identify the tremor source area by using the difference of apparent tremor energy at each station by mFSM. We estimated the apparent source tremor energy after correcting both site amplification factor and geometrical spreading. Finally we calculate a tremor source area if the difference of apparent tremor energy between each pair of sites is the smallest. We checked a validity of this analysis by using only tremors which were already detected by envelope correlation method [Idehara et al., 2014]. We calculated the average amplitude as apparent tremor energy in 5 minutes window after occurring tremor at each station. Our results almost consistent to hypocenters which were determined the envelope correlation method. We successfully determined apparent tremor source areas of weak continuous tremors after estimating possible tremor occurrence time windows by using mFSM.

Topics on distance correlation, feature screening and lifetime expectancy with application to Beaver Dam eye study data

NASA Astrophysics Data System (ADS)

Kong, Jing

This thesis includes 4 pieces of work. In Chapter 1, we present the work with a method for examining mortality as it is seen to run in families, and lifestyle factors that are also seen to run in families, in a subpopulation of the Beaver Dam Eye Study that has died by 2011. We find significant distance correlations between death ages, lifestyle factors, and family relationships. Considering only sib pairs compared to unrelated persons, distance correlation between siblings and mortality is, not surprisingly, stronger than that between more distantly related family members and mortality. Chapter 2 introduces a feature screening procedure with the use of distance correlation and covariance. We demonstrate a property for distance covariance, which is incorporated in a novel feature screening procedure based on distance correlation as a stopping criterion. The approach is further implemented to two real examples, namely the famous small round blue cell tumors data and the Cancer Genome Atlas ovarian cancer data Chapter 3 pays attention to the right censored human longevity data and the estimation of lifetime expectancy. We propose a general framework of backward multiple imputation for estimating the conditional lifetime expectancy function and the variance of the estimator in the right censoring setting and prove the properties of the estimator. In addition, we apply the method to the Beaver Dam eye study data to study human longevity, where the expected human lifetime are modeled with smoothing spline ANOVA based on the covariates including baseline age, gender, lifestyle factors and disease variables. Chapter 4 compares two imputation methods for right censored data, namely the famous Buckley-James estimator and the backward imputation method proposed in Chapter 3 and shows that backward imputation method is less biased and more robust with heterogeneity.

Psychometrics of Multiple Choice Questions with Non-Functioning Distracters: Implications to Medical Education.

PubMed

Deepak, Kishore K; Al-Umran, Khalid Umran; AI-Sheikh, Mona H; Dkoli, B V; Al-Rubaish, Abdullah

2015-01-01

The functionality of distracters in a multiple choice question plays a very important role. We examined the frequency and impact of functioning and non-functioning distracters on psychometric properties of 5-option items in clinical disciplines. We analyzed item statistics of 1115 multiple choice questions from 15 summative assessments of undergraduate medical students and classified the items into five groups by their number of non-functioning distracters. We analyzed the effect of varying degree of non-functionality ranging from 0 to 4, on test reliability, difficulty index, discrimination index and point biserial correlation. The non-functionality of distracters inversely affected the test reliability and quality of items in a predictable manner. The non-functioning distracters made the items easier and lowered the discrimination index significantly. Three non-functional distracters in a 5-option MCQ significantly affected all psychometric properties (p < 0.5). The corrected point biserial correlation revealed that the items with 3 functional options were psychometrically as effective as 5-option items. Our study reveals that a multiple choice question with 3 functional options provides lower most limit of item format that has adequate psychometric property. The test containing items with less number of functioning options have significantly lower reliability. The distracter function analysis and revision of nonfunctioning distracters can serve as important methods to improve the psychometrics and reliability of assessment.

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

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.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.

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.

Magnetic Resonance T2-Relaxometry and 2D L-Correlated Spectroscopy in Patients with Minimal Hepatic Encephalopathy

PubMed Central

Singhal, Aparna; Nagarajan, Rajakumar; Kumar, Rajesh; Huda, Amir; Gupta, Rakesh K.; Thomas, M. Albert

2010-01-01

Purpose To evaluate T2-relaxation changes in patients with minimal hepatic encephalopathy (MHE) using T2-relaxometry and to correlate T2 values with brain metabolites evaluated using two-dimensional (2D) magnetic resonance spectroscopy (MRS). Materials and Methods Eight MHE patients and 13 healthy subjects were evaluated using T2-relaxometry, and 8 patients and 9 healthy subjects underwent 2D MRS in right frontal and left occipital regions. Whole brain T2-relaxation maps were compared between MHE and control subjects using analysis-of-covariance, with age and gender included as covariates. T2 values derived from the right frontal and left occipital lobes were correlated with the metabolite ratios. Results Multiple brain regions including anterior and mid cingulate cortices, right anterior and left posterior insular cortices, right prefrontal, medial frontal, and right superior temporal cortices showed significantly increased T2 values in MHE patients compared to control subjects. MRS showed significantly increased ratios of glutamine/glutamate (Glx) and decreased ratios of myo-inositol, taurine, choline, and myo-inositol/choline (mICh) with respect to creatine (Cr_d) in patients compared to controls. Frontal Glx/Cr_d showed significantly positive correlation with T2 values. Conclusion MHE patients showed significantly increased T2 values in multiple brain regions reflecting increased free water content and T2 values in frontal lobe correlated with the increased Glx/Cr_d ratio. PMID:19856435

Expiratory and phonation times as measures of disease severity in patients with Multiple Sclerosis. A case-control study.

PubMed

Nordio, Sara; Bernitsas, Evanthia; Meneghello, Francesca; Palmer, Katie; Stabile, Maria Rosaria; Dipietro, Laura; Di Stadio, Arianna

2018-04-21

Speech disorders are common in patients with Multiple Sclerosis (MS). They can be assessed with several methods, which are however expensive, complex, and not easily accessible to physicians during routine clinic visits. This study aimed at measuring maximum phonation times, maximum expiratory times, and articulation abilities scores in patients with MS compared to healthy subjects and at investigating if any of these parameters could be used as a measure of MS progression. 50 MS patients and 50 gender- and age-matched healthy controls were enrolled in the study. Maximum expiratory times and maximum phonation times were collected from both groups. Articulation abilities were evaluated using the articulation subtest from the Fussi assessment (dysarthria scores). MS patients were evaluated with the Expanded Disability Status Scale (EDSS). Correlations between EDSS scores and maximum expiratory times, maximum phonation times, and dysarthria scores were calculated. EDSS scores of MS patients ranged from 4.5 to 7.5. In MS patients, maximum expiratory times, maximum phonation times, and dysarthria scores were significantly altered compared to healthy controls. Moreover, the EDSS scores were correlated with the maximum expiratory times; the maximum expiratory times were correlated with the maximum phonation times, and the maximum phonation times were correlated with the dysarthria scores. As the expiratory times were significantly correlated with the EDSS scores, they could be used to measure the severity of MS and to monitor its progression. Copyright © 2018 Elsevier B.V. All rights reserved.

Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

PubMed

Riley, Richard D; Elia, Eleni G; Malin, Gemma; Hemming, Karla; Price, Malcolm P

2015-07-30

A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta-analysis is difficult because primary studies often use different methods of measurement and/or different cut-points to dichotomise continuous factors into 'high' and 'low' groups; selective reporting is also common. We illustrate how multivariate random effects meta-analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut-points and/or methods of measurement. The models account for within-study and between-study correlations, which utilises more information and reduces the impact of unreported cut-points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut-point to reduce the number of unknown parameters. The models provide important inferential results for each cut-point and method of measurement, including the summary prognostic effect, the between-study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta-analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut-points than previously thought. In the second, a multivariate meta-analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut-points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A boostrap algorithm for temporal signal reconstruction in the presence of noise from its fractional Fourier transformed intensity spectra

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

Tan, Cheng-Yang; /Fermilab

2011-02-01

A bootstrap algorithm for reconstructing the temporal signal from four of its fractional Fourier intensity spectra in the presence of noise is described. An optical arrangement is proposed which realises the bootstrap method for the measurement of ultrashort laser pulses. The measurement of short laser pulses which are less than 1 ps is an ongoing challenge in optical physics. One reason is that no oscilloscope exists today which can directly measure the time structure of these pulses and so it becomes necessary to invent other techniques which indirectly provide the necessary information for temporal pulse reconstruction. One method called FROGmore » (frequency resolved optical gating) has been in use since 19911 and is one of the popular methods for recovering these types of short pulses. The idea behind FROG is the use of multiple time-correlated pulse measurements in the frequency domain for the reconstruction. Multiple data sets are required because only intensity information is recorded and not phase, and thus by collecting multiple data sets, there is enough redundant measurements to yield the original time structure, but not necessarily uniquely (or even up to an arbitrary constant phase offset). The objective of this paper is to describe another method which is simpler than FROG. Instead of collecting many auto-correlated data sets, only two spectral intensity measurements of the temporal signal are needed in the absence of noise. The first can be from the intensity components of its usual Fourier transform and the second from its FrFT (fractional Fourier transform). In the presence of noise, a minimum of four measurements are required with the same FrFT order but with two different apertures. Armed with these two or four measurements, a unique solution up to a constant phase offset can be constructed.« less

Cognitive status in patients with multiple sclerosis in Lanzarote

PubMed Central

Pérez-Martín, María Yaiza; Eguia-del Río, Pablo; González-Platas, Montserrat; Jiménez-Sosa, Alejandro

2016-01-01

Objectives Cognitive impairment is a common feature in multiple sclerosis affecting ~43%–72% of patients, which involves cognitive functions such as memory, processing speed, attention, and executive function. The aim of this study was to describe the extent and pattern of the involvement of cognitive impairment and psychological status in all patients with multiple sclerosis on a small Spanish island. Patients and methods In all, 70 patients and 56 healthy controls were included in the study between February 2013 and May 2013. All participants were assessed using the Brief Repeatable Battery of Neuropsychological Test. The patients also completed instruments to evaluate the presence of fatigue, perceived cognitive dysfunction, and symptoms of anxiety and depression. All procedures were performed in a single session. Results Cognitive impairment, defined as a score <1.5 standard deviation on two subtests of the battery, was present in 35% of the participants. The most frequently affected domain was working memory, followed by verbal memory and processing speed. Disease duration showed a moderate correlation with visuospatial memory and processing speed. The Expanded Disability Status Scale score correlated with verbal and processing speed. Verbal memory was correlated with depression symptoms and fatigue. Conclusion Cognitive impairment was present in 35% of the study population. The most affected domains were working memory and verbal memory. Working memory and verbal fluency deficit are independent factors of disease evolution. Cognitive decline is related to clinical variables and psychological measures such as fatigue or depression but not to anxiety. PMID:27418825

Monte Carlo simulation of the radiant field produced by a multiple-lamp quartz heating system

NASA Technical Reports Server (NTRS)

Turner, Travis L.

1991-01-01

A method is developed for predicting the radiant heat flux distribution produced by a reflected bank of tungsten-filament tubular-quartz radiant heaters. The method is correlated with experimental results from two cases, one consisting of a single lamp and a flat reflector and the other consisting of a single lamp and a parabolic reflector. The simulation methodology, computer implementation, and experimental procedures are discussed. Analytical refinements necessary for comparison with experiment are discussed and applied to a multilamp, common reflector heating system.

Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

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

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.

3D Simulation of Multiple Simultaneous Hydraulic Fractures with Different Initial Lengths in Rock

NASA Astrophysics Data System (ADS)

Tang, X.; Rayudu, N. M.; Singh, G.

2017-12-01

Hydraulic fracturing is widely used technique for extracting shale gas. During this process, fractures with various initial lengths are induced in rock mass with hydraulic pressure. Understanding the mechanism of propagation and interaction between these induced hydraulic cracks is critical for optimizing the fracking process. In this work, numerical results are presented for investigating the effect of in-situ parameters and fluid properties on growth and interaction of multi simultaneous hydraulic fractures. A fully coupled 3D fracture simulator, TOUGH- GFEM is used for simulating the effect of different vital parameters, including in-situ stress, initial fracture length, fracture spacing, fluid viscosity and flow rate on induced hydraulic fractures growth. This TOUGH-GFEM simulator is based on 3D finite volume method (FVM) and partition of unity element method (PUM). Displacement correlation method (DCM) is used for calculating multi - mode (Mode I, II, III) stress intensity factors. Maximum principal stress criteria is used for crack propagation. Key words: hydraulic fracturing, TOUGH, partition of unity element method , displacement correlation method, 3D fracturing simulator

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

PubMed

Langen, Carolyn D; White, Tonya; Ikram, M Arfan; Vernooij, Meike W; Niessen, Wiro J

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

Measurement of forward-backward multiplicity correlations in lead-lead, proton-lead, and proton-proton collisions with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-06-28

Two-particle pseudorapidity correlations are measured in √ sNN = 2.76TeV Pb + Pb, √ sNN = 5.02TeV p + Pb, and √s = 13 TeV pp collisions at the Large Hadron Collider (LHC), with total integrated luminosities of approximately 7μb –1, 28 nb –1, and 65 nb –1, respectively. The correlation function C N(η 1,η 2) is measured as a function of event multiplicity using charged particles in the pseudorapidity range |η| < 2.4. The correlation function contains a significant short-range component, which is estimated and subtracted. After removal of the short-range component, the shape of the correlation function ismore » described approximately by 1 + < a2 1 > 1/2η 1η 2 in all collision systems over the full multiplicity range. The values of < a 2 1 > 1/2 are consistent for the opposite-charge pairs and same-charge pairs, and for the three collision systems at similar multiplicity. The values of < a 2 1 > 1/2 and the magnitude of the short-range component both follow a power-law dependence on the event multiplicity. Here, the short-range component in p + Pb collisions, after symmetrizing the proton and lead directions, is found to be smaller at a given η than in pp collisions with comparable multiplicity.« less

Measurement of forward-backward multiplicity correlations in lead-lead, proton-lead, and proton-proton collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. 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H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; 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.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; 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, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-06-01

Two-particle pseudorapidity correlations are measured in √{sNN}=2.76 TeV Pb +Pb , √{sNN}=5.02 TeV p +Pb, and √{s }=13 TeV p p collisions at the Large Hadron Collider (LHC), with total integrated luminosities of approximately 7 μ b-1 , 28 nb-1, and 65 nb-1, respectively. The correlation function CN(η1,η2) is measured as a function of event multiplicity using charged particles in the pseudorapidity range |η |<2.4 . The correlation function contains a significant short-range component, which is estimated and subtracted. After removal of the short-range component, the shape of the correlation function is described approximately by 1 + 1 /2η1η2 in all collision systems over the full multiplicity range. The values of 1 /2 are consistent for the opposite-charge pairs and same-charge pairs, and for the three collision systems at similar multiplicity. The values of 1 /2 and the magnitude of the short-range component both follow a power-law dependence on the event multiplicity. The short-range component in p + Pb collisions, after symmetrizing the proton and lead directions, is found to be smaller at a given η than in p p collisions with comparable multiplicity.

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

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.

Multifield-graphs: an approach to visualizing correlations in multifield scalar data.

PubMed

Sauber, Natascha; Theisel, Holger; Seidel, Hans-Peter

2006-01-01

We present an approach to visualizing correlations in 3D multifield scalar data. The core of our approach is the computation of correlation fields, which are scalar fields containing the local correlations of subsets of the multiple fields. While the visualization of the correlation fields can be done using standard 3D volume visualization techniques, their huge number makes selection and handling a challenge. We introduce the Multifield-Graph to give an overview of which multiple fields correlate and to show the strength of their correlation. This information guides the selection of informative correlation fields for visualization. We use our approach to visually analyze a number of real and synthetic multifield datasets.

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-05-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Computationally Efficient Nonlinear Bell Inequalities for Quantum Networks

NASA Astrophysics Data System (ADS)

Luo, Ming-Xing

2018-04-01

The correlations in quantum networks have attracted strong interest with new types of violations of the locality. The standard Bell inequalities cannot characterize the multipartite correlations that are generated by multiple sources. The main problem is that no computationally efficient method is available for constructing useful Bell inequalities for general quantum networks. In this work, we show a significant improvement by presenting new, explicit Bell-type inequalities for general networks including cyclic networks. These nonlinear inequalities are related to the matching problem of an equivalent unweighted bipartite graph that allows constructing a polynomial-time algorithm. For the quantum resources consisting of bipartite entangled pure states and generalized Greenberger-Horne-Zeilinger (GHZ) states, we prove the generic nonmultilocality of quantum networks with multiple independent observers using new Bell inequalities. The violations are maximal with respect to the presented Tsirelson's bound for Einstein-Podolsky-Rosen states and GHZ states. Moreover, these violations hold for Werner states or some general noisy states. Our results suggest that the presented Bell inequalities can be used to characterize experimental quantum networks.

Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

PubMed

Kim, Eunhee; Zhang, Zheng; Wang, Youdan; Zeng, Donglin

2014-12-01

Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure. © 2014, The International Biometric Society.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

[Landscape quality evaluation and vertical structure optimization of natural broadleaf forest].

PubMed

Ouyang, Xun-zhi; Liao, Wei-ming; Peng, Shi-kui

2007-06-01

Taking the natural broadleaf forest in Wuyuan County of Jiangxi Province as study object, a total of 30 representative photos of near-view landscapes and related information were collected. The scenic beauty values were acquired by public judgment method, and the relationship models of scenic beauty values and landscape elements were established by using multiple mathematical model. The results showed that the main elements affecting the near-view landscape quality of natural broadleaf forest were the trunk form, stand density, undergrowth coverage and height, natural pruning, and color richness, with the partial correlation coefficients being 0.4482-0.7724, which were significant or very significant by t-test. The multiple correlation coefficient of the model reached 0.9508, showing very significant by F test (F = 36.11). Straight trunk, better natural pruning and rich color did well, while the super-high or low stand density and undergrowth coverage and height did harm to the scenic beauty. Several management measures for the vertical structure optimization of these landscape elements were put forward.

Preliminary evidence that self-efficacy predicts physical activity in multiple sclerosis.

PubMed

Motl, Robert W; McAuley, Edward; Doerksen, Shawna; Hu, Liang; Morris, Katherine S

2009-09-01

Individuals with multiple sclerosis (MS) are less physically active than non diseased people. One method for increasing physical activity levels involves the identification of factors that correlate with physical activity and that are modifiable by a well designed intervention. This study examined two types of self-efficacy as cross-sectional and prospective correlates of objectively measured physical activity in 16 individuals with a diagnosis of MS. The participants completed two measures of self-efficacy and then wore an accelerometer for a 5-day period at baseline and then at 3 months follow-up. Self-efficacy for continued physical activity was associated with baseline and follow-up levels of physical activity. Self-efficacy for overcoming barriers was associated with follow-up levels of physical activity and change in physical activity across a 3-month period. Researchers should consider self-efficacy as a possible component of an intervention that is designed to increase physical activity levels in those with MS. International Journal of Rehabilitation Research

Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression

USGS Publications Warehouse

Kokaly, R.F.; Clark, R.N.

1999-01-01

We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.30 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.301 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

Determination of organic compounds in water using ultraviolet LED

NASA Astrophysics Data System (ADS)

Kim, Chihoon; Ji, Taeksoo; Eom, Joo Beom

2018-04-01

This paper describes a method of detecting organic compounds in water using an ultraviolet LED (280 nm) spectroscopy system and a photodetector. The LED spectroscopy system showed a high correlation between the concentration of the prepared potassium hydrogen phthalate and that calculated by multiple linear regression, indicating an adjusted coefficient of determination ranging from 0.953-0.993. In addition, a comparison between the performance of the spectroscopy system and the total organic carbon analyzer indicated that the difference in concentration was small. Based on the close correlation between the spectroscopy and photodetector absorbance values, organic measurement with a photodetector could be configured for monitoring.

Correlation between blink reflex abnormalities and magnetic resonance imaging findings in patients with multiple sclerosis.

PubMed

Degirmenci, Eylem; Erdogan, Cagdas; Bir, Levent Sinan

2013-09-01

This study investigates the correlation between brain magnetic resonance imaging findings and blink reflex abnormalities in patients with relapsing remitting multiple sclerosis. Twenty-six patients and 17 healthy subjects were included in this study. Blink reflex test (BRT) results were obtained using right and left stimulations; thus, 52 BRT results were recorded for the patient group, and 34 BRT results were recorded for the control group. The magnetic resonance imaging (MRI) findings were classified based on the existence of brainstem lesions (hyperintense lesion on T2 weighted (W) and fast fluid-attenuated inversion recovery MRI or contrast-enhancing lesion on T1W MRI). Correlation analysis was performed for the BRT and MRI findings. The percentage of individuals with abnormal BRT results (including R1 latency, ipsilateral R2 latency, and contralateral R2 latency) was significantly higher in the patient group as compared to the control group (p values: 0.015, 0.001, and 0.002, respectively). Correlation analysis revealed significant correlations between contralateral R2 latency abnormalities and brainstem lesions (p value: 0.011). Our results showed significant correlation correlations between contralateral R2 latency abnormalities and brainstem lesions and these results may be explained the effects of multiple demyelinating lesions of the brain stem of patients with relapsing remitting multiple sclerosis.

Measurement of long-range near-side two-particle angular correlations in pp collisions at $$\\sqrt{s}$$ = 13 TeV

DOE PAGES

Khachatryan, Vardan

2016-04-27

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

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

Zawisza, I; Yan, H; Yin, F

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogatemore » signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.« less

MicroRNA signature of the human developing pancreas.

PubMed

Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L

2010-09-22

MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas.

MicroRNA signature of the human developing pancreas

PubMed Central

2010-01-01

Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas. PMID:20860821

Identification of quality markers of Yuanhu Zhitong tablets based on integrative pharmacology and data mining.

PubMed

Li, Ke; Li, Junfang; Su, Jin; Xiao, Xuefeng; Peng, Xiujuan; Liu, Feng; Li, Defeng; Zhang, Yi; Chong, Tao; Xu, Haiyu; Liu, Changxiao; Yang, Hongjun

2018-03-07

The quality evaluation of traditional Chinese medicine (TCM) formulations is needed to guarantee the safety and efficacy. In our laboratory, we established interaction rules between chemical quality control and biological activity evaluations to study Yuanhu Zhitong tablets (YZTs). Moreover, a quality marker (Q-marker) has recently been proposed as a new concept in the quality control of TCM. However, no appropriate methods are available for the identification of Q-markers from the complex TCM systems. We aimed to use an integrative pharmacological (IP) approach to further identify Q-markers from YZTs through the integration of multidisciplinary knowledge. In addition, data mining was used to determine the correlation between multiple constituents of this TCM and its bioactivity to improve quality control. The IP approach was used to identify the active constituents of YZTs and elucidate the molecular mechanisms by integrating chemical and biosynthetic analyses, drug metabolism, and network pharmacology. Data mining methods including grey relational analysis (GRA) and least squares support vector machine (LS-SVM) regression techniques, were used to establish the correlations among the constituents and efficacy, and dose efficacy in multiple dimensions. Seven constituents (tetrahydropalmatine, α-allocryptopine, protopine, corydaline, imperatorin, isoimperatorin, and byakangelicin) were identified as Q-markers of YZT using IP based on their high abundance, specific presence in the individual herbal constituents and the product, appropriate drug-like properties, and critical contribution to the bioactivity of the mixture of YZT constituents. Moreover, three Q-markers (protopine, α-allocryptopine, and corydaline) were highly correlated with the multiple bioactivities of the YZTs, as found using data mining. Finally, three constituents (tetrahydropalmatine, corydaline, and imperatorin) were chosen as minimum combinations that both distinguished the authentic components from false products and indicated the intensity of bioactivity to improve the quality control of YZTs. Tetrahydropalmatine, imperatorin, and corydaline could be used as minimum combinations to effectively control the quality of YZTs. Copyright © 2018. Published by Elsevier GmbH.

Validity of an Observation Method for Assessing Pain Behavior in Individuals With Multiple Sclerosis

PubMed Central

Cook, Karon F.; Roddey, Toni S.; Bamer, Alyssa M.; Amtmann, Dagmar; Keefe, Francis J

2012-01-01

Context Pain is a common and complex experience for individuals who live with multiple sclerosis (MS) that interferes with physical, psychological and social function. A valid and reliable tool for quantifying observed pain behaviors in MS is critical to understanding how pain behaviors contribute to pain-related disability in this clinical population. Objectives To evaluate the reliability and validity of a pain behavioral observation protocol in individuals who have MS. Methods Community-dwelling volunteers with multiple sclerosis (N=30), back pain (N=5), or arthritis (N=8) were recruited based on clinician referrals, advertisements, fliers, web postings, and participation in previous research. Participants completed measures of pain severity, pain interference, and self-reported pain behaviors and were videotaped doing typical activities (e.g., walking, sitting). Two coders independently recorded frequencies of pain behaviors by category (e.g., guarding, bracing) and inter-rater reliability statistics were calculated. Naïve observers reviewed videotapes of individuals with MS and rated their pain. Spearman correlations were calculated between pain behavior frequencies and self-reported pain and pain ratings by naïve observers. Results Inter-rater reliability estimates indicated the reliability of pain codes in the MS sample. Kappa coefficients ranged from moderate agreement (sighing = 0.40) to substantial agreement (guarding = 0.83). These values were comparable to those obtained in the combined back pain and arthritis sample. Concurrent validity was supported by correlations with self-reported pain (0.46-0.53) and with self-reports of pain behaviors (0.58). Construct validity was supported by finding of 0.87 correlation between total pain behaviors observed by coders and mean pain ratings by naïve observers. Conclusion Results support use of the pain behavior observation protocol for assessing pain behaviors of individuals with MS. Valid assessments of pain behaviors of individuals with MS in could lead to creative interventions in the management of chronic pain in this population. PMID:23159684

Altered Cortico-Striatal–Thalamic Connectivity in Relation to Spatial Working Memory Capacity in Children with ADHD

PubMed Central

Mills, Kathryn L.; Bathula, Deepti; Dias, Taciana G. Costa; Iyer, Swathi P.; Fenesy, Michelle C.; Musser, Erica D.; Stevens, Corinne A.; Thurlow, Bria L.; Carpenter, Samuel D.; Nagel, Bonnie J.; Nigg, Joel T.; Fair, Damien A.

2012-01-01

Introduction: Attention deficit hyperactivity disorder (ADHD) captures a heterogeneous group of children, who are characterized by a range of cognitive and behavioral symptoms. Previous resting-state functional connectivity MRI (rs-fcMRI) studies have sought to understand the neural correlates of ADHD by comparing connectivity measurements between those with and without the disorder, focusing primarily on cortical–striatal circuits mediated by the thalamus. To integrate the multiple phenotypic features associated with ADHD and help resolve its heterogeneity, it is helpful to determine how specific circuits relate to unique cognitive domains of the ADHD syndrome. Spatial working memory has been proposed as a key mechanism in the pathophysiology of ADHD. Methods: We correlated the rs-fcMRI of five thalamic regions of interest (ROIs) with spatial span working memory scores in a sample of 67 children aged 7–11 years [ADHD and typically developing children (TDC)]. In an independent dataset, we then examined group differences in thalamo-striatal functional connectivity between 70 ADHD and 89 TDC (7–11 years) from the ADHD-200 dataset. Thalamic ROIs were created based on previous methods that utilize known thalamo-cortical loops and rs-fcMRI to identify functional boundaries in the thalamus. Results/Conclusion: Using these thalamic regions, we found atypical rs-fcMRI between specific thalamic groupings with the basal ganglia. To identify the thalamic connections that relate to spatial working memory in ADHD, only connections identified in both the correlational and comparative analyses were considered. Multiple connections between the thalamus and basal ganglia, particularly between medial and anterior dorsal thalamus and the putamen, were related to spatial working memory and also altered in ADHD. These thalamo-striatal disruptions may be one of multiple atypical neural and cognitive mechanisms that relate to the ADHD clinical phenotype. PMID:22291667

Measurement of Long-Range Near-Side Two-Particle Angular Correlations in pp Collisions at sqrt[s]=13  TeV.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Knünz, V; König, A; Krammer, M; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schieck, J; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Keaveney, J; Lowette, S; Moreels, L; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Van Parijs, I; Barria, P; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Fasanella, G; Favart, L; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Maerschalk, T; Marinov, A; Perniè, L; Randle-Conde, A; Seva, T; Vander Velde, C; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Beernaert, K; Benucci, L; Cimmino, A; Crucy, S; Dobur, D; Fagot, A; Garcia, G; Gul, M; Mccartin, J; Ocampo Rios, A A; Poyraz, D; Ryckbosch, D; Salva, S; Sigamani, M; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Mertens, A; Musich, M; Nuttens, C; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Beliy, N; Hammad, G H; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hamer, 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; De Jesus Damiao, D; De Oliveira Martins, C; 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Hall-Wilton, R; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Mohapatra, A; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Sarangi, T; Savin, A; Sharma, A; Smith, N; Smith, W H; Taylor, D; Verwilligen, P; Woods, N

2016-04-29

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 Δη-Δϕ correlation functions. The magnitude of the correlation exhibits a pronounced maximum in the range 1.0

Comparison of scavenging capacities of vegetables by ORAC and EPR.

PubMed

Kameya, Hiromi; Watanabe, Jun; Takano-Ishikawa, Yuko; Todoriki, Setsuko

2014-02-15

Reactive oxygen species (ROS) are considered to be causative agents of many health problems. In spite of this, the radical-specific scavenging capacities of food samples have not been well studied. In the present work, we have developed an electron paramagnetic resonance (EPR) spin trapping method for analysis of the scavenging capacities of food samples for multiple ROS, utilising the same photolysis procedure for generating each type of radical. The optimal conditions for effective evaluation of hydroxyl, superoxide, and alkoxyl radical scavenging capacity were determined. Quantification of radical adducts was found to be highly reproducible, with variations of less than 4%. The optimised EPR spin trapping method was used to analyse the scavenging capacities of 54 different vegetable extracts for multiple radicals, and the results were compared with oxygen radical absorption capacity values. Good correlations between the two methods were observed for superoxide and alkoxyl radicals, but not for hydroxyl. Copyright © 2013 Elsevier Ltd. All rights reserved.

Correlated noise-based switches and stochastic resonance in a bistable genetic regulation system

NASA Astrophysics Data System (ADS)

Wang, Can-Jun; Yang, Ke-Li

2016-07-01

The correlated noise-based switches and stochastic resonance are investigated in a bistable single gene switching system driven by an additive noise (environmental fluctuations), a multiplicative noise (fluctuations of the degradation rate). The correlation between the two noise sources originates from on the lysis-lysogeny pathway system of the λ phage. The steady state probability distribution is obtained by solving the time-independent Fokker-Planck equation, and the effects of noises are analyzed. The effects of noises on the switching time between the two stable states (mean first passage time) is investigated by the numerical simulation. The stochastic resonance phenomenon is analyzed by the power amplification factor. The results show that the multiplicative noise can induce the switching from "on" → "off" of the protein production, while the additive noise and the correlation between the noise sources can induce the inverse switching "off" → "on". A nonmonotonic behaviour of the average switching time versus the multiplicative noise intensity, for different cross-correlation and additive noise intensities, is observed in the genetic system. There exist optimal values of the additive noise, multiplicative noise and cross-correlation intensities for which the weak signal can be optimal amplified.

A Reactive Balance Rating Method that Correlates with Kinematics after Trip-Like Perturbations on a Treadmill and Fall Risk Among Residents of Older Adult Congregate Housing.

PubMed

Madigan, Michael L; Aviles, Jessica; Allin, Leigh J; Nussbaum, Maury A; Alexander, Neil B

2018-04-16

A growing number of studies are using modified treadmills to train reactive balance after trip-like perturbations that require multiple steps to recover balance. The goal of this study was thus to develop and validate a low-tech reactive balance rating method in the context of trip-like treadmill perturbations to facilitate the implementation of this training outside the research setting. Thirty-five residents of five senior congregate housing facilities participated in the study. Subjects completed a series of reactive balance tests on a modified treadmill from which the reactive balance rating was determined, along with a battery of standard clinical balance and mobility tests that predict fall risk. We investigated the strength of correlation between the reactive balance rating and reactive balance kinematics. We compared the strength of correlation between the reactive balance rating and clinical tests predictive of fall risk, with the strength of correlation between reactive balance kinematics and the same clinical tests. We also compared the reactive balance rating between subjects predicted to be at a high or low risk of falling. The reactive balance rating was correlated with reactive balance kinematics (Spearman's rho squared = .04 - .30), exhibited stronger correlations with clinical tests than most kinematic measures (Spearman's rho squared = .00 - .23), and was 42-60% lower among subjects predicted to be at a high risk for falling. The reactive balance rating method may provide a low-tech, valid measure of reactive balance kinematics, and an indicator of fall risk, after trip-like postural perturbations.

Enhancing the sensitivity of fluorescence correlation spectroscopy by using time-correlated single photon counting.

PubMed

Lamb, D C; Müller, B K; Bräuchle, C

2005-10-01

Fluorescence correlation spectroscopy (FCS) and fluorescence cross-correlation spectroscopy (FCCS) are methods that extract information about a sample from the influence of thermodynamic equilibrium fluctuations on the fluorescence intensity. This method allows dynamic information to be obtained from steady state equilibrium measurements and its popularity has dramatically increased in the last 10 years due to the development of high sensitivity detectors and its combination with confocal microscopy. Using time-correlated single-photon counting (TCSPC) detection and pulsed excitation, information over the duration of the excited state can be extracted and incorporated in the analysis. In this short review, we discuss new methodologies that have recently emerged which incorporated fluorescence lifetime information or TCSPC data in the FCS and FCCS analysis. Time-gated FCS discriminates between which photons are to be incorporated in the analysis dependent upon their arrival time after excitation. This allows for accurate FCS measurements in the presence of fluorescent background, determination of sample homogeneity, and the ability to distinguish between static and dynamic heterogeneities. A similar method, time-resolved FCS can be used to resolve the individual correlation functions from multiple fluorophores through the different fluorescence lifetimes. Pulsed interleaved excitation (PIE) encodes the excitation source into the TCSPC data. PIE can be used to perform dual-channel FCCS with a single detector and allows elimination of spectral cross-talk with dual-channel detection. For samples that undergo fluorescence resonance energy transfer (FRET), quantitative FCCS measurements can be performed in spite of the FRET and the static FRET efficiency can be determined.

Correlation and Stacking of Relative Paleointensity and Oxygen Isotope Data

NASA Astrophysics Data System (ADS)

Lurcock, P. C.; Channell, J. E.; Lee, D.

2012-12-01

The transformation of a depth-series into a time-series is routinely implemented in the geological sciences. This transformation often involves correlation of a depth-series to an astronomically calibrated time-series. Eyeball tie-points with linear interpolation are still regularly used, although these have the disadvantages of being non-repeatable and not based on firm correlation criteria. Two automated correlation methods are compared: the simulated annealing algorithm (Huybers and Wunsch, 2004) and the Match protocol (Lisiecki and Lisiecki, 2002). Simulated annealing seeks to minimize energy (cross-correlation) as "temperature" is slowly decreased. The Match protocol divides records into intervals, applies penalty functions that constrain accumulation rates, and minimizes the sum of the squares of the differences between two series while maintaining the data sequence in each series. Paired relative paleointensity (RPI) and oxygen isotope records, such as those from IODP Site U1308 and/or reference stacks such as LR04 and PISO, are warped using known warping functions, and then the un-warped and warped time-series are correlated to evaluate the efficiency of the correlation methods. Correlations are performed in tandem to simultaneously optimize RPI and oxygen isotope data. Noise spectra are introduced at differing levels to determine correlation efficiency as noise levels change. A third potential method, known as dynamic time warping, involves minimizing the sum of distances between correlated point pairs across the whole series. A "cost matrix" between the two series is analyzed to find a least-cost path through the matrix. This least-cost path is used to nonlinearly map the time/depth of one record onto the depth/time of another. Dynamic time warping can be expanded to more than two dimensions and used to stack multiple time-series. This procedure can improve on arithmetic stacks, which often lose coherent high-frequency content during the stacking process.

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

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments

PubMed Central

Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria

2015-01-01

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162

a Task-Oriented Disaster Information Correlation Method

NASA Astrophysics Data System (ADS)

Linyao, Q.; Zhiqiang, D.; Qing, Z.

2015-07-01

With the rapid development of sensor networks and Earth observation technology, a large quantity of disaster-related data is available, such as remotely sensed data, historic data, case data, simulated data, and disaster products. However, the efficiency of current data management and service systems has become increasingly difficult due to the task variety and heterogeneous data. For emergency task-oriented applications, the data searches primarily rely on artificial experience based on simple metadata indices, the high time consumption and low accuracy of which cannot satisfy the speed and veracity requirements for disaster products. In this paper, a task-oriented correlation method is proposed for efficient disaster data management and intelligent service with the objectives of 1) putting forward disaster task ontology and data ontology to unify the different semantics of multi-source information, 2) identifying the semantic mapping from emergency tasks to multiple data sources on the basis of uniform description in 1), and 3) linking task-related data automatically and calculating the correlation between each data set and a certain task. The method goes beyond traditional static management of disaster data and establishes a basis for intelligent retrieval and active dissemination of disaster information. The case study presented in this paper illustrates the use of the method on an example flood emergency relief task.

The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

PubMed

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

2018-03-01

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

A New Method of Using Sensor Arrays for Gas Leakage Location Based on Correlation of the Time-Space Domain of Continuous Ultrasound

PubMed Central

Bian, Xu; Zhang, Yu; Li, Yibo; Gong, Xiaoyue; Jin, Shijiu

2015-01-01

This paper proposes a time-space domain correlation-based method for gas leakage detection and location. It acquires the propagated signal on the skin of the plate by using a piezoelectric acoustic emission (AE) sensor array. The signal generated from the gas leakage hole (which diameter is less than 2 mm) is time continuous. By collecting and analyzing signals from different sensors’ positions in the array, the correlation among those signals in the time-space domain can be achieved. Then, the directional relationship between the sensor array and the leakage source can be calculated. The method successfully solves the real-time orientation problem of continuous ultrasonic signals generated from leakage sources (the orientation time is about 15 s once), and acquires high accuracy location information of leakage sources by the combination of multiple sets of orientation results. According to the experimental results, the mean value of the location absolute error is 5.83 mm on a one square meter plate, and the maximum location error is generally within a ±10 mm interval. Meanwhile, the error variance is less than 20.17. PMID:25860070

A new method of using sensor arrays for gas leakage location based on correlation of the time-space domain of continuous ultrasound.

PubMed

Bian, Xu; Zhang, Yu; Li, Yibo; Gong, Xiaoyue; Jin, Shijiu

2015-04-09

This paper proposes a time-space domain correlation-based method for gas leakage detection and location. It acquires the propagated signal on the skin of the plate by using a piezoelectric acoustic emission (AE) sensor array. The signal generated from the gas leakage hole (which diameter is less than 2 mm) is time continuous. By collecting and analyzing signals from different sensors' positions in the array, the correlation among those signals in the time-space domain can be achieved. Then, the directional relationship between the sensor array and the leakage source can be calculated. The method successfully solves the real-time orientation problem of continuous ultrasonic signals generated from leakage sources (the orientation time is about 15 s once), and acquires high accuracy location information of leakage sources by the combination of multiple sets of orientation results. According to the experimental results, the mean value of the location absolute error is 5.83 mm on a one square meter plate, and the maximum location error is generally within a ±10 mm interval. Meanwhile, the error variance is less than 20.17.

Sports Participation and Positive Correlates in African American, Latino, and White Girls

PubMed Central

Duncan, Susan C.; Strycker, Lisa A.; Chaumeton, Nigel R.

2015-01-01

Purpose The purpose of the study was to examine relations among sports participation and positive correlates across African American, Latino, and white girls. Positive correlate variables were self-perceptions (self-worth, body attractiveness, athletic competence), less depression, and participation in extracurricular activities. Methods The sample comprised 372 girls (mean age = 12.03 years). Data were analyzed using multiple-sample structural equation models, controlling for age and income. Results Across all ethnic groups, greater sports participation was significantly related to higher self-worth, body attractiveness, and athletic competence, and to more extracurricular activity. Among Latino and white girls only, greater sports participation also was related to less depression. There were significant age and income influences on the positive correlates. Conclusions Findings confirm the existence of significant relationships between organized sports participation and positive correlates among early adolescent African American, Latino, and white girls. Despite a few ethnic differences in relationships, the current study revealed more similarities than differences. PMID:26692758

CORRELATOR 5.2 - A program for interactive lithostratigraphic correlation of wireline logs

USGS Publications Warehouse

Olea, R.A.

2004-01-01

The limited radius of investigation of petrophysical measurements made in boreholes and the relatively large distances between wells result in an incomplete sensing of the subsurface through well logging. CORRELATOR is a program for estimating geological properties between logged boreholes. An initial and fundamental step is the lithostratigraphic correlation of logs in different wells. The method employed by the program closely emulates the process of visual inspection used by experienced subsurface geologists in manual correlation. Mathematically, the determination of lithostratigraphical equivalence is based on the simultaneous assessment of similarity in shale content, similarity in the patterns of vertical variation in a petrophysical property that is measured with high vertical resolution, and spatial consistency of stratigraphic relationships as determined by an expert system. Multiple additional options for processing log readings allow maximization in the extraction of information from pairs of logs per well and great flexibility in the final display of results in the form of cross sections and dip diagrams. ?? 2004 Elsevier Ltd. All rights reserved.

Several Families of Sequences with Low Correlation and Large Linear Span

NASA Astrophysics Data System (ADS)

Zeng, Fanxin; Zhang, Zhenyu

In DS-CDMA systems and DS-UWB radios, low correlation of spreading sequences can greatly help to minimize multiple access interference (MAI) and large linear span of spreading sequences can reduce their predictability. In this letter, new sequence sets with low correlation and large linear span are proposed. Based on the construction Trm1[Trnm(αbt+γiαdt)]r for generating p-ary sequences of period pn-1, where n=2m, d=upm±v, b=u±v, γi∈GF(pn), and p is an arbitrary prime number, several methods to choose the parameter d are provided. The obtained sequences with family size pn are of four-valued, five-valued, six-valued or seven-valued correlation and the maximum nontrivial correlation value is (u+v-1)pm-1. The simulation by a computer shows that the linear span of the new sequences is larger than that of the sequences with Niho-type and Welch-type decimations, and similar to that of [10].

The application of a low-cost 3D depth camera for patient set-up and respiratory motion management in radiotherapy

NASA Astrophysics Data System (ADS)

Tahavori, Fatemeh

Respiratory motion induces uncertainty in External Beam Radiotherapy (EBRT), which can result in sub-optimal dose delivery to the target tissue and unwanted dose to normal tissue. The conventional approach to managing patient respiratory motion for EBRT within the area of abdominal-thoracic cancer is through the use of internal radiological imaging methods (e.g. Megavoltage imaging or Cone-Beam Computed Tomography) or via surrogate estimates of tumour position using external markers placed on the patient chest. This latter method uses tracking with video-based techniques, and relies on an assumed correlation or mathematical model, between the external surrogate signal and the internal target position. The marker's trajectory can be used in both respiratory gating techniques and real-time tracking methods. Internal radiological imaging methods bring with them limited temporal resolution, and additional radiation burden, which can be addressed by external marker-based methods that carry no such issues. Moreover, by including multiple external markers and placing them closer to the internal target organs, the effciency of correlation algorithms can be increased. However, the quality of such external monitoring methods is underpinned by the performance of the associated correlation model. Therefore, several new approaches to correlation modelling have been developed as part of this thesis and compared using publicly-available datasets. Highly competitive results have been obtained when compared against state-of-the-art methods. Marker-based methods also have the disadvantages of requiring manual set-up time for marker placement and patient positioning and potential issues with reproducibility of marker placement. This motivates the investigation of non-contact marker-free methods for use in EBRT, which is the main topic of this thesis. The Microsoft Kinect is used as an example of a low-cost consumer grade 3D depth camera for capturing and analysing external respiratory motion. This thesis makes the first presentation of detailed studies of external respiratory motion captured using such low-cost technology and demonstrates its potential in a healthcare environment. Firstly, the fundamental performance of a range of Microsoft Kinect sensors is assessed for use in radiotherapy (and potentially other healthcare applications), in terms of static and dynamic performance using both phantoms and volunteers. Then external respiratory motion is captured using the above technology from a group of 32 healthy volunteers and Principal Component Analysis (PCA) is applied to a region of interest encompassing the complete anterior surface to demonstrate breathing style. This work demonstrates that this surface motion can be compactly described by the first two PCA eigenvectors. The reproducibility of subject-specific EBRT set-up using conventional laser-based alignment and marker-based Deep Inspiration Breath Hold (DIBH) methods are also studied using the Microsoft Kinect sensor. A cohort of five healthy female volunteers is repeatedly set-up for left-sided breast cancer EBRT and multiple DIBH episodes captured over five separate sessions representing multiple fractionated radiotherapy treatment sessions, but without dose delivery. This provided an independent assessment that subjects were set-up and generally achieved variations within currently accepted margins of clinical practice. Moreover, this work demonstrated the potential role of consumer-grade 3D depth camera technology as a possible replacement for marker based set-up and DIBH management procedures. This brings with it the additional benefits of low cost, and potential through-put benefits, as patient set-up could ultimately be fully automated with this technology, and DIBH could be independently monitored without requiring preparatory manual intervention.

A semiparametric separation curve approach for comparing correlated ROC data from multiple markers

PubMed Central

Tang, Liansheng Larry; Zhou, Xiao-Hua

2012-01-01

In this article we propose a separation curve method to identify the range of false positive rates for which two ROC curves differ or one ROC curve is superior to the other. Our method is based on a general multivariate ROC curve model, including interaction terms between discrete covariates and false positive rates. It is applicable with most existing ROC curve models. Furthermore, we introduce a semiparametric least squares ROC estimator and apply the estimator to the separation curve method. We derive a sandwich estimator for the covariance matrix of the semiparametric estimator. We illustrate the application of our separation curve method through two real life examples. PMID:23074360

A theoretically based determination of bowen-ratio fetch requirements

USGS Publications Warehouse

Stannard, D.I.

1997-01-01

Determination of fetch requirements for accurate Bowen-ratio measurements of latent- and sensible-heat fluxes is more involved than for eddy-correlation measurements because Bowen-ratio sensors are located at two heights, rather than just one. A simple solution to the diffusion equation is used to derive an expression for Bowen-ratio fetch requirements, downwind of a step change in surface fluxes. These requirements are then compared to eddy-correlation fetch requirements based on the same diffusion equation solution. When the eddy-correlation and upper Bowen-ratio sensor heights are equal, and the available energy upwind and downwind of the step change is constant, the Bowen-ratio method requires less fetch than does eddy correlation. Differences in fetch requirements between the two methods are greatest over relatively smooth surfaces. Bowen-ratio fetch can be reduced significantly by lowering the lower sensor, as well as the upper sensor. The Bowen-ratio fetch model was tested using data from a field experiment where multiple Bowen-ratio systems were deployed simultaneously at various fetches and heights above a field of bermudagrass. Initial comparisons were poor, but improved greatly when the model was modified (and operated numerically) to account for the large roughness of the upwind cotton field.

Multiple skin neoplasms in subjects under 40 years of age in Goiania, Brazil

PubMed Central

Pereira, Samir; Curado, Maria Paula; Ribeiro, Ana Maria Quinteiro

2015-01-01

OBJECTIVE To describe the trend for malignant skin neoplasms in subjects under 40 years of age in a region with high ultraviolet radiation indices. METHODS A descriptive epidemiological study on melanoma and nonmelanoma skin cancers that was conducted in Goiania, Midwest Brazil, with 1,688 people under 40 years of age, between 1988 and 2009. Cases were obtained from Registro de Câncer de Base Populacional de Goiânia (Goiania’s Population-Based Cancer File). Frequency, trends, and incidence of cases with single and multiple lesions were analyzed; transplants and genetic skin diseases were found in cases with multiple lesions. RESULTS Over the period, 1,995 skin cancer cases were observed to found, of which 1,524 (90.3%) cases had single lesions and 164 (9.7%) had multiple lesions. Regarding single lesions, incidence on men was observed to have risen from 2.4 to 3.1/100,000 inhabitants; it differed significantly for women, shifting from 2.3 to 5.3/100,000 (Annual percentage change – [APC] 3.0%, p = 0.006). Regarding multiple lesions, incidence on men was observed to have risen from 0.30 to 0.98/100,000 inhabitants; for women, it rose from 0.43 to 1.16/100,000 (APC 8.6%, p = 0.003). Genetic skin diseases or transplants were found to have been correlated with 10.0% of cases with multiple lesions – an average of 5.1 lesions per patient. The average was 2.5 in cases without that correlation. CONCLUSIONS Skin cancer on women under 40 years of age has been observed to be increasing for both cases with single and multiple lesions. It is not unusual to find multiple tumors in young people – in most cases, they are not associated with genetic skin diseases or transplants. It is necessary to avoid excessive exposure to ultraviolet radiation from childhood. PMID:26465667

Noise-free recovery of optodigital encrypted and multiplexed images.

PubMed

Henao, Rodrigo; Rueda, Edgar; Barrera, John F; Torroba, Roberto

2010-02-01

We present a method that allows storing multiple encrypted data using digital holography and a joint transform correlator architecture with a controllable angle reference wave. In this method, the information is multiplexed by using a key and a different reference wave angle for each object. In the recovering process, the use of different reference wave angles prevents noise produced by the nonrecovered objects from being superimposed on the recovered object; moreover, the position of the recovered object in the exit plane can be fully controlled. We present the theoretical analysis and the experimental results that show the potential and applicability of the method.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Noise Identification in a Hot Transonic Jet Using Low-Dimensional Methods

DTIC Science & Technology

2008-03-01

calibration between the nozzle static pressure (transducer) and total pressure ( pitot probe) reveals a nearly linear relationship between the two, exhibiting... rakes of hot-wires. Multi-point correlations of velocity components coupled with assumptions of homogeneity and periodicity in the jet flow flied...axisymmetric incompressible jet at one downstream position using an in-house designed rake of 138 hot-wires. The experiment was then carried out at multiple

Multiple, correlated covariates associated with differential item functioning (DIF): Accounting for language DIF when education levels differ across languages.

PubMed

Gibbons, Laura E; Crane, Paul K; Mehta, Kala M; Pedraza, Otto; Tang, Yuxiao; Manly, Jennifer J; Narasimhalu, Kaavya; Teresi, Jeanne; Jones, Richard N; Mungas, Dan

2011-04-28

Differential item functioning (DIF) occurs when a test item has different statistical properties in subgroups, controlling for the underlying ability measured by the test. DIF assessment is necessary when evaluating measurement bias in tests used across different language groups. However, other factors such as educational attainment can differ across language groups, and DIF due to these other factors may also exist. How to conduct DIF analyses in the presence of multiple, correlated factors remains largely unexplored. This study assessed DIF related to Spanish versus English language in a 44-item object naming test. Data come from a community-based sample of 1,755 Spanish- and English-speaking older adults. We compared simultaneous accounting, a new strategy for handling differences in educational attainment across language groups, with existing methods. Compared to other methods, simultaneously accounting for language- and education-related DIF yielded salient differences in some object naming scores, particularly for Spanish speakers with at least 9 years of education. Accounting for factors that vary across language groups can be important when assessing language DIF. The use of simultaneous accounting will be relevant to other cross-cultural studies in cognition and in other fields, including health-related quality of life.

Multiple, correlated covariates associated with differential item functioning (DIF): Accounting for language DIF when education levels differ across languages

PubMed Central

Gibbons, Laura E.; Crane, Paul K.; Mehta, Kala M.; Pedraza, Otto; Tang, Yuxiao; Manly, Jennifer J.; Narasimhalu, Kaavya; Teresi, Jeanne; Jones, Richard N.; Mungas, Dan

2012-01-01

Differential item functioning (DIF) occurs when a test item has different statistical properties in subgroups, controlling for the underlying ability measured by the test. DIF assessment is necessary when evaluating measurement bias in tests used across different language groups. However, other factors such as educational attainment can differ across language groups, and DIF due to these other factors may also exist. How to conduct DIF analyses in the presence of multiple, correlated factors remains largely unexplored. This study assessed DIF related to Spanish versus English language in a 44-item object naming test. Data come from a community-based sample of 1,755 Spanish- and English-speaking older adults. We compared simultaneous accounting, a new strategy for handling differences in educational attainment across language groups, with existing methods. Compared to other methods, simultaneously accounting for language- and education-related DIF yielded salient differences in some object naming scores, particularly for Spanish speakers with at least 9 years of education. Accounting for factors that vary across language groups can be important when assessing language DIF. The use of simultaneous accounting will be relevant to other cross-cultural studies in cognition and in other fields, including health-related quality of life. PMID:22900138

Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1000 studies

NASA Astrophysics Data System (ADS)

Udupa, Jayaram K.; Nyul, Laszlo G.; Ge, Yulin; Grossman, Robert I.

2000-06-01

Multiple Sclerosis (MS) is an acquired disease of the central nervous system. Subjective cognitive and ambulatory test scores on a scale called EDSS are currently utilized to assess the disease severity. Various MRI protocols are being investigated to study the disease based on how it manifests itself in the images. In an attempt to eventually replace EDSS by an objective measure to assess the natural course of the disease and its response to therapy, we have developed image segmentation methods based on fuzzy connectedness to quantify various objects in multiprotocol MRI. These include the macroscopic objects such as lesions, the gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and brain parenchyma as well as the microscopic aspects of the diseased WM. Over 1000 studies have been processed to date. By far the strongest correlations with the clinical measures were demonstrated by the Magnetization Transfer Ratio (MTR) histogram parameters obtained for the various segmented tissue regions emphasizing the importance of considering the microscopic/diffused nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with the clinical measures indicating that brain atrophy is an important indicator of the disease. Fuzzy connectedness is a viable segmentation method for studying MS.

Serum betatrophin levels are increased and associated with insulin resistance in patients with polycystic ovary syndrome.

PubMed

Qu, Qinglan; Zhao, Dongmei; Zhang, Fengrong; Bao, Hongchu; Yang, Qiuhua

2017-02-01

Objective Betatrophin is a newly identified circulating protein that is significantly associated with type 2 diabetes mellitus (T2DM), adiposity, and metabolic syndrome. The aim of this study was to investigate whether betatrophin levels and polycystic ovary syndrome (PCOS) were associated. Methods Circulating betatrophin levels were measured in 162 patients with PCOS and 156 matched control females using specific enzyme-linked immunosorbent assay kits. Correlations between betatrophin levels and PCOS incidence as well as multiple key endocrine PCOS parameters were analyzed using multiple statistical methods. Results Betatrophin levels were significantly increased in patients with PCOS (685.3 ± 27.7 vs. 772.6 ± 42.5 pg/ml). When sub-grouping all investigated subjects according to the presence of insulin resistance, women with PCOS and insulin resistance exhibited markedly higher betatrophin concentrations. Furthermore, betatrophin levels were significantly correlated with fasting insulin levels and homeostatic model assessment of insulin resistance only in females with PCOS ( r = 0.531 and r = 0.628, respectively). Conclusion We provide the first report that betatrophin is strongly associated with PCOS. This study suggests that betatrophin may potentially serve as an independent predictor for the development of PCOS in at-risk women, especially those with insulin resistance.

Creative females have larger white matter structures: Evidence from a large sample study.

PubMed

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

2017-01-01

The importance of brain connectivity for creativity has been theoretically suggested and empirically demonstrated. Studies have shown sex differences in creativity measured by divergent thinking (CMDT) as well as sex differences in the structural correlates of CMDT. However, the relationships between regional white matter volume (rWMV) and CMDT and associated sex differences have never been directly investigated. In addition, structural studies have shown poor replicability and inaccuracy of multiple comparisons over the whole brain. To address these issues, we used the data from a large sample of healthy young adults (776 males and 560 females; mean age: 20.8 years, SD = 0.8). We investigated the relationship between CMDT and WMV using the newest version of voxel-based morphometry (VBM). We corrected for multiple comparisons over whole brain using the permutation-based method, which is known to be quite accurate and robust. Significant positive correlations between rWMV and CMDT scores were observed in widespread areas below the neocortex specifically in females. These associations with CMDT were not observed in analyses of fractional anisotropy using diffusion tensor imaging. Using rigorous methods, our findings further supported the importance of brain connectivity for creativity as well as its female-specific association. Hum Brain Mapp 38:414-430, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The effect of multiple stressors on salt marsh end-of-season biomass

USGS Publications Warehouse

Visser, J.M.; Sasser, C.E.; Cade, B.S.

2006-01-01

It is becoming more apparent that commonly used statistical methods (e.g., analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity, air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass. ?? 2006 Estuarine Research Federation.

The effect of multiple stressors on salt marsh end-of-season biomass

USGS Publications Warehouse

Visser, J.M.; Sasser, C.E.; Cade, B.S.

2006-01-01

It is becoming more apparent that commonly used statistical methods (e.g. analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass.

Artificial neural networks environmental forecasting in comparison with multiple linear regression technique: From heavy metals to organic micropollutants screening in agricultural soils

NASA Astrophysics Data System (ADS)

Bonelli, Maria Grazia; Ferrini, Mauro; Manni, Andrea

2016-12-01

The assessment of metals and organic micropollutants contamination in agricultural soils is a difficult challenge due to the extensive area used to collect and analyze a very large number of samples. With Dioxins and dioxin-like PCBs measurement methods and subsequent the treatment of data, the European Community advises the develop low-cost and fast methods allowing routing analysis of a great number of samples, providing rapid measurement of these compounds in the environment, feeds and food. The aim of the present work has been to find a method suitable to describe the relations occurring between organic and inorganic contaminants and use the value of the latter in order to forecast the former. In practice, the use of a metal portable soil analyzer coupled with an efficient statistical procedure enables the required objective to be achieved. Compared to Multiple Linear Regression, the Artificial Neural Networks technique has shown to be an excellent forecasting method, though there is no linear correlation between the variables to be analyzed.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

PubMed

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Locating non-volcanic tremor along the San Andreas Fault using a multiple array source imaging technique

USGS Publications Warehouse

Ryberg, T.; Haberland, C.H.; Fuis, G.S.; Ellsworth, W.L.; Shelly, D.R.

2010-01-01

Non-volcanic tremor (NVT) has been observed at several subduction zones and at the San Andreas Fault (SAF). Tremor locations are commonly derived by cross-correlating envelope-transformed seismic traces in combination with source-scanning techniques. Recently, they have also been located by using relative relocations with master events, that is low-frequency earthquakes that are part of the tremor; locations are derived by conventional traveltime-based methods. Here we present a method to locate the sources of NVT using an imaging approach for multiple array data. The performance of the method is checked with synthetic tests and the relocation of earthquakes. We also applied the method to tremor occurring near Cholame, California. A set of small-aperture arrays (i.e. an array consisting of arrays) installed around Cholame provided the data set for this study. We observed several tremor episodes and located tremor sources in the vicinity of SAF. During individual tremor episodes, we observed a systematic change of source location, indicating rapid migration of the tremor source along SAF. ?? 2010 The Authors Geophysical Journal International ?? 2010 RAS.

Comparison of Different Shrinkage Formulas in Estimating Population Multiple Correlation Coefficients.

ERIC Educational Resources Information Center

Carter, David S.

1979-01-01

There are a variety of formulas for reducing the positive bias which occurs in estimating R squared in multiple regression or correlation equations. Five different formulas are evaluated in a Monte Carlo study, and recommendations are made. (JKS)