Allowing for Correlations between Correlations in Random-Effects Meta-Analysis of Correlation Matrices

ERIC Educational Resources Information Center

Prevost, A. Toby; Mason, Dan; Griffin, Simon; Kinmonth, Ann-Louise; Sutton, Stephen; Spiegelhalter, David

2007-01-01

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of…

The Effects of Positively and Negatively Worded Items on the Factor Structure of the UCLA Loneliness Scale

ERIC Educational Resources Information Center

Dodeen, Hamzeh

2015-01-01

The purpose of this study was to evaluate the factor structure of the University of California, Los Angeles (UCLA) Loneliness Scale and examine possible wording effects on a sample of 1,429 students from the United Arab Emirates University. Correlated traits-correlated uniqueness as well as correlated traits-correlated methods were used to examine…

Accuracy Evaluation of the Unified P-Value from Combining Correlated P-Values

PubMed Central

Alves, Gelio; Yu, Yi-Kuo

2014-01-01

Meta-analysis methods that combine -values into a single unified -value are frequently employed to improve confidence in hypothesis testing. An assumption made by most meta-analysis methods is that the -values to be combined are independent, which may not always be true. To investigate the accuracy of the unified -value from combining correlated -values, we have evaluated a family of statistical methods that combine: independent, weighted independent, correlated, and weighted correlated -values. Statistical accuracy evaluation by combining simulated correlated -values showed that correlation among -values can have a significant effect on the accuracy of the combined -value obtained. Among the statistical methods evaluated those that weight -values compute more accurate combined -values than those that do not. Also, statistical methods that utilize the correlation information have the best performance, producing significantly more accurate combined -values. In our study we have demonstrated that statistical methods that combine -values based on the assumption of independence can produce inaccurate -values when combining correlated -values, even when the -values are only weakly correlated. Therefore, to prevent from drawing false conclusions during hypothesis testing, our study advises caution be used when interpreting the -value obtained from combining -values of unknown correlation. However, when the correlation information is available, the weighting-capable statistical method, first introduced by Brown and recently modified by Hou, seems to perform the best amongst the methods investigated. PMID:24663491

Correlated uncertainties in Monte Carlo reaction rate calculations

NASA Astrophysics Data System (ADS)

Longland, Richard

2017-07-01

Context. Monte Carlo methods have enabled nuclear reaction rates from uncertain inputs to be presented in a statistically meaningful manner. However, these uncertainties are currently computed assuming no correlations between the physical quantities that enter those calculations. This is not always an appropriate assumption. Astrophysically important reactions are often dominated by resonances, whose properties are normalized to a well-known reference resonance. This insight provides a basis from which to develop a flexible framework for including correlations in Monte Carlo reaction rate calculations. Aims: The aim of this work is to develop and test a method for including correlations in Monte Carlo reaction rate calculations when the input has been normalized to a common reference. Methods: A mathematical framework is developed for including correlations between input parameters in Monte Carlo reaction rate calculations. The magnitude of those correlations is calculated from the uncertainties typically reported in experimental papers, where full correlation information is not available. The method is applied to four illustrative examples: a fictional 3-resonance reaction, 27Al(p, γ)28Si, 23Na(p, α)20Ne, and 23Na(α, p)26Mg. Results: Reaction rates at low temperatures that are dominated by a few isolated resonances are found to minimally impacted by correlation effects. However, reaction rates determined from many overlapping resonances can be significantly affected. Uncertainties in the 23Na(α, p)26Mg reaction, for example, increase by up to a factor of 5. This highlights the need to take correlation effects into account in reaction rate calculations, and provides insight into which cases are expected to be most affected by them. The impact of correlation effects on nucleosynthesis is also investigated.

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

PubMed

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

2018-04-20

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

Optimized effective potential method and application to static RPA correlation

NASA Astrophysics Data System (ADS)

Fukazawa, Taro; Akai, Hisazumi

2015-03-01

The optimized effective potential (OEP) method is a promising technique for calculating the ground state properties of a system within the density functional theory. However, it is not widely used as its computational cost is rather high and, also, some ambiguity remains in the theoretical framework. In order to overcome these problems, we first introduced a method that accelerates the OEP scheme in a static RPA-level correlation functional. Second, the Krieger-Li-Iafrate (KLI) approximation is exploited to solve the OEP equation. Although seemingly too crude, this approximation did not reduce the accuracy of the description of the magnetic transition metals (Fe, Co, and Ni) examined here, the magnetic properties of which are rather sensitive to correlation effects. Finally, we reformulated the OEP method to render it applicable to the direct RPA correlation functional and other, more precise, functionals. Emphasis is placed on the following three points of the discussion: (i) level-crossing at the Fermi surface is taken into account; (ii) eigenvalue variations in a Kohn-Sham functional are correctly treated; and (iii) the resultant OEP equation is different from those reported to date.

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.

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

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

NASA Astrophysics Data System (ADS)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

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

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals.

PubMed

Xu, Yinlin; Ma, Qianli D Y; Schmitt, Daniel T; Bernaola-Galván, Pedro; Ivanov, Plamen Ch

2011-11-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals

PubMed Central

Xu, Yinlin; Ma, Qianli D.Y.; Schmitt, Daniel T.; Bernaola-Galván, Pedro; Ivanov, Plamen Ch.

2014-01-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences. PMID:25392599

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Cross-correlation photothermal optical coherence tomography with high effective resolution.

PubMed

Tang, Peijun; Liu, Shaojie; Chen, Junbo; Yuan, Zhiling; Xie, Bingkai; Zhou, Jianhua; Tang, Zhilie

2017-12-01

We developed a cross-correlation photothermal optical coherence tomography (CC-PTOCT) system for photothermal imaging with high lateral and axial resolution. The CC-PTOCT system consists of a phase-sensitive OCT system, a modulated pumping laser, and a digital cross-correlator. The pumping laser was used to induce the photothermal effect in the sample, causing a slight phase modulation of the OCT signals. A spatial phase differentiation method was employed to reduce phase accumulation. The noise brought by the phase differentiation method and the strong background noise were suppressed efficiently by the cross-correlator, which was utilized to extract the photothermal signals from the modulated signals. Combining the cross-correlation technique with spatial phase differentiation can improve both lateral and axial resolution of the PTOCT imaging system. Clear photothermal images of blood capillaries of a mouse ear in vivo were successfully obtained with high lateral and axial resolution. The experimental results demonstrated that this system can enhance the effective transverse resolution, effective depth resolution, and contrast of the PTOCT image effectively, aiding the ongoing development of the accurate 3D functional imaging.

Spatial correlation of shear-wave velocity in the San Francisco Bay Area sediments

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.

2007-01-01

Ground motions recorded within sedimentary basins are variable over short distances. One important cause of the variability is that local soil properties are variable at all scales. Regional hazard maps developed for predicting site effects are generally derived from maps of surficial geology; however, recent studies have shown that mapped geologic units do not correlate well with the average shear-wave velocity of the upper 30 m, Vs(30). We model the horizontal variability of near-surface soil shear-wave velocity in the San Francisco Bay Area to estimate values in unsampled locations in order to account for site effects in a continuous manner. Previous geostatistical studies of soil properties have shown horizontal correlations at the scale of meters to tens of meters while the vertical correlations are on the order of centimeters. In this paper we analyze shear-wave velocity data over regional distances and find that surface shear-wave velocity is correlated at horizontal distances up to 4 km based on data from seismic cone penetration tests and the spectral analysis of surface waves. We propose a method to map site effects by using geostatistical methods based on the shear-wave velocity correlation structure within a sedimentary basin. If used in conjunction with densely spaced shear-wave velocity profiles in regions of high seismic risk, geostatistical methods can produce reliable continuous maps of site effects. ?? 2006 Elsevier Ltd. All rights reserved.

Correlation Filter Learning Toward Peak Strength for Visual Tracking.

PubMed

Sui, Yao; Wang, Guanghui; Zhang, Li

2018-04-01

This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance. This paper aims at solving this issue and proposes a novel algorithm to learn the correlation filter. The proposed approach, by imposing an elastic net constraint on the filter, can adaptively eliminate those distractive features in the correlation filtering. A new peak strength metric is proposed to measure the discriminative capability of the learned correlation filter. It is demonstrated that the proposed approach effectively strengthens the peak of the correlation response, leading to more discriminative performance than previous methods. Extensive experiments on a challenging visual tracking benchmark demonstrate that the proposed tracker outperforms most state-of-the-art methods.

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

Generalized interferometry - I: theory for interstation correlations

NASA Astrophysics Data System (ADS)

Fichtner, Andreas; Stehly, Laurent; Ermert, Laura; Boehm, Christian

2017-02-01

We develop a general theory for interferometry by correlation that (i) properly accounts for heterogeneously distributed sources of continuous or transient nature, (ii) fully incorporates any type of linear and nonlinear processing, such as one-bit normalization, spectral whitening and phase-weighted stacking, (iii) operates for any type of medium, including 3-D elastic, heterogeneous and attenuating media, (iv) enables the exploitation of complete correlation waveforms, including seemingly unphysical arrivals, and (v) unifies the earthquake-based two-station method and ambient noise correlations. Our central theme is not to equate interferometry with Green function retrieval, and to extract information directly from processed interstation correlations, regardless of their relation to the Green function. We demonstrate that processing transforms the actual wavefield sources and actual wave propagation physics into effective sources and effective wave propagation. This transformation is uniquely determined by the processing applied to the observed data, and can be easily computed. The effective forward model, that links effective sources and propagation to synthetic interstation correlations, may not be perfect. A forward modelling error, induced by processing, describes the extent to which processed correlations can actually be interpreted as proper correlations, that is, as resulting from some effective source and some effective wave propagation. The magnitude of the forward modelling error is controlled by the processing scheme and the temporal variability of the sources. Applying adjoint techniques to the effective forward model, we derive finite-frequency Fréchet kernels for the sources of the wavefield and Earth structure, that should be inverted jointly. The structure kernels depend on the sources of the wavefield and the processing scheme applied to the raw data. Therefore, both must be taken into account correctly in order to make accurate inferences on Earth structure. Not making any restrictive assumptions on the nature of the wavefield sources, our theory can be applied to earthquake and ambient noise data, either separately or combined. This allows us (i) to locate earthquakes using interstation correlations and without knowledge of the origin time, (ii) to unify the earthquake-based two-station method and noise correlations without the need to exclude either of the two data types, and (iii) to eliminate the requirement to remove earthquake signals from noise recordings prior to the computation of correlation functions. In addition to the basic theory for acoustic wavefields, we present numerical examples for 2-D media, an extension to the most general viscoelastic case, and a method for the design of optimal processing schemes that eliminate the forward modelling error completely. This work is intended to provide a comprehensive theoretical foundation of full-waveform interferometry by correlation, and to suggest improvements to current passive monitoring methods.

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

Topics in Chemical Instrumentation. The Fourier Transform in Chemistry-NMR: Part 4. Two-Dimensional Methods.

ERIC Educational Resources Information Center

Williams, Kathryn R.; King, Roy W.

1990-01-01

Examined are some of the types of two-dimensional spectra. Their application to nuclear magnetic resonance for the elucidation of molecular structure is discussed. Included are J spectroscopy, H-H correlation spectroscopy, heteronuclear correlation spectroscopy, carbon-carbon correlation, nuclear Overhauser effect correlation, experimental…

Validity of three clinical performance assessments of internal medicine clerks.

PubMed

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

1995-06-01

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

The correcting method for the estimation of correlation energies of MF2 (M = Be, Mg, Ca) set molecules

NASA Astrophysics Data System (ADS)

Zhuo, Shuping; Wei, Jichong; Ju, Guanzhi

The intrapair and interpair correlation energies of MF2 (M = Be, Mg, Ca) set molecules are calculated and analysed, and the transferability of inner core correlation effects of Mδ+ are investigated. A detailed analysis of the comparison of correlation energies of neutral atoms with their corresponding ions of Mδ+ and Fδ-/2 is given in terms of the correlation contribution of this component. The study reveals that the total correlation energy of MF2 molecules can be obtained by summing the correlation contributions of Mδ+ and two Fδ-/2 components. This simple estimation method does shed light on the importance of searching useful means for the calculation of electron correlation energy for large biological systems.

A modified cross-correlation method for white-light optical fiber extrinsic Fabry-Perot interferometric hydrogen sensors

NASA Astrophysics Data System (ADS)

Yang, Zhen; Zhang, Min; Liao, Yanbiao; Lai, Shurong; Tian, Qian; Li, Qisheng; Zhang, Yi; Zhuang, Zhi

2009-11-01

An extrinsic Fabry-Perot interferometric (EFPI) optical fiber hydrogen sensor based on palladium silver (Pd-Ag) film is designed for hydrogen leakage detection. A modified cross correlation signal processing method for an optical fiber EFPI hydrogen sensor is presented. As the applying of a special correlating factor which advises the effect on the fringe visibility of the gap length and wavelength, the cross correlation method has a high accuracy which is insensitive to light source power drift or changes in attenuation in the fiber, and the segment search method is employed to reduce computation and demodulating speed is fast. The Fabry-Perot gap length resolution of better than 0.2nm is achieved in a certain concentration of hydrogen.

Multilevel Modeling with Correlated Effects

ERIC Educational Resources Information Center

Kim, Jee-Seon; Frees, Edward W.

2007-01-01

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…

Correlation and prediction of gaseous diffusion coefficients.

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Density matrix renormalization group with efficient dynamical electron correlation through range separation

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

Hedegård, Erik Donovan, E-mail: erik.hedegard@phys.chem.ethz.ch; Knecht, Stefan; Reiher, Markus, E-mail: markus.reiher@phys.chem.ethz.ch

2015-06-14

We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous description of dynamical and static electron-correlation effects in multiconfigurational electronic structure problems.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

Impact of correlation of predictors on discrimination of risk models in development and external populations.

PubMed

Kundu, Suman; Mazumdar, Madhu; Ferket, Bart

2017-04-19

The area under the ROC curve (AUC) of risk models is known to be influenced by differences in case-mix and effect size of predictors. The impact of heterogeneity in correlation among predictors has however been under investigated. We sought to evaluate how correlation among predictors affects the AUC in development and external populations. We simulated hypothetical populations using two different methods based on means, standard deviations, and correlation of two continuous predictors. In the first approach, the distribution and correlation of predictors were assumed for the total population. In the second approach, these parameters were modeled conditional on disease status. In both approaches, multivariable logistic regression models were fitted to predict disease risk in individuals. Each risk model developed in a population was validated in the remaining populations to investigate external validity. For both approaches, we observed that the magnitude of the AUC in the development and external populations depends on the correlation among predictors. Lower AUCs were estimated in scenarios of both strong positive and negative correlation, depending on the direction of predictor effects and the simulation method. However, when adjusted effect sizes of predictors were specified in the opposite directions, increasingly negative correlation consistently improved the AUC. AUCs in external validation populations were higher or lower than in the derivation cohort, even in the presence of similar predictor effects. Discrimination of risk prediction models should be assessed in various external populations with different correlation structures to make better inferences about model generalizability.

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.

Analytic uncertainty and sensitivity analysis of models with input correlations

NASA Astrophysics Data System (ADS)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Further Investigating Method Effects Associated with Negatively Worded Items on Self-Report Surveys

ERIC Educational Resources Information Center

DiStefano, Christine; Motl, Robert W.

2006-01-01

This article used multitrait-multimethod methodology and covariance modeling for an investigation of the presence and correlates of method effects associated with negatively worded items on the Rosenberg Self-Esteem (RSE) scale (Rosenberg, 1989) using a sample of 757 adults. Results showed that method effects associated with negative item phrasing…

Application of the differentiation process into the correlation-based leak detection in urban pipeline networks

NASA Astrophysics Data System (ADS)

Gao, Yan; Liu, Yuyou; Ma, Yifan; Cheng, Xiaobin; Yang, Jun

2018-11-01

One major challenge currently facing pipeline networks across the world is the improvement of leak detection technologies in urban environments. There is an imperative to locate accurately leaks in buried water pipes to avoid serious environmental, social and economic consequences. Much attention has been paid to time delay estimation (TDE) in determining the position of a leak by utilising cross-correlation, which has been proven to be effective with varying degrees of success over the past half century. Previous research in published literature has demonstrated the effectiveness of the pre-whitening process for accentuating the peak in the cross-correlation associated with the time delay. This paper is concerned with the implementation of the differentiation process for TDE, with particular focus on the problem of determining a leak in pipelines by means of pipe pressure measurements. Rather than the pre-whitening operation, the proposed cross-correlation via the differentiation process, termed here DIF, changes the characteristics of the pipe system so that the pipe effectively acts as a band-pass filter. This method has the potential to eliminate some ambiguity caused by the interference at low frequencies and to allow more high frequency information to pass. Given an appropriate differentiation order, a more pronounced and reliable peak is obtained in the cross-correlation result. The use of differentiation process may provide a viable cross-correlation method suited to water leak detection. Its performance in relation to leak detection is further compared to the basic cross-correlation and pre-whitening methods for TDE in detecting a leak from actual PVC water pipes. Experimental results are presented to show an additional property of the DIF compensating for the resonance effects that may exist in cross-spectral density measurements, and hence better performance for TDE.

Report on objective ride quality evaluation

NASA Technical Reports Server (NTRS)

Wambold, J. C.; Park, W. H.

1974-01-01

The correlation of absorbed power as an objective ride measure to the subjective evaluation for the bus data was investigated. For some individual bus rides the correlations were poor, but when a sufficient number of rides was used to give reasonable sample base, an excellent correlation was obtained. The following logarithmical function was derived: S = 1.7245 1n (39.6849 AP), where S = one subjective rating of the ride; and AP = the absorbed power in watts. A six-degree-of-freedom method developed for aircraft data was completed. Preliminary correlation of absorbed power with ISO standards further enhances the bus ride and absorbed power correlation numbers since the AP's obtained are of the same order of magnitude for both correlations. While it would then appear that one could just use ISO standards, there is no way to add the effect of three degrees of freedom. The absorbed power provides a method of adding the effects due to the three major directions plus the pitch and roll.

Classical Wigner method with an effective quantum force: application to reaction rates.

PubMed

Poulsen, Jens Aage; Li, Huaqing; Nyman, Gunnar

2009-07-14

We construct an effective "quantum force" to be used in the classical molecular dynamics part of the classical Wigner method when determining correlation functions. The quantum force is obtained by estimating the most important short time separation of the Feynman paths that enter into the expression for the correlation function. The evaluation of the force is then as easy as classical potential energy evaluations. The ideas are tested on three reaction rate problems. The resulting transmission coefficients are in much better agreement with accurate results than transmission coefficients from the ordinary classical Wigner method.

Information Encoding on a Pseudo Random Noise Radar Waveform

DTIC Science & Technology

2013-03-01

quadrature mirror filter bank (QMFB) tree diagram [18] . . . . . . . . . . . 18 2.7 QMFB layer 3 contour plot for 7-bit barker code binary phase shift...test signal . . . . . . . . 20 2.9 Block diagram of the FFT accumulation method (FAM) time smoothing method to estimate the spectral correlation ... Samples A m pl itu de (b) Correlator output for an WGN pulse in a AWGN channel Figure 2.2: Effectiveness of correlation for SNR = -10 dB 10 2.3 Radar

Radiative interactions in multi-dimensional chemically reacting flows using Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, Surendra N.

1994-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The amount and transfer of the emitted radiative energy in a finite volume element within a medium are considered in an exact manner. The spectral correlation between transmittances of two different segments of the same path in a medium makes the statistical relationship different from the conventional relationship, which only provides the non-correlated results for nongray methods is discussed. Validation of the Monte Carlo formulations is conducted by comparing results of this method of other solutions. In order to further establish the validity of the MCM, a relatively simple problem of radiative interactions in laminar parallel plate flows is considered. One-dimensional correlated Monte Carlo formulations are applied to investigate radiative heat transfer. The nongray Monte Carlo solutions are also obtained for the same problem and they also essentially match the available analytical solutions. the exact correlated and non-correlated Monte Carlo formulations are very complicated for multi-dimensional systems. However, by introducing the assumption of an infinitesimal volume element, the approximate correlated and non-correlated formulations are obtained which are much simpler than the exact formulations. Consideration of different problems and comparison of different solutions reveal that the approximate and exact correlated solutions agree very well, and so do the approximate and exact non-correlated solutions. However, the two non-correlated solutions have no physical meaning because they significantly differ from the correlated solutions. An accurate prediction of radiative heat transfer in any nongray and multi-dimensional system is possible by using the approximate correlated formulations. Radiative interactions are investigated in chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The governing equations are based on the fully elliptic Navier-Stokes equations. Chemical reaction mechanisms were described by a finite rate chemistry model. The correlated Monte Carlo method developed earlier was employed to simulate multi-dimensional radiative heat transfer. Results obtained demonstrate that radiative effects on the flowfield are minimal but radiative effects on the wall heat transfer are significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and nozzle size on the radiative and conductive wall fluxes.

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle.

PubMed

Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu

2017-02-26

In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions.

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

PubMed Central

Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu

2017-01-01

In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions. PMID:28245634

Structural predictions for Correlated Electron Materials Using the Functional Dynamical Mean Field Theory Approach

NASA Astrophysics Data System (ADS)

Haule, Kristjan

2018-04-01

The Dynamical Mean Field Theory (DMFT) in combination with the band structure methods has been able to address reach physics of correlated materials, such as the fluctuating local moments, spin and orbital fluctuations, atomic multiplet physics and band formation on equal footing. Recently it is getting increasingly recognized that more predictive ab-initio theory of correlated systems needs to also address the feedback effect of the correlated electronic structure on the ionic positions, as the metal-insulator transition is almost always accompanied with considerable structural distortions. We will review recently developed extension of merger between the Density Functional Theory (DFT) and DMFT method, dubbed DFT+ embedded DMFT (DFT+eDMFT), whichsuccessfully addresses this challenge. It is based on the stationary Luttinger-Ward functional to minimize the numerical error, it subtracts the exact double-counting of DFT and DMFT, and implements self-consistent forces on all atoms in the unit cell. In a few examples, we will also show how the method elucidated the important feedback effect of correlations on crystal structure in rare earth nickelates to explain the mechanism of the metal-insulator transition. The method showed that such feedback effect is also essential to understand the dynamic stability of the high-temperature body-centered cubic phase of elemental iron, and in particular it predicted strong enhancement of the electron-phonon coupling over DFT values in FeSe, which was very recently verified by pioneering time-domain experiment.

Effect of in-medium nucleon-nucleon cross section on proton-proton momentum correlation in intermediate-energy heavy-ion collisions

NASA Astrophysics Data System (ADS)

Wang, Ting-Ting; Ma, Yu-Gang; Zhang, Chun-Jian; Zhang, Zheng-Qiao

2018-03-01

The proton-proton momentum correlation function from different rapidity regions is systematically investigated for the Au + Au collisions at different impact parameters and different energies from 400 A MeV to 1500 A MeV in the framework of the isospin-dependent quantum molecular dynamics model complemented by the Lednický-Lyuboshitz analytical method. In particular, the in-medium nucleon-nucleon cross-section dependence of the correlation function is brought into focus, while the impact parameter and energy dependence of the momentum correlation function are also explored. The sizes of the emission source are extracted by fitting the momentum correlation functions using the Gaussian source method. We find that the in-medium nucleon-nucleon cross section obviously influences the proton-proton momentum correlation function, which is from the whole-rapidity or projectile or target rapidity region at smaller impact parameters, but there is no effect on the mid-rapidity proton-proton momentum correlation function, which indicates that the emission mechanism differs between projectile or target rapidity and mid-rapidity protons.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

Evaluation method based on the image correlation for laser jamming image

NASA Astrophysics Data System (ADS)

Che, Jinxi; Li, Zhongmin; Gao, Bo

2013-09-01

The jamming effectiveness evaluation of infrared imaging system is an important part of electro-optical countermeasure. The infrared imaging devices in the military are widely used in the searching, tracking and guidance and so many other fields. At the same time, with the continuous development of laser technology, research of laser interference and damage effect developed continuously, laser has been used to disturbing the infrared imaging device. Therefore, the effect evaluation of the infrared imaging system by laser has become a meaningful problem to be solved. The information that the infrared imaging system ultimately present to the user is an image, so the evaluation on jamming effect can be made from the point of assessment of image quality. The image contains two aspects of the information, the light amplitude and light phase, so the image correlation can accurately perform the difference between the original image and disturbed image. In the paper, the evaluation method of digital image correlation, the assessment method of image quality based on Fourier transform, the estimate method of image quality based on error statistic and the evaluation method of based on peak signal noise ratio are analysed. In addition, the advantages and disadvantages of these methods are analysed. Moreover, the infrared disturbing images of the experiment result, in which the thermal infrared imager was interfered by laser, were analysed by using these methods. The results show that the methods can better reflect the jamming effects of the infrared imaging system by laser. Furthermore, there is good consistence between evaluation results by using the methods and the results of subjective visual evaluation. And it also provides well repeatability and convenient quantitative analysis. The feasibility of the methods to evaluate the jamming effect was proved. It has some extent reference value for the studying and developing on electro-optical countermeasures equipments and effectiveness evaluation.

Double Photoionization of helium atom using Screening Potential Approach

NASA Astrophysics Data System (ADS)

Saha, Haripada

2014-05-01

The triple differential cross section for double Photoionization of helium atom will be investigated using our recently extended MCHF method. It is well known that electron correlation effects in both the initial and the final states are very important. To incorporate these effects we will use the multi-configuration Hartree-Fock method to account for electron correlation in the initial state. The electron correlation in the final state will be taken into account using the angle-dependent screening potential approximation. The triple differential cross section (TDCS) will be calculated for 20 eV photon energy, which has experimental results. Our results will be compared with available experimental and the theoretical observations.

Towards a First-Principles Determination of Effective Coulomb Interactions in Correlated Electron Materials: Role of Intershell Interactions

NASA Astrophysics Data System (ADS)

Seth, Priyanka; Hansmann, Philipp; van Roekeghem, Ambroise; Vaugier, Loig; Biermann, Silke

2017-08-01

The determination of the effective Coulomb interactions to be used in low-energy Hamiltonians for materials with strong electronic correlations remains one of the bottlenecks for parameter-free electronic structure calculations. We propose and benchmark a scheme for determining the effective local Coulomb interactions for charge-transfer oxides and related compounds. Intershell interactions between electrons in the correlated shell and ligand orbitals are taken into account in an effective manner, leading to a reduction of the effective local interactions on the correlated shell. Our scheme resolves inconsistencies in the determination of effective interactions as obtained by standard methods for a wide range of materials, and allows for a conceptual understanding of the relation of cluster model and dynamical mean field-based electronic structure calculations.

Towards a First-Principles Determination of Effective Coulomb Interactions in Correlated Electron Materials: Role of Intershell Interactions.

PubMed

Seth, Priyanka; Hansmann, Philipp; van Roekeghem, Ambroise; Vaugier, Loig; Biermann, Silke

2017-08-04

The determination of the effective Coulomb interactions to be used in low-energy Hamiltonians for materials with strong electronic correlations remains one of the bottlenecks for parameter-free electronic structure calculations. We propose and benchmark a scheme for determining the effective local Coulomb interactions for charge-transfer oxides and related compounds. Intershell interactions between electrons in the correlated shell and ligand orbitals are taken into account in an effective manner, leading to a reduction of the effective local interactions on the correlated shell. Our scheme resolves inconsistencies in the determination of effective interactions as obtained by standard methods for a wide range of materials, and allows for a conceptual understanding of the relation of cluster model and dynamical mean field-based electronic structure calculations.

Improved methods of performing coherent optical correlation

NASA Technical Reports Server (NTRS)

Husain-Abidi, A. S.

1972-01-01

Coherent optical correlators are described in which complex spatial filters are recorded by a quasi-Fourier transform method. The high-pass spatial filtering effects (due to the dynamic range of photographic films) normally encountered in Vander Lugt type complex filters are not present in this system. Experimental results for both transmittive as well as reflective objects are presented. Experiments are also performed by illuminating the object with diffused light. A correlator using paraboloidal mirror segments as the Fourier-transforming element is also described.

Relaxation method of compensation in an optical correlator

NASA Technical Reports Server (NTRS)

Juday, Richard D.; Daiuto, Brian J.

1987-01-01

An iterative method is proposed for the sharpening of programmable filters in a 4-f optical correlator. Continuously variable spatial light modulators (SLMs) permit the fine adjustment of optical processing filters so as to compensate for the departures from ideal behavior of a real optical system. Although motivated by the development of continuously variable phase-only SLMs, the proposed sharpening method is also applicable to amplitude modulators and, with appropriate adjustments, to binary modulators as well. A computer simulation is presented that illustrates the potential effectiveness of the method: an image is placed on the input to the correlator, and its corresponding phase-only filter is adjusted (allowed to relax) so as to produce a progressively brighter and more centralized peak in the correlation plane. The technique is highly robust against the form of the system's departure from ideal behavior.

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

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

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

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

PubMed

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

2018-01-01

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

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.

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.

Developing and evaluating a target-background similarity metric for camouflage detection.

PubMed

Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

2014-01-01

Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

Prediction of post-operative pulmonary function after lobectomy for primary lung cancer: A comparison among counting method, effective lobar volume, and lobar collapsibility using inspiratory/expiratory CT.

PubMed

Yabuuchi, Hidetake; Kawanami, Satoshi; Kamitani, Takeshi; Yonezawa, Masato; Yamasaki, Yuzo; Yamanouchi, Torahiko; Nagao, Michinobu; Okamoto, Tatsuro; Honda, Hiroshi

2016-11-01

To compare the predictabilities of postoperative pulmonary function after lobectomy for primary lung cancer among counting method, effective lobar volume, and lobar collapsibility. Forty-nine patients who underwent lobectomy for primary lung cancer were enrolled. All patients underwent inspiratory/expiratory CT and pulmonary function tests 2 weeks before surgery and postoperative pulmonary function tests 6-7 months after surgery. Pulmonary function losses (ΔFEV 1.0 and ΔVC) were calculated from the pulmonary function tests. Predictive postoperative pulmonary function losses (ppoΔFEV 1.0 and ppoΔVC) were calculated using counting method, effective volume, and lobar collapsibility. Correlations and agreements between ΔFEV 1.0 and ppoFEV 1.0 and those between ΔVC and ppoΔVC were tested among three methods using Spearman's correlation coefficient and Bland-Altman plots. ΔFEV 1.0 and ppoΔFEV 1.0insp-exp were strongly correlated (r=0.72), whereas ΔFEV 1.0 and ppoΔFEV 1.0count and ΔFEV 1.0 and Pred. ΔFEV 1.0eff.vol. were moderately correlated (r=0.50, 0.56). ΔVC and ppoΔVC eff.vol. (r=0.71) were strongly correlated, whereas ΔVC and ppoΔVC count , and ΔVC and ppoΔVC insp-exp were moderately correlated (r=0.55, 0.42). Volumetry from inspiratory/expiratory CT data could be useful to predict postoperative pulmonary function after lobectomy for primary lung cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analysis of Parent Perceptions on Effective School Correlates: A Springboard for Planning.

ERIC Educational Resources Information Center

Murray, David R.

This project was designed to solicit parental perceptions of Caroline Street Elementary School (Saratoga Springs, New York) in terms of Effective Schools, a method of assessing school improvement. Families (n=334) were asked to provide their perceptions regarding correlational characteristics identified as vital to successful school programs:…

Correlation, Breit and Quantum Electrodynamics effects on energy level and transition properties of W54+ ion

NASA Astrophysics Data System (ADS)

Ding, Xiaobin; Sun, Rui; Koike, Fumihiro; Kato, Daiji; Murakami, Izumi; Sakaue, Hiroyuki A.; Dong, Chenzhong

2017-03-01

The electron correlation effects and Breit interaction as well as Quantum Electro-Dynamics (QED) effects were expected to have important contribution to the energy level and transition properties of heavy highly charged ions. The ground states [Ne]3s23p63d2 and first excited states [Ne]3s23p53d3 of W54+ ion have been studied by using Multi-Configuration Dirac-Fock method with the implementation of Grasp2K package. A restricted active space method was employed to investigate the correlation contribution from different models. The Breit interaction and QED effects were taken into account in the relativistic configuration interaction calculation with the converged wavefunction. It is found that the correlation contribution from 3s and 3p orbital have important contribution to the energy level, transition wavelength and probability of the ground and the first excited state of W54+ ion. Contribution to the Topical Issue "Atomic and Molecular Data and their Applications", edited by Gordon W.F. Drake, Jung-Sik Yoon, Daiji Kato, Grzegorz Karwasz.

Population coding and decoding in a neural field: a computational study.

PubMed

Wu, Si; Amari, Shun-Ichi; Nakahara, Hiroyuki

2002-05-01

This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.

Determination of differential arrival times by cross-correlating worldwide seismological data

NASA Astrophysics Data System (ADS)

Godano, M.; Nolet, G.; Zaroli, C.

2012-12-01

Cross-correlation delays are the preferred body wave observables in global tomography. Heterogeneity is the main factor influencing delay times found by cross-correlation. Not only the waveform, but also the arrival time itself is affected by differences in seismic velocity encountered along the way. An accurate method for estimating differential times of seismic arrivals across a regional array by cross-correlation was developed by VanDecar and Crosson [1990]. For the estimation of global travel time delays in different frequency bands, Sigloch and Nolet [2006] developed a method for the estimation of body wave delays using a matched filter, which requires the separate estimation of the source time function. Sigloch et al. [2008] found that waveforms often cluster in and opposite the direction of rupture propagation on the fault, confirming that the directivity effect is a major factor in shaping the waveform of large events. We propose a generalization of the VanDecar-Crosson method to which we add a correction for the directivity effect in the seismological data. The new method allows large events to be treated without the need to estimate the source time function for the computation of a matched synthetic waveform. The procedure consists in (1) the detection of the directivity effect in the data and the determination of a rupture model (unilateral or bilateral) explaining the differences in pulse duration among the stations, (2) the determination of an apparent fault rupture length explaining the pulse durations, (3) the removal of the delay due to the directivity effect in the pulse duration , by stretching or contracting the seismograms for directive and anti-directive stations respectively and (4) the application of a generalized VanDecar and Crosson method using only delays between pairs of stations that have an acceptable correlation coefficient. We validate our method by performing tests on synthetic data. Results show that the error between theoretical and measured differential arrival time are significantly reduced for the corrected data. We illustrate our method on data from several real earthquakes.

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

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

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

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

An approach for estimating the magnetization direction of magnetic anomalies

NASA Astrophysics Data System (ADS)

Li, Jinpeng; Zhang, Yingtang; Yin, Gang; Fan, Hongbo; Li, Zhining

2017-02-01

An approach for estimating the magnetization direction of magnetic anomalies in the presence of remanent magnetization through correlation between normalized source strength (NSS) and reduced-to-the-pole (RTP) is proposed. The observation region was divided into several calculation areas and the RTP field was transformed using different assumed values of the magnetization directions. Following this, the cross-correlation between NSS and RTP field was calculated, and it was found that the correct magnetization direction was that corresponding to the maximum cross-correlation value. The approach was tested on both simulated and real magnetic data. The results showed that the approach was effective in a variety of situations and considerably reduced the effect of remanent magnetization. Thus, the method using NSS and RTP is more effective compared to other methods such as using the total magnitude anomaly and RTP.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-07-23

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]'), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal.

Performance of local correlation methods for halogen bonding: The case of Br{sub 2}–(H{sub 2}O){sub n},n = 4,5 clusters and Br{sub 2}@5{sup 12}6{sup 2} clathrate cage

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

Batista-Romero, Fidel A.; Bernal-Uruchurtu, Margarita I.; Hernández-Lamoneda, Ramón, E-mail: ramon@uaem.mx

The performance of local correlation methods is examined for the interactions present in clusters of bromine with water where the combined effect of hydrogen bonding (HB), halogen bonding (XB), and hydrogen-halogen (HX) interactions lead to many interesting properties. Local methods reproduce all the subtleties involved such as many-body effects and dispersion contributions provided that specific methodological steps are followed. Additionally, they predict optimized geometries that are nearly free of basis set superposition error that lead to improved estimates of spectroscopic properties. Taking advantage of the local correlation energy partitioning scheme, we compare the different interaction environments present in small clustersmore » and those inside the 5{sup 12}6{sup 2} clathrate cage. This analysis allows a clear identification of the reasons supporting the use of local methods for large systems where non-covalent interactions play a key role.« less

Electron correlation at the MgF2(110) surface: a comparison of incremental and local correlation methods.

PubMed

Hammerschmidt, Lukas; Maschio, Lorenzo; Müller, Carsten; Paulus, Beate

2015-01-13

We have applied the Method of Increments and the periodic Local-MP2 approach to the study of the (110) surface of magnesium fluoride, a system of significant interest in heterogeneous catalysis. After careful assessment of the approximations inherent in both methods, the two schemes, though conceptually different, are shown to yield nearly identical results. This remains true even when analyzed in fine detail through partition of the individual contribution to the total energy. This kind of partitioning also provides thorough insight into the electron correlation effects underlying the surface formation process, which are discussed in detail.

[Preliminary study on effective components of Tripterygium wilfordii for liver toxicity based on spectrum-effect correlation analysis].

PubMed

Zhao, Xiao-Mei; Pu, Shi-Biao; Zhao, Qing-Guo; Gong, Man; Wang, Jia-Bo; Ma, Zhi-Jie; Xiao, Xiao-He; Zhao, Kui-Jun

2016-08-01

In this paper, the spectrum-effect correlation analysis method was used to explore the main effective components of Tripterygium wilfordii for liver toxicity, and provide reference for promoting the quality control of T. wilfordii. Chinese medicine T.wilfordii was taken as the study object, and LC-Q-TOF-MS was used to characterize the chemical components in T. wilfordii samples from different areas, and their main components were initially identified after referring to the literature. With the normal human hepatocytes (LO2 cell line)as the carrier, acetaminophen as positive medicine, and cell inhibition rate as testing index, the simple correlation analysis and multivariate linear correlation analysis methods were used to screen the main components of T. wilfordii for liver toxicity. As a result, 10 kinds of main components were identified, and the spectrum-effect correlation analysis showed that triptolide may be the toxic component, which was consistent with previous results of traditional literature. Meanwhile it was found that tripterine and demethylzeylasteral may greatly contribute to liver toxicity in multivariate linear correlation analysis. T. wilfordii samples of different varieties or different origins showed large difference in quality, and the T. wilfordii from southwest China showed lower liver toxicity, while those from Hunan and Anhui province showed higher liver toxicity. This study will provide data support for further rational use of T. wilfordii and research on its liver toxicity ingredients. Copyright© by the Chinese Pharmaceutical Association.

Computational nanometrology of line-edge roughness: noise effects, cross-line correlations and the role of etch transfer

NASA Astrophysics Data System (ADS)

Constantoudis, Vassilios; Papavieros, George; Lorusso, Gian; Rutigliani, Vito; Van Roey, Frieda; Gogolides, Evangelos

2018-03-01

The aim of this paper is to investigate the role of etch transfer in two challenges of LER metrology raised by recent evolutions in lithography: the effects of SEM noise and the cross-line and edge correlations. The first comes from the ongoing scaling down of linewidths, which dictates SEM imaging with less scanning frames to reduce specimen damage and hence with more noise. During the last decade, it has been shown that image noise can be an important budget of the measured LER while systematically affects and alter the PSD curve of LER at high frequencies. A recent method for unbiased LER measurement is based on the systematic Fourier or correlation analysis to decompose the effects of noise from true LER (Fourier-Correlation filtering method). The success of the method depends on the PSD and HHCF curve. Previous experimental and model works have revealed that etch transfer affects the PSD of LER reducing its high frequency values. In this work, we estimate the noise contribution to the biased LER through PSD flat floor at high frequencies and relate it with the differences between the PSDs of lithography and etched LER. Based on this comparison, we propose an improvement of the PSD/HHCF-based method for noise-free LER measurement to include the missed high frequency real LER. The second issue is related with the increased density of lithographic patterns and the special characteristics of DSA and MP lithography patterns exhibits. In a previous work, we presented an enlarged LER characterization methodology for such patterns, which includes updated versions of the old metrics along with new metrics defined and developed to capture cross-edge and cross-line correlations. The fundamental concept has been the Line Center Roughness (LCR), the edge c-factor and the line c-factor correlation function and length quantifying the line fluctuations and the extent of cross-edge and cross-line correlations. In this work, we focus on the role of etch steps on cross-edge and line correlation metrics in SAQP data. We find that the spacer etch steps reduce edge correlations while etch steps with pattern transfer increase these. Furthermore, the density doubling and quadrupling increase edge correlations as well as cross-line correlations.

LEAKAGE CHARACTERISTICS OF BASE OF RIVERBANK BY SELF POTENTIAL METHOD AND EXAMINATION OF EFFECTIVENESS OF SELF POTENTIAL METHOD TO HEALTH MONITORING OF BASE OF RIVERBANK

NASA Astrophysics Data System (ADS)

Matsumoto, Kensaku; Okada, Takashi; Takeuchi, Atsuo; Yazawa, Masato; Uchibori, Sumio; Shimizu, Yoshihiko

Field Measurement of Self Potential Method using Copper Sulfate Electrode was performed in base of riverbank in WATARASE River, where has leakage problem to examine leakage characteristics. Measurement results showed typical S-shape what indicates existence of flow groundwater. The results agreed with measurement results by Ministry of Land, Infrastructure and Transport with good accuracy. Results of 1m depth ground temperature detection and Chain-Array detection showed good agreement with results of the Self Potential Method. Correlation between Self Potential value and groundwater velocity was examined model experiment. The result showed apparent correlation. These results indicate that the Self Potential Method was effective method to examine the characteristics of ground water of base of riverbank in leakage problem.

Importance of non-flow in mixed-harmonic multi-particle correlations in small collision systems

NASA Astrophysics Data System (ADS)

Huo, Peng; Gajdošová, Katarína; Jia, Jiangyong; Zhou, You

2018-02-01

Recently CMS Collaboration measured mixed-harmonic four-particle azimuthal correlations, known as symmetric cumulants SC (n , m), in pp and p+Pb collisions, and interpreted the non-zero SC (n , m) as evidence for long-range collectivity in these small collision systems. Using the PYTHIA and HIJING models which do not have genuine long-range collectivity, we show that the CMS results, obtained with standard cumulant method, could be dominated by non-flow effects associated with jet and dijets, especially in pp collisions. We show that the non-flow effects are largely suppressed using the recently proposed subevent cumulant methods by requiring azimuthal correlation between two or more pseudorapidity ranges. We argue that the reanalysis of SC (n , m) using the subevent method in experiments is necessary before they can used to provide further evidences for a long-range multi-particle collectivity and constraints on theoretical models in small collision systems.

Automated cerebral infarct volume measurement in follow-up noncontrast CT scans of patients with acute ischemic stroke.

PubMed

Boers, A M; Marquering, H A; Jochem, J J; Besselink, N J; Berkhemer, O A; van der Lugt, A; Beenen, L F; Majoie, C B

2013-08-01

Cerebral infarct volume as observed in follow-up CT is an important radiologic outcome measure of the effectiveness of treatment of patients with acute ischemic stroke. However, manual measurement of CIV is time-consuming and operator-dependent. The purpose of this study was to develop and evaluate a robust automated measurement of the CIV. The CIV in early follow-up CT images of 34 consecutive patients with acute ischemic stroke was segmented with an automated intensity-based region-growing algorithm, which includes partial volume effect correction near the skull, midline determination, and ventricle and hemorrhage exclusion. Two observers manually delineated the CIV. Interobserver variability of the manual assessments and the accuracy of the automated method were evaluated by using the Pearson correlation, Bland-Altman analysis, and Dice coefficients. The accuracy was defined as the correlation with the manual assessment as a reference standard. The Pearson correlation for the automated method compared with the reference standard was similar to the manual correlation (R = 0.98). The accuracy of the automated method was excellent with a mean difference of 0.5 mL with limits of agreement of -38.0-39.1 mL, which were more consistent than the interobserver variability of the 2 observers (-40.9-44.1 mL). However, the Dice coefficients were higher for the manual delineation. The automated method showed a strong correlation and accuracy with the manual reference measurement. This approach has the potential to become the standard in assessing the infarct volume as a secondary outcome measure for evaluating the effectiveness of treatment.

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.

Random-Phase Approximation Methods

NASA Astrophysics Data System (ADS)

Chen, Guo P.; Voora, Vamsee K.; Agee, Matthew M.; Balasubramani, Sree Ganesh; Furche, Filipp

2017-05-01

Random-phase approximation (RPA) methods are rapidly emerging as cost-effective validation tools for semilocal density functional computations. We present the theoretical background of RPA in an intuitive rather than formal fashion, focusing on the physical picture of screening and simple diagrammatic analysis. A new decomposition of the RPA correlation energy into plasmonic modes leads to an appealing visualization of electron correlation in terms of charge density fluctuations. Recent developments in the areas of beyond-RPA methods, RPA correlation potentials, and efficient algorithms for RPA energy and property calculations are reviewed. The ability of RPA to approximately capture static correlation in molecules is quantified by an analysis of RPA natural occupation numbers. We illustrate the use of RPA methods in applications to small-gap systems such as open-shell d- and f-element compounds, radicals, and weakly bound complexes, where semilocal density functional results exhibit strong functional dependence.

Correlation effects in superconducting quantum dot systems

NASA Astrophysics Data System (ADS)

Pokorný, Vladislav; Žonda, Martin

2018-05-01

We study the effect of electron correlations on a system consisting of a single-level quantum dot with local Coulomb interaction attached to two superconducting leads. We use the single-impurity Anderson model with BCS superconducting baths to study the interplay between the proximity induced electron pairing and the local Coulomb interaction. We show how to solve the model using the continuous-time hybridization-expansion quantum Monte Carlo method. The results obtained for experimentally relevant parameters are compared with results of self-consistent second order perturbation theory as well as with the numerical renormalization group method.

Estimation of Rank Correlation for Clustered Data

PubMed Central

Rosner, Bernard; Glynn, Robert

2017-01-01

It is well known that the sample correlation coefficient (Rxy) is the maximum likelihood estimator (MLE) of the Pearson correlation (ρxy) for i.i.d. bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the MLE of ρxy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (a) converting ranks of both X and Y to the probit scale, (b) estimating the Pearson correlation between probit scores for X and Y, and (c) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. PMID:28399615

Predicting missing links via correlation between nodes

NASA Astrophysics Data System (ADS)

Liao, Hao; Zeng, An; Zhang, Yi-Cheng

2015-10-01

As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the Pearson correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

New perspectives in face correlation: discrimination enhancement in face recognition based on iterative algorithm

NASA Astrophysics Data System (ADS)

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

2016-04-01

Here, we report a brief review on the recent developments of correlation algorithms. Several implementation schemes and specific applications proposed in recent years are also given to illustrate powerful applications of these methods. Following a discussion and comparison of the implementation of these schemes, we believe that all-numerical implementation is the most practical choice for application of the correlation method because the advantages of optical processing cannot compensate the technical and/or financial cost needed for an optical implementation platform. We also present a simple iterative algorithm to optimize the training images of composite correlation filters. By making use of three or four iterations, the peak-to-correlation energy (PCE) value of correlation plane can be significantly enhanced. A simulation test using the Pointing Head Pose Image Database (PHPID) illustrates the effectiveness of this statement. Our method can be applied in many composite filters based on linear composition of training images as an optimization means.

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.

Preparing Tomorrow's Administrators: A Quantitative Correlation Study of the Relationship between Emotional Intelligence and Effective Leadership Practices

ERIC Educational Resources Information Center

May-Vollmar, Kelly

2017-01-01

Purpose: The purpose of this quantitative correlation study was to identify whether there is a relationship between emotional intelligence and effective leadership practices, specifically with school administrators in Southern California K-12 public schools. Methods: This study was conducted using a quantitative descriptive design, correlation…

A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information.

PubMed

Delis, Ioannis; Berret, Bastien; Pozzo, Thierry; Panzeri, Stefano

2013-01-01

Muscle synergies have been hypothesized to be the building blocks used by the central nervous system to generate movement. According to this hypothesis, the accomplishment of various motor tasks relies on the ability of the motor system to recruit a small set of synergies on a single-trial basis and combine them in a task-dependent manner. It is conceivable that this requires a fine tuning of the trial-to-trial relationships between the synergy activations. Here we develop an analytical methodology to address the nature and functional role of trial-to-trial correlations between synergy activations, which is designed to help to better understand how these correlations may contribute to generating appropriate motor behavior. The algorithm we propose first divides correlations between muscle synergies into types (noise correlations, quantifying the trial-to-trial covariations of synergy activations at fixed task, and signal correlations, quantifying the similarity of task tuning of the trial-averaged activation coefficients of different synergies), and then uses single-trial methods (task-decoding and information theory) to quantify their overall effect on the task-discriminating information carried by muscle synergy activations. We apply the method to both synchronous and time-varying synergies and exemplify it on electromyographic data recorded during performance of reaching movements in different directions. Our method reveals the robust presence of information-enhancing patterns of signal and noise correlations among pairs of synchronous synergies, and shows that they enhance by 9-15% (depending on the set of tasks) the task-discriminating information provided by the synergy decompositions. We suggest that the proposed methodology could be useful for assessing whether single-trial activations of one synergy depend on activations of other synergies and quantifying the effect of such dependences on the task-to-task differences in muscle activation patterns.

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.

Dynamical Behaviors between the PM10 and the meteorological factor using the detrended cross-correlation analysis method

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Lee, Dong-In

2013-04-01

There is considerable interest in cross-correlations in collective modes of real data from atmospheric geophysics, seismology, finance, physiology, genomics, and nanodevices. If two systems interact mutually, that interaction gives rise to collective modes. This phenomenon is able to be analyzed using the cross-correlation of traditional methods, random matrix theory, and the detrended cross-correlation analysis method. The detrended cross-correlation analysis method was used in the past to analyze several models such as autoregressive fractionally integrated moving average processes, stock prices and their trading volumes, and taxi accidents. Particulate matter is composed of the organic and inorganic mixtures such as the natural sea salt, soil particle, vehicles exhaust, construction dust, and soot. The PM10 is known as the particle with the aerodynamic diameter (less than 10 microns) that is able to enter the human respiratory system. The PM10 concentration has an effect on the climate change by causing an unbalance of the global radiative equilibrium through the direct effect that blocks the stoma of plants and cuts off the solar radiation, different from the indirect effect that changes the optical property of clouds, cloudiness, and lifetime of clouds. Various factors contribute to the degree of the PM10 concentration. Notable among these are the land-use types, surface vegetation coverage, as well as meteorological factors. In this study, we analyze and simulate cross-correlations in time scales between the PM10 concentration and the meteorological factor (among temperature, wind speed and humidity) using the detrended cross-correlation analysis method through the removal of specific trends at eight cities in the Korean peninsula. We divide time series data into Asian dust events and non-Asian dust events to analyze the change of meteorological factors on the fluctuation of PM10 the concentration during Asian dust events. In particular, our result is compared to analytic findings from references published in all nations. ----------------------------------------------------------------- This work was supported by Center for the ASER (CATER 2012-6110) and by the NRFK through a grant provided by the KMEST(No.K1663000201107900).

Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

NASA Astrophysics Data System (ADS)

Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

2007-09-01

When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

Frontiers of two-dimensional correlation spectroscopy. Part 2. Perturbation methods, fields of applications, and types of analytical probes

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

Noteworthy experimental practices, which are advancing forward the frontiers of the field of two-dimensional (2D) correlation spectroscopy, are reviewed with the focus on various perturbation methods currently practiced to induce spectral changes, pertinent examples of applications in various fields, and types of analytical probes employed. Types of perturbation methods found in the published literature are very diverse, encompassing both dynamic and static effects. Although a sizable portion of publications report the use of dynamic perturbatuions, much greater number of studies employ static effect, especially that of temperature. Fields of applications covered by the literature are also very broad, ranging from fundamental research to practical applications in a number of physical, chemical and biological systems, such as synthetic polymers, composites and biomolecules. Aside from IR spectroscopy, which is the most commonly used tool, many other analytical probes are used in 2D correlation analysis. The ever expanding trend in depth, breadth and versatility of 2D correlation spectroscopy techniques and their broad applications all point to the robust and healthy state of the field.

Multivariate meta-analysis using individual participant data.

PubMed

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

2015-06-01

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. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Digital halftoning methods for selectively partitioning error into achromatic and chromatic channels

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

1990-01-01

A method is described for reducing the visibility of artifacts arising in the display of quantized color images on CRT displays. The method is based on the differential spatial sensitivity of the human visual system to chromatic and achromatic modulations. Because the visual system has the highest spatial and temporal acuity for the luminance component of an image, a technique which will reduce luminance artifacts at the expense of introducing high-frequency chromatic errors is sought. A method based on controlling the correlations between the quantization errors in the individual phosphor images is explored. The luminance component is greatest when the phosphor errors are positively correlated, and is minimized when the phosphor errors are negatively correlated. The greatest effect of the correlation is obtained when the intensity quantization step sizes of the individual phosphors have equal luminances. For the ordered dither algorithm, a version of the method can be implemented by simply inverting the matrix of thresholds for one of the color components.

Theoretical development and first-principles analysis of strongly correlated systems

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

Liu, Chen

A variety of quantum many-body methods have been developed for studying the strongly correlated electron systems. We have also proposed a computationally efficient and accurate approach, named the correlation matrix renormalization (CMR) method, to address the challenges. The initial implementation of the CMR method is designed for molecules which have theoretical advantages, including small size of system, manifest mechanism and strongly correlation effect such as bond breaking process. The theoretic development and benchmark tests of the CMR method are included in this thesis. Meanwhile, ground state total energy is the most important property of electronic calculations. We also investigated anmore » alternative approach to calculate the total energy, and extended this method for magnetic anisotropy energy (MAE) of ferromagnetic materials. In addition, another theoretical tool, dynamical mean- field theory (DMFT) on top of the DFT , has also been used in electronic structure calculations for an Iridium oxide to study the phase transition, which results from an interplay of the d electrons' internal degrees of freedom.« less

The Analysis of Surface EMG Signals with the Wavelet-Based Correlation Dimension Method

PubMed Central

Zhang, Yanyan; Wang, Jue

2014-01-01

Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy. PMID:24868240

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Relationships between autofocus methods for SAR and self-survey techniques for SONAR. [Synthetic Aperture Radar (SAR)

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

Wahl, D.E.; Jakowatz, C.V. Jr.; Ghiglia, D.C.

1991-01-01

Autofocus methods in SAR and self-survey techniques in SONAR have a common mathematical basis in that they both involve estimation and correction of phase errors introduced by sensor position uncertainties. Time delay estimation and correlation methods have been shown to be effective in solving the self-survey problem for towed SONAR arrays. Since it can be shown that platform motion errors introduce similar time-delay estimation problems in SAR imaging, the question arises as to whether such techniques could be effectively employed for autofocus of SAR imagery. With a simple mathematical model for motion errors in SAR, we will show why suchmore » correlation/time-delay techniques are not nearly as effective as established SAR autofocus algorithms such as phase gradient autofocus or sub-aperture based methods. This analysis forms an important bridge between signal processing methodologies for SAR and SONAR. 5 refs., 4 figs.« less

Predicted NMR properties of noble gas hydride cations RgH +

NASA Astrophysics Data System (ADS)

Cukras, Janusz; Sadlej, Joanna

2008-12-01

The NMR shielding constants and, for the first time, the spin-spin coupling constants of Rg and H in RgH + compounds for Rg = Ne, Ar, Kr, Xe have been investigated by non-relativistic Hartree-Fock (HF) and relativistic Dirac-Hartree-Fock (DHF) methods. Electron-correlation effects have been furthermore calculated using SOPPA and CCSD at the non-relativistic level. The correlation effects are large on both parameters and opposite to the relativistic effects. The results indicate that both the relativistic and correlation effects need to be taken into account in a quantitative computations, especially in the case of the spin-spin coupling constants.

A comparison of the simplified olecranon and digital methods of assessment of skeletal maturity during the pubertal growth spurt.

PubMed

Canavese, F; Charles, Y P; Dimeglio, A; Schuller, S; Rousset, M; Samba, A; Pereira, B; Steib, J-P

2014-11-01

Assessment of skeletal age is important in children's orthopaedics. We compared two simplified methods used in the assessment of skeletal age. Both methods have been described previously with one based on the appearance of the epiphysis at the olecranon and the other on the digital epiphyses. We also investigated the influence of assessor experience on applying these two methods. Our investigation was based on the anteroposterior left hand and lateral elbow radiographs of 44 boys (mean: 14.4; 12.4 to 16.1 ) and 78 girls (mean: 13.0; 11.1 to14.9) obtained during the pubertal growth spurt. A total of nine observers examined the radiographs with the observers assigned to three groups based on their experience (experienced, intermediate and novice). These raters were required to determined skeletal ages twice at six-week intervals. The correlation between the two methods was determined per assessment and per observer groups. Interclass correlation coefficients (ICC) evaluated the reproducibility of the two methods. The overall correlation between the two methods was r = 0.83 for boys and r = 0.84 for girls. The correlation was equal between first and second assessment, and between the observer groups (r ≥ 0.82). There was an equally strong ICC for the assessment effect (ICC ≤ 0.4%) and observer effect (ICC ≤ 3%) for each method. There was no significant (p < 0.05) difference between the levels of experience. The two methods are equally reliable in assessing skeletal maturity. The olecranon method offers detailed information during the pubertal growth spurt, while the digital method is as accurate but less detailed, making it more useful after the pubertal growth spurt once the olecranon has ossified. ©2014 The British Editorial Society of Bone & Joint Surgery.

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

The Temporal Effect of Training Utility Perceptions on Adopting a Trained Method: The Role of Perceived Organizational Support

ERIC Educational Resources Information Center

Madera, Juan M.; Steele, Stacey T.; Beier, Margaret

2011-01-01

The current study examined the temporal effect of perceived training utility on adoption of a trained method and how perceived organizational support influences the relationship between perceived training utility perceptions and adoption of a trained method. With the use of a correlational-survey-based design, this longitudinal study required…

Estimation of Comfort/Disconfort Based on EEG in Massage by Use of Clustering according to Correration and Incremental Learning type NN

NASA Astrophysics Data System (ADS)

Teramae, Tatsuya; Kushida, Daisuke; Takemori, Fumiaki; Kitamura, Akira

Authors proposed the estimation method combining k-means algorithm and NN for evaluating massage. However, this estimation method has a problem that discrimination ratio is decreased to new user. There are two causes of this problem. One is that generalization of NN is bad. Another one is that clustering result by k-means algorithm has not high correlation coefficient in a class. Then, this research proposes k-means algorithm according to correlation coefficient and incremental learning for NN. The proposed k-means algorithm is method included evaluation function based on correlation coefficient. Incremental learning is method that NN is learned by new data and initialized weight based on the existing data. The effect of proposed methods are verified by estimation result using EEG data when testee is given massage.

Comparison of methods applied in photoinduced transient spectroscopy to determining the defect center parameters: The correlation procedure and the signal analysis based on inverse Laplace transformation

NASA Astrophysics Data System (ADS)

Suproniuk, M.; Pawłowski, M.; Wierzbowski, M.; Majda-Zdancewicz, E.; Pawłowski, Ma.

2018-04-01

The procedure for determination of trap parameters by photo-induced transient spectroscopy is based on the Arrhenius plot that illustrates a thermal dependence of the emission rate. In this paper, we show that the Arrhenius plot obtained by the correlation method is shifted toward lower temperatures as compared to the one obtained with the inverse Laplace transformation. This shift is caused by the model adequacy error of the correlation method and introduces errors to a calculation procedure of defect center parameters. The effect is exemplified by comparing the results of the determination of trap parameters with both methods based on photocurrent transients for defect centers observed in tin-doped neutron-irradiated silicon crystals and in gallium arsenide grown with the Vertical Gradient Freeze method.

A method for the estimation of the significance of cross-correlations in unevenly sampled red-noise time series

NASA Astrophysics Data System (ADS)

Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.

2014-11-01

We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems.

PubMed

Ghosh, Soumen; Cramer, Christopher J; Truhlar, Donald G; Gagliardi, Laura

2017-04-01

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e. , systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. We recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functional theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet-triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet-triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.

Developing and Evaluating a Target-Background Similarity Metric for Camouflage Detection

PubMed Central

Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

2014-01-01

Background Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. Methodology In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. Significance The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results. PMID:24498310

Convective Heat Transfer Scaling of Ignition Delay and Burning Rate with Heat Flux and Stretch Rate in the Equivalent Low Stretch Apparatus

NASA Technical Reports Server (NTRS)

Olson, Sandra

2011-01-01

To better evaluate the buoyant contributions to the convective cooling (or heating) inherent in normal-gravity material flammability test methods, we derive a convective heat transfer correlation that can be used to account for the forced convective stretch effects on the net radiant heat flux for both ignition delay time and burning rate. The Equivalent Low Stretch Apparatus (ELSA) uses an inverted cone heater to minimize buoyant effects while at the same time providing a forced stagnation flow on the sample, which ignites and burns as a ceiling fire. Ignition delay and burning rate data is correlated with incident heat flux and convective heat transfer and compared to results from other test methods and fuel geometries using similarity to determine the equivalent stretch rates and thus convective cooling (or heating) rates for those geometries. With this correlation methodology, buoyant effects inherent in normal gravity material flammability test methods can be estimated, to better apply the test results to low stretch environments relevant to spacecraft material selection.

The double-soft limit in cosmological correlation functions and graviton exchange effects

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

Alinea, Allan L.; Kubota, Takahiro; Misumi, Nobuhiko, E-mail: alinea@het.phys.sci.osaka-u.ac.jp, E-mail: kubota@celas.osaka-u.ac.jp, E-mail: misumi.nobu@gmail.com

The graviton exchange effect on cosmological correlation functions is examined by employing the double-soft limit technique. A new relation among correlation functions that contain the effects due to graviton exchange diagrams in addition to those due to scalar-exchange and scalar-contact-interaction, is derived by using the background field method and independently by the method of Ward identities associated with dilatation symmetry. We compare these three terms, putting small values for the slow-roll parameters and (1− n {sub s} ) ≈ 0.042, where n {sub s} is the scalar spectral index. It is argued that the graviton exchange effects are more dominantmore » than the other two and could be observed in the trispectrum in the double-soft limit. Our observation strengthens the previous work by Seery, Sloth and Vernizzi, in which it has been argued that the graviton exchange dominates in the counter-collinear limit for single field slow-roll inflation.« less

Correlation- and covariance-supported normalization method for estimating orthodontic trainer treatment for clenching activity.

PubMed

Akdenur, B; Okkesum, S; Kara, S; Günes, S

2009-11-01

In this study, electromyography signals sampled from children undergoing orthodontic treatment were used to estimate the effect of an orthodontic trainer on the anterior temporal muscle. A novel data normalization method, called the correlation- and covariance-supported normalization method (CCSNM), based on correlation and covariance between features in a data set, is proposed to provide predictive guidance to the orthodontic technique. The method was tested in two stages: first, data normalization using the CCSNM; second, prediction of normalized values of anterior temporal muscles using an artificial neural network (ANN) with a Levenberg-Marquardt learning algorithm. The data set consists of electromyography signals from right anterior temporal muscles, recorded from 20 children aged 8-13 years with class II malocclusion. The signals were recorded at the start and end of a 6-month treatment. In order to train and test the ANN, two-fold cross-validation was used. The CCSNM was compared with four normalization methods: minimum-maximum normalization, z score, decimal scaling, and line base normalization. In order to demonstrate the performance of the proposed method, prevalent performance-measuring methods, and the mean square error and mean absolute error as mathematical methods, the statistical relation factor R2 and the average deviation have been examined. The results show that the CCSNM was the best normalization method among other normalization methods for estimating the effect of the trainer.

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.

The Mealiness and Quality of Herbal Medicine: Licorice for Example.

PubMed

Liu, Xueying; Hou, Weilong; Dou, Deqiang

2017-01-01

The morphological identification is an effective and simple quality evaluation method in Chinese drugs, and the traits of mealiness and color were widely used in the commercial market of Chinese drugs. The objective of this study was to explore the correlation between mealiness of herbal drugs and its quality; licorice was selected as an example. The mealiness of licorice was graded by its weight; meanwhile, the content of glycyrrhizic acid and liquiritin was determined by high-performance liquid chromatography-diode-array detection method; the content of polysaccharides, soluble sugars, pectin, total starch, amylose, and amylopectin was measured by colorimetric method; and the number and diameter of starch granule were observed by microscope. The results showed that the mealiness of licorice which collected from wild and cultivated plants is positively correlated with the content of glycyrrhizic acid, liquiritin, the ratio of amylose to total starch, and the number of starch granules whose diameter was over 5 μm. However, the mealiness is negatively correlated with the total starch. Further, the formation mechanism of starch granule was discussed. It is for the first time to report the positive correlation between the mealiness and the starch granule size, the ratio of amylose to total starch, which can provide rationality for the quality evaluation using the character of mealiness in herbal medicine. It is a convenient method to justify the quality of herbal medicine. To explore the correlation between mealiness of herbal drugs and its quality, licorice was selected as an example. The result indicated that the effective constituent is correlated with mealiness of licorice. Abbreviations Used: TCM: Traditional Chinese Medicine.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

PubMed Central

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-01-01

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]′), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal. PMID:26213935

Exact exchange-correlation potentials of singlet two-electron systems

NASA Astrophysics Data System (ADS)

Ryabinkin, Ilya G.; Ospadov, Egor; Staroverov, Viktor N.

2017-10-01

We suggest a non-iterative analytic method for constructing the exchange-correlation potential, v XC ( r ) , of any singlet ground-state two-electron system. The method is based on a convenient formula for v XC ( r ) in terms of quantities determined only by the system's electronic wave function, exact or approximate, and is essentially different from the Kohn-Sham inversion technique. When applied to Gaussian-basis-set wave functions, the method yields finite-basis-set approximations to the corresponding basis-set-limit v XC ( r ) , whereas the Kohn-Sham inversion produces physically inappropriate (oscillatory and divergent) potentials. The effectiveness of the procedure is demonstrated by computing accurate exchange-correlation potentials of several two-electron systems (helium isoelectronic series, H2, H3 + ) using common ab initio methods and Gaussian basis sets.

Correlates of the Rosenberg Self-Esteem Scale Method Effects

ERIC Educational Resources Information Center

Quilty, Lena C.; Oakman, Jonathan M.; Risko, Evan

2006-01-01

Investigators of personality assessment are becoming aware that using positively and negatively worded items in questionnaires to prevent acquiescence may negatively impact construct validity. The Rosenberg Self-Esteem Scale (RSES) has demonstrated a bifactorial structure typically proposed to result from these method effects. Recent work suggests…

Comparison of the quadratic configuration interaction and coupled cluster approaches to electron correlation including the effect of triple excitations

NASA Technical Reports Server (NTRS)

Taylor, Peter R.; Lee, Timothy J.; Rendell, Alistair P.

1990-01-01

The recently proposed quadratic configuration interaction (QCI) method is compared with the more rigorous coupled cluster (CC) approach for a variety of chemical systems. Some of these systems are well represented by a single-determinant reference function and others are not. The finite order singles and doubles correlation energy, the perturbational triples correlation energy, and a recently devised diagnostic for estimating the importance of multireference effects are considered. The spectroscopic constants of CuH, the equilibrium structure of cis-(NO)2 and the binding energies of Be3, Be4, Mg3, and Mg4 were calculated using both approaches. The diagnostic for estimating multireference character clearly demonstrates that the QCI method becomes less satisfactory than the CC approach as non-dynamical correlation becomes more important, in agreement with a perturbational analysis of the two methods and the numerical estimates of the triple excitation energies they yield. The results for CuH show that the differences between the two methods become more apparent as the chemical systems under investigation becomes more multireference in nature and the QCI results consequently become less reliable. Nonetheless, when the system of interest is dominated by a single reference determinant both QCI and CC give very similar results.

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

PubMed

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

2017-04-01

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

Estimation of rank correlation for clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J

2017-06-30

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

Determine equilibrium dissociation constant of drug-membrane receptor affinity using the cell membrane chromatography relative standard method.

PubMed

Ma, Weina; Yang, Liu; Lv, Yanni; Fu, Jia; Zhang, Yanmin; He, Langchong

2017-06-23

The equilibrium dissociation constant (K D ) of drug-membrane receptor affinity is the basic parameter that reflects the strength of interaction. The cell membrane chromatography (CMC) method is an effective technique to study the characteristics of drug-membrane receptor affinity. In this study, the K D value of CMC relative standard method for the determination of drug-membrane receptor affinity was established to analyze the relative K D values of drugs binding to the membrane receptors (Epidermal growth factor receptor and angiotensin II receptor). The K D values obtained by the CMC relative standard method had a strong correlation with those obtained by the frontal analysis method. Additionally, the K D values obtained by CMC relative standard method correlated with pharmacological activity of the drug being evaluated. The CMC relative standard method is a convenient and effective method to evaluate drug-membrane receptor affinity. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

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

Biological Methods and Manual Development

EPA Pesticide Factsheets

EPA scientists conduct research to develop and evaluate analytical methods for the identification, enumeration, evaluation of aquatic organisms exposed to environmental stressors and to correlate exposures with effects on chemical and biological indicators

Hydrodynamics and long range correlations

NASA Astrophysics Data System (ADS)

Bialas, A.; Zalewski, K.

2011-04-01

It is shown that the recently proposed method of studying the long-range correlations in multiparticle production can be effectively used to verify the hydrodynamic nature of the longitudinal expansion of the partonic system created in the collision. The case of ALICE detector is explicitly considered.

Improvement of photon correlation spectroscopy method for measuring nanoparticle size by using attenuated total reflectance.

PubMed

Krishtop, Victor; Doronin, Ivan; Okishev, Konstantin

2012-11-05

Photon correlation spectroscopy is an effective method for measuring nanoparticle sizes and has several advantages over alternative methods. However, this method suffers from a disadvantage in that its measuring accuracy reduces in the presence of convective flows of fluid containing nanoparticles. In this paper, we propose a scheme based on attenuated total reflectance in order to reduce the influence of convection currents. The autocorrelation function for the light-scattering intensity was found for this case, and it was shown that this method afforded a significant decrease in the time required to measure the particle sizes and an increase in the measuring accuracy.

A MIMO radar quadrature and multi-channel amplitude-phase error combined correction method based on cross-correlation

NASA Astrophysics Data System (ADS)

Yun, Lingtong; Zhao, Hongzhong; Du, Mengyuan

2018-04-01

Quadrature and multi-channel amplitude-phase error have to be compensated in the I/Q quadrature sampling and signal through multi-channel. A new method that it doesn't need filter and standard signal is presented in this paper. And it can combined estimate quadrature and multi-channel amplitude-phase error. The method uses cross-correlation and amplitude ratio between the signal to estimate the two amplitude-phase errors simply and effectively. And the advantages of this method are verified by computer simulation. Finally, the superiority of the method is also verified by measure data of outfield experiments.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

PubMed Central

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q.; Ducote, Justin L.; Su, Min-Ying; Molloi, Sabee

2013-01-01

Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. Conclusions: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications. PMID:24320536

The method of attachment influences accelerometer-based activity data in dogs.

PubMed

Martin, Kyle W; Olsen, Anastasia M; Duncan, Colleen G; Duerr, Felix M

2017-02-10

Accelerometer-based activity monitoring is a promising new tool in veterinary medicine used to objectively assess activity levels in dogs. To date, it is unknown how device orientation, attachment method, and attachment of a leash to the collar holding an accelerometer affect canine activity data. It was our goal to evaluate whether attachment methods of accelerometers affect activity counts. Eight healthy, client-owned dogs were fitted with two identical neck collars to which two identical activity monitors were attached using six different methods of attachment. These methods of attachment evaluated the use of a protective case, positioning of the activity monitor and the tightness of attachment of the accelerometer. Lastly, the effect of leash attachment to the collar was evaluated. For trials where the effect of leash attachment to the collar was not being studied, the leash was attached to a harness. Activity data obtained from separate monitors within a given experiment were compared using Pearson correlation coefficients and across all experiments using the Kruskal-Wallis Test. There was excellent correlation and low variability between activity monitors on separate collars when the leash was attached to a harness, regardless of their relative positions. There was good correlation when activity monitors were placed on the same collar regardless of orientation. There were poor correlations between activity monitors in three experiments: when the leash was fastened to the collar that held an activity monitor, when one activity monitor was housed in the protective casing, and when one activity monitor was loosely zip-tied to the collar rather than threaded on using the provided metal loop. Follow-up, pair-wise comparisons identified the correlation associated with these three methods of attachment to be statistically different from the level of correlation when monitors were placed on separate collars. While accelerometer-based activity monitors are useful tools to objectively assess physical activity in dogs, care must be taken when choosing a method to attach the device. The attachment of the activity monitor to the collar should utilize a second, dedicated collar that is not used for leash attachment and the attachment method should remain consistent throughout a study period.

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.

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

PubMed

Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

The use of least squares methods in functional optimization of energy use prediction models

NASA Astrophysics Data System (ADS)

Bourisli, Raed I.; Al-Shammeri, Basma S.; AlAnzi, Adnan A.

2012-06-01

The least squares method (LSM) is used to optimize the coefficients of a closed-form correlation that predicts the annual energy use of buildings based on key envelope design and thermal parameters. Specifically, annual energy use is related to a number parameters like the overall heat transfer coefficients of the wall, roof and glazing, glazing percentage, and building surface area. The building used as a case study is a previously energy-audited mosque in a suburb of Kuwait City, Kuwait. Energy audit results are used to fine-tune the base case mosque model in the VisualDOE{trade mark, serif} software. Subsequently, 1625 different cases of mosques with varying parameters were developed and simulated in order to provide the training data sets for the LSM optimizer. Coefficients of the proposed correlation are then optimized using multivariate least squares analysis. The objective is to minimize the difference between the correlation-predicted results and the VisualDOE-simulation results. It was found that the resulting correlation is able to come up with coefficients for the proposed correlation that reduce the difference between the simulated and predicted results to about 0.81%. In terms of the effects of the various parameters, the newly-defined weighted surface area parameter was found to have the greatest effect on the normalized annual energy use. Insulating the roofs and walls also had a major effect on the building energy use. The proposed correlation and methodology can be used during preliminary design stages to inexpensively assess the impacts of various design variables on the expected energy use. On the other hand, the method can also be used by municipality officials and planners as a tool for recommending energy conservation measures and fine-tuning energy codes.

Unbiased estimates of galaxy scaling relations from photometric redshift surveys

NASA Astrophysics Data System (ADS)

Rossi, Graziano; Sheth, Ravi K.

2008-06-01

Many physical properties of galaxies correlate with one another, and these correlations are often used to constrain galaxy formation models. Such correlations include the colour-magnitude relation, the luminosity-size relation, the fundamental plane, etc. However, the transformation from observable (e.g. angular size, apparent brightness) to physical quantity (physical size, luminosity) is often distance dependent. Noise in the distance estimate will lead to biased estimates of these correlations, thus compromising the ability of photometric redshift surveys to constrain galaxy formation models. We describe two methods which can remove this bias. One is a generalization of the Vmax method, and the other is a maximum-likelihood approach. We illustrate their effectiveness by studying the size-luminosity relation in a mock catalogue, although both methods can be applied to other scaling relations as well. We show that if one simply uses photometric redshifts one obtains a biased relation; our methods correct for this bias and recover the true relation.

Ab initio model potential calculations on the electronic spectrum of Ni2 + -doped MgO including correlation, spin-orbit and embedding effects

NASA Astrophysics Data System (ADS)

Llusar, Rosa; Casarrubios, Marcos; Barandiarán, Zoila; Seijo, Luis

1996-10-01

An ab initio theoretical study of the optical absorption spectrum of Ni2+-doped MgO has been conducted by means of calculations in a MgO-embedded (NiO6)10-cluster. The calculations include long- and short-range embedding effects of electrostatic and quantum nature brought about by the MgO crystalline lattice, as well as electron correlation and spin-orbit effects within the (NiO6)10- cluster. The spin-orbit calculations have been performed using the spin-orbit-CI WB-AIMP method [Chem. Phys. Lett. 147, 597 (1988); J. Chem. Phys. 102, 8078 (1995)] which has been recently proposed and is applied here for the first time to the field of impurities in crystals. The WB-AIMP method is extended in order to handle correlation effects which, being necessary to produce accurate energy differences between spin-free states, are not needed for the proper calculation of spin-orbit couplings. The extension of the WB-AIMP method, which is also aimed at keeping the size of the spin-orbit-CI within reasonable limits, is based on the use of spin-free-state shifting operators. It is shown that the unreasonable spin-orbit splittings obtained for MgO:Ni2+ in spin-orbit-CI calculations correlating only 8 electrons become correct when the proposed extension is applied, so that the same CI space is used but energy corrections due to correlating up to 26 electrons are included. The results of the ligand field spectrum of MgO:Ni2+ show good overall agreement with the experimental measurements and a reassignment of the observed Eg(b3T1g) excited state is proposed and discussed.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

PubMed

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-12-13

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

PubMed Central

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-01-01

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

Core-core and core-valence correlation

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

1988-01-01

The effect of (1s) core correlation on properties and energy separations was analyzed using full configuration-interaction (FCI) calculations. The Be 1 S - 1 P, the C 3 P - 5 S and CH+ 1 Sigma + or - 1 Pi separations, and CH+ spectroscopic constants, dipole moment and 1 Sigma + - 1 Pi transition dipole moment were studied. The results of the FCI calculations are compared to those obtained using approximate methods. In addition, the generation of atomic natural orbital (ANO) basis sets, as a method for contracting a primitive basis set for both valence and core correlation, is discussed. When both core-core and core-valence correlation are included in the calculation, no suitable truncated CI approach consistently reproduces the FCI, and contraction of the basis set is very difficult. If the (nearly constant) core-core correlation is eliminated, and only the core-valence correlation is included, CASSCF/MRCI approached reproduce the FCI results and basis set contraction is significantly easier.

Importance of non-flow in mixed-harmonic multi-particle correlations in small collision systems

DOE PAGES

Huo, Peng; Gajdosova, Katarina; Jia, Jiangyong; ...

2017-12-18

Recently CMS Collaboration measured mixed-harmonic four-particle azimuthal correlations, known as symmetric cumulants SC(n, m), in pp and p+Pb collisions, and interpreted the non-zero SC(n, m) as evidence for long-range collectivity in these small collision systems. Using the PYTHIA and HIJING models which do not have genuine long-range collectivity, we show that the CMS results, obtained with standard cumulant method, could be dominated by non-flow effects associated with jet and dijets, especially in pp collisions. We show that the non-flow effects are largely suppressed using the recently proposed subevent cumulant methods by requiring azimuthal correlation between two or more pseudorapidity ranges.more » As a result, we argue that the reanalysis of SC(n, m) using the subevent method in experiments is necessary before they can used to provide further evidences for a long-range multi-particle collectivity and constraints on theoretical models in small collision systems.« less

Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

NASA Astrophysics Data System (ADS)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.

[Study on objectively evaluating skin aging according to areas of skin texture].

PubMed

Shan, Gaixin; Gan, Ping; He, Ling; Sun, Lu; Li, Qiannan; Jiang, Zheng; He, Xiangqian

2015-02-01

Skin aging principles play important roles in skin disease diagnosis, the evaluation of skin cosmetic effect, forensic identification and age identification in sports competition, etc. This paper proposes a new method to evaluate the skin aging objectively and quantitatively by skin texture area. Firstly, the enlarged skin image was acquired. Then, the skin texture image was segmented by using the iterative threshold method, and the skin ridge image was extracted according to the watershed algorithm. Finally, the skin ridge areas of the skin texture were extracted. The experiment data showed that the average areas of skin ridges, of both men and women, had a good correlation with age (the correlation coefficient r of male was 0.938, and the correlation coefficient r of female was 0.922), and skin texture area and age regression curve showed that the skin texture area increased with age. Therefore, it is effective to evaluate skin aging objectively by the new method presented in this paper.

Importance of non-flow in mixed-harmonic multi-particle correlations in small collision systems

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

Huo, Peng; Gajdosova, Katarina; Jia, Jiangyong

Recently CMS Collaboration measured mixed-harmonic four-particle azimuthal correlations, known as symmetric cumulants SC(n, m), in pp and p+Pb collisions, and interpreted the non-zero SC(n, m) as evidence for long-range collectivity in these small collision systems. Using the PYTHIA and HIJING models which do not have genuine long-range collectivity, we show that the CMS results, obtained with standard cumulant method, could be dominated by non-flow effects associated with jet and dijets, especially in pp collisions. We show that the non-flow effects are largely suppressed using the recently proposed subevent cumulant methods by requiring azimuthal correlation between two or more pseudorapidity ranges.more » As a result, we argue that the reanalysis of SC(n, m) using the subevent method in experiments is necessary before they can used to provide further evidences for a long-range multi-particle collectivity and constraints on theoretical models in small collision systems.« less

A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data.

PubMed

Agogo, George O; van der Voet, Hilko; van 't Veer, Pieter; Ferrari, Pietro; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek C

2016-10-13

Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

Non-stationarity and cross-correlation effects in the MHD solar activity

NASA Astrophysics Data System (ADS)

Demin, S. A.; Nefedyev, Y. A.; Andreev, A. O.; Demina, N. Y.; Timashev, S. F.

2018-01-01

The analysis of turbulent processes in sunspots and pores which are self-organizing long-lived magnetic structures is a complicated and not yet solved problem. The present work focuses on studying such magneto-hydrodynamic (MHD) formations on the basis of flicker-noise spectroscopy using a new method of multi-parametric analysis. The non-stationarity and cross-correlation effects taking place in solar activity dynamics are considered. The calculated maximum values of non-stationarity factor may become precursors of significant restructuring in solar magnetic activity. The introduced cross-correlation functions enable us to judge synchronization effects between the signals of various solar activity indicators registered simultaneously.

Correlation Among the Variant Group, Effective Grain Size, and Elastic Strain Energy During the Phase Transformation in 9Ni Steels

NASA Astrophysics Data System (ADS)

Terasaki, Hidenori; Moriguchi, Koji; Tomio, Yusaku; Yamagishi, Hideki; Morito, Shigekazu

2017-12-01

The effect of carbon content on the density of variant-pair boundaries was investigated in 9Ni steel using an electron backscatter diffraction patterns method. The changes in the density of variant-pair boundaries were correlated with the nondestructive measured values of shear modulus of the austenite phase at the phase transformation point. Furthermore, the effective grain size was correlated with the shear modulus and the density of variant-pair boundaries. These relations are discussed from the viewpoint of self-accommodation of elastic strain energy and the nucleation event in the bainite and martensitic transformations.

Conical intersections of free energy surfaces in solution: Effect of electron correlation on a protonated Schiff base in methanol solution

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

Mori, Toshifumi; Nakano, Katsuhiro; Kato, Shigeki

2010-08-14

The minimum energy conical intersection (MECI) optimization method with taking account of the dynamic electron correlation effect [T. Mori and S. Kato, Chem. Phys. Lett. 476, 97 (2009)] is extended to locate the MECI of nonequilibrium free energy surfaces in solution. A multistate electronic perturbation theory is introduced into the nonequilibrium free energy formula, which is defined as a function of solute and solvation coordinates. The analytical free energy gradient and interstate coupling vectors are derived, and are applied to locate MECIs in solution. The present method is applied to study the cis-trans photoisomerization reaction of a protonated Schiff basemore » molecule (PSB3) in methanol (MeOH) solution. It is found that the effect of dynamic electron correlation largely lowers the energy of S{sub 1} state. We also show that the solvation effect strongly stabilizes the MECI obtained by twisting the terminal C=N bond to become accessible in MeOH solution, whereas the conical intersection is found to be unstable in gas phase. The present study indicates that both electron correlation and solvation effects are important in the photoisomerization reaction of PSB3. The effect of counterion is also examined, and seems to be rather small in solution. The structures of free energy surfaces around MECIs are also discussed.« less

Comparison of Methods for Determining Boundary Layer Edge Conditions for Transition Correlations

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Berry, Scott A.; Hollis, Brian R.; Horvath, Thomas J.

2003-01-01

Data previously obtained for the X-33 in the NASA Langley Research Center 20-Inch Mach 6 Air Tunnel have been reanalyzed to compare methods for determining boundary layer edge conditions for use in transition correlations. The experimental results were previously obtained utilizing the phosphor thermography technique to monitor the status of the boundary layer downstream of discrete roughness elements via global heat transfer images of the X-33 windward surface. A boundary layer transition correlation was previously developed for this data set using boundary layer edge conditions calculated using an inviscid/integral boundary layer approach. An algorithm was written in the present study to extract boundary layer edge quantities from higher fidelity viscous computational fluid dynamic solutions to develop transition correlations that account for viscous effects on vehicles of arbitrary complexity. The boundary layer transition correlation developed for the X-33 from the viscous solutions are compared to the previous boundary layer transition correlations. It is shown that the boundary layer edge conditions calculated using an inviscid/integral boundary layer approach are significantly different than those extracted from viscous computational fluid dynamic solutions. The present results demonstrate the differences obtained in correlating transition data using different computational methods.

Correlation mapping method of OCT for visualization blood vessels in brain

NASA Astrophysics Data System (ADS)

Izotova, O. A.; Kalyanov, A. L.; Lychagov, V. V.; Semyachkina-Glushkovskaya, O. V.

2013-11-01

The burning issue in modern medicine is the diagnosis and treatment of various life-threatening diseases, in particular the diseases of brain. One of them is intracranial hemorrhage (ICH). It occurs especially among newborn babies and is hard-diagnosed. In order to understand the nature of the ICH, the microcirculation of blood, which serves key functions within the body, is analyzed. On this basis a series of experiments was done, in the results of which it was showed, that latent stage of ICH is characterized by decrease of venous blood outflow and the loss of sensitivity of sagittal vein to vasoconstrictor effect of adrenaline. So, stress-related changes of the cerebral venous blood flow (CVBF) can be the source of this disease. In this paper registration CVBF was made with the help of commercially available Thorlabs Swept Source OCT System, using the correlation mapping method. In this method values of correlation coefficient of several images are analyzed. In the result of the algorithm the correlation map was obtained. By the resulting map the diameter of vessels was calculated, which is necessary for examination of effects of adrenalin to the vessels and identification symptoms of ICH.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Friend suggestion in social network based on user log

NASA Astrophysics Data System (ADS)

Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

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

Development of a method for efficient cost-effective screening of Aspergillus niger mutants having increased production of glucoamylase.

PubMed

Zhu, Xudong; Arman, Bessembayev; Chu, Ju; Wang, Yonghong; Zhuang, Yingping

2017-05-01

To develop an efficient cost-effective screening process to improve production of glucoamylase in Aspergillus niger. The cultivation of A. niger was achieved with well-dispersed morphology in 48-deep-well microtiter plates, which increased the throughput of the samples compared to traditional flask cultivation. There was a close negative correlation between glucoamylase and its pH of the fermentation broth. A novel high-throughput analysis method using Methyl Orange was developed. When compared to the conventional analysis method using 4-nitrophenyl α-D-glucopyranoside as substrate, a correlation coefficient of 0.96 by statistical analysis was obtained. Using this novel screening method, we acquired a strain with an activity of 2.2 × 10 3  U ml -1 , a 70% higher yield of glucoamylase than its parent strain.

Significance of distinct electron-correlation effects in determining the (P ,T )-odd electric dipole moment of 171Yb

NASA Astrophysics Data System (ADS)

Sahoo, B. K.; Singh, Yashpal

2017-06-01

The parity and time-reversal violating electric dipole moment (EDM) of 171Yb is calculated accounting for the electron-correlation effects over the Dirac-Hartree-Fock method in the relativistic Rayleigh-Schrödinger many-body perturbation theory, with the second- [MBPT(2) method] and third-order [MBPT(3) method] approximations, and two variants of all-order relativistic many-body approaches, in the random phase approximation (RPA) and coupled-cluster (CC) method with singles and doubles (CCSD method) framework. We consider electron-nucleus tensor-pseudotensor (T-PT) and nuclear Schiff moment (NSM) interactions as the predominant sources that induce EDM in a diamagnetic atomic system. Our results from the CCSD method to EDM (da) of 171Yb due to the T-PT and NSM interactions are found to be da=4.85 (6 ) ×10-20<σ > CT|e | cm and da=2.89 (4 ) ×10-17S /(|e |fm3) , respectively, where CT is the T-PT coupling constant and S is the NSM. These values differ significantly from the earlier calculations. The reason for the same has been attributed to large correlation effects arising through non-RPA type of interactions among the electrons in this atom that are observed by analyzing the differences in the RPA and CCSD results. This has been further scrutinized from the MBPT(2) and MBPT(3) results and their roles have been demonstrated explicitly.

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

Demosaicing images from colour cameras for digital image correlation

NASA Astrophysics Data System (ADS)

Forsey, A.; Gungor, S.

2016-11-01

Digital image correlation is not the intended use for consumer colour cameras, but with care they can be successfully employed in such a role. The main obstacle is the sparsely sampled colour data caused by the use of a colour filter array (CFA) to separate the colour channels. It is shown that the method used to convert consumer camera raw files into a monochrome image suitable for digital image correlation (DIC) can have a significant effect on the DIC output. A number of widely available software packages and two in-house methods are evaluated in terms of their performance when used with DIC. Using an in-plane rotating disc to produce a highly constrained displacement field, it was found that the bicubic spline based in-house demosaicing method outperformed the other methods in terms of accuracy and aliasing suppression.

Short-term test-retest-reliability of conditioned pain modulation using the cold-heat-pain method in healthy subjects and its correlation to parameters of standardized quantitative sensory testing.

PubMed

Gehling, Julia; Mainka, Tina; Vollert, Jan; Pogatzki-Zahn, Esther M; Maier, Christoph; Enax-Krumova, Elena K

2016-08-05

Conditioned Pain Modulation (CPM) is often used to assess human descending pain inhibition. Nine different studies on the test-retest-reliability of different CPM paradigms have been published, but none of them has investigated the commonly used heat-cold-pain method. The results vary widely and therefore, reliability measures cannot be extrapolated from one CPM paradigm to another. Aim of the present study was to analyse the test-retest-reliability of the common heat-cold-pain method and its correlation to pain thresholds. We tested the short-term test-retest-reliability within 40 ± 19.9 h using a cold-water immersion (10 °C, left hand) as conditioning stimulus (CS) and heat pain (43-49 °C, pain intensity 60 ± 5 on the 101-point numeric rating scale, right forearm) as test stimulus (TS) in 25 healthy right-handed subjects (12females, 31.6 ± 14.1 years). The TS was applied 30s before (TSbefore), during (TSduring) and after (TSafter) the 60s CS. The difference between the pain ratings for TSbefore and TSduring represents the early CPM-effect, between TSbefore and TSafter the late CPM-effect. Quantitative sensory testing (QST, DFNS protocol) was performed on both sessions before the CPM assessment. paired t-tests, Intraclass correlation coefficient (ICC), standard error of measurement (SEM), smallest real difference (SRD), Pearson's correlation, Bland-Altman analysis, significance level p < 0.05 with Bonferroni correction for multiple comparisons, when necessary. Pain ratings during CPM correlated significantly (ICC: 0.411…0.962) between both days, though ratings for TSafter were lower on day 2 (p < 0.005). The early (day 1: 16.7 ± 11.7; day 2: 19.5 ± 11.9; ICC: 0.618, SRD: 20.2) and late (day 1: 1.7 ± 9.2; day 2: 7.6 ± 11.5; ICC: 0.178, SRD: 27.0) CPM effect did not differ significantly between both days. Both early and late CPM-effects did not correlate with the pain thresholds. The short-term test-retest-reliability of the early CPM-effect using the heat-cold-pain method in healthy subjects achieved satisfying results in terms of the ICC. The SRD of the early CPM effect showed that an individual change of > 20 NRS can be attributed to a real change rather than chance. The late CPM-effect was weaker and not reliable.

Does leadership effectiveness correlates with leadership styles in healthcare executives of Iran University of Medical Sciences

PubMed Central

Ebadifard Azar, Farbod; Sarabi Asiabar, Ali

2015-01-01

Background: Effective leadership is essential to passing through obstacles facing the health field.The current health care system in Iran has major problems and gaps in the field of effective leadership. The aim of this study was to evaluate hospital managers’ leadership style through selfassessment and to determine the correlation between leadership styles with healthcare executives’ leadership readiness and leadership effectiveness. Methods: In this cross-sectional study a self-administered questionnaire completed by all internal healthcare executives of all teaching and non-teaching hospitals affiliated to Iran University of Medical Sciences. Questionnaire was composed to determine demographic information, leadership style questions, leadership effectiveness and leadership readiness. Descriptive statistics and Pearson correlation coefficient were used for data analysis. Results: According to the findings, the dominant style of healthcare executives was transformational leadership style (with a score of 4.34). The leadership effectiveness was estimated at about 4.36 that shows the appropriate level of leadership effectiveness. There was a significant correlation (correlation coefficient of 0.244) between leadership readiness and transformational leadership style (p<0.05). Also, there was a significant correlation between leadership effectiveness with transformational (0.051) and transactional (0.216) styles. Conclusion: There was a correlation between leadership readiness and leadership effectiveness with leadership styles. Application of this research will be crucial to universities and healthcare executives. This study suggests that strengthening the scientific basis is essential for leadership readiness and leadership effectiveness in healthcare system. PMID:26000260

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

DOE PAGES

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.; ...

2017-01-19

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

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

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Assessment of higher order correlation effects with the help of Moller-Plesset perturbation theory up to sixth order

NASA Astrophysics Data System (ADS)

He, Yuan; Cremer, Dieter

For 30 molecules and two atoms, MP n correlation energies up to n = 6 are computed and used to analyse higher order correlation effects and the initial convergence behaviour of the MP n series. Particularly useful is the analysis of correlation contributions E(n)XY ...( n = 4,5,6; X , Y ,... = S, D, T, Q denoting single, double, triple, and quadruple excitations) in the form of correlation energy spectra. Two classes of system are distinguished, namely class A systems possessing well separated electron pairs and class B systems which are characterized by electron clustering in certain regions of atomic and molecular space. For class A systems, electron pair correlation effects as described by D, Q, DD, DQ, QQ, DDD, etc., contributions are most important, which are stepwise included at MP n with n = 2,... ,6. Class A systems are reasonably described by MP n theory, which is reflected by the fact that convergence of the MP n series is monotonic (but relatively slow) for class A systems. The description of class B systems is difficult since three- and four-electron correlation effects and couplings between two-, three-, and four-electron correlation effects missing for lower order perturbation theory are significant. MP n methods, which do not cover these effects, simulate higher order with lower order correlation effects thus exaggerating the latter, which has to be corrected with increasing n. Consequently, the MP n series oscillates for class B systems at low orders. A possible divergence of the MP n series is mostly a consequence of an unbalanced basis set. For example, diffuse functions added to an unsaturated sp basis lead to an exaggeration of higher order correlation effects, which can cause enhanced oscillations and divergence of the MP n series.

Effect of short-range correlations on the single proton 3s1/2 wave function in 206Pb

NASA Astrophysics Data System (ADS)

Shlomo, S.; Talmi, I.; Anders, M. R.; Bonasera, G.

2018-02-01

We consider the experimental data for difference, Δρc (r), between the charge density distributions of the isotones 206Pb - 205Tl, deduced by analysis of elastic electron scattering measurements and corresponds to the shell model 3s1/2 proton orbit. We investigate the effects of two-body short-range correlations. This is done by: (a) Determining the corresponding single particle potential (mean-field), employing a novel method, directly from the single particle proton density and its first and second derivatives. We also carried out least-square fits to parametrized single particle potentials; (b) Determining the short-range correlations effect by employing the Jastrow correlated many-body wave function to derive a correlation factor for the single particle density distribution. The 3s 1/2 wave functions of the determined potentials reproduce fairly well the experimental data within the quoted errors. The calculated charge density difference, Δρc (r), obtained with the inclusion of the short-range correlation effect does not reproduce the experimental data.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

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.

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Correlated k-distribution method for radiative transfer in climate models: Application to effect of cirrus clouds on climate

NASA Technical Reports Server (NTRS)

Lacis, A. A.; Wang, W. C.; Hansen, J. E.

1979-01-01

A radiative transfer method appropriate for use in simple climate models and three dimensional global climate models was developed. It is fully interactive with climate changes, such as in the temperature-pressure profile, cloud distribution, and atmospheric composition, and it is accurate throughout the troposphere and stratosphere. The vertical inhomogeneity of the atmosphere is accounted for by assuming a correlation of gaseous k-distributions of different pressures and temperatures. Line-by-line calculations are made to demonstrate that The method is remarkably accurate. The method is then used in a one-dimensional radiative-convective climate model to study the effect of cirrus clouds on surface temperature. It is shown that an increase in cirrus cloud cover can cause a significant warming of the troposphere and the Earth's surface, by the mechanism of an enhanced green-house effect. The dependence of this phenomenon on cloud optical thickness, altitude, and latitude is investigated.

Exploring biorthonormal transformations of pair-correlation functions in atomic structure variational calculations

NASA Astrophysics Data System (ADS)

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

2010-04-01

Multiconfiguration expansions frequently target valence correlation and correlation between valence electrons and the outermost core electrons. Correlation within the core is often neglected. A large orbital basis is needed to saturate both the valence and core-valence correlation effects. This in turn leads to huge numbers of configuration state functions (CSFs), many of which are unimportant. To avoid the problems inherent to the use of a single common orthonormal orbital basis for all correlation effects in the multiconfiguration Hartree-Fock (MCHF) method, we propose to optimize independent MCHF pair-correlation functions (PCFs), bringing their own orthonormal one-electron basis. Each PCF is generated by allowing single- and double-excitations from a multireference (MR) function. This computational scheme has the advantage of using targeted and optimally localized orbital sets for each PCF. These pair-correlation functions are coupled together and with each component of the MR space through a low dimension generalized eigenvalue problem. Nonorthogonal orbital sets being involved, the interaction and overlap matrices are built using biorthonormal transformation of the coupled basis sets followed by a counter-transformation of the PCF expansions. Applied to the ground state of beryllium, the new method gives total energies that are lower than the ones from traditional complete active space (CAS)-MCHF calculations using large orbital active sets. It is fair to say that we now have the possibility to account for, in a balanced way, correlation deep down in the atomic core in variational calculations.

Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis

NASA Astrophysics Data System (ADS)

Lan, Tian; Cheng, Kai; Ren, Tina; Arce, Stephen Hugo; Tseng, Yiider

2016-09-01

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.

The Effects of Size and Type of Vocal Fold Polyp on Some Acoustic Voice Parameters

PubMed Central

Akbari, Elaheh; Seifpanahi, Sadegh; Ghorbani, Ali; Izadi, Farzad; Torabinezhad, Farhad

2018-01-01

Background Vocal abuse and misuse would result in vocal fold polyp. Certain features define the extent of vocal folds polyp effects on voice acoustic parameters. The present study aimed to define the effects of polyp size on acoustic voice parameters, and compare these parameters in hemorrhagic and non-hemorrhagic polyps. Methods In the present retrospective study, 28 individuals with hemorrhagic or non-hemorrhagic polyps of the true vocal folds were recruited to investigate acoustic voice parameters of vowel/ æ/ computed by the Praat software. The data were analyzed using the SPSS software, version 17.0. According to the type and size of polyps, mean acoustic differences and correlations were analyzed by the statistical t test and Pearson correlation test, respectively; with significance level below 0.05. Results The results indicated that jitter and the harmonics-to-noise ratio had a significant positive and negative correlation with the polyp size (P=0.01), respectively. In addition, both mentioned parameters were significantly different between the two types of the investigated polyps. Conclusion Both the type and size of polyps have effects on acoustic voice characteristics. In the present study, a novel method to measure polyp size was introduced. Further confirmation of this method as a tool to compare polyp sizes requires additional investigations. PMID:29749984

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.

A partitioned correlation function interaction approach for describing electron correlation in atoms

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Measurement of installation deformation of the acetabulum during prosthetic replacement of a hip joint using digital image correlation

NASA Astrophysics Data System (ADS)

Lei, Dong; Bai, Pengxiang; Zhu, Feipeng

2018-01-01

Nowadays, acetabulum prosthesis replacement is widely used in clinical medicine. However, there is no efficient way to evaluate the implantation effect of the prosthesis. Based on a modern photomechanics technique called digital image correlation (DIC), the evaluation method of the installation effect of the acetabulum was established during a prosthetic replacement of a hip joint. The DIC method determines strain field by comparing the speckle images between the undeformed sample and the deformed counterpart. Three groups of experiments were carried out to verify the feasibility of the DIC method on the acetabulum installation deformation test. Experimental results indicate that the installation deformation of acetabulum generally includes elastic deformation (corresponding to the principal strain of about 1.2%) and plastic deformation. When the installation angle is ideal, the plastic deformation can be effectively reduced, which could prolong the service life of acetabulum prostheses.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

Exact special twist method for quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Dagrada, Mario; Karakuzu, Seher; Vildosola, Verónica Laura; Casula, Michele; Sorella, Sandro

2016-12-01

We present a systematic investigation of the special twist method introduced by Rajagopal et al. [Phys. Rev. B 51, 10591 (1995), 10.1103/PhysRevB.51.10591] for reducing finite-size effects in correlated calculations of periodic extended systems with Coulomb interactions and Fermi statistics. We propose a procedure for finding special twist values which, at variance with previous applications of this method, reproduce the energy of the mean-field infinite-size limit solution within an adjustable (arbitrarily small) numerical error. This choice of the special twist is shown to be the most accurate single-twist solution for curing one-body finite-size effects in correlated calculations. For these reasons we dubbed our procedure "exact special twist" (EST). EST only needs a fully converged independent-particles or mean-field calculation within the primitive cell and a simple fit to find the special twist along a specific direction in the Brillouin zone. We first assess the performances of EST in a simple correlated model such as the three-dimensional electron gas. Afterwards, we test its efficiency within ab initio quantum Monte Carlo simulations of metallic elements of increasing complexity. We show that EST displays an overall good performance in reducing finite-size errors comparable to the widely used twist average technique but at a much lower computational cost since it involves the evaluation of just one wave function. We also demonstrate that the EST method shows similar performances in the calculation of correlation functions, such as the ionic forces for structural relaxation and the pair radial distribution function in liquid hydrogen. Our conclusions point to the usefulness of EST for correlated supercell calculations; our method will be particularly relevant when the physical problem under consideration requires large periodic cells.

A model for correlating flat plate film cooling effectiveness for rows of round holes

NASA Astrophysics Data System (ADS)

Lecuyer, M. R.; Soechting, F. O.

1985-09-01

An effective method of cooling, that has found widespread application in aircraft gas turbines, is the injection of a film of cooling air through holes into the hot mainstream gas to provide a buffer layer between the hot gas and the airfoil surface. Film cooling has been extensively investigated and the results have been reported in the literature. However, there is no generalized method reported in the literature to predict the film cooling performance as influenced by the major variables. A generalized film cooling correlation has been developed, utilizing data reported in the literature, for constant velocity and flat plate boundary layer development. This work provides a basic understanding of the complex interaction of the major variables effecting film cooling performance.

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery.

PubMed

Liu, Quan; Chen, Yi-Feng; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2017-08-01

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

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

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PubMed

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q; Ducote, Justin L; Su, Min-Ying; Molloi, Sabee

2013-12-01

Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

Spatial fluorescence cross-correlation spectroscopy between core and ring pinholes

NASA Astrophysics Data System (ADS)

Blancquaert, Yoann; Delon, Antoine; Derouard, Jacques; Jaffiol, Rodolphe

2006-04-01

Fluorescence Correlation Spectroscopy (FCS) is an attractive method to measure molecular concentration, mobility parameters and chemical kinetics. However its ability to descriminate different diffusing species needs to be improved. Recently, we have proposed a simplified spatial Fluorescence cross Correlation Spectroscopy (sFCCS) method, allowing, with only one focused laser beam to obtain two confocal volumes spatially shifted. Now, we present a new sFCCS optical geometry where the two pinholes, a ring and core, are encapsulated one in the other. In this approach all physical and chemical processes that occur in a single volume, like singlet-triplet dynamics and photobleaching, can be eliminated; moreover, this new optical geometry optimises the collection of fluorescence. The first cross Correlation curves for Rhodamine 6G (Rh6G) in Ethanol are presented, in addition to the effect of the size of fluorescent particules (nano-beads, diameters : 20, 100 and 200 nm). The relative simplicity of the method leads us to propose sFCCS as an appropriate method for the determination of diffusion parameters of fluorophores in solution or cells. Nevertheless, progresses in the ingeniering of the optical Molecular Detection Efficiency volumes are highly desirable, in order to improve the descrimination between the cross correlated volumes.

Methods of Muscle Activation Onset Timing Recorded During Spinal Manipulation.

PubMed

Currie, Stuart J; Myers, Casey A; Krishnamurthy, Ashok; Enebo, Brian A; Davidson, Bradley S

2016-05-01

The purpose of this study was to determine electromyographic threshold parameters that most reliably characterize the muscular response to spinal manipulation and compare 2 methods that detect muscle activity onset delay: the double-threshold method and cross-correlation method. Surface and indwelling electromyography were recorded during lumbar side-lying manipulations in 17 asymptomatic participants. Muscle activity onset delays in relation to the thrusting force were compared across methods and muscles using a generalized linear model. The threshold combinations that resulted in the lowest Detection Failures were the "8 SD-0 milliseconds" threshold (Detection Failures = 8) and the "8 SD-10 milliseconds" threshold (Detection Failures = 9). The average muscle activity onset delay for the double-threshold method across all participants was 149 ± 152 milliseconds for the multifidus and 252 ± 204 milliseconds for the erector spinae. The average onset delay for the cross-correlation method was 26 ± 101 for the multifidus and 67 ± 116 for the erector spinae. There were no statistical interactions, and a main effect of method demonstrated that the delays were higher when using the double-threshold method compared with cross-correlation. The threshold parameters that best characterized activity onset delays were an 8-SD amplitude and a 10-millisecond duration threshold. The double-threshold method correlated well with visual supervision of muscle activity. The cross-correlation method provides several advantages in signal processing; however, supervision was required for some results, negating this advantage. These results help standardize methods when recording neuromuscular responses of spinal manipulation and improve comparisons within and across investigations. Copyright © 2016 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

A Discrete Probability Function Method for the Equation of Radiative Transfer

NASA Technical Reports Server (NTRS)

Sivathanu, Y. R.; Gore, J. P.

1993-01-01

A discrete probability function (DPF) method for the equation of radiative transfer is derived. The DPF is defined as the integral of the probability density function (PDF) over a discrete interval. The derivation allows the evaluation of the PDF of intensities leaving desired radiation paths including turbulence-radiation interactions without the use of computer intensive stochastic methods. The DPF method has a distinct advantage over conventional PDF methods since the creation of a partial differential equation from the equation of transfer is avoided. Further, convergence of all moments of intensity is guaranteed at the basic level of simulation unlike the stochastic method where the number of realizations for convergence of higher order moments increases rapidly. The DPF method is described for a representative path with approximately integral-length scale-sized spatial discretization. The results show good agreement with measurements in a propylene/air flame except for the effects of intermittency resulting from highly correlated realizations. The method can be extended to the treatment of spatial correlations as described in the Appendix. However, information regarding spatial correlations in turbulent flames is needed prior to the execution of this extension.

Investigating the role of background and observation error correlations in improving a model forecast of forest carbon balance using four dimensional variational data assimilation.

NASA Astrophysics Data System (ADS)

Pinnington, Ewan; Casella, Eric; Dance, Sarah; Lawless, Amos; Morison, James; Nichols, Nancy; Wilkinson, Matthew; Quaife, Tristan

2016-04-01

Forest ecosystems play an important role in sequestering human emitted carbon-dioxide from the atmosphere and therefore greatly reduce the effect of anthropogenic induced climate change. For that reason understanding their response to climate change is of great importance. Efforts to implement variational data assimilation routines with functional ecology models and land surface models have been limited, with sequential and Markov chain Monte Carlo data assimilation methods being prevalent. When data assimilation has been used with models of carbon balance, background "prior" errors and observation errors have largely been treated as independent and uncorrelated. Correlations between background errors have long been known to be a key aspect of data assimilation in numerical weather prediction. More recently, it has been shown that accounting for correlated observation errors in the assimilation algorithm can considerably improve data assimilation results and forecasts. In this paper we implement a 4D-Var scheme with a simple model of forest carbon balance, for joint parameter and state estimation and assimilate daily observations of Net Ecosystem CO2 Exchange (NEE) taken at the Alice Holt forest CO2 flux site in Hampshire, UK. We then investigate the effect of specifying correlations between parameter and state variables in background error statistics and the effect of specifying correlations in time between observation error statistics. The idea of including these correlations in time is new and has not been previously explored in carbon balance model data assimilation. In data assimilation, background and observation error statistics are often described by the background error covariance matrix and the observation error covariance matrix. We outline novel methods for creating correlated versions of these matrices, using a set of previously postulated dynamical constraints to include correlations in the background error statistics and a Gaussian correlation function to include time correlations in the observation error statistics. The methods used in this paper will allow the inclusion of time correlations between many different observation types in the assimilation algorithm, meaning that previously neglected information can be accounted for. In our experiments we compared the results using our new correlated background and observation error covariance matrices and those using diagonal covariance matrices. We found that using the new correlated matrices reduced the root mean square error in the 14 year forecast of daily NEE by 44 % decreasing from 4.22 g C m-2 day-1 to 2.38 g C m-2 day-1.

Estimation of River Discharge at Ungauged Catchment using GIS Map Correlation Method as Applied in Sta. Lucia River in Mauban, Quezon, Philippines

NASA Astrophysics Data System (ADS)

Monjardin, Cris Edward F.; Uy, Francis Aldrine A.; Tan, Fibor J.

2017-06-01

This paper presents use of GIS Map Correlation Method, a novel method of Prediction of Ungauged Basin, which is used to estimate the river flow at an ungauged catchment. The PUB Method used here intends to reduce the time and costs of data gathering procedure since it will just rely on a reference calibrated watershed that has almost the same characteristics in terms of slope, curve number, land cover, climatic condition, and average basin elevation. Furthermore, this utilized a set of modelling software which used digital elevation models (DEM), rainfall and discharge data. The researchers estimated the river flow of Sta. Lucia River in Quezon province, which is the ungauged catchment. The researchers assessed 11 gauged catchments and determined which basin could be correlated to Sta. Lucia. After finding the most correlated basin, the researchers used the data considering adjusted parameters of the gauged catchment. In evaluating the accuracy of the method, the researchers simulated a rainfall event in the said catchment and compared the actual discharge and the generated discharge from HEC-HMS. The researchers found out that method showed a good fit in the compared results, proving GMC Method is effective for use in the calibration of ungauged catchments.

Research of diagnosis sensors fault based on correlation analysis of the bridge structural health monitoring system

NASA Astrophysics Data System (ADS)

Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia

2010-03-01

Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.

Studies of the Correlation Between Ionospheric Anomalies and Seismic Activities in the Indian Subcontinent

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

Sasmal, S.; Chakrabarti, S. K.; S. N. Bose National Centre for Basic Sciences, JD Block, Salt-Lake Kolkata-70098

2010-10-20

The VLF (Very Low Frequency) signals are long thought to give away important information about the Lithosphere-Ionosphere coupling. It is recently established that the ionosphere may be perturbed due to seismic activities. The effects of this perturbation can be detected through the VLF wave amplitude. There are several methods to find this correlations and these methods can be used for the prediction of these seismic events. In this paper, first we present a brief history of the use of VLF propagation method for the study of seismo-ionospheric correlations. Then we present different methods proposed by us to find out themore » seismo-ionospheric correlations. At the Indian Centre for Space Physics, Kolkata we have been monitoring the VTX station at Vijayanarayanam from 2002. In the initial stage, we received 17 kHz signal and latter we received 18.2 kHz signal. In this paper, first we present the results for the 17 kHz signal during Sumatra earthquake in 2004 obtained from the terminator time analysis method. Then we present much detailed and statistical analysis using some new methods and present the results for 18.2 kHz signal. In order to establish the correlation between the ionospheric activities and the earthquakes, we need to understand what are the reference signals throughout the year. We present the result of the sunrise and sunset terminators for the 18.2 kHz signal as a function of the day of the year for a period of four years, viz, 2005 to 2008 when the solar activity was very low. In this case, the signal would primarily be affected by the Sun due to normal sunrise and sunset effects. Any deviation from this standardized calibration curve would point to influences by terrestrial (such as earthquakes) and extra-terrestrial (such as solar activities and other high energy phenomena). We present examples of deviations which occur in a period of sixteen months and show that the correlations with seismic events is significant and typically the highest deviation in terminator shift takes place up to a couple of days prior to the seismic event. We introduce a new method where we find the effects of the seismic activities on D-layer preparation time (DLPT) and the D-layer disappearance time (DLDT). We identify those days in which DLPT and DLDT exhibit deviations from the average value and we correlate those days with seismic events. Separately, we compute the energy release by the earthquakes and using this, we compute the total energy released locally from distant earthquakes and find correlations of the deviations with them. In this case also we find pre-cursors a few days before the seismic events. In a third approach, we consider the nighttime fluctuation method (differently quantified than the conventional way). We analyzed the nighttime data for the year 2007 to check the correlation between the night time fluctuation of the signal amplitude and the seismic events. Using the statistical method for all the events of the year and for the individual individual earthquakes (Magnitude > 5) we found that the night time signal amplitude becomes very high on three days prior to the seismic events.« less

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Geological mapping by geobotanical and geophysical means: a case study from the Bükk Mountains (NE Hungary)

NASA Astrophysics Data System (ADS)

Németh, Norbert; Petho, Gabor

2009-03-01

Geological mapping of an unexposed area can be supported by indirect methods. Among these, the use of mushrooms as geobotanical indicators and the shallow-penetration electromagnetic VLF method proved to be useful in the Bükk Mountains. Mushrooms have not been applied to geological mapping before. Common species like Boletus edulis and Leccinum aurantiacum are correlated with siliciclastic and magmatic formations while Calocybe gambosa is correlated with limestone. The validity of this correlation observed in the eastern part of the Bükk Mts. was controlled on a site where there was an indicated (by the mushrooms only) but unexposed occurrence of siliciclastic rocks not mapped before. The extent and structure of this occurrence were explored with the VLF survey and a trial-and-error method was applied for the interpretation. This case study presented here demonstrates the effectiveness of the combination of these relatively simple and inexpensive methods.

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

Spatial Correlation Of Streamflows: An Analytical Approach

NASA Astrophysics Data System (ADS)

Betterle, A.; Schirmer, M.; Botter, G.

2016-12-01

The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the absence of discharge measurements.

Signatures of van der Waals binding: A coupling-constant scaling analysis

NASA Astrophysics Data System (ADS)

Jiao, Yang; Schröder, Elsebeth; Hyldgaard, Per

2018-02-01

The van der Waals (vdW) density functional (vdW-DF) method [Rep. Prog. Phys. 78, 066501 (2015), 10.1088/0034-4885/78/6/066501] describes dispersion or vdW binding by tracking the effects of an electrodynamic coupling among pairs of electrons and their associated exchange-correlation holes. This is done in a nonlocal-correlation energy term Ecnl, which permits density functional theory calculation in the Kohn-Sham scheme. However, to map the nature of vdW forces in a fully interacting materials system, it is necessary to also account for associated kinetic-correlation energy effects. Here, we present a coupling-constant scaling analysis, which permits us to compute the kinetic-correlation energy Tcnl that is specific to the vdW-DF account of nonlocal correlations. We thus provide a more complete spatially resolved analysis of the electrodynamical-coupling nature of nonlocal-correlation binding, including vdW attraction, in both covalently and noncovalently bonded systems. We find that kinetic-correlation energy effects play a significant role in the account of vdW or dispersion interactions among molecules. Furthermore, our mapping shows that the total nonlocal-correlation binding is concentrated to pockets in the sparse electron distribution located between the material fragments.

The Index cohesive effect on stock market correlations

NASA Astrophysics Data System (ADS)

Shapira, Y.; Kenett, D. Y.; Ben-Jacob, E.

2009-12-01

We present empirical examination and reassessment of the functional role of the market Index, using datasets of stock returns for eight years, by analyzing and comparing the results for two very different markets: 1) the New York Stock Exchange (NYSE), representing a large, mature market, and 2) the Tel Aviv Stock Exchange (TASE), representing a small, young market. Our method includes special collective (holographic) analysis of stock-Index correlations, of nested stock correlations (including the Index as an additional ghost stock) and of bare stock correlations (after subtraction of the Index return from the stocks returns). Our findings verify and strongly substantiate the assumed functional role of the index in the financial system as a cohesive force between stocks, i.e., the correlations between stocks are largely due to the strong correlation between each stock and the Index (the adhesive effect), rather than inter-stock dependencies. The Index adhesive and cohesive effects on the market correlations in the two markets are presented and compared in a reduced 3-D principal component space of the correlation matrices (holographic presentation). The results provide new insights into the interplay between an index and its constituent stocks in TASE-like versus NYSE-like markets.

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

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

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

Evaluation of Fiber Reinforced Cement Using Digital Image Correlation

PubMed Central

Melenka, Garrett W.; Carey, Jason P.

2015-01-01

The effect of short fiber reinforcements on the mechanical properties of cement has been examined using a splitting tensile – digital image correlation (DIC) measurement method. Three short fiber reinforcement materials have been used in this study: fiberglass, nylon, and polypropylene. The method outlined provides a simple experimental setup that can be used to evaluate the ultimate tensile strength of brittle materials as well as measure the full field strain across the surface of the splitting tensile test cylindrical specimen. Since the DIC measurement technique is a contact free measurement this method can be used to assess sample failure. PMID:26039590

Learning Bayesian Networks from Correlated Data

NASA Astrophysics Data System (ADS)

Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola

2016-05-01

Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.

Method for estimating effects of unknown correlations in spectral irradiance data on uncertainties of spectrally integrated colorimetric quantities

NASA Astrophysics Data System (ADS)

Kärhä, Petri; Vaskuri, Anna; Mäntynen, Henrik; Mikkonen, Nikke; Ikonen, Erkki

2017-08-01

Spectral irradiance data are often used to calculate colorimetric properties, such as color coordinates and color temperatures of light sources by integration. The spectral data may contain unknown correlations that should be accounted for in the uncertainty estimation. We propose a new method for estimating uncertainties in such cases. The method goes through all possible scenarios of deviations using Monte Carlo analysis. Varying spectral error functions are produced by combining spectral base functions, and the distorted spectra are used to calculate the colorimetric quantities. Standard deviations of the colorimetric quantities at different scenarios give uncertainties assuming no correlations, uncertainties assuming full correlation, and uncertainties for an unfavorable case of unknown correlations, which turn out to be a significant source of uncertainty. With 1% standard uncertainty in spectral irradiance, the expanded uncertainty of the correlated color temperature of a source corresponding to the CIE Standard Illuminant A may reach as high as 37.2 K in unfavorable conditions, when calculations assuming full correlation give zero uncertainty, and calculations assuming no correlations yield the expanded uncertainties of 5.6 K and 12.1 K, with wavelength steps of 1 nm and 5 nm used in spectral integrations, respectively. We also show that there is an absolute limit of 60.2 K in the error of the correlated color temperature for Standard Illuminant A when assuming 1% standard uncertainty in the spectral irradiance. A comparison of our uncorrelated uncertainties with those obtained using analytical methods by other research groups shows good agreement. We re-estimated the uncertainties for the colorimetric properties of our 1 kW photometric standard lamps using the new method. The revised uncertainty of color temperature is a factor of 2.5 higher than the uncertainty assuming no correlations.

A Preliminary Study of the Effects of Within-Group Covariance Structure on Recovery in Cluster Analysis. Research Report RR-94-46.

ERIC Educational Resources Information Center

Donoghue, John R.

Monte Carlo studies investigated effects of within-group covariance structure on subgroup recovery by several widely used hierarchical clustering methods. In Study 1, subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. All clustering methods were strongly affected by…

Continuous quantum measurement in spin environments

NASA Astrophysics Data System (ADS)

Xie, Dong; Wang, An Min

2015-08-01

We derive a stochastic master equation (SME) which describes the decoherence dynamics of a system in spin environments conditioned on the measurement record. Markovian and non-Markovian nature of environment can be revealed by a spectroscopy method based on weak continuous quantum measurement. On account of that correlated environments can lead to a non-local open system which exhibits strong non-Markovian effects although the local dynamics are Markovian, the spectroscopy method can be used to demonstrate that there is correlation between two environments.

The Role of Protected Areas in the Avoidance of Anthropogenic Conversion in a High Pressure Region: A Matching Method Analysis in the Core Region of the Brazilian Cerrado

PubMed Central

Paiva, Rodrigo José Oliveira; Brites, Ricardo Seixas; Machado, Ricardo Bomfim

2015-01-01

Global efforts to avoid anthropogenic conversion of natural habitat rely heavily on the establishment of protected areas. Studies that evaluate the effectiveness of these areas with a focus on preserving the natural habitat define effectiveness as a measure of the influence of protected areas on total avoided conversion. Changes in the estimated effectiveness are related to local and regional differences, evaluation methods, restriction categories that include the protected areas, and other characteristics. The overall objective of this study was to evaluate the effectiveness of protected areas to prevent the advance of the conversion of natural areas in the core region of the Brazil’s Cerrado Biome, taking into account the influence of the restriction degree, governmental sphere, time since the establishment of the protected area units, and the size of the area on the performance of protected areas. The evaluation was conducted using matching methods and took into account the following two fundamental issues: control of statistical biases caused by the influence of covariates on the likelihood of anthropogenic conversion and the non-randomness of the allocation of protected areas throughout the territory (spatial correlation effect) and the control of statistical bias caused by the influence of auto-correlation and leakage effect. Using a sample design that is not based on ways to control these biases may result in outcomes that underestimate or overestimate the effectiveness of those units. The matching method accounted for a bias reduction in 94–99% of the estimation of the average effect of protected areas on anthropogenic conversion and allowed us to obtain results with a reduced influence of the auto-correlation and leakage effects. Most protected areas had a positive influence on the maintenance of natural habitats, although wide variation in this effectiveness was dependent on the type, restriction, governmental sphere, size and age group of the unit. PMID:26222140

Methods for converging correlation energies within the dielectric matrix formalism

NASA Astrophysics Data System (ADS)

Dixit, Anant; Claudot, Julien; Gould, Tim; Lebègue, Sébastien; Rocca, Dario

2018-03-01

Within the dielectric matrix formalism, the random-phase approximation (RPA) and analogous methods that include exchange effects are promising approaches to overcome some of the limitations of traditional density functional theory approximations. The RPA-type methods however have a significantly higher computational cost, and, similarly to correlated quantum-chemical methods, are characterized by a slow basis set convergence. In this work we analyzed two different schemes to converge the correlation energy, one based on a more traditional complete basis set extrapolation and one that converges energy differences by accounting for the size-consistency property. These two approaches have been systematically tested on the A24 test set, for six points on the potential-energy surface of the methane-formaldehyde complex, and for reaction energies involving the breaking and formation of covalent bonds. While both methods converge to similar results at similar rates, the computation of size-consistent energy differences has the advantage of not relying on the choice of a specific extrapolation model.

Degree-strength correlation reveals anomalous trading behavior.

PubMed

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Wang, Zhao-Yang

2012-01-01

Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock markets. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying the anomalous traders using the transaction data of eight manipulated stocks and forty-four non-manipulated stocks during a one-year period. By analyzing the trading networks of stocks, we find that the trading networks of manipulated stocks exhibit significantly higher degree-strength correlation than the trading networks of non-manipulated stocks and the randomized trading networks. We further propose a method to detect anomalous traders of manipulated stocks based on statistical significance analysis of degree-strength correlation. Experimental results demonstrate that our method is effective at distinguishing the manipulated stocks from non-manipulated ones. Our method outperforms the traditional weight-threshold method at identifying the anomalous traders in manipulated stocks. More importantly, our method is difficult to be fooled by colluded traders.

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.

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

Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

PubMed

de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna

2014-07-01

This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.

CCLasso: correlation inference for compositional data through Lasso.

PubMed

Fang, Huaying; Huang, Chengcheng; Zhao, Hongyu; Deng, Minghua

2015-10-01

Direct analysis of microbial communities in the environment and human body has become more convenient and reliable owing to the advancements of high-throughput sequencing techniques for 16S rRNA gene profiling. Inferring the correlation relationship among members of microbial communities is of fundamental importance for genomic survey study. Traditional Pearson correlation analysis treating the observed data as absolute abundances of the microbes may lead to spurious results because the data only represent relative abundances. Special care and appropriate methods are required prior to correlation analysis for these compositional data. In this article, we first discuss the correlation definition of latent variables for compositional data. We then propose a novel method called CCLasso based on least squares with [Formula: see text] penalty to infer the correlation network for latent variables of compositional data from metagenomic data. An effective alternating direction algorithm from augmented Lagrangian method is used to solve the optimization problem. The simulation results show that CCLasso outperforms existing methods, e.g. SparCC, in edge recovery for compositional data. It also compares well with SparCC in estimating correlation network of microbe species from the Human Microbiome Project. CCLasso is open source and freely available from https://github.com/huayingfang/CCLasso under GNU LGPL v3. dengmh@pku.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effect of Coulomb Correlation on the Magnetic Properties of Mn Clusters.

PubMed

Huang, Chengxi; Zhou, Jian; Deng, Kaiming; Kan, Erjun; Jena, Puru

2018-05-03

In spite of decades of research, a fundamental understanding of the unusual magnetic behavior of small Mn clusters remains a challenge. Experiments show that Mn 2 is antiferromagnetic while small clusters containing up to five Mn atoms are ferromagnetic with magnetic moments of 5 μ B /atom and become ferrimagnetic as they grow further. Theoretical studies based on density functional theory (DFT), however, find Mn 2 to be ferromagnetic, with ferrimagnetic order setting in at different sizes that depend upon the computational methods used. While quantum chemical techniques correctly account for the antiferromagnetic ground state of Mn 2 , they are computationally too demanding to treat larger clusters, making it difficult to understand the evolution of magnetism. These studies clearly point to the importance of correlation and the need to find ways to treat it effectively for larger clusters and nanostructures. Here, we show that the DFT+ U method can be used to account for strong correlation. We determine the on-site Coulomb correlation, Hubbard U self-consistently by using the linear response theory and study its effect on the magnetic coupling of Mn clusters containing up to five atoms. With a calculated U value of 4.8 eV, we show that the ground state of Mn 2 is antiferromagnetic with a Mn-Mn distance of 3.34 Å, which agrees well with the electron spin resonance experiment. Equally important, we show that on-site Coulomb correlation also plays an important role in the evolution of magnetic coupling in larger clusters, as the results differ significantly from standard DFT calculations. We conclude that for a proper understanding of magnetism of Mn nanostructures (clusters, chains, and layers) one must take into account the effect of strong correlation.

Fluorescence background removal method for biological Raman spectroscopy based on empirical mode decomposition.

PubMed

Leon-Bejarano, Maritza; Dorantes-Mendez, Guadalupe; Ramirez-Elias, Miguel; Mendez, Martin O; Alba, Alfonso; Rodriguez-Leyva, Ildefonso; Jimenez, M

2016-08-01

Raman spectroscopy of biological tissue presents fluorescence background, an undesirable effect that generates false Raman intensities. This paper proposes the application of the Empirical Mode Decomposition (EMD) method to baseline correction. EMD is a suitable approach since it is an adaptive signal processing method for nonlinear and non-stationary signal analysis that does not require parameters selection such as polynomial methods. EMD performance was assessed through synthetic Raman spectra with different signal to noise ratio (SNR). The correlation coefficient between synthetic Raman spectra and the recovered one after EMD denoising was higher than 0.92. Additionally, twenty Raman spectra from skin were used to evaluate EMD performance and the results were compared with Vancouver Raman algorithm (VRA). The comparison resulted in a mean square error (MSE) of 0.001554. High correlation coefficient using synthetic spectra and low MSE in the comparison between EMD and VRA suggest that EMD could be an effective method to remove fluorescence background in biological Raman spectra.

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.

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.

The Effect of Sample Size on Parametric and Nonparametric Factor Analytical Methods

ERIC Educational Resources Information Center

Kalkan, Ömür Kaya; Kelecioglu, Hülya

2016-01-01

Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…

Designing a composite correlation filter based on iterative optimization of training images for distortion invariant face recognition

NASA Astrophysics Data System (ADS)

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

2017-06-01

We present a novel method to optimize the discrimination ability and noise robustness of composite filters. This method is based on the iterative preprocessing of training images which can extract boundary and detailed feature information of authentic training faces, thereby improving the peak-to-correlation energy (PCE) ratio of authentic faces and to be immune to intra-class variance and noise interference. By adding the training images directly, one can obtain a composite template with high discrimination ability and robustness for face recognition task. The proposed composite correlation filter does not involve any complicated mathematical analysis and computation which are often required in the design of correlation algorithms. Simulation tests have been conducted to check the effectiveness and feasibility of our proposal. Moreover, to assess robustness of composite filters using receiver operating characteristic (ROC) curves, we devise a new method to count the true positive and false positive rates for which the difference between PCE and threshold is involved.

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

PubMed Central

Hyun, Dongwoon; Crowley, Anna Lisa C.; Dahl, Jeremy J.

2017-01-01

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this study, we assess existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2. PMID:27913342

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations.

Stochastic dynamics of uncoupled neural oscillators: Fokker-Planck studies with the finite element method

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

Galan, Roberto F.; Urban, Nathaniel N.; Center for the Neural Basis of Cognition, Mellon Institute, Pittsburgh, Pennsylvania 15213

We have investigated the effect of the phase response curve on the dynamics of oscillators driven by noise in two limit cases that are especially relevant for neuroscience. Using the finite element method to solve the Fokker-Planck equation we have studied (i) the impact of noise on the regularity of the oscillations quantified as the coefficient of variation, (ii) stochastic synchronization of two uncoupled phase oscillators driven by correlated noise, and (iii) their cross-correlation function. We show that, in general, the limit of type II oscillators is more robust to noise and more efficient at synchronizing by correlated noise thanmore » type I.« less

Theoretical Study of Sodium Effect on the Gasification of Carbonaceous Materials with Carbon Dioxide.

PubMed

Calderón, Lucas A; Garza, Jorge; Espinal, Juan F

2015-12-24

The effect of sodium on the thermodynamics and kinetics of carbon gasification with carbon dioxide was studied by using quantum chemistry methods. Specifically, in the density functional context, two exchange-correlation functionals were used: B3LYP and M06. Some results obtained by these exchange-correlation functionals were contrasted with those obtained by the CCSD(T) method. It was found that density functional theory gives similar conclusions with respect to the coupled-cluster method. As one important conclusion we can mention that the thermodynamics of carbon monoxide desorption is not favored by the sodium presence. However, the presence of this metal induces: (a) an easier formation of one semiquinone group, (b) the dissociation of carbon dioxide, and (c) an increment on the CO desorption rate for one of the proposed pathways.

UNO DMRG CASCI calculations of effective exchange integrals for m-phenylene-bis-methylene spin clusters

NASA Astrophysics Data System (ADS)

Kawakami, Takashi; Sano, Shinsuke; Saito, Toru; Sharma, Sandeep; Shoji, Mitsuo; Yamada, Satoru; Takano, Yu; Yamanaka, Shusuke; Okumura, Mitsutaka; Nakajima, Takahito; Yamaguchi, Kizashi

2017-09-01

Theoretical examinations of the ferromagnetic coupling in the m-phenylene-bis-methylene molecule and its oligomer were carried out. These systems are good candidates for exchange-coupled systems to investigate strong electronic correlations. We studied effective exchange integrals (J), which indicated magnetic coupling between interacting spins in these species. First, theoretical calculations based on a broken-symmetry single-reference procedure, i.e. the UHF, UMP2, UMP4, UCCSD(T) and UB3LYP methods, were carried out with a GAUSSIAN program code under an SR wave function. From these results, the J value by the UHF method was largely positive because of the strong ferromagnetic spin polarisation effect. The J value by the UCCSD(T) and UB3LYP methods improved an overestimation problem by correcting the dynamical electronic correlation. Next, magnetic coupling among these spins was studied using the CAS-based method of the symmetry-adapted multireference methods procedure. Thus, the UNO DMRG CASCI (UNO, unrestricted natural orbital; DMRG, density matrix renormalised group; CASCI, complete active space configuration interaction) method was mainly employed with a combination of ORCA and BLOCK program codes. DMRG CASCI calculations in valence electron counting, which included all orbitals to full valence CI, provided the most reliable result, and support the UB3LYP method for extended systems.

Generalized nonequilibrium vertex correction method in coherent medium theory for quantum transport simulation of disordered nanoelectronics

NASA Astrophysics Data System (ADS)

Yan, Jiawei; Ke, Youqi

2016-07-01

Electron transport properties of nanoelectronics can be significantly influenced by the inevitable and randomly distributed impurities/defects. For theoretical simulation of disordered nanoscale electronics, one is interested in both the configurationally averaged transport property and its statistical fluctuation that tells device-to-device variability induced by disorder. However, due to the lack of an effective method to do disorder averaging under the nonequilibrium condition, the important effects of disorders on electron transport remain largely unexplored or poorly understood. In this work, we report a general formalism of Green's function based nonequilibrium effective medium theory to calculate the disordered nanoelectronics. In this method, based on a generalized coherent potential approximation for the Keldysh nonequilibrium Green's function, we developed a generalized nonequilibrium vertex correction method to calculate the average of a two-Keldysh-Green's-function correlator. We obtain nine nonequilibrium vertex correction terms, as a complete family, to express the average of any two-Green's-function correlator and find they can be solved by a set of linear equations. As an important result, the averaged nonequilibrium density matrix, averaged current, disorder-induced current fluctuation, and averaged shot noise, which involve different two-Green's-function correlators, can all be derived and computed in an effective and unified way. To test the general applicability of this method, we applied it to compute the transmission coefficient and its fluctuation with a square-lattice tight-binding model and compared with the exact results and other previously proposed approximations. Our results show very good agreement with the exact results for a wide range of disorder concentrations and energies. In addition, to incorporate with density functional theory to realize first-principles quantum transport simulation, we have also derived a general form of conditionally averaged nonequilibrium Green's function for multicomponent disorders.

Anomalous effects of radioactive decay rates and capacitance values measured inside a modified Faraday cage: Correlations with space weather

NASA Astrophysics Data System (ADS)

Scholkmann, F.; Milián-Sánchez, V.; Mocholí-Salcedo, A.; Milián, C.; Kolombet, V. A.; Verdú, G.

2017-03-01

Recently we reported (Milián-Sánchez V. et al., Nucl. Instrum. Methods A, 828 (2016) 210) our experimental results involving 226Ra decay rate and capacitance measurements inside a modified Faraday cage. Our measurements exhibited anomalous effects of unknown origin. In this letter we report new results regarding our investigation into the origins of the observed effects. We report preliminary findings of a correlation analysis between the radioactive decay rates and capacitance time series and space weather related variables (geomagnetic field disturbances and cosmic-ray neutron counts). A significant correlation was observed for specific data sets. The results are presented and possible implications for future work discussed.

Local unitary transformation method toward practical electron correlation calculations with scalar relativistic effect in large-scale molecules

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

Seino, Junji; Nakai, Hiromi, E-mail: nakai@waseda.jp; Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555

In order to perform practical electron correlation calculations, the local unitary transformation (LUT) scheme at the spin-free infinite-order Douglas–Kroll–Hess (IODKH) level [J. Seino and H. Nakai, J. Chem. Phys.136, 244102 (2012); J. Seino and H. Nakai, J. Chem. Phys.137, 144101 (2012)], which is based on the locality of relativistic effects, has been combined with the linear-scaling divide-and-conquer (DC)-based Hartree–Fock (HF) and electron correlation methods, such as the second-order Møller–Plesset (MP2) and the coupled cluster theories with single and double excitations (CCSD). Numerical applications in hydrogen halide molecules, (HX){sub n} (X = F, Cl, Br, and I), coinage metal chain systems,more » M{sub n} (M = Cu and Ag), and platinum-terminated polyynediyl chain, trans,trans-((p-CH{sub 3}C{sub 6}H{sub 4}){sub 3}P){sub 2}(C{sub 6}H{sub 5})Pt(C≡C){sub 4}Pt(C{sub 6}H{sub 5})((p-CH{sub 3}C{sub 6}H{sub 4}){sub 3}P){sub 2}, clarified that the present methods, namely DC-HF, MP2, and CCSD with the LUT-IODKH Hamiltonian, reproduce the results obtained using conventional methods with small computational costs. The combination of both LUT and DC techniques could be the first approach that achieves overall quasi-linear-scaling with a small prefactor for relativistic electron correlation calculations.« less

Development and Application of Explicitly Correlated Wave Function Based Methods for the Investigation of Optical Properties of Semiconductor Nanomaterials

NASA Astrophysics Data System (ADS)

Elward, Jennifer Mary

Semiconductor nanoparticles, or quantum dots (QDs), are well known to have very unique optical and electronic properties. These properties can be controlled and tailored as a function of several influential factors, including but not limited to the particle size and shape, effect of composition and heterojunction as well as the effect of ligand on the particle surface. This customizable nature leads to extensive experimental and theoretical research on the capabilities of these quantum dots for many application purposes. However, in order to be able to understand and thus further the development of these materials, one must first understand the fundamental interaction within these nanoparticles. In this thesis, I have developed a theoretical method which is called electron-hole explicitly correlated Hartee-Fock (eh-XCHF). It is a variational method for solving the electron-hole Schrodinger equation and has been used in this work to study electron-hole interaction in semiconductor quantum dots. The method was benchmarked with respect to a parabolic quantum dot system, and ground state energy and electron-hole recombination probability were computed. Both of these properties were found to be in good agreement with expected results. Upon successful benchmarking, I have applied the eh-XCHF method to study optical properties of several quantum dot systems including the effect of dot size on exciton binding energy and recombination probability in a CdSe quantum dot, the effect of shape on a CdSe quantum dot, the effect of heterojunction on a CdSe/ZnS quantum dot and the effect of quantum dot-biomolecule interaction within a CdSe-firefly Luciferase protein conjugate system. As metrics for assessing the effect of these influencers on the electron-hole interaction, the exciton binding energy, electron-hole recombination probability and the average electron-hole separation distance have been computed. These excitonic properties have been found to be strongly infuenced by the changing composition of the particle. It has also been found through this work that the explicitly correlated method performs very well when computing these properties as it provides a feasible computational route to compare to both experimental and other theoretical results.

Correlation effects during liquid infiltration into hydrophobic nanoporous media

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

Borman, V. D., E-mail: vdborman@mephi.ru; Belogorlov, A. A.; Byrkin, V. A.

To explain the thermal effects observed during the infiltration of a nonwetting liquid into a disordered nanoporous medium, we have constructed a model that includes correlation effects in a disordered medium. It is based on analytical methods of the percolation theory. The infiltration of a porous medium is considered as the infiltration of pores in an infinite cluster of interconnected pores. Using the model of randomly situated spheres (RSS), we have been able to take into account the correlation effect of the spatial arrangement and connectivity of pores in the medium. The other correlation effect of the mutual arrangement ofmore » filled and empty pores on the shell of an infinite percolation cluster of filled pores determines the infiltration fluctuation probability. This probability has been calculated analytically. Allowance for these correlation effects during infiltration and defiltration makes it possible to suggest a physical mechanism of the contact angle hysteresis and to calculate the dependences of the contact angles on the degree of infiltration, porosity of the medium, and temperature. Based on the suggested model, we have managed to describe the temperature dependences of the infiltration and defiltration pressures and the thermal effects that accompany the absorption of energy by disordered porous medium-nonwetting liquid systems with various porosities in a unified way.« less

[The effect of an exercise program to strengthen pelvic floor muscles in multiparous women].

PubMed

Assis, Thaís Rocha; Sá, Ana Claudia Antonio Maranhão; Amaral, Waldemar Naves do; Batista, Elicéia Marcia; Formiga, Cibelle Kayenne Martins Roberto; Conde, Délio Marques

2013-01-01

To investigate the effect of an individualized and supervised exercise program for the pelvic floor muscles (PFM) in the postpartum period of multiparous women, and to verify the correlation between two methods used to assess PFM strength. An open clinical trial was performed with puerperal, multiparous women aged 18 to 35 years. The sample consisted of 23 puerperal women divided into two groups: Intervention Group (IG, n=11) and Control Group (CG, n=12). The puerperal women in IG participated in an eight-week PFM exercise program, twice a week. The puerperal women in CG did not receive any recommendations regarding exercise. PFM strength was assessed using digital vaginal palpation and a perineometer. The statistical analysis was performed using the following tests: Fisher's exact, χ(2), Student's t, Kolmogorov-Smirnov for two samples, and Pearson's correlation coefficient. Significance was defined as p<0.05. The participants' mean age was 24 ± 4.5 years in IG and 25.3 ± 4 years in CG (p=0.4). After the exercise program, a significant difference was found between the groups in both modalities of muscle strength assessment (p<0.001). The two muscle strength assessment methods showed a significant correlation in both assessments (1(st) assessment: r=0.889, p<0.001; 2(nd) assessment: r=0.925, p<0.001). The exercise program promoted a significant improvement in PFM strength. Good correlation was observed between digital vaginal palpation and a perineometer, which indicates that vaginal palpation can be used in clinical practice, since it is an inexpensive method that demonstrated significant correlation with an objective method, i.e. the use of a perioneometer.

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.

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

PubMed

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

2016-07-22

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

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

PubMed Central

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

2016-01-01

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

A correlation method to predict the surface pressure distribution of an infinite plate or a body of revolution from which a jet is issuing

NASA Technical Reports Server (NTRS)

Perkins, S. C., Jr.; Mendenhall, M. R.

1980-01-01

A correlation method to predict pressures induced on an infinite plate by a jet exhausting normal to the plate into a subsonic free stream was extended to jets exhausting at angles to the plate and to jets exhausting normal to the surface of a body revolution. The complete method consisted of an analytical method which models the blockage and entrainment properties of the jet and an empirical correlation which accounts for viscous effects. For the flat plate case, the method was applicable to jet velocity ratios up to ten, jet inclination angles up to 45 deg from the normal, and radial distances up to five diameters from the jet. For the body of revolution case, the method was applicable to a body at zero degrees angle of attack, jet velocity ratios 1.96 and 3.43, circumferential angles around the body up to 25 deg from the jet, axial distances up to seven diameters from the jet, and jet-to-body diameter ratios less than 0.1.

Performance analysis of structured gradient algorithm. [for adaptive beamforming linear arrays

NASA Technical Reports Server (NTRS)

Godara, Lal C.

1990-01-01

The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.

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.

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

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Relativistic coupled-cluster-theory analysis of energies, hyperfine-structure constants, and dipole polarizabilities of Cd+

NASA Astrophysics Data System (ADS)

Li, Cheng-Bin; Yu, Yan-Mei; Sahoo, B. K.

2018-02-01

Roles of electron correlation effects in the determination of attachment energies, magnetic-dipole hyperfine-structure constants, and electric-dipole (E 1 ) matrix elements of the low-lying states in the singly charged cadmium ion (Cd+) have been analyzed. We employ the singles and doubles approximated relativistic coupled-cluster (RCC) method to calculate these properties. Intermediate results from the Dirac-Hartree-Fock approximation,the second-order many-body perturbation theory, and considering only the linear terms of the RCC method are given to demonstrate propagation of electron correlation effects in this ion. Contributions from important RCC terms are also given to highlight the importance of various correlation effects in the evaluation of these properties. At the end, we also determine E 1 polarizabilities (αE 1) of the ground and 5 p 2P1 /2 ;3 /2 states of Cd+ in the ab initio approach. We estimate them again by replacing some of the E 1 matrix elements and energies from the measurements to reduce their uncertainties so that they can be used in the high-precision experiments of this ion.

[Interparental conflict and mental health in children and adolescents: the mediating effect of self-concept].

PubMed

Gao, Meng; Li, Yu-Chen; Zhang, Wei

2017-04-01

To examine the mediating effect of self-concept between interparental conflict and mental health in children and adolescents. A total of 689 students (10-18 years) were surveyed using the convenient sampling method, and their mental health, self-concept, and interparental conflict were examined by the general status questionnaire, Strengths and Difficulties Questionnaire, Self-Description Questionnaire, and Children's Perception of Interparental Conflict Scale. Structural equation modeling (SEM) and simultaneous analysis of several groups were used to construct the mediator model and analyze the data, respectively. The Bootstrap method was used to assess the significance of the mediating effects. Interparental conflict was positively correlated with mental health of children and adolescents (P<0.05), but was negatively correlated with self-concept (P<0.01). Self-concept was negatively correlated with mental health (P<0.01). Self-concept had a partial (60%) mediating effect between interparental conflict and mental health. Academic stage, but not gender, had a regulatory role on interparental conflict, mental health, and self-concept. Self-concept plays an important role between interparental conflict and mental health. It is necessary to improve self-concept level in children and adolescents exposed to interparental conflict.

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

DOE PAGES

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

2017-08-01

Here, we describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. This apparatus employs a novel measurement technique in which the angular correlation is converted into a proton time-of-flight asymmetry that is counted directly, avoiding the need for proton spectroscopy. We present details of the method, apparatus, detectors, data acquisition, and data reduction scheme, along with a discussion of the important systematic effects.

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

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

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

Here, we describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. This apparatus employs a novel measurement technique in which the angular correlation is converted into a proton time-of-flight asymmetry that is counted directly, avoiding the need for proton spectroscopy. We present details of the method, apparatus, detectors, data acquisition, and data reduction scheme, along with a discussion of the important systematic effects.

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

PubMed

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

2017-08-01

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

Correlation Study Of Diffenrential Skin Temperatures (DST) For Ovulation Detection Using Infra-Red Thermography

NASA Astrophysics Data System (ADS)

Rao, K. H. S.; Shah, A. v.; Ruedi, B.

1982-11-01

The importance of ovulation time detection in the Practice of Natural Birth Control (NBC) as a contraceptive tool, and for natural/artificial insemination among women having the problem of in-fertility, is well known. The simple Basal Body Temperature (BBT) method of ovulation detection is so far unreliable. A newly proposed Differential Skin Temperature (DST) method may help minimize disturbing physiological effects and improve reliability. This paper explains preliminary results of a detailed correlative study on the DST method, using Infra-Red Thermography (IRT) imaging, and computer analysis techniques. Results obtained with five healthy, normally menstruating women volunteers will be given.

Comparison of theoretically predicted lateral-directional aerodynamic characteristics with full-scale wind tunnel data on the ATLIT airplane

NASA Technical Reports Server (NTRS)

Griswold, M.; Roskam, J.

1980-01-01

An analytical method is presented for predicting lateral-directional aerodynamic characteristics of light twin engine propeller-driven airplanes. This method is applied to the Advanced Technology Light Twin Engine airplane. The calculated characteristics are correlated against full-scale wind tunnel data. The method predicts the sideslip derivatives fairly well, although angle of attack variations are not well predicted. Spoiler performance was predicted somewhat high but was still reasonable. The rudder derivatives were not well predicted, in particular the effect of angle of attack. The predicted dynamic derivatives could not be correlated due to lack of experimental data.

Evaluation of dysphagia in early stroke patients by bedside, endoscopic, and electrophysiological methods.

PubMed

Umay, Ebru Karaca; Unlu, Ece; Saylam, Guleser Kılıc; Cakci, Aytul; Korkmaz, Hakan

2013-09-01

We aimed in this study to evaluate dysphagia in early stroke patients using a bedside screening test and flexible fiberoptic endoscopic evaluation of swallowing (FFEES) and electrophysiological evaluation (EE) methods and to compare the effectiveness of these methods. Twenty-four patients who were hospitalized in our clinic within the first 3 months after stroke were included in this study. Patients were evaluated using a bedside screening test [including bedside dysphagia score (BDS), neurological examination dysphagia score (NEDS), and total dysphagia score (TDS)] and FFEES and EE methods. Patients were divided into normal-swallowing and dysphagia groups according to the results of the evaluation methods. Patients with dysphagia as determined by any of these methods were compared to the patients with normal swallowing based on the results of the other two methods. Based on the results of our study, a high BDS was positively correlated with dysphagia identified by FFEES and EE methods. Moreover, the FFEES and EE methods were positively correlated. There was no significant correlation between NEDS and TDS levels and either EE or FFEES method. Bedside screening tests should be used mainly as an initial screening test; then FFEES and EE methods should be combined in patients who show risks. This diagnostic algorithm may provide a practical and fast solution for selected stroke patients.

Correlative Super-Resolution Microscopy: New Dimensions and New Opportunities.

PubMed

Hauser, Meghan; Wojcik, Michal; Kim, Doory; Mahmoudi, Morteza; Li, Wan; Xu, Ke

2017-06-14

Correlative microscopy, the integration of two or more microscopy techniques performed on the same sample, produces results that emphasize the strengths of each technique while offsetting their individual weaknesses. Light microscopy has historically been a central method in correlative microscopy due to its widespread availability, compatibility with hydrated and live biological samples, and excellent molecular specificity through fluorescence labeling. However, conventional light microscopy can only achieve a resolution of ∼300 nm, undercutting its advantages in correlations with higher-resolution methods. The rise of super-resolution microscopy (SRM) over the past decade has drastically improved the resolution of light microscopy to ∼10 nm, thus creating exciting new opportunities and challenges for correlative microscopy. Here we review how these challenges are addressed to effectively correlate SRM with other microscopy techniques, including light microscopy, electron microscopy, cryomicroscopy, atomic force microscopy, and various forms of spectroscopy. Though we emphasize biological studies, we also discuss the application of correlative SRM to materials characterization and single-molecule reactions. Finally, we point out current limitations and discuss possible future improvements and advances. We thus demonstrate how a correlative approach adds new dimensions of information and provides new opportunities in the fast-growing field of SRM.

Self-worth and psychological adjustment of obese children: An analysis through the Draw-A-Person

PubMed Central

Scimeca, Giuseppe; Alborghetti, Amelia; Bruno, Antonio; Troili, Giulia Maria; Pandolfo, Gianluca; Muscatello, Maria Rosaria Anna; Zoccali, Rocco Antonio

2016-01-01

AIM To investigate psychopathological correlates of child obesity via the Draw-A-Person test (DAP). METHODS The participants were 50 children with a mean age of 9.74 years. Body mass index (BMI) was used as a measure of body fat. Children were divided into normal (n = 17), overweight (n = 14) and obese (n = 19). Two qualitative methods of scoring the DAP based on an integrative approach were used to assess self-concept (ESW) and overall level of children’s adjustment (EAC). A procedure for judging interpretative skills of clinicians was implemented before they evaluated children’s drawings. RESULTS As predicted by our hypothesis, BMI was negatively correlated with ESW, r (50) = -0.29, P < 0.05, but not with EAC, r (50) = - 0.08, P = ns. To evaluate the effect of gender, Pearson correlations were re-computed regrouping the sample accordingly: BMI and EAC reached a significant negative correlation in female subjects, r (24) = -0.36, P < 0.05, and a positive correlation in male subjects, r (26) = 0.37, P = < 0.05; negative correlation between BMI and ESW became stronger in females, r (24) = -0.51, P < 0.01 but not in males, whose correlation disappeared resulting not-significant, r (26) = -0.06, P = ns. No effect of age was found. Results indicate that obesity has a negative correlation exclusively on overall adjustment and self-concept in female children. CONCLUSION It was concluded that there is a negative bias toward females that reveals how the stigma of obesity is widespread in Western society. PMID:27679772

Publication Bias in Psychology: A Diagnosis Based on the Correlation between Effect Size and Sample Size

PubMed Central

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

Background The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. Methods We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values. Results We found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings. Conclusion The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology. PMID:25192357

Relativistic equation-of-motion coupled-cluster method using open-shell reference wavefunction: Application to ionization potential

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

Pathak, Himadri, E-mail: hmdrpthk@gmail.com; Sasmal, Sudip, E-mail: sudipsasmal.chem@gmail.com; Vaval, Nayana

2016-08-21

The open-shell reference relativistic equation-of-motion coupled-cluster method within its four-component description is successfully implemented with the consideration of single- and double- excitation approximations using the Dirac-Coulomb Hamiltonian. At the first attempt, the implemented method is employed to calculate ionization potential value of heavy atomic (Ag, Cs, Au, Fr, and Lr) and molecular (HgH and PbF) systems, where the effect of relativity does really matter to obtain highly accurate results. Not only the relativistic effect but also the effect of electron correlation is crucial in these heavy atomic and molecular systems. To justify the fact, we have taken two further approximationsmore » in the four-component relativistic equation-of-motion framework to quantify how the effect of electron correlation plays a role in the calculated values at different levels of theory. All these calculated results are compared with the available experimental data as well as with other theoretically calculated values to judge the extent of accuracy obtained in our calculations.« less

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Motivational Correlates of Physical Activity in Persons with an Intellectual Disability: A Systematic Literature Review

ERIC Educational Resources Information Center

Hutzler, Y.; Korsensky, O.

2010-01-01

Background: The purpose of this study is to systematically retrieve, examine and discuss scientific studies focusing on motivational correlates that both contribute to, and can be assumed to be effects of, participation in sport, recreation, or health-related physical activities in persons with intellectual disability (ID). Methods: A systematic…

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

PubMed

Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

FAST TRACK COMMUNICATION A DFT + DMFT approach for nanosystems

NASA Astrophysics Data System (ADS)

Turkowski, Volodymyr; Kabir, Alamgir; Nayyar, Neha; Rahman, Talat S.

2010-11-01

We propose a combined density-functional-theory-dynamical-mean-field-theory (DFT + DMFT) approach for reliable inclusion of electron-electron correlation effects in nanosystems. Compared with the widely used DFT + U approach, this method has several advantages, the most important of which is that it takes into account dynamical correlation effects. The formalism is illustrated through different calculations of the magnetic properties of a set of small iron clusters (number of atoms 2 <= N <= 5). It is shown that the inclusion of dynamical effects leads to a reduction in the cluster magnetization (as compared to results from DFT + U) and that, even for such small clusters, the magnetization values agree well with experimental estimations. These results justify confidence in the ability of the method to accurately describe the magnetic properties of clusters of interest to nanoscience.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Air film cooling in a nonadiabatic wall conical nozzle.

NASA Technical Reports Server (NTRS)

Boldman, D. R.; Papell, S. S.; Ehlers, R. C.

1972-01-01

Experimental data for an air-film cooled conical nozzle operating with a heated-air main stream and a water-cooled wall confirm the validity of Lieu's (1964) method for correlating film cooling data in the accelerated flow of a nonadiabatic-wall nozzle. The film cooling effectiveness modified for nonadiabatic walls by Lieu can be used to correlate film cooling under the condition that the main-stream to coolant velocity ratio at the slot is about 1. Such a ratio provides the optimum cooling effectiveness.

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.

Improvement in the measurement error of the specific binding ratio in dopamine transporter SPECT imaging due to exclusion of the cerebrospinal fluid fraction using the threshold of voxel RI count.

PubMed

Mizumura, Sunao; Nishikawa, Kazuhiro; Murata, Akihiro; Yoshimura, Kosei; Ishii, Nobutomo; Kokubo, Tadashi; Morooka, Miyako; Kajiyama, Akiko; Terahara, Atsuro

2018-05-01

In Japan, the Southampton method for dopamine transporter (DAT) SPECT is widely used to quantitatively evaluate striatal radioactivity. The specific binding ratio (SBR) is the ratio of specific to non-specific binding observed after placing pentagonal striatal voxels of interest (VOIs) as references. Although the method can reduce the partial volume effect, the SBR may fluctuate due to the presence of low-count areas of cerebrospinal fluid (CSF), caused by brain atrophy, in the striatal VOIs. We examined the effect of the exclusion of low-count VOIs on SBR measurement. We retrospectively reviewed DAT imaging of 36 patients with parkinsonian syndromes performed after injection of 123 I-FP-CIT. SPECT data were reconstructed using three conditions. We defined the CSF area in each SPECT image after segmenting the brain tissues. A merged image of gray and white matter images was constructed from each patient's magnetic resonance imaging (MRI) to create an idealized brain image that excluded the CSF fraction (MRI-mask method). We calculated the SBR and asymmetric index (AI) in the MRI-mask method for each reconstruction condition. We then calculated the mean and standard deviation (SD) of voxel RI counts in the reference VOI without the striatal VOIs in each image, and determined the SBR by excluding the low-count pixels (threshold method) using five thresholds: mean-0.0SD, mean-0.5SD, mean-1.0SD, mean-1.5SD, and mean-2.0SD. We also calculated the AIs from the SBRs measured using the threshold method. We examined the correlation among the SBRs of the threshold method, between the uncorrected SBRs and the SBRs of the MRI-mask method, and between the uncorrected AIs and the AIs of the MRI-mask method. The intraclass correlation coefficient indicated an extremely high correlation among the SBRs and among the AIs of the MRI-mask and threshold methods at thresholds between mean-2.0D and mean-1.0SD, regardless of the reconstruction correction. The differences among the SBRs and the AIs of the two methods were smallest at thresholds between man-2.0SD and mean-1.0SD. The SBR calculated using the threshold method was highly correlated with the MRI-SBR. These results suggest that the CSF correction of the threshold method is effective for the calculation of idealized SBR and AI values.

Application of portable gas detector in point and scanning method to estimate spatial distribution of methane emission in landfill.

PubMed

Lando, Asiyanthi Tabran; Nakayama, Hirofumi; Shimaoka, Takayuki

2017-01-01

Methane from landfills contributes to global warming and can pose an explosion hazard. To minimize these effects emissions must be monitored. This study proposed application of portable gas detector (PGD) in point and scanning measurements to estimate spatial distribution of methane emissions in landfills. The aims of this study were to discover the advantages and disadvantages of point and scanning methods in measuring methane concentrations, discover spatial distribution of methane emissions, cognize the correlation between ambient methane concentration and methane flux, and estimate methane flux and emissions in landfills. This study was carried out in Tamangapa landfill, Makassar city-Indonesia. Measurement areas were divided into basic and expanded area. In the point method, PGD was held one meter above the landfill surface, whereas scanning method used a PGD with a data logger mounted on a wire drawn between two poles. Point method was efficient in time, only needed one person and eight minutes in measuring 400m 2 areas, whereas scanning method could capture a lot of hot spots location and needed 20min. The results from basic area showed that ambient methane concentration and flux had a significant (p<0.01) positive correlation with R 2 =0.7109 and y=0.1544 x. This correlation equation was used to describe spatial distribution of methane emissions in the expanded area by using Kriging method. The average of estimated flux from scanning method was 71.2gm -2 d -1 higher than 38.3gm -2 d -1 from point method. Further, scanning method could capture the lower and higher value, which could be useful to evaluate and estimate the possible effects of the uncontrolled emissions in landfill. Copyright © 2016 Elsevier Ltd. All rights reserved.

An improved evaluation method for measuring TOC of the Longmaxi Formation shale in the Sichuan Basin, south China

NASA Astrophysics Data System (ADS)

Zhang, Y.; Hu, C.; Wang, M.

2017-12-01

The evaluation of total organic carbon (TOC) in shale using logging data is one of the most crucial steps in shale gas exploration. However, it didn't achieve the ideal effect for the application of `ΔlogR' method in the Longmaxi Formation shale of Sichuan Basin.The reason may be the organic matter carbonization in Longmaxi Formation. An improved evaluation method, using the classification by lithology and sedimentary structure: 1) silty mudstone (wellsite logging data show silty); 2) calcareous mudstone (calcareous content > 25%); 3) laminated mudstone (laminations are recognized by core and imaging logging technology); 4) massive mudstone (massive textures are recognized by core and imaging logging technology, was proposed. This study compares two logging evaluation methods for measuring TOC in shale: the △logR method and the new proposed method. The results showed that the correlation coefficient between the calculated TOC and the tested TOC, based on the △logR method, was only 0.17. The correlation coefficient obtained according to the new method reached 0.80. The calculation results illustrated that, because of the good correlation between lithologies and sedimentary structure zones and TOC of different types of shale, the shale reservoirs could be graded according to four shale types. The new proposed method is more efficient, faster, and has higher vertical resolution than the △logR method. In addition, a new software had been completed. It was found to be especially effective under conditions of insufficient data during the early stages of shale gas exploration in the Silurian Longmaxi Formation, Muai Syncline Belt, south of the Sichuan Basin.

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

Jason L. Wright; Milos Manic

Time synchronization and event time correlation are important in wireless sensor networks. In particular, time is used to create a sequence events or time line to answer questions of cause and effect. Time is also used as a basis for determining the freshness of received packets and the validity of cryptographic certificates. This paper presents secure method of time synchronization and event time correlation for TESLA-based hierarchical wireless sensor networks. The method demonstrates that events in a TESLA network can be accurately timestamped by adding only a few pieces of data to the existing protocol.

On the interpretation of domain averaged Fermi hole analyses of correlated wavefunctions.

PubMed

Francisco, E; Martín Pendás, A; Costales, Aurora

2014-03-14

Few methods allow for a physically sound analysis of chemical bonds in cases where electron correlation may be a relevant factor. The domain averaged Fermi hole (DAFH) analysis, a tool firstly proposed by Robert Ponec in the 1990's to provide interpretations of the chemical bonding existing between two fragments Ω and Ω' that divide the real space exhaustively, is one of them. This method allows for a partition of the delocalization index or bond order between Ω and Ω' into one electron contributions, but the chemical interpretation of its parameters has been firmly established only for single determinant wavefunctions. In this paper we report a general interpretation based on the concept of excluded density that is also valid for correlated descriptions. Both analytical models and actual computations on a set of simple molecules (H2, N2, LiH, and CO) are discussed, and a classification of the possible DAFH situations is presented. Our results show that this kind of analysis may reveal several correlated assisted bonding patterns that might be difficult to detect using other methods. In agreement with previous knowledge, we find that the effective bond order in covalent links decreases due to localization of electrons driven by Coulomb correlation.

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope

NASA Astrophysics Data System (ADS)

Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau

2012-05-01

This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror.

Comparison of common lignin methods and modifications on forage and lignocellulosic biomass materials.

PubMed

Goff, Ben M; Murphy, Patrick T; Moore, Kenneth J

2012-03-15

A variety of methods have been developed for estimating lignin concentration within plant materials. The objective of this study was to compare the lignin concentrations produced by six methods on a diverse population of forage and biomass materials and to examine the relationship between these concentrations and the portions of these materials that are available for utilisation by livestock or for ethanol conversion. Several methods produced lignin concentrations that were highly correlated with the digestibility of the forages, but there were few relationships between these methods and the available carbohydrate of the biomass materials. The use of Na₂SO₃ during preparation of residues for hydrolysis resulted in reduced lignin concentrations and decreased correlation with digestibility of forage materials, particularly the warm-season grasses. There were several methods that were well suited for predicting the digestible portion of forage materials, with the acid detergent lignin and Klason lignin method giving the highest correlation across the three types of forage. The continued use of Na₂SO₃ during preparation of Van Soest fibres needs to be evaluated owing to its ability to reduce lignin concentrations and effectiveness in predicting the utilisation of feedstuffs and feedstocks. Because there was little correlation between the lignin concentration and the biomass materials, there is a need to examine alternative or develop new methods to estimate lignin concentrations that may be used to predict the availability of carbohydrates for ethanol conversion. Copyright © 2011 Society of Chemical Industry.

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.

Ambient Noise Correlation Amplitudes and Local Site Response

NASA Astrophysics Data System (ADS)

Bowden, D. C.; Tsai, V. C.; Lin, F. C.

2014-12-01

We investigate amplitudes from ambient noise cross correlations in a spatially dense array. Our study of wave propagation effects and ambient noise is focused on the Long Beach Array, with more than 5000 single component geophones in an area of about 100 square kilometers, providing high resolution imaging of shallow crustal features. The method allows for observations of ground properties like site response and attenuation, which can well supplement traditional velocity models and simulations for seismic hazard. Traditional ambient noise cross correlations have proven to be an effective means of measuring velocity information about surface waves, but the amplitudes of such signals in traditional processing are often distorted. We discuss a method of signal processing which preserves relative amplitudes of signals within an array, and the subsequent processing to track wave motion across the array. Previous work showed promising correlation to known local structure, but did not represent a thorough application of tomographic methods. Now we extend the methodology to more robustly consider wavefront focusing and defocusing, interference with higher modes, and discuss the differing effects of local site response, attenuation, and scattering. Application of Helmholtz tomography and determination of local site amplification has previously been demonstrated using earthquake data on the continental scale with USArray, but the exploitation of the ambient noise field is required both for the higher frequencies needed by seismic hazard studies and for the short deployment time of a Long Beach scale array. We outline both the successes and shortcomings of the methodology, and show how it can be extended for use on future arrays.

Susceptibility Testing of Medically Important Parasites.

PubMed

Genetu Bayih, Abebe; Debnath, Anjan; Mitre, Edward; Huston, Christopher D; Laleu, Benoît; Leroy, Didier; Blasco, Benjamin; Campo, Brice; Wells, Timothy N C; Willis, Paul A; Sjö, Peter; Van Voorhis, Wesley C; Pillai, Dylan R

2017-07-01

In the last 2 decades, renewed attention to neglected tropical diseases (NTDs) has spurred the development of antiparasitic agents, especially in light of emerging drug resistance. The need for new drugs has required in vitro screening methods using parasite culture. Furthermore, clinical laboratories sought to correlate in vitro susceptibility methods with treatment outcomes, most notably with malaria. Parasites with their various life cycles present greater complexity than bacteria, for which standardized susceptibility methods exist. This review catalogs the state-of-the-art methodologies used to evaluate the effects of drugs on key human parasites from the point of view of drug discovery as well as the need for laboratory methods that correlate with clinical outcomes. Copyright © 2017 American Society for Microbiology.

Application of firefly luciferase assay for adenosine triphosphate (ATP) to antimicrobial drug sensitivity testing

NASA Technical Reports Server (NTRS)

Picciolo, G. L.; Tuttle, S. A.; Schrock, C. G.; Deming, J. W.; Barza, M. J.; Wienstein, L.; Chappelle, E. W.

1977-01-01

The development of a rapid method for determining microbial susceptibilities to antibiotics using the firefly luciferase assay for adenosine triphosphate (ATP) is documented. The reduction of bacterial ATP by an antimicrobial agent was determined to be a valid measure of drug effect in most cases. The effect of 12 antibiotics on 8 different bacterial species gave a 94 percent correlation with the standard Kirby-Buer-Agar disc diffusion method. A 93 percent correlation was obtained when the ATP assay method was applied directly to 50 urine specimens from patients with urinary tract infections. Urine samples were centrifuged first to that bacterial pellets could be suspended in broth. No primary isolation or subculturing was required. Mixed cultures in which one species was predominant gave accurate results for the most abundant organism. Since the method is based on an increase in bacterial ATP with time, the presence of leukocytes did not interfere with the interpretation of results. Both the incubation procedure and the ATP assays are compatible with automation.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

NASA Astrophysics Data System (ADS)

Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

2017-10-01

Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution, appendix 2

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1988-01-01

This thesis reviews the technique established to clear channels in the Power Spectral Estimate by applying linear combinations of well known window functions to the autocorrelation function. The need for windowing the auto correlation function is due to the fact that the true auto correlation is not generally used to obtain the Power Spectral Estimate. When applied, the windows serve to reduce the effect that modifies the auto correlation by truncating the data and possibly the autocorrelation has on the Power Spectral Estimate. It has been shown in previous work that a single channel has been cleared, allowing for the detection of a small peak in the presence of a large peak in the Power Spectral Estimate. The utility of this method is dependent on the robustness of it on different input situations. We extend the analysis in this paper, to include clearing up to three channels. We examine the relative positions of the spikes to each other and also the effect of taking different percentages of lags of the auto correlation in the Power Spectral Estimate. This method could have application wherever the Power Spectrum is used. An example of this is beam forming for source location, where a small target can be located next to a large target. Other possibilities extend into seismic data processing. As the method becomes more automated other applications may present themselves.

A basic guide to overlay design using nondestructive testing equipment data

NASA Astrophysics Data System (ADS)

Turner, Vernon R.

1990-08-01

The purpose of this paper is to provide a basic and concise guide to designing asphalt concrete (AC) overlays over existing AC pavements. The basis for these designs is deflection data obtained from nondestructive testing (NDT) equipment. This data is used in design procedures which produce required overlay thickness or an estimate of remaining pavement life. This guide enables one to design overlays or better monitor the designs being performed by others. This paper will discuss three types of NDT equipment, the Asphalt Institute Overlay Designs by Deflection Analysis and by the effective thickness method as well as a method of estimating remaining pavement life, correlations between NDT equipment and recent correlations in Washington State. Asphalt overlays provide one of the most cost effective methods of improving existing pavements. Asphalt overlays can be used to strengthen existing pavements, to reduce maintenance costs, to increase pavement life, to provide a smoother ride, and to improve skid resistance.

Effect of Malmquist bias on correlation studies with IRAS data base

NASA Technical Reports Server (NTRS)

Verter, Frances

1993-01-01

The relationships between galaxy properties in the sample of Trinchieri et al. (1989) are reexamined with corrections for Malmquist bias. The linear correlations are tested and linear regressions are fit for log-log plots of L(FIR), L(H-alpha), and L(B) as well as ratios of these quantities. The linear correlations for Malmquist bias are corrected using the method of Verter (1988), in which each galaxy observation is weighted by the inverse of its sampling volume. The linear regressions are corrected for Malmquist bias by a new method invented here in which each galaxy observation is weighted by its sampling volume. The results of correlation and regressions among the sample are significantly changed in the anticipated sense that the corrected correlation confidences are lower and the corrected slopes of the linear regressions are lower. The elimination of Malmquist bias eliminates the nonlinear rise in luminosity that has caused some authors to hypothesize additional components of FIR emission.

Beyond Kohn-Sham Approximation: Hybrid Multistate Wave Function and Density Functional Theory.

PubMed

Gao, Jiali; Grofe, Adam; Ren, Haisheng; Bao, Peng

2016-12-15

A multistate density functional theory (MSDFT) is presented in which the energies and densities for the ground and excited states are treated on the same footing using multiconfigurational approaches. The method can be applied to systems with strong correlation and to correctly describe the dimensionality of the conical intersections between strongly coupled dissociative potential energy surfaces. A dynamic-then-static framework for treating electron correlation is developed to first incorporate dynamic correlation into contracted state functions through block-localized Kohn-Sham density functional theory (KSDFT), followed by diagonalization of the effective Hamiltonian to include static correlation. MSDFT can be regarded as a hybrid of wave function and density functional theory. The method is built on and makes use of the current approximate density functional developed in KSDFT, yet it retains its computational efficiency to treat strongly correlated systems that are problematic for KSDFT but too large for accurate WFT. The results presented in this work show that MSDFT can be applied to photochemical processes involving conical intersections.

The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis.

PubMed

Af Wåhlberg, A E; Barraclough, P; Freeman, J

2015-12-01

The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include unpublished results. The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, using the mean of accidents as proxy for effect indicated that studies where effects for violations are not reported have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which tendencies are controlled for. Methodological factors and dissemination bias have inflated the published effect sizes of the DBQ. Strong evidence of various artefactual effects is apparent. A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Computing thermal Wigner densities with the phase integration method

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

Beutier, J.; Borgis, D.; Vuilleumier, R.

2014-08-28

We discuss how the Phase Integration Method (PIM), recently developed to compute symmetrized time correlation functions [M. Monteferrante, S. Bonella, and G. Ciccotti, Mol. Phys. 109, 3015 (2011)], can be adapted to sampling/generating the thermal Wigner density, a key ingredient, for example, in many approximate schemes for simulating quantum time dependent properties. PIM combines a path integral representation of the density with a cumulant expansion to represent the Wigner function in a form calculable via existing Monte Carlo algorithms for sampling noisy probability densities. The method is able to capture highly non-classical effects such as correlation among the momenta andmore » coordinates parts of the density, or correlations among the momenta themselves. By using alternatives to cumulants, it can also indicate the presence of negative parts of the Wigner density. Both properties are demonstrated by comparing PIM results to those of reference quantum calculations on a set of model problems.« less

Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach.

PubMed

Viladomat, Júlia; Mazumder, Rahul; McInturff, Alex; McCauley, Douglas J; Hastie, Trevor

2014-06-01

We propose a method to test the correlation of two random fields when they are both spatially autocorrelated. In this scenario, the assumption of independence for the pair of observations in the standard test does not hold, and as a result we reject in many cases where there is no effect (the precision of the null distribution is overestimated). Our method recovers the null distribution taking into account the autocorrelation. It uses Monte-Carlo methods, and focuses on permuting, and then smoothing and scaling one of the variables to destroy the correlation with the other, while maintaining at the same time the initial autocorrelation. With this simulation model, any test based on the independence of two (or more) random fields can be constructed. This research was motivated by a project in biodiversity and conservation in the Biology Department at Stanford University. © 2014, The International Biometric Society.

Computing thermal Wigner densities with the phase integration method.

PubMed

Beutier, J; Borgis, D; Vuilleumier, R; Bonella, S

2014-08-28

We discuss how the Phase Integration Method (PIM), recently developed to compute symmetrized time correlation functions [M. Monteferrante, S. Bonella, and G. Ciccotti, Mol. Phys. 109, 3015 (2011)], can be adapted to sampling/generating the thermal Wigner density, a key ingredient, for example, in many approximate schemes for simulating quantum time dependent properties. PIM combines a path integral representation of the density with a cumulant expansion to represent the Wigner function in a form calculable via existing Monte Carlo algorithms for sampling noisy probability densities. The method is able to capture highly non-classical effects such as correlation among the momenta and coordinates parts of the density, or correlations among the momenta themselves. By using alternatives to cumulants, it can also indicate the presence of negative parts of the Wigner density. Both properties are demonstrated by comparing PIM results to those of reference quantum calculations on a set of model problems.

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

On the insignificance of Herschel's sunspot correlation

NASA Astrophysics Data System (ADS)

Love, Jeffrey J.

2013-08-01

We examine William Herschel's hypothesis that solar-cycle variation of the Sun's irradiance has a modulating effect on the Earth's climate and that this is, specifically, manifested as an anticorrelation between sunspot number and the market price of wheat. Since Herschel first proposed his hypothesis in 1801, it has been regarded with both interest and skepticism. Recently, reports have been published that either support Herschel's hypothesis or rely on its validity. As a test of Herschel's hypothesis, we seek to reject a null hypothesis of a statistically random correlation between historical sunspot numbers, wheat prices in London and the United States, and wheat farm yields in the United States. We employ binary-correlation, Pearson-correlation, and frequency-domain methods. We test our methods using a historical geomagnetic activity index, well known to be causally correlated with sunspot number. As expected, the measured correlation between sunspot number and geomagnetic activity would be an unlikely realization of random data; the correlation is "statistically significant." On the other hand, measured correlations between sunspot number and wheat price and wheat yield data would be very likely realizations of random data; these correlations are "insignificant." Therefore, Herschel's hypothesis must be regarded with skepticism. We compare and contrast our results with those of other researchers. We discuss procedures for evaluating hypotheses that are formulated from historical data.

What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations

NASA Astrophysics Data System (ADS)

Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.

2017-12-01

The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.

Calibration of the DRASTIC ground water vulnerability mapping method

USGS Publications Warehouse

Rupert, M.G.

2001-01-01

Ground water vulnerability maps developed using the DRASTIC method have been produced in many parts of the world. Comparisons of those maps with actual ground water quality data have shown that the DRASTIC method is typically a poor predictor of ground water contamination. This study significantly improved the effectiveness of a modified DRASTIC ground water vulnerability map by calibrating the point rating schemes to actual ground water quality data by using nonparametric statistical techniques and a geographic information system. Calibration was performed by comparing data on nitrite plus nitrate as nitrogen (NO2 + NO3-N) concentrations in ground water to land-use, soils, and depth to first-encountered ground water data. These comparisons showed clear statistical differences between NO2 + NO3-N concentrations and the various categories. Ground water probability point ratings for NO2 + NO3-N contamination were developed from the results of these comparisons, and a probability map was produced. This ground water probability map was then correlated with an independent set of NO2 + NO3-N data to demonstrate its effectiveness in predicting elevated NO2 + NO3-N concentrations in ground water. This correlation demonstrated that the probability map was effective, but a vulnerability map produced with the uncalibrated DRASTIC method in the same area and using the same data layers was not effective. Considerable time and expense have been outlaid to develop ground water vulnerability maps with the DRASTIC method. This study demonstrates a cost-effective method to improve and verify the effectiveness of ground water vulnerability maps.

Improving regression-model-based streamwater constituent load estimates derived from serially correlated data

USGS Publications Warehouse

Aulenbach, Brent T.

2013-01-01

A regression-model based approach is a commonly used, efficient method for estimating streamwater constituent load when there is a relationship between streamwater constituent concentration and continuous variables such as streamwater discharge, season and time. A subsetting experiment using a 30-year dataset of daily suspended sediment observations from the Mississippi River at Thebes, Illinois, was performed to determine optimal sampling frequency, model calibration period length, and regression model methodology, as well as to determine the effect of serial correlation of model residuals on load estimate precision. Two regression-based methods were used to estimate streamwater loads, the Adjusted Maximum Likelihood Estimator (AMLE), and the composite method, a hybrid load estimation approach. While both methods accurately and precisely estimated loads at the model’s calibration period time scale, precisions were progressively worse at shorter reporting periods, from annually to monthly. Serial correlation in model residuals resulted in observed AMLE precision to be significantly worse than the model calculated standard errors of prediction. The composite method effectively improved upon AMLE loads for shorter reporting periods, but required a sampling interval of at least 15-days or shorter, when the serial correlations in the observed load residuals were greater than 0.15. AMLE precision was better at shorter sampling intervals and when using the shortest model calibration periods, such that the regression models better fit the temporal changes in the concentration–discharge relationship. The models with the largest errors typically had poor high flow sampling coverage resulting in unrepresentative models. Increasing sampling frequency and/or targeted high flow sampling are more efficient approaches to ensure sufficient sampling and to avoid poorly performing models, than increasing calibration period length.

Markov and non-Markov processes in complex systems by the dynamical information entropy

NASA Astrophysics Data System (ADS)

Yulmetyev, R. M.; Gafarov, F. M.

1999-12-01

We consider the Markov and non-Markov processes in complex systems by the dynamical information Shannon entropy (DISE) method. The influence and important role of the two mutually dependent channels of entropy alternation (creation or generation of correlation) and anti-correlation (destroying or annihilation of correlation) have been discussed. The developed method has been used for the analysis of the complex systems of various natures: slow neutron scattering in liquid cesium, psychology (short-time numeral and pattern human memory and effect of stress on the dynamical taping-test), random dynamics of RR-intervals in human ECG (problem of diagnosis of various disease of the human cardio-vascular systems), chaotic dynamics of the parameters of financial markets and ecological systems.

Memory Effects and Nonequilibrium Correlations in the Dynamics of Open Quantum Systems

NASA Astrophysics Data System (ADS)

Morozov, V. G.

2018-01-01

We propose a systematic approach to the dynamics of open quantum systems in the framework of Zubarev's nonequilibrium statistical operator method. The approach is based on the relation between ensemble means of the Hubbard operators and the matrix elements of the reduced statistical operator of an open quantum system. This key relation allows deriving master equations for open systems following a scheme conceptually identical to the scheme used to derive kinetic equations for distribution functions. The advantage of the proposed formalism is that some relevant dynamical correlations between an open system and its environment can be taken into account. To illustrate the method, we derive a non-Markovian master equation containing the contribution of nonequilibrium correlations associated with energy conservation.

Distribution of Response Time, Cortical, and Cardiac Correlates during Emotional Interference in Persons with Subclinical Psychotic Symptoms

PubMed Central

Holper, Lisa K. B.; Aleksandrowicz, Alekandra; Müller, Mario; Ajdacic-Gross, Vladeta; Haker, Helene; Fallgatter, Andreas J.; Hagenmuller, Florence; Kawohl, Wolfram; Rössler, Wulf

2016-01-01

A psychosis phenotype can be observed below the threshold of clinical detection. The study aimed to investigate whether subclinical psychotic symptoms are associated with deficits in controlling emotional interference, and whether cortical brain and cardiac correlates of these deficits can be detected using functional near-infrared spectroscopy (fNIRS). A data set derived from a community sample was obtained from the Zurich Program for Sustainable Development of Mental Health Services. 174 subjects (mean age 29.67 ± 6.41, 91 females) were assigned to four groups ranging from low to high levels of subclinical psychotic symptoms (derived from the Symptom Checklist-90-R). Emotional interference was assessed using the emotional Stroop task comprising neutral, positive, and negative conditions. Statistical distributional methods based on delta plots [behavioral response time (RT) data] and quantile analysis (fNIRS data) were applied to evaluate the emotional interference effects. Results showed that both interference effects and disorder-specific (i.e., group-specific) effects could be detected, based on behavioral RTs, cortical hemodynamic signals (brain correlates), and heart rate variability (cardiac correlates). Subjects with high compared to low subclinical psychotic symptoms revealed significantly reduced amplitudes in dorsolateral prefrontal cortices (interference effect, p < 0.001) and middle temporal gyrus (disorder-specific group effect, p < 0.001), supported by behavioral and heart rate results. The present findings indicate that distributional analyses methods can support the detection of emotional interference effects in the emotional Stroop. The results suggested that subjects with high subclinical psychosis exhibit enhanced emotional interference effects. Based on these observations, subclinical psychosis may therefore prove to represent a valid extension of the clinical psychosis phenotype. PMID:27660608

Distribution of Response Time, Cortical, and Cardiac Correlates during Emotional Interference in Persons with Subclinical Psychotic Symptoms.

PubMed

Holper, Lisa K B; Aleksandrowicz, Alekandra; Müller, Mario; Ajdacic-Gross, Vladeta; Haker, Helene; Fallgatter, Andreas J; Hagenmuller, Florence; Kawohl, Wolfram; Rössler, Wulf

2016-01-01

A psychosis phenotype can be observed below the threshold of clinical detection. The study aimed to investigate whether subclinical psychotic symptoms are associated with deficits in controlling emotional interference, and whether cortical brain and cardiac correlates of these deficits can be detected using functional near-infrared spectroscopy (fNIRS). A data set derived from a community sample was obtained from the Zurich Program for Sustainable Development of Mental Health Services. 174 subjects (mean age 29.67 ± 6.41, 91 females) were assigned to four groups ranging from low to high levels of subclinical psychotic symptoms (derived from the Symptom Checklist-90-R). Emotional interference was assessed using the emotional Stroop task comprising neutral, positive, and negative conditions. Statistical distributional methods based on delta plots [behavioral response time (RT) data] and quantile analysis (fNIRS data) were applied to evaluate the emotional interference effects. Results showed that both interference effects and disorder-specific (i.e., group-specific) effects could be detected, based on behavioral RTs, cortical hemodynamic signals (brain correlates), and heart rate variability (cardiac correlates). Subjects with high compared to low subclinical psychotic symptoms revealed significantly reduced amplitudes in dorsolateral prefrontal cortices (interference effect, p < 0.001) and middle temporal gyrus (disorder-specific group effect, p < 0.001), supported by behavioral and heart rate results. The present findings indicate that distributional analyses methods can support the detection of emotional interference effects in the emotional Stroop. The results suggested that subjects with high subclinical psychosis exhibit enhanced emotional interference effects. Based on these observations, subclinical psychosis may therefore prove to represent a valid extension of the clinical psychosis phenotype.

Method for suppressing noise in measurements

NASA Technical Reports Server (NTRS)

Carson, Paul J. (Inventor); Madsen, Louis A. (Inventor); Leskowitz, Garett M. (Inventor); Weitekamp, Daniel P. (Inventor)

2000-01-01

Techniques of combining separate but correlated measurements to form a second-order or higher order correlation function to suppress the effects of noise in the initial condition of a system capable of retaining memory of an initial state of the system with a characteristic relaxation time. At least two separate measurements are obtained from the system. The temporal separation between the two separate measurements is preferably comparable to or less than the characteristic relaxation time and is adjusted to allow for a correlation between two measurements.

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

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

Effect of interjunction coupling on superconducting current and charge correlations in intrinsic Josephson junctions

NASA Astrophysics Data System (ADS)

Shukrinov, Yu. M.; Hamdipour, M.; Kolahchi, M. R.

2009-07-01

Charge formations on superconducting layers and creation of the longitudinal plasma wave in the stack of intrinsic Josephson junctions change crucially the superconducting current through the stack. Investigation of the correlations of superconducting currents in neighboring Josephson junctions and the charge correlations in neighboring superconducting layers allows us to predict the additional features in the current-voltage characteristics. The charge autocorrelation functions clearly demonstrate the difference between harmonic and chaotic behavior in the breakpoint region. Use of the correlation functions gives us a powerful method for the analysis of the current-voltage characteristics of coupled Josephson junctions.

Multifractal analysis of the Korean agricultural market

NASA Astrophysics Data System (ADS)

Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan

2011-11-01

We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.

Nonlinear gamma correction via normed bicoherence minimization in optical fringe projection metrology

NASA Astrophysics Data System (ADS)

Kamagara, Abel; Wang, Xiangzhao; Li, Sikun

2018-03-01

We propose a method to compensate for the projector intensity nonlinearity induced by gamma effect in three-dimensional (3-D) fringe projection metrology by extending high-order spectra analysis and bispectral norm minimization to digital sinusoidal fringe pattern analysis. The bispectrum estimate allows extraction of vital signal information features such as spectral component correlation relationships in fringe pattern images. Our approach exploits the fact that gamma introduces high-order harmonic correlations in the affected fringe pattern image. Estimation and compensation of projector nonlinearity is realized by detecting and minimizing the normed bispectral coherence of these correlations. The proposed technique does not require calibration information and technical knowledge or specification of fringe projection unit. This is promising for developing a modular and calibration-invariant model for intensity nonlinear gamma compensation in digital fringe pattern projection profilometry. Experimental and numerical simulation results demonstrate this method to be efficient and effective in improving the phase measuring accuracies with phase-shifting fringe pattern projection profilometry.

New insights into time series analysis. II - Non-correlated observations

NASA Astrophysics Data System (ADS)

Ferreira Lopes, C. E.; Cross, N. J. G.

2017-08-01

Context. Statistical parameters are used to draw conclusions in a vast number of fields such as finance, weather, industrial, and science. These parameters are also used to identify variability patterns on photometric data to select non-stochastic variations that are indicative of astrophysical effects. New, more efficient, selection methods are mandatory to analyze the huge amount of astronomical data. Aims: We seek to improve the current methods used to select non-stochastic variations on non-correlated data. Methods: We used standard and new data-mining parameters to analyze non-correlated data to find the best way to discriminate between stochastic and non-stochastic variations. A new approach that includes a modified Strateva function was performed to select non-stochastic variations. Monte Carlo simulations and public time-domain data were used to estimate its accuracy and performance. Results: We introduce 16 modified statistical parameters covering different features of statistical distribution such as average, dispersion, and shape parameters. Many dispersion and shape parameters are unbound parameters, I.e. equations that do not require the calculation of average. Unbound parameters are computed with single loop and hence decreasing running time. Moreover, the majority of these parameters have lower errors than previous parameters, which is mainly observed for distributions with few measurements. A set of non-correlated variability indices, sample size corrections, and a new noise model along with tests of different apertures and cut-offs on the data (BAS approach) are introduced. The number of mis-selections are reduced by about 520% using a single waveband and 1200% combining all wavebands. On the other hand, the even-mean also improves the correlated indices introduced in Paper I. The mis-selection rate is reduced by about 18% if the even-mean is used instead of the mean to compute the correlated indices in the WFCAM database. Even-statistics allows us to improve the effectiveness of both correlated and non-correlated indices. Conclusions: The selection of non-stochastic variations is improved by non-correlated indices. The even-averages provide a better estimation of mean and median for almost all statistical distributions analyzed. The correlated variability indices, which are proposed in the first paper of this series, are also improved if the even-mean is used. The even-parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improvement on the efficiency of selection of variable stars, is now complete. Many of these techniques may be useful for a large number of fields. Next, we will commence a new step of this project regarding the analysis of period search methods.

Exploiting the spatial locality of electron correlation within the parametric two-electron reduced-density-matrix method

NASA Astrophysics Data System (ADS)

DePrince, A. Eugene; Mazziotti, David A.

2010-01-01

The parametric variational two-electron reduced-density-matrix (2-RDM) method is applied to computing electronic correlation energies of medium-to-large molecular systems by exploiting the spatial locality of electron correlation within the framework of the cluster-in-molecule (CIM) approximation [S. Li et al., J. Comput. Chem. 23, 238 (2002); J. Chem. Phys. 125, 074109 (2006)]. The 2-RDMs of individual molecular fragments within a molecule are determined, and selected portions of these 2-RDMs are recombined to yield an accurate approximation to the correlation energy of the entire molecule. In addition to extending CIM to the parametric 2-RDM method, we (i) suggest a more systematic selection of atomic-orbital domains than that presented in previous CIM studies and (ii) generalize the CIM method for open-shell quantum systems. The resulting method is tested with a series of polyacetylene molecules, water clusters, and diazobenzene derivatives in minimal and nonminimal basis sets. Calculations show that the computational cost of the method scales linearly with system size. We also compute hydrogen-abstraction energies for a series of hydroxyurea derivatives. Abstraction of hydrogen from hydroxyurea is thought to be a key step in its treatment of sickle cell anemia; the design of hydroxyurea derivatives that oxidize more rapidly is one approach to devising more effective treatments.

Degree-Strength Correlation Reveals Anomalous Trading Behavior

PubMed Central

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Wang, Zhao-Yang

2012-01-01

Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock markets. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying the anomalous traders using the transaction data of eight manipulated stocks and forty-four non-manipulated stocks during a one-year period. By analyzing the trading networks of stocks, we find that the trading networks of manipulated stocks exhibit significantly higher degree-strength correlation than the trading networks of non-manipulated stocks and the randomized trading networks. We further propose a method to detect anomalous traders of manipulated stocks based on statistical significance analysis of degree-strength correlation. Experimental results demonstrate that our method is effective at distinguishing the manipulated stocks from non-manipulated ones. Our method outperforms the traditional weight-threshold method at identifying the anomalous traders in manipulated stocks. More importantly, our method is difficult to be fooled by colluded traders. PMID:23082114

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.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Investigation of difficult component effects on finite element model vibration prediction for the Bell AG-1G helicopter. Volume 2: Correlation results

NASA Technical Reports Server (NTRS)

Dompka, R. V.

1989-01-01

Under the NASA-sponsored DAMVIBS (Design Analysis Methods for VIBrationS) program, a series of ground vibration tests and NASTRAN finite element model (FEM) correlations were conducted on the Bell AH-1G helicopter gunship to investigate the effects of difficult components on the vibration response of the airframe. Previous correlations of the AG-1G showed good agreement between NASTRAN and tests through 15 to 20 Hz, but poor agreement in the higher frequency range of 20 to 30 Hz. Thus, this effort emphasized the higher frequency airframe vibration response correlations and identified areas that need further R and T work. To conduct the investigations, selected difficult components (main rotor pylon, secondary structure, nonstructural doors/panels, landing gear, engine, furl, etc.) were systematically removed to quantify their effects on overall vibratory response of the airframe. The entire effort was planned and documented, and the results reviewed by NASA and industry experts in order to ensure scientific control of the testing, analysis, and correlation exercise. In particular, secondary structure and damping had significant effects on the frequency response of the airframe above 15 Hz. Also, the nonlinear effects of thrust stiffening and elastomer mounts were significant on the low frequency pylon modes below main rotor 1p (5.4 Hz). The results of the NASTRAN FEM correlations are given.

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

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

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

Correlation effects in focused transmission through disordered media (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hsu, Chia Wei; Liew, Seng Fatt; Goetschy, Arthur; Cao, Hui; Stone, A. Douglas

2017-02-01

By controlling the many degrees of freedom in the incident wavefront, one can manipulate wave propagation in complex structures. Such wavefront-shaping methods have been used extensively for controlling light transmitted into wavelength-scale regions (speckles), a property that is insensitive to correlations in the speckle pattern. Extending coherent control to larger regions is of great interest both scientifically and for applications such as optical communications, photothermal therapy, and the imaging of large objects within or behind a diffusive medium. However, waves diffusing through a disordered medium are known to exhibit non-local intensity correlations, and their effect on coherent control has not been fully understood. Here, we demonstrate the effects of correlations with wavefront-shaping experiments on a scattering sample of zinc oxide microparticles. Long-range correlations substantially increase the dynamic range of coherent control over light transmitted onto larger target regions, far beyond what would be achievable if correlations were negligible. This and other effects of correlations emerge when the number of speckles targeted, M2, exceeds the dimensionless conductance g. Using a filtered random matrix ensemble appropriate for describing coherent diffusion and the lateral spreading in an open geometry, we show analytically that M2/g appears as the controlling parameter in universal scaling laws for several statistical properties of interest--predictions that we quantitatively confirm with experimental data. Our work elucidates the roles of speckle correlations and provides a general theoretical framework for modeling open systems in wavefront-shaping experiments.

Correlation of ground tests and analyses of a dynamically scaled Space Station model configuration

NASA Technical Reports Server (NTRS)

Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.

1993-01-01

Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.

Influence of electron correlation on the cross section and linear polarization of radiation emitted by electron-impact excitation of Ca+ and Ba+ ions

NASA Astrophysics Data System (ADS)

Chen, Zhan-Bin

2018-04-01

Calculations of the electron-impact excitation (EIE) of singly charged Ca+ and Ba+ ions and subsequent de-excitation process are performed using a fully relativistic distorted wave (RDW) method. To resolve the discrepancy between previous theory and experiment, careful consideration is given to the generation of the target state wave-functions through the systematic inclusion of electron correlations. It is found that the electron correlation effects play a significant role on the cross section, while the effects on the linear polarization of the emitted radiation are relatively small. Good agreement between our result and experiment is obtained.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

Adapted all-numerical correlator for face recognition applications

NASA Astrophysics Data System (ADS)

Elbouz, M.; Bouzidi, F.; Alfalou, A.; Brosseau, C.; Leonard, I.; Benkelfat, B.-E.

2013-03-01

In this study, we suggest and validate an all-numerical implementation of a VanderLugt correlator which is optimized for face recognition applications. The main goal of this implementation is to take advantage of the benefits (detection, localization, and identification of a target object within a scene) of correlation methods and exploit the reconfigurability of numerical approaches. This technique requires a numerical implementation of the optical Fourier transform. We pay special attention to adapt the correlation filter to this numerical implementation. One main goal of this work is to reduce the size of the filter in order to decrease the memory space required for real time applications. To fulfil this requirement, we code the reference images with 8 bits and study the effect of this coding on the performances of several composite filters (phase-only filter, binary phase-only filter). The saturation effect has for effect to decrease the performances of the correlator for making a decision when filters contain up to nine references. Further, an optimization is proposed based for an optimized segmented composite filter. Based on this approach, we present tests with different faces demonstrating that the above mentioned saturation effect is significantly reduced while minimizing the size of the learning data base.

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

Multipion Bose-Einstein correlations in p p ,p -Pb, and Pb-Pb collisions at energies available at the CERN Large Hadron Collider

NASA Astrophysics Data System (ADS)

Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; 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.; Benacek, P.; 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.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Bourjau, C.; 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.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; 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.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; de, S.; de Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; de Falco, A.; de Gruttola, D.; De Marco, N.; de Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; di Bari, D.; di Mauro, A.; di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; 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.; Fronze, G. G.; 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.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Horak, D.; Hosokawa, R.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Incani, E.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; 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.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kostarakis, P.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; León Vargas, H.; 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.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lutz, T. H.; 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.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; 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.; Melikyan, Y.; 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.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molñar, L.; Montaño Zetina, L.; Montes, E.; Moreira de Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; 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.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; 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.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Pereira da Costa, H.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, 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.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; 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.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarma, P.; Scapparone, E.; Scarlassara, F.; 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.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shahzad, M. I.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; de Souza, R. D.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stankus, P.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; 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.; Trombetta, G.; 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.; Villatoro Tello, A.; 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.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yang, H.; Yang, P.; Yano, S.; Yasin, Z.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.; Alice Collaboration

2016-05-01

Three- and four-pion Bose-Einstein correlations are presented in p p ,p -Pb, and Pb-Pb collisions at the LHC. We compare our measured four-pion correlations to the expectation derived from two- and three-pion measurements. Such a comparison provides a method to search for coherent pion emission. We also present mixed-charge correlations in order to demonstrate the effectiveness of several analysis procedures such as Coulomb corrections. Same-charge four-pion correlations in p p and p -Pb appear consistent with the expectations from three-pion measurements. However, the presence of non-negligible background correlations in both systems prevent a conclusive statement. In Pb-Pb collisions, we observe a significant suppression of three- and four-pion Bose-Einstein correlations compared to expectations from two-pion measurements. There appears to be no centrality dependence of the suppression within the 0%-50% centrality interval. The origin of the suppression is not clear. However, by postulating either coherent pion emission or large multibody Coulomb effects, the suppression may be explained.

Multipion Bose-Einstein correlations in p p , p -Pb, and Pb-Pb collisions at energies available at the CERN Large Hadron Collider

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

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

Three- and four-pion Bose-Einstein correlations are presented in pp,p-Pb, and Pb-Pb collisions at the LHC. We compare our measured four-pion correlations to the expectation derived from two- and three-pion measurements. Such a comparison provides a method to search for coherent pion emission. We also present mixed-charge correlations in order to demonstrate the effectiveness of several analysis procedures such as Coulomb corrections. Same-charge four-pion correlations in pp and p-Pb appear consistent with the expectations from three-pion measurements. However, the presence of non-negligible background correlations in both systems prevent a conclusive statement. In Pb-Pb collisions, we observe a significant suppression of three-more » and four-pion Bose-Einstein correlations compared to expectations from two-pion measurements. There appears to be no centrality dependence of the suppression within the 0%-50% centrality interval. The origin of the suppression is not clear. However, by postulating either coherent pion emission or large multibody Coulomb effects, the suppression may be explained.« less

Multipion Bose-Einstein correlations in p p , p -Pb, and Pb-Pb collisions at energies available at the CERN Large Hadron Collider

DOE PAGES

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

2016-05-18

Three- and four-pion Bose-Einstein correlations are presented in pp,p-Pb, and Pb-Pb collisions at the LHC. We compare our measured four-pion correlations to the expectation derived from two- and three-pion measurements. Such a comparison provides a method to search for coherent pion emission. We also present mixed-charge correlations in order to demonstrate the effectiveness of several analysis procedures such as Coulomb corrections. Same-charge four-pion correlations in pp and p-Pb appear consistent with the expectations from three-pion measurements. However, the presence of non-negligible background correlations in both systems prevent a conclusive statement. In Pb-Pb collisions, we observe a significant suppression of three-more » and four-pion Bose-Einstein correlations compared to expectations from two-pion measurements. There appears to be no centrality dependence of the suppression within the 0%-50% centrality interval. The origin of the suppression is not clear. However, by postulating either coherent pion emission or large multibody Coulomb effects, the suppression may be explained.« less

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

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

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

Correlation analysis of tree growth, climate, and acid deposition in the Lake States.

Treesearch

Margaret R. Holdaway

1990-01-01

Describes research designed to detect subtle regional tree growth trends related to sulfate (SO4) deposition in the Lake States. Correlation methods were used to analyze climatic and SO4 deposition. Effects of SO4 deposition are greater on climatically stressed trees, especially pine species on dry sites, than on unstressed trees. Jack pine growth shows the...

The Influence of Sex on the Course and Psychiatric Correlates of ADHD from Childhood to Adolescence: A Longitudinal Study

ERIC Educational Resources Information Center

Monuteaux, Michael C.; Mick, Eric; Faraone, Stephen V.; Biederman, Joseph

2010-01-01

Background: Little is known about the influence of sex on the course of attention-deficit/hyperactivity disorder (ADHD) and its comorbid psychiatric conditions. The purpose of this study was to examine the effect of sex on the course and psychiatric correlates of ADHD from childhood into adolescence. Methods: Two identically designed,…

Features of the Asynchronous Correlation between the China Coal Price Index and Coal Mining Accidental Deaths.

PubMed

Huang, Yuecheng; Cheng, Wuyi; Luo, Sida; Luo, Yun; Ma, Chengchen; He, Tailin

2016-01-01

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices.

Electrical response grading versus House-Brackmann scale for evaluation of facial nerve injury after Bell's palsy: a comparative study.

PubMed

Huang, Bin; Zhou, Zhang-ling; Wang, Li-li; Zuo, Cong; Lu, Yan; Chen, Yong

2014-07-01

There are no convenient techniques to evaluate the degree of facial nerve injury during a course of acupuncture treatment for Bell's palsy. Our previous studies found that observing the electrical response of specific facial muscles provided reasonable correlation with the prognosis of electroacupuncture treatment. Hence, we used the new method to evaluate the degree of facial nerve injury in patients with Bell's palsy in comparison with the House-Brackmann scale. The relationship between therapeutic effects and prognosis was analyzed to explore an objective method for evaluating Bell's palsy. The facial nerve function of 68 patients with Bell's palsy was assessed with both electrical response grading and the House-Brackmann scale before treatment. Then differences in evaluation results of the two methods were compared. All enrolled patients received electroacupuncture treatment with disperse-dense wave at 1/100 Hz for 4 weeks. After treatment, correlation analysis was conducted to find the relationship between electrical response and therapeutic effects or prognosis. Checking consistency between electrical response grading and House-Brackmann scale: Kappa value 0.028 (P = 0.578). Correlation analysis: the two methods were correlated with the prognosis, and electrical response grading (rER = 0.789) was better than the House-Brackmann scale (rHB = 0.423). Electrical response grading is superior to the House-Brackmann scale in efficacy and reliability, and can conveniently assess the degree of facial nerve injury. The House-Brackmann scale is suitable for the patients with mild facial nerve injury, but its evaluation quality for severe facial nerve injury is poor.

Adulteration detection in milk using infrared spectroscopy combined with two-dimensional correlation analysis

NASA Astrophysics Data System (ADS)

He, Bin; Liu, Rong; Yang, Renjie; Xu, Kexin

2010-02-01

Adulteration of milk and dairy products has brought serious threats to human health as well as enormous economic losses to the food industry. Considering the diversity of adulterants possibly mixed in milk, such as melamine, urea, tetracycline, sugar/salt and so forth, a rapid, widely available, high-throughput, cost-effective method is needed for detecting each of the components in milk at once. In this paper, a method using Fourier Transform Infrared spectroscopy (FTIR) combined with two-dimensional (2D) correlation spectroscopy is established for the discriminative analysis of adulteration in milk. Firstly, the characteristic peaks of the raw milk are found in the 4000-400 cm-1 region by its original spectra. Secondly, the adulterant samples are respectively detected with the same method to establish a spectral database for subsequent comparison. Then, 2D correlation spectra of the samples are obtained which have high time resolution and can provide information about concentration-dependent intensity changes not readily accessible from one-dimensional spectra. And the characteristic peaks in the synchronous 2D correlation spectra of the suspected samples are compared with those of raw milk. The differences among their synchronous spectra imply that the suspected milk sample must contain some kinds of adulterants. Melamine, urea, tetracycline and glucose adulterants in milk are identified respectively. This nondestructive method can be used for a correct discrimination on whether the milk and dairy products are adulterated with deleterious substances and it provides a new simple and cost-effective alternative to test the components of milk.

Pair natural orbital and canonical coupled cluster reaction enthalpies involving light to heavy alkali and alkaline earth metals: the importance of sub-valence correlation.

PubMed

Minenkov, Yury; Bistoni, Giovanni; Riplinger, Christoph; Auer, Alexander A; Neese, Frank; Cavallo, Luigi

2017-04-05

In this work, we tested canonical and domain based pair natural orbital coupled cluster methods (CCSD(T) and DLPNO-CCSD(T), respectively) for a set of 32 ligand exchange and association/dissociation reaction enthalpies involving ionic complexes of Li, Be, Na, Mg, Ca, Sr, Ba and Pb(ii). Two strategies were investigated: in the former, only valence electrons were included in the correlation treatment, giving rise to the computationally very efficient FC (frozen core) approach; in the latter, all non-ECP electrons were included in the correlation treatment, giving rise to the AE (all electron) approach. Apart from reactions involving Li and Be, the FC approach resulted in non-homogeneous performance. The FC approach leads to very small errors (<2 kcal mol -1 ) for some reactions of Na, Mg, Ca, Sr, Ba and Pb, while for a few reactions of Ca and Ba deviations up to 40 kcal mol -1 have been obtained. Large errors are both due to artificial mixing of the core (sub-valence) orbitals of metals and the valence orbitals of oxygen and halogens in the molecular orbitals treated as core, and due to neglecting core-core and core-valence correlation effects. These large errors are reduced to a few kcal mol -1 if the AE approach is used or the sub-valence orbitals of metals are included in the correlation treatment. On the technical side, the CCSD(T) and DLPNO-CCSD(T) results differ by a fraction of kcal mol -1 , indicating the latter method as the perfect choice when the CPU efficiency is essential. For completely black-box applications, as requested in catalysis or thermochemical calculations, we recommend the DLPNO-CCSD(T) method with all electrons that are not covered by effective core potentials included in the correlation treatment and correlation-consistent polarized core valence basis sets of cc-pwCVQZ(-PP) quality.

Robust alignment of chromatograms by statistically analyzing the shifts matrix generated by moving window fast Fourier transform cross-correlation.

PubMed

Zhang, Mingjing; Wen, Ming; Zhang, Zhi-Min; Lu, Hongmei; Liang, Yizeng; Zhan, Dejian

2015-03-01

Retention time shift is one of the most challenging problems during the preprocessing of massive chromatographic datasets. Here, an improved version of the moving window fast Fourier transform cross-correlation algorithm is presented to perform nonlinear and robust alignment of chromatograms by analyzing the shifts matrix generated by moving window procedure. The shifts matrix in retention time can be estimated by fast Fourier transform cross-correlation with a moving window procedure. The refined shift of each scan point can be obtained by calculating the mode of corresponding column of the shifts matrix. This version is simple, but more effective and robust than the previously published moving window fast Fourier transform cross-correlation method. It can handle nonlinear retention time shift robustly if proper window size has been selected. The window size is the only one parameter needed to adjust and optimize. The properties of the proposed method are investigated by comparison with the previous moving window fast Fourier transform cross-correlation and recursive alignment by fast Fourier transform using chromatographic datasets. The pattern recognition results of a gas chromatography mass spectrometry dataset of metabolic syndrome can be improved significantly after preprocessing by this method. Furthermore, the proposed method is available as an open source package at https://github.com/zmzhang/MWFFT2. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

NASA Astrophysics Data System (ADS)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

Course 4: Density Functional Theory, Methods, Techniques, and Applications

NASA Astrophysics Data System (ADS)

Chrétien, S.; Salahub, D. R.

Contents 1 Introduction 2 Density functional theory 2.1 Hohenberg and Kohn theorems 2.2 Levy's constrained search 2.3 Kohn-Sham method 3 Density matrices and pair correlation functions 4 Adiabatic connection or coupling strength integration 5 Comparing and constrasting KS-DFT and HF-CI 6 Preparing new functionals 7 Approximate exchange and correlation functionals 7.1 The Local Spin Density Approximation (LSDA) 7.2 Gradient Expansion Approximation (GEA) 7.3 Generalized Gradient Approximation (GGA) 7.4 meta-Generalized Gradient Approximation (meta-GGA) 7.5 Hybrid functionals 7.6 The Optimized Effective Potential method (OEP) 7.7 Comparison between various approximate functionals 8 LAP correlation functional 9 Solving the Kohn-Sham equations 9.1 The Kohn-Sham orbitals 9.2 Coulomb potential 9.3 Exchange-correlation potential 9.4 Core potential 9.5 Other choices and sources of error 9.6 Functionality 10 Applications 10.1 Ab initio molecular dynamics for an alanine dipeptide model 10.2 Transition metal clusters: The ecstasy, and the agony... 10.3 The conversion of acetylene to benzene on Fe clusters 11 Conclusions

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

3D digital image correlation using a single 3CCD colour camera and dichroic filter

NASA Astrophysics Data System (ADS)

Zhong, F. Q.; Shao, X. X.; Quan, C.

2018-04-01

In recent years, three-dimensional digital image correlation methods using a single colour camera have been reported. In this study, we propose a simplified system by employing a dichroic filter (DF) to replace the beam splitter and colour filters. The DF can be used to combine two views from different perspectives reflected by two planar mirrors and eliminate their interference. A 3CCD colour camera is then used to capture two different views simultaneously via its blue and red channels. Moreover, the measurement accuracy of the proposed method is higher since the effect of refraction is reduced. Experiments are carried out to verify the effectiveness of the proposed method. It is shown that the interference between the blue and red views is insignificant. In addition, the measurement accuracy of the proposed method is validated on the rigid body displacement. The experimental results demonstrate that the measurement accuracy of the proposed method is higher compared with the reported methods using a single colour camera. Finally, the proposed method is employed to measure the in- and out-of-plane displacements of a loaded plastic board. The re-projection errors of the proposed method are smaller than those of the reported methods using a single colour camera.

Attenuation Tomography of Northern California and the Yellow Sea / Korean Peninsula from Coda-source Normalized and Direct Lg Amplitudes

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

Ford, S R; Dreger, D S; Phillips, W S

2008-07-16

Inversions for regional attenuation (1/Q) of Lg are performed in two different regions. The path attenuation component of the Lg spectrum is isolated using the coda-source normalization method, which corrects the Lg spectral amplitude for the source using the stable, coda-derived source spectra. Tomographic images of Northern California agree well with one-dimensional (1-D) Lg Q estimated from five different methods. We note there is some tendency for tomographic smoothing to increase Q relative to targeted 1-D methods. For example in the San Francisco Bay Area, which contains high attenuation relative to the rest of it's region, Q is over-estimated bymore » {approx}30. Coda-source normalized attenuation tomography is also carried out for the Yellow Sea/Korean Peninsula (YSKP) where output parameters (site, source, and path terms) are compared with those from the amplitude tomography method of Phillips et al. (2005) as well as a new method that ties the source term to the MDAC formulation (Walter and Taylor, 2001). The source terms show similar scatter between coda-source corrected and MDAC source perturbation methods, whereas the amplitude method has the greatest correlation with estimated true source magnitude. The coda-source better represents the source spectra compared to the estimated magnitude and could be the cause of the scatter. The similarity in the source terms between the coda-source and MDAC-linked methods shows that the latter method may approximate the effect of the former, and therefore could be useful in regions without coda-derived sources. The site terms from the MDAC-linked method correlate slightly with global Vs30 measurements. While the coda-source and amplitude ratio methods do not correlate with Vs30 measurements, they do correlate with one another, which provides confidence that the two methods are consistent. The path Q{sup -1} values are very similar between the coda-source and amplitude ratio methods except for small differences in the Da-xin-anling Mountains, in the northern YSKP. However there is one large difference between the MDAC-linked method and the others in the region near stations TJN and INCN, which point to site-effect as the cause for the difference.« less

Pressure effects on the electronic properties in CeCoIn5: A first-principle study

NASA Astrophysics Data System (ADS)

Medeiros, Gustavo; Gonzalez, J. L.; Scopel, Wanderlã L.

2017-11-01

Superconducting heavy fermions are exotic materials with strong electronic correlations. The temperature-pressure phase diagrams of some of these materials show a complex interplay between superconductivity and magnetism that is essential to understand the physical properties of these systems. In this work, first principle calculations are performed in order to study the pressure effects on the electronic correlations in the CeCoIn5 system, which is superconducting at ambient pressure with Tc = 2.3 K. The density functional theory (DFT) method was used to include on-site coulomb repulsions (U) at the d (Co and In) and f (Ce) electrons of the CeCoIn5 compound. External applied pressures were simulated by correlating an applied pressure with a reduction of the volume of the unit cell, but keeping constant the c/a relation, as reported in experiments. Our findings reveal that the U parameters for all atomic species increase linearly with the pressure (P), being this effect higher for the f-electrons of the cerium ions, where dU / dP = 1.2 eV/GPa. In summary, these results not only suggest that the pressure effect can be correlated with an increase in the electronic correlations in the CeCoIn5 compound, as also, the work allows quantify this effect.

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.

Effective screening length and quasiuniversality for the restricted primitive model of an electrolyte solution.

PubMed

Janecek, Jirí; Netz, Roland R

2009-02-21

Monte Carlo simulations for the restricted primitive model of an electrolyte solution above the critical temperature are performed at a wide range of concentrations and temperatures. Thermodynamic properties such as internal energy, osmotic coefficient, activity coefficient, as well as spatial correlation functions are determined. These observables are used to investigate whether quasiuniversality in terms of an effective screening length exists, similar to the role played by the effective electron mass in solid-state physics. To that end, an effective screening length is extracted from the asymptotic behavior of the Fourier-transformed charge-correlation function and plugged into the Debye-Huckel limiting expressions for various thermodynamic properties. Comparison with numerical results is favorable, suggesting that correlation and other effects not captured on the Debye-Huckel limiting level can be successfully incorporated by a single effective parameter while keeping the functional form of Debye-Huckel expressions. We also compare different methods to determine mean ionic activity coefficient in molecular simulations and check the internal consistency of the numerical data.

Global and System-Specific Resting-State fMRI Fluctuations Are Uncorrelated: Principal Component Analysis Reveals Anti-Correlated Networks

PubMed Central

Carbonell, Felix; Bellec, Pierre

2011-01-01

Abstract The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)–based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations. PMID:22444074

Visual tracking using objectness-bounding box regression and correlation filters

NASA Astrophysics Data System (ADS)

Mbelwa, Jimmy T.; Zhao, Qingjie; Lu, Yao; Wang, Fasheng; Mbise, Mercy

2018-03-01

Visual tracking is a fundamental problem in computer vision with extensive application domains in surveillance and intelligent systems. Recently, correlation filter-based tracking methods have shown a great achievement in terms of robustness, accuracy, and speed. However, such methods have a problem of dealing with fast motion (FM), motion blur (MB), illumination variation (IV), and drifting caused by occlusion (OCC). To solve this problem, a tracking method that integrates objectness-bounding box regression (O-BBR) model and a scheme based on kernelized correlation filter (KCF) is proposed. The scheme based on KCF is used to improve the tracking performance of FM and MB. For handling drift problem caused by OCC and IV, we propose objectness proposals trained in bounding box regression as prior knowledge to provide candidates and background suppression. Finally, scheme KCF as a base tracker and O-BBR are fused to obtain a state of a target object. Extensive experimental comparisons of the developed tracking method with other state-of-the-art trackers are performed on some of the challenging video sequences. Experimental comparison results show that our proposed tracking method outperforms other state-of-the-art tracking methods in terms of effectiveness, accuracy, and robustness.

Comparing Hall Effect and Field Effect Measurements on the Same Single Nanowire.

PubMed

Hultin, Olof; Otnes, Gaute; Borgström, Magnus T; Björk, Mikael; Samuelson, Lars; Storm, Kristian

2016-01-13

We compare and discuss the two most commonly used electrical characterization techniques for nanowires (NWs). In a novel single-NW device, we combine Hall effect and back-gated and top-gated field effect measurements and quantify the carrier concentrations in a series of sulfur-doped InP NWs. The carrier concentrations from Hall effect and field effect measurements are found to correlate well when using the analysis methods described in this work. This shows that NWs can be accurately characterized with available electrical methods, an important result toward better understanding of semiconductor NW doping.

Probing phenylalanine/adenine pi-stacking interactions in protein complexes with explicitly correlated and CCSD(T) computations.

PubMed

Copeland, Kari L; Anderson, Julie A; Farley, Adam R; Cox, James R; Tschumper, Gregory S

2008-11-13

To examine the effects of pi-stacking interactions between aromatic amino acid side chains and adenine bearing ligands in crystalline protein structures, 26 toluene/(N9-methyl)adenine model configurations have been constructed from protein/ligand crystal structures. Full geometry optimizations with the MP2 method cause the 26 crystal structures to collapse to six unique structures. The complete basis set (CBS) limit of the CCSD(T) interaction energies has been determined for all 32 structures by combining explicitly correlated MP2-R12 computations with a correction for higher-order correlation effects from CCSD(T) calculations. The CCSD(T) CBS limit interaction energies of the 26 crystal structures range from -3.19 to -6.77 kcal mol (-1) and average -5.01 kcal mol (-1). The CCSD(T) CBS limit interaction energies of the optimized complexes increase by roughly 1.5 kcal mol (-1) on average to -6.54 kcal mol (-1) (ranging from -5.93 to -7.05 kcal mol (-1)). Corrections for higher-order correlation effects are extremely important for both sets of structures and are responsible for the modest increase in the interaction energy after optimization. The MP2 method overbinds the crystal structures by 2.31 kcal mol (-1) on average compared to 4.50 kcal mol (-1) for the optimized structures.

Diverse trends of electron correlation effects for properties with different radial and angular factors in an atomic system: a case study in Ca+

NASA Astrophysics Data System (ADS)

Kumar, Pradeep; Li, Cheng-Bin; Sahoo, B. K.

2018-03-01

Dependencies of electron correlation effects with the rank and radial behavior of spectroscopic properties are analyzed in the singly charged calcium ion (Ca+). To demonstrate these trends, we have determined field shift constants, magnetic dipole and electric quadrupole hyperfine structure constants, Landé g J factors, and electric quadrupole moments that are described by electronic operators with different radial and angular factors. Radial dependencies are investigated by comparing correlation trends among the properties that have similar angular factors and vice versa. To highlight these observations, we present results from the mean-field approach to all-orders along with intermediate contributions. Contributions from higher relativistic corrections are also given. These findings suggest that sometime lower-order approximations can give results agreeing with the experimental results, but inclusion of some of higher-order correlation effects can cause large disagreement with the experimental values. Therefore, validity of a method for accurate evaluation of atomic properties can be tested by performing calculations of several properties simultaneously that have diverse dependencies on the angular and radial factors and comparing with the available experimental results. Nevertheless, it is imperative to include full triple and quadrupole excitations in the all-order many-body methods for high-precision calculations that are yet to be developed adopting spherical coordinate system for atomic studies.

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.

A modified anomaly detection method for capsule endoscopy images using non-linear color conversion and Higher-order Local Auto-Correlation (HLAC).

PubMed

Hu, Erzhong; Nosato, Hirokazu; Sakanashi, Hidenori; Murakawa, Masahiro

2013-01-01

Capsule endoscopy is a patient-friendly endoscopy broadly utilized in gastrointestinal examination. However, the efficacy of diagnosis is restricted by the large quantity of images. This paper presents a modified anomaly detection method, by which both known and unknown anomalies in capsule endoscopy images of small intestine are expected to be detected. To achieve this goal, this paper introduces feature extraction using a non-linear color conversion and Higher-order Local Auto Correlation (HLAC) Features, and makes use of image partition and subspace method for anomaly detection. Experiments are implemented among several major anomalies with combinations of proposed techniques. As the result, the proposed method achieved 91.7% and 100% detection accuracy for swelling and bleeding respectively, so that the effectiveness of proposed method is demonstrated.

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.

Temperature sensitivity of organic compound destruction in SCWO process.

PubMed

Tan, Yaqin; Shen, Zhemin; Guo, Weimin; Ouyang, Chuang; Jia, Jinping; Jiang, Weili; Zhou, Haiyun

2014-03-01

To study the temperature sensitivity of the destruction of organic compounds in supercritical water oxidation process (SCWO), oxidation effects of twelve chemicals in supercritical water were investigated. The SCWO reaction rates of different compounds improved to varying degrees with the increase of temperature, so the highest slope of the temperature-effect curve (imax) was defined as the maximum ratio of removal ratio to working temperature. It is an important index to stand for the temperature sensitivity effect in SCWO. It was proven that the higher imax is, the more significant the effect of temperature on the SCWO effect is. Since the high-temperature area of SCWO equipment is subject to considerable damage from fatigue, the temperature is of great significance in SCWO equipment operation. Generally, most compounds (imax > 0.25) can be completely oxidized when the reactor temperature reaches 500°C. However, some compounds (imax > 0.25) need a higher temperature for complete oxidation, up to 560°C. To analyze the correlation coefficients between imax and various molecular descriptors, a quantum chemical method was used in this study. The structures of the twelve organic compounds were optimized by the Density Functional Theory B3LYP/6-311G method, as well as their quantum properties. It was shown that six molecular descriptors were negatively correlated to imax while other three descriptors were positively correlated to imax. Among them, dipole moment had the greatest effect on the oxidation thermodynamics of the twelve organic compounds. Once a correlation between molecular descriptors and imax is established, SCWO can be run at an appropriate temperature according to molecular structure. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Objective evaluation of the knocking sound of a diesel engine considering the temporal and frequency masking effect simultaneously

NASA Astrophysics Data System (ADS)

Yun, Dong-Un; Lee, Sang-Kwon

2017-06-01

In this paper, we present a novel method for an objective evaluation of knocking noise emitted by diesel engines based on the temporal and frequency masking theory. The knocking sound of a diesel engine is a vibro-acoustic sound correlated with the high-frequency resonances of the engine structure and a periodic impulsive sound with amplitude modulation. Its period is related to the engine speed and includes specific frequency bands related to the resonances of the engine structure. A knocking sound with the characteristics of a high-frequency impulsive wave can be masked by low-frequency sounds correlated with the harmonics of the firing frequency and broadband noise. The degree of modulation of the knocking sound signal was used for such objective evaluations in previous studies, without considering the masking effect. However, the frequency masking effect must be considered for the objective evaluation of the knocking sound. In addition to the frequency masking effect, the temporal masking effect occurs because the period of the knocking sound changes according to the engine speed. Therefore, an evaluation method considering the temporal and frequency masking effect is required to analyze the knocking sound objectively. In this study, an objective evaluation method considering the masking effect was developed based on the masking theory of sound and signal processing techniques. The method was applied successfully for the objective evaluation of the knocking sound of a diesel engine.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

A Study on the Visualization Skills of 6th Grade Students

ERIC Educational Resources Information Center

Özkan, Ayten; Arikan, Elif Esra; Özkan, Erdogan Mehmet

2018-01-01

Visualization is an effective method for students to internalize concepts and to establish correlations between concepts. Visualization method is especially more important in mathematics which is perceived as the combination of abstract concepts. In this study, whether 6th grade students can solve questions about "Fractions" by using…

Development of Mobile Tracer Correlation Method for Quantification of Emissions from Landfills and Other Large Area Sources

EPA Science Inventory

There is an emerging need to develop cost effective measurement methods for greenhouse gas and air pollutant emissions from large area sources such as landfills, waste water treatment ponds, open area processing units, agricultural operations, CO2 sequestration fields, and site r...

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

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods

NASA Astrophysics Data System (ADS)

Piao, Lin; Fu, Zuntao

2016-11-01

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods.

PubMed

Piao, Lin; Fu, Zuntao

2016-11-09

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Polarization and amplitude probes in Hanle effect EIT noise spectroscopy of a buffer gas cell

NASA Astrophysics Data System (ADS)

O'Leary, Shannon; Zheng, Aojie; Crescimanno, Michael

2015-05-01

Noise correlation spectroscopy on systems manifesting Electromagnetically Induced Transparency (EIT) holds promise as a simple, robust method for performing high-resolution spectroscopy used in applications such as EIT-based atomic magnetometry and clocks. While this noise conversion can diminish the precision of EIT applications, noise correlation techniques transform the noise into a useful spectroscopic tool that can improve the application's precision. We study intensity noise, originating from the large phase noise of a semiconductor diode laser's light, in Rb vapor EIT in the Hanle configuration. We report here on our recent experimental work on and complementary theoretical modeling of the effects of light polarization preparation and post-selection on the correlation spectrum and on the independent noise channel traces. We also explain methodology and recent results for delineating the effects of residual laser amplitude fluctuations on the correlation noise resonance as compared to other contributing processes. Understanding these subtleties are essential for optimizing EIT-noise applications.

Rayleigh-enhanced attosecond sum-frequency polarization beats via twin color-locking noisy lights

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

Zhang Yanpeng; Li Long; Ma Ruiqiong

2005-07-15

Based on color-locking noisy field correlation, a time-delayed method is proposed to suppress the thermal effect, and the ultrafast longitudinal relaxation time can be measured even in an absorbing medium. One interesting feature in field-correlation effects is that Rayleigh-enhanced four-wave mixing (RFWM) with color-locking noisy light exhibits spectral symmetry and temporal asymmetry with no coherence spike at {tau}=0. Due to the interference between the Rayleigh-resonant signal and the nonresonant background, RFWM exhibits hybrid radiation-matter detuning with terahertz damping oscillations. The subtle Markovian high-order correlation effects have been investigated in the homodyne- or heterodyne-detected Rayleigh-enhanced attosecond sum-frequency polarization beats (RASPBs). Analyticmore » closed forms of fourth-order Markovian stochastic correlations are characterized for homodyne (quadratic) and heterodyne (linear) detection, respectively. Based on the polarization interference between two four-wave mixing processes, the phase-sensitive detection of RASPBs has also been used to obtain the real and imaginary parts of the Rayleigh resonance.« less

Validation of Web-Based Physical Activity Measurement Systems Using Doubly Labeled Water

PubMed Central

Yamaguchi, Yukio; Yamada, Yosuke; Tokushima, Satoru; Hatamoto, Yoichi; Sagayama, Hiroyuki; Kimura, Misaka; Higaki, Yasuki; Tanaka, Hiroaki

2012-01-01

Background Online or Web-based measurement systems have been proposed as convenient methods for collecting physical activity data. We developed two Web-based physical activity systems—the 24-hour Physical Activity Record Web (24hPAR WEB) and 7 days Recall Web (7daysRecall WEB). Objective To examine the validity of two Web-based physical activity measurement systems using the doubly labeled water (DLW) method. Methods We assessed the validity of the 24hPAR WEB and 7daysRecall WEB in 20 individuals, aged 25 to 61 years. The order of email distribution and subsequent completion of the two Web-based measurements systems was randomized. Each measurement tool was used for a week. The participants’ activity energy expenditure (AEE) and total energy expenditure (TEE) were assessed over each week using the DLW method and compared with the respective energy expenditures estimated using the Web-based systems. Results The mean AEE was 3.90 (SD 1.43) MJ estimated using the 24hPAR WEB and 3.67 (SD 1.48) MJ measured by the DLW method. The Pearson correlation for AEE between the two methods was r = .679 (P < .001). The Bland-Altman 95% limits of agreement ranged from –2.10 to 2.57 MJ between the two methods. The Pearson correlation for TEE between the two methods was r = .874 (P < .001). The mean AEE was 4.29 (SD 1.94) MJ using the 7daysRecall WEB and 3.80 (SD 1.36) MJ by the DLW method. The Pearson correlation for AEE between the two methods was r = .144 (P = .54). The Bland-Altman 95% limits of agreement ranged from –3.83 to 4.81 MJ between the two methods. The Pearson correlation for TEE between the two methods was r = .590 (P = .006). The average input times using terminal devices were 8 minutes and 10 seconds for the 24hPAR WEB and 6 minutes and 38 seconds for the 7daysRecall WEB. Conclusions Both Web-based systems were found to be effective methods for collecting physical activity data and are appropriate for use in epidemiological studies. Because the measurement accuracy of the 24hPAR WEB was moderate to high, it could be suitable for evaluating the effect of interventions on individuals as well as for examining physical activity behavior. PMID:23010345

The Effects of Size and Type of Vocal Fold Polyp on Some Acoustic Voice Parameters.

PubMed

Akbari, Elaheh; Seifpanahi, Sadegh; Ghorbani, Ali; Izadi, Farzad; Torabinezhad, Farhad

2018-03-01

Vocal abuse and misuse would result in vocal fold polyp. Certain features define the extent of vocal folds polyp effects on voice acoustic parameters. The present study aimed to define the effects of polyp size on acoustic voice parameters, and compare these parameters in hemorrhagic and non-hemorrhagic polyps. In the present retrospective study, 28 individuals with hemorrhagic or non-hemorrhagic polyps of the true vocal folds were recruited to investigate acoustic voice parameters of vowel/ æ/ computed by the Praat software. The data were analyzed using the SPSS software, version 17.0. According to the type and size of polyps, mean acoustic differences and correlations were analyzed by the statistical t test and Pearson correlation test, respectively; with significance level below 0.05. The results indicated that jitter and the harmonics-to-noise ratio had a significant positive and negative correlation with the polyp size (P=0.01), respectively. In addition, both mentioned parameters were significantly different between the two types of the investigated polyps. Both the type and size of polyps have effects on acoustic voice characteristics. In the present study, a novel method to measure polyp size was introduced. Further confirmation of this method as a tool to compare polyp sizes requires additional investigations.

Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems.

PubMed

Tanaka, Shigenori; Mochizuki, Yuji; Komeiji, Yuto; Okiyama, Yoshio; Fukuzawa, Kaori

2014-06-14

Recent developments in the fragment molecular orbital (FMO) method for theoretical formulation, implementation, and application to nano and biomolecular systems are reviewed. The FMO method has enabled ab initio quantum-mechanical calculations for large molecular systems such as protein-ligand complexes at a reasonable computational cost in a parallelized way. There have been a wealth of application outcomes from the FMO method in the fields of biochemistry, medicinal chemistry and nanotechnology, in which the electron correlation effects play vital roles. With the aid of the advances in high-performance computing, the FMO method promises larger, faster, and more accurate simulations of biomolecular and related systems, including the descriptions of dynamical behaviors in solvent environments. The current status and future prospects of the FMO scheme are addressed in these contexts.

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

PubMed Central

Huang, Desheng; Guan, Peng; Guo, Junqiao; Wang, Ping; Zhou, Baosen

2008-01-01

Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations. PMID:18816415

Untangling the Relatedness among Correlations, Part II: Inter-Subject Correlation Group Analysis through Linear Mixed-Effects Modeling

PubMed Central

Chen, Gang; Taylor, Paul A.; Shin, Yong-Wook; Reynolds, Richard C.; Cox, Robert W.

2016-01-01

It has been argued that naturalistic conditions in FMRI studies provide a useful paradigm for investigating perception and cognition through a synchronization measure, inter-subject correlation (ISC). However, one analytical stumbling block has been the fact that the ISC values associated with each single subject are not independent, and our previous paper (Chen et al., 2016) used simulations and analyses of real data to show that the methodologies adopted in the literature do not have the proper control for false positives. In the same paper, we proposed nonparametric subject-wise bootstrapping and permutation testing techniques for one and two groups, respectively, which account for the correlation structure, and these greatly outperformed the prior methods in controlling the false positive rate (FPR); that is, subject-wise bootstrapping (SWB) worked relatively well for both cases with one and two groups, and subject-wise permutation (SWP) testing was virtually ideal for group comparisons. Here we seek to explicate and adopt a parametric approach through linear mixed-effects (LME) modeling for studying the ISC values, building on the previous correlation framework, with the benefit that the LME platform offers wider adaptability, more powerful interpretations, and quality control checking capability than nonparametric methods. We describe both theoretical and practical issues involved in the modeling and the manner in which LME with crossed random effects (CRE) modeling is applied. A data-doubling step further allows us to conveniently track the subject index, and achieve easy implementations. We pit the LME approach against the best nonparametric methods, and find that the LME framework achieves proper control for false positives. The new LME methodologies are shown to be both efficient and robust, and they will be added as an additional option and settings in an existing open source program, 3dLME, in AFNI (http://afni.nimh.nih.gov). PMID:27751943

Directly patching high-level exchange-correlation potential based on fully determined optimized effective potentials

NASA Astrophysics Data System (ADS)

Huang, Chen; Chi, Yu-Chieh

2017-12-01

The key element in Kohn-Sham (KS) density functional theory is the exchange-correlation (XC) potential. We recently proposed the exchange-correlation potential patching (XCPP) method with the aim of directly constructing high-level XC potential in a large system by patching the locally computed, high-level XC potentials throughout the system. In this work, we investigate the patching of the exact exchange (EXX) and the random phase approximation (RPA) correlation potentials. A major challenge of XCPP is that a cluster's XC potential, obtained by solving the optimized effective potential equation, is only determined up to an unknown constant. Without fully determining the clusters' XC potentials, the patched system's XC potential is "uneven" in the real space and may cause non-physical results. Here, we developed a simple method to determine this unknown constant. The performance of XCPP-RPA is investigated on three one-dimensional systems: H20, H10Li8, and the stretching of the H19-H bond. We investigated two definitions of EXX: (i) the definition based on the adiabatic connection and fluctuation dissipation theorem (ACFDT) and (ii) the Hartree-Fock (HF) definition. With ACFDT-type EXX, effective error cancellations were observed between the patched EXX and the patched RPA correlation potentials. Such error cancellations were absent for the HF-type EXX, which was attributed to the fact that for systems with fractional occupation numbers, the integral of the HF-type EXX hole is not -1. The KS spectra and band gaps from XCPP agree reasonably well with the benchmarks as we make the clusters large.

Assessment of Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk

PubMed Central

Czarnota, Jenna; Gennings, Chris; Wheeler, David C

2015-01-01

In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case–control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome. PMID:26005323

Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk.

PubMed

Czarnota, Jenna; Gennings, Chris; Wheeler, David C

2015-01-01

In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case-control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome.

Reanalysis, compatibility and correlation in analysis of modified antenna structures

NASA Technical Reports Server (NTRS)

Levy, R.

1989-01-01

A simple computational procedure is synthesized to process changes in the microwave-antenna pathlength-error measure when there are changes in the antenna structure model. The procedure employs structural modification reanalysis methods combined with new extensions of correlation analysis to provide the revised rms pathlength error. Mainframe finite-element-method processing of the structure model is required only for the initial unmodified structure, and elementary postprocessor computations develop and deal with the effects of the changes. Several illustrative computational examples are included. The procedure adapts readily to processing spectra of changes for parameter studies or sensitivity analyses.

Correlation effect and magnetic moments in Cr2Te3

NASA Astrophysics Data System (ADS)

Youn, S. J.; Kwon, S. K.; Min, B. I.

2007-05-01

The electronic and magnetic structures of Cr2Te3 have been studied theoretically using the linearized muffin-tin orbitals band method. Experimental photoemission spectra and magnetic moments can be described better when the on-site Coulomb correlation U of Cr 3d electrons is considered using the local spin-density approximation+U method. The proper size of U is found to be U ˜1.7eV. The complex magnetic behaviors of Cr2Te3 come from the degeneracy of parallel and antiparallel alignments of CrI spin to CrII and CrIII spins.

Multicomponent Density Functional Theory: Impact of Nuclear Quantum Effects on Proton Affinities and Geometries.

PubMed

Brorsen, Kurt R; Yang, Yang; Hammes-Schiffer, Sharon

2017-08-03

Nuclear quantum effects such as zero point energy play a critical role in computational chemistry and often are included as energetic corrections following geometry optimizations. The nuclear-electronic orbital (NEO) multicomponent density functional theory (DFT) method treats select nuclei, typically protons, quantum mechanically on the same level as the electrons. Electron-proton correlation is highly significant, and inadequate treatments lead to highly overlocalized nuclear densities. A recently developed electron-proton correlation functional, epc17, has been shown to provide accurate nuclear densities for molecular systems. Herein, the NEO-DFT/epc17 method is used to compute the proton affinities for a set of molecules and to examine the role of nuclear quantum effects on the equilibrium geometry of FHF - . The agreement of the computed results with experimental and benchmark values demonstrates the promise of this approach for including nuclear quantum effects in calculations of proton affinities, pK a 's, optimized geometries, and reaction paths.

Correlation effects in fcc-Fe(x)Ni(1-x) alloys investigated by means of the KKR-CPA.

PubMed

Minár, J; Mankovsky, S; Šipr, O; Benea, D; Ebert, H

2014-07-09

The electronic structure and magnetic properties of the disordered alloy system fcc-FexNi1-x (fcc: face centered cubic) have been investigated by means of the KKR-CPA (Korringa-Kohn-Rostoker coherent potential approximation) band structure method. To investigate the impact of correlation effects, the calculations have been performed on the basis of the LSDA (local spin density approximation), the LSDA + U as well as the LSDA + DMFT (dynamical mean field theory). It turned out that the inclusion of correlation effects hardly changed the spin magnetic moments and the related hyperfine fields. The spin-orbit induced orbital magnetic moments and hyperfine fields, on the other hand, show a pronounced and element-specific enhancement. These findings are in full accordance with the results of a recent experimental study.

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

NASA Astrophysics Data System (ADS)

Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

2008-12-01

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

Improvement of correlation-based centroiding methods for point source Shack-Hartmann wavefront sensor

NASA Astrophysics Data System (ADS)

Li, Xuxu; Li, Xinyang; wang, Caixia

2018-03-01

This paper proposes an efficient approach to decrease the computational costs of correlation-based centroiding methods used for point source Shack-Hartmann wavefront sensors. Four typical similarity functions have been compared, i.e. the absolute difference function (ADF), ADF square (ADF2), square difference function (SDF), and cross-correlation function (CCF) using the Gaussian spot model. By combining them with fast search algorithms, such as three-step search (TSS), two-dimensional logarithmic search (TDL), cross search (CS), and orthogonal search (OS), computational costs can be reduced drastically without affecting the accuracy of centroid detection. Specifically, OS reduces calculation consumption by 90%. A comprehensive simulation indicates that CCF exhibits a better performance than other functions under various light-level conditions. Besides, the effectiveness of fast search algorithms has been verified.

Contour-time approach to the Bose-Hubbard model in the strong coupling regime: Studying two-point spatio-temporal correlations at the Hartree-Fock-Bogoliubov level

NASA Astrophysics Data System (ADS)

Fitzpatrick, Matthew R. C.; Kennett, Malcolm P.

2018-05-01

We develop a formalism that allows the study of correlations in space and time in both the superfluid and Mott insulating phases of the Bose-Hubbard Model. Specifically, we obtain a two particle irreducible effective action within the contour-time formalism that allows for both equilibrium and out of equilibrium phenomena. We derive equations of motion for both the superfluid order parameter and two-point correlation functions. To assess the accuracy of this formalism, we study the equilibrium solution of the equations of motion and compare our results to existing strong coupling methods as well as exact methods where possible. We discuss applications of this formalism to out of equilibrium situations.

The full-sky relativistic correlation function and power spectrum of galaxy number counts. Part I: theoretical aspects

NASA Astrophysics Data System (ADS)

Tansella, Vittorio; Bonvin, Camille; Durrer, Ruth; Ghosh, Basundhara; Sellentin, Elena

2018-03-01

We derive an exact expression for the correlation function in redshift shells including all the relativistic contributions. This expression, which does not rely on the distant-observer or flat-sky approximation, is valid at all scales and includes both local relativistic corrections and integrated contributions, like gravitational lensing. We present two methods to calculate this correlation function, one which makes use of the angular power spectrum Cl(z1,z2) and a second method which evades the costly calculations of the angular power spectra. The correlation function is then used to define the power spectrum as its Fourier transform. In this work theoretical aspects of this procedure are presented, together with quantitative examples. In particular, we show that gravitational lensing modifies the multipoles of the correlation function and of the power spectrum by a few percent at redshift z=1 and by up to 30% and more at z=2. We also point out that large-scale relativistic effects and wide-angle corrections generate contributions of the same order of magnitude and have consequently to be treated in conjunction. These corrections are particularly important at small redshift, z=0.1, where they can reach 10%. This means in particular that a flat-sky treatment of relativistic effects, using for example the power spectrum, is not consistent.

Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476

Method for stationarity-segmentation of spike train data with application to the Pearson cross-correlation.

PubMed

Quiroga-Lombard, Claudio S; Hass, Joachim; Durstewitz, Daniel

2013-07-01

Correlations among neurons are supposed to play an important role in computation and information coding in the nervous system. Empirically, functional interactions between neurons are most commonly assessed by cross-correlation functions. Recent studies have suggested that pairwise correlations may indeed be sufficient to capture most of the information present in neural interactions. Many applications of correlation functions, however, implicitly tend to assume that the underlying processes are stationary. This assumption will usually fail for real neurons recorded in vivo since their activity during behavioral tasks is heavily influenced by stimulus-, movement-, or cognition-related processes as well as by more general processes like slow oscillations or changes in state of alertness. To address the problem of nonstationarity, we introduce a method for assessing stationarity empirically and then "slicing" spike trains into stationary segments according to the statistical definition of weak-sense stationarity. We examine pairwise Pearson cross-correlations (PCCs) under both stationary and nonstationary conditions and identify another source of covariance that can be differentiated from the covariance of the spike times and emerges as a consequence of residual nonstationarities after the slicing process: the covariance of the firing rates defined on each segment. Based on this, a correction of the PCC is introduced that accounts for the effect of segmentation. We probe these methods both on simulated data sets and on in vivo recordings from the prefrontal cortex of behaving rats. Rather than for removing nonstationarities, the present method may also be used for detecting significant events in spike trains.

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.

Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui

2018-05-01

In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.

Single-trial analysis of the neural correlates of speech quality perception.

PubMed

Porbadnigk, Anne K; Treder, Matthias S; Blankertz, Benjamin; Antons, Jan-Niklas; Schleicher, Robert; Möller, Sebastian; Curio, Gabriel; Müller, Klaus-Robert

2013-10-01

Assessing speech quality perception is a challenge typically addressed in behavioral and opinion-seeking experiments. Only recently, neuroimaging methods were introduced, which were used to study the neural processing of quality at group level. However, our electroencephalography (EEG) studies show that the neural correlates of quality perception are highly individual. Therefore, it became necessary to establish dedicated machine learning methods for decoding subject-specific effects. The effectiveness of our methods is shown by the data of an EEG study that investigates how the quality of spoken vowels is processed neurally. Participants were asked to indicate whether they had perceived a degradation of quality (signal-correlated noise) in vowels, presented in an oddball paradigm. We find that the P3 amplitude is attenuated with increasing noise. Single-trial analysis allows one to show that this is partly due to an increasing jitter of the P3 component. A novel classification approach helps to detect trials with presumably non-conscious processing at the threshold of perception. We show that this approach uncovers a non-trivial confounder between neural hits and neural misses. The combined use of EEG signals and machine learning methods results in a significant 'neural' gain in sensitivity (in processing quality loss) when compared to standard behavioral evaluation; averaged over 11 subjects, this amounts to a relative improvement in sensitivity of 35%.

Comparison of scoring approaches for the NEI VFQ-25 in low vision.

PubMed

Dougherty, Bradley E; Bullimore, Mark A

2010-08-01

The aim of this study was to evaluate different approaches to scoring the National Eye Institute Visual Functioning Questionnaire-25 (NEI VFQ-25) in patients with low vision including scoring by the standard method, by Rasch analysis, and by use of an algorithm created by Massof to approximate Rasch person measure. Subscale validity and use of a 7-item short form instrument proposed by Ryan et al. were also investigated. NEI VFQ-25 data from 50 patients with low vision were analyzed using the standard method of summing Likert-type scores and calculating an overall average, Rasch analysis using Winsteps software, and the Massof algorithm in Excel. Correlations between scores were calculated. Rasch person separation reliability and other indicators were calculated to determine the validity of the subscales and of the 7-item instrument. Scores calculated using all three methods were highly correlated, but evidence of floor and ceiling effects was found with the standard scoring method. None of the subscales investigated proved valid. The 7-item instrument showed acceptable person separation reliability and good targeting and item performance. Although standard scores and Rasch scores are highly correlated, Rasch analysis has the advantages of eliminating floor and ceiling effects and producing interval-scaled data. The Massof algorithm for approximation of the Rasch person measure performed well in this group of low-vision patients. The validity of the subscales VFQ-25 should be reconsidered.

Gene set analysis using variance component tests.

PubMed

Huang, Yen-Tsung; Lin, Xihong

2013-06-28

Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

Rigorous evaluation of chemical measurement uncertainty: liquid chromatographic analysis methods using detector response factor calibration

NASA Astrophysics Data System (ADS)

Toman, Blaza; Nelson, Michael A.; Bedner, Mary

2017-06-01

Chemical measurement methods are designed to promote accurate knowledge of a measurand or system. As such, these methods often allow elicitation of latent sources of variability and correlation in experimental data. They typically implement measurement equations that support quantification of effects associated with calibration standards and other known or observed parametric variables. Additionally, multiple samples and calibrants are usually analyzed to assess accuracy of the measurement procedure and repeatability by the analyst. Thus, a realistic assessment of uncertainty for most chemical measurement methods is not purely bottom-up (based on the measurement equation) or top-down (based on the experimental design), but inherently contains elements of both. Confidence in results must be rigorously evaluated for the sources of variability in all of the bottom-up and top-down elements. This type of analysis presents unique challenges due to various statistical correlations among the outputs of measurement equations. One approach is to use a Bayesian hierarchical (BH) model which is intrinsically rigorous, thus making it a straightforward method for use with complex experimental designs, particularly when correlations among data are numerous and difficult to elucidate or explicitly quantify. In simpler cases, careful analysis using GUM Supplement 1 (MC) methods augmented with random effects meta analysis yields similar results to a full BH model analysis. In this article we describe both approaches to rigorous uncertainty evaluation using as examples measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

Cross-correlation patterns in social opinion formation with sequential data

NASA Astrophysics Data System (ADS)

Chakrabarti, Anindya S.

2016-11-01

Recent research on large-scale internet data suggests existence of patterns in the collective behavior of billions of people even though each of them may pursue own activities. In this paper, we interpret online rating activity as a process of forming social opinion about individual items, where people sequentially choose a rating based on the current information set comprising all previous ratings and own preferences. We construct an opinion index from the sequence of ratings and we show that (1) movie-specific opinion converges much slower than an independent and identically distributed (i.i.d.) sequence of ratings, (2) rating sequence for individual movies shows lesser variation compared to an i.i.d. sequence of ratings, (3) the probability density function of the asymptotic opinions has more spread than that defined over opinion arising from i.i.d. sequence of ratings, (4) opinion sequences across movies are correlated with significantly higher and lower correlation compared to opinion constructed from i.i.d. sequence of ratings, creating a bimodal cross-correlation structure. By decomposing the temporal correlation structures from panel data of movie ratings, we show that the social effects are very prominent whereas group effects cannot be differentiated from those of surrogate data and individual effects are quite small. The former explains a large part of extreme positive or negative correlations between sequences of opinions. In general, this method can be applied to any rating data to extract social or group-specific effects in correlation structures. We conclude that in this particular case, social effects are important in opinion formation process.

A novel method for effective diffusion coefficient measurement in gas diffusion media of polymer electrolyte fuel cells

NASA Astrophysics Data System (ADS)

Yang, Linlin; Sun, Hai; Fu, Xudong; Wang, Suli; Jiang, Luhua; Sun, Gongquan

2014-07-01

A novel method for measuring effective diffusion coefficient of porous materials is developed. The oxygen concentration gradient is established by an air-breathing proton exchange membrane fuel cell (PEMFC). The porous sample is set in a sample holder located in the cathode plate of the PEMFC. At a given oxygen flux, the effective diffusion coefficients are related to the difference of oxygen concentration across the samples, which can be correlated with the differences of the output voltage of the PEMFC with and without inserting the sample in the cathode plate. Compared to the conventional electrical conductivity method, this method is more reliable for measuring non-wetting samples.

Ionospheric earthquake effects detection based on Total Electron Content (TEC) GPS Correlation

NASA Astrophysics Data System (ADS)

Sunardi, Bambang; Muslim, Buldan; Eka Sakya, Andi; Rohadi, Supriyanto; Sulastri; Murjaya, Jaya

2018-03-01

Advances in science and technology showed that ground-based GPS receiver was able to detect ionospheric Total Electron Content (TEC) disturbances caused by various natural phenomena such as earthquakes. One study of Tohoku (Japan) earthquake, March 11, 2011, magnitude M 9.0 showed TEC fluctuations observed from GPS observation network spread around the disaster area. This paper discussed the ionospheric earthquake effects detection using TEC GPS data. The case studies taken were Kebumen earthquake, January 25, 2014, magnitude M 6.2, Sumba earthquake, February 12, 2016, M 6.2 and Halmahera earthquake, February 17, 2016, M 6.1. TEC-GIM (Global Ionosphere Map) correlation methods for 31 days were used to monitor TEC anomaly in ionosphere. To ensure the geomagnetic disturbances due to solar activity, we also compare with Dst index in the same time window. The results showed anomalous ratio of correlation coefficient deviation to its standard deviation upon occurrences of Kebumen and Sumba earthquake, but not detected a similar anomaly for the Halmahera earthquake. It was needed a continous monitoring of TEC GPS data to detect the earthquake effects in ionosphere. This study giving hope in strengthening the earthquake effect early warning system using TEC GPS data. The method development of continuous TEC GPS observation derived from GPS observation network that already exists in Indonesia is needed to support earthquake effects early warning systems.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Fine reservoir structure modeling based upon 3D visualized stratigraphic correlation between horizontal wells: methodology and its application

NASA Astrophysics Data System (ADS)

Chenghua, Ou; Chaochun, Li; Siyuan, Huang; Sheng, James J.; Yuan, Xu

2017-12-01

As the platform-based horizontal well production mode has been widely applied in petroleum industry, building a reliable fine reservoir structure model by using horizontal well stratigraphic correlation has become very important. Horizontal wells usually extend between the upper and bottom boundaries of the target formation, with limited penetration points. Using these limited penetration points to conduct well deviation correction means the formation depth information obtained is not accurate, which makes it hard to build a fine structure model. In order to solve this problem, a method of fine reservoir structure modeling, based on 3D visualized stratigraphic correlation among horizontal wells, is proposed. This method can increase the accuracy when estimating the depth of the penetration points, and can also effectively predict the top and bottom interfaces in the horizontal penetrating section. Moreover, this method will greatly increase not only the number of points of depth data available, but also the accuracy of these data, which achieves the goal of building a reliable fine reservoir structure model by using the stratigraphic correlation among horizontal wells. Using this method, four 3D fine structure layer models have been successfully built of a specimen shale gas field with platform-based horizontal well production mode. The shale gas field is located to the east of Sichuan Basin, China; the successful application of the method has proven its feasibility and reliability.

Triplet p + ip pairing correlations in the doped Kane-Mele-Hubbard model: A quantum Monte Carlo study

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

Ma, Tianxing; Lin, Hai-Qing; Gubernatis, James E.

2015-09-01

By using the constrained-phase quantum Monte Carlo method, we performed a systematic study of the pairing correlations in the ground state of the doped Kane-Mele-Hubbard model on a honeycomb lattice. We find that pairing correlations with d + id symmetry dominate close to half filling, but pairing correlations with p+ip symmetry dominate as hole doping moves the system below three-quarters filling. We correlate these behaviors of the pairing correlations with the topology of the Fermi surfaces of the non-interacting problem. We also find that the effective pairing correlation is enhanced greatly as the interaction increases, and these superconducting correlations aremore » robust against varying the spin-orbit coupling strength. Finally, our numerical results suggest a possible way to realize spin triplet superconductivity in doped honeycomb-like materials or ultracold atoms in optical traps.« less

On the insignificance of Herschel's sunspot correlation

USGS Publications Warehouse

Love, Jeffrey J.

2013-01-01

We examine William Herschel's hypothesis that solar-cycle variation of the Sun's irradiance has a modulating effect on the Earth's climate and that this is, specifically, manifested as an anticorrelation between sunspot number and the market price of wheat. Since Herschel first proposed his hypothesis in 1801, it has been regarded with both interest and skepticism. Recently, reports have been published that either support Herschel's hypothesis or rely on its validity. As a test of Herschel's hypothesis, we seek to reject a null hypothesis of a statistically random correlation between historical sunspot numbers, wheat prices in London and the United States, and wheat farm yields in the United States. We employ binary-correlation, Pearson-correlation, and frequency-domain methods. We test our methods using a historical geomagnetic activity index, well known to be causally correlated with sunspot number. As expected, the measured correlation between sunspot number and geomagnetic activity would be an unlikely realization of random data; the correlation is “statistically significant.” On the other hand, measured correlations between sunspot number and wheat price and wheat yield data would be very likely realizations of random data; these correlations are “insignificant.” Therefore, Herschel's hypothesis must be regarded with skepticism. We compare and contrast our results with those of other researchers. We discuss procedures for evaluating hypotheses that are formulated from historical data.

Is traditional contraceptive use in Moldova associated with poverty and isolation?

PubMed

Lyons-Amos, Mark J; Durrant, Gabriele B; Padmadas, Sabu S

2011-05-01

This study investigates the correlates of traditional contraceptive use in Moldova, a poor country in Europe with one of the highest proportions of traditional contraceptive method users. The high reliance on traditional methods, particularly in the context of sub-replacement level fertility rate, has not been systematically evaluated in demographic research. Using cross-sectional data on a sub-sample of 6039 sexually experienced women from the 2005 Moldovan Demographic and Health Survey, this study hypothesizes that (a) economic and spatial disadvantages increase the likelihood of traditional method use, and (b) high exposure to family planning/reproductive health (FP/RH) programmes increases the propensity to modern method use. Multilevel multinomial models are used to examine the correlates of traditional method use controlling for exposure to sexual activity, socioeconomic and demographic characteristics and data structure. The results show that economic disadvantage increases the probability of traditional method use, but the overall effect is small. Although higher family planning media exposure decreases the reliance on traditional methods among younger women, it has only a marginal effect in increasing modern method use among older women. Family planning programmes designed to encourage women to switch from traditional to modern methods have some success--although the effect is considerably reduced in regions outside of the capital Chisinau. The study concludes that FP/RH efforts directed towards the poorest may have limited impact, but interventions targeted at older women could reduce the burden of unwanted pregnancies and abortions. Addressing differentials in accessing modern methods could improve uptake in rural areas.

Allowable SEM noise for unbiased LER measurement

NASA Astrophysics Data System (ADS)

Papavieros, George; Constantoudis, Vassilios; Gogolides, Evangelos

2018-03-01

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

Association between the accessibility to lethal methods and method-specific suicide rates: An ecological study in Taiwan.

PubMed

Lin, Jin-Jia; Lu, Tsung-Hsueh

2006-07-01

To examine the association between availability of lethal methods of suicide and method-specific suicide rates at the city/ county level in Taiwan. Age-adjusted and age-specific suicide rates of 23 cities/counties in Taiwan for the years 1999 to 2003 were calculated. Partial correlation coefficients were used to examine cross-sectional associations between independent variables, i.e., proportion of agricultural population and proportion of households living on the sixth floor or above, and suicide rates by different methods (poisoning by solids/liquids, jumping, and hanging) after adjusting for unemployment rates and prevalence of depression. The partial correlation coefficient was 0.77 (p < .001) for proportion of agricultural population with solids/liquids poisoning suicide rates. It was 0.73 (p < .001) for the proportion of households living on the sixth floor or above with suicide rates by jumping. Correlations between hanging suicide rates and proportion of agricultural population or between hanging suicide rates and proportion of households living on the sixth floor or above were not significant. The results showed strong positive associations between access to lethal methods and method-specific suicide rates. Controlling the availability of pesticides and fencing high buildings or installing window guards may be effective measures for suicide prevention.

Quantum treatment of protons with the reduced explicitly correlated Hartree-Fock approach

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

Sirjoosingh, Andrew; Pak, Michael V.; Brorsen, Kurt R.

2015-06-07

The nuclear-electronic orbital (NEO) approach treats select nuclei quantum mechanically on the same level as the electrons and includes nonadiabatic effects between the electrons and the quantum nuclei. The practical implementation of this approach is challenging due to the significance of electron-nucleus dynamical correlation. Herein, we present a general extension of the previously developed reduced NEO explicitly correlated Hartree-Fock (RXCHF) approach, in which only select electronic orbitals are explicitly correlated to each quantum nuclear orbital via Gaussian-type geminal functions. Approximations of the electronic exchange between the geminal-coupled electronic orbitals and the other electronic orbitals are also explored. This general approachmore » enables computationally tractable yet accurate calculations on molecular systems with quantum protons. The RXCHF method is applied to the hydrogen cyanide (HCN) and FHF{sup −} systems, where the proton and all electrons are treated quantum mechanically. For the HCN system, only the two electronic orbitals associated with the CH covalent bond are geminal-coupled to the proton orbital. For the FHF{sup −} system, only the four electronic orbitals associated with the two FH covalent bonds are geminal-coupled to the proton orbital. For both systems, the RXCHF method produces qualitatively accurate nuclear densities, in contrast to mean field-based NEO approaches. The development and implementation of the RXCHF method provide the framework to perform calculations on systems such as proton-coupled electron transfer reactions, where electron-proton nonadiabatic effects are important.« less

Comparative Analysis of Results from a Cognitive Emotion Regulation Questionnaire Between International Students from West Asia and Xinjiang College Students in China

PubMed Central

HU, Hongxing; ALSRON, Bahargul; XU, Bin; HAO, Wei

2016-01-01

Background The Cognitive Emotion Regulation Questionnaire (CERQ) is a cognitive and emotional tool measuring how individuals deal with stressful life events. However differences exist in the results of CERQ among individuals. Objective This study was conducted to investigate the CERQ results and depressive symptoms of students at our university (both local and international students) in order to provide further guidance for psychological interventions. Methods 255 sophomore and junior international students (171 male and 84 female) and 262 sophomore and junior Chinese students (124 male and 138 female) were investigated using CERQ, ASLEC and SDS questionnaires. Results were analyzed using SPSS 16.0. Result Compared to Chinese students, international students more often used cognitive adjustment methods such as “positive refocusing”,“re-focus on planning” and “catastrophizing”. In regression equations where depression symptoms were used as the dependent variable, “self-blaming” and “catastrophizing”positively contributed to depression symptoms in international students, while“acceptance” was negatively correlated with depression symptoms.In Chinese students, “life events score” and “catastrophizing”were positively correlated withdepression symptoms, while “positive re-evaluating” was negatively correlated with depression symptoms. Conclusion Among students of different races, positive coping methods were negatively correlated with depression symptoms and could possibly prevent the occurrence of depression, while negative coping methods were positively correlated with depression.Encouraging students to use adaptive coping methods during psychological intervention is an effective way to adjust cognitions and behavior for depression prevention. PMID:28638209

The QAP weighted network analysis method and its application in international services trade

NASA Astrophysics Data System (ADS)

Xu, Helian; Cheng, Long

2016-04-01

Based on QAP (Quadratic Assignment Procedure) correlation and complex network theory, this paper puts forward a new method named QAP Weighted Network Analysis Method. The core idea of the method is to analyze influences among relations in a social or economic group by building a QAP weighted network of networks of relations. In the QAP weighted network, a node depicts a relation and an undirect edge exists between any pair of nodes if there is significant correlation between relations. As an application of the QAP weighted network, we study international services trade by using the QAP weighted network, in which nodes depict 10 kinds of services trade relations. After the analysis of international services trade by QAP weighted network, and by using distance indicators, hierarchy tree and minimum spanning tree, the conclusion shows that: Firstly, significant correlation exists in all services trade, and the development of any one service trade will stimulate the other nine. Secondly, as the economic globalization goes deeper, correlations in all services trade have been strengthened continually, and clustering effects exist in those services trade. Thirdly, transportation services trade, computer and information services trade and communication services trade have the most influence and are at the core in all services trade.

Applications of interferometrically derived terrain slopes: Normalization of SAR backscatter and the interferometric correlation coefficient

NASA Technical Reports Server (NTRS)

Werner, Charles L.; Wegmueller, Urs; Small, David L.; Rosen, Paul A.

1994-01-01

Terrain slopes, which can be measured with Synthetic Aperture Radar (SAR) interferometry either from a height map or from the interferometric phase gradient, were used to calculate the local incidence angle and the correct pixel area. Both are required for correct thematic interpretation of SAR data. The interferometric correlation depends on the pixel area projected on a plane perpendicular to the look vector and requires correction for slope effects. Methods for normalization of the backscatter and interferometric correlation for ERS-1 SAR are presented.

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

PubMed

Han, Fang; Liu, Han

2017-02-01

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

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.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography

PubMed Central

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E.; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-01-01

Purpose Partial volume effects (PVE) are consequences of the limited spatial resolution in emission tomography leading to under-estimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multi-resolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model which may introduce artefacts in regions where no significant correlation exists between anatomical and functional details. Methods A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Results Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present the new model outperformed the 2D global approach, avoiding artefacts and significantly improving quality of the corrected images and their quantitative accuracy. Conclusions A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multi-resolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information. PMID:21978037

Towards prediction of correlated material properties using quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Wagner, Lucas

Correlated electron systems offer a richness of physics far beyond noninteracting systems. If we would like to pursue the dream of designer correlated materials, or, even to set a more modest goal, to explain in detail the properties and effective physics of known materials, then accurate simulation methods are required. Using modern computational resources, quantum Monte Carlo (QMC) techniques offer a way to directly simulate electron correlations. I will show some recent results on a few extremely challenging materials including the metal-insulator transition of VO2, the ground state of the doped cuprates, and the pressure dependence of magnetic properties in FeSe. By using a relatively simple implementation of QMC, at least some properties of these materials can be described truly from first principles, without any adjustable parameters. Using the QMC platform, we have developed a way of systematically deriving effective lattice models from the simulation. This procedure is particularly attractive for correlated electron systems because the QMC methods treat the one-body and many-body components of the wave function and Hamiltonian on completely equal footing. I will show some examples of using this downfolding technique and the high accuracy of QMC to connect our intuitive ideas about interacting electron systems with high fidelity simulations. The work in this presentation was supported in part by NSF DMR 1206242, the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program under Award Number FG02-12ER46875, and the Center for Emergent Superconductivity, Department of Energy Frontier Research Center under Grant No. DEAC0298CH1088. Computing resources were provided by a Blue Waters Illinois grant and INCITE PhotSuper and SuperMatSim allocations.

Understanding the Relative Contributions of Direct Environmental Effects and Passive Genotype-Environment Correlations in the Association between Familial Risk Factors and Child Disruptive Behavior Disorders

PubMed Central

Bornovalova, Marina A.; Cummings, Jenna R.; Hunt, Elizabeth; Blazei, Ryan; Malone, Steve; Iacono, William G.

2013-01-01

Background: Previous work reports an association between familial risk factors stemming from parental characteristics and offspring disruptive behavior disorders (DBDs). This association may reflect a) the direct effects of familial environment, and b) a passive gene-environment correlation, wherein the parents provide both the genes and the environment. The current study examined the contributions of direct environmental influences and passive gene-environment correlations by comparing the effects of familial risk factors on child DBDs in genetically related (biological) and non-related (adoptive) families. Method: Participants were 402 adoptive and 204 biological families. Familial environment was defined as maternal and paternal maladaptive parenting and antisociality, marital conflict, and divorce; offspring DBDs included attention deficit/hyperactivity disorder, conduct disorder, and oppositional defiant disorder. Mixed-level regressions estimated the main effects of familial environment, adoption status, and the familial environment by adoption status interaction term, which tested for a presence of passive gene-environment correlations. Results: There was a main effect of maternal and paternal maladaptive parenting and marital discord on child DBDs, indicating a direct environmental effect. There was no direct environmental effect of maternal or paternal antisociality, but maternal and paternal antisociality had stronger associations with child DBDs in biological families than adoptive families, indicating the presence of a passive gene-environment correlation. Conclusions: Many familial risk factors affected children equally across genetically-related and non-related families, providing evidence for direct environmental effects. The relationship of parental antisociality and offspring DBDs was best explained by a passive gene-environment correlation, where a general vulnerability toward externalizing psychopathology is passed down by the parents to the children. PMID:23714724

A correlated meta-analysis strategy for data mining "OMIC" scans.

PubMed

Province, Michael A; Borecki, Ingrid B

2013-01-01

Meta-analysis is becoming an increasingly popular and powerful tool to integrate findings across studies and OMIC dimensions. But there is the danger that hidden dependencies between putatively "independent" studies can cause inflation of type I error, due to reinforcement of the evidence from false-positive findings. We present here a simple method for conducting meta-analyses that automatically estimates the degree of any such non-independence between OMIC scans and corrects the inference for it, retaining the proper type I error structure. The method does not require the original data from the source studies, but operates only on summary analysis results from these in OMIC scans. The method is applicable in a wide variety of situations including combining GWAS and or sequencing scan results across studies with dependencies due to overlapping subjects, as well as to scans of correlated traits, in a meta-analysis scan for pleiotropic genetic effects. The method correctly detects which scans are actually independent in which case it yields the traditional meta-analysis, so it may safely be used in all cases, when there is even a suspicion of correlation amongst scans.

Evaluation of a Teaching Assistant Program for Third-Year Pharmacy Students.

PubMed

Bradley, Courtney L; Khanova, Julia; Scolaro, Kelly L

2016-11-25

Objectives. To determine if a teaching assistant (TA) program for third-year pharmacy students (PY3s) improves confidence in teaching abilities. Additionally, 3 assessment methods (faculty, student, and TA self-evaluations) were compared for similarities and correlations. Methods. An application and interview process was used to select 21 pharmacy students to serve as TAs for the Pharmaceutical Care Laboratory course for 2 semesters. Participants' self-perceived confidence in teaching abilities was assessed at the start, midpoint, and conclusion of the program. The relationships between the scores were analyzed using 3 assessment methods. Results. All 21 TAs agreed to participate in the study and completed the 2 teaching semesters. The TAs confidence in overall teaching abilities increased significantly (80.7 vs 91.4, p <0.001). There was a significant difference between the three assessment scores in the fall ( p =0.027) and spring ( p <0.001) semesters. However, no correlation was found among the assessment scores. Conclusions. The TA program was effective in improving confidence in teaching abilities. The lack of correlation among the assessment methods highlights the importance of various forms of feedback.

STELLAR ATMOSPHERES, ATMOSPHERIC EXTENSION, AND FUNDAMENTAL PARAMETERS: WEIGHING STARS USING THE STELLAR MASS INDEX

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

Neilson, Hilding R.; Lester, John B.; Baron, Fabien

2016-10-20

One of the great challenges of understanding stars is measuring their masses. The best methods for measuring stellar masses include binary interaction, asteroseismology, and stellar evolution models, but these methods are not ideal for red giant and supergiant stars. In this work, we propose a novel method for inferring stellar masses of evolved red giant and supergiant stars using interferometric and spectrophotometric observations combined with spherical model stellar atmospheres to measure what we call the stellar mass index, defined as the ratio between the stellar radius and mass. The method is based on the correlation between different measurements of angularmore » diameter, used as a proxy for atmospheric extension, and fundamental stellar parameters. For a given star, spectrophotometry measures the Rosseland angular diameter while interferometric observations generally probe a larger limb-darkened angular diameter. The ratio of these two angular diameters is proportional to the relative extension of the stellar atmosphere, which is strongly correlated to the star’s effective temperature, radius, and mass. We show that these correlations are strong and can lead to precise measurements of stellar masses.« less

The Complex Action Recognition via the Correlated Topic Model

PubMed Central

Tu, Hong-bin; Xia, Li-min; Wang, Zheng-wu

2014-01-01

Human complex action recognition is an important research area of the action recognition. Among various obstacles to human complex action recognition, one of the most challenging is to deal with self-occlusion, where one body part occludes another one. This paper presents a new method of human complex action recognition, which is based on optical flow and correlated topic model (CTM). Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms of an occlusion state variable. Secondly, the structure from motion (SFM) is used for reconstructing the missing data of point trajectories. Then, we can extract the key frame based on motion feature from optical flow and the ratios of the width and height are extracted by the human silhouette. Finally, we use the topic model of correlated topic model (CTM) to classify action. Experiments were performed on the KTH, Weizmann, and UIUC action dataset to test and evaluate the proposed method. The compared experiment results showed that the proposed method was more effective than compared methods. PMID:24574920

Wavelet filtered shifted phase-encoded joint transform correlation for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.

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.

Estimating correlation of prevalence at two locations in the farm-to-table continuum using qualitative test data.

PubMed

Williams, Michael S; Ebel, Eric D

2017-03-20

The presence or absence of contaminants in food samples changes as a commodity moves along the farm-to-table continuum. Interest lies in the degree to which the prevalence (i.e., infected animals or contaminated sample units) at one location in the continuum, as measured by the proportion of test-positive samples, is correlated with the prevalence at a location later in the continuum. If prevalence of a contaminant at one location in the continuum is strongly correlated with the prevalence of the contaminant later in the continuum, then the effect of changes in contamination on overall food safety can be better understood. Pearson's correlation coefficient is one of the simplest metrics of association between two measurements of prevalence but it is biased when data consisting of presence/absence testing results are used to directly estimate the correlation. This study demonstrates the potential magnitude of this bias and explores the utility of three methods for unbiased estimation of the degree of correlation in prevalence. An example, based on testing broiler chicken carcasses for Salmonella at re-hang and post-chill, is used to demonstrate the methods. Published by Elsevier B.V.

Meta-analysis of correlations revisited: attempted replication and extension of Field's (2001) simulation studies.

PubMed

Hafdahl, Adam R; Williams, Michelle A

2009-03-01

In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-z and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-z correlations, especially with heterogeneous correlation parameters. The present attempt to replicate Field's simulations included comparisons with analytic values as well as results for efficiency and confidence-interval coverage. Field's results under homogeneity were mostly replicable, but those under heterogeneity were not: The latter exhibited up to over .17 more bias than ours and, for tests of the mean correlation and homogeneity, respectively, nonnull rejection rates up to .60 lower and .65 higher. Changes to Field's observations and conclusions are recommended, and practical guidance is offered regarding simulation evidence and choices among methods. Most cautions about poor performance of Fisher-z methods are largely unfounded, especially with a more appropriate z-to-r transformation. The Appendix gives a computer program for obtaining Pearson-r moments from a normal Fisher-z distribution, which is used to demonstrate distortion due to direct z-to-r transformation of a mean Fisher-z correlation.

Evaluation of Phytoavailability of Heavy Metals to Chinese Cabbage (Brassica chinensis L.) in Rural Soils

PubMed Central

Hseu, Zeng-Yei; Zehetner, Franz

2014-01-01

This study compared the extractability of Cd, Cu, Ni, Pb, and Zn by 8 extraction protocols for 22 representative rural soils in Taiwan and correlated the extractable amounts of the metals with their uptake by Chinese cabbage for developing an empirical model to predict metal phytoavailability based on soil properties. Chemical agents in these protocols included dilute acids, neutral salts, and chelating agents, in addition to water and the Rhizon soil solution sampler. The highest concentrations of extractable metals were observed in the HCl extraction and the lowest in the Rhizon sampling method. The linear correlation coefficients between extractable metals in soil pools and metals in shoots were higher than those in roots. Correlations between extractable metal concentrations and soil properties were variable; soil pH, clay content, total metal content, and extractable metal concentration were considered together to simulate their combined effects on crop uptake by an empirical model. This combination improved the correlations to different extents for different extraction methods, particularly for Pb, for which the extractable amounts with any extraction protocol did not correlate with crop uptake by simple correlation analysis. PMID:25295297

Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data.

PubMed

Xing, Dongyuan; Huang, Yangxin; Chen, Henian; Zhu, Yiliang; Dagne, Getachew A; Baldwin, Julie

2017-08-01

Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew- t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method.

Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

PubMed Central

Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

2012-01-01

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

PubMed

Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

2012-01-01

Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

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.

[Effects of Tillage on Distribution of Heavy Metals and Organic Matter Within Purple Paddy Soil Aggregates].

PubMed

Shi, Qiong-bin; Zhao, Xiu-lan; Chang, Tong-ju; Lu, Ji-wen

2016-05-15

A long-term experiment was utilized to study the effects of tillage methods on the contents and distribution characteristics of organic matter and heavy metals (Cu, Zn, Pb, Cd, Fe and Mn) in aggregates with different sizes (including 1-2, 0.25-1, 0.05-0.25 mm and < 0.05 mm) in a purple paddy soil under two tillage methods including flooded paddy field (FPF) and paddy-upland rotation (PR). The relationship between heavy metals and organic matter in soil aggregates was also analyzed. The results showed that the aggregates of two tillage methods were dominated by 0.05-0.25 mm and < 0.05 mm particle size, respectively. The contents of organic matter in each aggregate decreased with the decrease of aggregate sizes, however, compared to PR, FPF could significantly increase the contents of organic matter in soils and aggregates. The tillage methods did not significantly affect the contents of heavy metals in soils, but FPF could enhance the accumulation and distribution of aggregate, organic matter and heavy metals in aggregates with diameters of 1-2 mm and 0.25-1 mm. Correlation analysis found that there was a negative correlation between the contents of heavy metals and organic matter in soil aggregates, but a positive correlation between the amounts of heavy metal and organic matter accumulated in soil aggregates. From the slope of the correlation analysis equations, we could found that the sensitivities of heavy metals to the changes of soil organic matters followed the order of Mn > Zn > Pb > Cu > Fe > Cd under the same tillage. When it came to the same heavy metal, it was more sensitive in PR than in FPF.

Relationship between pore geometric characteristics and SIP/NMR parameters observed for mudstones

NASA Astrophysics Data System (ADS)

Robinson, J.; Slater, L. D.; Keating, K.; Parker, B. L.; Robinson, T.

2017-12-01

The reliable estimation of permeability remains one of the most challenging problems in hydrogeological characterization. Cost effective, non-invasive geophysical methods such as spectral induced polarization (SIP) and nuclear magnetic resonance (NMR) offer an alternative to traditional sampling methods as they are sensitive to the mineral surfaces and pore spaces that control permeability. We performed extensive physical characterization, SIP and NMR geophysical measurements on fractured rock cores extracted from a mudstone site in an effort to compare 1) the pore size characterization determined from traditional and geophysical methods and 2) the performance of permeability models based on these methods. We focus on two physical characterizations that are well-correlated with hydraulic properties: the pore volume normalized surface area (Spor) and an interconnected pore diameter (Λ). We find the SIP polarization magnitude and relaxation time are better correlated with Spor than Λ, the best correlation of these SIP measures for our sample dataset was found with Spor divided by the electrical formation factor (F). NMR parameters are, similarly, better correlated with Spor than Λ. We implement previously proposed mechanistic and empirical permeability models using SIP and NMR parameters. A sandstone-calibrated SIP model using a polarization magnitude does not perform well while a SIP model using a mean relaxation time performs better in part by more sufficiently accounting for the effects of fluid chemistry. A sandstone-calibrated NMR permeability model using an average measure of the relaxation time does not perform well, presumably due to small pore sizes which are either not connected or contain water of limited mobility. An NMR model based on the laboratory determined portions of the bound versus mobile portions of the relaxation distribution performed reasonably well. While limitations exist, there are many opportunities to use geophysical data to predict permeability in mudstone formations.

[Differentiation of Staphylococcus aureus isolates based on phenotypical characters].

PubMed

Miedzobrodzki, Jacek; Małachowa, Natalia; Markiewski, Tomasz; Białecka, Anna; Kasprowicz, Andrzej

2008-06-30

Typing of Staphylococcus aureus isolates is a necessary procedure for monitoring the transmission of S. aureus among carriers and in epidemiology. Evaluation of the range of relationship among isolates rely on epidemiological markers and is possible because of the clonal character of S. aureus species. Effective typing shows the scheme of transmission of infection in a selected area, enables identifying the reservoir of the microorganism, and may enhance effective eradication. A set of typing methods for use in analyses of epidemiological correlations and the identification of S. aureus isolates is presented. The following methods of typing are described: biotyping, serotyping, antibiogram, protein electrophoresis, cell protein profiles (proteom), immunoblotting, multilocus enzyme electrophoresis (MLEE), zymotyping, and standard species identification of S. aureus in the diagnostic laboratory. Phenotyping methods for S. aureus isolates used in the past and today in epidemiological investigations and in analyses of correlations among S. aureus isolates are presented in this review. The presented methods use morphological characteristics, physiological properties, and chemical structures of the bacteria as criteria for typing. The precision of these standard methods is not always satisfactory as S. aureus strains with atypical biochemical characters have evolved recently. Therefore it is essential to introduce additional typing procedures using molecular biology methods without neglecting phenotypic methods.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Functional renormalization group and Kohn-Sham scheme in density functional theory

NASA Astrophysics Data System (ADS)

Liang, Haozhao; Niu, Yifei; Hatsuda, Tetsuo

2018-04-01

Deriving accurate energy density functional is one of the central problems in condensed matter physics, nuclear physics, and quantum chemistry. We propose a novel method to deduce the energy density functional by combining the idea of the functional renormalization group and the Kohn-Sham scheme in density functional theory. The key idea is to solve the renormalization group flow for the effective action decomposed into the mean-field part and the correlation part. Also, we propose a simple practical method to quantify the uncertainty associated with the truncation of the correlation part. By taking the φ4 theory in zero dimension as a benchmark, we demonstrate that our method shows extremely fast convergence to the exact result even for the highly strong coupling regime.

The protonation of N2O reexamined - A case study on the reliability of various electron correlation methods for minima and transition states

NASA Technical Reports Server (NTRS)

Martin, J. M. L.; Lee, Timothy J.

1993-01-01

The protonation of N2O and the intramolecular proton transfer in N2OH(+) are studied using various basis sets and a variety of methods, including second-order many-body perturbation theory (MP2), singles and doubles coupled cluster (CCSD), the augmented coupled cluster (CCSD/T/), and complete active space self-consistent field (CASSCF) methods. For geometries, MP2 leads to serious errors even for HNNO(+); for the transition state, only CCSD/T/ produces a reliable geometry due to serious nondynamical correlation effects. The proton affinity at 298.15 K is estimated at 137.6 kcal/mol, in close agreement with recent experimental determinations of 137.3 +/- 1 kcal/mol.

A procedure for testing the quality of LANDSAT atmospheric correction algorithms

NASA Technical Reports Server (NTRS)

Dias, L. A. V. (Principal Investigator); Vijaykumar, N. L.; Neto, G. C.

1982-01-01

There are two basic methods for testing the quality of an algorithm to minimize atmospheric effects on LANDSAT imagery: (1) test the results a posteriori, using ground truth or control points; (2) use a method based on image data plus estimation of additional ground and/or atmospheric parameters. A procedure based on the second method is described. In order to select the parameters, initially the image contrast is examined for a series of parameter combinations. The contrast improves for better corrections. In addition the correlation coefficient between two subimages, taken at different times, of the same scene is used for parameter's selection. The regions to be correlated should not have changed considerably in time. A few examples using this proposed procedure are presented.

Lossless Compression of JPEG Coded Photo Collections.

PubMed

Wu, Hao; Sun, Xiaoyan; Yang, Jingyu; Zeng, Wenjun; Wu, Feng

2016-04-06

The explosion of digital photos has posed a significant challenge to photo storage and transmission for both personal devices and cloud platforms. In this paper, we propose a novel lossless compression method to further reduce the size of a set of JPEG coded correlated images without any loss of information. The proposed method jointly removes inter/intra image redundancy in the feature, spatial, and frequency domains. For each collection, we first organize the images into a pseudo video by minimizing the global prediction cost in the feature domain. We then present a hybrid disparity compensation method to better exploit both the global and local correlations among the images in the spatial domain. Furthermore, the redundancy between each compensated signal and the corresponding target image is adaptively reduced in the frequency domain. Experimental results demonstrate the effectiveness of the proposed lossless compression method. Compared to the JPEG coded image collections, our method achieves average bit savings of more than 31%.

Comparative Analysis of Results from a Cognitive Emotion Regulation Questionnaire Between International Students from West Asia and Xinjiang College Students in China.

PubMed

Hu, Hongxing; Alsron, Bahargul; Xu, Bin; Hao, Wei

2016-12-25

The Cognitive Emotion Regulation Questionnaire (CERQ) is a cognitive and emotional tool measuring how individuals deal with stressful life events. However differences exist in the results of CERQ among individuals. This study was conducted to investigate the CERQ results and depressive symptoms of students at our university (both local and international students) in order to provide further guidance for psychological interventions. 255 sophomore and junior international students (171 male and 84 female) and 262 sophomore and junior Chinese students (124 male and 138 female) were investigated using CERQ, ASLEC and SDS questionnaires. Results were analyzed using SPSS 16.0. Compared to Chinese students, international students more often used cognitive adjustment methods such as "positive refocusing","re-focus on planning" and "catastrophizing". In regression equations where depression symptoms were used as the dependent variable, "self-blaming" and "catastrophizing"positively contributed to depression symptoms in international students, while"acceptance" was negatively correlated with depression symptoms.In Chinese students, "life events score" and "catastrophizing"were positively correlated withdepression symptoms, while "positive re-evaluating" was negatively correlated with depression symptoms. Among students of different races, positive coping methods were negatively correlated with depression symptoms and could possibly prevent the occurrence of depression, while negative coping methods were positively correlated with depression.Encouraging students to use adaptive coping methods during psychological intervention is an effective way to adjust cognitions and behavior for depression prevention.

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

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.

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.

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.

Features of the Asynchronous Correlation between the China Coal Price Index and Coal Mining Accidental Deaths

PubMed Central

Huang, Yuecheng; Cheng, Wuyi; Luo, Sida; Luo, Yun; Ma, Chengchen; He, Tailin

2016-01-01

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices. PMID:27902748

Measurement of the dipole in the cross-correlation function of galaxies

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

Gaztanaga, Enrique; Bonvin, Camille; Hui, Lam, E-mail: gazta@ice.cat, E-mail: camille.bonvin@unige.ch, E-mail: lhui@astro.columbia.edu

It is usually assumed that in the linear regime the two-point correlation function of galaxies contains only a monopole, quadrupole and hexadecapole. Looking at cross-correlations between different populations of galaxies, this turns out not to be the case. In particular, the cross-correlations between a bright and a faint population of galaxies contain also a dipole. In this paper we present the first attempt to measure this dipole. We discuss the four types of effects that contribute to the dipole: relativistic distortions, evolution effect, wide-angle effect and large-angle effect. We show that the first three contributions are intrinsic anti-symmetric contributions thatmore » do not depend on the choice of angle used to measure the dipole. On the other hand the large-angle effect appears only if the angle chosen to extract the dipole breaks the symmetry of the problem. We show that the relativistic distortions, the evolution effect and the wide-angle effect are too small to be detected in the LOWz and CMASS sample of the BOSS survey. On the other hand with a specific combination of angles we are able to measure the large-angle effect with high significance. We emphasise that this large-angle dipole does not contain new physical information, since it is just a geometrical combination of the monopole and the quadrupole. However this measurement, which is in excellent agreement with theoretical predictions, validates our method for extracting the dipole from the two-point correlation function and it opens the way to the detection of relativistic effects in future surveys like e.g. DESI.« less

Dynamic correlation effects in fully differential cross sections for 75-keV proton-impact ionization of helium

NASA Astrophysics Data System (ADS)

Niu, Xiaojie; Sun, Shiyan; Wang, Fujun; Jia, Xiangfu

2017-08-01

The effect of final-state dynamic correlation is investigated for helium single ionization by 75-keV proton impact analyzing fully differential cross sections (FDCS). The final state is represented by a continuum correlated wave (CCW-PT) function which accounts for the interaction between the projectile and the residual target ion (PT interaction). This continuum correlated wave function partially includes the correlation of electron-projectile and electron-target relative motion as coupling terms of the wave equation. The transition matrix is evaluated using the CCW-PT function and the Born initial state. The analytical expression of the transition matrix has been obtained. We have shown that this series is strongly convergent and analyzed the contribution of their different terms to the FDCS within the perturbation method. Illustrative computations are performed in the scattering plane and in the perpendicular plane. Both the correlation effects and the PT interaction are checked by the preset calculations. Our results are compared with absolute experimental data as well as other theoretical models. We have shown that the dynamic correlation plays an important role in the single ionization of atoms by proton impact at intermediate projectile energies, especially at large transverse momentum transfer. While overall agreement between theory and the experimental data is encouraging, detailed agreement is lacking. The need for more theoretical and experimental work is emphasized.

Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

PubMed Central

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries. PMID:24278146

Quantum coherence selective 2D Raman–2D electronic spectroscopy

PubMed Central

Spencer, Austin P.; Hutson, William O.; Harel, Elad

2017-01-01

Electronic and vibrational correlations report on the dynamics and structure of molecular species, yet revealing these correlations experimentally has proved extremely challenging. Here, we demonstrate a method that probes correlations between states within the vibrational and electronic manifold with quantum coherence selectivity. Specifically, we measure a fully coherent four-dimensional spectrum which simultaneously encodes vibrational–vibrational, electronic–vibrational and electronic–electronic interactions. By combining near-impulsive resonant and non-resonant excitation, the desired fifth-order signal of a complex organic molecule in solution is measured free of unwanted lower-order contamination. A critical feature of this method is electronic and vibrational frequency resolution, enabling isolation and assignment of individual quantum coherence pathways. The vibronic structure of the system is then revealed within an otherwise broad and featureless 2D electronic spectrum. This method is suited for studying elusive quantum effects in which electronic transitions strongly couple to phonons and vibrations, such as energy transfer in photosynthetic pigment–protein complexes. PMID:28281541

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.

Effects of diffraction by ionospheric electron density irregularities on the range error in GNSS dual-frequency positioning and phase decorrelation

NASA Astrophysics Data System (ADS)

Gherm, Vadim E.; Zernov, Nikolay N.; Strangeways, Hal J.

2011-06-01

It can be important to determine the correlation of different frequency signals in L band that have followed transionospheric paths. In the future, both GPS and the new Galileo satellite system will broadcast three frequencies enabling more advanced three frequency correction schemes so that knowledge of correlations of different frequency pairs for scintillation conditions is desirable. Even at present, it would be helpful to know how dual-frequency Global Navigation Satellite Systems positioning can be affected by lack of correlation between the L1 and L2 signals. To treat this problem of signal correlation for the case of strong scintillation, a previously constructed simulator program, based on the hybrid method, has been further modified to simulate the fields for both frequencies on the ground, taking account of their cross correlation. Then, the errors in the two-frequency range finding method caused by scintillation have been estimated for particular ionospheric conditions and for a realistic fully three-dimensional model of the ionospheric turbulence. The results which are presented for five different frequency pairs (L1/L2, L1/L3, L1/L5, L2/L3, and L2/L5) show the dependence of diffractional errors on the scintillation index S4 and that the errors diverge from a linear relationship, the stronger are scintillation effects, and may reach up to ten centimeters, or more. The correlation of the phases at spaced frequencies has also been studied and found that the correlation coefficients for different pairs of frequencies depend on the procedure of phase retrieval, and reduce slowly as both the variance of the electron density fluctuations and cycle slips increase.

Mathematics Performance and Principal Effectiveness: A Case Study of Some Coastal Primary Schools in Sri Lanka

ERIC Educational Resources Information Center

Egodawatte, Gunawardena

2012-01-01

This mixed method research study is situated in the school effectiveness research paradigm to examine the correlation between the effectiveness of urban, primary school principals and their students' performance in mathematics. Nine, urban, primary schools from Negombo, a coastal fishing area in Sri Lanka, were selected; their student achievements…

Water 16-mers and hexamers: assessment of the three-body and electrostatically embedded many-body approximations of the correlation energy or the nonlocal energy as ways to include cooperative effects.

PubMed

Qi, Helena W; Leverentz, Hannah R; Truhlar, Donald G

2013-05-30

This work presents a new fragment method, the electrostatically embedded many-body expansion of the nonlocal energy (EE-MB-NE), and shows that it, along with the previously proposed electrostatically embedded many-body expansion of the correlation energy (EE-MB-CE), produces accurate results for large systems at the level of CCSD(T) coupled cluster theory. We primarily study water 16-mers, but we also test the EE-MB-CE method on water hexamers. We analyze the distributions of two-body and three-body terms to show why the many-body expansion of the electrostatically embedded correlation energy converges faster than the many-body expansion of the entire electrostatically embedded interaction potential. The average magnitude of the dimer contributions to the pairwise additive (PA) term of the correlation energy (which neglects cooperative effects) is only one-half of that of the average dimer contribution to the PA term of the expansion of the total energy; this explains why the mean unsigned error (MUE) of the EE-PA-CE approximation is only one-half of that of the EE-PA approximation. Similarly, the average magnitude of the trimer contributions to the three-body (3B) term of the EE-3B-CE approximation is only one-fourth of that of the EE-3B approximation, and the MUE of the EE-3B-CE approximation is one-fourth that of the EE-3B approximation. Finally, we test the efficacy of two- and three-body density functional corrections. One such density functional correction method, the new EE-PA-NE method, with the OLYP or the OHLYP density functional (where the OHLYP functional is the OptX exchange functional combined with the LYP correlation functional multiplied by 0.5), has the best performance-to-price ratio of any method whose computational cost scales as the third power of the number of monomers and is competitive in accuracy in the tests presented here with even the electrostatically embedded three-body approximation.

A new generation of effective core potentials for correlated calculations

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

Bennett, Michael Chandler; Melton, Cody A.; Annaberdiyev, Abdulgani

Here, we outline ideas on desired properties for a new generation of effective core potentials (ECPs) that will allow valence-only calculations to reach the full potential offered by recent advances in many-body wave function methods. The key improvements include consistent use of correlated methods throughout ECP constructions and improved transferability as required for an accurate description of molecular systems over a range of geometries. The guiding principle is the isospectrality of all-electron and ECP Hamiltonians for a subset of valence states. We illustrate these concepts on a few first- and second-row atoms (B, C, N, O, S), and we obtainmore » higher accuracy in transferability than previous constructions while using semi-local ECPs with a small number of parameters. In addition, the constructed ECPs enable many-body calculations of valence properties with higher (or same) accuracy than their all-electron counterparts with uncorrelated cores. This implies that the ECPs include also some of the impacts of core-core and core-valence correlations on valence properties. The results open further prospects for ECP improvements and refinements.« less

A new generation of effective core potentials for correlated calculations

DOE PAGES

Bennett, Michael Chandler; Melton, Cody A.; Annaberdiyev, Abdulgani; ...

2017-12-12

Here, we outline ideas on desired properties for a new generation of effective core potentials (ECPs) that will allow valence-only calculations to reach the full potential offered by recent advances in many-body wave function methods. The key improvements include consistent use of correlated methods throughout ECP constructions and improved transferability as required for an accurate description of molecular systems over a range of geometries. The guiding principle is the isospectrality of all-electron and ECP Hamiltonians for a subset of valence states. We illustrate these concepts on a few first- and second-row atoms (B, C, N, O, S), and we obtainmore » higher accuracy in transferability than previous constructions while using semi-local ECPs with a small number of parameters. In addition, the constructed ECPs enable many-body calculations of valence properties with higher (or same) accuracy than their all-electron counterparts with uncorrelated cores. This implies that the ECPs include also some of the impacts of core-core and core-valence correlations on valence properties. The results open further prospects for ECP improvements and refinements.« less

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.

Effect of sample stratification on dairy GWAS results

PubMed Central

2012-01-01

Background Artificial insemination and genetic selection are major factors contributing to population stratification in dairy cattle. In this study, we analyzed the effect of sample stratification and the effect of stratification correction on results of a dairy genome-wide association study (GWAS). Three methods for stratification correction were used: the efficient mixed-model association expedited (EMMAX) method accounting for correlation among all individuals, a generalized least squares (GLS) method based on half-sib intraclass correlation, and a principal component analysis (PCA) approach. Results Historical pedigree data revealed that the 1,654 contemporary cows in the GWAS were all related when traced through approximately 10–15 generations of ancestors. Genome and phenotype stratifications had a striking overlap with the half-sib structure. A large elite half-sib family of cows contributed to the detection of favorable alleles that had low frequencies in the general population and high frequencies in the elite cows and contributed to the detection of X chromosome effects. All three methods for stratification correction reduced the number of significant effects. EMMAX method had the most severe reduction in the number of significant effects, and the PCA method using 20 principal components and GLS had similar significance levels. Removal of the elite cows from the analysis without using stratification correction removed many effects that were also removed by the three methods for stratification correction, indicating that stratification correction could have removed some true effects due to the elite cows. SNP effects with good consensus between different methods and effect size distributions from USDA’s Holstein genomic evaluation included the DGAT1-NIBP region of BTA14 for production traits, a SNP 45kb upstream from PIGY on BTA6 and two SNPs in NIBP on BTA14 for protein percentage. However, most of these consensus effects had similar frequencies in the elite and average cows. Conclusions Genetic selection and extensive use of artificial insemination contributed to overlapped genome, pedigree and phenotype stratifications. The presence of an elite cluster of cows was related to the detection of rare favorable alleles that had high frequencies in the elite cluster and low frequencies in the remaining cows. Methods for stratification correction could have removed some true effects associated with genetic selection. PMID:23039970

Treating Subvalence Correlation Effects in Domain Based Pair Natural Orbital Coupled Cluster Calculations: An Out-of-the-Box Approach.

PubMed

Bistoni, Giovanni; Riplinger, Christoph; Minenkov, Yury; Cavallo, Luigi; Auer, Alexander A; Neese, Frank

2017-07-11

The validity of the main approximations used in canonical and domain based pair natural orbital coupled cluster methods (CCSD(T) and DLPNO-CCSD(T), respectively) in standard chemical applications is discussed. In particular, we investigate the dependence of the results on the number of electrons included in the correlation treatment in frozen-core (FC) calculations and on the main threshold governing the accuracy of DLPNO all-electron (AE) calculations. Initially, scalar relativistic orbital energies for the ground state of the atoms from Li to Rn in the periodic table are calculated. An energy criterion is used for determining the orbitals that can be excluded from the correlation treatment in FC coupled cluster calculations without significant loss of accuracy. The heterolytic dissociation energy (HDE) of a series of metal compounds (LiF, NaF, AlF 3 , CaF 2 , CuF, GaF 3 , YF 3 , AgF, InF 3 , HfF 4 , and AuF) is calculated at the canonical CCSD(T) level, and the dependence of the results on the number of correlated electrons is investigated. Although for many of the studied reactions subvalence correlation effects contribute significantly to the HDE, the use of an energy criterion permits a conservative definition of the size of the core, allowing FC calculations to be performed in a black-box fashion while retaining chemical accuracy. A comparison of the CCSD and the DLPNO-CCSD methods in describing the core-core, core-valence, and valence-valence components of the correlation energy is given. It is found that more conservative thresholds must be used for electron pairs containing at least one core electron in order to achieve high accuracy in AE DLPNO-CCSD calculations relative to FC calculations. With the new settings, the DLPNO-CCSD method reproduces canonical CCSD results in both AE and FC calculations with the same accuracy.

Meta-Analyzing a Complex Correlational Dataset: A Case Study Using Correlations That Measure the Relationship between Parental Involvement and Academic Achievement

ERIC Educational Resources Information Center

Polanin, Joshua R.; Wilson, Sandra Jo

2014-01-01

The purpose of this project is to demonstrate the practical methods developed to utilize a dataset consisting of both multivariate and multilevel effect size data. The context for this project is a large-scale meta-analytic review of the predictors of academic achievement. This project is guided by three primary research questions: (1) How do we…

Core-core and core-valence correlation

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

1988-01-01

The effect of 1s core correlation on properties and energy separations are analyzed using full configuration-interaction (FCI) calculations. The Be1S - 1P, the C 3P - 5S,m and CH(+) 1Sigma(+) - 1Pi separations, and CH(+) spectroscopic constants, dipole moment, and 1Sigma(+) - 1Pi transition dipole moment have been studied. The results of the FCI calculations are compared to those obtained using approximate methods.

Combining individual participant and aggregated data in a meta-analysis with correlational studies.

PubMed

Pigott, Terri; Williams, Ryan; Polanin, Joshua

2012-12-01

This paper presents methods for combining individual participant data (IPD) with aggregated study level data (AD) in a meta-analysis of correlational studies. Although medical researchers have employed IPD in a wide range of studies, only a single example exists in the social sciences. New policies at the National Science Foundation requiring grantees to submit data archiving plans may increase social scientists' access to individual level data that could be combined with traditional meta-analysis. The methods presented here extend prior work on IPD to meta-analyses using correlational studies. The examples presented illustrate the synthesis of publicly available national datasets in education with aggregated study data from a meta-analysis examining the correlation of socioeconomic status measures and academic achievement. The major benefit of the inclusion of the individual level is that both within-study and between-study interactions among moderators of effect size can be estimated. Given the potential growth in data archives in the social sciences, we should see a corresponding increase in the ability to synthesize IPD and AD in a single meta-analysis, leading to a more complete understanding of how within-study and between-study moderators relate to effect size. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

38 CFR 1.17 - Evaluation of studies relating to health effects of radiation exposure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... health effects of radiation exposure. (a) From time to time, the Secretary shall publish evaluations of... paragraph a valid study is one which: (i) Has adequately described the study design and methods of data... studies affecting epidemiological assessments including case series, correlational studies and studies...

38 CFR 1.17 - Evaluation of studies relating to health effects of radiation exposure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... health effects of radiation exposure. (a) From time to time, the Secretary shall publish evaluations of... paragraph a valid study is one which: (i) Has adequately described the study design and methods of data... studies affecting epidemiological assessments including case series, correlational studies and studies...

38 CFR 1.17 - Evaluation of studies relating to health effects of radiation exposure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... health effects of radiation exposure. (a) From time to time, the Secretary shall publish evaluations of... paragraph a valid study is one which: (i) Has adequately described the study design and methods of data... studies affecting epidemiological assessments including case series, correlational studies and studies...

38 CFR 1.17 - Evaluation of studies relating to health effects of radiation exposure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... health effects of radiation exposure. (a) From time to time, the Secretary shall publish evaluations of... paragraph a valid study is one which: (i) Has adequately described the study design and methods of data... studies affecting epidemiological assessments including case series, correlational studies and studies...

38 CFR 1.17 - Evaluation of studies relating to health effects of radiation exposure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... health effects of radiation exposure. (a) From time to time, the Secretary shall publish evaluations of... paragraph a valid study is one which: (i) Has adequately described the study design and methods of data... studies affecting epidemiological assessments including case series, correlational studies and studies...

Finite word length effects on digital filter implementation.

NASA Technical Reports Server (NTRS)

Bowman, J. D.; Clark, F. H.

1972-01-01

This paper is a discussion of two known techniques to analyze finite word length effects on digital filters. These techniques are extended to several additional programming forms and the results verified experimentally. A correlation of the analytical weighting functions for the two methods is made through the Mason Gain Formula.

RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint

PubMed Central

Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

2016-01-01

The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods. PMID:27827882

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed hydrology. However, a thorough validation and a comparison with other methods are recommended before using the JBC method, since it may perform worse than the IBC method for some cases due to bias nonstationarity of climate model outputs.

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.

Removal of correlated noise online for in situ measurements by using multichannel magnetic resonance sounding system

NASA Astrophysics Data System (ADS)

Lin, Tingting; Zhang, Siyuan; Zhang, Yang; Wan, Ling; Lin, Jun

2017-01-01

Compared with the other geophysical approaches, magnetic resonance sounding (MRS) technique is direct and nondestructive in subsurface water exploration. It provides water content distribution and estimates hydrogeological properties. The biggest challenge is that MRS measurement always suffers bad signal-to-noise ratio, and it can be carried out only far from sources of noise. To solve this problem, a series of de-noising methods are developed. However, most of them are post-processing, leading the data quality uncontrolled for in situ measurements. In the present study, a new approach that removal of correlated noise online is found to overcome the restriction. Based on LabVIEW, a method is provided to enable online data quality control by the way of realizing signal acquisition and noise filtering simultaneously. Using one or more reference coils, adaptive noise cancellation based on LabVIEW to eliminate the correlated noise is available for in situ measurements. The approach was examined through numerical simulation and field measurements. The correlated noise is mitigated effectively and the application of MRS measurements is feasible in high-level noise environment. The method shortens the measurement time and improves the measurement efficiency.

Residual stress measurement of PMMA by combining drilling-hole with digital speckle correlation method

NASA Astrophysics Data System (ADS)

Yao, X. F.; Xiong, T. C.; Xu, H. M.; Wan, J. P.; Long, G. R.

2008-11-01

The residual stresses of the PMMA (polymethyl methacrylate) specimens after being drilled, reamed and polished respectively are investigated using the digital speckle correlation experimental method,. According to the displacement fields around the correlated calculated region, the polynomial curve fitting method is used to obtain the continuous displacement fields, and the strain fields can be obtained from the derivative of the displacement fields. Considering the constitutive equation of the material, the expression of the residual stress can be presented. During the data processing, according to the fitting effect of the data, the calculation region of the correlated speckles and the degree of the polynomial fitting curve is decided. These results show that the maximum stress is at the hole-wall of the drilling hole specimen and with the increasing of the diameter of the drilled hole, the residual stress resulting from the hole drilling increases, whereas the process of reaming and polishing hole can reduce the residual stress. The relative large discrete degree of the residual stress is due to the chip removal ability of the drill bit, the cutting feed of the drill and other various reasons.

Network analysis of a financial market based on genuine correlation and threshold method

NASA Astrophysics Data System (ADS)

Namaki, A.; Shirazi, A. H.; Raei, R.; Jafari, G. R.

2011-10-01

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock network. For a better risk management, we clean the correlation matrix by removing the market mode from data and then construct this matrix based on the residuals. We show that this technique has an important effect on correlation coefficient distribution by applying it for Dow Jones Industrial Average (DJIA). To study the topological structure of a network we apply the removing market mode technique and the threshold method to Tehran Stock Exchange (TSE) as an example. We show that this network follows a power-law model in certain intervals. We also show the behavior of clustering coefficients and component numbers of this network for different thresholds. These outputs are useful for both theoretical and practical purposes such as asset allocation and risk management.

Analyzing Baryon Acoustic Oscillations in Sparse Spectroscopic Samples via Cross-Correlation with Dense Photometry

NASA Astrophysics Data System (ADS)

Patej, Anna; Eisenstein, Daniel J.

2018-04-01

We develop a formalism for measuring the cosmological distance scale from baryon acoustic oscillations (BAO) using the cross-correlation of a sparse redshift survey with a denser photometric sample. This reduces the shot noise that would otherwise affect the auto-correlation of the sparse spectroscopic map. As a proof of principle, we make the first on-sky application of this method to a sparse sample defined as the z > 0.6 tail of the Sloan Digital Sky Survey's (SDSS) BOSS/CMASS sample of galaxies and a dense photometric sample from SDSS DR9. We find a 2.8σ preference for the BAO peak in the cross-correlation at an effective z = 0.64, from which we measure the angular diameter distance DM(z = 0.64) = (2418 ± 73 Mpc)(rs/rs, fid). Accordingly, we expect that using this method to combine sparse spectroscopy with the deep, high quality imaging that is just now becoming available will enable higher precision BAO measurements than possible with the spectroscopy alone.

Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhang, Minjia; Li, Qingchen

2017-04-01

This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

Incoherent coincidence imaging of space objects

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Gu, Guohua

2016-10-01

Incoherent Coincidence Imaging (ICI), which is based on the second or higher order correlation of fluctuating light field, has provided great potentialities with respect to standard conventional imaging. However, the deployment of reference arm limits its practical applications in the detection of space objects. In this article, an optical aperture synthesis with electronically connected single-pixel photo-detectors was proposed to remove the reference arm. The correlation in our proposed method is the second order correlation between the intensity fluctuations observed by any two detectors. With appropriate locations of single-pixel detectors, this second order correlation is simplified to absolute-square Fourier transform of source and the unknown object. We demonstrate the image recovery with the Gerchberg-Saxton-like algorithms and investigate the reconstruction quality of our approach. Numerical experiments has been made to show that both binary and gray-scale objects can be recovered. This proposed method provides an effective approach to promote detection of space objects and perhaps even the exo-planets.

GENETIC AND ENVIRONMENTAL EFFECTS ON BODY MASS INDEX DURING ADOLESCENCE: A PROSPECTIVE STUDY AMONG FINNISH TWINS

PubMed Central

Lajunen, Hanna-Reetta; Kaprio, Jaakko; Keski-Rahkonen, Anna; Rose, Richard J.; Pulkkinen, Lea; Rissanen, Aila; Silventoinen, Karri

2009-01-01

Objective To study genetic and environmental factors affecting body mass index (BMI) and BMI phenotypic correlations across adolescence. Design Prospective, population-based, twin cohort study. Subjects and methods We used twin modeling in 2413 monozygotic and same-sex and opposite-sex dizygotic Finnish twin pairs born in 1983–1987 and assessed by self-report questionnaires at 11–12, 14, and 17 years. Results Heritability of BMI was estimated to be 0.58–0.69 among 11–12- and 14-year-old boys and girls, 0.83 among 17-year-old boys and 0.74 among girls. Common environmental effects shared by siblings were 0.15–0.24 among 11–12- and 14-year-old boys and girls but no longer discernible at 17 y. Unique environmental effects were 0.15–0.23. Additive genetic factors explained 90–96% of the BMI phenotypic correlations across adolescence, whereas unique environmental factors explained the rest. Common environment had no effect on BMI phenotypic correlations. Conclusions The genetic contribution to BMI is strong during adolescence, and it mainly explains BMI phenotypic correlations across adolescence. Common environmental factors have an effect on BMI during early adolescence, but that effect disappears by late adolescence. PMID:19337205

Adaptive Correlation Space Adjusted Open-Loop Tracking Approach for Vehicle Positioning with Global Navigation Satellite System in Urban Areas

PubMed Central

Ruan, Hang; Li, Jian; Zhang, Lei; Long, Teng

2015-01-01

For vehicle positioning with Global Navigation Satellite System (GNSS) in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N0) varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA) is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N0. The novel Equivalent Weighted Pseudo Range Error (EWPRE) is raised to obtain the optimal code search grid sizes for different C/N0. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area. PMID:26343683

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Coarse-Grained Theory of Biological Charge Transfer with Spatially and Temporally Correlated Noise.

PubMed

Liu, Chaoren; Beratan, David N; Zhang, Peng

2016-04-21

System-environment interactions are essential in determining charge-transfer (CT) rates and mechanisms. We developed a computationally accessible method, suitable to simulate CT in flexible molecules (i.e., DNA) with hundreds of sites, where the system-environment interactions are explicitly treated with numerical noise modeling of time-dependent site energies and couplings. The properties of the noise are tunable, providing us a flexible tool to investigate the detailed effects of correlated thermal fluctuations on CT mechanisms. The noise is parametrizable by molecular simulation and quantum calculation results of specific molecular systems, giving us better molecular resolution in simulating the system-environment interactions than sampling fluctuations from generic spectral density functions. The spatially correlated thermal fluctuations among different sites are naturally built-in in our method but are not readily incorporated using approximate spectral densities. Our method has quantitative accuracy in systems with small redox potential differences (

Accurate study on the properties of spectral lines for Br-like W39+

NASA Astrophysics Data System (ADS)

Guo, X. L.; Li, M. C.; Si, R.; He, X. D.; Wang, K.; Dai, Z. T.; Liu, Y. M.; Zhang, H. J.; Chen, C. Y.

2018-01-01

As a primary candidate in tokamak plasmas, the spectroscopic parameters of tungsten ions have been studied extensively over the past decade. In this paper, we perform calculations of excitation energies, lifetimes, wavelengths and transition rates for all levels of the 4{s}24{p}5, 4{s}24{p}44d, and 4s4{p}6 configurations of {{{W}}}39+ by using the multiconfiguration Dirac-Hartree-Fock (MCDHF) method, and also the relativistic many-body perturbation theory (RMBPT) method. Detailed convergence studies on excitation energy from electron-correlation effects and relativistic effects are presented. It is necessary to include the core-valence correlation from deep lying subshells, e.g. 3d and 3p, to produce reliable atomic parameters. Results are compared with available theoretical and experimental work, and the accuracy of the results is confirmed.

Cost-effective method for determining the grindability of ceramics. Final report

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

Guo, C.; Chand, R.H.

1997-02-01

The objective of this program was to develop a cost-effective method to determine the grindability of ceramics leading to cost-effective methods for machining such ceramics. In this first phase of activity, Chand Kare Technical Ceramics directed its efforts towards development of a definition for ceramic grindability, design of grindability-test experiments, and development of a ceramics-grindability test system (CGTS). The grindability study also included the establishment of the correlation between the grindability and conventional grinding practices. The above goals were achieved. A definition based on material removal rate under controlled force grinding was developed. Three prototypes CGTSs were developed and tested;more » suitable design was identified. Based on this, a fully automatic CGTS was developed and is ready for delivery to Oak Ridge National Laboratory. Comprehensive grindability tests for various commercially available engineering ceramics were conducted. Experimental results indicated that ceramics have significantly different grindabilities even though their mechanical properties were not significantly different. This implies that grindability of ceramics can be greatly improved. Further study is needed to establish correlations between microstructure and grindability. Therefore, grindability should be evaluated during the development of new ceramics or improvement of existing ones. In this report, the development of the ceramic-grindability definition, the development of CGTS, extensive grindability results, and the preliminary correlation between grindability and mechanical properties (such as flexural strength, hardness, elastic modulus, and fracture toughness) were summarized.« less

Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively

NASA Astrophysics Data System (ADS)

Fan, Xiaoqian; Yuan, Ying; Zhuang, Xintian; Jin, Xiu

2017-03-01

Taking Baidu Index as a proxy for abnormal investor attention (AIA), the long memory property in the AIA of Shanghai Stock Exchange (SSE) 50 Index component stocks was empirically investigated using detrended fluctuation analysis (DFA) method. The results show that abnormal investor attention is power-law correlated with Hurst exponents between 0.64 and 0.98. Furthermore, the cross-correlations between abnormal investor attention and trading volume, volatility respectively are studied using detrended cross-correlation analysis (DCCA) and the DCCA cross-correlation coefficient (ρDCCA). The results suggest that there are positive correlations between AIA and trading volume, volatility respectively. In addition, the correlations for trading volume are in general higher than the ones for volatility. By carrying on rescaled range analysis (R/S) and rolling windows analysis, we find that the results mentioned above are effective and significant.

Five radiographic methods for assessing skeletal maturity in a Spanish population: is there a correlation?

PubMed

Camacho-Basallo, Paula; Yáñez-Vico, Rosa-María; Solano-Reina, Enrique; Iglesias-Linares, Alejandro

2017-03-01

The need for accurate techniques of estimating age has sharply increased in line with the rise in illegal migration and the political, economic and socio-demographic problems that this poses in developed countries today. The methods routinely employed for determining chronological age are mainly based on determining skeletal maturation using radiological techniques. The objective of this study was to correlate five different methods for assessing skeletal maturation. 606 radiographs of growing patients were analyzed, and each patient was classified according to two cervical vertebral-based methods, two hand-wrist-based methods and one tooth-based method. Spearman's rank-order correlation coefficient was applied to assess the relationship between chronological age and the five methods of assessing maturation, as well as correlations between the five methods (p < 0.05). Spearman's rank correlation coefficients for chronological age and cervical vertebral maturation stage using both methods were 0.656/0.693 (p < 0.001), respectively, for males. For females, the correlation was stronger for both methods. The correlation coefficients for chronological age against the two hand-wrist assessment methods were statistically significant only for Fishman's method, 0.722 (p < 0.001) and 0.839 (p < 0.001), respectively for males and females. The cervical vertebral, hand-wrist and dental maturation methods of assessment were all found to correlate strongly with each other, irrespective of gender, except for Grave and Brown's method. The results found the strongest correlation between the second molars and females, and the second premolar and males. This study sheds light on and correlates with the five radiographic methods most commonly used for assessing skeletal maturation in a Spanish population in southern Europe.

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

PubMed

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Impacting the effect of fMRI noise through hardware and acquisition choices - Implications for controlling false positive rates.

PubMed

Wald, Lawrence L; Polimeni, Jonathan R

2017-07-01

We review the components of time-series noise in fMRI experiments and the effect of image acquisition parameters on the noise. In addition to helping determine the total amount of signal and noise (and thus temporal SNR), the acquisition parameters have been shown to be critical in determining the ratio of thermal to physiological induced noise components in the time series. Although limited attention has been given to this latter metric, we show that it determines the degree of spatial correlations seen in the time-series noise. The spatially correlations of the physiological noise component are well known, but recent studies have shown that they can lead to a higher than expected false-positive rate in cluster-wise inference based on parametric statistical methods used by many researchers. Based on understanding the effect of acquisition parameters on the noise mixture, we propose several acquisition strategies that might be helpful reducing this elevated false-positive rate, such as moving to high spatial resolution or using highly-accelerated acquisitions where thermal sources dominate. We suggest that the spatial noise correlations at the root of the inflated false-positive rate problem can be limited with these strategies, and the well-behaved spatial auto-correlation functions (ACFs) assumed by the conventional statistical methods are retained if the high resolution data is smoothed to conventional resolutions. Copyright © 2017 Elsevier Inc. All rights reserved.

On the estimation of jet-induced fountain lift and additional suckdown in hover for two-jet configurations

NASA Technical Reports Server (NTRS)

Kuhn, Richard E.; Bellavia, David C.; Corsiglia, Victor R.; Wardwell, Douglas A.

1991-01-01

Currently available methods for estimating the net suckdown induced on jet V/STOL aircraft hovering in ground effect are based on a correlation of available force data and are, therefore, limited to configurations similar to those in the data base. Experience with some of these configurations has shown that both the fountain lift and additional suckdown are overestimated but these effects cancel each other for configurations within the data base. For other configurations, these effects may not cancel and the net suckdown could be grossly overestimated or underestimated. Also, present methods do not include the prediction of the pitching moments associated with the suckdown induced in ground effect. An attempt to develop a more logically based method for estimating the fountain lift and suckdown based on the jet-induced pressures is initiated. The analysis is based primarily on the data from a related family of three two-jet configurations (all using the same jet spacing) and limited data from two other two-jet configurations. The current status of the method, which includes expressions for estimating the maximum pressure induced in the fountain regions, and the sizes of the fountain and suckdown regions is presented. Correlating factors are developed to be used with these areas and pressures to estimate the fountain lift, the suckdown, and the related pitching moment increments.

Wavelet filter analysis of local atmospheric pressure effects in the long-period tidal bands

NASA Astrophysics Data System (ADS)

Hu, X.-G.; Liu, L. T.; Ducarme, B.; Hsu, H. T.; Sun, H.-P.

2006-11-01

It is well known that local atmospheric pressure variations obviously affect the observation of short-period Earth tides, such as diurnal tides, semi-diurnal tides and ter-diurnal tides, but local atmospheric pressure effects on the long-period Earth tides have not been studied in detail. This is because the local atmospheric pressure is believed not to be sufficient for an effective pressure correction in long-period tidal bands, and there are no efficient methods to investigate local atmospheric effects in these bands. The usual tidal analysis software package, such as ETERNA, Baytap-G and VAV, cannot provide detailed pressure admittances for long-period tidal bands. We propose a wavelet method to investigate local atmospheric effects on gravity variations in long-period tidal bands. This method constructs efficient orthogonal filter bank with Daubechies wavelets of high vanishing moments. The main advantage of the wavelet filter bank is that it has excellent low frequency response and efficiently suppresses instrumental drift of superconducting gravimeters (SGs) without using any mathematical model. Applying the wavelet method to the 13-year continuous gravity observations from SG T003 in Brussels, Belgium, we filtered 12 long-period tidal groups into eight narrow frequency bands. Wavelet method demonstrates that local atmospheric pressure fluctuations are highly correlated with the noise of SG measurements in the period band 4-40 days with correlation coefficients higher than 0.95 and local atmospheric pressure variations are the main error source for the determination of the tidal parameters in these bands. We show the significant improvement of long-period tidal parameters provided by wavelet method in term of precision.

Carbon isotope ratios and isotopic correlations between components in fruit juices

NASA Astrophysics Data System (ADS)

Wierzchnicki, Ryszard

2013-04-01

Nowadays food products are defined by geographical origin, method of production and by some regulations concerning terms of their authenticity. Important data for confirm the authenticity of product are providing by isotopic methods of food control. The method checks crucial criteria which characterize the authenticity of inspected product. The European Union Regulations clearly show the tendency for application of the isotopic methods for food authenticity control (wine, honey, juice). The aim of the legislation steps is the protection of European market from possibility of the commercial frauds. Method of isotope ratio mass spectrometry is very effective tool for the use distinguishably the food products of various geographical origin. The basic problem for identification of the sample origin is the lack of databases of isotopic composition of components and information about the correlations of the data. The subject of the work was study the isotopic correlations existing between components of fruits. The chemical and instrumental methods of separation: water, sugars, organic acids and pulp from fruit were implemented. IRMS technique was used to measure isotopic composition of samples. The final results for original samples of fruits (apple, strawberry etc.) will be presented and discussed. Acknowledgement: This work was supported by the Polish Ministry of Science and Higher Education under grant NR12-0043-10/2010.

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

PubMed

Lu, H Peter

2011-04-21

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

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.

Respiratory-phase domain analysis of heart rate variability can accurately estimate cardiac vagal activity during a mental arithmetic task.

PubMed

Kotani, Kiyoshi; Takamasu, Kiyoshi; Tachibana, Makoto

2007-01-01

The objectives of this paper were to present a method to extract the amplitude of RSA in the respiratory-phase domain, to compare that with subjective or objective indices of the MWL (mental workload), and to compare that with a conventional frequency analysis in terms of its accuracy during a mental arithmetic task. HRV (heart rate variability), ILV (instantaneous lung volume), and motion of the throat were measured under a mental arithmetic experiment and subjective and objective indices were also obtained. The amplitude of RSA was extracted in the respiratory-phase domain, and its correlation with the load level was compared with the results of the frequency domain analysis, which is the standard analysis of the HRV. The subjective and objective indices decreased as the load level increased, showing that the experimental protocol was appropriate. Then, the amplitude of RSA in the respiratory-phase domain also decreased with the increase in the load level. The results of the correlation analysis showed that the respiratory-phase domain analysis has higher negative correlations, -0.84 and -0.82, with the load level as determined by simple correlation and rank correlation, respectively, than does frequency analysis, for which the correlations were found to be -0.54 and -0.63, respectively. In addition, it was demonstrated that the proposed method could be applied to the short-term extraction of RSA amplitude. We proposed a simple and effective method to extract the amplitude of the respiratory sinus arrhythmia (RSA) in the respiratory-phase domain and the results show that this method can estimate cardiac vagal activity more accurately than frequency analysis.

An adiabatic linearized path integral approach for quantum time-correlation functions II: a cumulant expansion method for improving convergence.

PubMed

Causo, Maria Serena; Ciccotti, Giovanni; Bonella, Sara; Vuilleumier, Rodolphe

2006-08-17

Linearized mixed quantum-classical simulations are a promising approach for calculating time-correlation functions. At the moment, however, they suffer from some numerical problems that may compromise their efficiency and reliability in applications to realistic condensed-phase systems. In this paper, we present a method that improves upon the convergence properties of the standard algorithm for linearized calculations by implementing a cumulant expansion of the relevant averages. The effectiveness of the new approach is tested by applying it to the challenging computation of the diffusion of an excess electron in a metal-molten salt solution.

Ab initio approaches for the determination of heavy element energetics: Ionization energies of trivalent lanthanides (Ln = La-Eu)

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

Peterson, Charles; Penchoff, Deborah A.; Wilson, Angela K., E-mail: wilson@chemistry.msu.edu

2015-11-21

An effective approach for the determination of lanthanide energetics, as demonstrated by application to the third ionization energy (in the gas phase) for the first half of the lanthanide series, has been developed. This approach uses a combination of highly correlated and fully relativistic ab initio methods to accurately describe the electronic structure of heavy elements. Both scalar and fully relativistic methods are used to achieve an approach that is both computationally feasible and accurate. The impact of basis set choice and the number of electrons included in the correlation space has also been examined.

The Eysenckian personality factors and their correlations with academic performance.

PubMed

Poropat, Arthur E

2011-03-01

BACKGROUND. The relationship between personality and academic performance has long been explored, and a recent meta-analysis established that measures of the five-factor model (FFM) dimension of Conscientiousness have similar validity to intelligence measures. Although currently dominant, the FFM is only one of the currently accepted models of personality, and has limited theoretical support. In contrast, the Eysenckian personality model was developed to assess a specific theoretical model and is still commonly used in educational settings and research. AIMS. This meta-analysis assessed the validity of the Eysenckian personality measures for predicting academic performance. SAMPLE. Statistics were obtained for correlations with Psychoticism, Extraversion, and Neuroticism (20-23 samples; N from 8,013 to 9,191), with smaller aggregates for the Lie scale (7 samples; N= 3,910). METHODS. The Hunter-Schmidt random effects method was used to estimate population correlations between the Eysenckian personality measures and academic performance. Moderating effects were tested using weighted least squares regression. RESULTS. Significant but modest validities were reported for each scale. Neuroticism and Extraversion had relationships with academic performance that were consistent with previous findings, while Psychoticism appears to be linked to academic performance because of its association with FFM Conscientiousness. Age and educational level moderated correlations with Neuroticism and Extraversion, and gender had no moderating effect. Correlations varied significantly based on the measurement instrument used. CONCLUSIONS. The Eysenckian scales do not add to the prediction of academic performance beyond that provided by FFM scales. Several measurement problems afflict the Eysenckian scales, including low to poor internal reliability and complex factor structures. In particular, the measurement and validity problems of Psychoticism mean its continued use in academic settings is unjustified. © 2010 The Author. British Journal of Educational Psychology. © 2010 The British Psychological Society.

Electron correlation and the self-interaction error of density functional theory

NASA Astrophysics Data System (ADS)

Polo, Victor; Kraka, Elfi; Cremer, Dieter

The self-interaction error (SIE) of commonly used DFT functionals has been systematically investigated by comparing the electron density distribution ρ( r ) generated by self-interaction corrected DFT (SIC-DFT) with a series of reference densities obtained by DFT or wavefunction theory (WFT) methods that cover typical electron correlation effects. Although the SIE of GGA functionals is considerably smaller than that of LDA functionals, it has significant consequences for the coverage of electron correlation effects at the DFT level of theory. The exchange SIE mimics long range (non-dynamic) pair correlation effects, and is responsible for the fact that the electron density of DFT exchange-only calculations resembles often that of MP4, MP2 or even CCSD(T) calculations. Changes in the electron density caused by SICDFT exchange are comparable with those that are associated with HF exchange. Correlation functionals contract the density towards the bond and the valence region, thus taking negative charge out of the van der Waals region where these effects are exaggerated by the influence of the SIE of the correlation functional. Hence, SIC-DFT leads in total to a relatively strong redistribution of negative charge from van der Waals, non-bonding, and valence regions of heavy atoms to the bond regions. These changes, although much stronger, resemble those obtained when comparing the densities of hybrid functionals such as B3LYP with the corresponding GGA functional BLYP. Hence, the balanced mixing of local and non-local exchange and correlation effects as it is achieved by hybrid functionals mimics SIC-DFT and can be considered as an economic way to include some SIC into standard DFT. However, the investigation shows also that the SIC-DFT description of molecules is unreliable because the standard functionals used were optimized for DFT including the SIE.

Translation and validation of the Rhinosinusitis Disability Index for use in Nigeria.

PubMed

Asoegwu, C N; Nwawolo, C C; Okubadejo, N U

2017-07-01

The Rhinosinusitis Disability Index (RSDI) is a validated and reliable measure of severity of chronic rhinosinusitis. The objective of this study was to translate and validate the instrument for use in Nigeria. This is a methodological study. 71 patients with chronic rhinosinusitis attending two Otolaryngology clinics in Lagos, Nigeria. Using standardized methods and trained translators, the RSDI was translated to vernacular (Yoruba language) and back-translated to culturally appropriate English. Data analysis comprised of assessment of the item quality, content validity and internal consistency of the back-translated Rhinosinusitis Disability Index (bRSDI), and correlation to the original RSDI. Content validity (floor and ceiling effects) showed 0% floor and ceiling effects for the total scores, 0% ceiling effects for all domains and floor effect for physical domain, and 9.9 and 8.5% floor effects for functional and emotional domains, respectively. The mean item-own correlation for physical domain was 0.54 ± 0.08, 0.72 ± 0.08 for functional domain and 0.74 ± 0.07 for emotional domain. All domain item-own correlations were higher than item-other domain correlations. The total Cronbach's alpha was 0.936 and was higher than 0.70 for all the domains representing good internal consistency. Pearson correlation analysis showed strong correlation of RSDI to bRSDI (total score 0.881; p = 0.000, and domain subscores-physical: 0.788; p = 0.000, functional: 0.830; p = 0.000, and emotional: 0.888; p = 0.000). The back-translated Rhinosinusitis Disability Index shows good face and content validity with good internal consistency while correlating linearly and significantly with the original Rhinosinusitis Disability Index and is recommended for use in Nigeria.

Bioactive Compounds in Potato Tubers: Effects of Farming System, Cooking Method, and Flesh Color

PubMed Central

Czerko, Zbigniew; Zarzyńska, Krystyna; Borowska-Komenda, Monika

2016-01-01

We investigated the effect of cultivation system (conventional or organic), cooking method, and flesh color on the contents of ascorbic acid (AA) and total phenolics (TPs), and on total antioxidant activity (Trolox equivalents, TE) in Solanum tuberosum (potato) tubers. The research material, consisting of 4 potato cultivars, was grown in experimental fields, using organic and conventional systems, at the experimental station in 2012 and 2013. The analysis showed that organically grown potatoes with creamy, light yellow, and yellow flesh had significantly higher TPs than did potatoes grown conventionally. Flesh color and cooking method also affected AA. The greatest losses of AA occurred in yellow-fleshed potatoes grown conventionally and cooked in the microwave; such losses were not observed in potatoes grown organically. A dry cooking method (baking in a microwave) increased the TP contents in potatoes by about 30%, regardless of the flesh color and the production system. TE was significantly higher in organically grown potatoes (raw and cooked in a steamer) than in conventionally grown potatoes. TE and AA contents showed a significant positive correlation, but only in potatoes from the organic system [R2 = 0.686]. By contrast, the positive correlation between TE and TPs was observed regardless of the production system. Therefore, we have identified the effects of farming system, cooking method, and flesh color on the contents of bioactive compounds in potato tubers. PMID:27139188

Comparison of methods to evaluate the fungal biomass in heating, ventilation, and air-conditioning (HVAC) dust.

PubMed

Biyeyeme Bi Mve, Marie-Jeanne; Cloutier, Yves; Lacombe, Nancy; Lavoie, Jacques; Debia, Maximilien; Marchand, Geneviève

2016-12-01

Heating, ventilation, and air-conditioning (HVAC) systems contain dust that can be contaminated with fungal spores (molds), which may have harmful effects on the respiratory health of the occupants of a building. HVAC cleaning is often based on visual inspection of the quantity of dust, without taking the mold content into account. The purpose of this study is to propose a method to estimate fungal contamination of dust in HVAC systems. Comparisons of different analytical methods were carried out on dust deposited in a controlled-atmosphere exposure chamber. Sixty samples were analyzed using four methods: culture, direct microscopic spore count (DMSC), β-N-acetylhexosaminidase (NAHA) dosing and qPCR. For each method, the limit of detection, replicability, and repeatability were assessed. The Pearson correlation coefficients between the methods were also evaluated. Depending on the analytical method, mean spore concentrations per 100 cm 2 of dust ranged from 10,000 to 682,000. Limits of detection varied from 120 to 217,000 spores/100 cm 2 . Replicability and repeatability were between 1 and 15%. Pearson correlation coefficients varied from -0.217 to 0.83. The 18S qPCR showed the best sensitivity and precision, as well as the best correlation with the culture method. PCR targets only molds, and a total count of fungal DNA is obtained. Among the methods, mold DNA amplification by qPCR is the method suggested for estimating the fungal content found in dust of HVAC systems.

[The correlation between the levels of cortisol and free radical oxidation in patients with heroin addiction depending on gender differences].

PubMed

Shatyrko, M A; Isarovskyi, B V; Golodnii, S V; Kozochkin, D A; Tseilikman, V E

2015-01-01

To evaluate gender effects on the correlation between cortisol, molecular products of lipid peroxidation (LPO) and carbonylation of proteins in patients with heroin addiction. Authors examined 82 patients, 49 men and 33 women, with heroin addiction. Biochemical and statistical methods were used. Gender differences in the carbonylation of proteins were noted. In men, but not in women, the low level of cortisol was associated with an increased content of carbonylated proteins. In women the level of these proteins was lower than in men. Gender did not exert an effect on LPO.

Modeling Bose-Einstein correlations via elementary emitting cells

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

Utyuzh, Oleg; Wilk, Grzegorz; Wlodarczyk, Zbigniew

2007-04-01

We propose a method of numerical modeling Bose-Einstein correlations by using the notion of the elementary emitting cell (EEC). They are intermediary objects containing identical bosons and are supposed to be produced independently during the hadronization process. Only bosons in the EEC, which represents a single quantum state here, are subjected to the effects of Bose-Einstein (BE) statistics, which forces them to follow a geometrical distribution. There are no such effects between particles from different EECs. We illustrate our proposition by calculating a representative number of typical distributions and discussing their sensitivity to EECs and their characteristics.

Quantum Impurity Models as Reference Systems for Strongly Correlated Materials: The Road from the Kondo Impurity Model to First Principles Electronic Structure Calculations with Dynamical Mean-Field Theory

NASA Astrophysics Data System (ADS)

Kotliar, Gabriel

2005-01-01

Dynamical mean field theory (DMFT) relates extended systems (bulk solids, surfaces and interfaces) to quantum impurity models (QIM) satisfying a self-consistency condition. This mapping provides an economic description of correlated electron materials. It is currently used in practical computations of physical properties of real materials. It has also great conceptual value, providing a simple picture of correlated electron phenomena on the lattice, using concepts derived from quantum impurity models such as the Kondo effect. DMFT can also be formulated as a first principles electronic structure method and is applicable to correlated materials.

The self-trapping transition in the non-half-filled strongly correlated extended Holstein-Hubbard model in two-dimensions

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

Sankar, I. V., E-mail: ivshankar27@gmail.com; Chatterjee, Ashok, E-mail: ivshankar27@gmail.com

2014-04-24

The two-dimensional extended Holstein-Hubbard model (EHH) has been considered at strong correlation regime in the non-half-filled band case to understand the self-trapping transition of electrons in strongly correlated electron system. We have used the method of optimized canonical transformations to transform an EHH model into an effective extended Hubbard (EEH) model. In the strong on-site correlation limit an EH model can be transformed into a t-J model which is finally solved using Hartree-Fock approximation (HFA). We found that, for non-half-filled band case, the transition is abrupt in the adiabatic region whereas it is continuous in the anti-adiabatic region.

Oxidation stability of biodiesel fuels and blends using the Rancimat and PetroOXY methods. Effect of 4-allyl-2,6-dimetoxiphenol and cathecol as biodiesel additives on oxidation stability

NASA Astrophysics Data System (ADS)

Botella, Lucía; Bimbela, Fernando; Martín, Lorena; Arauzo, Jesús; Sanchez, Jose Luis

2014-07-01

In the present work, several fatty acid methyl esters (FAME) have been synthesized from various fatty acid feedstocks: used frying olive oil, pork fat, soybean, rapeseed, sunflower and coconut. The oxidation stabilities of the biodiesel samples and of several blends have been measured simultaneously by both the Rancimat method, accepted by EN14112 standard, and the PetroOXY method, prEN16091 standard, with the aim of finding a correlation between both methodologies. Other biodiesel properties such as composition, cold filter plugging point (CFPP), flash point (FP) and kinematic viscosity have also been analyzed using standard methods in order to further characterize the biodiesel produced. In addition, the effect on the biodiesel properties of using 4-allyl-2,6-dimetoxiphenol and cathecol as additives in biodiesel blends with rapeseed and with soybean has also been analyzed. The use of both antioxidants results in a considerable improvement in the oxidation stability of both types of biodiesel, especially using cathecol. Adding cathecol loads as low as 0.05 % (m/m) in blends with soybean biodiesel and as low as 0.10 % (m/m) in blends with rapeseed biodiesel is sufficient for the oxidation stabilities to comply with the restrictions established by the European EN14214 standard.An empirical linear equation is proposed to correlate the oxidation stability by the two methods, PetroOXY and Rancimat. It has been found that the presence of either cathecol or 4-allyl-2,6-dimetoxiphenol as additives affects the correlation observed.

A new adaptive estimation method of spacecraft thermal mathematical model with an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Akita, T.; Takaki, R.; Shima, E.

2012-04-01

An adaptive estimation method of spacecraft thermal mathematical model is presented. The method is based on the ensemble Kalman filter, which can effectively handle the nonlinearities contained in the thermal model. The state space equations of the thermal mathematical model is derived, where both temperature and uncertain thermal characteristic parameters are considered as the state variables. In the method, the thermal characteristic parameters are automatically estimated as the outputs of the filtered state variables, whereas, in the usual thermal model correlation, they are manually identified by experienced engineers using trial-and-error approach. A numerical experiment of a simple small satellite is provided to verify the effectiveness of the presented method.

Investigation of Portevin-Le Chatelier effect in 5456 Al-based alloy using digital image correlation

NASA Astrophysics Data System (ADS)

Cheng, Teng; Xu, Xiaohai; Cai, Yulong; Fu, Shihua; Gao, Yue; Su, Yong; Zhang, Yong; Zhang, Qingchuan

2015-02-01

A variety of experimental methods have been proposed for Portevin-Le Chatelier (PLC) effect. They mainly focused on the in-plane deformation. In order to achieve the high-accuracy measurement, three-dimensional digital image correlation (3D-DIC) was employed in this work to investigate the PLC effect in 5456 Al-based alloy. The temporal and spatial evolutions of deformation in the full field of specimen surface were observed. The large deformation of localized necking was determined experimentally. The distributions of out-of-plane displacement over the loading procedure were also obtained. Furthermore, a comparison of measurement accuracy between two-dimensional digital image correlation (2D-DIC) and 3D-DIC was also performed. Due to the theoretical restriction, the measurement accuracy of 2D-DIC decreases with the increase of deformation. A maximum discrepancy of about 20% with 3D-DIC was observed in this work. Therefore, 3D-DIC is actually more essential for the high-accuracy investigation of PLC effect.

Refraction error correction for deformation measurement by digital image correlation at elevated temperature

NASA Astrophysics Data System (ADS)

Su, Yunquan; Yao, Xuefeng; Wang, Shen; Ma, Yinji

2017-03-01

An effective correction model is proposed to eliminate the refraction error effect caused by an optical window of a furnace in digital image correlation (DIC) deformation measurement under high-temperature environment. First, a theoretical correction model with the corresponding error correction factor is established to eliminate the refraction error induced by double-deck optical glass in DIC deformation measurement. Second, a high-temperature DIC experiment using a chromium-nickel austenite stainless steel specimen is performed to verify the effectiveness of the correction model by the correlation calculation results under two different conditions (with and without the optical glass). Finally, both the full-field and the divisional displacement results with refraction influence are corrected by the theoretical model and then compared to the displacement results extracted from the images without refraction influence. The experimental results demonstrate that the proposed theoretical correction model can effectively improve the measurement accuracy of DIC method by decreasing the refraction errors from measured full-field displacements under high-temperature environment.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

PubMed

Wu, Lin; Wang, Yang; Pan, Shirui

2017-12-01

It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

PubMed

Ma, Chuang; Wang, Xiangfeng

2012-09-01

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

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

PubMed Central

Ma, Chuang; Wang, Xiangfeng

2012-01-01

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

Algorithmic implementation of particle-particle ladder diagram approximation to study strongly-correlated metals and semiconductors

NASA Astrophysics Data System (ADS)

Prayogi, A.; Majidi, M. A.

2017-07-01

In condensed-matter physics, strongly-correlated systems refer to materials that exhibit variety of fascinating properties and ordered phases, depending on temperature, doping, and other factors. Such unique properties most notably arise due to strong electron-electron interactions, and in some cases due to interactions involving other quasiparticles as well. Electronic correlation effects are non-trivial that one may need a sufficiently accurate approximation technique with quite heavy computation, such as Quantum Monte-Carlo, in order to capture particular material properties arising from such effects. Meanwhile, less accurate techniques may come with lower numerical cost, but the ability to capture particular properties may highly depend on the choice of approximation. Among the many-body techniques derivable from Feynman diagrams, we aim to formulate algorithmic implementation of the Ladder Diagram approximation to capture the effects of electron-electron interactions. We wish to investigate how these correlation effects influence the temperature-dependent properties of strongly-correlated metals and semiconductors. As we are interested to study the temperature-dependent properties of the system, the Ladder diagram method needs to be applied in Matsubara frequency domain to obtain the self-consistent self-energy. However, at the end we would also need to compute the dynamical properties like density of states (DOS) and optical conductivity that are defined in the real frequency domain. For this purpose, we need to perform the analytic continuation procedure. At the end of this study, we will test the technique by observing the occurrence of metal-insulator transition in strongly-correlated metals, and renormalization of the band gap in strongly-correlated semiconductors.

Event-shape-engineering study of charge separation in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Wen, Fufang; Bryon, Jacob; Wen, Liwen; Wang, Gang

2018-01-01

Recent measurements of charge-dependent azimuthal correlations in high-energy heavy-ion collisions have indicated charge-separation signals perpendicular to the reaction plane, and have been related to the chiral magnetic effect (CME). However, the correlation signal is contaminated with the background caused by the collective motion (flow) of the collision system, and an effective approach is needed to remove the flow background from the correlation. We present a method study with simplified Monte Carlo simulations and a multi-phase transport model, and develop a scheme to reveal the true CME signal via event-shape engineering with the flow vector of the particles of interest. Supported by a grant (DE-FG02-88ER40424) from U.S. Department of Energy, Office of Nuclear Physics

A semiconductor photon-sorter

NASA Astrophysics Data System (ADS)

Bennett, A. J.; Lee, J. P.; Ellis, D. J. P.; Farrer, I.; Ritchie, D. A.; Shields, A. J.

2016-10-01

Obtaining substantial nonlinear effects at the single-photon level is a considerable challenge that holds great potential for quantum optical measurements and information processing. Of the progress that has been made in recent years one of the most promising methods is to scatter coherent light from quantum emitters, imprinting quantum correlations onto the photons. We report effective interactions between photons, controlled by a single semiconductor quantum dot that is weakly coupled to a monolithic cavity. We show that the nonlinearity of a transition modifies the counting statistics of a Poissonian beam, sorting the photons in number. This is used to create strong correlations between detection events and to create polarization-correlated photons from an uncorrelated stream using a single spin. These results pave the way for semiconductor optical switches operated by single quanta of light.

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.

Tuning time-frequency methods for the detection of metered HF speech

NASA Astrophysics Data System (ADS)

Nelson, Douglas J.; Smith, Lawrence H.

2002-12-01

Speech is metered if the stresses occur at a nearly regular rate. Metered speech is common in poetry, and it can occur naturally in speech, if the speaker is spelling a word or reciting words or numbers from a list. In radio communications, the CQ request, call sign and other codes are frequently metered. In tactical communications and air traffic control, location, heading and identification codes may be metered. Moreover metering may be expected to survive even in HF communications, which are corrupted by noise, interference and mistuning. For this environment, speech recognition and conventional machine-based methods are not effective. We describe Time-Frequency methods which have been adapted successfully to the problem of mitigation of HF signal conditions and detection of metered speech. These methods are based on modeled time and frequency correlation properties of nearly harmonic functions. We derive these properties and demonstrate a performance gain over conventional correlation and spectral methods. Finally, in addressing the problem of HF single sideband (SSB) communications, the problems of carrier mistuning, interfering signals, such as manual Morse, and fast automatic gain control (AGC) must be addressed. We demonstrate simple methods which may be used to blindly mitigate mistuning and narrowband interference, and effectively invert the fast automatic gain function.

Quantitative analysis of tympanic membrane perforation: a simple and reliable method.

PubMed

Ibekwe, T S; Adeosun, A A; Nwaorgu, O G

2009-01-01

Accurate assessment of the features of tympanic membrane perforation, especially size, site, duration and aetiology, is important, as it enables optimum management. To describe a simple, cheap and effective method of quantitatively analysing tympanic membrane perforations. The system described comprises a video-otoscope (capable of generating still and video images of the tympanic membrane), adapted via a universal serial bus box to a computer screen, with images analysed using the Image J geometrical analysis software package. The reproducibility of results and their correlation with conventional otoscopic methods of estimation were tested statistically with the paired t-test and correlational tests, using the Statistical Package for the Social Sciences version 11 software. The following equation was generated: P/T x 100 per cent = percentage perforation, where P is the area (in pixels2) of the tympanic membrane perforation and T is the total area (in pixels2) for the entire tympanic membrane (including the perforation). Illustrations are shown. Comparison of blinded data on tympanic membrane perforation area obtained independently from assessments by two trained otologists, of comparative years of experience, using the video-otoscopy system described, showed similar findings, with strong correlations devoid of inter-observer error (p = 0.000, r = 1). Comparison with conventional otoscopic assessment also indicated significant correlation, comparing results for two trained otologists, but some inter-observer variation was present (p = 0.000, r = 0.896). Correlation between the two methods for each of the otologists was also highly significant (p = 0.000). A computer-adapted video-otoscope, with images analysed by Image J software, represents a cheap, reliable, technology-driven, clinical method of quantitative analysis of tympanic membrane perforations and injuries.

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparison of two dietary assessment methods by food consumption: results of the German National Nutrition Survey II.

PubMed

Eisinger-Watzl, Marianne; Straßburg, Andrea; Ramünke, Josa; Krems, Carolin; Heuer, Thorsten; Hoffmann, Ingrid

2015-04-01

To further characterise the performance of the diet history method and the 24-h recalls method, both in an updated version, a comparison was conducted. The National Nutrition Survey II, representative for Germany, assessed food consumption with both methods. The comparison was conducted in a sample of 9,968 participants aged 14-80. Besides calculating mean differences, statistical agreement measurements encompass Spearman and intraclass correlation coefficients, ranking participants in quartiles and the Bland-Altman method. Mean consumption of 12 out of 18 food groups was higher assessed with the diet history method. Three of these 12 food groups had a medium to large effect size (e.g., raw vegetables) and seven showed at least a small strength while there was basically no difference for coffee/tea or ice cream. Intraclass correlations were strong only for beverages (>0.50) and revealed the least correlation for vegetables (<0.20). Quartile classification of participants exhibited more than two-thirds being ranked in the same or adjacent quartile assessed by both methods. For every food group, Bland-Altman plots showed that the agreement of both methods weakened with increasing consumption. The cognitive effort essential for the diet history method to remember consumption of the past 4 weeks may be a source of inaccurateness, especially for inhomogeneous food groups. Additionally, social desirability gains significance. There is no assessment method without errors and attention to specific food groups is a critical issue with every method. Altogether, the 24-h recalls method applied in the presented study, offers advantages approximating food consumption as compared to the diet history method.

The Use of Time Series Analysis and t Tests with Serially Correlated Data Tests.

ERIC Educational Resources Information Center

Nicolich, Mark J.; Weinstein, Carol S.

1981-01-01

Results of three methods of analysis applied to simulated autocorrelated data sets with an intervention point (varying in autocorrelation degree, variance of error term, and magnitude of intervention effect) are compared and presented. The three methods are: t tests; maximum likelihood Box-Jenkins (ARIMA); and Bayesian Box Jenkins. (Author/AEF)

Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator); Haas, R. H.; Deering, D. W.; Schell, J. A.; Harlan, J. C.

1974-01-01

The author has identified the following significant results. The Great Plains Corridor rangeland project successfully utilized natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. An effective method was developed for quantitative measurement of vegetation conditions, including green biomass estimates, recorded in bands 5 and 6, corrected for sun angle, were used to compute a ratio parameter (TV16) which is shown to be highly correlated with green biomass and vegatation moisture content. Analyses results of ERTS-1 digital data and correlated ground data are summarized. Attention was given to analyzing weather influences and test site variables on vegetation condition measurements with ERTS-1 data.

Uncovering underlying processes of semantic priming by correlating item-level effects.

PubMed

Heyman, Tom; Hutchison, Keith A; Storms, Gert

2016-04-01

The current study examines the underlying processes of semantic priming using the largest priming database available (i.e., Semantic Priming Project, Hutchison et al. Behavior Research Methods, 45(4), 1099-1114, 2013). Specifically, it compares priming effects in two tasks: lexical decision and pronunciation. Task similarities were assessed at two different stimulus onset asynchronies (SOAs) (i.e., 200 and 1,200 ms) and for both primary and other associates. To evaluate how consistent priming is across these two tasks, item-level priming effects obtained in each task were correlated for each condition separately. The results revealed significant correlations at the short SOA for both primary and other associates. The correlations at the long SOA were significantly smaller and only reached significance when z-transformed response times were used. Furthermore, this pattern remained essentially the same when only asymmetric forward associates (e.g., panda-bear) were considered, suggesting that the cross-task stability at the short SOA was not merely caused by retrospective processes such as semantic matching. Instead, these findings provide evidence for a rapidly operating, item-based, relational characteristic such as spreading activation.

Motion tracking in MR-guided liver therapy by using navigator echoes and projection profile matching.

PubMed

Tokuda, Junichi; Morikawa, Shigehiro; Dohi, Takeyoshi; Hata, Nobuhiko

2004-01-01

Image registration in magnetic resonance (MR) image-guided liver therapy enhances surgical guidance by fusing preoperative multimodality images with intraoperative images, or by fusing intramodality images to correlate serial intraoperative images to monitor the effect of therapy. The objective of this paper is to describe the application of navigator echo and projection profile matching to fast two-dimensional image registration for MR-guided liver therapy. We obtain navigator echoes along the read-out and phase-encoding directions by using modified gradient echo imaging. This registration is made possible by masking out the liver profile from the image and performing profile matching with cross-correlation or mutual information as similarity measures. The set of experiments include a phantom study with a 2.0-T experimental MR scanner, and a volunteer and a clinical study with a 0.5-T open-configuration MR scanner, and these evaluate the accuracy and effectiveness of this method for liver therapy. Both the phantom and volunteer study indicate that this method can perform registration in 34 ms with root-mean-square error of 1.6 mm when the given misalignment of a liver is 30 mm. The clinical studies demonstrate that the method can track liver motion of up to approximately 40 mm. Matching profiles with cross-correlation information perform better than with mutual information in terms of robustness and speed. The proposed image registration method has potential clinical impact on and advantages for MR-guided liver therapy.

Cross-correlation least-squares reverse time migration in the pseudo-time domain

NASA Astrophysics Data System (ADS)

Li, Qingyang; Huang, Jianping; Li, Zhenchun

2017-08-01

The least-squares reverse time migration (LSRTM) method with higher image resolution and amplitude is becoming increasingly popular. However, the LSRTM is not widely used in field land data processing because of its sensitivity to the initial migration velocity model, large computational cost and mismatch of amplitudes between the synthetic and observed data. To overcome the shortcomings of the conventional LSRTM, we propose a cross-correlation least-squares reverse time migration algorithm in pseudo-time domain (PTCLSRTM). Our algorithm not only reduces the depth/velocity ambiguities, but also reduces the effect of velocity error on the imaging results. It relieves the accuracy requirements on the migration velocity model of least-squares migration (LSM). The pseudo-time domain algorithm eliminates the irregular wavelength sampling in the vertical direction, thus it can reduce the vertical grid points and memory requirements used during computation, which makes our method more computationally efficient than the standard implementation. Besides, for field data applications, matching the recorded amplitudes is a very difficult task because of the viscoelastic nature of the Earth and inaccuracies in the estimation of the source wavelet. To relax the requirement for strong amplitude matching of LSM, we extend the normalized cross-correlation objective function to the pseudo-time domain. Our method is only sensitive to the similarity between the predicted and the observed data. Numerical tests on synthetic and land field data confirm the effectiveness of our method and its adaptability for complex models.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

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

Parametric analysis for matched pair survival data.

PubMed

Manatunga, A K; Oakes, D

1999-12-01

Hougaard's (1986) bivariate Weibull distribution with positive stable frailties is applied to matched pairs survival data when either or both components of the pair may be censored and covariate vectors may be of arbitrary fixed length. When there is no censoring, we quantify the corresponding gain in Fisher information over a fixed-effects analysis. With the appropriate parameterization, the results take a simple algebraic form. An alternative marginal ("independence working model") approach to estimation is also considered. This method ignores the correlation between the two survival times in the derivation of the estimator, but provides a valid estimate of standard error. It is shown that when both the correlation between the two survival times is high, and the ratio of the within-pair variability to the between-pair variability of the covariates is high, the fixed-effects analysis captures most of the information about the regression coefficient but the independence working model does badly. When the correlation is low, and/or most of the variability of the covariates occurs between pairs, the reverse is true. The random effects model is applied to data on skin grafts, and on loss of visual acuity among diabetics. In conclusion some extensions of the methods are indicated and they are placed in a wider context of Generalized Estimation Equation methodology.

[Application of numerical convolution in in vivo/in vitro correlation research].

PubMed

Yue, Peng

2009-01-01

This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.