On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

A density difference based analysis of orbital-dependent exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Grabowski, Ireneusz; Teale, Andrew M.; Fabiano, Eduardo; Śmiga, Szymon; Buksztel, Adam; Della Sala, Fabio

2014-03-01

We present a density difference based analysis for a range of orbital-dependent Kohn-Sham functionals. Results for atoms, some members of the neon isoelectronic series and small molecules are reported and compared with ab initio wave function calculations. Particular attention is paid to the quality of approximations to the exchange-only optimised effective potential (OEP) approach: we consider both the localised Hartree-Fock as well as the Krieger-Li-Iafrate methods. Analysis of density differences at the exchange-only level reveals the impact of the approximations on the resulting electronic densities. These differences are further quantified in terms of the ground state energies, frontier orbital energy differences and highest occupied orbital energies obtained. At the correlated level, an OEP approach based on a perturbative second-order correlation energy expression is shown to deliver results comparable with those from traditional wave function approaches, making it suitable for use as a benchmark against which to compare standard density functional approximations.

The impact of tics, obsessive-compulsive symptoms, and impulsivity on global functioning in Tourette syndrome.

PubMed

Kano, Yukiko; Kono, Toshiaki; Matsuda, Natsumi; Nonaka, Maiko; Kuwabara, Hitoshi; Shimada, Takafumi; Shishikura, Kurie; Konno, Chizue; Ohta, Masataka

2015-03-30

This study investigated the relationships between tics, obsessive-compulsive symptoms (OCS), and impulsivity, and their effects on global functioning in Japanese patients with Tourette syndrome (TS), using the dimensional approach for OCS. Fifty-three TS patients were assessed using the Yale Global Tic Severity Scale, the Dimensional Yale-Brown Obsessive-Compulsive Scale, the Impulsivity Rating Scale, and the Global Assessment of Functioning Scale. Although tic severity scores were significantly and positively correlated with OCS severity scores, impulsivity severity scores were not significantly correlated with either. The global functioning score was significantly and negatively correlated with tic and OCS severity scores. Of the 6 dimensional OCS scores, only aggression scores had a significant negative correlation with global functioning scores. A stepwise multiple regression analysis showed that only OCS severity scores were significantly associated with global functioning scores. Despite a moderate correlation between tic severity and OCS severity, the impact of OCS on global functioning was greater than that of tics. Of the OCS dimensions, only aggression had a significant impact on global functioning. Our findings suggest that it is important to examine OCS using a dimensional approach when analyzing global functioning in TS patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Colour-dressed hexagon tessellations for correlation functions and non-planar corrections

NASA Astrophysics Data System (ADS)

Eden, Burkhard; Jiang, Yunfeng; le Plat, Dennis; Sfondrini, Alessandro

2018-02-01

We continue the study of four-point correlation functions by the hexagon tessellation approach initiated in [38] and [39]. We consider planar tree-level correlation functions in N=4 supersymmetric Yang-Mills theory involving two non-protected operators. We find that, in order to reproduce the field theory result, it is necessary to include SU( N) colour factors in the hexagon formalism; moreover, we find that the hexagon approach as it stands is naturally tailored to the single-trace part of correlation functions, and does not account for multi-trace admixtures. We discuss how to compute correlators involving double-trace operators, as well as more general 1 /N effects; in particular we compute the whole next-to-leading order in the large- N expansion of tree-level BMN two-point functions by tessellating a torus with punctures. Finally, we turn to the issue of "wrapping", Lüscher-like corrections. We show that SU( N) colour-dressing reproduces an earlier empirical rule for incorporating single-magnon wrapping, and we provide a direct interpretation of such wrapping processes in terms of N=2 supersymmetric Feynman diagrams.

Detecting nonlinear dynamics of functional connectivity

NASA Astrophysics Data System (ADS)

LaConte, Stephen M.; Peltier, Scott J.; Kadah, Yasser; Ngan, Shing-Chung; Deshpande, Gopikrishna; Hu, Xiaoping

2004-04-01

Functional magnetic resonance imaging (fMRI) is a technique that is sensitive to correlates of neuronal activity. The application of fMRI to measure functional connectivity of related brain regions across hemispheres (e.g. left and right motor cortices) has great potential for revealing fundamental physiological brain processes. Primarily, functional connectivity has been characterized by linear correlations in resting-state data, which may not provide a complete description of its temporal properties. In this work, we broaden the measure of functional connectivity to study not only linear correlations, but also those arising from deterministic, non-linear dynamics. Here the delta-epsilon approach is extended and applied to fMRI time series. The method of delays is used to reconstruct the joint system defined by a reference pixel and a candidate pixel. The crux of this technique relies on determining whether the candidate pixel provides additional information concerning the time evolution of the reference. As in many correlation-based connectivity studies, we fix the reference pixel. Every brain location is then used as a candidate pixel to estimate the spatial pattern of deterministic coupling with the reference. Our results indicate that measured connectivity is often emphasized in the motor cortex contra-lateral to the reference pixel, demonstrating the suitability of this approach for functional connectivity studies. In addition, discrepancies with traditional correlation analysis provide initial evidence for non-linear dynamical properties of resting-state fMRI data. Consequently, the non-linear characterization provided from our approach may provide a more complete description of the underlying physiology and brain function measured by this type of data.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

A Gaussian theory for fluctuations in simple liquids.

PubMed

Krüger, Matthias; Dean, David S

2017-04-07

Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point correlation functions (such as the intermediate scattering function) are derived. We show that this correlation function is exact at short times, for any interaction and, in particular, for arbitrary external potentials so that it applies to confined systems. Furthermore, we discuss the relation of this approach to previous ones, such as dynamical density functional theory as well as the formally exact treatment. This approach, inspired by the well known Landau-Ginzburg Hamiltonians, and the corresponding "Model B" equation of motion, may be seen as its microscopic version, containing information about the details on the particle level.

A Gaussian theory for fluctuations in simple liquids

NASA Astrophysics Data System (ADS)

Krüger, Matthias; Dean, David S.

2017-04-01

Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point correlation functions (such as the intermediate scattering function) are derived. We show that this correlation function is exact at short times, for any interaction and, in particular, for arbitrary external potentials so that it applies to confined systems. Furthermore, we discuss the relation of this approach to previous ones, such as dynamical density functional theory as well as the formally exact treatment. This approach, inspired by the well known Landau-Ginzburg Hamiltonians, and the corresponding "Model B" equation of motion, may be seen as its microscopic version, containing information about the details on the particle level.

The separate universe approach to soft limits

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

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

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

Neural Correlates of Visual Perceptual Expertise: Evidence from Cognitive Neuroscience Using Functional Neuroimaging

ERIC Educational Resources Information Center

Gegenfurtner, Andreas; Kok, Ellen M.; van Geel, Koos; de Bruin, Anique B. H.; Sorger, Bettina

2017-01-01

Functional neuroimaging is a useful approach to study the neural correlates of visual perceptual expertise. The purpose of this paper is to review the functional-neuroimaging methods that have been implemented in previous research in this context. First, we will discuss research questions typically addressed in visual expertise research. Second,…

Analysis of spatial correlations in a model two-dimensional liquid through eigenvalues and eigenvectors of atomic-level stress matrices.

PubMed

Levashov, V A; Stepanov, M G

2016-01-01

Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.

Bond breaking and bond formation: how electron correlation is captured in many-body perturbation theory and density-functional theory.

PubMed

Caruso, Fabio; Rohr, Daniel R; Hellgren, Maria; Ren, Xinguo; Rinke, Patrick; Rubio, Angel; Scheffler, Matthias

2013-04-05

For the paradigmatic case of H(2) dissociation, we compare state-of-the-art many-body perturbation theory in the GW approximation and density-functional theory in the exact-exchange plus random-phase approximation (RPA) for the correlation energy. For an unbiased comparison and to prevent spurious starting point effects, both approaches are iterated to full self-consistency (i.e., sc-RPA and sc-GW). The exchange-correlation diagrams in both approaches are topologically identical, but in sc-RPA they are evaluated with noninteracting and in sc-GW with interacting Green functions. This has a profound consequence for the dissociation region, where sc-RPA is superior to sc-GW. We argue that for a given diagrammatic expansion, sc-RPA outperforms sc-GW when it comes to bond breaking. We attribute this to the difference in the correlation energy rather than the treatment of the kinetic energy.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Dangers and uses of cross-correlation in analyzing time series in perception, performance, movement, and neuroscience: The importance of constructing transfer function autoregressive models.

PubMed

Dean, Roger T; Dunsmuir, William T M

2016-06-01

Many articles on perception, performance, psychophysiology, and neuroscience seek to relate pairs of time series through assessments of their cross-correlations. Most such series are individually autocorrelated: they do not comprise independent values. Given this situation, an unfounded reliance is often placed on cross-correlation as an indicator of relationships (e.g., referent vs. response, leading vs. following). Such cross-correlations can indicate spurious relationships, because of autocorrelation. Given these dangers, we here simulated how and why such spurious conclusions can arise, to provide an approach to resolving them. We show that when multiple pairs of series are aggregated in several different ways for a cross-correlation analysis, problems remain. Finally, even a genuine cross-correlation function does not answer key motivating questions, such as whether there are likely causal relationships between the series. Thus, we illustrate how to obtain a transfer function describing such relationships, informed by any genuine cross-correlations. We illustrate the confounds and the meaningful transfer functions by two concrete examples, one each in perception and performance, together with key elements of the R software code needed. The approach involves autocorrelation functions, the establishment of stationarity, prewhitening, the determination of cross-correlation functions, the assessment of Granger causality, and autoregressive model development. Autocorrelation also limits the interpretability of other measures of possible relationships between pairs of time series, such as mutual information. We emphasize that further complexity may be required as the appropriate analysis is pursued fully, and that causal intervention experiments will likely also be needed.

Time-dependent importance sampling in semiclassical initial value representation calculations for time correlation functions. II. A simplified implementation.

PubMed

Tao, Guohua; Miller, William H

2012-09-28

An efficient time-dependent (TD) Monte Carlo (MC) importance sampling method has recently been developed [G. Tao and W. H. Miller, J. Chem. Phys. 135, 024104 (2011)] for the evaluation of time correlation functions using the semiclassical (SC) initial value representation (IVR) methodology. In this TD-SC-IVR method, the MC sampling uses information from both time-evolved phase points as well as their initial values, and only the "important" trajectories are sampled frequently. Even though the TD-SC-IVR was shown in some benchmark examples to be much more efficient than the traditional time-independent sampling method (which uses only initial conditions), the calculation of the SC prefactor-which is computationally expensive, especially for large systems-is still required for accepted trajectories. In the present work, we present an approximate implementation of the TD-SC-IVR method that is completely prefactor-free; it gives the time correlation function as a classical-like magnitude function multiplied by a phase function. Application of this approach to flux-flux correlation functions (which yield reaction rate constants) for the benchmark H + H(2) system shows very good agreement with exact quantum results. Limitations of the approximate approach are also discussed.

Image correlation and sampling study

NASA Technical Reports Server (NTRS)

Popp, D. J.; Mccormack, D. S.; Sedwick, J. L.

1972-01-01

The development of analytical approaches for solving image correlation and image sampling of multispectral data is discussed. Relevant multispectral image statistics which are applicable to image correlation and sampling are identified. The general image statistics include intensity mean, variance, amplitude histogram, power spectral density function, and autocorrelation function. The translation problem associated with digital image registration and the analytical means for comparing commonly used correlation techniques are considered. General expressions for determining the reconstruction error for specific image sampling strategies are developed.

Spin Hartree-Fock approach to studying quantum Heisenberg antiferromagnets in low dimensions

NASA Astrophysics Data System (ADS)

Werth, A.; Kopietz, P.; Tsyplyatyev, O.

2018-05-01

We construct a new mean-field theory for a quantum (spin-1/2) Heisenberg antiferromagnet in one (1D) and two (2D) dimensions using a Hartree-Fock decoupling of the four-point correlation functions. We show that the solution to the self-consistency equations based on two-point correlation functions does not produce any unphysical finite-temperature phase transition, in accord with the Mermin-Wagner theorem, unlike the common approach based on the mean-field equation for the order parameter. The next-neighbor spin-spin correlation functions, calculated within this approach, reproduce closely the strong renormalization by quantum fluctuations obtained via a Bethe ansatz in 1D and a small renormalization of the classical antiferromagnetic state in 2D. The heat capacity approximates with reasonable accuracy the full Bethe ansatz result at all temperatures in 1D. In 2D, we obtain a reduction of the peak height in the heat capacity at a finite temperature that is accessible by high-order 1 /T expansions.

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models.

PubMed

Chen, Yongsheng; Persaud, Bhagwant

2014-09-01

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

A generalized estimating equations approach for resting-state functional MRI group analysis.

PubMed

D'Angelo, Gina M; Lazar, Nicole A; Eddy, William F; Morris, John C; Sheline, Yvette I

2011-01-01

An Alzheimer's fMRI study has motivated us to evaluate inter-regional correlations between groups. The overall objective is to assess inter-regional correlations at a resting-state with no stimulus or task. We propose using a generalized estimating equation (GEE) transition model and a GEE marginal model to model the within-subject correlation for each region. Residuals calculated from the GEE models are used to correlate brain regions and assess between group differences. The standard pooling approach of group averages of the Fisher-z transformation assuming temporal independence is a typical approach used to compare group correlations. The GEE approaches and standard Fisher-z pooling approach are demonstrated with an Alzheimer's disease (AD) connectivity study in a population of AD subjects and healthy control subjects. We also compare these methods using simulation studies and show that the transition model may have better statistical properties.

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.

Peculiarities of the momentum distribution functions of strongly correlated charged fermions

NASA Astrophysics Data System (ADS)

Larkin, A. S.; Filinov, V. S.; Fortov, V. E.

2018-01-01

New numerical version of the Wigner approach to quantum thermodynamics of strongly coupled systems of particles has been developed for extreme conditions, when analytical approximations based on different kinds of perturbation theories cannot be applied. An explicit analytical expression of the Wigner function has been obtained in linear and harmonic approximations. Fermi statistical effects are accounted for by effective pair pseudopotential depending on coordinates, momenta and degeneracy parameter of particles and taking into account Pauli blocking of fermions. A new quantum Monte-Carlo method for calculations of average values of arbitrary quantum operators has been developed. Calculations of the momentum distribution functions and the pair correlation functions of degenerate ideal Fermi gas have been carried out for testing the developed approach. Comparison of the obtained momentum distribution functions of strongly correlated Coulomb systems with the Maxwell-Boltzmann and the Fermi distributions shows the significant influence of interparticle interaction both at small momenta and in high energy quantum ‘tails’.

A perturbative approach to the redshift space correlation function: beyond the Standard Model

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Koyama, Kazuya

2017-08-01

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

Explicitly-correlated Gaussian geminals in electronic structure calculations

NASA Astrophysics Data System (ADS)

Szalewicz, Krzysztof; Jeziorski, Bogumił

2010-11-01

Explicitly correlated functions have been used since 1929, but initially only for two-electron systems. In 1960, Boys and Singer showed that if the correlating factor is of Gaussian form, many-electron integrals can be computed for general molecules. The capability of explicitly correlated Gaussian (ECG) functions to accurately describe many-electron atoms and molecules was demonstrated only in the early 1980s when Monkhorst, Zabolitzky and the present authors cast the many-body perturbation theory (MBPT) and coupled cluster (CC) equations as a system of integro-differential equations and developed techniques of solving these equations with two-electron ECG functions (Gaussian-type geminals, GTG). This work brought a new accuracy standard to MBPT/CC calculations. In 1985, Kutzelnigg suggested that the linear r 12 correlating factor can also be employed if n-electron integrals, n > 2, are factorised with the resolution of identity. Later, this factor was replaced by more general functions f (r 12), most often by ? , usually represented as linear combinations of Gaussian functions which makes the resulting approach (called F12) a special case of the original GTG expansion. The current state-of-art is that, for few-electron molecules, ECGs provide more accurate results than any other basis available, but for larger systems the F12 approach is the method of choice, giving significant improvements over orbital calculations.

The neural correlates of agrammatism: Evidence from aphasic and healthy speakers performing an overt picture description task

PubMed Central

Schönberger, Eva; Heim, Stefan; Meffert, Elisabeth; Pieperhoff, Peter; da Costa Avelar, Patricia; Huber, Walter; Binkofski, Ferdinand; Grande, Marion

2014-01-01

Functional brain imaging studies have improved our knowledge of the neural localization of language functions and the functional reorganization after a lesion. However, the neural correlates of agrammatic symptoms in aphasia remain largely unknown. The present fMRI study examined the neural correlates of morpho-syntactic encoding and agrammatic errors in continuous language production by combining three approaches. First, the neural mechanisms underlying natural morpho-syntactic processing in a picture description task were analyzed in 15 healthy speakers. Second, agrammatic-like speech behavior was induced in the same group of healthy speakers to study the underlying functional processes by limiting the utterance length. In a third approach, five agrammatic participants performed the picture description task to gain insights in the neural correlates of agrammatism and the functional reorganization of language processing after stroke. In all approaches, utterances were analyzed for syntactic completeness, complexity, and morphology. Event-related data analysis was conducted by defining every clause-like unit (CLU) as an event with its onset-time and duration. Agrammatic and correct CLUs were contrasted. Due to the small sample size as well as heterogeneous lesion sizes and sites with lesion foci in the insula lobe, inferior frontal, superior temporal and inferior parietal areas the activation patterns in the agrammatic speakers were analyzed on a single subject level. In the group of healthy speakers, posterior temporal and inferior parietal areas were associated with greater morpho-syntactic demands in complete and complex CLUs. The intentional manipulation of morpho-syntactic structures and the omission of function words were associated with additional inferior frontal activation. Overall, the results revealed that the investigation of the neural correlates of agrammatic language production can be reasonably conducted with an overt language production paradigm. PMID:24711802

Constraint on the second functional derivative of the exchange-correlation energy

NASA Astrophysics Data System (ADS)

Joubert, D. P.

2012-09-01

Using the density functional adiabatic connection approach for an N-electron system it is shown that ? γ is the coupling constant that scales the electron-electron interaction strength. For the non-interacting Kohn-Sham Hamiltonian γ = 0 and for the fully interacting system γ = 1. ? is the Hartree plus exchange-correlation energy while f 0(r) and fγ(r) are the Fukui functions of the non-interacting and interacting systems, respectively. This identity can serve to test the internal self-consistency or quality of approximate functionals. The quality of some popular approximate exchange and correlation functionals are tested for a simple model system.

A DYNAMIC DENSITY FUNCTIONAL THEORY APPROACH TO DIFFUSION IN WHITE DWARFS AND NEUTRON STAR ENVELOPES

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

Diaw, A.; Murillo, M. S.

2016-09-20

We develop a multicomponent hydrodynamic model based on moments of the Born–Bogolyubov–Green–Kirkwood–Yvon hierarchy equations for physical conditions relevant to astrophysical plasmas. These equations incorporate strong correlations through a density functional theory closure, while transport enters through a relaxation approximation. This approach enables the introduction of Coulomb coupling correction terms into the standard Burgers equations. The diffusive currents for these strongly coupled plasmas is self-consistently derived. The settling of impurities and its impact on cooling can be greatly affected by strong Coulomb coupling, which we show can be quantified using the direct correlation function.

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.

A time correlation function theory describing static field enhanced third order optical effects at interfaces.

PubMed

Neipert, Christine; Space, Brian

2006-12-14

Sum vibrational frequency spectroscopy, a second order optical process, is interface specific in the dipole approximation. At charged interfaces, there exists a static field, and as a direct consequence, the experimentally detected signal is a combination of enhanced second and static field induced third order contributions. There is significant evidence in the literature of the importance/relative magnitude of this third order contribution, but no previous molecularly detailed approach existed to separately calculate the second and third order contributions. Thus, for the first time, a molecularly detailed time correlation function theory is derived here that allows for the second and third order contributions to sum frequency vibrational spectra to be individually determined. Further, a practical, molecular dynamics based, implementation procedure for the derived correlation functions that describe the third order phenomenon is also presented. This approach includes a novel generalization of point atomic polarizability models to calculate the hyperpolarizability of a molecular system. The full system hyperpolarizability appears in the time correlation functions responsible for third order contributions in the presence of a static field.

Comparing ab initio density-functional and wave function theories: the impact of correlation on the electronic density and the role of the correlation potential.

PubMed

Grabowski, Ireneusz; Teale, Andrew M; Śmiga, Szymon; Bartlett, Rodney J

2011-09-21

The framework of ab initio density-functional theory (DFT) has been introduced as a way to provide a seamless connection between the Kohn-Sham (KS) formulation of DFT and wave-function based ab initio approaches [R. J. Bartlett, I. Grabowski, S. Hirata, and S. Ivanov, J. Chem. Phys. 122, 034104 (2005)]. Recently, an analysis of the impact of dynamical correlation effects on the density of the neon atom was presented [K. Jankowski, K. Nowakowski, I. Grabowski, and J. Wasilewski, J. Chem. Phys. 130, 164102 (2009)], contrasting the behaviour for a variety of standard density functionals with that of ab initio approaches based on second-order Møller-Plesset (MP2) and coupled cluster theories at the singles-doubles (CCSD) and singles-doubles perturbative triples [CCSD(T)] levels. In the present work, we consider ab initio density functionals based on second-order many-body perturbation theory and coupled cluster perturbation theory in a similar manner, for a range of small atomic and molecular systems. For comparison, we also consider results obtained from MP2, CCSD, and CCSD(T) calculations. In addition to this density based analysis, we determine the KS correlation potentials corresponding to these densities and compare them with those obtained for a range of ab initio density functionals via the optimized effective potential method. The correlation energies, densities, and potentials calculated using ab initio DFT display a similar systematic behaviour to those derived from electronic densities calculated using ab initio wave function theories. In contrast, typical explicit density functionals for the correlation energy, such as VWN5 and LYP, do not show behaviour consistent with this picture of dynamical correlation, although they may provide some degree of correction for already erroneous explicitly density-dependent exchange-only functionals. The results presented here using orbital dependent ab initio density functionals show that they provide a treatment of exchange and correlation contributions within the KS framework that is more consistent with traditional ab initio wave function based methods.

Angular correlations in pair production at the LHC in the parton Reggeization approach

NASA Astrophysics Data System (ADS)

Karpishkov, Anton; Nefedov, Maxim; Saleev, Vladimir

2017-10-01

We calculate angular correlation spectra between beauty (B) and anti-beauty mesons in proton-proton collisions in the leading order approximation of the parton Reggeization approach consistently merged with the next-to-leading order corrections from the emission of additional hard gluon (NLO* approximation). To describe b-quark hadronization we use the universal scale-depended parton-to-meson fragmentation functions extracted from the combined e+e- annihilation data. The Kimber-Martin-Ryskin model for the unintegrated parton distribution functions in a proton is implied. We have obtained good agreement between our predictions and data from the CMS Collaboration at the energy TeV for angular correlations within uncertainties and without free parameters.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

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

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

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

Isentropic calculation for thermodynamic properties of polarized liquid 3He by considering the effect of spin-dependent correlation function

NASA Astrophysics Data System (ADS)

Bordbar, G. H.; Hosseini, S.; Poostforush, A.

2017-05-01

Correlations in quantum fluids such as liquid 3He continue to be of high interest to scientists. Based on this prospect, the present work is devoted to study the effects of spin-spin correlation function on the thermodynamic properties of polarized liquid 3He such as pressure, velocity of sound, adiabatic index and adiabatic compressibility along different isentropic paths, using the Lennard-Jones potential and employing the variational approach based on cluster expansion of the energy functional. The inclusion of this correlation improves our previous calculations and leads to good agreements with experimental results.

Correlation Function Approach for Estimating Thermal Conductivity in Highly Porous Fibrous Materials

NASA Technical Reports Server (NTRS)

Martinez-Garcia, Jorge; Braginsky, Leonid; Shklover, Valery; Lawson, John W.

2011-01-01

Heat transport in highly porous fiber networks is analyzed via two-point correlation functions. Fibers are assumed to be long and thin to allow a large number of crossing points per fiber. The network is characterized by three parameters: the fiber aspect ratio, the porosity and the anisotropy of the structure. We show that the effective thermal conductivity of the system can be estimated from knowledge of the porosity and the correlation lengths of the correlation functions obtained from a fiber structure image. As an application, the effects of the fiber aspect ratio and the network anisotropy on the thermal conductivity is studied.

Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

Arterial input function derived from pairwise correlations between PET-image voxels.

PubMed

Schain, Martin; Benjaminsson, Simon; Varnäs, Katarina; Forsberg, Anton; Halldin, Christer; Lansner, Anders; Farde, Lars; Varrone, Andrea

2013-07-01

A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [(11)C]flumazenil and [(11)C]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (VT) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in VT was good (∼3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.

Extraction of temporal information in functional MRI

NASA Astrophysics Data System (ADS)

Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

2002-10-01

The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.

Next-to-leading order weighted Sivers asymmetry in semi-inclusive deep inelastic scattering: three-gluon correlator

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

Dai, Lingyun; Prokudin, Alexei; Kang, Zhong-Bo

2015-09-01

We study the three-gluon correlation function contribution to the Sivers asymmetry in semi-inclusive deep inelastic scattering. We first establish the matching between the usual twist-3 collinear factorization approach and transverse momentum dependent factorization formalism for the moderate transverse momentum region. We then derive the so-called coefficient functions used in the usual TMD evolution formalism. Finally, we perform the next-to-leading order calculation for the transverse-momentum-weighted spin-dependent differential cross section, from which we identify the QCD collinear evolution of the twist-3 Qiu-Sterman function: the off-diagonal contribution from the three-gluon correlation functions.

Fermionic Approach to Weighted Hurwitz Numbers and Topological Recursion

NASA Astrophysics Data System (ADS)

Alexandrov, A.; Chapuy, G.; Eynard, B.; Harnad, J.

2017-12-01

A fermionic representation is given for all the quantities entering in the generating function approach to weighted Hurwitz numbers and topological recursion. This includes: KP and 2D Toda {τ} -functions of hypergeometric type, which serve as generating functions for weighted single and double Hurwitz numbers; the Baker function, which is expanded in an adapted basis obtained by applying the same dressing transformation to all vacuum basis elements; the multipair correlators and the multicurrent correlators. Multiplicative recursion relations and a linear differential system are deduced for the adapted bases and their duals, and a Christoffel-Darboux type formula is derived for the pair correlator. The quantum and classical spectral curves linking this theory with the topological recursion program are derived, as well as the generalized cut-and-join equations. The results are detailed for four special cases: the simple single and double Hurwitz numbers, the weakly monotone case, corresponding to signed enumeration of coverings, the strongly monotone case, corresponding to Belyi curves and the simplest version of quantum weighted Hurwitz numbers.

Fermionic Approach to Weighted Hurwitz Numbers and Topological Recursion

NASA Astrophysics Data System (ADS)

Alexandrov, A.; Chapuy, G.; Eynard, B.; Harnad, J.

2018-06-01

A fermionic representation is given for all the quantities entering in the generating function approach to weighted Hurwitz numbers and topological recursion. This includes: KP and 2 D Toda {τ} -functions of hypergeometric type, which serve as generating functions for weighted single and double Hurwitz numbers; the Baker function, which is expanded in an adapted basis obtained by applying the same dressing transformation to all vacuum basis elements; the multipair correlators and the multicurrent correlators. Multiplicative recursion relations and a linear differential system are deduced for the adapted bases and their duals, and a Christoffel-Darboux type formula is derived for the pair correlator. The quantum and classical spectral curves linking this theory with the topological recursion program are derived, as well as the generalized cut-and-join equations. The results are detailed for four special cases: the simple single and double Hurwitz numbers, the weakly monotone case, corresponding to signed enumeration of coverings, the strongly monotone case, corresponding to Belyi curves and the simplest version of quantum weighted Hurwitz numbers.

Statistics of time delay and scattering correlation functions in chaotic systems. I. Random matrix theory

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

Novaes, Marcel

2015-06-15

We consider the statistics of time delay in a chaotic cavity having M open channels, in the absence of time-reversal invariance. In the random matrix theory approach, we compute the average value of polynomial functions of the time delay matrix Q = − iħS{sup †}dS/dE, where S is the scattering matrix. Our results do not assume M to be large. In a companion paper, we develop a semiclassical approximation to S-matrix correlation functions, from which the statistics of Q can also be derived. Together, these papers contribute to establishing the conjectured equivalence between the random matrix and the semiclassical approaches.

Exchange and correlation in positronium-molecule scattering

NASA Astrophysics Data System (ADS)

Fabrikant, I. I.; Wilde, R. S.

2018-05-01

Exchange and correlations play a particularly important role in positronium (Ps) collisions with atoms and molecules, since the static potential for Ps interaction with a neutral system is zero. Theoretical description of both effects is a very challenging task. In the present work we use the free-electron-gas model to describe exchange and correlations in Ps collisions with molecules similar to the approach widely used in the theory of electron-molecule collisions. The results for exchange and correlation energies are presented as functions of the Fermi momentum of the electron gas and the Ps incident energy. Using the Thomas-Fermi model, these functions can be converted into exchange and correlation potentials for Ps interaction with molecules as functions of the distance between the projectile and the target.

A perturbative approach to the redshift space correlation function: beyond the Standard Model

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

Bose, Benjamin; Koyama, Kazuya, E-mail: benjamin.bose@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model whichmore » is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpc h ≤ s ≤ 180Mpc/ h . Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.« less

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

PubMed

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach

NASA Astrophysics Data System (ADS)

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-01

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

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.

Blind channel estimation and deconvolution in colored noise using higher-order cumulants

NASA Astrophysics Data System (ADS)

Tugnait, Jitendra K.; Gummadavelli, Uma

1994-10-01

Existing approaches to blind channel estimation and deconvolution (equalization) focus exclusively on channel or inverse-channel impulse response estimation. It is well-known that the quality of the deconvolved output depends crucially upon the noise statistics also. Typically it is assumed that the noise is white and the signal-to-noise ratio is known. In this paper we remove these restrictions. Both the channel impulse response and the noise model are estimated from the higher-order (fourth, e.g.) cumulant function and the (second-order) correlation function of the received data via a least-squares cumulant/correlation matching criterion. It is assumed that the noise higher-order cumulant function vanishes (e.g., Gaussian noise, as is the case for digital communications). Consistency of the proposed approach is established under certain mild sufficient conditions. The approach is illustrated via simulation examples involving blind equalization of digital communications signals.

Hard-spin mean-field theory: A systematic derivation and exact correlations in one dimension

PubMed

Kabakcioglu

2000-04-01

Hard-spin mean-field theory is an improved mean-field approach which has proven to give accurate results, especially for frustrated spin systems, with relatively little computational effort. In this work, the previous phenomenological derivation is supplanted by a systematic and generic derivation that opens the possibility for systematic improvements, especially for the calculation of long-range correlation functions. A first level of improvement suffices to recover the exact long-range values of the correlation functions in one dimension.

Mapping the Structure-Function Relationship in Glaucoma and Healthy Patients Measured with Spectralis OCT and Humphrey Perimetry

PubMed Central

Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema

2018-01-01

Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196

Internet use and well-being in later life: a functional approach.

PubMed

Lifshitz, Rinat; Nimrod, Galit; Bachner, Yaacov G

2018-01-01

This study aimed at exploring the Internet's role in supporting subjective well-being in later life by applying a functional approach, namely, simultaneously but separately examining each of the principal online functions common among older adults (interpersonal communication, information, task performance and leisure). Data were collected online from 306 Internet users aged 50 years and over. Subjective well-being was measured according to indicators of depression and life satisfaction. Interpersonal communication and information seeking were the most commonly used Internet functions, followed by task performance; use for leisure and recreation was significantly less prevalent. All four online functions were positively correlated with life satisfaction, and task performance and leisure were negatively correlated with depression. After controlling for sociodemographic variables, only leisure associated significantly with the well-being measures. These findings revealed a paradoxical situation in which the most beneficial use of the Internet is the least popular.

Nonperturbative renormalization-group approach preserving the momentum dependence of correlation functions

NASA Astrophysics Data System (ADS)

Rose, F.; Dupuis, N.

2018-05-01

We present an approximation scheme of the nonperturbative renormalization group that preserves the momentum dependence of correlation functions. This approximation scheme can be seen as a simple improvement of the local potential approximation (LPA) where the derivative terms in the effective action are promoted to arbitrary momentum-dependent functions. As in the LPA, the only field dependence comes from the effective potential, which allows us to solve the renormalization-group equations at a relatively modest numerical cost (as compared, e.g., to the Blaizot-Mendéz-Galain-Wschebor approximation scheme). As an application we consider the two-dimensional quantum O(N ) model at zero temperature. We discuss not only the two-point correlation function but also higher-order correlation functions such as the scalar susceptibility (which allows for an investigation of the "Higgs" amplitude mode) and the conductivity. In particular, we show how, using Padé approximants to perform the analytic continuation i ωn→ω +i 0+ of imaginary frequency correlation functions χ (i ωn) computed numerically from the renormalization-group equations, one can obtain spectral functions in the real-frequency domain.

Complex Correlation Calculation of e-H Total Cross Sections

NASA Technical Reports Server (NTRS)

Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)

2001-01-01

Calculation of e-H total and elastic partial wave cross sections is being carried out using the complex correlation variational T-matrix method. In this preliminary study, elastic partial wave phase shifts are calculated with the correlation functions which are confined to be real. In that case the method reduces to the conventional optical potential approach with projection operators. The number of terms in the Hylleraas-type wave function for the S phase shifts is 95 while for the S it is 56, except for k=0.8 where it is 84. Our results, which are rigorous lower bounds, are given. They are seen to be in general agreement with those of Schwartz, but they are of 0 greater accuracy and outside of his error limits for k=0.3 and 0.4 for S. The main aim of this approach' is the application to higher energy scattering. By virtue of the complex correlation functions, the T matrix is not unitary so that elastic and total scattering cross sections are independent of each other. Our results will be compared specifically with those of Bray and Stelbovics.

Complex Correlation Calculation of e(-) - H Total Cross Sections

NASA Technical Reports Server (NTRS)

Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)

2001-01-01

Calculation of e(-) - H total and elastic partial wave cross sections is being carried out using the complex correlation variational T-matrix method. In this preliminary study, elastic partial wave phase shifts are calculated with the correlation functions which are confined to be real. In that case the method reduces to the conventional optical potential approach with 2 projection operators. The number of terms in the Hylleraas-type wave function for the S-1 phase shifts is 95 while for the S-3 it is 56, except for k = 0.8 where it is 84. Our results, which are rigorous lower bounds, are seen to be in general agreement with those of Schwartz, but they are of greater accuracy and outside of his error limits for k = 0.3 and 0.4 for S-1. The main aim of this approach is the application to higher energy scattering. By virtue of the complex correlation functions, the T-matrix is not unitary so that elastic and total scattering cross sections are independent of each other. Our results will be compared specifically with those of Bray and Stelbovics.

Influence of Initial Correlations on Evolution of a Subsystem in a Heat Bath and Polaron Mobility

NASA Astrophysics Data System (ADS)

Los, Victor F.

2017-08-01

A regular approach to accounting for initial correlations, which allows to go beyond the unrealistic random phase (initial product state) approximation in deriving the evolution equations, is suggested. An exact homogeneous (time-convolution and time-convolutionless) equations for a relevant part of the two-time equilibrium correlation function for the dynamic variables of a subsystem interacting with a boson field (heat bath) are obtained. No conventional approximation like RPA or Bogoliubov's principle of weakening of initial correlations is used. The obtained equations take into account the initial correlations in the kernel governing their evolution. The solution to these equations is found in the second order of the kernel expansion in the electron-phonon interaction, which demonstrates that generally the initial correlations influence the correlation function's evolution in time. It is explicitly shown that this influence vanishes on a large timescale (actually at t→ ∞) and the evolution process enters an irreversible kinetic regime. The developed approach is applied to the Fröhlich polaron and the low-temperature polaron mobility (which was under a long-time debate) is found with a correction due to initial correlations.

An open-chain imaginary-time path-integral sampling approach to the calculation of approximate symmetrized quantum time correlation functions.

PubMed

Cendagorta, Joseph R; Bačić, Zlatko; Tuckerman, Mark E

2018-03-14

We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.

An open-chain imaginary-time path-integral sampling approach to the calculation of approximate symmetrized quantum time correlation functions

NASA Astrophysics Data System (ADS)

Cendagorta, Joseph R.; Bačić, Zlatko; Tuckerman, Mark E.

2018-03-01

We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.

Measuring Work Functioning: Validity of a Weighted Composite Work Functioning Approach.

PubMed

Boezeman, Edwin J; Sluiter, Judith K; Nieuwenhuijsen, Karen

2015-09-01

To examine the construct validity of a weighted composite work functioning measurement approach. Workers (health-impaired/healthy) (n = 117) completed a composite measure survey that recorded four central work functioning aspects with existing scales: capacity to work, quality of work performance, quantity of work, and recovery from work. Previous derived weights reflecting the relative importance of these aspects of work functioning were used to calculate the composite weighted work functioning score of the workers. Work role functioning, productivity, and quality of life were used for validation. Correlations were calculated and norms applied to examine convergent and divergent construct validity. A t test was conducted and a norm applied to examine discriminative construct validity. Overall the weighted composite work functioning measure demonstrated construct validity. As predicted, the weighted composite score correlated (p < .001) strongly (r > .60) with work role functioning and productivity (convergent construct validity), and moderately (.30 < r < .60) with physical quality of life and less strongly than work role functioning and productivity with mental quality of life (divergent validity). Further, the weighted composite measure detected that health-impaired workers show with a large effect size (Cohen's d > .80) significantly worse work functioning than healthy workers (discriminative validity). The weighted composite work functioning measurement approach takes into account the relative importance of the different work functioning aspects and demonstrated good convergent, fair divergent, and good discriminative construct validity.

Electron Correlation from the Adiabatic Connection for Multireference Wave Functions

NASA Astrophysics Data System (ADS)

Pernal, Katarzyna

2018-01-01

An adiabatic connection (AC) formula for the electron correlation energy is derived for a broad class of multireference wave functions. The AC expression recovers dynamic correlation energy and assures a balanced treatment of the correlation energy. Coupling the AC formalism with the extended random phase approximation allows one to find the correlation energy only from reference one- and two-electron reduced density matrices. If the generalized valence bond perfect pairing model is employed a simple closed-form expression for the approximate AC formula is obtained. This results in the overall M5 scaling of the computation cost making the method one of the most efficient multireference approaches accounting for dynamic electron correlation also for the strongly correlated systems.

Functional correlation approach to operational risk in banking organizations

NASA Astrophysics Data System (ADS)

Kühn, Reimer; Neu, Peter

2003-05-01

A Value-at-Risk-based model is proposed to compute the adequate equity capital necessary to cover potential losses due to operational risks, such as human and system process failures, in banking organizations. Exploring the analogy to a lattice gas model from physics, correlations between sequential failures are modeled by as functionally defined, heterogeneous couplings between mutually supportive processes. In contrast to traditional risk models for market and credit risk, where correlations are described as equal-time-correlations by a covariance matrix, the dynamics of the model shows collective phenomena such as bursts and avalanches of process failures.

A review on the neural bases of episodic odor memory: from laboratory-based to autobiographical approaches

PubMed Central

Saive, Anne-Lise; Royet, Jean-Pierre; Plailly, Jane

2014-01-01

Odors are powerful cues that trigger episodic memories. However, in light of the amount of behavioral data describing the characteristics of episodic odor memory, the paucity of information available on the neural substrates of this function is startling. Furthermore, the diversity of experimental paradigms complicates the identification of a generic episodic odor memory network. We conduct a systematic review of the literature depicting the current state of the neural correlates of episodic odor memory in healthy humans by placing a focus on the experimental approaches. Functional neuroimaging data are introduced by a brief characterization of the memory processes investigated. We present and discuss laboratory-based approaches, such as odor recognition and odor associative memory, and autobiographical approaches, such as the evaluation of odor familiarity and odor-evoked autobiographical memory. We then suggest the development of new laboratory-ecological approaches allowing for the controlled encoding and retrieval of specific multidimensional events that could open up new prospects for the comprehension of episodic odor memory and its neural underpinnings. While large conceptual differences distinguish experimental approaches, the overview of the functional neuroimaging findings suggests relatively stable neural correlates of episodic odor memory. PMID:25071494

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Minimal gravity and Frobenius manifolds: bulk correlation on sphere and disk

NASA Astrophysics Data System (ADS)

Aleshkin, Konstantin; Belavin, Vladimir; Rim, Chaiho

2017-11-01

There are two alternative approaches to the minimal gravity — direct Liouville approach and matrix models. Recently there has been a certain progress in the matrix model approach, growing out of presence of a Frobenius manifold (FM) structure embedded in the theory. The previous studies were mainly focused on the spherical topology. Essentially, it was shown that the action principle of Douglas equation allows to define the free energy and to compute the correlation numbers if the resonance transformations are properly incorporated. The FM structure allows to find the explicit form of the resonance transformation as well as the closed expression for the partition function. In this paper we elaborate on the case of gravitating disk. We focus on the bulk correlators and show that in the similar way as in the closed topology the generating function can be formulated using the set of flat coordinates on the corresponding FM. Moreover, the resonance transformations, which follow from the spherical topology consideration, are exactly those needed to reproduce FZZ result of the Liouville gravity approach.

Subsystem density functional theory with meta-generalized gradient approximation exchange-correlation functionals.

PubMed

Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio

2015-04-21

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.

Short-range density functional correlation within the restricted active space CI method

NASA Astrophysics Data System (ADS)

Casanova, David

2018-03-01

In the present work, I introduce a hybrid wave function-density functional theory electronic structure method based on the range separation of the electron-electron Coulomb operator in order to recover dynamic electron correlations missed in the restricted active space configuration interaction (RASCI) methodology. The working equations and the computational algorithm for the implementation of the new approach, i.e., RAS-srDFT, are presented, and the method is tested in the calculation of excitation energies of organic molecules. The good performance of the RASCI wave function in combination with different short-range exchange-correlation functionals in the computation of relative energies represents a quantitative improvement with respect to the RASCI results and paves the path for the development of RAS-srDFT as a promising scheme in the computation of the ground and excited states where nondynamic and dynamic electron correlations are important.

Polymer Coatings Degradation Properties

DTIC Science & Technology

1985-02-01

undertaken 124). The Box-Jenkins approach first evaluates the partial auto -correlation function and determines the order of the moving average memory function...78 - Tables 15 and 16 show the resalit- f- a, the partial auto correlation plots. Second order moving .-. "ra ;;th -he appropriate lags were...coated films. Kaempf, Guenter; Papenroth, Wolfgang; Kunststoffe Date: 1982 Volume: 72 Number:7 Pages: 424-429 Parameters influencing the accelerated

Penalized Weighted Least-Squares Approach to Sinogram Noise Reduction and Image Reconstruction for Low-Dose X-Ray Computed Tomography

PubMed Central

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-01-01

Reconstructing low-dose X-ray CT (computed tomography) images is a noise problem. This work investigated a penalized weighted least-squares (PWLS) approach to address this problem in two dimensions, where the WLS considers first- and second-order noise moments and the penalty models signal spatial correlations. Three different implementations were studied for the PWLS minimization. One utilizes a MRF (Markov random field) Gibbs functional to consider spatial correlations among nearby detector bins and projection views in sinogram space and minimizes the PWLS cost function by iterative Gauss-Seidel algorithm. Another employs Karhunen-Loève (KL) transform to de-correlate data signals among nearby views and minimizes the PWLS adaptively to each KL component by analytical calculation, where the spatial correlation among nearby bins is modeled by the same Gibbs functional. The third one models the spatial correlations among image pixels in image domain also by a MRF Gibbs functional and minimizes the PWLS by iterative successive over-relaxation algorithm. In these three implementations, a quadratic functional regularization was chosen for the MRF model. Phantom experiments showed a comparable performance of these three PWLS-based methods in terms of suppressing noise-induced streak artifacts and preserving resolution in the reconstructed images. Computer simulations concurred with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS implementation may have the advantage in terms of computation for high-resolution dynamic low-dose CT imaging. PMID:17024831

Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography.

PubMed

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-09-01

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation 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 multiresolution 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 artifacts in regions where no significant correlation exists between anatomical and functional details. 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. 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 artifacts and significantly improving quality of the corrected images and their quantitative accuracy. A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multiresolution 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.

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

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Multivariate η-μ fading distribution with arbitrary correlation model

NASA Astrophysics Data System (ADS)

Ghareeb, Ibrahim; Atiani, Amani

2018-03-01

An extensive analysis for the multivariate ? distribution with arbitrary correlation is presented, where novel analytical expressions for the multivariate probability density function, cumulative distribution function and moment generating function (MGF) of arbitrarily correlated and not necessarily identically distributed ? power random variables are derived. Also, this paper provides exact-form expression for the MGF of the instantaneous signal-to-noise ratio at the combiner output in a diversity reception system with maximal-ratio combining and post-detection equal-gain combining operating in slow frequency nonselective arbitrarily correlated not necessarily identically distributed ?-fading channels. The average bit error probability of differentially detected quadrature phase shift keying signals with post-detection diversity reception system over arbitrarily correlated and not necessarily identical fading parameters ?-fading channels is determined by using the MGF-based approach. The effect of fading correlation between diversity branches, fading severity parameters and diversity level is studied.

Computing many-body wave functions with guaranteed precision: the first-order Møller-Plesset wave function for the ground state of helium atom.

PubMed

Bischoff, Florian A; Harrison, Robert J; Valeev, Edward F

2012-09-14

We present an approach to compute accurate correlation energies for atoms and molecules using an adaptive discontinuous spectral-element multiresolution representation for the two-electron wave function. Because of the exponential storage complexity of the spectral-element representation with the number of dimensions, a brute-force computation of two-electron (six-dimensional) wave functions with high precision was not practical. To overcome the key storage bottlenecks we utilized (1) a low-rank tensor approximation (specifically, the singular value decomposition) to compress the wave function, and (2) explicitly correlated R12-type terms in the wave function to regularize the Coulomb electron-electron singularities of the Hamiltonian. All operations necessary to solve the Schrödinger equation were expressed so that the reconstruction of the full-rank form of the wave function is never necessary. Numerical performance of the method was highlighted by computing the first-order Møller-Plesset wave function of a helium atom. The computed second-order Møller-Plesset energy is precise to ~2 microhartrees, which is at the precision limit of the existing general atomic-orbital-based approaches. Our approach does not assume special geometric symmetries, hence application to molecules is straightforward.

Communication: a density functional with accurate fractional-charge and fractional-spin behaviour for s-electrons.

PubMed

Johnson, Erin R; Contreras-García, Julia

2011-08-28

We develop a new density-functional approach combining physical insight from chemical structure with treatment of multi-reference character by real-space modeling of the exchange-correlation hole. We are able to recover, for the first time, correct fractional-charge and fractional-spin behaviour for atoms of groups 1 and 2. Based on Becke's non-dynamical correlation functional [A. D. Becke, J. Chem. Phys. 119, 2972 (2003)] and explicitly accounting for core-valence separation and pairing effects, this method is able to accurately describe dissociation and strong correlation in s-shell many-electron systems. © 2011 American Institute of Physics

Bayesian Approach to Spectral Function Reconstruction for Euclidean Quantum Field Theories

NASA Astrophysics Data System (ADS)

Burnier, Yannis; Rothkopf, Alexander

2013-11-01

We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33TC.

Bayesian approach to spectral function reconstruction for Euclidean quantum field theories.

PubMed

Burnier, Yannis; Rothkopf, Alexander

2013-11-01

We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33T(C).

Emergent behaviors of the Schrödinger-Lohe model on cooperative-competitive networks

NASA Astrophysics Data System (ADS)

Huh, Hyungjin; Ha, Seung-Yeal; Kim, Dohyun

2017-12-01

We present several sufficient frameworks leading to the emergent behaviors of the coupled Schrödinger-Lohe (S-L) model under the same one-body external potential on cooperative-competitive networks. The S-L model was first introduced as a possible phenomenological model exhibiting quantum synchronization and its emergent dynamics on all-to-all cooperative networks has been treated via two distinct approaches, Lyapunov functional approach and the finite-dimensional reduction based on pairwise correlations. In this paper, we further generalize the finite-dimensional dynamical systems approach for pairwise correlation functions on cooperative-competitive networks and provide several sufficient frameworks leading to the collective exponential synchronization. For small systems consisting of three and four quantum subsystem, we also show that the system for pairwise correlations can be reduced to the Lotka-Volterra model with cooperative and competitive interactions, in which lots of interesting dynamical patterns appear, e.g., existence of closed orbits and limit-cycles.

Brain functional connectivity changes in children that differ in impulsivity temperamental trait

PubMed Central

Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V.; García-Santos, Jose M.; Fuentes, Luis J.

2014-01-01

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior. PMID:24834038

Brain functional connectivity changes in children that differ in impulsivity temperamental trait.

PubMed

Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V; García-Santos, Jose M; Fuentes, Luis J

2014-01-01

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

Algorithm for quantum-mechanical finite-nuclear-mass variational calculations of atoms with two p electrons using all-electron explicitly correlated Gaussian basis functions

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

Sharkey, Keeper L.; Pavanello, Michele; Bubin, Sergiy

2009-12-15

A new algorithm for calculating the Hamiltonian matrix elements with all-electron explicitly correlated Gaussian functions for quantum-mechanical calculations of atoms with two p electrons or a single d electron have been derived and implemented. The Hamiltonian used in the approach was obtained by rigorously separating the center-of-mass motion and it explicitly depends on the finite mass of the nucleus. The approach was employed to perform test calculations on the isotopes of the carbon atom in their ground electronic states and to determine the finite-nuclear-mass corrections for these states.

Generalized elimination of the global translation from explicitly correlated Gaussian functions

NASA Astrophysics Data System (ADS)

Muolo, Andrea; Mátyus, Edit; Reiher, Markus

2018-02-01

This paper presents the multi-channel generalization of the center-of-mass kinetic energy elimination approach [B. Simmen et al., Mol. Phys. 111, 2086 (2013)] when the Schrödinger equation is solved variationally with explicitly correlated Gaussian functions. The approach has immediate relevance in many-particle systems which are handled without the Born-Oppenheimer approximation and can be employed also for Dirac-type Hamiltonians. The practical realization and numerical properties of solving the Schrödinger equation in laboratory-frame Cartesian coordinates are demonstrated for the ground rovibronic state of the H2+={p+,p+,e- } ion and the H2 = {p+, p+, e-, e-} molecule.

Direct reconstruction of the two-dimensional pair distribution function in partially ordered systems with angular correlations.

PubMed

Zaluzhnyy, I A; Kurta, R P; Menushenkov, A P; Ostrovskii, B I; Vartanyants, I A

2016-09-01

An x-ray scattering approach to determine the two-dimensional (2D) pair distribution function (PDF) in partially ordered 2D systems is proposed. We derive relations between the structure factor and PDF that enable quantitative studies of positional and bond-orientational (BO) order in real space. We apply this approach in the x-ray study of a liquid crystal (LC) film undergoing the smectic-A-hexatic-B phase transition, to analyze the interplay between the positional and BO order during the temperature evolution of the LC film. We analyze the positional correlation length in different directions in real space.

Generalized elimination of the global translation from explicitly correlated Gaussian functions.

PubMed

Muolo, Andrea; Mátyus, Edit; Reiher, Markus

2018-02-28

This paper presents the multi-channel generalization of the center-of-mass kinetic energy elimination approach [B. Simmen et al., Mol. Phys. 111, 2086 (2013)] when the Schrödinger equation is solved variationally with explicitly correlated Gaussian functions. The approach has immediate relevance in many-particle systems which are handled without the Born-Oppenheimer approximation and can be employed also for Dirac-type Hamiltonians. The practical realization and numerical properties of solving the Schrödinger equation in laboratory-frame Cartesian coordinates are demonstrated for the ground rovibronic state of the H 2 + ={p + ,p + ,e - } ion and the H 2 = {p + , p + , e - , e - } molecule.

Total Quality Management (TQM) in Self-Financed Technical Institutions: A Quality Function Deployment (QFD) and Force Field Analysis Approach

ERIC Educational Resources Information Center

Thakkar, Jitesh; Deshmukh, S. G.; Shastree, Anil

2006-01-01

Purpose: To explore the potential for adoption of TQM in self-financed technical institutions in the light of new demands and challenges posed by customers/students and society. Design/methodology/approach: The paper presents use of quality function deployment (QFD) which prioritizes technical requirements and correlates them with various…

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.

Exact exchange and Wilson-Levy correlation: a pragmatic device for studying complex weakly-bonded systems.

PubMed

Walsh, T R

2005-02-07

The Wilson-Levy (WL) correlation functional is used together with Hartree-Fock (HF) theory to evaluate interaction energies at intermediate separations (i.e. around equilibrium separation) for several weakly-bonded systems. The HF+WL approach reproduces binding trends for all complexes studied: selected rare-gas dimers, isomers of the methane dimer, benzene dimer and naphthalene dimer, and base-pair stacking structures for pyrimidine, cytosine, uracil and guanine dimers. These HF+WL data are contrasted against results obtained from some popular functionals (including B3LYP and PBE), as well as two newly-developed functionals, X3LYP and xPBE. The utility of HF+WL, with reference to exact-exchange (EXX) density-functional theory, is discussed in terms of a suggested EXXWL exchange-correlation functional.

Modeling Electronic-Nuclear Interactions for Excitation Energy Transfer Processes in Light-Harvesting Complexes.

PubMed

Lee, Mi Kyung; Coker, David F

2016-08-18

An accurate approach for computing intermolecular and intrachromophore contributions to spectral densities to describe the electronic-nuclear interactions relevant for modeling excitation energy transfer processes in light harvesting systems is presented. The approach is based on molecular dynamics (MD) calculations of classical correlation functions of long-range contributions to excitation energy fluctuations and a separate harmonic analysis and single-point gradient quantum calculations for electron-intrachromophore vibrational couplings. A simple model is also presented that enables detailed analysis of the shortcomings of standard MD-based excitation energy fluctuation correlation function approaches. The method introduced here avoids these problems, and its reliability is demonstrated in accurate predictions for bacteriochlorophyll molecules in the Fenna-Matthews-Olson pigment-protein complex, where excellent agreement with experimental spectral densities is found. This efficient approach can provide instantaneous spectral densities for treating the influence of fluctuations in environmental dissipation on fast electronic relaxation.

Open-Ended Recursive Approach for the Calculation of Multiphoton Absorption Matrix Elements

PubMed Central

2015-01-01

We present an implementation of single residues for response functions to arbitrary order using a recursive approach. Explicit expressions in terms of density-matrix-based response theory for the single residues of the linear, quadratic, cubic, and quartic response functions are also presented. These residues correspond to one-, two-, three- and four-photon transition matrix elements. The newly developed code is used to calculate the one-, two-, three- and four-photon absorption cross sections of para-nitroaniline and para-nitroaminostilbene, making this the first treatment of four-photon absorption in the framework of response theory. We find that the calculated multiphoton absorption cross sections are not very sensitive to the size of the basis set as long as a reasonably large basis set with diffuse functions is used. The choice of exchange–correlation functional, however, significantly affects the calculated cross sections of both charge-transfer transitions and other transitions, in particular, for the larger para-nitroaminostilbene molecule. We therefore recommend the use of a range-separated exchange–correlation functional in combination with the augmented correlation-consistent double-ζ basis set aug-cc-pVDZ for the calculation of multiphoton absorption properties. PMID:25821415

Asymptotic correlation functions and FFLO signature for the one-dimensional attractive Hubbard model

NASA Astrophysics Data System (ADS)

Cheng, Song; Jiang, Yuzhu; Yu, Yi-Cong; Batchelor, Murray T.; Guan, Xi-Wen

2018-04-01

We study the long-distance asymptotic behavior of various correlation functions for the one-dimensional (1D) attractive Hubbard model in a partially polarized phase through the Bethe ansatz and conformal field theory approaches. We particularly find the oscillating behavior of these correlation functions with spatial power-law decay, of which the pair (spin) correlation function oscillates with a frequency ΔkF (2 ΔkF). Here ΔkF = π (n↑ -n↓) is the mismatch in the Fermi surfaces of spin-up and spin-down particles. Consequently, the pair correlation function in momentum space has peaks at the mismatch k = ΔkF, which has been observed in recent numerical work on this model. These singular peaks in momentum space together with the spatial oscillation suggest an analog of the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state in the 1D Hubbard model. The parameter β representing the lattice effect becomes prominent in critical exponents which determine the power-law decay of all correlation functions. We point out that the backscattering of unpaired fermions and bound pairs within their own Fermi points gives a microscopic origin of the FFLO pairing in 1D.

Cyber-Physical Correlations for Infrastructure Resilience: A Game-Theoretic Approach

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

Rao, Nageswara S; He, Fei; Ma, Chris Y. T.

In several critical infrastructures, the cyber and physical parts are correlated so that disruptions to one affect the other and hence the whole system. These correlations may be exploited to strategically launch components attacks, and hence must be accounted for ensuring the infrastructure resilience, specified by its survival probability. We characterize the cyber-physical interactions at two levels: (i) the failure correlation function specifies the conditional survival probability of cyber sub-infrastructure given the physical sub-infrastructure as a function of their marginal probabilities, and (ii) the individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions. We formulate a resiliencemore » problem for infrastructures composed of discrete components as a game between the provider and attacker, wherein their utility functions consist of an infrastructure survival probability term and a cost term expressed in terms of the number of components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost term, correlation function and sub-infrastructure survival probabilities. These results generalize earlier ones based on linear failure correlation functions and independent component failures. We apply the results to models of cloud computing infrastructures and energy grids.« less

Principal Component Analysis reveals correlation of cavities evolution and functional motions in proteins.

PubMed

Desdouits, Nathan; Nilges, Michael; Blondel, Arnaud

2015-02-01

Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Synthesis of correlation filters: a generalized space-domain approach for improved filter characteristics

NASA Astrophysics Data System (ADS)

Sudharsanan, Subramania I.; Mahalanobis, Abhijit; Sundareshan, Malur K.

1990-12-01

Discrete frequency domain design of Minimum Average Correlation Energy filters for optical pattern recognition introduces an implementational limitation of circular correlation. An alternative methodology which uses space domain computations to overcome this problem is presented. The technique is generalized to construct an improved synthetic discriminant function which satisfies the conflicting requirements of reduced noise variance and sharp correlation peaks to facilitate ease of detection. A quantitative evaluation of the performance characteristics of the new filter is conducted and is shown to compare favorably with the well known Minimum Variance Synthetic Discriminant Function and the space domain Minimum Average Correlation Energy filter, which are special cases of the present design.

Exact density functional and wave function embedding schemes based on orbital localization

NASA Astrophysics Data System (ADS)

Hégely, Bence; Nagy, Péter R.; Ferenczy, György G.; Kállay, Mihály

2016-08-01

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up the system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

[Quantitative measures for assessing the functional state of the human body during diagnostic procedure].

PubMed

Artemenko, M V

2008-01-01

Two approaches to calculation of the qualitative measures for assessing the functional state level of human body are considered. These approaches are based on image and fuzzy set recognition theories and are used to construct diagnostic decision rules. The first approach uses the data on deviation of detected parameters from those for healthy persons; the second approach analyzes the degree of deviation of detected parameters from the approximants characterizing the correlation differences between the parameters. A method for synthesis of decision rules and the results of blood count-based research for a number of diseases (hemophilia, thrombocytopathy, hypertension, arrhythmia, hepatic cirrhosis, trichophytia) are considered. An effect of a change in the functional link between the cholesterol content in blood and the relative rate of variation of AST and ALT enzymes in blood from direct proportional (healthy state) to inverse proportional (hepatic cirrhosis) is discussed. It is shown that analysis of correlation changes in detected parameters of the human body state during diagnostic process is more effective for application in decision support systems than the state space analysis.

Universal RCFT correlators from the holomorphic bootstrap

NASA Astrophysics Data System (ADS)

Mukhi, Sunil; Muralidhara, Girish

2018-02-01

We elaborate and extend the method of Wronskian differential equations for conformal blocks to compute four-point correlation functions on the plane for classes of primary fields in rational (and possibly more general) conformal field theories. This approach leads to universal differential equations for families of CFT's and provides a very simple re-derivation of the BPZ results for the degenerate fields ϕ 1,2 and ϕ 2,1 in the c < 1 minimal models. We apply this technique to compute correlators for the WZW models corresponding to the Deligne-Cvitanović exceptional series of Lie algebras. The application turns out to be subtle in certain cases where there are multiple decoupled primaries. The power of this approach is demonstrated by applying it to compute four-point functions for the Baby Monster CFT, which does not belong to any minimal series.

Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory

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

Morse, David C.

2006-10-15

Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules,more » and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of binary homopolymer blends and diblock copolymer melts.« less

Speckle-field propagation in 'frozen' turbulence: brightness function approach

NASA Astrophysics Data System (ADS)

Dudorov, Vadim V.; Vorontsov, Mikhail A.; Kolosov, Valeriy V.

2006-08-01

Speckle-field long- and short-exposure spatial correlation characteristics for target-in-the-loop (TIL) laser beam propagation and scattering in atmospheric turbulence are analyzed through the use of two different approaches: the conventional Monte Carlo (MC) technique and the recently developed brightness function (BF) method. Both the MC and the BF methods are applied to analysis of speckle-field characteristics averaged over target surface roughness realizations under conditions of 'frozen' turbulence. This corresponds to TIL applications where speckle-field fluctuations associated with target surface roughness realization updates occur within a time scale that can be significantly shorter than the characteristic atmospheric turbulence time. Computational efficiency and accuracy of both methods are compared on the basis of a known analytical solution for the long-exposure mutual correlation function. It is shown that in the TIL propagation scenarios considered the BF method provides improved accuracy and requires significantly less computational time than the conventional MC technique. For TIL geometry with a Gaussian outgoing beam and Lambertian target surface, both analytical and numerical estimations for the speckle-field long-exposure correlation length are obtained. Short-exposure speckle-field correlation characteristics corresponding to propagation in 'frozen' turbulence are estimated using the BF method. It is shown that atmospheric turbulence-induced static refractive index inhomogeneities do not significantly affect the characteristic correlation length of the speckle field, whereas long-exposure spatial correlation characteristics are strongly dependent on turbulence strength.

Speckle-field propagation in 'frozen' turbulence: brightness function approach.

PubMed

Dudorov, Vadim V; Vorontsov, Mikhail A; Kolosov, Valeriy V

2006-08-01

Speckle-field long- and short-exposure spatial correlation characteristics for target-in-the-loop (TIL) laser beam propagation and scattering in atmospheric turbulence are analyzed through the use of two different approaches: the conventional Monte Carlo (MC) technique and the recently developed brightness function (BF) method. Both the MC and the BF methods are applied to analysis of speckle-field characteristics averaged over target surface roughness realizations under conditions of 'frozen' turbulence. This corresponds to TIL applications where speckle-field fluctuations associated with target surface roughness realization updates occur within a time scale that can be significantly shorter than the characteristic atmospheric turbulence time. Computational efficiency and accuracy of both methods are compared on the basis of a known analytical solution for the long-exposure mutual correlation function. It is shown that in the TIL propagation scenarios considered the BF method provides improved accuracy and requires significantly less computational time than the conventional MC technique. For TIL geometry with a Gaussian outgoing beam and Lambertian target surface, both analytical and numerical estimations for the speckle-field long-exposure correlation length are obtained. Short-exposure speckle-field correlation characteristics corresponding to propagation in 'frozen' turbulence are estimated using the BF method. It is shown that atmospheric turbulence-induced static refractive index inhomogeneities do not significantly affect the characteristic correlation length of the speckle field, whereas long-exposure spatial correlation characteristics are strongly dependent on turbulence strength.

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

PubMed

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

2018-04-20

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

An 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.

Retrieving robust noise-based seismic velocity changes from sparse data sets: synthetic tests and application to Klyuchevskoy volcanic group (Kamchatka)

NASA Astrophysics Data System (ADS)

Gómez-García, C.; Brenguier, F.; Boué, P.; Shapiro, N. M.; Droznin, D. V.; Droznina, S. Ya; Senyukov, S. L.; Gordeev, E. I.

2018-05-01

Continuous noise-based monitoring of seismic velocity changes provides insights into volcanic unrest, earthquake mechanisms and fluid injection in the sub-surface. The standard monitoring approach relies on measuring travel time changes of late coda arrivals between daily and reference noise cross-correlations, usually chosen as stacks of daily cross-correlations. The main assumption of this method is that the shape of the noise correlations does not change over time or, in other terms, that the ambient-noise sources are stationary through time. These conditions are not fulfilled when a strong episodic source of noise, such as a volcanic tremor for example, perturbs the reconstructed Green's function. In this paper we propose a general formulation for retrieving continuous time series of noise-based seismic velocity changes without the requirement of any arbitrary reference cross-correlation function. Instead, we measure the changes between all possible pairs of daily cross-correlations and invert them using different smoothing parameters to obtain the final velocity change curve. We perform synthetic tests in order to establish a general framework for future applications of this technique. In particular, we study the reliability of velocity change measurements versus the stability of noise cross-correlation functions. We apply this approach to a complex dataset of noise cross-correlations at Klyuchevskoy volcanic group (Kamchatka), hampered by loss of data and the presence of highly non-stationary seismic tremors.

Self-calibrated correlation imaging with k-space variant correlation functions.

PubMed

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

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

PubMed

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

2015-07-01

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

Importance of the correlation contribution for local hybrid functionals: range separation and self-interaction corrections.

PubMed

Arbuznikov, Alexei V; Kaupp, Martin

2012-01-07

Local hybrid functionals with their position-dependent exact-exchange admixture are a conceptually simple and promising extension of the concept of a hybrid functional. Local hybrids based on a simple mixing of the local spin density approximation (LSDA) with exact exchange have been shown to be successful for thermochemistry, reaction barriers, and a range of other properties. So far, the combination of this generation of local hybrids with an LSDA correlation functional has been found to give the most favorable results for atomization energies, for a range of local mixing functions (LMFs) governing the exact-exchange admixture. Here, we show that the choice of correlation functional to be used with local hybrid exchange crucially influences the parameterization also of the exchange part as well as the overall performance. A novel ansatz for the correlation part of local hybrids is suggested based on (i) range-separation of LSDA correlation into short-range (SR) and long-range (LR) parts, and (ii) partial or full elimination of the one-electron self-correlation from the SR part. It is shown that such modified correlation functionals allow overall larger exact exchange admixture in thermochemically competitive local hybrids than before. This results in improvements for reaction barriers and for other properties crucially influenced by self-interaction errors, as demonstrated by a number of examples. Based on the range-separation approach, a fresh view on the breakdown of the correlation energy into dynamical and non-dynamical parts is suggested.

Decomposition of conditional probability for high-order symbolic Markov chains.

PubMed

Melnik, S S; Usatenko, O V

2017-07-01

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements. At weak correlations, the memory functions are uniquely expressed in terms of the high-order symbolic correlation functions. The proposed method fills the gap between two approaches, namely the likelihood estimation and the additive Markov chains. The obtained results may have applications for sequential approximation of artificial neural network training.

Decomposition of conditional probability for high-order symbolic Markov chains

NASA Astrophysics Data System (ADS)

Melnik, S. S.; Usatenko, O. V.

2017-07-01

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements. At weak correlations, the memory functions are uniquely expressed in terms of the high-order symbolic correlation functions. The proposed method fills the gap between two approaches, namely the likelihood estimation and the additive Markov chains. The obtained results may have applications for sequential approximation of artificial neural network training.

Magnetized liquid 3He at finite temperature: A variational calculation approach

NASA Astrophysics Data System (ADS)

Bordbar, Gholam Hossein; Mohammadi Sabet, Mohammad Taghi

2016-08-01

Using the spin-dependent (SD) and spin-independent (SI) correlation functions, we have investigated the properties of liquid 3He in the presence of magnetic field at finite temperature. Our calculations have been done using the variational method based on cluster expansion of the energy functional. Our results show that the low field magnetic susceptibility obeys Curie law at high temperatures. This behavior is in a good agreement with the experimental data as well as the molecular field theory results in which the spin dependency has been introduced in correlation function. Reduced susceptibility as a function of temperature as well as reduced temperature has been also investigated, and again we have seen that the spin-dependent correlation function leads to a good agreement with the experimental data. The Landau parameter, F0a, has been calculated, and for this parameter, a value about - 0.75 has been found in the case of spin-spin correlation. In the case of spin-independent correlation function, this value is about - 0.7. Therefore, inclusion of spin dependency in the correlation function leads to a more compatible value of F0a with experimental data. The magnetization and susceptibility of liquid 3He have also been investigated as a function of magnetic field. Our results show a downward curvature in magnetization of system with spin-dependent correlation for all densities and relevant temperatures. A metamagnetic behavior has been observed as a maximum in susceptibility versus magnetic field, when the spin-spin correlation has been considered. This maximum occurs at 45T ≤ B ≤ 100T for all densities and temperatures. This behavior has not been observed in the case of spin-independent correlation function.

Functional Neuroanatomical Correlates of The Frontal Assessment Battery Performance in Alzheimer Disease: A FDG-PET Study.

PubMed

Lee, Jun Ho; Byun, Min Soo; Sohn, Bo Kyung; Choe, Young Min; Yi, Dahyun; Han, Ji Young; Choi, Hyo Jung; Baek, Hyewon; Woo, Jong Inn; Lee, Dong Young

2015-09-01

We aimed to elucidate the functional neuroanatomical correlates of Frontal Assessment Battery (FAB) performances by applying [(18)F]fluorodeoxyglucose positron emission tomography (FDG-PET) to a large population of patients with Alzheimer disease (AD). The FAB was administered to 177 patients with AD, and regional cerebral glucose metabolism (rCMglc) was measured by FDG-PET scan. Correlations between FAB scores and rCMglc were explored using both region-of-interest-based (ROI-based) and voxel-based approaches. The ROI-based analysis showed that FAB scores correlated with the rCMglc of the dorsolateral prefrontal cortices. Voxel-based approach revealed significant positive correlations between FAB scores and rCMglc which were in various cortical regions including the temporal and parietal cortices as well as frontal regions, independent of age, gender, and education. After controlling the effect of global disease severity with Mini-Mental State Examination score, significant positive correlation was found only in the bilateral prefrontal regions. Although FAB scores are influenced by temporoparietal dysfunction due to the overall progression of AD, it likely reflects prefrontal dysfunction specifically regardless of global cognitive state or disease severity in patients with AD. © The Author(s) 2015.

Modulational Instability of Cylindrical and Spherical NLS Equations. Statistical Approach

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

Grecu, A. T.; Grecu, D.; Visinescu, Anca

2010-01-21

The modulational (Benjamin-Feir) instability for cylindrical and spherical NLS equations (c/s NLS equations) is studied using a statistical approach (SAMI). A kinetic equation for a two-point correlation function is written and analyzed using the Wigner-Moyal transform. The linear stability of the Fourier transform of the two-point correlation function is studied and an implicit integral form for the dispersion relation is found. This is solved for different expressions of the initial spectrum (delta-spectrum, Lorentzian, Gaussian), and in the case of a Lorentzian spectrum the total growth of the instability is calculated. The similarities and differences with the usual one-dimensional NLS equationmore » are emphasized.« less

Image correlation microscopy for uniform illumination.

PubMed

Gaborski, T R; Sealander, M N; Ehrenberg, M; Waugh, R E; McGrath, J L

2010-01-01

Image cross-correlation microscopy is a technique that quantifies the motion of fluorescent features in an image by measuring the temporal autocorrelation function decay in a time-lapse image sequence. Image cross-correlation microscopy has traditionally employed laser-scanning microscopes because the technique emerged as an extension of laser-based fluorescence correlation spectroscopy. In this work, we show that image correlation can also be used to measure fluorescence dynamics in uniform illumination or wide-field imaging systems and we call our new approach uniform illumination image correlation microscopy. Wide-field microscopy is not only a simpler, less expensive imaging modality, but it offers the capability of greater temporal resolution over laser-scanning systems. In traditional laser-scanning image cross-correlation microscopy, lateral mobility is calculated from the temporal de-correlation of an image, where the characteristic length is the illuminating laser beam width. In wide-field microscopy, the diffusion length is defined by the feature size using the spatial autocorrelation function. Correlation function decay in time occurs as an object diffuses from its original position. We show that theoretical and simulated comparisons between Gaussian and uniform features indicate the temporal autocorrelation function depends strongly on particle size and not particle shape. In this report, we establish the relationships between the spatial autocorrelation function feature size, temporal autocorrelation function characteristic time and the diffusion coefficient for uniform illumination image correlation microscopy using analytical, Monte Carlo and experimental validation with particle tracking algorithms. Additionally, we demonstrate uniform illumination image correlation microscopy analysis of adhesion molecule domain aggregation and diffusion on the surface of human neutrophils.

Reliable computation from contextual correlations

NASA Astrophysics Data System (ADS)

Oestereich, André L.; Galvão, Ernesto F.

2017-12-01

An operational approach to the study of computation based on correlations considers black boxes with one-bit inputs and outputs, controlled by a limited classical computer capable only of performing sums modulo-two. In this setting, it was shown that noncontextual correlations do not provide any extra computational power, while contextual correlations were found to be necessary for the deterministic evaluation of nonlinear Boolean functions. Here we investigate the requirements for reliable computation in this setting; that is, the evaluation of any Boolean function with success probability bounded away from 1 /2 . We show that bipartite CHSH quantum correlations suffice for reliable computation. We also prove that an arbitrarily small violation of a multipartite Greenberger-Horne-Zeilinger noncontextuality inequality also suffices for reliable computation.

Functional Anthology of Intrinsic Disorder. II. Cellular Components, Domains, Technical Terms, Developmental Processes and Coding Sequence Diversities Correlated with Long Disordered Regions

PubMed Central

Vucetic, Slobodan; Xie, Hongbo; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Obradovic, Zoran; Uversky, Vladimir N.

2008-01-01

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie H., Vucetic S., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. I. Biological processes and functions of proteins with long disordered regions. J. Proteome Res.). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes ~90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes and coding sequence diversities possessing strong positive and negative correlation with long disordered regions. PMID:17391015

Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions.

PubMed

Vucetic, Slobodan; Xie, Hongbo; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Obradovic, Zoran; Uversky, Vladimir N

2007-05-01

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes approximately 90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions.

Design of exchange-correlation functionals through the correlation factor approach

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

Pavlíková Přecechtělová, Jana, E-mail: j.precechtelova@gmail.com, E-mail: Matthias.Ernzerhof@UMontreal.ca; Institut für Chemie, Theoretische Chemie / Quantenchemie, Sekr. C7, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin; Bahmann, Hilke

The correlation factor model is developed in which the spherically averaged exchange-correlation hole of Kohn-Sham theory is factorized into an exchange hole model and a correlation factor. The exchange hole model reproduces the exact exchange energy per particle. The correlation factor is constructed in such a manner that the exchange-correlation energy correctly reduces to exact exchange in the high density and rapidly varying limits. Four different correlation factor models are presented which satisfy varying sets of physical constraints. Three models are free from empirical adjustments to experimental data, while one correlation factor model draws on one empirical parameter. The correlationmore » factor models are derived in detail and the resulting exchange-correlation holes are analyzed. Furthermore, the exchange-correlation energies obtained from the correlation factor models are employed to calculate total energies, atomization energies, and barrier heights. It is shown that accurate, non-empirical functionals can be constructed building on exact exchange. Avenues for further improvements are outlined as well.« less

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.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-03-01

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

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

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

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE PAGES

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu; ...

2016-11-09

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

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.

Functional segregation of the human cingulate cortex is confirmed by functional connectivity based neuroanatomical parcellation.

PubMed

Yu, Chunshui; Zhou, Yuan; Liu, Yong; Jiang, Tianzi; Dong, Haiwei; Zhang, Yunting; Walter, Martin

2011-02-14

The four-region model with 7 specified subregions represents a theoretical construct of functionally segregated divisions of the cingulate cortex based on integrated neurobiological assessments. Under this framework, we aimed to investigate the functional specialization of the human cingulate cortex by analyzing the resting-state functional connectivity (FC) of each subregion from a network perspective. In 20 healthy subjects we systematically investigated the FC patterns of the bilateral subgenual (sACC) and pregenual (pACC) anterior cingulate cortices, anterior (aMCC) and posterior (pMCC) midcingulate cortices, dorsal (dPCC) and ventral (vPCC) posterior cingulate cortices and retrosplenial cortices (RSC). We found that each cingulate subregion was specifically integrated in the predescribed functional networks and showed anti-correlated resting-state fluctuations. The sACC and pACC were involved in an affective network and anti-correlated with the sensorimotor and cognitive networks, while the pACC also correlated with the default-mode network and anti-correlated with the visual network. In the midcingulate cortex, however, the aMCC was correlated with the cognitive and sensorimotor networks and anti-correlated with the visual, affective and default-mode networks, whereas the pMCC only correlated with the sensorimotor network and anti-correlated with the cognitive and visual networks. The dPCC and vPCC involved in the default-mode network and anti-correlated with the sensorimotor, cognitive and visual networks, in contrast, the RSC was mainly correlated with the PCC and thalamus. Based on a strong hypothesis driven approach of anatomical partitions of the cingulate cortex, we could confirm their segregation in terms of functional neuroanatomy, as suggested earlier by task studies or exploratory multi-seed investigations. Copyright © 2010 Elsevier Inc. All rights reserved.

Classical density functional theory and the phase-field crystal method using a rational function to describe the two-body direct correlation function.

PubMed

Pisutha-Arnond, N; Chan, V W L; Iyer, M; Gavini, V; Thornton, K

2013-01-01

We introduce a new approach to represent a two-body direct correlation function (DCF) in order to alleviate the computational demand of classical density functional theory (CDFT) and enhance the predictive capability of the phase-field crystal (PFC) method. The approach utilizes a rational function fit (RFF) to approximate the two-body DCF in Fourier space. We use the RFF to show that short-wavelength contributions of the two-body DCF play an important role in determining the thermodynamic properties of materials. We further show that using the RFF to empirically parametrize the two-body DCF allows us to obtain the thermodynamic properties of solids and liquids that agree with the results of CDFT simulations with the full two-body DCF without incurring significant computational costs. In addition, the RFF can also be used to improve the representation of the two-body DCF in the PFC method. Last, the RFF allows for a real-space reformulation of the CDFT and PFC method, which enables descriptions of nonperiodic systems and the use of nonuniform and adaptive grids.

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011

Assessing Hubbard-corrected AM05+ U and PBEsol+ U density functionals for strongly correlated oxides CeO 2 and Ce 2O 3

DOE PAGES

Weck, Philippe F.; Kim, Eunja

2016-09-12

The structure–property relationships of bulk CeO 2 and Ce 2O 3 have been investigated using AM05 and PBEsol exchange–correlation functionals within the frameworks of Hubbard-corrected density functional theory (DFT+ U) and density functional perturbation theory (DFPT+ U). Compared with conventional PBE+ U, RPBE+ U, PW91+ U and LDA+ U functionals, AM05+ U and PBEsol+ U describe experimental crystalline parameters and properties of CeO 2 and Ce 2O 3 with superior accuracy, especially when + U is chosen close to its value derived by the linear-response approach. Lastly, the present findings call for a reexamination of some of the problematic oxidemore » materials featuring strong f- and d-electron correlation using AM05+ U and PBEsol+ U.« less

Assessing Hubbard-corrected AM05+ U and PBEsol+ U density functionals for strongly correlated oxides CeO 2 and Ce 2O 3

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

Weck, Philippe F.; Kim, Eunja

The structure–property relationships of bulk CeO 2 and Ce 2O 3 have been investigated using AM05 and PBEsol exchange–correlation functionals within the frameworks of Hubbard-corrected density functional theory (DFT+ U) and density functional perturbation theory (DFPT+ U). Compared with conventional PBE+ U, RPBE+ U, PW91+ U and LDA+ U functionals, AM05+ U and PBEsol+ U describe experimental crystalline parameters and properties of CeO 2 and Ce 2O 3 with superior accuracy, especially when + U is chosen close to its value derived by the linear-response approach. Lastly, the present findings call for a reexamination of some of the problematic oxidemore » materials featuring strong f- and d-electron correlation using AM05+ U and PBEsol+ U.« less

Lanczos algorithm with matrix product states for dynamical correlation functions

NASA Astrophysics Data System (ADS)

Dargel, P. E.; Wöllert, A.; Honecker, A.; McCulloch, I. P.; Schollwöck, U.; Pruschke, T.

2012-05-01

The density-matrix renormalization group (DMRG) algorithm can be adapted to the calculation of dynamical correlation functions in various ways which all represent compromises between computational efficiency and physical accuracy. In this paper we reconsider the oldest approach based on a suitable Lanczos-generated approximate basis and implement it using matrix product states (MPS) for the representation of the basis states. The direct use of matrix product states combined with an ex post reorthogonalization method allows us to avoid several shortcomings of the original approach, namely the multitargeting and the approximate representation of the Hamiltonian inherent in earlier Lanczos-method implementations in the DMRG framework, and to deal with the ghost problem of Lanczos methods, leading to a much better convergence of the spectral weights and poles. We present results for the dynamic spin structure factor of the spin-1/2 antiferromagnetic Heisenberg chain. A comparison to Bethe ansatz results in the thermodynamic limit reveals that the MPS-based Lanczos approach is much more accurate than earlier approaches at minor additional numerical cost.

The Heats of Formation of GaCl3 and its Fragments

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Arnold, James (Technical Monitor)

1998-01-01

The heats of formation of GaC13 and its fragments are computed. The geometries and frequencies are obtained at the B3LYP level. The CCSD(T) approach is used to solve the correlation problem. The effect of Ga 3d correlation is studied, and found to affect the bond energies by up to 1 kcal/mol. Both basis set extrapolation and bond functions are considered as ways to approach the basis set limit. Spin-orbit and scalar relativistic effects are also considered.

Development and application of a 2-electron reduced density matrix approach to electron transport via molecular junctions

NASA Astrophysics Data System (ADS)

Hoy, Erik P.; Mazziotti, David A.; Seideman, Tamar

2017-11-01

Can an electronic device be constructed using only a single molecule? Since this question was first asked by Aviram and Ratner in the 1970s [Chem. Phys. Lett. 29, 277 (1974)], the field of molecular electronics has exploded with significant experimental advancements in the understanding of the charge transport properties of single molecule devices. Efforts to explain the results of these experiments and identify promising new candidate molecules for molecular devices have led to the development of numerous new theoretical methods including the current standard theoretical approach for studying single molecule charge transport, i.e., the non-equilibrium Green's function formalism (NEGF). By pairing this formalism with density functional theory (DFT), a wide variety of transport problems in molecular junctions have been successfully treated. For some systems though, the conductance and current-voltage curves predicted by common DFT functionals can be several orders of magnitude above experimental results. In addition, since density functional theory relies on approximations to the exact exchange-correlation functional, the predicted transport properties can show significant variation depending on the functional chosen. As a first step to addressing this issue, the authors have replaced density functional theory in the NEGF formalism with a 2-electron reduced density matrix (2-RDM) method, creating a new approach known as the NEGF-RDM method. 2-RDM methods provide a more accurate description of electron correlation compared to density functional theory, and they have lower computational scaling compared to wavefunction based methods of similar accuracy. Additionally, 2-RDM methods are capable of capturing static electron correlation which is untreatable by existing NEGF-DFT methods. When studying dithiol alkane chains and dithiol benzene in model junctions, the authors found that the NEGF-RDM predicts conductances and currents that are 1-2 orders of magnitude below those of B3LYP and M06 DFT functionals. This suggests that the NEGF-RDM method could be a viable alternative to NEGF-DFT for molecular junction calculations.

A systematic way for the cost reduction of density fitting methods

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

Kállay, Mihály, E-mail: kallay@mail.bme.hu

2014-12-28

We present a simple approach for the reduction of the size of auxiliary basis sets used in methods exploiting the density fitting (resolution of identity) approximation for electron repulsion integrals. Starting out of the singular value decomposition of three-center two-electron integrals, new auxiliary functions are constructed as linear combinations of the original fitting functions. The new functions, which we term natural auxiliary functions (NAFs), are analogous to the natural orbitals widely used for the cost reduction of correlation methods. The use of the NAF basis enables the systematic truncation of the fitting basis, and thereby potentially the reduction of themore » computational expenses of the methods, though the scaling with the system size is not altered. The performance of the new approach has been tested for several quantum chemical methods. It is demonstrated that the most pronounced gain in computational efficiency can be expected for iterative models which scale quadratically with the size of the fitting basis set, such as the direct random phase approximation. The approach also has the promise of accelerating local correlation methods, for which the processing of three-center Coulomb integrals is a bottleneck.« less

GW electronic Correlations in Quantum Transport : Renormalization and finite lifetime effects on real systems

NASA Astrophysics Data System (ADS)

Darancet, Pierre; Ferretti, Andrea; Mayou, Didier; Olevano, Valerio

2007-03-01

We present an ab initio approach to electronic transport in nanoscale systems which includes electronic correlations through the GW approximation. With respect to Landauer approaches based on density-functional theory (DFT), we introduce a physical quasiparticle electronic-structure into a non-equilibrium Green's function theory framework. We use an equilibrium non-selfconsistent G^0W^0 self-energy considering both full non-hermiticity and dynamical effects. The method is applied to a real system, a gold mono-atomic chain. With respect to DFT results, the conductance profile is modified and reduced by to the introduction of diffusion and loss-of-coherence effects. The linear response conductance characteristic appear to be in agreement with experimental results.

Coherence and dimensionality of intense spatiospectral twin beams

NASA Astrophysics Data System (ADS)

Peřina, Jan

2015-07-01

Spatiospectral properties of twin beams at their transition from low to high intensities are analyzed in parametric and paraxial approximations using decomposition into paired spatial and spectral modes. Intensity auto- and cross-correlation functions are determined and compared in the spectral and temporal domains as well as the transverse wave-vector and crystal output planes. Whereas the spectral, temporal, and transverse wave-vector coherence increases with the increasing pump intensity, coherence in the crystal output plane is almost independent of the pump intensity owing to the mode structure in this plane. The corresponding auto- and cross-correlation functions approach each other for larger pump intensities. The entanglement dimensionality of a twin beam is determined with a comparison of several approaches.

Clinical, Functional, and Biological Correlates of Cognitive Dimensions in Major Depressive Disorder – Rationale, Design, and Characteristics of the Cognitive Function and Mood Study (CoFaM-Study)

PubMed Central

Baune, Bernhard T.; Air, Tracy

2016-01-01

Cross-sectional and longitudinal studies exploring clinical, functional, and biological correlates of major depressive disorder are frequent. In this type of research, depression is most commonly defined as a categorical diagnosis based on studies using diagnostic instruments. Given the phenotypic and biological heterogeneity of depression, we chose to focus the phenotypic assessments on three cognitive dimensions of depression including (a) cognitive performance, (b) emotion processing, and (c) social cognitive functioning. Hence, the overall aim of the study is to investigate the long-term clinical course of these cognitive dimensions in depression and its functional (psychosocial) correlates. We also aim to identify biological “genomic” correlates of these three cognitive dimensions of depression. To address the above overall aim, we created the Cognition and Mood Study (CoFaMS) with the key objective to investigate the clinical, functional, and biological correlates of cognitive dimensions of depression by employing a prospective study design and including a healthy control group. The study commenced in April 2015, including patients with a primary diagnosis of a major depressive episode of major depressive disorder or bipolar disorder according to DSM-IV-TR criteria. The assessments cover the three cognitive dimensions of depression (cognitive performance, emotion processing, and social cognition), cognitive function screening instrument, plus functional scales to assess general, work place, and psychosocial function, depression symptom scales, and clinical course of illness. Blood is collected for comprehensive genomic discovery analyses of biological correlates of cognitive dimensions of depression. The CoFaM-Study represents an innovative approach focusing on cognitive dimensions of depression and its functional and biological “genomic” correlates. The CoFaMS team welcomes collaborations with both national and international researchers. PMID:27616997

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

PubMed Central

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779

Universal spatial correlation functions for describing and reconstructing soil microstructure.

PubMed

Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.

Clinical, Functional, and Biological Correlates of Cognitive Dimensions in Major Depressive Disorder - Rationale, Design, and Characteristics of the Cognitive Function and Mood Study (CoFaM-Study).

PubMed

Baune, Bernhard T; Air, Tracy

2016-01-01

Cross-sectional and longitudinal studies exploring clinical, functional, and biological correlates of major depressive disorder are frequent. In this type of research, depression is most commonly defined as a categorical diagnosis based on studies using diagnostic instruments. Given the phenotypic and biological heterogeneity of depression, we chose to focus the phenotypic assessments on three cognitive dimensions of depression including (a) cognitive performance, (b) emotion processing, and (c) social cognitive functioning. Hence, the overall aim of the study is to investigate the long-term clinical course of these cognitive dimensions in depression and its functional (psychosocial) correlates. We also aim to identify biological "genomic" correlates of these three cognitive dimensions of depression. To address the above overall aim, we created the Cognition and Mood Study (CoFaMS) with the key objective to investigate the clinical, functional, and biological correlates of cognitive dimensions of depression by employing a prospective study design and including a healthy control group. The study commenced in April 2015, including patients with a primary diagnosis of a major depressive episode of major depressive disorder or bipolar disorder according to DSM-IV-TR criteria. The assessments cover the three cognitive dimensions of depression (cognitive performance, emotion processing, and social cognition), cognitive function screening instrument, plus functional scales to assess general, work place, and psychosocial function, depression symptom scales, and clinical course of illness. Blood is collected for comprehensive genomic discovery analyses of biological correlates of cognitive dimensions of depression. The CoFaM-Study represents an innovative approach focusing on cognitive dimensions of depression and its functional and biological "genomic" correlates. The CoFaMS team welcomes collaborations with both national and international researchers.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function.

PubMed

Levashov, V A

2017-11-14

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2017-11-01

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Analyses of Third Order Bose-Einstein Correlation by Means of Coulomb Wave Function

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

Biyajima, Minoru; Mizoguchi, Takuya; Suzuki, Naomichi

2006-04-11

In order to include a correction by the Coulomb interaction in Bose-Einstein correlation (BEC), the wave function for the Coulomb scattering were introduced in the quantum optical approach to BEC in the previous work. If we formulate the amplitude written by Coulomb wave functions according to the diagram for BEC in the plane wave formulation, the formula for 3{pi} -BEC becomes simpler than that of our previous work. We re-analyze the raw data of 3{pi} -BEC by NA44 and STAR Collaborations by this formula. Results are compared with the previous ones.

Partial Roc Reveals Superiority of Mutual Rank of Pearson's Correlation Coefficient as a Coexpression Measure to Elucidate Functional Association of Genes

NASA Astrophysics Data System (ADS)

Obayashi, Takeshi; Kinoshita, Kengo

2013-01-01

Gene coexpression analysis is a powerful approach to elucidate gene function. We have established and developed this approach using vast amount of publicly available gene expression data measured by microarray techniques. The coexpressed genes are used to estimate gene function of the guide gene or to construct gene coexpression networks. In the case to construct gene networks, researchers should introduce an arbitrary threshold of gene coexpression, because gene coexpression value is continuous value. In the viewpoint to introduce common threshold of gene coexpression, we previously reported rank of Pearson's correlation coefficient (PCC) is more useful than the original PCC value. In this manuscript, we re-assessed the measure of gene coexpression to construct gene coexpression network, and found that mutual rank (MR) of PCC showed better performance than rank of PCC and the original PCC in low false positive rate.

Spectral analysis of pair-correlation bandwidth: application to cell biology images.

PubMed

Binder, Benjamin J; Simpson, Matthew J

2015-02-01

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

Spectral functions at small energies and the electrical conductivity in hot quenched lattice QCD.

PubMed

Aarts, Gert; Allton, Chris; Foley, Justin; Hands, Simon; Kim, Seyong

2007-07-13

In lattice QCD, the maximum entropy method can be used to reconstruct spectral functions from Euclidean correlators obtained in numerical simulations. We show that at finite temperature the most commonly used algorithm, employing Bryan's method, is inherently unstable at small energies and gives a modification that avoids this. We demonstrate this approach using the vector current-current correlator obtained in quenched QCD at finite temperature. Our first results indicate a small electrical conductivity above the deconfinement transition.

Properties of atomic pairs produced in the collision of Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Ziń, Paweł; Wasak, Tomasz

2018-04-01

During a collision of Bose-Einstein condensates correlated pairs of atoms are emitted. The scattered massive particles, in analogy to photon pairs in quantum optics, might be used in the violation of Bell's inequalities, demonstration of Einstein-Podolsky-Rosen correlations, or sub-shot-noise atomic interferometry. Usually, a theoretical description of the collision relies either on stochastic numerical methods or on analytical treatments involving various approximations. Here, we investigate elastic scattering of atoms from colliding elongated Bose-Einstein condensates within the Bogoliubov method, carefully controlling performed approximations at every stage of the analysis. We derive expressions for the one- and two-particle correlation functions. The obtained formulas, which relate the correlation functions to the condensate wave function, are convenient for numerical calculations. We employ the variational approach for condensate wave functions to obtain analytical expressions for the correlation functions, whose properties we analyze in detail. We also present a useful semiclassical model of the process and compare its results with the quantum one. The results are relevant for recent experiments with excited helium atoms, as well as for planned experiments aimed at investigating the nonclassicality of the system.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

PubMed

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2008-02-15

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

A Method for Functional Network Connectivity Among Spatially Independent Resting-State Components in Schizophrenia

PubMed Central

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2011-01-01

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. PMID:18082428

An Investigation of Possible Correlations Between Individual Pilot Performance and Neurological Functions.

DTIC Science & Technology

1977-05-23

ed these findings with tests on peptic ulcer patients.1’ In 1949, Sau l , using a psychoanalytic approach in searching for correlates of personality...this area : PILOT PERFOR MANCE ANA L YSIS 1) With respect to the system developed and used for this study, research should be conducted to determine

Generating series for GUE correlators

NASA Astrophysics Data System (ADS)

Dubrovin, Boris; Yang, Di

2017-11-01

We extend to the Toda lattice hierarchy the approach of Bertola et al. (Phys D Nonlinear Phenom 327:30-57, 2016; IMRN, 2016) to computation of logarithmic derivatives of tau-functions in terms of the so-called matrix resolvents of the corresponding difference Lax operator. As a particular application we obtain explicit generating series for connected GUE correlators. On this basis an efficient recursive procedure for computing the correlators in full genera is developed.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Increasing the applicability of density functional theory. IV. Consequences of ionization-potential improved exchange-correlation potentials.

PubMed

Verma, Prakash; Bartlett, Rodney J

2014-05-14

This paper's objective is to create a "consistent" mean-field based Kohn-Sham (KS) density functional theory (DFT) meaning the functional should not only provide good total energy properties, but also the corresponding KS eigenvalues should be accurate approximations to the vertical ionization potentials (VIPs) of the molecule, as the latter condition attests to the viability of the exchange-correlation potential (VXC). None of the prominently used DFT approaches show these properties: the optimized effective potential VXC based ab initio dft does. A local, range-separated hybrid potential cam-QTP-00 is introduced as the basis for a "consistent" KS DFT approach. The computed VIPs as the negative of KS eigenvalue have a mean absolute error of 0.8 eV for an extensive set of molecule's electron ionizations, including the core. Barrier heights, equilibrium geometries, and magnetic properties obtained from the potential are in good agreement with experiment. A similar accuracy with less computational efforts can be achieved by using a non-variational global hybrid variant of the QTP-00 approach.

Correlational signatures of time-reversal symmetry breaking in two-dimensional flow

NASA Astrophysics Data System (ADS)

Hogg, Charlie; Ouellette, Nicholas

2015-11-01

Classical turbulence theories posit that broken spatial symmetries should be (statistically) restored at small scales. But since turbulent flows are inherently dissipative, time reversal symmetry is expected to remain broken throughout the cascade. However, the precise dynamical signature of this broken symmetry is not well understood. Recent work has shed new light on this fundamental question by considering the Lagrangian structure functions of power. Here, we take a somewhat different approach by studying the Lagrangian correlation functions of velocity and acceleration. We measured these correlations using particle tracking velocimetry in a quasi-two-dimensional electromagnetically driven flow that displayed net inverse energy transfer. We show that the correlation functions of the velocity and acceleration magnitudes are not symmetric in time, and that the degree of asymmetry can be related to the flux of energy between scales, suggesting that the asymmetry has a dynamical origin.

Temporal cross-correlation asymmetry and departure from equilibrium in a bistable chemical system.

PubMed

Bianca, C; Lemarchand, A

2014-06-14

This paper aims at determining sustained reaction fluxes in a nonlinear chemical system driven in a nonequilibrium steady state. The method relies on the computation of cross-correlation functions for the internal fluctuations of chemical species concentrations. By employing Langevin-type equations, we derive approximate analytical formulas for the cross-correlation functions associated with nonlinear dynamics. Kinetic Monte Carlo simulations of the chemical master equation are performed in order to check the validity of the Langevin equations for a bistable chemical system. The two approaches are found in excellent agreement, except for critical parameter values where the bifurcation between monostability and bistability occurs. From the theoretical point of view, the results imply that the behavior of cross-correlation functions cannot be exploited to measure sustained reaction fluxes in a specific nonlinear system without the prior knowledge of the associated chemical mechanism and the rate constants.

Brain Structure and Resting-State Functional Connectivity in University Professors with High Academic Achievement

ERIC Educational Resources Information Center

Li, Weiwei; Yang, Wenjing; Li, Wenfu; Li, Yadan; Wei, Dongtao; Li, Huimin; Qiu, Jiang; Zhang, Qinglin

2015-01-01

Creative persons play an important role in technical innovation and social progress. There is little research on the neural correlates with researchers with high academic achievement. We used a combined structural (regional gray matter volume, rGMV) and functional (resting-state functional connectivity analysis, rsFC) approach to examine the…

Correlation between sexual function and postrenal transplant quality of life: does gender matter?

PubMed

Tavallaii, Seyed Abbas; Fathi-Ashtiani, Ali; Nasiri, Mahmoud; Assari, Shervin; Maleki, Pouria; Einollahi, Behzad

2007-11-01

Subjective health perceptions affect sexual function differently in males and females; such differences, however, have not hitherto been studied comprehensively in kidney-transplant recipients. This study sought to investigate gender effect on the correlation between sexual function and quality-of-life (QOL) subdomains in kidney-transplant recipients by evaluating intercourse frequency (IF) and intercourse satisfaction (IS). In a cross-sectional study, 124 married kidney-transplant recipients, who were randomly selected, were interviewed. The bivariate correlations between QOL subdomains, and IF and IS were analyzed with the Pearson test in the males and females, separately. The IF and IS using the relationship and sexuality scale, and also the QOL using Short Form 36 (SF-36) were assessed. Sixty-seven subjects (54%) reported having no intercourse within the preceding months. Fifty subjects (40%) reported having no intercourse satisfaction. While IF and IS correlated with the total SF-36 score in the males (r = 0.252 and 0.263, P < 0.05), there was no such correlation in the females. In the males, IS correlated with physical health (r = 0.281, P < 0.05) and physical function (r = 0.274, P < 0.05), and there was a correlation between IF and role limitation due to emotional problems (r = 0.250, P < 0.05). In the females, whereas IF correlated with general health (r = 0.372, P < 0.05) and mental health (r = 0.305, P < 0.05), there was no correlation between IS and QOL subdomains (P > 0.05). Sexual function and satisfaction seem to be correlated with mental and physical health in female and male kidney-transplant recipients, respectively. Although in the two genders, both physical and mental health should be equally evaluated; improving of the sexual function may be better achieved through different approaches.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

Universal freezing of quantum correlations within the geometric approach

PubMed Central

Cianciaruso, Marco; Bromley, Thomas R.; Roga, Wojciech; Lo Franco, Rosario; Adesso, Gerardo

2015-01-01

Quantum correlations in a composite system can be measured by resorting to a geometric approach, according to which the distance from the state of the system to a suitable set of classically correlated states is considered. Here we show that all distance functions, which respect natural assumptions of invariance under transposition, convexity, and contractivity under quantum channels, give rise to geometric quantifiers of quantum correlations which exhibit the peculiar freezing phenomenon, i.e., remain constant during the evolution of a paradigmatic class of states of two qubits each independently interacting with a non-dissipative decohering environment. Our results demonstrate from first principles that freezing of geometric quantum correlations is independent of the adopted distance and therefore universal. This finding paves the way to a deeper physical interpretation and future practical exploitation of the phenomenon for noisy quantum technologies. PMID:26053239

Functional renormalization-group approaches, one-particle (irreducible) reducible with respect to local Green’s functions, with dynamical mean-field theory as a starting point

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

Katanin, A. A., E-mail: katanin@mail.ru

We consider formulations of the functional renormalization-group (fRG) flow for correlated electronic systems with the dynamical mean-field theory as a starting point. We classify the corresponding renormalization-group schemes into those neglecting one-particle irreducible six-point vertices (with respect to the local Green’s functions) and neglecting one-particle reducible six-point vertices. The former class is represented by the recently introduced DMF{sup 2}RG approach [31], but also by the scale-dependent generalization of the one-particle irreducible representation (with respect to local Green’s functions, 1PI-LGF) of the generating functional [20]. The second class is represented by the fRG flow within the dual fermion approach [16, 32].more » We compare formulations of the fRG approach in each of these cases and suggest their further application to study 2D systems within the Hubbard model.« less

Kinetic theory of coupled oscillators.

PubMed

Hildebrand, Eric J; Buice, Michael A; Chow, Carson C

2007-02-02

We present an approach for the description of fluctuations that are due to finite system size induced correlations in the Kuramoto model of coupled oscillators. We construct a hierarchy for the moments of the density of oscillators that is analogous to the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy in the kinetic theory of plasmas and gases. To calculate the lowest order system size effect, we truncate this hierarchy at second order and solve the resulting closed equations for the two-oscillator correlation function around the incoherent state. We use this correlation function to compute the fluctuations of the order parameter, including the effect of transients, and compare this computation with numerical simulations.

Spatial distribution of nuclei in progressive nucleation: Modeling and application

NASA Astrophysics Data System (ADS)

Tomellini, Massimo

2018-04-01

Phase transformations ruled by non-simultaneous nucleation and growth do not lead to random distribution of nuclei. Since nucleation is only allowed in the untransformed portion of space, positions of nuclei are correlated. In this article an analytical approach is presented for computing pair-correlation function of nuclei in progressive nucleation. This quantity is further employed for characterizing the spatial distribution of nuclei through the nearest neighbor distribution function. The modeling is developed for nucleation in 2D space with power growth law and it is applied to describe electrochemical nucleation where correlation effects are significant. Comparison with both computer simulations and experimental data lends support to the model which gives insights into the transition from Poissonian to correlated nearest neighbor probability density.

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

PubMed

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

Bulk dynamics of Brownian hard disks: Dynamical density functional theory versus experiments on two-dimensional colloidal hard spheres

NASA Astrophysics Data System (ADS)

Stopper, Daniel; Thorneywork, Alice L.; Dullens, Roel P. A.; Roth, Roland

2018-03-01

Using dynamical density functional theory (DDFT), we theoretically study Brownian self-diffusion and structural relaxation of hard disks and compare to experimental results on quasi two-dimensional colloidal hard spheres. To this end, we calculate the self-van Hove correlation function and distinct van Hove correlation function by extending a recently proposed DDFT-approach for three-dimensional systems to two dimensions. We find that the theoretical results for both self-part and distinct part of the van Hove function are in very good quantitative agreement with the experiments up to relatively high fluid packing fractions of roughly 0.60. However, at even higher densities, deviations between the experiment and the theoretical approach become clearly visible. Upon increasing packing fraction, in experiments, the short-time self-diffusive behavior is strongly affected by hydrodynamic effects and leads to a significant decrease in the respective mean-squared displacement. By contrast, and in accordance with previous simulation studies, the present DDFT, which neglects hydrodynamic effects, shows no dependence on the particle density for this quantity.

Thresholding functional connectomes by means of mixture modeling.

PubMed

Bielczyk, Natalia Z; Walocha, Fabian; Ebel, Patrick W; Haak, Koen V; Llera, Alberto; Buitelaar, Jan K; Glennon, Jeffrey C; Beckmann, Christian F

2018-05-01

Functional connectivity has been shown to be a very promising tool for studying the large-scale functional architecture of the human brain. In network research in fMRI, functional connectivity is considered as a set of pair-wise interactions between the nodes of the network. These interactions are typically operationalized through the full or partial correlation between all pairs of regional time series. Estimating the structure of the latent underlying functional connectome from the set of pair-wise partial correlations remains an open research problem though. Typically, this thresholding problem is approached by proportional thresholding, or by means of parametric or non-parametric permutation testing across a cohort of subjects at each possible connection. As an alternative, we propose a data-driven thresholding approach for network matrices on the basis of mixture modeling. This approach allows for creating subject-specific sparse connectomes by modeling the full set of partial correlations as a mixture of low correlation values associated with weak or unreliable edges in the connectome and a sparse set of reliable connections. Consequently, we propose to use alternative thresholding strategy based on the model fit using pseudo-False Discovery Rates derived on the basis of the empirical null estimated as part of the mixture distribution. We evaluate the method on synthetic benchmark fMRI datasets where the underlying network structure is known, and demonstrate that it gives improved performance with respect to the alternative methods for thresholding connectomes, given the canonical thresholding levels. We also demonstrate that mixture modeling gives highly reproducible results when applied to the functional connectomes of the visual system derived from the n-back Working Memory task in the Human Connectome Project. The sparse connectomes obtained from mixture modeling are further discussed in the light of the previous knowledge of the functional architecture of the visual system in humans. We also demonstrate that with use of our method, we are able to extract similar information on the group level as can be achieved with permutation testing even though these two methods are not equivalent. We demonstrate that with both of these methods, we obtain functional decoupling between the two hemispheres in the higher order areas of the visual cortex during visual stimulation as compared to the resting state, which is in line with previous studies suggesting lateralization in the visual processing. However, as opposed to permutation testing, our approach does not require inference at the cohort level and can be used for creating sparse connectomes at the level of a single subject. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Using a Multi-Trait Approach to Manipulate Plant Functional Diversity in a Biodiversity-Ecosystem Function Experiment

PubMed Central

Schittko, Conrad; Hawa, Mahmoud; Wurst, Susanne

2014-01-01

A frequent pattern emerging from biodiversity-ecosystem function studies is that functional group richness enhances ecosystem functions such as primary productivity. However, the manipulation of functional group richness goes along with major disadvantages like the transformation of functional trait data into categories or the exclusion of functional differences between organisms in the same group. In a mesocosm study we manipulated plant functional diversity based on the multi-trait Functional Diversity (FD)-approach of Petchey and Gaston by using database data of seven functional traits and information on the origin of the species in terms of being native or exotic. Along a gradient ranging from low to high FD we planted 40 randomly selected eight-species mixtures under controlled conditions. We found a significant positive linear correlation of FD with aboveground productivity and a negative correlation with invasibility of the plant communities. Based on community-weighted mean calculations for each functional trait, we figured out that the traits N-fixation and species origin, i.e. being native or exotic, played the most important role for community productivity. Our results suggest that the identification of the impact of functional trait diversity and the relative contributions of relevant traits is essential for a mechanistic understanding of the role of biodiversity for ecosystem functions such as aboveground biomass production and resistance against invasion. PMID:24897501

Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

NASA Astrophysics Data System (ADS)

Angulo, Raul E.; Hilbert, Stefan

2015-03-01

We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.

PubMed

Jiang, Z; Chen, W; Burkhart, C

2013-11-01

Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Ionic Asymmetry and Solvent Excluded Volume Effects on Spherical Electric Double Layers: A Density Functional Approach

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

Medasani, Bharat; Ovanesyan, Zaven; Thomas, Dennis G.

In this article we present a classical density functional theory for electrical double layers of spherical macroions that extends the capabilities of conventional approaches by accounting for electrostatic ion correlations, size asymmetry and excluded volume effects. The approach is based on a recent approximation introduced by Hansen-Goos and Roth for the hard sphere excess free energy of inhomogeneous fluids (J. Chem. Phys. 124, 154506). It accounts for the proper and efficient description of the effects of ionic asymmetry and solvent excluded volume, especially at high ion concentrations and size asymmetry ratios including those observed in experimental studies. Additionally, we utilizemore » a leading functional Taylor expansion approximation of the ion density profiles. In addition, we use the Mean Spherical Approximation for multi-component charged hard sphere fluids to account for the electrostatic ion correlation effects. These approximations are implemented in our theoretical formulation into a suitable decomposition of the excess free energy which plays a key role in capturing the complex interplay between charge correlations and excluded volume effects. We perform Monte Carlo simulations in various scenarios to validate the proposed approach, obtaining a good compromise between accuracy and computational cost. We use the proposed computational approach to study the effects of ion size, ion size asymmetry and solvent excluded volume on the ion profiles, integrated charge, mean electrostatic potential, and ionic coordination number around spherical macroions in various electrolyte mixtures. Our results show that both solvent hard sphere diameter and density play a dominant role in the distribution of ions around spherical macroions, mainly for experimental water molarity and size values where the counterion distribution is characterized by a tight binding to the macroion, similar to that predicted by the Stern model.« less

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

Hégely, Bence; Nagy, Péter R.; Kállay, Mihály, E-mail: kallay@mail.bme.hu

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up themore » system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.« less

Influence of molecular geometry, exchange-correlation functional, and solvent effects in the modeling of vertical excitation energies in phthalocyanines using time-dependent density functional theory (TDDFT) and polarized continuum model TDDFT methods: can modern computational chemistry methods explain experimental controversies?

PubMed

Nemykin, Victor N; Hadt, Ryan G; Belosludov, Rodion V; Mizuseki, Hiroshi; Kawazoe, Yoshiyuki

2007-12-20

A time-dependent density functional theory (TDDFT) approach coupled with 14 different exchange-correlation functionals was used for the prediction of vertical excitation energies in zinc phthalocyanine (PcZn). In general, the TDDFT approach provides a more accurate description of both visible and ultraviolet regions of the UV-vis and magnetic circular dichroism (MCD) spectra of PcZn in comparison to the more popular semiempirical ZINDO/S and PM3 methods. It was found that the calculated vertical excitation energies of PcZn correlate with the amount of Hartree-Fock exchange involved in the exchange-correlation functional. The correlation was explained on the basis of the calculated difference in energy between occupied and unoccupied molecular orbitals. The influence of PcZn geometry, optimized using different exchange-correlation functionals, on the calculated vertical excitation energies in PcZn was found to be relatively small. The influence of solvents on the calculated vertical excitation energies in PcZn was considered for the first time using a polarized continuum model TDDFT (PCM-TDDFT) method and was found to be relatively small in excellent agreement with the experimental data. For all tested TDDFT and PCM-TDDFT cases, an assignment of the Q-band as an almost pure a1u (HOMO)-->eg (LUMO) transition, initially suggested by Gouterman, was confirmed. Pure exchange-correlation functionals indicate the presence of six 1Eu states in the B-band region of the UV-vis spectrum of PcZn, while hybrid exchange-correlation functionals predict only five 1Eu states for the same energy envelope. The first two symmetry-forbidden n-->pi* transitions were predicted in the Q0-2 region and in the low-energy tail of the B-band, while the first two symmetry-allowed n-->pi* transitions were found within the B-band energy envelope when pure exchange-correlation functionals were used for TDDFT calculations. The presence of a symmetry-forbidden but vibronically allowed n-->pi* transition in the Q0-2 spectral envelope explains the long-time controversy between the experimentally observed low-intensity transition in the Q0-2 region and previous semiempirical and TDDFT calculations, which were unable to predict any electronic transitions in this area. To prove the conceptual possibility of the presence of several degenerate 1Eu states in the B-band region of PcZn, room-temperature UV-vis and MCD spectra of zinc tetra-tert-butylphthalocyanine (PctZn) in non-coordinating solvents were recorded and analyzed using band deconvolution analysis. It was found that the B-band region of the UV-vis and MCD spectra of PctZn can be easily deconvoluted using six MCD Faraday A-terms and two MCD Faraday B-terms with energies close to those predicted by TDDFT calculations for 1Eu and 1A2u excited states, respectively. Such a good agreement between theory and experiment clearly indicates the possibility of employing a TDDFT approach for the accurate prediction of vertical excitation energies in phthalocyanines within a large energy range.

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

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

None, None

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE PAGES

None, None

2016-11-21

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

A functional architecture of the human brain: Emerging insights from the science of emotion

PubMed Central

Lindquist, Kristen A.; Barrett, Lisa Feldman

2012-01-01

The ‘faculty psychology’ approach to the mind, which attempts to explain mental function in terms of categories that reflect modular ‘faculties’, such as emotions, cognitions, and perceptions, has dominated research into the mind and its physical correlates. In this paper, we argue that brain organization does not respect the commonsense categories belonging to the faculty psychology approach. We review recent research from the science of emotion demonstrating that the human brain contains broadly distributed functional networks that can each be re-described as basic psychological operations that interact to produce a range of mental states, including, but not limited to, anger, sadness, fear, disgust, and so on. When compared to the faculty psychology approach, this ‘constructionist’ approach provides an alternative functional architecture to guide the design and interpretation of experiments in cognitive neuroscience. PMID:23036719

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Akın, Ata

2017-12-01

A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.

Neural network post-processing of grayscale optical correlator

NASA Technical Reports Server (NTRS)

Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

2005-01-01

In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

Approximating the Shifted Hartree-Exchange-Correlation Potential in Direct Energy Kohn-Sham Theory.

PubMed

Sharpe, Daniel J; Levy, Mel; Tozer, David J

2018-02-13

Levy and Zahariev [Phys. Rev. Lett. 113 113002 (2014)] have proposed a new approach for performing density functional theory calculations, termed direct energy Kohn-Sham (DEKS) theory. In this approach, the electronic energy equals the sum of orbital energies, obtained from Kohn-Sham-like orbital equations involving a shifted Hartree-exchange-correlation potential, which must be approximated. In the present study, density scaling homogeneity considerations are used to facilitate DEKS calculations on a series of atoms and molecules, leading to three nonlocal approximations to the shifted potential. The first two rely on preliminary Kohn-Sham calculations using a standard generalized gradient approximation (GGA) exchange-correlation functional and the results illustrate the benefit of describing the dominant Hartree component of the shift exactly. A uniform electron gas analysis is used to eliminate the need for these preliminary Kohn-Sham calculations, leading to a potential with an unconventional form that yields encouraging results, providing strong motivation for further research in DEKS theory.

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy

DOE PAGES

Liu, Yijin; Meirer, Florian; Krest, Courtney M.; ...

2016-08-30

To understand how hierarchically structured functional materials operate, analytical tools are needed that can reveal small structural and chemical details in large sample volumes. Often, a single method alone is not sufficient to get a complete picture of processes happening at multiple length scales. Here we present a correlative approach combining three-dimensional X-ray imaging techniques at different length scales for the analysis of metal poisoning of an individual catalyst particle. The correlative nature of the data allowed establishing a macro-pore network model that interprets metal accumulations as a resistance to mass transport and can, by tuning the effect of metalmore » deposition, simulate the response of the network to a virtual ageing of the catalyst particle. In conclusion, the developed approach is generally applicable and provides an unprecedented view on dynamic changes in a material’s pore space, which is an essential factor in the rational design of functional porous materials.« less

On the accuracy of density-functional theory exchange-correlation functionals for H bonds in small water clusters: Benchmarks approaching the complete basis set limit

NASA Astrophysics Data System (ADS)

Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias

2007-11-01

The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Møller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.

On the accuracy of density-functional theory exchange-correlation functionals for H bonds in small water clusters: benchmarks approaching the complete basis set limit.

PubMed

Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias

2007-11-14

The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Moller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.

A unified stochastic formulation of dissipative quantum dynamics. I. Generalized hierarchical equations

NASA Astrophysics Data System (ADS)

Hsieh, Chang-Yu; Cao, Jianshu

2018-01-01

We extend a standard stochastic theory to study open quantum systems coupled to a generic quantum environment. We exemplify the general framework by studying a two-level quantum system coupled bilinearly to the three fundamental classes of non-interacting particles: bosons, fermions, and spins. In this unified stochastic approach, the generalized stochastic Liouville equation (SLE) formally captures the exact quantum dissipations when noise variables with appropriate statistics for different bath models are applied. Anharmonic effects of a non-Gaussian bath are precisely encoded in the bath multi-time correlation functions that noise variables have to satisfy. Starting from the SLE, we devise a family of generalized hierarchical equations by averaging out the noise variables and expand bath multi-time correlation functions in a complete basis of orthonormal functions. The general hierarchical equations constitute systems of linear equations that provide numerically exact simulations of quantum dynamics. For bosonic bath models, our general hierarchical equation of motion reduces exactly to an extended version of hierarchical equation of motion which allows efficient simulation for arbitrary spectral densities and temperature regimes. Similar efficiency and flexibility can be achieved for the fermionic bath models within our formalism. The spin bath models can be simulated with two complementary approaches in the present formalism. (I) They can be viewed as an example of non-Gaussian bath models and be directly handled with the general hierarchical equation approach given their multi-time correlation functions. (II) Alternatively, each bath spin can be first mapped onto a pair of fermions and be treated as fermionic environments within the present formalism.

High-resolution definition of humoral immune response correlates of effective immunity against HIV.

PubMed

Alter, Galit; Dowell, Karen G; Brown, Eric P; Suscovich, Todd J; Mikhailova, Anastassia; Mahan, Alison E; Walker, Bruce D; Nimmerjahn, Falk; Bailey-Kellogg, Chris; Ackerman, Margaret E

2018-03-26

Defining correlates of immunity by comprehensively interrogating the extensive biological diversity in naturally or experimentally protected subjects may provide insights critical for guiding the development of effective vaccines and antibody-based therapies. We report advances in a humoral immunoprofiling approach and its application to elucidate hallmarks of effective HIV-1 viral control. Systematic serological analysis for a cohort of HIV-infected subjects with varying viral control was conducted using both a high-resolution, high-throughput biophysical antibody profiling approach, providing unbiased dissection of the humoral response, along with functional antibody assays, characterizing antibody-directed effector functions such as complement fixation and phagocytosis that are central to protective immunity. Profiles of subjects with varying viral control were computationally analyzed and modeled in order to deconvolute relationships among IgG Fab properties, Fc characteristics, and effector functions and to identify humoral correlates of potent antiviral antibody-directed effector activity and effective viral suppression. The resulting models reveal multifaceted and coordinated contributions of polyclonal antibodies to diverse antiviral responses, and suggest key biophysical features predictive of viral control. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Path integral approach to the Wigner representation of canonical density operators for discrete systems coupled to harmonic baths.

PubMed

Montoya-Castillo, Andrés; Reichman, David R

2017-01-14

We derive a semi-analytical form for the Wigner transform for the canonical density operator of a discrete system coupled to a harmonic bath based on the path integral expansion of the Boltzmann factor. The introduction of this simple and controllable approach allows for the exact rendering of the canonical distribution and permits systematic convergence of static properties with respect to the number of path integral steps. In addition, the expressions derived here provide an exact and facile interface with quasi- and semi-classical dynamical methods, which enables the direct calculation of equilibrium time correlation functions within a wide array of approaches. We demonstrate that the present method represents a practical path for the calculation of thermodynamic data for the spin-boson and related systems. We illustrate the power of the present approach by detailing the improvement of the quality of Ehrenfest theory for the correlation function C zz (t)=Re⟨σ z (0)σ z (t)⟩ for the spin-boson model with systematic convergence to the exact sampling function. Importantly, the numerically exact nature of the scheme presented here and its compatibility with semiclassical methods allows for the systematic testing of commonly used approximations for the Wigner-transformed canonical density.

Agreement in functional assessment: graphic approaches to displaying respondent effects.

PubMed

Haley, Stephen M; Ni, Pengsheng; Coster, Wendy J; Black-Schaffer, Randie; Siebens, Hilary; Tao, Wei

2006-09-01

The objective of this study was to examine the agreement between respondents of summary scores from items representing three functional content areas (physical and mobility, personal care and instrumental, applied cognition) within the Activity Measure for Postacute Care (AM-PAC). We compare proxy vs. patient report in both hospital and community settings as represented by intraclass correlation coefficients and two graphic approaches. The authors conducted a prospective, cohort study of a convenience sample of adults (n = 47) receiving rehabilitation services either in hospital (n = 31) or community (n = 16) settings. In addition to using intraclass correlation coefficients (ICC) as indices of agreement, we applied two graphic approaches to serve as complements to help interpret the direction and magnitude of respondent disagreements. We created a "mountain plot" based on a cumulative distribution curve and a "survival-agreement plot" with step functions used in the analysis of survival data. ICCs on summary scores between patient and proxy report were physical and mobility ICC = 0.92, personal care and instrumental ICC = 0.93, and applied cognition ICC = 0.77. Although combined respondent agreement was acceptable, graphic approaches helped interpret differences in separate analyses of clinician and family agreement. Graphic analyses allow for a simple interpretation of agreement data and may be useful in determining the meaningfulness of the amount and direction of interrespondent variation.

Towards an ab-initio treatment of nonlocal electronic correlations with dynamical vertex approximation

NASA Astrophysics Data System (ADS)

Galler, Anna; Gunacker, Patrik; Tomczak, Jan; Thunström, Patrik; Held, Karsten

Recently, approaches such as the dynamical vertex approximation (D ΓA) or the dual-fermion method have been developed. These diagrammatic approaches are going beyond dynamical mean field theory (DMFT) by including nonlocal electronic correlations on all length scales as well as the local DMFT correlations. Here we present our efforts to extend the D ΓA methodology to ab-initio materials calculations (ab-initio D ΓA). Our approach is a unifying framework which includes both GW and DMFT-type of diagrams, but also important nonlocal correlations beyond, e.g. nonlocal spin fluctuations. In our multi-band implementation we are using a worm sampling technique within continuous-time quantum Monte Carlo in the hybridization expansion to obtain the DMFT vertex, from which we construct the reducible vertex function using the two particle-hole ladders. As a first application we show results for transition metal oxides. Support by the ERC project AbinitioDGA (306447) is acknowledged.

Does the greater involvement of executive control in memory with age act as a compensatory mechanism?

PubMed

Bouazzaoui, Badiâa; Angel, Lucie; Fay, Séverine; Taconnat, Laurence; Charlotte, Froger; Isingrini, Michel

2014-03-01

Recent behavioural and imaging data have shown that memory functioning seems to rely more on executive functions and on the prefrontal cortex (PFC) in older than in young adults. Using a behavioural approach, our objective was to confirm the hypothesis that young and older adults present different patterns of correlation between episodic memory performance and executive functioning. We report three studies comparing the correlations of young and older adults in a broad range of episodic memory and executive function tasks. The results indicated that memory and executive performance were consistently and significantly correlated in older but not in younger adults. Regression analyses confirmed that age-related differences in episodic memory performance could be explained by individual differences in executive functioning. The results are consistent with the view that memory functioning in aging is accompanied by a shift from automatic to controlled forms of processing. They also generalise the executive hypothesis of episodic memory aging and are in line with the idea that executive functions act as a compensatory mechanism against age-related memory decline.

Efficient construction of exchange and correlation potentials by inverting the Kohn-Sham equations.

PubMed

Kananenka, Alexei A; Kohut, Sviataslau V; Gaiduk, Alex P; Ryabinkin, Ilya G; Staroverov, Viktor N

2013-08-21

Given a set of canonical Kohn-Sham orbitals, orbital energies, and an external potential for a many-electron system, one can invert the Kohn-Sham equations in a single step to obtain the corresponding exchange-correlation potential, vXC(r). For orbitals and orbital energies that are solutions of the Kohn-Sham equations with a multiplicative vXC(r) this procedure recovers vXC(r) (in the basis set limit), but for eigenfunctions of a non-multiplicative one-electron operator it produces an orbital-averaged potential. In particular, substitution of Hartree-Fock orbitals and eigenvalues into the Kohn-Sham inversion formula is a fast way to compute the Slater potential. In the same way, we efficiently construct orbital-averaged exchange and correlation potentials for hybrid and kinetic-energy-density-dependent functionals. We also show how the Kohn-Sham inversion approach can be used to compute functional derivatives of explicit density functionals and to approximate functional derivatives of orbital-dependent functionals.

Charged particle layers in the Debye limit.

PubMed

Golden, Kenneth I; Kalman, Gabor J; Kyrkos, Stamatios

2002-09-01

We develop an equivalent of the Debye-Hückel weakly coupled equilibrium theory for layered classical charged particle systems composed of one single charged species. We consider the two most important configurations, the charged particle bilayer and the infinite superlattice. The approach is based on the link provided by the classical fluctuation-dissipation theorem between the random-phase approximation response functions and the Debye equilibrium pair correlation function. Layer-layer pair correlation functions, screened and polarization potentials, static structure functions, and static response functions are calculated. The importance of the perfect screening and compressibility sum rules in determining the overall behavior of the system, especially in the r--> infinity limit, is emphasized. The similarities and differences between the quasi-two-dimensional bilayer and the quasi-three-dimensional superlattice are highlighted. An unexpected behavior that emerges from the analysis is that the screened potential, the correlations, and the screening charges carried by the individual layers exhibit a marked nonmonotonic dependence on the layer separation.

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.

A Parallel Approach in Computing Correlation Immunity up to Six Variables

DTIC Science & Technology

2015-03-10

their nonlinearity is divisible by 4. Let CI(n, k) (respectively, BCI (n, k)) be the number of exact order k correlation im- mune, (respectively...further balanced) n-variable Boolean functions. The notations CI(n, k, d), BCI (n, k, d) restricts the previous count to degree d Boolean functions...Theorem 3. The following are true: (i) BCI (n, n, 0) = 0, CI(n, n, 0) = 2, CI(n, k, 1) = BCI (n, k, 1) = 2 ( n k+1 ) , 0 ≤ k ≤ n− 1. (ii) BCI (n, n− 2) = 2

Correlation between Relatives given Complete Genotypes: from Identity by Descent to Identity by Function

PubMed Central

Sverdlov, Serge; Thompson, Elizabeth A.

2013-01-01

In classical quantitative genetics, the correlation between the phenotypes of individuals with unknown genotypes and a known pedigree relationship is expressed in terms of probabilities of IBD states. In existing approaches to the inverse problem where genotypes are observed but pedigree relationships are not, dependence between phenotypes is either modeled as Bayesian uncertainty or mapped to an IBD model via inferred relatedness parameters. Neither approach yields a relationship between genotypic similarity and phenotypic similarity with a probabilistic interpretation corresponding to a generative model. We introduce a generative model for diploid allele effect based on the classic infinite allele mutation process. This approach motivates the concept of IBF (Identity by Function). The phenotypic covariance between two individuals given their diploid genotypes is expressed in terms of functional identity states. The IBF parameters define a genetic architecture for a trait without reference to specific alleles or population. Given full genome sequences, we treat a gene-scale functional region, rather than a SNP, as a QTL, modeling patterns of dominance for multiple alleles. Applications demonstrated by simulation include phenotype and effect prediction and association, and estimation of heritability and classical variance components. A simulation case study of the Missing Heritability problem illustrates a decomposition of heritability under the IBF framework into Explained and Unexplained components. PMID:23851163

An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2017-12-01

Hybrid polynomial correlated function expansion (H-PCFE) is a novel metamodel formulated by coupling polynomial correlated function expansion (PCFE) and Kriging. Unlike commonly available metamodels, H-PCFE performs a bi-level approximation and hence, yields more accurate results. However, till date, it is only applicable to medium scaled problems. In order to address this apparent void, this paper presents an improved H-PCFE, referred to as locally refined hp - adaptive H-PCFE. The proposed framework computes the optimal polynomial order and important component functions of PCFE, which is an integral part of H-PCFE, by using global variance based sensitivity analysis. Optimal number of training points are selected by using distribution adaptive sequential experimental design. Additionally, the formulated model is locally refined by utilizing the prediction error, which is inherently obtained in H-PCFE. Applicability of the proposed approach has been illustrated with two academic and two industrial problems. To illustrate the superior performance of the proposed approach, results obtained have been compared with those obtained using hp - adaptive PCFE. It is observed that the proposed approach yields highly accurate results. Furthermore, as compared to hp - adaptive PCFE, significantly less number of actual function evaluations are required for obtaining results of similar accuracy.

Spectral functions of strongly correlated extended systems via an exact quantum embedding

NASA Astrophysics Data System (ADS)

Booth, George H.; Chan, Garnet Kin-Lic

2015-04-01

Density matrix embedding theory (DMET) [Phys. Rev. Lett. 109, 186404 (2012), 10.1103/PhysRevLett.109.186404], introduced an approach to quantum cluster embedding methods whereby the mapping of strongly correlated bulk problems to an impurity with finite set of bath states was rigorously formulated to exactly reproduce the entanglement of the ground state. The formalism provided similar physics to dynamical mean-field theory at a tiny fraction of the cost but was inherently limited by the construction of a bath designed to reproduce ground-state, static properties. Here, we generalize the concept of quantum embedding to dynamic properties and demonstrate accurate bulk spectral functions at similarly small computational cost. The proposed spectral DMET utilizes the Schmidt decomposition of a response vector, mapping the bulk dynamic correlation functions to that of a quantum impurity cluster coupled to a set of frequency-dependent bath states. The resultant spectral functions are obtained on the real-frequency axis, without bath discretization error, and allows for the construction of arbitrary dynamic correlation functions. We demonstrate the method on the one- (1D) and two-dimensional (2D) Hubbard model, where we obtain zero temperature and thermodynamic limit spectral functions, and show the trivial extension to two-particle Green's functions. This advance therefore extends the scope and applicability of DMET in condensed-matter problems as a computationally tractable route to correlated spectral functions of extended systems and provides a competitive alternative to dynamical mean-field theory for dynamic quantities.

Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach

NASA Astrophysics Data System (ADS)

Chowdhury, R.; Adhikari, S.

2012-10-01

Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.

Correlations and Functional Connections in a Population of Grid Cells

PubMed Central

Roudi, Yasser

2015-01-01

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908

Sample size determination for equivalence assessment with multiple endpoints.

PubMed

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.

Effects of correlation in transition radiation of super-short electron bunches

NASA Astrophysics Data System (ADS)

Danilova, D. K.; Tishchenko, A. A.; Strikhanov, M. N.

2017-07-01

The effect of correlations between electrons in transition radiation is investigated. The correlation function is obtained with help of the approach similar to the Debye-Hückel theory. The corrections due to correlations are estimated to be near 2-3% for the parameters of future projects SINBAD and FLUTE for bunches with extremely small lengths (∼1-10 fs). For the bunches with number of electrons about ∼ 2.5 ∗1010 and more, and short enough that the radiation would be coherent, the corrections due to correlations are predicted to reach 20%.

2pBAb5. Validation of three-dimensional strain tracking by volumetric ultrasound image correlation in a pubovisceral muscle model

PubMed Central

Nagle, Anna S.; Nageswaren, Ashok R.; Haridas, Balakrishna; Mast, T. D.

2014-01-01

Little is understood about the biomechanical changes leading to pelvic floor disorders such as stress urinary incontinence. In order to measure regional biomechanical properties of the pelvic floor muscles in vivo, a three dimensional (3D) strain tracking technique employing correlation of volumetric ultrasound images has been implemented. In this technique, local 3D displacements are determined as a function of applied stress and then converted to strain maps. To validate this approach, an in vitro model of the pubovisceral muscle, with a hemispherical indenter emulating the downward stress caused by intra-abdominal pressure, was constructed. Volumetric B-scan images were recorded as a function of indenter displacement while muscle strain was measured independently by a sonomicrometry system (Sonometrics). Local strains were computed by ultrasound image correlation and compared with sonomicrometry-measured strains to assess strain tracking accuracy. Image correlation by maximizing an exponential likelihood function was found more reliable than the Pearson correlation coefficient. Strain accuracy was dependent on sizes of the subvolumes used for image correlation, relative to characteristic speckle length scales of the images. Decorrelation of echo signals was mapped as a function of indenter displacement and local tissue orientation. Strain measurement accuracy was weakly related to local echo decorrelation. PMID:24900165

Ontological and epistemological terrains revisited.

PubMed

Bandura, A

1996-12-01

The present commentary discusses the scientific legitimacy of theories confined to correlations of observables and those that specify the mechanisms governing the relations between observable events. Operant analysts frame the theoretical differences misleadingly when the operant approach is portrayed as addressing environmental influence for effecting change but cognitive approaches are depicted as disembodied from environmental influences and thus can only provide correlates with action. In point of fact, both approaches encompass environmental influences. The major issues in contention are whether human thinking is entirely or only partially shaped by environmental influences; whether the influences in the person-environment relation flow unidirectionally or bidirectionally; and whether human thought serves a determinative function or is a functionless epiphenomenon. Proponents of epiphenomenalism regard other people's thinking as functionless by-products of conditioned responses, but present their own thoughts on matters as the right ones that provide functional guides for structuring interventions. This commentary discusses the self-negating nature of the epiphenomenalism argument. It also corrects misunderstandings and misrepresentations of self-efficacy theory.

Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction

NASA Astrophysics Data System (ADS)

Hansen, Matthew; Everett, Logan; Singh, Larry; Hannenhalli, Sridhar

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

A correlative and quantitative imaging approach enabling characterization of primary cell-cell communication: Case of human CD4+ T cell-macrophage immunological synapses.

PubMed

Kasprowicz, Richard; Rand, Emma; O'Toole, Peter J; Signoret, Nathalie

2018-05-22

Cell-to-cell communication engages signaling and spatiotemporal reorganization events driven by highly context-dependent and dynamic intercellular interactions, which are difficult to capture within heterogeneous primary cell cultures. Here, we present a straightforward correlative imaging approach utilizing commonly available instrumentation to sample large numbers of cell-cell interaction events, allowing qualitative and quantitative characterization of rare functioning cell-conjugates based on calcium signals. We applied this approach to examine a previously uncharacterized immunological synapse, investigating autologous human blood CD4 + T cells and monocyte-derived macrophages (MDMs) forming functional conjugates in vitro. Populations of signaling conjugates were visualized, tracked and analyzed by combining live imaging, calcium recording and multivariate statistical analysis. Correlative immunofluorescence was added to quantify endogenous molecular recruitments at the cell-cell junction. By analyzing a large number of rare conjugates, we were able to define calcium signatures associated with different states of CD4 + T cell-MDM interactions. Quantitative image analysis of immunostained conjugates detected the propensity of endogenous T cell surface markers and intracellular organelles to polarize towards cell-cell junctions with high and sustained calcium signaling profiles, hence defining immunological synapses. Overall, we developed a broadly applicable approach enabling detailed single cell- and population-based investigations of rare cell-cell communication events with primary cells.

Generating Dynamic Persistence in the Time Domain

NASA Astrophysics Data System (ADS)

Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.

2001-12-01

Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.

Fluorescence correlation spectroscopy: the case of subdiffusion.

PubMed

Lubelski, Ariel; Klafter, Joseph

2009-03-18

The theory of fluorescence correlation spectroscopy is revisited here for the case of subdiffusing molecules. Subdiffusion is assumed to stem from a continuous-time random walk process with a fat-tailed distribution of waiting times and can therefore be formulated in terms of a fractional diffusion equation (FDE). The FDE plays the central role in developing the fluorescence correlation spectroscopy expressions, analogous to the role played by the simple diffusion equation for regular systems. Due to the nonstationary nature of the continuous-time random walk/FDE, some interesting properties emerge that are amenable to experimental verification and may help in discriminating among subdiffusion mechanisms. In particular, the current approach predicts 1), a strong dependence of correlation functions on the initial time (aging); 2), sensitivity of correlation functions to the averaging procedure, ensemble versus time averaging (ergodicity breaking); and 3), that the basic mean-squared displacement observable depends on how the mean is taken.

Performance of an Optimally Tuned Range-Separated Hybrid Functional for 0-0 Electronic Excitation Energies.

PubMed

Jacquemin, Denis; Moore, Barry; Planchat, Aurélien; Adamo, Carlo; Autschbach, Jochen

2014-04-08

Using a set of 40 conjugated molecules, we assess the performance of an "optimally tuned" range-separated hybrid functional in reproducing the experimental 0-0 energies. The selected protocol accounts for the impact of solvation using a corrected linear-response continuum approach and vibrational corrections through calculations of the zero-point energies of both ground and excited-states and provides basis set converged data thanks to the systematic use of diffuse-containing atomic basis sets at all computational steps. It turns out that an optimally tuned long-range corrected hybrid form of the Perdew-Burke-Ernzerhof functional, LC-PBE*, delivers both the smallest mean absolute error (0.20 eV) and standard deviation (0.15 eV) of all tested approaches, while the obtained correlation (0.93) is large but remains slightly smaller than its M06-2X counterpart (0.95). In addition, the efficiency of two other recently developed exchange-correlation functionals, namely SOGGA11-X and ωB97X-D, has been determined in order to allow more complete comparisons with previously published data.

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Universal Long Ranged Correlations in Driven Binary Mixtures

NASA Astrophysics Data System (ADS)

Poncet, Alexis; Bénichou, Olivier; Démery, Vincent; Oshanin, Gleb

2017-03-01

When two populations of "particles" move in opposite directions, like oppositely charged colloids under an electric field or intersecting flows of pedestrians, they can move collectively, forming lanes along their direction of motion. The nature of this "laning transition" is still being debated and, in particular, the pair correlation functions, which are the key observables to quantify this phenomenon, have not been characterized yet. Here, we determine the correlations using an analytical approach based on a linearization of the stochastic equations for the density fields, which is valid for dense systems of soft particles. We find that the correlations decay algebraically along the direction of motion, and have a self-similar exponential profile in the transverse direction. Brownian dynamics simulations confirm our theoretical predictions and show that they also hold beyond the validity range of our analytical approach, pointing to a universal behavior.

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

PubMed

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

2018-05-15

Reliability of subject-level resting-state functional connectivity (FC) is determined in part by the statistical techniques employed in its estimation. Methods that pool information across subjects to inform estimation of subject-level effects (e.g., Bayesian approaches) have been shown to enhance reliability of subject-level FC. However, fully Bayesian approaches are computationally demanding, while empirical Bayesian approaches typically rely on using repeated measures to estimate the variance components in the model. Here, we avoid the need for repeated measures by proposing a novel measurement error model for FC describing the different sources of variance and error, which we use to perform empirical Bayes shrinkage of subject-level FC towards the group average. In addition, since the traditional intra-class correlation coefficient (ICC) is inappropriate for biased estimates, we propose a new reliability measure denoted the mean squared error intra-class correlation coefficient (ICC MSE ) to properly assess the reliability of the resulting (biased) estimates. We apply the proposed techniques to test-retest resting-state fMRI data on 461 subjects from the Human Connectome Project to estimate connectivity between 100 regions identified through independent components analysis (ICA). We consider both correlation and partial correlation as the measure of FC and assess the benefit of shrinkage for each measure, as well as the effects of scan duration. We find that shrinkage estimates of subject-level FC exhibit substantially greater reliability than traditional estimates across various scan durations, even for the most reliable connections and regardless of connectivity measure. Additionally, we find partial correlation reliability to be highly sensitive to the choice of penalty term, and to be generally worse than that of full correlations except for certain connections and a narrow range of penalty values. This suggests that the penalty needs to be chosen carefully when using partial correlations. Copyright © 2018. Published by Elsevier Inc.

Stochastic reconstructions of spectral functions: Application to lattice QCD

NASA Astrophysics Data System (ADS)

Ding, H.-T.; Kaczmarek, O.; Mukherjee, Swagato; Ohno, H.; Shu, H.-T.

2018-05-01

We present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM) and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, firstly, we apply these methods to various reasonably chosen model correlation functions and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0.75 and 1.5 Tc, Tc being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

Susceptibility of the Ising Model on a Kagomé Lattice by Using Wang-Landau Sampling

NASA Astrophysics Data System (ADS)

Kim, Seung-Yeon; Kwak, Wooseop

2018-03-01

The susceptibility of the Ising model on a kagomé lattice has never been obtained. We investigate the properties of the kagomé-lattice Ising model by using the Wang-Landau sampling method. We estimate both the magnetic scaling exponent yh = 1.90(1) and the thermal scaling exponent yt = 1.04(2) only from the susceptibility. From the estimated values of yh and yt, we obtain all the critical exponents, the specific-heat critical exponent α = 0.08(4), the spontaneous-magnetization critical exponent β = 0.10(1), the susceptibility critical exponent γ = 1.73(5), the isothermalmagnetization critical exponent δ = 16(4), the correlation-length critical exponent ν = 0.96(2), and the correlation-function critical exponent η = 0.20(4), without using any other thermodynamic function, such as the specific heat, magnetization, correlation length, and correlation function. One should note that the evaluation of all the critical exponents only from information on the susceptibility is an innovative approach.

The heterogeneity of segmental dynamics of filled EPDM by (1)H transverse relaxation NMR.

PubMed

Moldovan, D; Fechete, R; Demco, D E; Culea, E; Blümich, B; Herrmann, V; Heinz, M

2011-01-01

Residual second moment of dipolar interactions M(2) and correlation time segmental dynamics distributions were measured by Hahn-echo decays in combination with inverse Laplace transform for a series of unfilled and filled EPDM samples as functions of carbon-black N683 filler content. The fillers-polymer chain interactions which dramatically restrict the mobility of bound rubber modify the dynamics of mobile chains. These changes depend on the filler content and can be evaluated from distributions of M(2). A dipolar filter was applied to eliminate the contribution of bound rubber. In the first approach the Hahn-echo decays were fitted with a theoretical relationship to obtain the average values of the (1)H residual second moment and correlation time <τ(c)>. For the mobile EPDM segments the power-law distribution of correlation function was compared to the exponential correlation function and found inadequate in the long-time regime. In the second approach a log-Gauss distribution for the correlation time was assumed. Furthermore, using an averaged value of the correlation time, the distributions of the residual second moment were determined using an inverse Laplace transform for the entire series of measured samples. The unfilled EPDM sample shows a bimodal distribution of residual second moments, which can be associated to the mobile polymer sub-chains (M(2) ≅ 6.1 rad (2) s(-2)) and the second one associated to the dangling chains M(2) ≅ 5.4 rad(2) s(-2)). By restraining the mobility of bound rubber, the carbon-black fillers induce diversity in the segmental dynamics like the apparition of a distinct mobile component and changes in the distribution of mobile and free-end polymer segments. Copyright © 2010 Elsevier Inc. All rights reserved.

The heterogeneity of segmental dynamics of filled EPDM by 1H transverse relaxation NMR

NASA Astrophysics Data System (ADS)

Moldovan, D.; Fechete, R.; Demco, D. E.; Culea, E.; Blümich, B.; Herrmann, V.; Heinz, M.

2011-01-01

Residual second moment of dipolar interactions M∼2 and correlation time segmental dynamics distributions were measured by Hahn-echo decays in combination with inverse Laplace transform for a series of unfilled and filled EPDM samples as functions of carbon-black N683 filler content. The fillers-polymer chain interactions which dramatically restrict the mobility of bound rubber modify the dynamics of mobile chains. These changes depend on the filler content and can be evaluated from distributions of M∼2. A dipolar filter was applied to eliminate the contribution of bound rubber. In the first approach the Hahn-echo decays were fitted with a theoretical relationship to obtain the average values of the 1H residual second moment and correlation time <τc>. For the mobile EPDM segments the power-law distribution of correlation function was compared to the exponential correlation function and found inadequate in the long-time regime. In the second approach a log-Gauss distribution for the correlation time was assumed. Furthermore, using an averaged value of the correlation time, the distributions of the residual second moment were determined using an inverse Laplace transform for the entire series of measured samples. The unfilled EPDM sample shows a bimodal distribution of residual second moments, which can be associated to the mobile polymer sub-chains (M∼2≅6.1 rad s) and the second one associated to the dangling chains M∼2≅5.4 rad s). By restraining the mobility of bound rubber, the carbon-black fillers induce diversity in the segmental dynamics like the apparition of a distinct mobile component and changes in the distribution of mobile and free-end polymer segments.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Scaling within the spectral function approach

NASA Astrophysics Data System (ADS)

Sobczyk, J. E.; Rocco, N.; Lovato, A.; Nieves, J.

2018-03-01

Scaling features of the nuclear electromagnetic response functions unveil aspects of nuclear dynamics that are crucial for interpreting neutrino- and electron-scattering data. In the large momentum-transfer regime, the nucleon-density response function defines a universal scaling function, which is independent of the nature of the probe. In this work, we analyze the nucleon-density response function of 12C, neglecting collective excitations. We employ particle and hole spectral functions obtained within two distinct many-body methods, both widely used to describe electroweak reactions in nuclei. We show that the two approaches provide compatible nucleon-density scaling functions that for large momentum transfers satisfy first-kind scaling. Both methods yield scaling functions characterized by an asymmetric shape, although less pronounced than that of experimental scaling functions. This asymmetry, only mildly affected by final state interactions, is mostly due to nucleon-nucleon correlations, encoded in the continuum component of the hole spectral function.

B B ¯ angular correlations at the LHC in the parton Reggeization approach merged with higher-order matrix elements

NASA Astrophysics Data System (ADS)

Karpishkov, A. V.; Nefedov, M. A.; Saleev, V. A.

2017-11-01

We calculate the angular distribution spectra between beauty (B ) and antibeauty (B ¯) mesons in proton-proton collisions in the leading order approximation of the parton Reggeization approach consistently merged with the next-to-leading order corrections from the emission of an additional hard gluon. To describe b-quark hadronization we use the universal scale-dependent parton-to-meson fragmentation functions extracted from the world e+e- annihilation data. We have obtained good agreement between our predictions and data from the CMS Collaboration at the energy √{S }=7 TeV for B B ¯ angular correlations within uncertainties and without free parameters. Predictions for analogous correlation observables at √{S }=13 TeV are provided.

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.

Seismic interferometry by crosscorrelation and by multidimensional deconvolution: a systematic comparison

NASA Astrophysics Data System (ADS)

Wapenaar, Kees; van der Neut, Joost; Ruigrok, Elmer; Draganov, Deyan; Hunziker, Jürg; Slob, Evert; Thorbecke, Jan; Snieder, Roel

2011-06-01

Seismic interferometry, also known as Green's function retrieval by crosscorrelation, has a wide range of applications, ranging from surface-wave tomography using ambient noise, to creating virtual sources for improved reflection seismology. Despite its successful applications, the crosscorrelation approach also has its limitations. The main underlying assumptions are that the medium is lossless and that the wavefield is equipartitioned. These assumptions are in practice often violated: the medium of interest is often illuminated from one side only, the sources may be irregularly distributed, and losses may be significant. These limitations may partly be overcome by reformulating seismic interferometry as a multidimensional deconvolution (MDD) process. We present a systematic analysis of seismic interferometry by crosscorrelation and by MDD. We show that for the non-ideal situations mentioned above, the correlation function is proportional to a Green's function with a blurred source. The source blurring is quantified by a so-called interferometric point-spread function which, like the correlation function, can be derived from the observed data (i.e. without the need to know the sources and the medium). The source of the Green's function obtained by the correlation method can be deblurred by deconvolving the correlation function for the point-spread function. This is the essence of seismic interferometry by MDD. We illustrate the crosscorrelation and MDD methods for controlled-source and passive-data applications with numerical examples and discuss the advantages and limitations of both methods.

The rank correlated SLW model of gas radiation in non-uniform media

NASA Astrophysics Data System (ADS)

Solovjov, Vladimir P.; Andre, Frederic; Lemonnier, Denis; Webb, Brent W.

2017-08-01

A comprehensive theoretical development of possible reference approaches in modelling of radiation transfer in non-uniform gaseous media is developed within the framework of the Generalized SLW Model. The notion of absorption spectrum ;correlation; adopted currently for global methods in gas radiation is critically revisited and replaced by a less restrictive concept of rank correlated spectrum. Within this framework it is shown that eight different reference approaches are possible, of which only three have been reported in the literature. Among the approaches presented is a novel Rank Correlated SLW Model, which is distinguished by the fact that i) it does not require the specification of a reference gas thermodynamic state, and ii) it preserves the emission term in the spectrally integrated Radiative Transfer Equation. Construction of this reference model requires only two absorption line blackbody distribution functions, and subdivision into gray gases can be performed using standard quadratures. Consequently, this new reference approach appears to have significant advantages over all other methods, and is, in general, a significant improvement in the global modelling of gas radiation. All reference approaches are summarized in the present work, and their use in radiative transfer prediction is demonstrated for simple example cases. Further, a detailed rigorous theoretical development of the improved methods is provided.

Kinetic theory for strongly coupled Coulomb systems

NASA Astrophysics Data System (ADS)

Dufty, James; Wrighton, Jeffrey

2018-01-01

The calculation of dynamical properties for matter under extreme conditions is a challenging task. The popular Kubo-Greenwood model exploits elements from equilibrium density-functional theory (DFT) that allow a detailed treatment of electron correlations, but its origin is largely phenomenological; traditional kinetic theories have a more secure foundation but are limited to weak ion-electron interactions. The objective here is to show how a combination of the two evolves naturally from the short-time limit for the generator of the effective single-electron dynamics governing time correlation functions without such limitations. This provides a theoretical context for the current DFT-related approach, the Kubo-Greenwood model, while showing the nature of its corrections. The method is to calculate the short-time dynamics in the single-electron subspace for a given configuration of the ions. This differs from the usual kinetic theory approach in which an average over the ions is performed as well. In this way the effective ion-electron interaction includes strong Coulomb coupling and is shown to be determined from DFT. The correlation functions have the form of the random-phase approximation for an inhomogeneous system but with renormalized ion-electron and electron-electron potentials. The dynamic structure function, density response function, and electrical conductivity are calculated as examples. The static local field corrections in the dielectric function are identified in this way. The current analysis is limited to semiclassical electrons (quantum statistical potentials), so important quantum conditions are excluded. However, a quantization of the kinetic theory is identified for broader application while awaiting its detailed derivation.

Multiconfigurational short-range density-functional theory for open-shell systems

NASA Astrophysics Data System (ADS)

Hedegârd, Erik Donovan; Toulouse, Julien; Jensen, Hans Jørgen Aagaard

2018-06-01

Many chemical systems cannot be described by quantum chemistry methods based on a single-reference wave function. Accurate predictions of energetic and spectroscopic properties require a delicate balance between describing the most important configurations (static correlation) and obtaining dynamical correlation efficiently. The former is most naturally done through a multiconfigurational (MC) wave function, whereas the latter can be done by, e.g., perturbation theory. We have employed a different strategy, namely, a hybrid between multiconfigurational wave functions and density-functional theory (DFT) based on range separation. The method is denoted by MC short-range DFT (MC-srDFT) and is more efficient than perturbative approaches as it capitalizes on the efficient treatment of the (short-range) dynamical correlation by DFT approximations. In turn, the method also improves DFT with standard approximations through the ability of multiconfigurational wave functions to recover large parts of the static correlation. Until now, our implementation was restricted to closed-shell systems, and to lift this restriction, we present here the generalization of MC-srDFT to open-shell cases. The additional terms required to treat open-shell systems are derived and implemented in the DALTON program. This new method for open-shell systems is illustrated on dioxygen and [Fe(H2O)6]3+.

Dimensional psychiatry: reward dysfunction and depressive mood across psychiatric disorders.

PubMed

Hägele, Claudia; Schlagenhauf, Florian; Rapp, Michael; Sterzer, Philipp; Beck, Anne; Bermpohl, Felix; Stoy, Meline; Ströhle, Andreas; Wittchen, Hans-Ulrich; Dolan, Raymond J; Heinz, Andreas

2015-01-01

A dimensional approach in psychiatry aims to identify core mechanisms of mental disorders across nosological boundaries. We compared anticipation of reward between major psychiatric disorders, and investigated whether reward anticipation is impaired in several mental disorders and whether there is a common psychopathological correlate (negative mood) of such an impairment. We used functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task to study the functional correlates of reward anticipation across major psychiatric disorders in 184 subjects, with the diagnoses of alcohol dependence (n = 26), schizophrenia (n = 44), major depressive disorder (MDD, n = 24), bipolar disorder (acute manic episode, n = 13), attention deficit/hyperactivity disorder (ADHD, n = 23), and healthy controls (n = 54). Subjects' individual Beck Depression Inventory-and State-Trait Anxiety Inventory-scores were correlated with clusters showing significant activation during reward anticipation. During reward anticipation, we observed significant group differences in ventral striatal (VS) activation: patients with schizophrenia, alcohol dependence, and major depression showed significantly less ventral striatal activation compared to healthy controls. Depressive symptoms correlated with dysfunction in reward anticipation regardless of diagnostic entity. There was no significant correlation between anxiety symptoms and VS functional activation. Our findings demonstrate a neurobiological dysfunction related to reward prediction that transcended disorder categories and was related to measures of depressed mood. The findings underline the potential of a dimensional approach in psychiatry and strengthen the hypothesis that neurobiological research in psychiatric disorders can be targeted at core mechanisms that are likely to be implicated in a range of clinical entities.

How to calculate H3 better.

PubMed

Pavanello, Michele; Tung, Wei-Cheng; Adamowicz, Ludwik

2009-11-14

Efficient optimization of the basis set is key to achieving a very high accuracy in variational calculations of molecular systems employing basis functions that are explicitly dependent on the interelectron distances. In this work we present a method for a systematic enlargement of basis sets of explicitly correlated functions based on the iterative-complement-interaction approach developed by Nakatsuji [Phys. Rev. Lett. 93, 030403 (2004)]. We illustrate the performance of the method in the variational calculations of H(3) where we use explicitly correlated Gaussian functions with shifted centers. The total variational energy (-1.674 547 421 Hartree) and the binding energy (-15.74 cm(-1)) obtained in the calculation with 1000 Gaussians are the most accurate results to date.

An engineering approach to design of dextran microgels size fabricated by water/oil emulsification.

PubMed

Salimi-Kenari, Hamed; Imani, Mohammad; Nodehi, Azizollah; Abedini, Hossein

2016-09-01

A correlation, based on fluid mechanics, has been investigated for the mean particle diameter of crosslinked dextran microgels (CDMs) prepared via a water/oil emulsification methodology conducted in a single-stirred vessel. To this end, non-dimensional correlations were developed to predict the mean particle size of CDMs as a function of Weber number, Reynolds number and viscosity number similar to ones introduced for liquid-liquid dispersions. Moreover, a Rosin-Rammler distribution function has been successfully applied to the microgel particle size distributions. The correlations were validated using experimentally obtained mean particle sizes for CDMs prepared at different stirring conditions. The validated correlation is especially applicable to medical and pharmaceutical applications where strict control on the mean particle size and size distribution of CDMs are extremely essential. [Formula: see text].

Connection between two statistical approaches for the modelling of particle velocity and concentration distributions in turbulent flow: The mesoscopic Eulerian formalism and the two-point probability density function method

NASA Astrophysics Data System (ADS)

Simonin, Olivier; Zaichik, Leonid I.; Alipchenkov, Vladimir M.; Février, Pierre

2006-12-01

The objective of the paper is to elucidate a connection between two approaches that have been separately proposed for modelling the statistical spatial properties of inertial particles in turbulent fluid flows. One of the approaches proposed recently by Février, Simonin, and Squires [J. Fluid Mech. 533, 1 (2005)] is based on the partitioning of particle turbulent velocity field into spatially correlated (mesoscopic Eulerian) and random-uncorrelated (quasi-Brownian) components. The other approach stems from a kinetic equation for the two-point probability density function of the velocity distributions of two particles [Zaichik and Alipchenkov, Phys. Fluids 15, 1776 (2003)]. Comparisons between these approaches are performed for isotropic homogeneous turbulence and demonstrate encouraging agreement.

Algebraic approach to electronic spectroscopy and dynamics.

PubMed

Toutounji, Mohamad

2008-04-28

Lie algebra, Zassenhaus, and parameter differentiation techniques are utilized to break up the exponential of a bilinear Hamiltonian operator into a product of noncommuting exponential operators by the virtue of the theory of Wei and Norman [J. Math. Phys. 4, 575 (1963); Proc. Am. Math. Soc., 15, 327 (1964)]. There are about three different ways to find the Zassenhaus exponents, namely, binomial expansion, Suzuki formula, and q-exponential transformation. A fourth, and most reliable method, is provided. Since linearly displaced and distorted (curvature change upon excitation/emission) Hamiltonian and spin-boson Hamiltonian may be classified as bilinear Hamiltonians, the presented algebraic algorithm (exponential operator disentanglement exploiting six-dimensional Lie algebra case) should be useful in spin-boson problems. The linearly displaced and distorted Hamiltonian exponential is only treated here. While the spin-boson model is used here only as a demonstration of the idea, the herein approach is more general and powerful than the specific example treated. The optical linear dipole moment correlation function is algebraically derived using the above mentioned methods and coherent states. Coherent states are eigenvectors of the bosonic lowering operator a and not of the raising operator a(+). While exp(a(+)) translates coherent states, exp(a(+)a(+)) operation on coherent states has always been a challenge, as a(+) has no eigenvectors. Three approaches, and the results, of that operation are provided. Linear absorption spectra are derived, calculated, and discussed. The linear dipole moment correlation function for the pure quadratic coupling case is expressed in terms of Legendre polynomials to better show the even vibronic transitions in the absorption spectrum. Comparison of the present line shapes to those calculated by other methods is provided. Franck-Condon factors for both linear and quadratic couplings are exactly accounted for by the herein calculated linear absorption spectra. This new methodology should easily pave the way to calculating the four-point correlation function, F(tau(1),tau(2),tau(3),tau(4)), of which the optical nonlinear response function may be procured, as evaluating F(tau(1),tau(2),tau(3),tau(4)) is only evaluating the optical linear dipole moment correlation function iteratively over different time intervals, which should allow calculating various optical nonlinear temporal/spectral signals.

Linked-cluster formulation of electron-hole interaction kernel in real-space representation without using unoccupied states.

PubMed

Bayne, Michael G; Scher, Jeremy A; Ellis, Benjamin H; Chakraborty, Arindam

2018-05-21

Electron-hole or quasiparticle representation plays a central role in describing electronic excitations in many-electron systems. For charge-neutral excitation, the electron-hole interaction kernel is the quantity of interest for calculating important excitation properties such as optical gap, optical spectra, electron-hole recombination and electron-hole binding energies. The electron-hole interaction kernel can be formally derived from the density-density correlation function using both Green's function and TDDFT formalism. The accurate determination of the electron-hole interaction kernel remains a significant challenge for precise calculations of optical properties in the GW+BSE formalism. From the TDDFT perspective, the electron-hole interaction kernel has been viewed as a path to systematic development of frequency-dependent exchange-correlation functionals. Traditional approaches, such as MBPT formalism, use unoccupied states (which are defined with respect to Fermi vacuum) to construct the electron-hole interaction kernel. However, the inclusion of unoccupied states has long been recognized as the leading computational bottleneck that limits the application of this approach for larger finite systems. In this work, an alternative derivation that avoids using unoccupied states to construct the electron-hole interaction kernel is presented. The central idea of this approach is to use explicitly correlated geminal functions for treating electron-electron correlation for both ground and excited state wave functions. Using this ansatz, it is derived using both diagrammatic and algebraic techniques that the electron-hole interaction kernel can be expressed only in terms of linked closed-loop diagrams. It is proved that the cancellation of unlinked diagrams is a consequence of linked-cluster theorem in real-space representation. The electron-hole interaction kernel derived in this work was used to calculate excitation energies in many-electron systems and results were found to be in good agreement with the EOM-CCSD and GW+BSE methods. The numerical results highlight the effectiveness of the developed method for overcoming the computational barrier of accurately determining the electron-hole interaction kernel to applications of large finite systems such as quantum dots and nanorods.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Generalization of the optimized-effective-potential model to include electron correlation: A variational derivation of the Sham-Schlueter equation for the exact exchange-correlation potential

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

Casida, M.E.

1995-03-01

The now classic optimized-effective-potential (OEP) approach of Sharp and Horton [Phys Rev. 90, 317 (1953)] and Talman and Shadwick [Phys. Rev. A 14, 36 (1976)] seeks the local potential that is variationally optimized to best approximate the Hartree-Fock exchange operator. The resulting OEP can be identified as the exchange potential of Kohn-Sham density-functional theory. The present work generalizes this OEP approach to treat the correlated case, and shows that the Kohn-Sham exchange-correlation potential is the variationally best local approximation to the exchange-correlation self-energy. This provides a variational derivation of the equation for the exact exchange-correlation potential that was derived bymore » Sham and Schlueter using a density condition. Implications for an approximate physical interpretation of the Kohn-Sham orbitals are discussesd. A correlated generalization of the Sharp-Horton--Krieger-Li-Iafrate [Phys Lett. A 146, 256 (1990)] approximation of the exchange potential is introduced in the quasiparticle limit.« less

Data analytics using canonical correlation analysis and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

2017-07-01

A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

Density functional with full exact exchange, balanced nonlocality of correlations, and constraint satisfaction

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

Tao, Jianmin; Perdew, John P; Staroverov, Viktor N

2008-01-01

We construct a nonlocal density functional approximation with full exact exchange, while preserving the constraint-satisfaction approach and justified error cancellations of simpler semilocal functionals. This is achieved by interpolating between different approximations suitable for two extreme regions of the electron density. In a 'normal' region, the exact exchange-correlation hole density around an electron is semilocal because its spatial range is reduced by correlation and because it integrates over a narrow range to -1. These regions are well described by popular semilocal approximations (many of which have been constructed nonempirically), because of proper accuracy for a slowly-varying density or because ofmore » error cancellation between exchange and correlation. 'Abnormal' regions, where non locality is unveiled, include those in which exchange can dominate correlation (one-electron, nonuniform high-density, and rapidly-varying limits), and those open subsystems of fluctuating electron number over which the exact exchange-correlation hole integrates to a value greater than -1. Regions between these extremes are described by a hybrid functional mixing exact and semi local exchange energy densities locally (i.e., with a mixing fraction that is a function of position r and a functional of the density). Because our mixing fraction tends to 1 in the high-density limit, we employ full exact exchange according to the rigorous definition of the exchange component of any exchange-correlation energy functional. Use of full exact exchange permits the satisfaction of many exact constraints, but the nonlocality of exchange also requires balanced nonlocality of correlation. We find that this nonlocality can demand at least five empirical parameters (corresponding roughly to the four kinds of abnormal regions). Our local hybrid functional is perhaps the first accurate size-consistent density functional with full exact exchange. It satisfies other known exact constraints, including exactness for all one-electron densities, and provides an excellent, fit 1.0 the 223 molecular enthalpies of formation of the G3/99 set and the 42 reaction barrier heights of the BH42/03 set, improving both (but especially the latter) over most semilocal functionals and global hybrids. Exact constraints, physical insights, and paradigm examples hopefully suppress 'overfitting'.« less

Heisenberg symmetry and collective modes of one dimensional unitary correlated fermions

NASA Astrophysics Data System (ADS)

Abhinav, Kumar; Chandrasekhar, B.; Vyas, Vivek M.; Panigrahi, Prasanta K.

2017-02-01

The correlated fermionic many-particle system, near infinite scattering length, reveals an underlying Heisenberg symmetry in one dimension, as compared to an SO (2 , 1) symmetry in two dimensions. This facilitates an exact map from the interacting to the non-interacting system, both with and without a harmonic trap, and explains the short-distance scaling behavior of the wave-function. Taking advantage of the phenomenological Calogero-Sutherland-type interaction, motivated by the density functional approach, we connect the ground-state energy shift, to many-body correlation effect. For the excited states, modes at integral values of the harmonic frequency ω are predicted in one dimension, in contrast to the breathing modes with frequency 2ω in two dimensions.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Hartree-Fock implementation using a Laguerre-based wave function for the ground state and correlation energies of two-electron atoms.

PubMed

King, Andrew W; Baskerville, Adam L; Cox, Hazel

2018-03-13

An implementation of the Hartree-Fock (HF) method using a Laguerre-based wave function is described and used to accurately study the ground state of two-electron atoms in the fixed nucleus approximation, and by comparison with fully correlated (FC) energies, used to determine accurate electron correlation energies. A variational parameter A is included in the wave function and is shown to rapidly increase the convergence of the energy. The one-electron integrals are solved by series solution and an analytical form is found for the two-electron integrals. This methodology is used to produce accurate wave functions, energies and expectation values for the helium isoelectronic sequence, including at low nuclear charge just prior to electron detachment. Additionally, the critical nuclear charge for binding two electrons within the HF approach is calculated and determined to be Z HF C =1.031 177 528.This article is part of the theme issue 'Modern theoretical chemistry'. © 2018 The Author(s).

Beyond the constraints underlying Kolmogorov-Johnson-Mehl-Avrami theory related to the growth laws.

PubMed

Tomellini, M; Fanfoni, M

2012-02-01

The theory of Kolmogorov-Johnson-Mehl-Avrami for phase transition kinetics is subjected to severe limitations concerning the functional form of the growth law. This paper is devoted to sidestepping this drawback through the use of the correlation function approach. Moreover, we put forward an easy-to-handle formula, written in terms of the experimentally accessible actual extended volume fraction, which is found to match several types of growths. Computer simulations have been performed for corroborating the theoretical approach. © 2012 American Physical Society

Large-scale 3D galaxy correlation function and non-Gaussianity

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

Raccanelli, Alvise; Doré, Olivier; Bertacca, Daniele

We investigate the properties of the 2-point galaxy correlation function at very large scales, including all geometric and local relativistic effects --- wide-angle effects, redshift space distortions, Doppler terms and Sachs-Wolfe type terms in the gravitational potentials. The general three-dimensional correlation function has a nonzero dipole and octupole, in addition to the even multipoles of the flat-sky limit. We study how corrections due to primordial non-Gaussianity and General Relativity affect the multipolar expansion, and we show that they are of similar magnitude (when f{sub NL} is small), so that a relativistic approach is needed. Furthermore, we look at how large-scalemore » corrections depend on the model for the growth rate in the context of modified gravity, and we discuss how a modified growth can affect the non-Gaussian signal in the multipoles.« less

Discriminating topology in galaxy distributions using network analysis

NASA Astrophysics Data System (ADS)

Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

2016-07-01

The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.

Combining electronic structure and many-body theory with large databases: A method for predicting the nature of 4 f states in Ce compounds

NASA Astrophysics Data System (ADS)

Herper, H. C.; Ahmed, T.; Wills, J. M.; Di Marco, I.; Björkman, T.; Iuşan, D.; Balatsky, A. V.; Eriksson, O.

2017-08-01

Recent progress in materials informatics has opened up the possibility of a new approach to accessing properties of materials in which one assays the aggregate properties of a large set of materials within the same class in addition to a detailed investigation of each compound in that class. Here we present a large scale investigation of electronic properties and correlated magnetism in Ce-based compounds accompanied by a systematic study of the electronic structure and 4 f -hybridization function of a large body of Ce compounds. We systematically study the electronic structure and 4 f -hybridization function of a large body of Ce compounds with the goal of elucidating the nature of the 4 f states and their interrelation with the measured Kondo energy in these compounds. The hybridization function has been analyzed for more than 350 data sets (being part of the IMS database) of cubic Ce compounds using electronic structure theory that relies on a full-potential approach. We demonstrate that the strength of the hybridization function, evaluated in this way, allows us to draw precise conclusions about the degree of localization of the 4 f states in these compounds. The theoretical results are entirely consistent with all experimental information, relevant to the degree of 4 f localization for all investigated materials. Furthermore, a more detailed analysis of the electronic structure and the hybridization function allows us to make precise statements about Kondo correlations in these systems. The calculated hybridization functions, together with the corresponding density of states, reproduce the expected exponential behavior of the observed Kondo temperatures and prove a consistent trend in real materials. This trend allows us to predict which systems may be correctly identified as Kondo systems. A strong anticorrelation between the size of the hybridization function and the volume of the systems has been observed. The information entropy for this set of systems is about 0.42. Our approach demonstrates the predictive power of materials informatics when a large number of materials is used to establish significant trends. This predictive power can be used to design new materials with desired properties. The applicability of this approach for other correlated electron systems is discussed.

Virial Coefficients for the Liquid Argon

NASA Astrophysics Data System (ADS)

Korth, Micheal; Kim, Saesun

2014-03-01

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

Gluon and ghost correlation functions of 2-color QCD at finite density

NASA Astrophysics Data System (ADS)

Hajizadeh, Ouraman; Boz, Tamer; Maas, Axel; Skullerud, Jon-Ivar

2018-03-01

2-color QCD, i. e. QCD with the gauge group SU(2), is the simplest non-Abelian gauge theory without sign problem at finite quark density. Therefore its study on the lattice is a benchmark for other non-perturbative approaches at finite density. To provide such benchmarks we determine the minimal-Landau-gauge 2-point and 3-gluon correlation functions of the gauge sector and the running gauge coupling at finite density. We observe no significant effects, except for some low-momentum screening of the gluons at and above the supposed high-density phase transition.

Local electric dipole moments for periodic systems via density functional theory embedding.

PubMed

Luber, Sandra

2014-12-21

We describe a novel approach for the calculation of local electric dipole moments for periodic systems. Since the position operator is ill-defined in periodic systems, maximally localized Wannier functions based on the Berry-phase approach are usually employed for the evaluation of local contributions to the total electric dipole moment of the system. We propose an alternative approach: within a subsystem-density functional theory based embedding scheme, subset electric dipole moments are derived without any additional localization procedure, both for hybrid and non-hybrid exchange-correlation functionals. This opens the way to a computationally efficient evaluation of local electric dipole moments in (molecular) periodic systems as well as their rigorous splitting into atomic electric dipole moments. As examples, Infrared spectra of liquid ethylene carbonate and dimethyl carbonate are presented, which are commonly employed as solvents in Lithium ion batteries.

Determining Protease Activity In Vivo by Fluorescence Cross-Correlation Analysis

PubMed Central

Kohl, Tobias; Haustein, Elke; Schwille, Petra

2005-01-01

To date, most biochemical approaches to unravel protein function have focused on purified proteins in vitro. Whereas they analyze enzyme performance under assay conditions, they do not necessarily tell us what is relevant within a living cell. Ideally, cellular functions should be examined in situ. In particular, association/dissociation reactions are ubiquitous, but so far there is no standard technique permitting online analysis of these processes in vivo. Featuring single-molecule sensitivity combined with intrinsic averaging, fluorescence correlation spectroscopy is a minimally invasive technique ideally suited to monitor proteins. Moreover, endogenous fluorescence-based assays can be established by genetically encoding fusions of autofluorescent proteins and cellular proteins, thus avoiding the disadvantages of in vitro protein labeling and subsequent delivery to cells. Here, we present an in vivo protease assay as a model system: Green and red autofluorescent proteins were connected by Caspase-3- sensitive and insensitive protein linkers to create double-labeled protease substrates. Then, dual-color fluorescence cross-correlation spectroscopy was employed to study the protease reaction in situ. Allowing assessment of multiple dynamic parameters simultaneously, this method provided internal calibration and improved experimental resolution for quantifying protein stability. This approach, which is easily extended to reversible protein-protein interactions, seems very promising for elucidating intracellular protein functions. PMID:16055538

Phenomenological analysis of medical time series with regular and stochastic components

NASA Astrophysics Data System (ADS)

Timashev, Serge F.; Polyakov, Yuriy S.

2007-06-01

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions), which complement the information of each other. The structural function stochastic component is formed exclusively by "jumps" of the dynamic variable while the power spectrum stochastic component is formed by both spikes and "jumps" on every level of the hierarchy. The information "passport" characteristics that are determined by fitting the derived expressions to the experimental variations for the stochastic components of power spectra and structural functions are interpreted as the correlation times and parameters that describe the rate of "memory loss" on these correlation time intervals for different irregularities. The number of the extracted parameters is determined by the requirements of the problem under study. Application of this approach to the analysis of tremor velocity signals for a Parkinsonian patient is discussed.

Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

PubMed

Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

2018-01-01

Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models

NASA Astrophysics Data System (ADS)

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-04-01

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.

Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models

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

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-04-15

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simplemore » Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.« less

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

A Multi-Functional Imaging Approach to High-Content Protein Interaction Screening

PubMed Central

Matthews, Daniel R.; Fruhwirth, Gilbert O.; Weitsman, Gregory; Carlin, Leo M.; Ofo, Enyinnaya; Keppler, Melanie; Barber, Paul R.; Tullis, Iain D. C.; Vojnovic, Borivoj; Ng, Tony; Ameer-Beg, Simon M.

2012-01-01

Functional imaging can provide a level of quantification that is not possible in what might be termed traditional high-content screening. This is due to the fact that the current state-of-the-art high-content screening systems take the approach of scaling-up single cell assays, and are therefore based on essentially pictorial measures as assay indicators. Such phenotypic analyses have become extremely sophisticated, advancing screening enormously, but this approach can still be somewhat subjective. We describe the development, and validation, of a prototype high-content screening platform that combines steady-state fluorescence anisotropy imaging with fluorescence lifetime imaging (FLIM). This functional approach allows objective, quantitative screening of small molecule libraries in protein-protein interaction assays. We discuss the development of the instrumentation, the process by which information on fluorescence resonance energy transfer (FRET) can be extracted from wide-field, acceptor fluorescence anisotropy imaging and cross-checking of this modality using lifetime imaging by time-correlated single-photon counting. Imaging of cells expressing protein constructs where eGFP and mRFP1 are linked with amino-acid chains of various lengths (7, 19 and 32 amino acids) shows the two methodologies to be highly correlated. We validate our approach using a small-scale inhibitor screen of a Cdc42 FRET biosensor probe expressed in epidermoid cancer cells (A431) in a 96 microwell-plate format. We also show that acceptor fluorescence anisotropy can be used to measure variations in hetero-FRET in protein-protein interactions. We demonstrate this using a screen of inhibitors of internalization of the transmembrane receptor, CXCR4. These assays enable us to demonstrate all the capabilities of the instrument, image processing and analytical techniques that have been developed. Direct correlation between acceptor anisotropy and donor FLIM is observed for FRET assays, providing an opportunity to rapidly screen proteins, interacting on the nano-meter scale, using wide-field imaging. PMID:22506000

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

Simultaneous Correlative Scanning Electron and High-NA Fluorescence Microscopy

PubMed Central

Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Effting, Andries P. J.; Voorneveld, Philip W.; Lucas, Miriam S.; Hardwick, James C.; Wepf, Roger A.; Kruit, Pieter; Hoogenboom, Jacob P.

2013-01-01

Correlative light and electron microscopy (CLEM) is a unique method for investigating biological structure-function relations. With CLEM protein distributions visualized in fluorescence can be mapped onto the cellular ultrastructure measured with electron microscopy. Widespread application of correlative microscopy is hampered by elaborate experimental procedures related foremost to retrieving regions of interest in both modalities and/or compromises in integrated approaches. We present a novel approach to correlative microscopy, in which a high numerical aperture epi-fluorescence microscope and a scanning electron microscope illuminate the same area of a sample at the same time. This removes the need for retrieval of regions of interest leading to a drastic reduction of inspection times and the possibility for quantitative investigations of large areas and datasets with correlative microscopy. We demonstrate Simultaneous CLEM (SCLEM) analyzing cell-cell connections and membrane protrusions in whole uncoated colon adenocarcinoma cell line cells stained for actin and cortactin with AlexaFluor488. SCLEM imaging of coverglass-mounted tissue sections with both electron-dense and fluorescence staining is also shown. PMID:23409024

Non-linear non-local molecular electrodynamics with nano-optical fields.

PubMed

Chernyak, Vladimir Y; Saurabh, Prasoon; Mukamel, Shaul

2015-10-28

The interaction of optical fields sculpted on the nano-scale with matter may not be described by the dipole approximation since the fields may vary appreciably across the molecular length scale. Rather than incrementally adding higher multipoles, it is advantageous and more physically transparent to describe the optical process using non-local response functions that intrinsically include all multipoles. We present a semi-classical approach for calculating non-local response functions based on the minimal coupling Hamiltonian. The first, second, and third order response functions are expressed in terms of correlation functions of the charge and the current densities. This approach is based on the gauge invariant current rather than the polarization, and on the vector potential rather than the electric and magnetic fields.

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

PubMed Central

Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola

2016-01-01

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243

Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies.

PubMed

Hoischen, Christian; Monajembashi, Shamci; Weisshart, Klaus; Hemmerich, Peter

2018-01-01

The promyelocytic leukemia ( pml ) gene product PML is a tumor suppressor localized mainly in the nucleus of mammalian cells. In the cell nucleus, PML seeds the formation of macromolecular multiprotein complexes, known as PML nuclear bodies (PML NBs). While PML NBs have been implicated in many cellular functions including cell cycle regulation, survival and apoptosis their role as signaling hubs along major genome maintenance pathways emerged more clearly. However, despite extensive research over the past decades, the precise biochemical function of PML in these pathways is still elusive. It remains a big challenge to unify all the different previously suggested cellular functions of PML NBs into one mechanistic model. With the advent of genetically encoded fluorescent proteins it became possible to trace protein function in living specimens. In parallel, a variety of fluorescence fluctuation microscopy (FFM) approaches have been developed which allow precise determination of the biophysical and interaction properties of cellular factors at the single molecule level in living cells. In this report, we summarize the current knowledge on PML nuclear bodies and describe several fluorescence imaging, manipulation, FFM, and super-resolution techniques suitable to analyze PML body assembly and function. These include fluorescence redistribution after photobleaching, fluorescence resonance energy transfer, fluorescence correlation spectroscopy, raster image correlation spectroscopy, ultraviolet laser microbeam-induced DNA damage, erythrocyte-mediated force application, and super-resolution microscopy approaches. Since most if not all of the microscopic equipment to perform these techniques may be available in an institutional or nearby facility, we hope to encourage more researches to exploit sophisticated imaging tools for their research in cancer biology.

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

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Genomic and Functional Approaches to Understanding Cancer Aneuploidy.

PubMed

Taylor, Alison M; Shih, Juliann; Ha, Gavin; Gao, Galen F; Zhang, Xiaoyang; Berger, Ashton C; Schumacher, Steven E; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J; Cherniack, Andrew D; Beroukhim, Rameen; Meyerson, Matthew

2018-04-09

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Quantification of uncertainty in first-principles predicted mechanical properties of solids: Application to solid ion conductors

NASA Astrophysics Data System (ADS)

Ahmad, Zeeshan; Viswanathan, Venkatasubramanian

2016-08-01

Computationally-guided material discovery is being increasingly employed using a descriptor-based screening through the calculation of a few properties of interest. A precise understanding of the uncertainty associated with first-principles density functional theory calculated property values is important for the success of descriptor-based screening. The Bayesian error estimation approach has been built in to several recently developed exchange-correlation functionals, which allows an estimate of the uncertainty associated with properties related to the ground state energy, for example, adsorption energies. Here, we propose a robust and computationally efficient method for quantifying uncertainty in mechanical properties, which depend on the derivatives of the energy. The procedure involves calculating energies around the equilibrium cell volume with different strains and fitting the obtained energies to the corresponding energy-strain relationship. At each strain, we use instead of a single energy, an ensemble of energies, giving us an ensemble of fits and thereby, an ensemble of mechanical properties associated with each fit, whose spread can be used to quantify its uncertainty. The generation of ensemble of energies is only a post-processing step involving a perturbation of parameters of the exchange-correlation functional and solving for the energy non-self-consistently. The proposed method is computationally efficient and provides a more robust uncertainty estimate compared to the approach of self-consistent calculations employing several different exchange-correlation functionals. We demonstrate the method by calculating the uncertainty bounds for several materials belonging to different classes and having different structures using the developed method. We show that the calculated uncertainty bounds the property values obtained using three different GGA functionals: PBE, PBEsol, and RPBE. Finally, we apply the approach to calculate the uncertainty associated with the DFT-calculated elastic properties of solid state Li-ion and Na-ion conductors.

A classical density functional theory of ionic liquids.

PubMed

Forsman, Jan; Woodward, Clifford E; Trulsson, Martin

2011-04-28

We present a simple, classical density functional approach to the study of simple models of room temperature ionic liquids. Dispersion attractions as well as ion correlation effects and excluded volume packing are taken into account. The oligomeric structure, common to many ionic liquid molecules, is handled by a polymer density functional treatment. The theory is evaluated by comparisons with simulations, with an emphasis on the differential capacitance, an experimentally measurable quantity of significant practical interest.

Pilot dynamics for instrument approach tasks: Full panel multiloop and flight director operations

NASA Technical Reports Server (NTRS)

Weir, D. H.; Mcruer, D. T.

1972-01-01

Measurements and interpretations of single and mutiloop pilot response properties during simulated instrument approach are presented. Pilot subjects flew Category 2-like ILS approaches in a fixed base DC-8 simulaton. A conventional instrument panel and controls were used, with simulated vertical gust and glide slope beam bend forcing functions. Reduced and interpreted pilot describing functions and remmant are given for pitch attitude, flight director, and multiloop (longitudinal) control tasks. The response data are correlated with simultaneously recorded eye scanning statistics, previously reported in NASA CR-1535. The resulting combined response and scanning data and their interpretations provide a basis for validating and extending the theory of manual control displays.

Executive function, approach sensitivity, and emotional decision making as influences on risk behaviors in young adults.

PubMed

Patrick, Megan E; Blair, Clancy; Maggs, Jennifer L

2008-05-01

Relations among executive function, behavioral approach sensitivity, emotional decision making, and risk behaviors (alcohol use, drug use, and delinquent behavior) were examined in single female college students (N = 72). Hierarchical multiple regressions indicated a significant Approach Sensitivity x Working Memory interaction in which higher levels of alcohol use were associated with the combination of greater approach tendency and better working memory. This Approach Sensitivity x Working Memory interaction was also marginally significant for drug use and delinquency. Poor emotional decision making, as measured by a gambling task, was also associated with higher levels of alcohol use, but only for individuals low in inhibitory control. Findings point to the complexity of relations among aspects of self-regulation and personality and provide much needed data on neuropsychological correlates of risk behaviors in a nonclinical population.

The Effect of Group Therapy With Transactional Analysis Approach on Emotional Intelligence, Executive Functions and Drug Dependency.

PubMed

Forghani, Masoomeh; Ghanbari Hashem Abadi, Bahram Ali

2016-06-01

The aim of the present study was to evaluate the effect of group psychotherapy with transactional analysis (TA) approach on emotional intelligence (EI), executive functions and substance dependency among drug-addicts at rehabilitation centers in Mashhad city, Iran, in 2013. In this quasi-experimental study with pretest, posttest, case- control stages, 30 patients were selected from a rehabilitation center and randomly divided into two groups. The case group received 12 sessions of group psychotherapy with transactional analysis approach. Then the effects of independent variable (group psychotherapy with TA approach) on EI, executive function and drug dependency were assessed. The Bar-on test was used for EI, Stroop test for measuring executive function and morphine test, meth-amphetamines and B2 test for evaluating drug dependency. Data were analyzed using multifactorial covariance analysis, Levenes' analysis, MANCOVA, t-student and Pearson correlation coefficient tests t with SPSS software. Our results showed that group psychotherapy with the TA approach was effective in improving EI, executive functions and decreasing drug dependency (P < 0.05). The result of this study showed that group psychotherapy with TA approach has significant effects on addicts and prevents addiction recurrence by improving the coping capabilities and some mental functions of the subjects. However, there are some limitations regarding this study including follow-up duration and sample size.

Electrical impedance myography for the assessment of children with muscular dystrophy: a preliminary study

NASA Astrophysics Data System (ADS)

Rutkove, S. B.; Darras, B. T.

2013-04-01

Electrical impedance myography (EIM) provides a non-invasive approach for quantifying the severity of neuromuscular disease. Here we determine how well EIM data correlates to functional and ultrasound (US) measures of disease in children with Duchenne muscular dystrophy (DMD) and healthy subjects. Thirteen healthy boys, aged 2-12 years and 14 boys with DMD aged 4-12 years underwent both EIM and US measurements of deltoid, biceps, wrist flexors, quadriceps, tibialis anterior, and medial gastrocnemius. EIM measurements were performed with a custom-designed probe using a commercial multifrequency bioimpedance device. US luminosity data were quantified using a gray-scale analysis approach. Children also underwent the 6-minute walk test, timed tests and strength measurements. EIM and US data were combined across muscles. EIM 50 kHz phase was able to discriminate DMD children from healthy subjects with 98% accuracy. In the DMD patients, average EIM phase measurements also correlated well with standard functional measures. For example the 50 kHz phase correlated with the Northstar Ambulatory Assessment test (R = 0.83, p = 0.02). EIM 50 kHz phase and US correlated as well, with R = -0.79 (p < 0.001). These results show that EIM provides valuable objective measures Duchenne muscular dystrophy severity.

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

PubMed

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

2018-01-01

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

Limitations of the clump-correlation theories of shear-induced turbulence suppression

NASA Astrophysics Data System (ADS)

Zhang, Y. Z.; Mahajan, S. M.

2017-05-01

The clump theory, primarily constructed by Dupree [Phys. Fluids 15, 334 (1972)] based on the moment approach and then generalized to the correlation theory [Y. Z. Zhang and S. M. Mahajan, Phys. Fluids B 5, 2000 (1993)], has long served as a basis for constructing theories of turbulence suppression by shear flow. In order to reveal the "intrinsic approximation" invoked in the clump-correlation theory, we examine a model based on two dimensional magnetized drift waves. After a rigorous derivation of the exact response function—a key to average the Green function of the system—we show that the Dupree, Zhang-Mahajan approach is recovered as the lowest order approximation in a small dimensionless parameter ϒ which is a triple product of the correlation time, wave number, and fluctuating drift velocity. The clump-correlation theory, thus, constitutes the Gaussian and lowest order non-Markovian process for a homogeneous stationary turbulence. We also provide, especially for the tokamak community, a readily usable formula to evaluate the effectiveness of shear-flow suppression; this formula pertains regardless of the specific model of correlation time.

Asymptotic behaviour of two-point functions in multi-species models

NASA Astrophysics Data System (ADS)

Kozlowski, Karol K.; Ragoucy, Eric

2016-05-01

We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU (3)-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.

Quantum Monte Carlo for atoms and molecules

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

Barnett, R.N.

1989-11-01

The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H{sub 2}, LiH, Li{sub 2}, and H{sub 2}O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li{sub 2}, and H{sub 2}O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations,more » the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions.« less

Disambiguating brain functional connectivity.

PubMed

Duff, Eugene P; Makin, Tamar; Cottaar, Michiel; Smith, Stephen M; Woolrich, Mark W

2018-06-01

Functional connectivity (FC) analyses of correlations of neural activity are used extensively in neuroimaging and electrophysiology to gain insights into neural interactions. However, analyses assessing changes in correlation fail to distinguish effects produced by sources as different as changes in neural signal amplitudes or noise levels. This ambiguity substantially diminishes the value of FC for inferring system properties and clinical states. Network modelling approaches may avoid ambiguities, but require specific assumptions. We present an enhancement to FC analysis with improved specificity of inferences, minimal assumptions and no reduction in flexibility. The Additive Signal Change (ASC) approach characterizes FC changes into certain prevalent classes of signal change that involve the input of additional signal to existing activity. With FMRI data, the approach reveals a rich diversity of signal changes underlying measured changes in FC, suggesting that it could clarify our current understanding of FC changes in many contexts. The ASC method can also be used to disambiguate other measures of dependency, such as regression and coherence, providing a flexible tool for the analysis of neural data. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Thermal noise model of antiferromagnetic dynamics: A macroscopic approach

NASA Astrophysics Data System (ADS)

Li, Xilai; Semenov, Yuriy; Kim, Ki Wook

In the search for post-silicon technologies, antiferromagnetic (AFM) spintronics is receiving widespread attention. Due to faster dynamics when compared with its ferromagnetic counterpart, AFM enables ultra-fast magnetization switching and THz oscillations. A crucial factor that affects the stability of antiferromagnetic dynamics is the thermal fluctuation, rarely considered in AFM research. Here, we derive from theory both stochastic dynamic equations for the macroscopic AFM Neel vector (L-vector) and the corresponding Fokker-Plank equation for the L-vector distribution function. For the dynamic equation approach, thermal noise is modeled by a stochastic fluctuating magnetic field that affects the AFM dynamics. The field is correlated within the correlation time and the amplitude is derived from the energy dissipation theory. For the distribution function approach, the inertial behavior of AFM dynamics forces consideration of the generalized space, including both coordinates and velocities. Finally, applying the proposed thermal noise model, we analyze a particular case of L-vector reversal of AFM nanoparticles by voltage controlled perpendicular magnetic anisotropy (PMA) with a tailored pulse width. This work was supported, in part, by SRC/NRI SWAN.

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Hybrid density-functional calculations of phonons in LaCoO3

NASA Astrophysics Data System (ADS)

Gryaznov, Denis; Evarestov, Robert A.; Maier, Joachim

2010-12-01

Phonon frequencies at Γ point in nonmagnetic rhombohedral phase of LaCoO3 were calculated using density-functional theory with hybrid exchange correlation functional PBE0. The calculations involved a comparison of results for two types of basis functions commonly used in ab initio calculations, namely, the plane-wave approach and linear combination of atomic orbitals, as implemented in VASP and CRYSTAL computer codes, respectively. A good qualitative, but also within an error margin of less than 30%, a quantitative agreement was observed not only between the two formalisms but also between theoretical and experimental phonon frequency predictions. Moreover, the correlation between the phonon symmetries in cubic and rhombohedral phases is discussed in detail on the basis of group-theoretical analysis. It is concluded that the hybrid PBE0 functional is able to predict correctly the phonon properties in LaCoO3 .

Molecular Excitation Energies from Time-Dependent Density Functional Theory Employing Random-Phase Approximation Hessians with Exact Exchange.

PubMed

Heßelmann, Andreas

2015-04-14

Molecular excitation energies have been calculated with time-dependent density-functional theory (TDDFT) using random-phase approximation Hessians augmented with exact exchange contributions in various orders. It has been observed that this approach yields fairly accurate local valence excitations if combined with accurate asymptotically corrected exchange-correlation potentials used in the ground-state Kohn-Sham calculations. The inclusion of long-range particle-particle with hole-hole interactions in the kernel leads to errors of 0.14 eV only for the lowest excitations of a selection of three alkene, three carbonyl, and five azabenzene molecules, thus surpassing the accuracy of a number of common TDDFT and even some wave function correlation methods. In the case of long-range charge-transfer excitations, the method typically underestimates accurate reference excitation energies by 8% on average, which is better than with standard hybrid-GGA functionals but worse compared to range-separated functional approximations.

Robust validation of approximate 1-matrix functionals with few-electron harmonium atoms

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

Cioslowski, Jerzy, E-mail: jerzy@wmf.univ.szczecin.pl; Piris, Mario; Matito, Eduard

2015-12-07

A simple comparison between the exact and approximate correlation components U of the electron-electron repulsion energy of several states of few-electron harmonium atoms with varying confinement strengths provides a stringent validation tool for 1-matrix functionals. The robustness of this tool is clearly demonstrated in a survey of 14 known functionals, which reveals their substandard performance within different electron correlation regimes. Unlike spot-testing that employs dissociation curves of diatomic molecules or more extensive benchmarking against experimental atomization energies of molecules comprising some standard set, the present approach not only uncovers the flaws and patent failures of the functionals but, even moremore » importantly, also allows for pinpointing their root causes. Since the approximate values of U are computed at exact 1-densities, the testing requires minimal programming and thus is particularly suitable for rapid screening of new functionals.« less

First-Principles Momentum-Dependent Local Ansatz Wavefunction and Momentum Distribution Function Bands of Iron

NASA Astrophysics Data System (ADS)

Kakehashi, Yoshiro; Chandra, Sumal

2016-04-01

We have developed a first-principles local ansatz wavefunction approach with momentum-dependent variational parameters on the basis of the tight-binding LDA+U Hamiltonian. The theory goes beyond the first-principles Gutzwiller approach and quantitatively describes correlated electron systems. Using the theory, we find that the momentum distribution function (MDF) bands of paramagnetic bcc Fe along high-symmetry lines show a large deviation from the Fermi-Dirac function for the d electrons with eg symmetry and yield the momentum-dependent mass enhancement factors. The calculated average mass enhancement m*/m = 1.65 is consistent with low-temperature specific heat data as well as recent angle-resolved photoemission spectroscopy (ARPES) data.

Density-Functional Theory with Dispersion-Correcting Potentials for Methane: Bridging the Efficiency and Accuracy Gap between High-Level Wave Function and Classical Molecular Mechanics Methods.

PubMed

Torres, Edmanuel; DiLabio, Gino A

2013-08-13

Large clusters of noncovalently bonded molecules can only be efficiently modeled by classical mechanics simulations. One prominent challenge associated with this approach is obtaining force-field parameters that accurately describe noncovalent interactions. High-level correlated wave function methods, such as CCSD(T), are capable of correctly predicting noncovalent interactions, and are widely used to produce reference data. However, high-level correlated methods are generally too computationally costly to generate the critical reference data required for good force-field parameter development. In this work we present an approach to generate Lennard-Jones force-field parameters to accurately account for noncovalent interactions. We propose the use of a computational step that is intermediate to CCSD(T) and classical molecular mechanics, that can bridge the accuracy and computational efficiency gap between them, and demonstrate the efficacy of our approach with methane clusters. On the basis of CCSD(T)-level binding energy data for a small set of methane clusters, we develop methane-specific, atom-centered, dispersion-correcting potentials (DCPs) for use with the PBE0 density-functional and 6-31+G(d,p) basis sets. We then use the PBE0-DCP approach to compute a detailed map of the interaction forces associated with the removal of a single methane molecule from a cluster of eight methane molecules and use this map to optimize the Lennard-Jones parameters for methane. The quality of the binding energies obtained by the Lennard-Jones parameters we obtained is assessed on a set of methane clusters containing from 2 to 40 molecules. Our Lennard-Jones parameters, used in combination with the intramolecular parameters of the CHARMM force field, are found to closely reproduce the results of our dispersion-corrected density-functional calculations. The approach outlined can be used to develop Lennard-Jones parameters for any kind of molecular system.

Impact of Androgen Deprivation Therapy on Self-Reported Cognitive Function in Men with Prostate Cancer.

PubMed

Marzouk, Shireen; Naglie, Gary; Tomlinson, George; Duff Canning, Sarah; Breunis, Henriette; Timilshina, Narhari; Alibhai, Shabbir M H

2018-03-01

Although androgen deprivation therapy is widely used to treat prostate cancer, its effects on cognitive function are unclear. To our knowledge no prior report has examined the impact of androgen deprivation therapy on self-reported cognitive function. Three groups of men 50 years old or older who were matched on age and education were enrolled in the study, including 81 with prostate cancer starting on continuous androgen deprivation therapy, 84 controls with prostate cancer not receiving androgen deprivation therapy and 85 healthy controls. Two scales from the FACT-Cog (Functional Assessment of Cancer Therapy-Cognitive subscale) version 3 were used to assess self-reported cognitive function. Changes in cognitive scores with time were analyzed by 2 approaches, including 1) multivariable regression and 2) calculation of the proportion of subjects per group with a decrease of 1 SD or more. Multivariable regression was applied to assess predictors of a decline in self-reported cognitive function. We also examined relationships between the FACT-Cog and a neuropsychological battery of 15 tests. Mean participant age was 69 years (range 50 to 87). The mean educational level was 15 years (range 8 to 24). FACT-Cog scores were similar at baseline across the cohorts. Neither analytical approach revealed that androgen deprivation therapy was associated with changes in self-reported cognitive function on either FACT-Cog scale. Mood and fatigue correlated with changes in self-reported cognitive function. The relationship between self-reported and objective cognitive measures was weak (maximum Spearman correlation coefficient 0.14) and only 2 of 30 correlations were statistically significant. A total of 12 months of androgen deprivation therapy were not associated with self-reported cognitive function changes in older men with nonmetastatic prostate cancer. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Functional Brain Connectome and Its Relation to Hoehn and Yahr Stage in Parkinson Disease.

PubMed

Suo, Xueling; Lei, Du; Li, Nannan; Cheng, Lan; Chen, Fuqin; Wang, Meiyun; Kemp, Graham J; Peng, Rong; Gong, Qiyong

2017-12-01

Purpose To use resting-state functional magnetic resonance (MR) imaging and graph theory approaches to investigate the brain functional connectome and its potential relation to disease severity in Parkinson disease (PD). Materials and Methods This case-control study was approved by the local research ethics committee, and all participants provided informed consent. There were 153 right-handed patients with PD and 81 healthy control participants recruited who were matched for age, sex, and handedness to undergo a 3-T resting-state functional MR examination. The whole-brain functional connectome was constructed by thresholding the Pearson correlation matrices of 90 brain regions, and the topologic properties were analyzed by using graph theory approaches. Nonparametric permutation tests were used to compare topologic properties, and their relationship to disease severity was assessed. Results The functional connectome in PD showed abnormalities at the global level (ie, decrease in clustering coefficient, global efficiency, and local efficiency, and increase in characteristic path length) and at the nodal level (decreased nodal centralities in the sensorimotor cortex, default mode, and temporal-occipital regions; P < .001, false discovery rate corrected). Further, the nodal centralities in left postcentral gyrus and left superior temporal gyrus correlated negatively with Unified Parkinson's Disease Rating Scale III score (P = .038, false discovery rate corrected, r = -0.198; and P = .009, false discovery rate corrected, r = -0.270, respectively) and decreased with increasing Hoehn and Yahr stage in patients with PD. Conclusion The configurations of brain functional connectome in patients with PD were perturbed and correlated with disease severity, notably with those responsible for motor functions. These results provide topologic insights into understanding the neural functional changes in relation to disease severity of PD. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on September 11, 2017.

A statistically compiled test battery for feasible evaluation of knee function after rupture of the Anterior Cruciate Ligament - derived from long-term follow-up data.

PubMed

Schelin, Lina; Tengman, Eva; Ryden, Patrik; Häger, Charlotte

2017-01-01

Clinical test batteries for evaluation of knee function after injury to the Anterior Cruciate Ligament (ACL) should be valid and feasible, while reliably capturing the outcome of rehabilitation. There is currently a lack of consensus as to which of the many available assessment tools for knee function that should be included. The present aim was to use a statistical approach to investigate the contribution of frequently used tests to avoid redundancy, and filter them down to a proposed comprehensive and yet feasible test battery for long-term evaluation after ACL injury. In total 48 outcome variables related to knee function, all potentially relevant for a long-term follow-up, were included from a cross-sectional study where 70 ACL-injured (17-28 years post injury) individuals were compared to 33 controls. Cluster analysis and logistic regression were used to group variables and identify an optimal test battery, from which a summarized estimator of knee function representing various functional aspects was derived. As expected, several variables were strongly correlated, and the variables also fell into logical clusters with higher within-correlation (max ρ = 0.61) than between clusters (max ρ = 0.19). An extracted test battery with just four variables assessing one-leg balance, isokinetic knee extension strength and hop performance (one-leg hop, side hop) were mathematically combined to an estimator of knee function, which acceptably classified ACL-injured individuals and controls. This estimator, derived from objective measures, correlated significantly with self-reported function, e.g. Lysholm score (ρ = 0.66; p<0.001). The proposed test battery, based on a solid statistical approach, includes assessments which are all clinically feasible, while also covering complementary aspects of knee function. Similar test batteries could be determined for earlier phases of ACL rehabilitation or to enable longitudinal monitoring. Such developments, established on a well-grounded consensus of measurements, would facilitate comparisons of studies and enable evidence-based rehabilitation.

Toward calculations of the 129Xe chemical shift in Xe@C60 at experimental conditions: relativity, correlation, and dynamics.

PubMed

Straka, Michal; Lantto, Perttu; Vaara, Juha

2008-03-27

We calculate the 129Xe chemical shift in endohedral Xe@C60 with systematic inclusion of the contributing physical effects to model the real experimental conditions. These are relativistic effects, electron correlation, the temperature-dependent dynamics, and solvent effects. The ultimate task is to obtain the right result for the right reason and to develop a physically justified methodological model for calculations and simulations of endohedral Xe fullerenes and other confined Xe systems. We use the smaller Xe...C6H6 model to calibrate density functional theory approaches against accurate correlated wave function methods. Relativistic effects as well as the coupling of relativity and electron correlation are evaluated using the leading-order Breit-Pauli perturbation theory. The dynamic effects are treated in two ways. In the first approximation, quantum dynamics of the Xe atom in a rigid cage takes advantage of the centrosymmetric potential for Xe within the thermally accessible distance range from the center of the cage. This reduces the problem of obtaining the solution of a diatomic rovibrational problem. In the second approach, first-principles classical molecular dynamics on the density functional potential energy hypersurface is used to produce the dynamical trajectory for the whole system, including the dynamic cage. Snapshots from the trajectory are used for calculations of the dynamic contribution to the absorption 129Xe chemical shift. The calculated nonrelativistic Xe shift is found to be highly sensitive to the optimized molecular structure and to the choice of the exchange-correlation functional. Relativistic and dynamic effects are significant and represent each about 10% of the nonrelativistic static shift at the minimum structure. While the role of the Xe dynamics inside of the rigid cage is negligible, the cage dynamics turns out to be responsible for most of the dynamical correction to the 129Xe shift. Solvent effects evaluated with a polarized continuum model are found to be very small.

iCI: Iterative CI toward full CI.

PubMed

Liu, Wenjian; Hoffmann, Mark R

2016-03-08

It is shown both theoretically and numerically that the minimal multireference configuration interaction (CI) approach [Liu, W.; Hoffmann, M. R. Theor. Chem. Acc. 2014, 133, 1481] converges quickly and monotonically from above to full CI by updating the primary, external, and secondary states that describe the respective static, dynamic, and again static components of correlation iteratively, even when starting with a rather poor description of a strongly correlated system. In short, the iterative CI (iCI) is a very effective means toward highly correlated wave functions and, ultimately, full CI.

Towards a model-based cognitive neuroscience of stopping - a neuroimaging perspective.

PubMed

Sebastian, Alexandra; Forstmann, Birte U; Matzke, Dora

2018-07-01

Our understanding of the neural correlates of response inhibition has greatly advanced over the last decade. Nevertheless the specific function of regions within this stopping network remains controversial. The traditional neuroimaging approach cannot capture many processes affecting stopping performance. Despite the shortcomings of the traditional neuroimaging approach and a great progress in mathematical and computational models of stopping, model-based cognitive neuroscience approaches in human neuroimaging studies are largely lacking. To foster model-based approaches to ultimately gain a deeper understanding of the neural signature of stopping, we outline the most prominent models of response inhibition and recent advances in the field. We highlight how a model-based approach in clinical samples has improved our understanding of altered cognitive functions in these disorders. Moreover, we show how linking evidence-accumulation models and neuroimaging data improves the identification of neural pathways involved in the stopping process and helps to delineate these from neural networks of related but distinct functions. In conclusion, adopting a model-based approach is indispensable to identifying the actual neural processes underlying stopping. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach

NASA Astrophysics Data System (ADS)

Panholzer, Martin; Gatti, Matteo; Reining, Lucia

2018-04-01

The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 rs or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach.

PubMed

Panholzer, Martin; Gatti, Matteo; Reining, Lucia

2018-04-20

The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 r_{s} or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

Estimation of gas and tissue lung volumes by MRI: functional approach of lung imaging.

PubMed

Qanadli, S D; Orvoen-Frija, E; Lacombe, P; Di Paola, R; Bittoun, J; Frija, G

1999-01-01

The purpose of this work was to assess the accuracy of MRI for the determination of lung gas and tissue volumes. Fifteen healthy subjects underwent MRI of the thorax and pulmonary function tests [vital capacity (VC) and total lung capacity (TLC)] in the supine position. MR examinations were performed at inspiration and expiration. Lung volumes were measured by a previously validated technique on phantoms. Both individual and total lung volumes and capacities were calculated. MRI total vital capacity (VC(MRI)) was compared with spirometric vital capacity (VC(SP)). Capacities were correlated to lung volumes. Tissue volume (V(T)) was estimated as the difference between the total lung volume at full inspiration and the TLC. No significant difference was seen between VC(MRI) and VC(SP). Individual capacities were well correlated (r = 0.9) to static volume at full inspiration. The V(T) was estimated to be 836+/-393 ml. This preliminary study demonstrates that MRI can accurately estimate lung gas and tissue volumes. The proposed approach appears well suited for functional imaging of the lung.

Partition-free theory of time-dependent current correlations in nanojunctions in response to an arbitrary time-dependent bias

NASA Astrophysics Data System (ADS)

Ridley, Michael; MacKinnon, Angus; Kantorovich, Lev

2017-04-01

Working within the nonequilibrium Green's function formalism, a formula for the two-time current correlation function is derived for the case of transport through a nanojunction in response to an arbitrary time-dependent bias. The one-particle Hamiltonian and the wide-band limit approximation are assumed, enabling us to extract all necessary Green's functions and self-energies for the system, extending the analytic work presented previously [Ridley et al., Phys. Rev. B 91, 125433 (2015), 10.1103/PhysRevB.91.125433]. We show that our expression for the two-time correlation function generalizes the Büttiker theory of shot and thermal noise on the current through a nanojunction to the time-dependent bias case including the transient regime following the switch-on. Transient terms in the correlation function arise from an initial state that does not assume (as is usually done) that the system is initially uncoupled, i.e., our approach is partition free. We show that when the bias loses its time dependence, the long-time limit of the current correlation function depends on the time difference only, as in this case an ideal steady state is reached. This enables derivation of known results for the single-frequency power spectrum and for the zero-frequency limit of this power spectrum. In addition, we present a technique which facilitates fast calculations of the transient quantum noise, valid for arbitrary temperature, time, and voltage scales. We apply this formalism to a molecular wire system for both dc and ac biases, and find a signature of the traversal time for electrons crossing the wire in the time-dependent cross-lead current correlations.

Atom and Bond Fukui Functions and Matrices: A Hirshfeld-I Atoms-in-Molecule Approach.

PubMed

Oña, Ofelia B; De Clercq, Olivier; Alcoba, Diego R; Torre, Alicia; Lain, Luis; Van Neck, Dimitri; Bultinck, Patrick

2016-09-19

The Fukui function is often used in its atom-condensed form by isolating it from the molecular Fukui function using a chosen weight function for the atom in the molecule. Recently, Fukui functions and matrices for both atoms and bonds separately were introduced for semiempirical and ab initio levels of theory using Hückel and Mulliken atoms-in-molecule models. In this work, a double partitioning method of the Fukui matrix is proposed within the Hirshfeld-I atoms-in-molecule framework. Diagonalizing the resulting atomic and bond matrices gives eigenvalues and eigenvectors (Fukui orbitals) describing the reactivity of atoms and bonds. The Fukui function is the diagonal element of the Fukui matrix and may be resolved in atom and bond contributions. The extra information contained in the atom and bond resolution of the Fukui matrices and functions is highlighted. The effect of the choice of weight function arising from the Hirshfeld-I approach to obtain atom- and bond-condensed Fukui functions is studied. A comparison of the results with those generated by using the Mulliken atoms-in-molecule approach shows low correlation between the two partitioning schemes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Scale-dependence of transverse momentum correlations in PbAu collisions at 158A GeV/c

NASA Astrophysics Data System (ADS)

Ceres Collaboration; Adamová, D.; Agakichiev, G.; Antończyk, D.; Appelshäuser, H.; Belaga, V.; Bielcikova, S.; Braun-Munzinger, P.; Busch, O.; Cherlin, A.; Damjanović, S.; Dietel, T.; Dietrich, L.; Drees, A.; Dubitzky, W.; Esumi, S. I.; Filimonov, K.; Fomenko, K.; Fraenkel, Z.; Garabatos, C.; Glässel, P.; Holeczek, J.; Kushpil, V.; Maas, A.; Marín, A.; Milošević, J.; Milov, A.; Miśkowiec, D.; Panebrattsev, Yu.; Petchenova, O.; Petráček, V.; Pfeiffer, A.; Płoskoń, M.; Radomski, S.; Rak, J.; Ravinovich, I.; Rehak, P.; Sako, H.; Schmitz, W.; Sedykh, S.; Shimansky, S.; Stachel, J.; Šumbera, M.; Tilsner, H.; Tserruya, I.; Tsiledakis, G.; Wessels, J. P.; Wienold, T.; Wurm, J. P.; Xie, W.; Yurevich, S.; Yurevich, V.

2008-10-01

We present results on transverse momentum correlations of charged particle pairs produced in PbAu collisions at 158A GeV/c at the Super Proton Synchrotron. The transverse momentum correlations have been studied as a function of collision centrality, angular separation of the particle pairs, transverse momentum and charge sign. We demonstrate that the results are in agreement with previous findings in scale-independent analyses at the same beam energy. Employing the two-particle momentum correlator <Δp,Δp> and the cumulative p variable x(p), we identify, using the scale-dependent approach presented in this paper, different sources contributing to the measured correlations, such as quantum and Coulomb correlations, elliptic flow and mini-jet fragmentation.

Reporting Recommended Patch Density from Vehicle Panel Vibration Convergence Studies using both DAF and TBL Fits of the Spatial Correlation Function

NASA Technical Reports Server (NTRS)

Smith, Andrew M.; Davis, Robert Ben; LaVerde, Bruce T.; Jones, Douglas C.; Band, Jonathon L.

2012-01-01

Using the patch method to represent the continuous spatial correlation function of a phased pressure field over a structural surface is an approximation. The approximation approaches the continuous function as patches become smaller. Plotting comparisons of the approximation vs the continuous function may provide insight revealing: (1) For what patch size/density should the approximation be very good? (2) What the approximation looks like when it begins to break down? (3) What the approximation looks like when the patch size is grossly too large. Following these observations with a convergence study using one FEM may allow us to see the importance of patch density. We may develop insights that help us to predict sufficient patch density to provide adequate convergence for the intended purpose frequency range of interest

Proprioception: where are we now? A commentary on clinical assessment, changes across the life course, functional implications and future interventions.

PubMed

Suetterlin, Karen Joan; Sayer, Avan Aihie

2014-05-01

Proprioception, the sense of where one is in space, is essential for effective interaction with the environment. A lack of or reduction in proprioceptive acuity has been directly correlated with falls and with reduced functional independence in older people. Proprioceptive losses have also been shown to negatively correlate with functional recovery post stroke and play a significant role in other conditions such as Parkinson's disease. However, despite its central importance to many geriatric syndromes, the clinical assessment of proprioception has remained remarkably static. We look at approaches to the clinical assessment of proprioception, changes in proprioception across the life course, functional implications of proprioception in health and disease and the potential for targeted interventions in the future such as joint taping, and proprioception-specific rehabilitation and footwear.

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.

Nonequilibrium Langevin approach to quantum optics in semiconductor microcavities

NASA Astrophysics Data System (ADS)

Portolan, S.; di Stefano, O.; Savasta, S.; Rossi, F.; Girlanda, R.

2008-01-01

Recently, the possibility of generating nonclassical polariton states by means of parametric scattering has been demonstrated. Excitonic polaritons propagate in a complex interacting environment and contain real electronic excitations subject to scattering events and noise affecting quantum coherence and entanglement. Here, we present a general theoretical framework for the realistic investigation of polariton quantum correlations in the presence of coherent and incoherent interaction processes. The proposed theoretical approach is based on the nonequilibrium quantum Langevin approach for open systems applied to interacting-electron complexes described within the dynamics controlled truncation scheme. It provides an easy recipe to calculate multitime correlation functions which are key quantities in quantum optics. As a first application, we analyze the buildup of polariton parametric emission in semiconductor microcavities including the influence of noise originating from phonon-induced scattering.

Dynamics of Intersubject Brain Networks during Anxious Anticipation

PubMed Central

Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz

2017-01-01

How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184

On One Possible Generalization of the Regression Theorem

NASA Astrophysics Data System (ADS)

Bogolubov, N. N.; Soldatov, A. V.

2018-03-01

A general approach to derivation of formally exact closed time-local or time-nonlocal evolution equations for non-equilibrium multi-time correlations functions made of observables of an open quantum system interacting simultaneously with external time-dependent classical fields and dissipative environment is discussed. The approach allows for the subsequent treatment of these equations within a perturbative scheme assuming that the system-environment interaction is weak.

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Validation of Vehicle Panel/Equipment Response from Diffuse Acoustic Field Excitation Using Spatially Correlated Transfer Function Approach

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Fulcher, Clay; Hunt, Ron

2012-01-01

An approach for predicting the vibration, strain, and force responses of a flight-like vehicle panel assembly to acoustic pressures is presented. Important validation for the approach is provided by comparison to ground test measurements in a reverberant chamber. The test article and the corresponding analytical model were assembled in several configurations to demonstrate the suitability of the approach for response predictions when the vehicle panel is integrated with equipment. Critical choices in the analysis necessary for convergence of the predicted and measured responses are illustrated through sensitivity studies. The methodology includes representation of spatial correlation of the pressure field over the panel surface. Therefore, it is possible to demonstrate the effects of hydrodynamic coincidence in the response. The sensitivity to pressure patch density clearly illustrates the onset of coincidence effects on the panel response predictions.

Spatial correlation of the dynamic propensity of a glass-forming liquid

NASA Astrophysics Data System (ADS)

Razul, M. Shajahan G.; Matharoo, Gurpreet S.; Poole, Peter H.

2011-06-01

We present computer simulation results on the dynamic propensity (as defined by Widmer-Cooper et al 2004 Phys. Rev. Lett. 93 135701) in a Kob-Andersen binary Lennard-Jones liquid system consisting of 8788 particles. We compute the spatial correlation function for the dynamic propensity as a function of both the reduced temperature T, and the time scale on which the particle displacements are measured. For T <= 0.6, we find that non-zero correlations occur at the largest length scale accessible in our system. We also show that a cluster-size analysis of particles with extremal values of the dynamic propensity, as well as 3D visualizations, reveal spatially correlated regions that approach the size of our system as T decreases, consistently with the behavior of the spatial correlation function. Next, we define and examine the 'coordination propensity', the isoconfigurational average of the coordination number of the minority B particles around the majority A particles. We show that a significant correlation exists between the spatial fluctuations of the dynamic and coordination propensities. In addition, we find non-zero correlations of the coordination propensity occurring at the largest length scale accessible in our system for all T in the range 0.466 < T < 1.0. We discuss the implications of these results for understanding the length scales of dynamical heterogeneity in glass-forming liquids.

Role of non-local exchange in the electronic structure of correlated oxides

NASA Astrophysics Data System (ADS)

Iori, Federico; Gatti, Matteo; Rubio Secades, Angel

Transition-metal oxides (TMO) with partially filled d or f shells are a prototype of correlated materials. They exhibit very interesting properties, like metal-insulator phase transitions (MIT). In this work we consider several TMO insulators in which Kohn-Sham LDA band structures are metallic: VO2, V2O3, Ti2O3, LaTiO3 and YTiO3. In the past, this failure of LDA has been explained in terms of its inadequacy to capture the strong interactions taking place between correlated electrons. In the spirit of the Hubbard model, possible corrections to improve onsite correlation are the LDA +U and LDA +DMFT approaches. Here we make use of the HSE06 hybrid functional. We show that, without invoking strong-correlation effects, the contribution of the non-local Fock exchange is essential to correct the LDA results, by curing its delocalization error. In fact, HSE06 provides insulating band structures and correctly describes the MIT in all the considered compounds. We further discuss the advantages and the limitations of the HSE06 hybrid functional in correlated TMO

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

Exact Time-Dependent Exchange-Correlation Potential in Electron Scattering Processes

NASA Astrophysics Data System (ADS)

Suzuki, Yasumitsu; Lacombe, Lionel; Watanabe, Kazuyuki; Maitra, Neepa T.

2017-12-01

We identify peak and valley structures in the exact exchange-correlation potential of time-dependent density functional theory that are crucial for time-resolved electron scattering in a model one-dimensional system. These structures are completely missed by adiabatic approximations that, consequently, significantly underestimate the scattering probability. A recently proposed nonadiabatic approximation is shown to correctly capture the approach of the electron to the target when the initial Kohn-Sham state is chosen judiciously, and it is more accurate than standard adiabatic functionals but ultimately fails to accurately capture reflection. These results may explain the underestimation of scattering probabilities in some recent studies on molecules and surfaces.

A multivariate extension of mutual information for growing neural networks.

PubMed

Ball, Kenneth R; Grant, Christopher; Mundy, William R; Shafer, Timothy J

2017-11-01

Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson's correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generalized Langevin dynamics of a nanoparticle using a finite element approach: Thermostating with correlated noise

NASA Astrophysics Data System (ADS)

Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.

2011-09-01

A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.

Integrated data analysis for genome-wide research.

PubMed

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

2007-01-01

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

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

PubMed

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

2018-02-16

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

EEG-based functional networks evoked by acupuncture at ST 36: A data-driven thresholding study

NASA Astrophysics Data System (ADS)

Li, Huiyan; Wang, Jiang; Yi, Guosheng; Deng, Bin; Zhou, Hexi

2017-10-01

This paper investigates how acupuncture at ST 36 modulates the brain functional network. 20 channel EEG signals from 15 healthy subjects are respectively recorded before, during and after acupuncture. The correlation between two EEG channels is calculated by using Pearson’s coefficient. A data-driven approach is applied to determine the threshold, which is performed by considering the connected set, connected edge and network connectivity. Based on such thresholding approach, the functional network in each acupuncture period is built with graph theory, and the associated functional connectivity is determined. We show that acupuncturing at ST 36 increases the connectivity of the EEG-based functional network, especially for the long distance ones between two hemispheres. The properties of the functional network in five EEG sub-bands are also characterized. It is found that the delta and gamma bands are affected more obviously by acupuncture than the other sub-bands. These findings highlight the modulatory effects of acupuncture on the EEG-based functional connectivity, which is helpful for us to understand how it participates in the cortical or subcortical activities. Further, the data-driven threshold provides an alternative approach to infer the functional connectivity under other physiological conditions.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package.

PubMed

Womack, James C; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-28

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package

NASA Astrophysics Data System (ADS)

Womack, James C.; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-01

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Quantifying confidence in density functional theory predictions of magnetic ground states

NASA Astrophysics Data System (ADS)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there needs to be a systematic test of a collection of plausible magnetic states, especially in identifying antiferromagnetic (AFM) ground states. We believe that our approach of estimating uncertainty can be readily incorporated into all high-throughput computational material discovery efforts and this will lead to a dramatic increase in the likelihood of finding good candidate materials.

Genomic and Proteomic Profiling Reveals Reduced Mitochondrial Function and Disruption of the Neuromuscular Junction Driving Rat Sarcopenia

PubMed Central

Ibebunjo, Chikwendu; Chick, Joel M.; Kendall, Tracee; Eash, John K.; Li, Christine; Zhang, Yunyu; Vickers, Chad; Wu, Zhidan; Clarke, Brian A.; Shi, Jun; Cruz, Joseph; Fournier, Brigitte; Brachat, Sophie; Gutzwiller, Sabine; Ma, QiCheng; Markovits, Judit; Broome, Michelle; Steinkrauss, Michelle; Skuba, Elizabeth; Galarneau, Jean-Rene; Gygi, Steven P.

2013-01-01

Molecular mechanisms underlying sarcopenia, the age-related loss of skeletal muscle mass and function, remain unclear. To identify molecular changes that correlated best with sarcopenia and might contribute to its pathogenesis, we determined global gene expression profiles in muscles of rats aged 6, 12, 18, 21, 24, and 27 months. These rats exhibit sarcopenia beginning at 21 months. Correlation of the gene expression versus muscle mass or age changes, and functional annotation analysis identified gene signatures of sarcopenia distinct from gene signatures of aging. Specifically, mitochondrial energy metabolism (e.g., tricarboxylic acid cycle and oxidative phosphorylation) pathway genes were the most downregulated and most significantly correlated with sarcopenia. Also, perturbed were genes/pathways associated with neuromuscular junction patency (providing molecular evidence of sarcopenia-related functional denervation and neuromuscular junction remodeling), protein degradation, and inflammation. Proteomic analysis of samples at 6, 18, and 27 months confirmed the depletion of mitochondrial energy metabolism proteins and neuromuscular junction proteins. Together, these findings suggest that therapeutic approaches that simultaneously stimulate mitochondrogenesis and reduce muscle proteolysis and inflammation have potential for treating sarcopenia. PMID:23109432

Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies

PubMed Central

Hoischen, Christian; Monajembashi, Shamci; Weisshart, Klaus; Hemmerich, Peter

2018-01-01

The promyelocytic leukemia (pml) gene product PML is a tumor suppressor localized mainly in the nucleus of mammalian cells. In the cell nucleus, PML seeds the formation of macromolecular multiprotein complexes, known as PML nuclear bodies (PML NBs). While PML NBs have been implicated in many cellular functions including cell cycle regulation, survival and apoptosis their role as signaling hubs along major genome maintenance pathways emerged more clearly. However, despite extensive research over the past decades, the precise biochemical function of PML in these pathways is still elusive. It remains a big challenge to unify all the different previously suggested cellular functions of PML NBs into one mechanistic model. With the advent of genetically encoded fluorescent proteins it became possible to trace protein function in living specimens. In parallel, a variety of fluorescence fluctuation microscopy (FFM) approaches have been developed which allow precise determination of the biophysical and interaction properties of cellular factors at the single molecule level in living cells. In this report, we summarize the current knowledge on PML nuclear bodies and describe several fluorescence imaging, manipulation, FFM, and super-resolution techniques suitable to analyze PML body assembly and function. These include fluorescence redistribution after photobleaching, fluorescence resonance energy transfer, fluorescence correlation spectroscopy, raster image correlation spectroscopy, ultraviolet laser microbeam-induced DNA damage, erythrocyte-mediated force application, and super-resolution microscopy approaches. Since most if not all of the microscopic equipment to perform these techniques may be available in an institutional or nearby facility, we hope to encourage more researches to exploit sophisticated imaging tools for their research in cancer biology. PMID:29888200

Objective measures of motor dysfunction after compression spinal cord injury in adult rats: correlations with locomotor rating scores.

PubMed

Semler, Joerg; Wellmann, Katharina; Wirth, Felicitas; Stein, Gregor; Angelova, Srebrina; Ashrafi, Mahak; Schempf, Greta; Ankerne, Janina; Ozsoy, Ozlem; Ozsoy, Umut; Schönau, Eckhard; Angelov, Doychin N; Irintchev, Andrey

2011-07-01

Precise assessment of motor deficits after traumatic spinal cord injury (SCI) in rodents is crucial for understanding the mechanisms of functional recovery and testing therapeutic approaches. Here we analyzed the applicability to a rat SCI model of an objective approach, the single-frame motion analysis, created and used for functional analysis in mice. Adult female Wistar rats were subjected to graded compression of the spinal cord. Recovery of locomotion was analyzed using video recordings of beam walking and inclined ladder climbing. Three out of four parameters used in mice appeared suitable: the foot-stepping angle (FSA) and the rump-height index (RHI), measured during beam walking, and for estimating paw placement and body weight support, respectively, and the number of correct ladder steps (CLS), assessing skilled limb movements. These parameters, similar to the Basso, Beattie, and Bresnahan (BBB) locomotor rating scores, correlated with lesion volume and showed significant differences between moderately and severely injured rats at 1-9 weeks after SCI. The beam parameters, but not CLS, correlated well with the BBB scores within ranges of poor and good locomotor abilities. FSA co-varied with RHI only in the severely impaired rats, while RHI and CLS were barely correlated. Our findings suggest that the numerical parameters estimate, as intended by design, predominantly different aspects of locomotion. The use of these objective measures combined with BBB rating provides a time- and cost-efficient opportunity for versatile and reliable functional evaluations in both severely and moderately impaired rats, combining clinical assessment with precise numerical measures.

Dimensionality Controlled Octahedral Symmetry-Mismatch and Functionalities in Epitaxial LaCoO₃/SrTiO₃ Heterostructures.

PubMed

Qiao, Liang; Jang, Jae Hyuck; Singh, David J; Gai, Zheng; Xiao, Haiyan; Mehta, Apurva; Vasudevan, Rama K; Tselev, Alexander; Feng, Zhenxing; Zhou, Hua; Li, Sean; Prellier, Wilfrid; Zu, Xiaotao; Liu, Zijiang; Borisevich, Albina; Baddorf, Arthur P; Biegalski, Michael D

2015-07-08

Epitaxial strain provides a powerful approach to manipulate physical properties of materials through rigid compression or extension of their chemical bonds via lattice-mismatch. Although symmetry-mismatch can lead to new physics by stabilizing novel interfacial structures, challenges in obtaining atomic-level structural information as well as lack of a suitable approach to separate it from the parasitical lattice-mismatch have limited the development of this field. Here, we present unambiguous experimental evidence that the symmetry-mismatch can be strongly controlled by dimensionality and significantly impact the collective electronic and magnetic functionalities in ultrathin perovskite LaCoO3/SrTiO3 heterojunctions. State-of-art diffraction and microscopy reveal that symmetry breaking dramatically modifies the interfacial structure of CoO6 octahedral building-blocks, resulting in expanded octahedron volume, reduced covalent screening, and stronger electron correlations. Such phenomena fundamentally alter the electronic and magnetic behaviors of LaCoO3 thin-films. We conclude that for epitaxial systems, correlation strength can be tuned by changing orbital hybridization, thus affecting the Coulomb repulsion, U, instead of by changing the band structure as the common paradigm in bulks. These results clarify the origin of magnetic ordering for epitaxial LaCoO3 and provide a route to manipulate electron correlation and magnetic functionality by orbital engineering at oxide heterojunctions.

Direct Calculation of the Scattering Amplitude Without Partial Wave Decomposition. III; Inclusion of Correlation Effects

NASA Technical Reports Server (NTRS)

Shertzer, Janine; Temkin, Aaron

2007-01-01

In the first two papers in this series, we developed a method for studying electron-hydrogen scattering that does not use partial wave analysis. We constructed an ansatz for the wave function in both the static and static exchange approximations and calculated the full scattering amplitude. Here we go beyond the static exchange approximation, and include correlation in the wave function via a modified polarized orbital. This correlation function provides a significant improvement over the static exchange approximation: the resultant elastic scattering amplitudes are in very good agreement with fully converged partial wave calculations for electron-hydrogen scattering. A fully variational modification of this approach is discussed in the conclusion of the article Popular summary of Direct calculation of the scattering amplitude without partial wave expansion. III ....." by J. Shertzer and A. Temkin. In this paper we continue the development of In this paper we continue the development of a new approach to the way in which researchers have traditionally used to calculate the scattering cross section of (low-energy) electrons from atoms. The basic mathematical problem is to solve the Schroedinger Equation (SE) corresponding the above physical process. Traditionally it was always the case that the SE was reduced to a sequence of one-dimensional (ordinary) differential equations - called partial waves which were solved and from the solutions "phase shifts" were extracted, from which the scattering cross section was calculated.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

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

Seljak, Uroš; McDonald, Patrick, E-mail: useljak@berkeley.edu, E-mail: pvmcdonald@lbl.gov

We develop a phase space distribution function approach to redshift space distortions (RSD), in which the redshift space density can be written as a sum over velocity moments of the distribution function. These moments are density weighted and have well defined physical interpretation: their lowest orders are density, momentum density, and stress energy density. The series expansion is convergent if kμu/aH < 1, where k is the wavevector, H the Hubble parameter, u the typical gravitational velocity and μ = cos θ, with θ being the angle between the Fourier mode and the line of sight. We perform an expansionmore » of these velocity moments into helicity modes, which are eigenmodes under rotation around the axis of Fourier mode direction, generalizing the scalar, vector, tensor decomposition of perturbations to an arbitrary order. We show that only equal helicity moments correlate and derive the angular dependence of the individual contributions to the redshift space power spectrum. We show that the dominant term of μ{sup 2} dependence on large scales is the cross-correlation between the density and scalar part of momentum density, which can be related to the time derivative of the matter power spectrum. Additional terms contributing to μ{sup 2} and dominating on small scales are the vector part of momentum density-momentum density correlations, the energy density-density correlations, and the scalar part of anisotropic stress density-density correlations. The second term is what is usually associated with the small scale Fingers-of-God damping and always suppresses power, but the first term comes with the opposite sign and always adds power. Similarly, we identify 7 terms contributing to μ{sup 4} dependence. Some of the advantages of the distribution function approach are that the series expansion converges on large scales and remains valid in multi-stream situations. We finish with a brief discussion of implications for RSD in galaxies relative to dark matter, highlighting the issue of scale dependent bias of velocity moments correlators.« less

Fast large scale structure perturbation theory using one-dimensional fast Fourier transforms

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

Schmittfull, Marcel; Vlah, Zvonimir; McDonald, Patrick

The usual fluid equations describing the large-scale evolution of mass density in the universe can be written as local in the density, velocity divergence, and velocity potential fields. As a result, the perturbative expansion in small density fluctuations, usually written in terms of convolutions in Fourier space, can be written as a series of products of these fields evaluated at the same location in configuration space. Based on this, we establish a new method to numerically evaluate the 1-loop power spectrum (i.e., Fourier transform of the 2-point correlation function) with one-dimensional fast Fourier transforms. This is exact and a fewmore » orders of magnitude faster than previously used numerical approaches. Numerical results of the new method are in excellent agreement with the standard quadrature integration method. This fast model evaluation can in principle be extended to higher loop order where existing codes become painfully slow. Our approach follows by writing higher order corrections to the 2-point correlation function as, e.g., the correlation between two second-order fields or the correlation between a linear and a third-order field. These are then decomposed into products of correlations of linear fields and derivatives of linear fields. In conclusion, the method can also be viewed as evaluating three-dimensional Fourier space convolutions using products in configuration space, which may also be useful in other contexts where similar integrals appear.« less

Fast large scale structure perturbation theory using one-dimensional fast Fourier transforms

DOE PAGES

Schmittfull, Marcel; Vlah, Zvonimir; McDonald, Patrick

2016-05-01

The usual fluid equations describing the large-scale evolution of mass density in the universe can be written as local in the density, velocity divergence, and velocity potential fields. As a result, the perturbative expansion in small density fluctuations, usually written in terms of convolutions in Fourier space, can be written as a series of products of these fields evaluated at the same location in configuration space. Based on this, we establish a new method to numerically evaluate the 1-loop power spectrum (i.e., Fourier transform of the 2-point correlation function) with one-dimensional fast Fourier transforms. This is exact and a fewmore » orders of magnitude faster than previously used numerical approaches. Numerical results of the new method are in excellent agreement with the standard quadrature integration method. This fast model evaluation can in principle be extended to higher loop order where existing codes become painfully slow. Our approach follows by writing higher order corrections to the 2-point correlation function as, e.g., the correlation between two second-order fields or the correlation between a linear and a third-order field. These are then decomposed into products of correlations of linear fields and derivatives of linear fields. In conclusion, the method can also be viewed as evaluating three-dimensional Fourier space convolutions using products in configuration space, which may also be useful in other contexts where similar integrals appear.« less

Algebraic approach to electronic spectroscopy and dynamics

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

Toutounji, Mohamad

Lie algebra, Zassenhaus, and parameter differentiation techniques are utilized to break up the exponential of a bilinear Hamiltonian operator into a product of noncommuting exponential operators by the virtue of the theory of Wei and Norman [J. Math. Phys. 4, 575 (1963); Proc. Am. Math. Soc., 15, 327 (1964)]. There are about three different ways to find the Zassenhaus exponents, namely, binomial expansion, Suzuki formula, and q-exponential transformation. A fourth, and most reliable method, is provided. Since linearly displaced and distorted (curvature change upon excitation/emission) Hamiltonian and spin-boson Hamiltonian may be classified as bilinear Hamiltonians, the presented algebraic algorithm (exponentialmore » operator disentanglement exploiting six-dimensional Lie algebra case) should be useful in spin-boson problems. The linearly displaced and distorted Hamiltonian exponential is only treated here. While the spin-boson model is used here only as a demonstration of the idea, the herein approach is more general and powerful than the specific example treated. The optical linear dipole moment correlation function is algebraically derived using the above mentioned methods and coherent states. Coherent states are eigenvectors of the bosonic lowering operator a and not of the raising operator a{sup +}. While exp(a{sup +}) translates coherent states, exp(a{sup +}a{sup +}) operation on coherent states has always been a challenge, as a{sup +} has no eigenvectors. Three approaches, and the results, of that operation are provided. Linear absorption spectra are derived, calculated, and discussed. The linear dipole moment correlation function for the pure quadratic coupling case is expressed in terms of Legendre polynomials to better show the even vibronic transitions in the absorption spectrum. Comparison of the present line shapes to those calculated by other methods is provided. Franck-Condon factors for both linear and quadratic couplings are exactly accounted for by the herein calculated linear absorption spectra. This new methodology should easily pave the way to calculating the four-point correlation function, F({tau}{sub 1},{tau}{sub 2},{tau}{sub 3},{tau}{sub 4}), of which the optical nonlinear response function may be procured, as evaluating F({tau}{sub 1},{tau}{sub 2},{tau}{sub 3},{tau}{sub 4}) is only evaluating the optical linear dipole moment correlation function iteratively over different time intervals, which should allow calculating various optical nonlinear temporal/spectral signals.« less

Electronic structure, transport, and collective effects in molecular layered systems.

PubMed

Hahn, Torsten; Ludwig, Tim; Timm, Carsten; Kortus, Jens

2017-01-01

The great potential of organic heterostructures for organic device applications is exemplified by the targeted engineering of the electronic properties of phthalocyanine-based systems. The transport properties of two different phthalocyanine systems, a pure copper phthalocyanine (CoPc) and a flourinated copper phthalocyanine-manganese phthalocyanine (F 16 CoPc/MnPc) heterostructure, are investigated by means of density functional theory (DFT) and the non-equilibrium Green's function (NEGF) approach. Furthermore, a master-equation-based approach is used to include electronic correlations beyond the mean-field-type approximation of DFT. We describe the essential theoretical tools to obtain the parameters needed for the master equation from DFT results. Finally, an interacting molecular monolayer is considered within a master-equation approach.

Correlations between critical current density, j{sub c}, critical temperature, T{sub c}, and structural quality of Y{sub 1}B{sub 2}Cu{sub 3}O{sub 7-x} thin superconducting films

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

Chrzanowski, J.; Xing, W.B.; Atlan, D.

1994-12-31

Correlations between critical current density (j{sub c}) critical temperature (T{sub c}) and the density of edge dislocations and nonuniform strain have been observed in YBCO thin films deposited by pulsed laser ablation on (001) LaAlO{sub 3} single crystals. Distinct maxima in j{sub c} as a function of the linewidths of the (00{ell}) Bragg reflections and as a function of the mosaic spread have been found in the epitaxial films. These maxima in j{sub c} indicate that the magnetic flux lines, in films of structural quality approaching that of single crystals, are insufficiently pinned which results in a decreased critical currentmore » density. T{sub c} increased monotonically with improving crystalline quality and approached a value characteristic of a pure single crystal. A strong correlation between j{sub c} and the density of edge dislocations N{sub D} was found. At the maximum of the critical current density the density of edge dislocations was estimated to be N{sub D}{approximately}1-2 x 10{sup 9}/cm{sup 2}.« less

A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy

NASA Astrophysics Data System (ADS)

Karsten, Sven; Bokarev, Sergey I.; Aziz, Saadullah G.; Ivanov, Sergei D.; Kühn, Oliver

2017-06-01

Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.

A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy.

PubMed

Karsten, Sven; Bokarev, Sergey I; Aziz, Saadullah G; Ivanov, Sergei D; Kühn, Oliver

2017-06-14

Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.

When can time-dependent currents be reproduced by the Landauer steady-state approximation?

NASA Astrophysics Data System (ADS)

Carey, Rachel; Chen, Liping; Gu, Bing; Franco, Ignacio

2017-05-01

We establish well-defined limits in which the time-dependent electronic currents across a molecular junction subject to a fluctuating environment can be quantitatively captured via the Landauer steady-state approximation. For this, we calculate the exact time-dependent non-equilibrium Green's function (TD-NEGF) current along a model two-site molecular junction, in which the site energies are subject to correlated noise, and contrast it with that obtained from the Landauer approach. The ability of the steady-state approximation to capture the TD-NEGF behavior at each instant of time is quantified via the same-time correlation function of the currents obtained from the two methods, while their global agreement is quantified by examining differences in the average currents. The Landauer steady-state approach is found to be a useful approximation when (i) the fluctuations do not disrupt the degree of delocalization of the molecular eigenstates responsible for transport and (ii) the characteristic time for charge exchange between the molecule and leads is fast with respect to the molecular correlation time. For resonant transport, when these conditions are satisfied, the Landauer approach is found to accurately describe the current, both on average and at each instant of time. For non-resonant transport, we find that while the steady-state approach fails to capture the time-dependent transport at each instant of time, it still provides a good approximation to the average currents. These criteria can be employed to adopt effective modeling strategies for transport through molecular junctions in interaction with a fluctuating environment, as is necessary to describe experiments.

A hydrodynamic approach to cosmology - Texture-seeded cold dark matter and hot dark matter cosmogonies

NASA Technical Reports Server (NTRS)

Cen, R. Y.; Ostriker, J. P.; Spergel, D. N.; Turok, N.

1991-01-01

Hydrodynamical simulations of galaxy formation in a texture-seeded cosmology are presented, with attention given to Omega = 1 galaxies dominated by both hot dark matter (HDM) and cold dark matter (CDM). The simulations include both gravitational and hydrodynamical physics with a detailed treatment of collisional and radiative thermal processes, and use a cooling criterion to estimate galaxy formation. Background radiation fields and Zel'dovich-Sunyaev fluctuations are explicitly computed. The derived galaxy mass function is well fitted by the observed Schechter luminosity function for a baryonic M/L of 3 and total M/L of 60 in galaxies. In both HDM and CDM texture scenarios, the 'galaxies' and 'clusters' are significantly more strongly correlated than the dark matter due to physical bias processes. The slope of the correlation function in both cases is consistent with observations. In contrast to Gaussian models, peaks in the dark matter density distributrion are less correlated than average.

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Exploring the limit of accuracy for density functionals based on the generalized gradient approximation: Local, global hybrid, and range-separated hybrid functionals with and without dispersion corrections

DOE PAGES

Mardirossian, Narbe; Head-Gordon, Martin

2014-03-25

The limit of accuracy for semi-empirical generalized gradient approximation (GGA) density functionals is explored in this paper by parameterizing a variety of local, global hybrid, and range-separated hybrid functionals. The training methodology employed differs from conventional approaches in 2 main ways: (1) Instead of uniformly truncating the exchange, same-spin correlation, and opposite-spin correlation functional inhomogeneity correction factors, all possible fits up to fourth order are considered, and (2) Instead of selecting the optimal functionals based solely on their training set performance, the fits are validated on an independent test set and ranked based on their overall performance on the trainingmore » and test sets. The 3 different methods of accounting for exchange are trained both with and without dispersion corrections (DFT-D2 and VV10), resulting in a total of 491 508 candidate functionals. For each of the 9 functional classes considered, the results illustrate the trade-off between improved training set performance and diminished transferability. Since all 491 508 functionals are uniformly trained and tested, this methodology allows the relative strengths of each type of functional to be consistently compared and contrasted. Finally, the range-separated hybrid GGA functional paired with the VV10 nonlocal correlation functional emerges as the most accurate form for the present training and test sets, which span thermochemical energy differences, reaction barriers, and intermolecular interactions involving lighter main group elements.« less

Protein oligomerization monitored by fluorescence fluctuation spectroscopy: Self-assembly of Rubisco activase

USDA-ARS?s Scientific Manuscript database

A methodology is presented to characterize complex protein assembly pathways by fluorescence correlation spectroscopy. We have derived the total autocorrelation function describing the behavior of mixtures of labeled and unlabeled protein under equilibrium conditions. Our modeling approach allows us...

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

Ab initio approach to the ion stopping power at the plasma-solid interface

NASA Astrophysics Data System (ADS)

Bonitz, Michael; Schlünzen, Niclas; Wulff, Lasse; Joost, Jan-Philip; Balzer, Karsten

2016-10-01

The energy loss of ions in solids is of key relevance for many applications of plasmas, ranging from plasma technology to fusion. Standard approaches are based on density functional theory or SRIM simulations, however, the applicability range and accuracy of these results are difficult to assess, in particular, for low energies. Here we present an independent approach that is based on ab initio nonequilibrium Green functions theory, e.g. that allows to incorporate electronic correlations effects of the solid. We present the first application of this method to low-temperature plasmas, concentrating on proton and alpha-particle stopping in a graphene layer. In addition to the stopping power we present time-dependent results for the local electron density, the spectral function and the photoemission spectrum that is directly accessible in optical, UV or x-ray diagnostics. http://www.itap.uni-kiel.de/theo-physik/bonitz/.

Self-interaction-corrected time-dependent density-functional-theory calculations of x-ray-absorption spectra

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

Tu, Guangde; Rinkevicius, Zilvinas; Vahtras, Olav

We outline an approach within time-dependent density functional theory that predicts x-ray spectra on an absolute scale. The approach rests on a recent formulation of the resonant-convergent first-order polarization propagator [P. Norman et al., J. Chem. Phys. 123, 194103 (2005)] and corrects for the self-interaction energy of the core orbital. This polarization propagator approach makes it possible to directly calculate the x-ray absorption cross section at a particular frequency without explicitly addressing the excited-state spectrum. The self-interaction correction for the employed density functional accounts for an energy shift of the spectrum, and fully correlated absolute-scale x-ray spectra are thereby obtainedmore » based solely on optimization of the electronic ground state. The procedure is benchmarked against experimental spectra of a set of small organic molecules at the carbon, nitrogen, and oxygen K edges.« less

Differentiation and Characterization of Excitatory and Inhibitory Synapses by Cryo-electron Tomography and Correlative Microscopy

PubMed Central

Sun, Rong; Zhang, Bin; Qi, Lei; Shivakoti, Sakar; Tian, Chong-Li; Lau, Pak-Ming

2018-01-01

As key functional units in neural circuits, different types of neuronal synapses play distinct roles in brain information processing, learning, and memory. Synaptic abnormalities are believed to underlie various neurological and psychiatric disorders. Here, by combining cryo-electron tomography and cryo-correlative light and electron microscopy, we distinguished intact excitatory and inhibitory synapses of cultured hippocampal neurons, and visualized the in situ 3D organization of synaptic organelles and macromolecules in their native state. Quantitative analyses of >100 synaptic tomograms reveal that excitatory synapses contain a mesh-like postsynaptic density (PSD) with thickness ranging from 20 to 50 nm. In contrast, the PSD in inhibitory synapses assumes a thin sheet-like structure ∼12 nm from the postsynaptic membrane. On the presynaptic side, spherical synaptic vesicles (SVs) of 25–60 nm diameter and discus-shaped ellipsoidal SVs of various sizes coexist in both synaptic types, with more ellipsoidal ones in inhibitory synapses. High-resolution tomograms obtained using a Volta phase plate and electron filtering and counting reveal glutamate receptor-like and GABAA receptor-like structures that interact with putative scaffolding and adhesion molecules, reflecting details of receptor anchoring and PSD organization. These results provide an updated view of the ultrastructure of excitatory and inhibitory synapses, and demonstrate the potential of our approach to gain insight into the organizational principles of cellular architecture underlying distinct synaptic functions. SIGNIFICANCE STATEMENT To understand functional properties of neuronal synapses, it is desirable to analyze their structure at molecular resolution. We have developed an integrative approach combining cryo-electron tomography and correlative fluorescence microscopy to visualize 3D ultrastructural features of intact excitatory and inhibitory synapses in their native state. Our approach shows that inhibitory synapses contain uniform thin sheet-like postsynaptic densities (PSDs), while excitatory synapses contain previously known mesh-like PSDs. We discovered “discus-shaped” ellipsoidal synaptic vesicles, and their distributions along with regular spherical vesicles in synaptic types are characterized. High-resolution tomograms further allowed identification of putative neurotransmitter receptors and their heterogeneous interaction with synaptic scaffolding proteins. The specificity and resolution of our approach enables precise in situ analysis of ultrastructural organization underlying distinct synaptic functions. PMID:29311144

Statistical tests for power-law cross-correlated processes

NASA Astrophysics Data System (ADS)

Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

2011-12-01

For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

Effective Perron-Frobenius eigenvalue for a correlated random map

NASA Astrophysics Data System (ADS)

Pool, Roman R.; Cáceres, Manuel O.

2010-09-01

We investigate the evolution of random positive linear maps with various type of disorder by analytic perturbation and direct simulation. Our theoretical result indicates that the statistics of a random linear map can be successfully described for long time by the mean-value vector state. The growth rate can be characterized by an effective Perron-Frobenius eigenvalue that strongly depends on the type of correlation between the elements of the projection matrix. We apply this approach to an age-structured population dynamics model. We show that the asymptotic mean-value vector state characterizes the population growth rate when the age-structured model has random vital parameters. In this case our approach reveals the nontrivial dependence of the effective growth rate with cross correlations. The problem was reduced to the calculation of the smallest positive root of a secular polynomial, which can be obtained by perturbations in terms of Green’s function diagrammatic technique built with noncommutative cumulants for arbitrary n -point correlations.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Stress hormones are associated with the neuronal correlates of instructed fear conditioning.

PubMed

Merz, Christian Josef; Stark, Rudolf; Vaitl, Dieter; Tabbert, Katharina; Wolf, Oliver Tobias

2013-01-01

The effects of sex and stress hormones on classical fear conditioning have been subject of recent experimental studies. A correlation approach between basal cortisol concentrations and neuronal activation in fear-related structures seems to be a promising alternative approach in order to foster our understanding of how cortisol influences emotional learning. In this functional magnetic resonance imaging study, participants with varying sex hormone status (20 men, 15 women taking oral contraceptives, 15 women tested in the luteal phase) underwent an instructed fear conditioning protocol with geometrical figures as conditioned stimuli and an electrical stimulation as unconditioned stimulus. Salivary cortisol concentrations were measured and afterwards correlated with fear conditioned brain responses. Results revealed a positive correlation between basal cortisol levels and differential activation in the amygdala in men and OC women only. These results suggest that elevated endogenous cortisol levels are associated with enhanced fear anticipation depending on current sex hormone availability. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling Unproductive Behavior in Online Homework in Terms of Latent Student Traits: An Approach Based on Item Response Theory

NASA Astrophysics Data System (ADS)

Gönülateş, Emre; Kortemeyer, Gerd

2017-04-01

Homework is an important component of most physics courses. One of the functions it serves is to provide meaningful formative assessment in preparation for examinations. However, correlations between homework and examination scores tend to be low, likely due to unproductive student behavior such as copying and random guessing of answers. In this study, we attempt to model these two counterproductive learner behaviors within the framework of Item Response Theory in order to provide an ability measurement that strongly correlates with examination scores. We find that introducing additional item parameters leads to worse predictions of examination grades, while introducing additional learner traits is a more promising approach.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

An Integrated Model of Suicidal Ideation in Transcultural Populations of Chinese Adolescents.

PubMed

Leung, Cyrus L K; Kwok, Sylvia Y C L; Ling, Chloe C Y

2016-07-01

This study tested the model of suicidal ideation, incorporating family and personal factors to predict suicidal ideation with hopelessness as a mediating factor in the Hong Kong sample, to a sample in Shanghai. Using MGSEM, the study aims to investigate the personal correlates and the family correlates of suicidal ideation in Hong Kong and Shanghai adolescents. We integrated the family ecological and diathesis-stress-hopelessness models of suicidal ideation in connecting the correlates. A cross-sectional design was used. The full model achieved metric invariance and partial path-loading invariance. Family functioning and social problem solving negatively predicted hopelessness or suicidal ideation in both the Hong Kong and Shanghai adolescents. The results supported an integrative approach in facilitating parent-adolescent communication and strengthening family functioning, and reducing the use of negative social problem-solving styles in adolescent suicide prevention.

Angular resolution and range of dipole-dipole correlations in water

NASA Astrophysics Data System (ADS)

Mathias, Gerald; Tavan, Paul

2004-03-01

We investigate the dipolar correlations in liquid water at angular resolution by molecular-dynamics simulations of a large periodic simulation system containing about 40 000 molecules. Because we are particularly interested in the long-range ordering, we use a simple three-point model for these molecules. The electrostatics is treated both by Ewald summation and by minimum image truncation combined with a reaction field approach. To gain insight into the angular dependence of the simulated dipolar ordering we introduce a suitable expansion of the molecular pair distribution function into a set of two-dimensional correlation functions. We show that these functions enable detailed insights into the shell structure of the dipolar ordering around a given water molecule. For these functions we derive analytical expressions in the particular case in which liquid water is conceived as a dielectric continuum. Comparisons of these continuum models with the correlation functions derived from the simulations yield the key result that liquid water behaves like a continuum dielectric beyond distances of about 15 Å from a given water molecule. We argue that this should be a generic property of water independent of our modeling. By comparison of the results of the two different electrostatics treatments with the continuum description we show that the boundary artifacts occurring in both methods are isotropically distributed and are locally small in the respective boundary regions.

Computing sextic centrifugal distortion constants by DFT: A benchmark analysis on halogenated compounds

NASA Astrophysics Data System (ADS)

Pietropolli Charmet, Andrea; Stoppa, Paolo; Tasinato, Nicola; Giorgianni, Santi

2017-05-01

This work presents a benchmark study on the calculation of the sextic centrifugal distortion constants employing cubic force fields computed by means of density functional theory (DFT). For a set of semi-rigid halogenated organic compounds several functionals (B2PLYP, B3LYP, B3PW91, M06, M06-2X, O3LYP, X3LYP, ωB97XD, CAM-B3LYP, LC-ωPBE, PBE0, B97-1 and B97-D) were used for computing the sextic centrifugal distortion constants. The effects related to the size of basis sets and the performances of hybrid approaches, where the harmonic data obtained at higher level of electronic correlation are coupled with cubic force constants yielded by DFT functionals, are presented and discussed. The predicted values were compared to both the available data published in the literature and those obtained by calculations carried out at increasing level of electronic correlation: Hartree-Fock Self Consistent Field (HF-SCF), second order Møller-Plesset perturbation theory (MP2), and coupled-cluster single and double (CCSD) level of theory. Different hybrid approaches, having the cubic force field computed at DFT level of theory coupled to harmonic data computed at increasing level of electronic correlation (up to CCSD level of theory augmented by a perturbational estimate of the effects of connected triple excitations, CCSD(T)) were considered. The obtained results demonstrate that they can represent reliable and computationally affordable methods to predict sextic centrifugal terms with an accuracy almost comparable to that yielded by the more expensive anharmonic force fields fully computed at MP2 and CCSD levels of theory. In view of their reduced computational cost, these hybrid approaches pave the route to the study of more complex systems.

Sensory phenomena related to tics, obsessive-compulsive symptoms, and global functioning in Tourette syndrome.

PubMed

Kano, Yukiko; Matsuda, Natsumi; Nonaka, Maiko; Fujio, Miyuki; Kuwabara, Hitoshi; Kono, Toshiaki

2015-10-01

Sensory phenomena, including premonitory urges, are experienced by patients with Tourette syndrome (TS) and obsessive-compulsive disorder (OCD). The goal of the present study was to investigate such phenomena related to tics, obsessive-compulsive symptoms (OCS), and global functioning in Japanese patients with TS. Forty-one patients with TS were assessed using the University of São Paulo Sensory Phenomena Scale (USP-SPS), the Premonitory Urge for Tics Scale (PUTS), the Yale Global Tic Severity Scale (YGTSS), the Dimensional Yale-Brown Obsessive-Compulsive Scale (DY-BOCS), and the Global Assessment of Functioning (GAF) Scale. USP-SPS and PUTS total scores were significantly correlated with YGTSS total and vocal tics scores. Additionally, both sensory phenomena severity scores were significantly correlated with DY-BOCS total OCS scores. Of the six dimensional OCS scores, the USP-SPS scores were significantly correlated with measures of aggression and sexual/religious dimensions. Finally, the PUTS total scores were significantly and negatively correlated with GAF scores. By assessing premonitory urges and broader sensory phenomena, and by viewing OCS from a dimensional approach, this study provides significant insight into sensory phenomena related to tics, OCS, and global functioning in patients with TS. Copyright © 2015 Elsevier Inc. All rights reserved.

Linearized semiclassical initial value time correlation functions with maximum entropy analytic continuation.

PubMed

Liu, Jian; Miller, William H

2008-09-28

The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. LSC-IVR provides a very effective "prior" for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25 and 14 K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T=25 K, but the MEAC procedure produces a significant correction at the lower temperature (T=14 K). Comparisons are also made as to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Scale-dependence of transverse momentum correlations in Pb sbnd Au collisions at 158A GeV/c

NASA Astrophysics Data System (ADS)

Adamová, D.; Agakichiev, G.; Antończyk, D.; Appelshäuser, H.; Belaga, V.; Bielcikova, S.; Braun-Munzinger, P.; Busch, O.; Cherlin, A.; Damjanović, S.; Dietel, T.; Dietrich, L.; Drees, A.; Dubitzky, W.; Esumi, S. I.; Filimonov, K.; Fomenko, K.; Fraenkel, Z.; Garabatos, C.; Glässel, P.; Holeczek, J.; Kushpil, V.; Maas, A.; Marín, A.; Milošević, J.; Milov, A.; Miśkowiec, D.; Panebrattsev, Yu.; Petchenova, O.; Petráček, V.; Pfeiffer, A.; Płoskoń, M.; Radomski, S.; Rak, J.; Ravinovich, I.; Rehak, P.; Sako, H.; Schmitz, W.; Sedykh, S.; Shimansky, S.; Stachel, J.; Šumbera, M.; Tilsner, H.; Tserruya, I.; Tsiledakis, G.; Wessels, J. P.; Wienold, T.; Wurm, J. P.; Xie, W.; Yurevich, S.; Yurevich, V.; Ceres Collaboration

2008-10-01

We present results on transverse momentum correlations of charged particle pairs produced in Pb sbnd Au collisions at 158A GeV/c at the Super Proton Synchrotron. The transverse momentum correlations have been studied as a function of collision centrality, angular separation of the particle pairs, transverse momentum and charge sign. We demonstrate that the results are in agreement with previous findings in scale-independent analyses at the same beam energy. Employing the two-particle momentum correlator <Δp,Δp> and the cumulative p variable x(p), we identify, using the scale-dependent approach presented in this paper, different sources contributing to the measured correlations, such as quantum and Coulomb correlations, elliptic flow and mini-jet fragmentation.

Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Yu-Jin; Lu, Chun-Ming; Biswal, Bharat B.; Zang, Yu-Feng; Peng, Dan-Lin; Zhu, Chao-Zhe

2010-07-01

Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.

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.

Raman Optical Activity Spectra from Density Functional Perturbation Theory and Density-Functional-Theory-Based Molecular Dynamics.

PubMed

Luber, Sandra

2017-03-14

We describe the calculation of Raman optical activity (ROA) tensors from density functional perturbation theory, which has been implemented into the CP2K software package. Using the mixed Gaussian and plane waves method, ROA spectra are evaluated in the double-harmonic approximation. Moreover, an approach for the calculation of ROA spectra by means of density functional theory-based molecular dynamics is derived and used to obtain an ROA spectrum via time correlation functions, which paves the way for the calculation of ROA spectra taking into account anharmonicities and dynamic effects at ambient conditions.

Wave functions of symmetry-protected topological phases from conformal field theories

NASA Astrophysics Data System (ADS)

Scaffidi, Thomas; Ringel, Zohar

2016-03-01

We propose a method for analyzing two-dimensional symmetry-protected topological (SPT) wave functions using a correspondence with conformal field theories (CFTs) and integrable lattice models. This method generalizes the CFT approach for the fractional quantum Hall effect wherein the wave-function amplitude is written as a many-operator correlator in the CFT. Adopting a bottom-up approach, we start from various known microscopic wave functions of SPTs with discrete symmetries and show how the CFT description emerges at large scale, thereby revealing a deep connection between group cocycles and critical, sometimes integrable, models. We show that the CFT describing the bulk wave function is often also the one describing the entanglement spectrum, but not always. Using a plasma analogy, we also prove the existence of hidden quasi-long-range order for a large class of SPTs. Finally, we show how response to symmetry fluxes is easily described in terms of the CFT.

Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions.

PubMed

Ritchie, David W; Kozakov, Dima; Vajda, Sandor

2008-09-01

Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.

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

Multiple Scattering of Waves in Discrete Random Media.

DTIC Science & Technology

1987-12-31

expanding the two body correlation functions in Legendre polynomials. This permits us to consider the angular correlations that exist for non-spherical...a scat- of the translation matrix after the angular and radial parts have terer fixed at it. been absorbed in the integration. Expressions for them...Approach New York: Pergamon Press. 1980 ’" close to the actual values for FeO, in isolation since they 171 A R. Edmonds. Angular Momentum in Quantum . h(pa

Few-body problem in terms of correlated Gaussians

NASA Astrophysics Data System (ADS)

Silvestre-Brac, Bernard; Mathieu, Vincent

2007-10-01

In their textbook, Suzuki and Varga [Stochastic Variational Approach to Quantum-Mechanical Few-Body Problems (Springer, Berlin, 1998)] present the stochastic variational method with the correlated Gaussian basis in a very exhaustive way. However, the Fourier transform of these functions and their application to the management of a relativistic kinetic energy operator are missing and cannot be found in the literature. In this paper we present these interesting formulas. We also give a derivation for formulations concerning central potentials.

Correlates of immune protection: Standardized and automated assays to interrogate correlates of immunity--Phacilitate Vaccine Forum Washington 2011. The Grand Hyatt, Washington, DC January 24–26, 2011.

PubMed

Bolton, Wade

2011-06-01

The utility of functional cell mediated immune assays in the assessment of immune response or immunogenicity is increasing significantly as we search for surrogates to determine vaccine efficacy or therapeutic response. No definitive reports to date have demonstrated that CMI assays in human clinical trials correlate with clinical outcome, although animal and non human primate studies have reported surrogacy in varying degrees. This report discusses the approaches identified, their advantages and disadvantages, and their justification for inclusion in the clinical trial setting.

Double counting in the density functional plus dynamical mean-field theory of transition metal oxides

NASA Astrophysics Data System (ADS)

Dang, Hung

2015-03-01

Recently, the combination of density functional theory (DFT) and dynamical mean-field theory (DMFT) has become a widely-used beyond-mean-field approach for strongly correlated materials. However, not only is the correlation treated in DMFT but also in DFT to some extent, a problem arises as the correlation is counted twice in the DFT+DMFT framework. The correction for this problem is still not well-understood. To gain more understanding of this ``double counting'' problem, I provide a detailed study of the metal-insulator transition in transition metal oxides in the subspace of oxygen p and transition metal correlated d orbitals using DFT+DMFT. I will show that the fully charge self-consistent DFT+DMFT calculations with the standard ``fully-localized limit'' (FLL) double counting correction fail to predict correctly materials such as LaTiO3, LaVO3, YTiO3 and SrMnO3 as insulators. Investigations in a wide range of the p- d splitting, the d occupancy, the lattice structure and the double counting correction itself will be presented to understand the reason behind this failure. I will also show that if the double counting correction is chosen to reproduce the p- d splitting consistent with experimental data, the DFT+DMFT approach can still give reasonable results in comparison with experiments.

Synthesizing trait correlations and functional relationships across multiple scales: A Hierarchical Bayes approach

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Cowdery, E.; Dietze, M.

2016-12-01

Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.

H4: A challenging system for natural orbital functional approximations

NASA Astrophysics Data System (ADS)

Ramos-Cordoba, Eloy; Lopez, Xabier; Piris, Mario; Matito, Eduard

2015-10-01

The correct description of nondynamic correlation by electronic structure methods not belonging to the multireference family is a challenging issue. The transition of D2h to D4h symmetry in H4 molecule is among the most simple archetypal examples to illustrate the consequences of missing nondynamic correlation effects. The resurgence of interest in density matrix functional methods has brought several new methods including the family of Piris Natural Orbital Functionals (PNOF). In this work, we compare PNOF5 and PNOF6, which include nondynamic electron correlation effects to some extent, with other standard ab initio methods in the H4 D4h/D2h potential energy surface (PES). Thus far, the wrongful behavior of single-reference methods at the D2h-D4h transition of H4 has been attributed to wrong account of nondynamic correlation effects, whereas in geminal-based approaches, it has been assigned to a wrong coupling of spins and the localized nature of the orbitals. We will show that actually interpair nondynamic correlation is the key to a cusp-free qualitatively correct description of H4 PES. By introducing interpair nondynamic correlation, PNOF6 is shown to avoid cusps and provide the correct smooth PES features at distances close to the equilibrium, total and local spin properties along with the correct electron delocalization, as reflected by natural orbitals and multicenter delocalization indices.

NMR relaxation studies on the hydrate layer of intrinsically unstructured proteins.

PubMed

Bokor, Mónika; Csizmók, Veronika; Kovács, Dénes; Bánki, Péter; Friedrich, Peter; Tompa, Peter; Tompa, Kálmán

2005-03-01

Intrinsically unstructured/disordered proteins (IUPs) exist in a disordered and largely solvent-exposed, still functional, structural state under physiological conditions. As their function is often directly linked with structural disorder, understanding their structure-function relationship in detail is a great challenge to structural biology. In particular, their hydration and residual structure, both closely linked with their mechanism of action, require close attention. Here we demonstrate that the hydration of IUPs can be adequately approached by a technique so far unexplored with respect to IUPs, solid-state NMR relaxation measurements. This technique provides quantitative information on various features of hydrate water bound to these proteins. By freezing nonhydrate (bulk) water out, we have been able to measure free induction decays pertaining to protons of bound water from which the amount of hydrate water, its activation energy, and correlation times could be calculated. Thus, for three IUPs, the first inhibitory domain of calpastatin, microtubule-associated protein 2c, and plant dehydrin early responsive to dehydration 10, we demonstrate that they bind a significantly larger amount of water than globular proteins, whereas their suboptimal hydration and relaxation parameters are correlated with their differing modes of function. The theoretical treatment and experimental approach presented in this article may have general utility in characterizing proteins that belong to this novel structural class.

Impact of transient emotions on functional connectivity during subsequent resting state: a wavelet correlation approach.

PubMed

Eryilmaz, Hamdi; Van De Ville, Dimitri; Schwartz, Sophie; Vuilleumier, Patrik

2011-02-01

The functional properties of resting brain activity are poorly understood, but have generally been related to self-monitoring and introspective processes. Here we investigated how emotionally positive and negative information differentially influenced subsequent brain activity at rest. We acquired fMRI data in 15 participants during rest periods following fearful, joyful, and neutral movies. Several brain regions were more active during resting than during movie-watching, including posterior/anterior cingulate cortices (PCC, ACC), bilateral insula and inferior parietal lobules (IPL). Functional connectivity at different frequency bands was also assessed using a wavelet correlation approach and small-world network analysis. Resting activity in ACC and insula as well as their coupling were strongly enhanced by preceding emotions, while coupling between ventral-medial prefrontal cortex and amygdala was selectively reduced. These effects were more pronounced after fearful than joyful movies for higher frequency bands. Moreover, the initial suppression of resting activity in ACC and insula after emotional stimuli was followed by a gradual restoration over time. Emotions did not affect IPL average activity but increased its connectivity with other regions. These findings reveal specific neural circuits recruited during the recovery from emotional arousal and highlight the complex functional dynamics of default mode networks in emotionally salient contexts. Copyright © 2010 Elsevier Inc. All rights reserved.

The integrated bispectrum in modified gravity theories

NASA Astrophysics Data System (ADS)

Munshi, Dipak

2017-01-01

Gravity-induced non-Gaussianity can provide important clues to Modified Gravity (MG) Theories. Several recent studies have suggested using the Integrated Bispectrum (IB) as a probe for squeezed configuration of bispectrum. Extending previous studies on the IB, we include redshift-space distortions to study a class of (parametrised) MG theories that include the string-inspired Dvali, Gabadadze & Porrati (DGP) model. Various contributions from redshift-space distortions are derived in a transparent manner, and squeezed contributions from these terms are derived separately. Results are obtained using the Zel'dovich Approximation (ZA). Results are also presented for projected surveys (2D). We use the Press-Schechter (PS) and Sheth-Tormen (ST) mass functions to compute the IB for collapsed objects that can readily be extended to peak-theory based approaches. The cumulant correlators (CCs) generalise the ordinary cumulants and are known to probe collapsed configurations of higher order correlation functions. We generalise the concept of CCs to halos of different masses. We also introduce a generating function based approach to analyse more general non-local biasing models. The Fourier representations of the CCs, the skew-spectrum, or the kurt-spctra are discussed in this context. The results are relevant for the study of the Minkowski Functionals (MF) of collapsed tracers in redshift-space.

Ionization energies and electron affinities from a random-phase-approximation many-body Green's-function method including exchange interactions

NASA Astrophysics Data System (ADS)

Heßelmann, Andreas

2017-06-01

A many-body Green's-function method employing an infinite order summation of ring and exchange-ring contributions to the self-energy is presented. The individual correlation and relaxation contributions to the quasiparticle energies are calculated using an iterative scheme which utilizes density fitting of the particle-hole, particle-particle and hole-hole densities. It is shown that the ionization energies and electron affinities of this approach agree better with highly accurate coupled-cluster singles and doubles with perturbative triples energy difference results than those obtained with second-order Green's-function approaches. An analysis of the correlation and relaxation terms of the self-energy for the direct- and exchange-random-phase-approximation (RPA) Green's-function methods shows that the inclusion of exchange interactions leads to a reduction of the two contributions in magnitude. These differences, however, strongly cancel each other when summing the individual terms to the quasiparticle energies. Due to this, the direct- and exchange-RPA methods perform similarly for the description of ionization energies (IPs) and electron affinities (EAs). The coupled-cluster reference IPs and EAs, if corrected to the adiabatic energy differences between the neutral and charged molecules, were shown to be in very good agreement with experimental measurements.

The integrated bispectrum in modified gravity theories

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

Munshi, Dipak, E-mail: D.Munshi@sussex.ac.uk

2017-01-01

Gravity-induced non-Gaussianity can provide important clues to Modified Gravity (MG) Theories. Several recent studies have suggested using the Integrated Bispectrum (IB) as a probe for squeezed configuration of bispectrum. Extending previous studies on the IB, we include redshift-space distortions to study a class of (parametrised) MG theories that include the string-inspired Dvali, Gabadadze and Porrati (DGP) model. Various contributions from redshift-space distortions are derived in a transparent manner, and squeezed contributions from these terms are derived separately. Results are obtained using the Zel'dovich Approximation (ZA). Results are also presented for projected surveys (2D). We use the Press-Schechter (PS) and Sheth-Tormenmore » (ST) mass functions to compute the IB for collapsed objects that can readily be extended to peak-theory based approaches. The cumulant correlators (CCs) generalise the ordinary cumulants and are known to probe collapsed configurations of higher order correlation functions. We generalise the concept of CCs to halos of different masses. We also introduce a generating function based approach to analyse more general non-local biasing models. The Fourier representations of the CCs, the skew-spectrum, or the kurt-spctra are discussed in this context. The results are relevant for the study of the Minkowski Functionals (MF) of collapsed tracers in redshift-space.« less

Identification of material properties of orthotropic composite plate using experimental frequency response function data

NASA Astrophysics Data System (ADS)

Tam, Jun Hui; Ong, Zhi Chao; Ismail, Zubaidah; Ang, Bee Chin; Khoo, Shin Yee

2018-05-01

The demand for composite materials is increasing due to their great superiority in material properties, e.g., lightweight, high strength and high corrosion resistance. As a result, the invention of composite materials of diverse properties is becoming prevalent, and thus, leading to the development of material identification methods for composite materials. Conventional identification methods are destructive, time-consuming and costly. Therefore, an accurate identification approach is proposed to circumvent these drawbacks, involving the use of Frequency Response Function (FRF) error function defined by the correlation discrepancy between experimental and Finite-Element generated FRFs. A square E-glass epoxy composite plate is investigated under several different configurations of boundary conditions. It is notable that the experimental FRFs are used as the correlation reference, such that, during computation, the predicted FRFs are continuously updated with reference to the experimental FRFs until achieving a solution. The final identified elastic properties, namely in-plane elastic moduli, Ex and Ey, in-plane shear modulus, Gxy, and major Poisson's ratio, vxy of the composite plate are subsequently compared to the benchmark parameters as well as with those obtained using modal-based approach. As compared to the modal-based approach, the proposed method is found to have yielded relatively better results. This can be explained by the direct employment of raw data in the proposed method that avoids errors that might incur during the stage of modal extraction.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Demystifying the memory effect: A geometrical approach to understanding speckle correlations

NASA Astrophysics Data System (ADS)

Prunty, Aaron C.; Snieder, Roel K.

2017-05-01

The memory effect has seen a surge of research into its fundamental properties and applications since its discovery by Feng et al. [Phys. Rev. Lett. 61, 834 (1988)]. While the wave trajectories for which the memory effect holds are hidden implicitly in the diffusion probability function [Phys. Rev. B 40, 737 (1989)], the physical intuition of why these trajectories satisfy the memory effect has often been masked by the derivation of the memory correlation function itself. In this paper, we explicitly derive the specific trajectories through a random medium for which the memory effect holds. Our approach shows that the memory effect follows from a simple conservation argument, which imposes geometrical constraints on the random trajectories that contribute to the memory effect. We illustrate the time-domain effects of these geometrical constraints with numerical simulations of pulse transmission through a random medium. The results of our derivation and numerical simulations are consistent with established theory and experimentation.

Towards an exact correlated orbital theory for electrons

NASA Astrophysics Data System (ADS)

Bartlett, Rodney J.

2009-12-01

The formal and computational attraction of effective one-particle theories like Hartree-Fock and density functional theory raise the question of how far such approaches can be taken to offer exact results for selected properties of electrons in atoms, molecules, and solids. Some properties can be exactly described within an effective one-particle theory, like principal ionization potentials and electron affinities. This fact can be used to develop equations for a correlated orbital theory (COT) that guarantees a correct one-particle energy spectrum. They are built upon a coupled-cluster based frequency independent self-energy operator presented here, which distinguishes the approach from Dyson theory. The COT also offers an alternative to Kohn-Sham density functional theory (DFT), whose objective is to represent the electronic density exactly as a single determinant, while paying less attention to the energy spectrum. For any estimate of two-electron terms COT offers a litmus test of its accuracy for principal Ip's and Ea's. This feature for approximating the COT equations is illustrated numerically.

Individual variation in functional brain connectivity: implications for personalized approaches to psychiatric disease.

PubMed

Finn, Emily S; Todd Constable, R

2016-09-01

Functional brain connectivity measured with functional magnetic resonance imaging (fMRI) is a popular technique for investigating neural organization in both healthy subjects and patients with mental illness. Despite a rapidly growing body of literature, however, functional connectivity research has yet to deliver biomarkers that can aid psychiatric diagnosis or prognosis at the single-subject level. One impediment to developing such practical tools has been uncertainty regarding the ratio of intra- to interindividual variability in functional connectivity; in other words, how much variance is state- versus trait-related. Here, we review recent evidence that functional connectivity profiles are both reliable within subjects and unique across subjects, and that features of these profiles relate to behavioral phenotypes. Together, these results suggest the potential to discover reliable correlates of present and future illness and/or response to treatment in the strength of an individual's functional brain connections. Ultimately, this work could help develop personalized approaches to psychiatric illness.

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.

Density Functional Calculations for Prediction of 57Fe Mössbauer Isomer Shifts and Quadrupole Splittings in β-Diketiminate Complexes

PubMed Central

2017-01-01

The relative ease of Mössbauer spectroscopy and of density functional theory (DFT) calculations encourages the use of Mössbauer parameters as a validation method for calculations, and the use of calculations as a double check on crystallographic structures. A number of studies have proposed correlations between the computationally determined electron density at the iron nucleus and the observed isomer shift, but deviations from these correlations in low-valent iron β-diketiminate complexes encouraged us to determine a new correlation for these compounds. The use of B3LYP/def2-TZVP in the ORCA platform provides an excellent balance of accuracy and speed. We provide here not only this new correlation and a clear guide to its use but also a systematic analysis of the limitations of this approach. We also highlight the impact of crystallographic inaccuracies, DFT model truncation, and spin states, with intent to assist experimentalists to use Mössbauer spectroscopy and calculations together. PMID:28691111

Digital Posturography Games Correlate with Gross Motor Function in Children with Cerebral Palsy.

PubMed

Bingham, Peter M; Calhoun, Barbara

2015-04-01

This pilot study aimed to assess whether performance on posturography games correlates with the Gross Motor Function Measure (GMFM) in children with cerebral palsy. Simple games using static posturography technology allowed subjects to control screen events via postural sway. Game performance was compared with GMFMs using correlation analysis in a convenience sample of nine girls and six boys with cerebral palsy. Likert scales were used to obtain subjective responses to the balance games. GMFM scores correlated with game performance, especially measures emphasizing rhythmic sway. Twelve of the 15 subjects enjoyed the game and asserted an interest in playing again. Digital posturography games engage children with cerebral palsy in balance tasks, provide visual feedback in a balance control task, and have the potential to increase autonomy in balance control training among pediatric patients with cerebral palsy. This approach can support the relationship between child and therapist. The potential for interactive posturography to complement the assessment and treatment of balance in cerebral palsy bears continuing study.

The Bose-Einstein correlations in CDFII experiment

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

Lovás, Lubomír

We present the results of a study of pmore » $$\\bar{p}$$ collisions at √s = 1.96 TeV collected by the CDF-II experiment at Tevatron collider. The Bose-Einstein correlations of the π ±π ± two boson system have been studied in the minimum-bias high-multiplicity events. The research was carried out on the sample at the size of 173761 events. The two pion correlations have been retrieved. The final results were corrected to the coulomb interactions. Two different reference samples were compared and discussed. A significant two-pion correlation enhancement near origin is observed. This enhancement effect has been used to evaluate the radius of the two-pion emitter source. We have used the TOF detector to distinguish between π and K mesons. The C 2(Q) function parameters have also been retrieved for the sample containing only tagged π mesons. A comparison between four different parametrizations based on two diff t theoretical approaches of the C 2(Q) function is given.« less

Neuroimaging in pedophilia.

PubMed

Wiebking, Christine; Northoff, Georg

2013-04-01

Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.

Altered topology of neural circuits in congenital prosopagnosia.

PubMed

Rosenthal, Gideon; Tanzer, Michal; Simony, Erez; Hasson, Uri; Behrmann, Marlene; Avidan, Galia

2017-08-21

Using a novel, fMRI-based inter-subject functional correlation (ISFC) approach, which isolates stimulus-locked inter-regional correlation patterns, we compared the cortical topology of the neural circuit for face processing in participants with an impairment in face recognition, congenital prosopagnosia (CP), and matched controls. Whereas the anterior temporal lobe served as the major network hub for face processing in controls, this was not the case for the CPs. Instead, this group evinced hyper-connectivity in posterior regions of the visual cortex, mostly associated with the lateral occipital and the inferior temporal cortices. Moreover, the extent of this hyper-connectivity was correlated with the face recognition deficit. These results offer new insights into the perturbed cortical topology in CP, which may serve as the underlying neural basis of the behavioral deficits typical of this disorder. The approach adopted here has the potential to uncover altered topologies in other neurodevelopmental disorders, as well.

Quenching the XXZ spin chain: quench action approach versus generalized Gibbs ensemble

NASA Astrophysics Data System (ADS)

Mestyán, M.; Pozsgay, B.; Takács, G.; Werner, M. A.

2015-04-01

Following our previous work (Pozsgay et al 2014 Phys. Rev. Lett. 113 117203) we present here a detailed comparison of the quench action approach and the predictions of the generalized Gibbs ensemble, with the result that while the quench action formalism correctly captures the steady state, the GGE does not give a correct description of local short-distance correlation functions. We extend our studies to include another initial state, the so-called q-dimer state. We present important details of our construction, including new results concerning exact overlaps for the dimer and q-dimer states, and we also give an exact solution of the quench-action-based overlap-TBA for the q-dimer. Furthermore, we extend our computations to include the xx spin correlations besides the zz correlations treated previously, and give a detailed discussion of the underlying reasons for the failure of the GGE, especially in the light of new developments.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

Toward ab initio molecular dynamics modeling for sum-frequency generation spectra; an efficient algorithm based on surface-specific velocity-velocity correlation function.

PubMed

Ohto, Tatsuhiko; Usui, Kota; Hasegawa, Taisuke; Bonn, Mischa; Nagata, Yuki

2015-09-28

Interfacial water structures have been studied intensively by probing the O-H stretch mode of water molecules using sum-frequency generation (SFG) spectroscopy. This surface-specific technique is finding increasingly widespread use, and accordingly, computational approaches to calculate SFG spectra using molecular dynamics (MD) trajectories of interfacial water molecules have been developed and employed to correlate specific spectral signatures with distinct interfacial water structures. Such simulations typically require relatively long (several nanoseconds) MD trajectories to allow reliable calculation of the SFG response functions through the dipole moment-polarizability time correlation function. These long trajectories limit the use of computationally expensive MD techniques such as ab initio MD and centroid MD simulations. Here, we present an efficient algorithm determining the SFG response from the surface-specific velocity-velocity correlation function (ssVVCF). This ssVVCF formalism allows us to calculate SFG spectra using a MD trajectory of only ∼100 ps, resulting in the substantial reduction of the computational costs, by almost an order of magnitude. We demonstrate that the O-H stretch SFG spectra at the water-air interface calculated by using the ssVVCF formalism well reproduce those calculated by using the dipole moment-polarizability time correlation function. Furthermore, we applied this ssVVCF technique for computing the SFG spectra from the ab initio MD trajectories with various density functionals. We report that the SFG responses computed from both ab initio MD simulations and MD simulations with an ab initio based force field model do not show a positive feature in its imaginary component at 3100 cm(-1).

Functional brain networks associated with eating behaviors in obesity.

PubMed

Park, Bo-Yong; Seo, Jongbum; Park, Hyunjin

2016-03-31

Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores.

Exact correlators on the Wilson loop in N=4 SYM: localization, defect CFT, and integrability

NASA Astrophysics Data System (ADS)

Giombi, Simone; Komatsu, Shota

2018-05-01

We compute a set of correlation functions of operator insertions on the 1 /8 BPS Wilson loop in N=4 SYM by employing supersymmetric localization, OPE and the Gram-Schmidt orthogonalization. These correlators exhibit a simple determinant structure, are position-independent and form a topological subsector, but depend nontrivially on the 't Hooft coupling and the rank of the gauge group. When applied to the 1 /2 BPS circular (or straight) Wilson loop, our results provide an infinite family of exact defect CFT data, including the structure constants of protected defect primaries of arbitrary length inserted on the loop. At strong coupling, we show precise agreement with a direct calculation using perturbation theory around the AdS2 string worldsheet. We also explain the connection of our results to the "generalized Bremsstrahlung functions" previously computed from integrability techniques, reproducing the known results in the planar limit as well as obtaining their finite N generalization. Furthermore, we show that the correlators at large N can be recast as simple integrals of products of polynomials (known as Q-functions) that appear in the Quantum Spectral Curve approach. This suggests an interesting interplay between localization, defect CFT and integrability.

Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l₁-norm as approximation of Pearson's temporal correlation: proof-of-concept and example vector hardware implementation.

PubMed

Minati, Ludovico; Zacà, Domenico; D'Incerti, Ludovico; Jovicich, Jorge

2014-09-01

An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1(9)-1(11) links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l1-norm. Even though the adjacency matrices derived from correlation coefficients and l1-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l1-norm on an array of 4096 zero instruction-set processors. Calculation times <1000 s are attainable, removing the major deterrent to voxel-based resting-sate network mapping and revealing fine-grained node degree heterogeneity. L1-norm should be given consideration as a substitute for correlation in very high-density resting-state functional connectivity analyses. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Binary collision approximations for the memory function for density fluctuations in equilibrium atomic liquids

NASA Astrophysics Data System (ADS)

Noah, Joyce E.

Time correlation functions of density fluctuations of liquids at equilibrium can be used to relate the microscopic dynamics of a liquid to its macroscopic transport properties. Time correlation functions are especially useful since they can be generated in a variety of ways, from scattering experiments to computer simulation to analytic theory. The kinetic theory of fluctuations in equilibrium liquids is an analytic theory for calculating correlation functions using memory functions. In this work, we use a diagrammatic formulation of the kinetic theory to develop a series of binary collision approximations for the collisional part of the memory function. We define binary collisions as collisions between two distinct density fluctuations whose identities are fixed during the duration of a collsion. R approximations are for the short time part of the memory function, and build upon the work of Ranganathan and Andersen. These approximations have purely repulsive interactions between the fluctuations. The second type of approximation, RA approximations, is for the longer time part of the memory function, where the density fluctuations now interact via repulsive and attractive forces. Although RA approximations are a natural extension of R approximations, they permit two density fluctuations to become trapped in the wells of the interaction potential, leading to long-lived oscillatory behavior, which is unphysical. Therefore we consider S approximations which describe binary particles which experience the random effect of the surroundings while interacting via repulsive or repulsive and attractive interactions. For each of these approximations for the memory function we numerically solve the kinetic equation to generate correlation functions. These results are compared to molecular dynamics results for the correlation functions. Comparing the successes and failures of the different approximations, we conclude that R approximations give more accurate intermediate and long time results while RA and S approximations do particularly well at predicting the short time behavior. Lastly, we also develop a series of non-graphically derived approximations and use an optimization procedure to determine the underlying memory function from the simulation data. These approaches provide valuable information about the memory function that will be used in the development of future kinetic theories.

Function Lateralization via Measuring Coherence Laterality

PubMed Central

Wang, Ze; Mechanic-Hamilton, Dawn; Pluta, John; Glynn, Simon; Detre, John A.

2009-01-01

A data-driven approach for lateralization of brain function based on the spatial coherence difference of functional MRI (fMRI) data in homologous regions-of-interest (ROI) in each hemisphere is proposed. The utility of using coherence laterality (CL) to determine function laterality was assessed first by examining motor laterality using normal subjects’ data acquired both at rest and with a simple unilateral motor task and subsequently by examining mesial temporal lobe memory laterality in normal subjects and patients with temporal lobe epilepsy. The motor task was used to demonstrate that CL within motor ROI correctly lateralized functional stimulation. In patients with unilateral epilepsy studied during a scene-encoding task, CL in a hippocampus-parahippocampus-fusiform (HPF) ROI was concordant with lateralization based on task activation, and the CL index (CLI) significantly differentiated the right side group to the left side group. By contrast, normal controls showed a symmetric HPF CLI distribution. Additionally, similar memory laterality prediction results were still observed using CL in epilepsy patients with unilateral seizures after the memory encoding effect was removed from the data, suggesting the potential for lateralization of pathological brain function based on resting fMRI data. A better lateralization was further achieved via a combination of the proposed approach and the standard activation based approach, demonstrating that assessment of spatial coherence changes provides a complementary approach to quantifying task-correlated activity for lateralizing brain function. PMID:19345736

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

A simplified implementation of van der Waals density functionals for first-principles molecular dynamics applications

NASA Astrophysics Data System (ADS)

Wu, Jun; Gygi, François

2012-06-01

We present a simplified implementation of the non-local van der Waals correlation functional introduced by Dion et al. [Phys. Rev. Lett. 92, 246401 (2004)] and reformulated by Román-Pérez et al. [Phys. Rev. Lett. 103, 096102 (2009)]. The proposed numerical approach removes the logarithmic singularity of the kernel function. Complete expressions of the self-consistent correlation potential and of the stress tensor are given. Combined with various choices of exchange functionals, five versions of van der Waals density functionals are implemented. Applications to the computation of the interaction energy of the benzene-water complex and to the computation of the equilibrium cell parameters of the benzene crystal are presented. As an example of crystal structure calculation involving a mixture of hydrogen bonding and dispersion interactions, we compute the equilibrium structure of two polymorphs of aspirin (2-acetoxybenzoic acid, C9H8O4) in the P21/c monoclinic structure.

Fatigue crack growth in unidirectional metal matrix composite

NASA Technical Reports Server (NTRS)

Ghosn, Louis J.; Telesman, Jack; Kantzos, Peter

1990-01-01

The weight function method was used to determine the effective stress intensity factor and the crack opening profile for a fatigue tested composite which exhibited fiber bridging. The bridging mechanism was modeled using two approaches; the crack closure approach and the shear lag approach. The numerically determined stress intensity factor values from both methods were compared and correlated with the experimentally obtained crack growth rates for SiC/Ti-15-3 (0)(sub 8) oriented composites. The near crack tip opening profile was also determined for both methods and compared with the experimentally obtained measurements.

On the accuracy of van der Waals inclusive density-functional theory exchange-correlation functionals for ice at ambient and high pressures.

PubMed

Santra, Biswajit; Klimes, Jirí; Tkatchenko, Alexandre; Alfè, Dario; Slater, Ben; Michaelides, Angelos; Car, Roberto; Scheffler, Matthias

2013-10-21

Density-functional theory (DFT) has been widely used to study water and ice for at least 20 years. However, the reliability of different DFT exchange-correlation (xc) functionals for water remains a matter of considerable debate. This is particularly true in light of the recent development of DFT based methods that account for van der Waals (vdW) dispersion forces. Here, we report a detailed study with several xc functionals (semi-local, hybrid, and vdW inclusive approaches) on ice Ih and six proton ordered phases of ice. Consistent with our previous study [B. Santra, J. Klimeš, D. Alfè, A. Tkatchenko, B. Slater, A. Michaelides, R. Car, and M. Scheffler, Phys. Rev. Lett. 107, 185701 (2011)] which showed that vdW forces become increasingly important at high pressures, we find here that all vdW inclusive methods considered improve the relative energies and transition pressures of the high-pressure ice phases compared to those obtained with semi-local or hybrid xc functionals. However, we also find that significant discrepancies between experiment and the vdW inclusive approaches remain in the cohesive properties of the various phases, causing certain phases to be absent from the phase diagram. Therefore, room for improvement in the description of water at ambient and high pressures remains and we suggest that because of the stern test the high pressure ice phases pose they should be used in future benchmark studies of simulation methods for water.

Time-sliced perturbation theory for large scale structure I: general formalism

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

Blas, Diego; Garny, Mathias; Sibiryakov, Sergey

2016-07-01

We present a new analytic approach to describe large scale structure formation in the mildly non-linear regime. The central object of the method is the time-dependent probability distribution function generating correlators of the cosmological observables at a given moment of time. Expanding the distribution function around the Gaussian weight we formulate a perturbative technique to calculate non-linear corrections to cosmological correlators, similar to the diagrammatic expansion in a three-dimensional Euclidean quantum field theory, with time playing the role of an external parameter. For the physically relevant case of cold dark matter in an Einstein-de Sitter universe, the time evolution ofmore » the distribution function can be found exactly and is encapsulated by a time-dependent coupling constant controlling the perturbative expansion. We show that all building blocks of the expansion are free from spurious infrared enhanced contributions that plague the standard cosmological perturbation theory. This paves the way towards the systematic resummation of infrared effects in large scale structure formation. We also argue that the approach proposed here provides a natural framework to account for the influence of short-scale dynamics on larger scales along the lines of effective field theory.« less

A Holistic approach to assess older adults' wellness using e-health technologies.

PubMed

Thompson, Hilaire J; Demiris, George; Rue, Tessa; Shatil, Evelyn; Wilamowska, Katarzyna; Zaslavsky, Oleg; Reeder, Blaine

2011-12-01

To date, methodologies are lacking that address a holistic assessment of wellness in older adults. Technology applications may provide a platform for such an assessment, but have not been validated. We set out to demonstrate whether e-health applications could support the assessment of older adults' wellness in community-dwelling older adults. Twenty-seven residents of independent retirement community were followed over 8 weeks. Subjects engaged in the use of diverse technologies to assess cognitive performance, physiological and functional variables, as well as psychometric components of wellness. Data were integrated from various e-health sources into one study database. Correlations were assessed between different parameters, and hierarchical cluster analysis was used to explore the validity of the wellness model. We found strong associations across multiple parameters of wellness within the conceptual model, including cognitive, functional, and physical. However, spirituality did not correlate with any other parameter studied in contrast to prior studies of older adults. Participants expressed overall positive attitudes toward the e-health tools and the holistic approach to the assessment of wellness, without expressing any privacy concerns. Parameters were highly correlated across multiple domains of wellness. Important clusters were noted to be formed across cognitive and physiological domains, giving further evidence of need for an integrated approach to the assessment of wellness. This finding warrants further replication in larger and more diverse samples of older adults to standardize and deploy these technologies across population groups.

Role of temperature on static correlational properties in a spin-polarized electron gas

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

Arora, Priya; Moudgil, R. K., E-mail: rkmoudgil@kuk.ac.in; Kumar, Krishan

We have studied the effect of temperature on the static correlational properties of a spin-polarized three-dimensional electron gas (3DEG) over a wide coupling and temperature regime. This problem has been very recently studied by Brown et al. using the restricted path-integral Monte Carlo (RPIMC) technique in the warm-dense regime. To this endeavor, we have used the finite temperature version of the dynamical mean-field theory of Singwi et al, the so-called quantum STLS (qSTLS) approach. The static density structure factor and the static pair-correlation function are calculated, and compared with the RPIMC simulation data. We find an excellent agreement with themore » simulation at high temperature over a wide coupling range. However, the agreement is seen to somewhat deteriorate with decreasing temperature. The pair-correlation function is found to become small negative for small electron separation. This may be attributed to the inadequacy of the mean-field theory in dealing with the like spin electron correlations in the strong-coupling domain. A nice agreement with RPIMC data at high temperature seems to arise due to weakening of both the exchange and coulomb correlations with rising temperature.« less

Comparison of muscle/lean mass measurement methods: correlation with functional and biochemical testing.

PubMed

Buehring, B; Siglinsky, E; Krueger, D; Evans, W; Hellerstein, M; Yamada, Y; Binkley, N

2018-03-01

DXA-measured lean mass is often used to assess muscle mass but has limitations. Thus, we compared DXA lean mass with two novel methods-bioelectric impedance spectroscopy and creatine (methyl-d3) dilution. The examined methodologies did not measure lean mass similarly and the correlation with muscle biomarkers/function varied. Muscle function tests predict adverse health outcomes better than lean mass measurement. This may reflect limitations of current mass measurement methods. Newer approaches, e.g., bioelectric impedance spectroscopy (BIS) and creatine (methyl-d3) dilution (D3-C), may more accurately assess muscle mass. We hypothesized that BIS and D3-C measured muscle mass would better correlate with function and bone/muscle biomarkers than DXA measured lean mass. Evaluations of muscle/lean mass, function, and serum biomarkers were obtained in older community-dwelling adults. Mass was assessed by DXA, BIS, and orally administered D3-C. Grip strength, timed up and go, and jump power were examined. Potential muscle/bone serum biomarkers were measured. Mass measurements were compared with functional and serum data using regression analyses; differences between techniques were determined by paired t tests. Mean (SD) age of the 112 (89F/23M) participants was 80.6 (6.0) years. The lean/muscle mass assessments were correlated (.57-.88) but differed (p < 0.0001) from one another with DXA total body less head being highest at 37.8 (7.3) kg, D3-C muscle mass at 21.1 (4.6) kg, and BIS total body intracellular water at 17.4 (3.5) kg. All mass assessment methods correlated with grip strength and jump power (R = 0.35-0.63, p < 0.0002), but not with gait speed or repeat chair rise. Lean mass measures were unrelated to the serum biomarkers measured. These three methodologies do not similarly measure muscle/lean mass and should not be viewed as being equivalent. Functional tests assessing maximal muscle strength/power (grip strength and jump power) correlated with all mass measures whereas gait speed was not. None of the selected serum measures correlated with mass. Efforts to optimize muscle mass assessment and identify their relationships with health outcomes are needed.

Jordanian Men's and Women's Attitudes Toward Intimate Partner Violence and Its Correlates With Family Functioning and Demographics.

PubMed

Alzoubi, Fatmeh Ahmad; Ali, Reem Ahmad

2018-04-01

Jordan is a developing country in the Middle East and, much like other countries in the world, has high rates of intimate partner violence (IPV). Little information is available on Jordanian men's and women's attitudes toward IPV. The purpose of this study is to examine men's and women's attitudes toward IPV in Jordan and its relationship with some demographics and family functioning. A descriptive cross-sectional correlational design with a sample of 401 men and women was used. Descriptive statistics ( M, SD), Pearson r, t test, and ANOVA were used. The results indicated that Jordanian men and women have a lower score of IPVAS, 40.06 ( SD = 8.20), indicating lower acceptance of IPV compared with the literature. Family functioning was 3.12 ( SD = 0.46), indicating more healthy families. Family functioning was negatively correlated with IPVAS scores ( r = -.22, p = .00). All demographic variables showed small to moderate correlations with IPVAS. Education for both study participants and their spouses had a negative correlation with IPVAS ( r = -.27, p = .00) and ( r = -.20, p = .00), respectively. Male participants, individuals who were living with extended family, and those living in rural areas had significantly high IPVAS scores, indicating more accepting attitudes toward IPV. Practitioners should provide families with education on the methods of conflict resolution, effective communication within the family, problem-solving approaches, equal role distribution, and appropriate styles of establishing a family.

Seed germination strategies: an evolutionary trajectory independent of vegetative functional traits

PubMed Central

Hoyle, Gemma L.; Steadman, Kathryn J.; Good, Roger B.; McIntosh, Emma J.; Galea, Lucy M. E.; Nicotra, Adrienne B.

2015-01-01

Seed germination strategies vary dramatically among species but relatively little is known about how germination traits correlate with other elements of plant strategy systems. Understanding drivers of germination strategy is critical to our understanding of the evolutionary biology of plant reproduction.We present a novel assessment of seed germination strategies focussing on Australian alpine species as a case study. We describe the distribution of germination strategies and ask whether these are correlated with, or form an independent axis to, other plant functional traits. Our approach to describing germination strategy mimicked realistic temperatures that seeds experience in situ following dispersal. Strategies were subsequently assigned using an objective clustering approach. We hypothesized that two main strategies would emerge, involving dormant or non-dormant seeds, and that while these strategies would be correlated with seed traits (e.g., mass or endospermy) they would be largely independent of vegetative traits when analysed in a phylogenetically structured manner.Across all species, three germination strategies emerged. The majority of species postponed germination until after a period of cold, winter-like temperatures indicating physiological and/or morphological dormancy mechanisms. Other species exhibited immediate germination at temperatures representative of those at dispersal. Interestingly, seeds of an additional 13 species “staggered” germination over time. Germination strategies were generally conserved within families. Across a broad range of ecological traits only seed mass and endospermy showed any correlation with germination strategy when phylogenetic relatedness was accounted for; vegetative traits showed no significant correlations with germination strategy. The results indicate that germination traits correlate with other aspects of seed ecology but form an independent axis relative to vegetative traits. PMID:26528294

Aggregation models on hypergraphs

NASA Astrophysics Data System (ADS)

Alberici, Diego; Contucci, Pierluigi; Mingione, Emanuele; Molari, Marco

2017-01-01

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer-dimer case. After translating those relations into structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.

Perspective: Toward "synthesis by design": Exploring atomic correlations during inorganic materials synthesis

NASA Astrophysics Data System (ADS)

Soderholm, L.; Mitchell, J. F.

2016-05-01

Synthesis of inorganic extended solids is a critical starting point from which real-world functional materials and their consequent technologies originate. However, unlike the rich mechanistic foundation of organic synthesis, with its underlying rules of assembly (e.g., functional groups and their reactivities), the synthesis of inorganic materials lacks an underpinning of such robust organizing principles. In the latter case, any such rules must account for the diversity of chemical species and bonding motifs inherent to inorganic materials and the potential impact of mass transport on kinetics, among other considerations. Without such assembly rules, there is less understanding, less predictive power, and ultimately less control of properties. Despite such hurdles, developing a mechanistic understanding for synthesis of inorganic extended solids would dramatically impact the range of new material discoveries and resulting new functionalities, warranting a broad call to explore what is possible. Here we discuss our recent approaches toward a mechanistic framework for the synthesis of bulk inorganic extended solids, in which either embryonic atomic correlations or fully developed phases in solutions or melts can be identified and tracked during product selection and crystallization. The approach hinges on the application of high-energy x-rays, with their penetrating power and large Q-range, to explore reaction pathways in situ. We illustrate this process using two examples: directed assembly of Zr clusters in aqueous solution and total phase awareness during crystallization from K-Cu-S melts. These examples provide a glimpse of what we see as a larger vision, in which large scale simulations, data-driven science, and in situ studies of atomic correlations combine to accelerate materials discovery and synthesis, based on the assembly of well-defined, prenucleated atomic correlations.

Perspective: Toward “synthesis by design”: Exploring atomic correlations during inorganic materials synthesis

DOE PAGES

Soderholm, L.; Mitchell, J. F.

2016-05-26

Synthesis of inorganic extended solids is a critical starting point from which real-world functional materials and their consequent technologies originate. However, unlike the rich mechanistic foundation of organic synthesis, with its underlying rules of assembly (e.g., functional groups and their reactivities), the synthesis of inorganic materials lacks an underpinning of such robust organizing principles. In the latter case, any such rules must account for the diversity of chemical species and bonding motifs inherent to inorganic materials and the potential impact of mass transport on kinetics, among other considerations. Without such assembly rules, there is less understanding, less predictive power, andmore » ultimately less control of properties. Despite such hurdles, developing a mechanistic understanding for synthesis of inorganic extended solids would dramatically impact the range of new material discoveries and resulting new functionalities, warranting a broad call to explore what is possible. Here we discuss our recent approaches toward a mechanistic framework for the synthesis of bulk inorganic extended solids, in which either embryonic atomic correlations or fully developed phases in solutions or melts can be identified and tracked during product selection and crystallization. The approach hinges on the application of high-energy x-rays, with their penetrating power and large Q-range, to explore reaction pathways in situ. We illustrate this process using two examples: directed assembly of Zr clusters in aqueous solution and total phase awareness during crystallization from K–Cu–S melts. These examples provide a glimpse of what we see as a larger vision, in which large scale simulations, data-driven science, and in situ studies of atomic correlations combine to accelerate materials discovery and synthesis, based on the assembly of well-defined, prenucleated atomic correlations.« less

Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Hierarchical Brain Networks Active in Approach and Avoidance Goal Pursuit

PubMed Central

Spielberg, Jeffrey M.; Heller, Wendy; Miller, Gregory A.

2013-01-01

Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures. PMID:23785328

Hierarchical brain networks active in approach and avoidance goal pursuit.

PubMed

Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

2013-01-01

Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

Experimental and first principle studies on electronic structure of BaTiO{sub 3}

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

Sagdeo, Archna, E-mail: archnaj@rrcat.gov.in; Ghosh, Haranath, E-mail: archnaj@rrcat.gov.in; Chakrabarti, Aparna, E-mail: archnaj@rrcat.gov.in

2014-04-24

We have carried out photoemission experiments to obtain valence band spectra of various crystallographic symmetries of BaTiO{sub 3} system which arise as a function of temperature. We also present results of a detailed first principle study of these symmetries of BaTiO{sub 3} using generalized gradient approximation for the exchange-correlation potential. Here we present theoretical results of density of states obtained from DFT based simulations to compare with the experimental valence band spectra. Further, we also perform calculations using post density functional approaches like GGA + U method as well as non-local hybrid exchange-correlation potentials like PBE0, B3LYP, HSE in ordermore » to understand the extent of effect of correlation on band gaps of different available crystallographic symmetries (5 in number) of BaTiO{sub 3}.« less

The Cognitive Assessment Interview (CAI): development and validation of an empirically derived, brief interview-based measure of cognition.

PubMed

Ventura, Joseph; Reise, Steven P; Keefe, Richard S E; Baade, Lyle E; Gold, James M; Green, Michael F; Kern, Robert S; Mesholam-Gately, Raquelle; Nuechterlein, Keith H; Seidman, Larry J; Bilder, Robert M

2010-08-01

Practical, reliable "real world" measures of cognition are needed to supplement neurocognitive performance data to evaluate possible efficacy of new drugs targeting cognitive deficits associated with schizophrenia. Because interview-based measures of cognition offer one possible approach, data from the MATRICS initiative (n=176) were used to examine the psychometric properties of the Schizophrenia Cognition Rating Scale (SCoRS) and the Clinical Global Impression of Cognition in Schizophrenia (CGI-CogS). We used classical test theory methods and item response theory to derive the 10-item Cognitive Assessment Interview (CAI) from the SCoRS and CGI-CogS ("parent instruments"). Sources of information for CAI ratings included the patient and an informant. Validity analyses examined the relationship between the CAI and objective measures of cognitive functioning, intermediate measures of cognition, and functional outcome. The rater's score from the newly derived CAI (10 items) correlate highly (r=.87) with those from the combined set of the SCoRS and CGI-CogS (41 items). Both the patient (r=.82) and the informant (r=.95) data were highly correlated with the rater's score. The CAI was modestly correlated with objectively measured neurocognition (r=-.32), functional capacity (r=-.44), and functional outcome (r=-.32), which was comparable to the parent instruments. The CAI allows for expert judgment in evaluating a patient's cognitive functioning and was modestly correlated with neurocognitive functioning, functional capacity, and functional outcome. The CAI is a brief, repeatable, and potentially valuable tool for rating cognition in schizophrenia patients who are participating in clinical trials. Copyright 2010 Elsevier B.V. All rights reserved.

The Cognitive Assessment Interview (CAI): Development and Validation of an Empirically Derived, Brief Interview-Based Measure of Cognition

PubMed Central

Ventura, Joseph; Reise, Steven P.; Keefe, Richard S. E.; Baade, Lyle E.; Gold, James M.; Green, Michael F.; Kern, Robert S.; Mesholam-Gately, Raquelle; Nuechterlein, Keith H.; Seidman, Larry J.; Bilder, Robert M.

2011-01-01

Background Practical, reliable “real world” measures of cognition are needed to supplement neurocognitive performance data to evaluate possible efficacy of new drugs targeting cognitive deficits associated with schizophrenia. Because interview-based measures of cognition offer one possible approach, data from the MATRICS initiative (n=176) were used to examine the psychometric properties of the Schizophrenia Cognition Rating Scale (SCoRS) and the Clinical Global Impression of Cognition in Schizophrenia (CGI-CogS). Method We used classical test theory methods and item response theory to derive the 10 item Cognitive Assessment Interview (CAI) from the SCoRS and CGI-Cogs (“parent instruments”). Sources of information for CAI ratings included the patient and an informant. Validity analyses examined the relationship between the CAI and objective measures of cognitive functioning, intermediate measures of cognition, and functional outcome. Results The rater’s score from the newly derived CAI (10-items) correlate highly (r = .87) with those from the combined set of the SCoRS and CGI-CogS (41 items). Both the patient (r= .82) and the informant (r= .95) data were highly correlated with the rater’s score. The CAI was modestly correlated with objectively measured neurocognition (r = −.32), functional capacity (r = −.44), and functional outcome (r = −.32), which was comparable to the parent instruments. Conclusions The CAI allows for expert judgment in evaluating a patient’s cognitive functioning and was modestly correlated with neurocognitive functioning, functional capacity, and functional outcome. The CAI is a brief, repeatable, and potentially valuable tool for rating cognition in schizophrenia patients who are participating in clinical trials. PMID:20542412

A New Approach in Generating Meteorological Forecasts for Ensemble Streamflow Forecasting using Multivariate Functions

NASA Astrophysics Data System (ADS)

Khajehei, S.; Madadgar, S.; Moradkhani, H.

2014-12-01

The reliability and accuracy of hydrological predictions are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model parameters and model structure. To reduce the total uncertainty in hydrological applications, one approach is to reduce the uncertainty in meteorological forcing by using the statistical methods based on the conditional probability density functions (pdf). However, one of the requirements for current methods is to assume the Gaussian distribution for the marginal distribution of the observed and modeled meteorology. Here we propose a Bayesian approach based on Copula functions to develop the conditional distribution of precipitation forecast needed in deriving a hydrologic model for a sub-basin in the Columbia River Basin. Copula functions are introduced as an alternative approach in capturing the uncertainties related to meteorological forcing. Copulas are multivariate joint distribution of univariate marginal distributions, which are capable to model the joint behavior of variables with any level of correlation and dependency. The method is applied to the monthly forecast of CPC with 0.25x0.25 degree resolution to reproduce the PRISM dataset over 1970-2000. Results are compared with Ensemble Pre-Processor approach as a common procedure used by National Weather Service River forecast centers in reproducing observed climatology during a ten-year verification period (2000-2010).

A statistically compiled test battery for feasible evaluation of knee function after rupture of the Anterior Cruciate Ligament – derived from long-term follow-up data

PubMed Central

2017-01-01

Purpose Clinical test batteries for evaluation of knee function after injury to the Anterior Cruciate Ligament (ACL) should be valid and feasible, while reliably capturing the outcome of rehabilitation. There is currently a lack of consensus as to which of the many available assessment tools for knee function that should be included. The present aim was to use a statistical approach to investigate the contribution of frequently used tests to avoid redundancy, and filter them down to a proposed comprehensive and yet feasible test battery for long-term evaluation after ACL injury. Methods In total 48 outcome variables related to knee function, all potentially relevant for a long-term follow-up, were included from a cross-sectional study where 70 ACL-injured (17–28 years post injury) individuals were compared to 33 controls. Cluster analysis and logistic regression were used to group variables and identify an optimal test battery, from which a summarized estimator of knee function representing various functional aspects was derived. Results As expected, several variables were strongly correlated, and the variables also fell into logical clusters with higher within-correlation (max ρ = 0.61) than between clusters (max ρ = 0.19). An extracted test battery with just four variables assessing one-leg balance, isokinetic knee extension strength and hop performance (one-leg hop, side hop) were mathematically combined to an estimator of knee function, which acceptably classified ACL-injured individuals and controls. This estimator, derived from objective measures, correlated significantly with self-reported function, e.g. Lysholm score (ρ = 0.66; p<0.001). Conclusions The proposed test battery, based on a solid statistical approach, includes assessments which are all clinically feasible, while also covering complementary aspects of knee function. Similar test batteries could be determined for earlier phases of ACL rehabilitation or to enable longitudinal monitoring. Such developments, established on a well-grounded consensus of measurements, would facilitate comparisons of studies and enable evidence-based rehabilitation. PMID:28459885

Wave-function-based approach to quasiparticle bands: Insight into the electronic structure of c-ZnS

NASA Astrophysics Data System (ADS)

Stoyanova, A.; Hozoi, L.; Fulde, P.; Stoll, H.

2011-05-01

Ab initio wave-function-based methods are employed for the study of quasiparticle energy bands of zinc-blende ZnS, with focus on the Zn 3d “semicore” states. The relative energies of these states with respect to the top of the S 3p valence bands appear to be poorly described as compared to experimental values not only within the local density approximation (LDA), but also when many-body corrections within the GW approximation are applied to the LDA or LDA + U mean-field solutions [T. Miyake, P. Zhang, M. L. Cohen, and S. G. Louie, Phys. Rev. BPRBMDO1098-012110.1103/PhysRevB.74.245213 74, 245213 (2006)]. In the present study, we show that for the accurate description of the Zn 3d states a correlation treatment based on wave-function methods is needed. Our study rests on a local Hamiltonian approach which rigorously describes the short-range polarization and charge redistribution effects around an extra hole or electron placed into the valence respective conduction bands of semiconductors and insulators. The method also facilitates the computation of electron correlation effects beyond relaxation and polarization. The electron correlation treatment is performed on finite clusters cut off the infinite system. The formalism makes use of localized Wannier functions and embedding potentials derived explicitly from prior periodic Hartree-Fock calculations. The on-site and nearest-neighbor charge relaxation lead to corrections of several eV to the Hartree-Fock band energies and gap. Corrections due to long-range polarization are of the order of 1.0 eV. The dispersion of the Hartree-Fock bands is only slightly affected by electron correlations. We find the Zn 3d “semicore” states to lie ~9.0 eV below the top of the S 3p valence bands, in very good agreement with values from valence-band x-ray photoemission.

Relationship Between Persistent Negative Symptoms and Findings of Neurocognition and Neuroimaging in Schizophrenia.

PubMed

İnce, Ezgi; Üçok, Alp

2018-01-01

Negative symptoms are defined as loss or reduction of otherwise present behaviors or functions in illness situation, and they have constituted an important aspect of schizophrenia. Although negative symptoms have usually been considered as a single entity, neurobiological investigations yielded discrepant results. To overcome challenges that derive from this discrepancy, researchers have proposed several approaches to structure negative symptoms into more homogenous constructs. Concept of persistent negative symptoms (PNS) is one of the proposed approaches, and includes both primary and secondary negative symptoms that persist after adequate treatment. PNS is relatively easy to assess, and by definition, more inclusive; yet it represents an unmet therapeutic need. Therefore, it is a target of several neurobiological and pharmacological studies. There are several structural and functional brain alterations associated with negative symptoms. On the other hand, neurocognitive investigations in patients with schizophrenia have revealed deficits in several domains that showed correlations with negative symptoms. There are several shared features between negative symptoms and neurocognitive deficits in schizophrenia such as prevalence rates, course through the illness, prognostic importance, and impact on social functioning. However, exact mechanisms behind the neurobiology of PNS and how it interacts with neurocognition remain to be explained. Earlier reviews on neuroimaging and neurocognitive correlates of PNS have been focused on studies with broadly defined negative symptoms that were selected by methodological closeness to PNS. In this review, we focus on neural correlates and neurocognitive associations of PNS, and we discuss PNS findings available to date.

Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

PubMed

Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

2015-10-01

The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Network modelling methods for FMRI.

PubMed

Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

2011-01-15

There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

{Phi}{sup 4} kinks: Statistical mechanics

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

Habib, S.

1995-12-31

Some recent investigations of the thermal equilibrium properties of kinks in a 1+1-dimensional, classical {phi}{sup 4} field theory are reviewed. The distribution function, kink density, correlation function, and certain thermodynamic quantities were studied both theoretically and via large scale simulations. A simple double Gaussian variational approach within the transfer operator formalism was shown to give good results in the intermediate temperature range where the dilute gas theory is known to fail.

Statistical Approach To Extraction Of Texture In SAR

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Kwok, Ronald

1992-01-01

Improved statistical method of extraction of textural features in synthetic-aperture-radar (SAR) images takes account of effects of scheme used to sample raw SAR data, system noise, resolution of radar equipment, and speckle. Treatment of speckle incorporated into overall statistical treatment of speckle, system noise, and natural variations in texture. One computes speckle auto-correlation function from system transfer function that expresses effect of radar aperature and incorporates range and azimuth resolutions.

Percolation thresholds and fractal dimensions for square and cubic lattices with long-range correlated defects

NASA Astrophysics Data System (ADS)

Zierenberg, Johannes; Fricke, Niklas; Marenz, Martin; Spitzner, F. P.; Blavatska, Viktoria; Janke, Wolfhard

2017-12-01

We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as a function of the correlation strength. The correlations are generated using a discrete version of the Fourier filtering method. We consider two different metrics to set the length scales over which the correlations decay, showing that the percolation thresholds are highly sensitive to such system details. By contrast, we verify that the fractal dimension df is a universal quantity and unaffected by the choice of metric. We also show that for weak correlations, its value coincides with that for the uncorrelated system. In two dimensions we observe a clear increase of the fractal dimension with increasing correlation strength, approaching df→2 . The onset of this change does not seem to be determined by the extended Harris criterion.

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

Tang, Zhoufei; Ouyang, Xiaolong; Gong, Zhihao

An extended hierarchy equation of motion (HEOM) is proposed and applied to study the dynamics of the spin-boson model. In this approach, a complete set of orthonormal functions are used to expand an arbitrary bath correlation function. As a result, a complete dynamic basis set is constructed by including the system reduced density matrix and auxiliary fields composed of these expansion functions, where the extended HEOM is derived for the time derivative of each element. The reliability of the extended HEOM is demonstrated by comparison with the stochastic Hamiltonian approach under room-temperature classical ohmic and sub-ohmic noises and the multilayermore » multiconfiguration time-dependent Hartree theory under zero-temperature quantum ohmic noise. Upon increasing the order in the hierarchical expansion, the result obtained from the extended HOEM systematically converges to the numerically exact answer.« less

Mind Operational Semantics and Brain Operational Architectonics: A Putative Correspondence

PubMed Central

Benedetti, Giulio; Marchetti, Giorgio; Fingelkurts, Alexander A; Fingelkurts, Andrew A

2010-01-01

Despite allowing for the unprecedented visualization of brain functional activity, modern neurobiological techniques have not yet been able to provide satisfactory answers to important questions about the relationship between brain and mind. The aim of this paper is to show how two different but complementary approaches, Mind Operational Semantics (OS) and Brain Operational Architectonics (OA), can help bridge the gap between a specific kind of mental activity—the higher-order reflective thought or linguistic thought—and brain. The fundamental notion that allows the two different approaches to be jointly used under a common framework is that of operation. According to OS, which is based on introspection and linguistic data, the meanings of words can be analyzed in terms of elemental mental operations (EOMC), amongst which those of attention play a key role. Linguistic thought is made possible by special kinds of elements, which OS calls “correlators”, which have the function of tying together the other elements of thought, which OS calls “correlata” (a "correlational network” that is, a sentence, is so formed). Therefore, OS conceives of linguistic thought as a hierarchy of operations of increasing complexity. Likewise, according to OA, which is based on the joint analysis of cognitive and electromagnetic data (EEG and MEG), every conscious phenomenon is brought to existence by the joint operations of many functional and transient neuronal assemblies in the brain. According to OA, the functioning of the brain is always operational (made up of operations), and its structure is characterized by a hierarchy of operations of increasing complexity: single neurons, single assemblies of neurons, synchronized neuronal assemblies or Operational Modules (OM), integrated or complex OMs. The authors put forward the hypothesis that the whole level of OS’s description (EOMC, correlators, and correlational networks) corresponds to the level of OMs (or set of them) of different complexity within OA’s theory: EOMC could correspond to simple OMs, correlators to complex OMs and the correlational network to a set of simple and complex OMs. Finally, a set of experiments is proposed to verify the putative correspondence between OS and OA and prove the existence of an integrated continuum between brain and mind. PMID:21113277

Nutritional approach for designing meat-based functional food products with nuts.

PubMed

Olmedilla-Alonso, B; Granado-Lorencio, F; Herrero-Barbudo, C; Blanco-Navarro, I

2006-01-01

Meat and meat products are essential components of diets in developed countries and despite the convincing evidence that relate them to an increased risk for CVD, a growing consumption of meat products is foreseen. Epidemiological studies show that regular consumption of nuts, in general, and walnuts in particular, correlates inversely with myocardial infarction and ischaemic vascular disease. We assess the nutritional basis for and technological approach to the development of functional meat-based products potentially relevant in cardiovascular disease (CVD) risk reduction. Using the available strategies in the meat industry (reformulation processes) and a food-based approach, we address the design and development of restructured beef steak with added walnuts, potentially functional for CVD risk reduction. Its adequacy as a vehicle for active nutrients is confirmed by a pharmacokinetic pilot study in humans using gamma-tocopherol as an exposure biomarker in chylomicrons during the post-prandial state. Effect and potential "functionality" is being assessed by a dietary intervention study in subjects at risk and markers and indicators related to CVD are being evaluated. Within the conceptual framework of evidence-based medicine, development of meat-based functional products may become a useful approach for specific applications, with a potential market and health benefits of great importance at a population level.

Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study

PubMed Central

2016-01-01

Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the experimental data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, we can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches. PMID:28005370

Predicting catalyst-support interactions between metal nanoparticles and amorphous silica supports

NASA Astrophysics Data System (ADS)

Ewing, Christopher S.; Veser, Götz; McCarthy, Joseph J.; Lambrecht, Daniel S.; Johnson, J. Karl

2016-10-01

Metal-support interactions significantly affect the stability and activity of supported catalytic nanoparticles (NPs), yet there is no simple and reliable method for estimating NP-support interactions, especially for amorphous supports. We present an approach for rapid prediction of catalyst-support interactions between Pt NPs and amorphous silica supports for NPs of various sizes and shapes. We use density functional theory calculations of 13 atom Pt clusters on model amorphous silica supports to determine linear correlations relating catalyst properties to NP-support interactions. We show that these correlations can be combined with fast discrete element method simulations to predict adhesion energy and NP net charge for NPs of larger sizes and different shapes. Furthermore, we demonstrate that this approach can be successfully transferred to Pd, Au, Ni, and Fe NPs. This approach can be used to quickly screen stability and net charge transfer and leads to a better fundamental understanding of catalyst-support interactions.

Effective theory of squeezed correlation functions

NASA Astrophysics Data System (ADS)

Mirbabayi, Mehrdad; Simonović, Marko

2016-03-01

Various inflationary scenarios can often be distinguished from one another by looking at the squeezed limit behavior of correlation functions. Therefore, it is useful to have a framework designed to study this limit in a more systematic and efficient way. We propose using an expansion in terms of weakly coupled super-horizon degrees of freedom, which is argued to generically exist in a near de Sitter space-time. The modes have a simple factorized form which leads to factorization of the squeezed-limit correlation functions with power-law behavior in klong/kshort. This approach reproduces the known results in single-, quasi-single-, and multi-field inflationary models. However, it is applicable even if, unlike the above examples, the additional degrees of freedom are not weakly coupled at sub-horizon scales. Stronger results are derived in two-field (or sufficiently symmetric multi-field) inflationary models. We discuss the observability of the non-Gaussian 3-point function in the large-scale structure surveys, and argue that the squeezed limit behavior has a higher detectability chance than equilateral behavior when it scales as (klong/kshort)Δ with Δ < 1—where local non-Gaussianity corresponds to Δ = 0.

Periodontal Ligament Entheses and their Adaptive Role in the Context of Dentoalveolar Joint Function

PubMed Central

Lin, Jeremy D.; Jang, Andrew T.; Kurylo, Michael P.; Hurng, Jonathan; Yang, Feifei; Yang, Lynn; Pal, Arvin; Chen, Ling; Ho, Sunita P.

2017-01-01

Objectives The dynamic bone-periodontal ligament (PDL)-tooth fibrous joint consists of two adaptive functionally graded interfaces (FGI), the PDL-bone and PDL-cementum that respond to mechanical strain transmitted during mastication. In general, from a materials and mechanics perspective, FGI prevent catastrophic failure during prolonged cyclic loading. This review is a discourse of results gathered from literature to illustrate the dynamic adaptive nature of the fibrous joint in response to physiologic and pathologic simulated functions, and experimental tooth movement. Methods Historically, studies have investigated soft to hard tissue transitions through analytical techniques that provided insights into structural, biochemical, and mechanical characterization methods. Experimental approaches included two dimensional to three dimensional advanced in situ imaging and analytical techniques. These techniques allowed mapping and correlation of deformations to physicochemical and mechanobiological changes within volumes of the complex subjected to concentric and eccentric loading regimes respectively. Results Tooth movement is facilitated by mechanobiological activity at the interfaces of the fibrous joint and generates elastic discontinuities at these interfaces in response to eccentric loading. Both concentric and eccentric loads mediated cellular responses to strains, and prompted self-regulating mineral forming and resorbing zones that in turn altered the functional space of the joint. Significance A multiscale biomechanics and mechanobiology approach is important for correlating joint function to tissue-level strain-adaptive properties with overall effects on joint form as related to physiologic and pathologic functions. Elucidating the shift in localization of biomolecules specifically at interfaces during development, function, and therapeutic loading of the joint is critical for developing “functional regeneration and adaptation” strategies with an emphasis on restoring physiologic joint function. PMID:28476202

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series.

PubMed

Halliday, David M; Senik, Mohd Harizal; Stevenson, Carl W; Mason, Rob

2016-08-01

The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. However, the validity of using low order AR models for neurophysiological signals has been questioned. A recent article introduced a non-parametric approach to estimate directionality in bivariate data, non-parametric approaches are free from concerns over model validity. We extend the non-parametric framework to include measures of directed conditional independence, using scalar measures that decompose the overall partial correlation coefficient summatively by direction, and a set of functions that decompose the partial coherence summatively by direction. A time domain partial correlation function allows both time and frequency views of the data to be constructed. The conditional independence estimates are conditioned on a single predictor. The framework is applied to simulated cortical neuron networks and mixtures of Gaussian time series data with known interactions. It is applied to experimental data consisting of local field potential recordings from bilateral hippocampus in anaesthetised rats. The framework offers a non-parametric approach to estimation of directed interactions in multivariate neuronal recordings, and increased flexibility in dealing with both spike train and time series data. The framework offers a novel alternative non-parametric approach to estimate directed interactions in multivariate neuronal recordings, and is applicable to spike train and time series data. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiple Measurements Regarding the Competence of the Andragogical Learner

ERIC Educational Resources Information Center

Boone, Timothy Keith

2013-01-01

Evidence suggests that many adult learners have not developed the competencies needed to fully function effectively in today's society. Questions remain, however, on the levels of influence exerted on self-direction and motivation among this population. The purpose of this correlational study using a multiple measurements assessment approach was…

Family Correlates of Adjustment Profiles in Mexican-Origin Female Adolescents

ERIC Educational Resources Information Center

Bamaca-Colbert, Mayra Y.; Gayles, Jochebed G.; Lara, Rebecca

2011-01-01

This study used a person-centered approach to examine patterns of adjustment along psychological (i.e., depression, self-esteem, anxiety) and academic (i.e., academic motivation) domains in a sample (N = 338) of Mexican-origin female adolescents. Four adjustment profiles were identified. A "High Functioning" (n = 173) group, which…

Magnitude and sign of long-range correlated time series: Decomposition and surrogate signal generation.

PubMed

Gómez-Extremera, Manuel; Carpena, Pedro; Ivanov, Plamen Ch; Bernaola-Galván, Pedro A

2016-04-01

We systematically study the scaling properties of the magnitude and sign of the fluctuations in correlated time series, which is a simple and useful approach to distinguish between systems with different dynamical properties but the same linear correlations. First, we decompose artificial long-range power-law linearly correlated time series into magnitude and sign series derived from the consecutive increments in the original series, and we study their correlation properties. We find analytical expressions for the correlation exponent of the sign series as a function of the exponent of the original series. Such expressions are necessary for modeling surrogate time series with desired scaling properties. Next, we study linear and nonlinear correlation properties of series composed as products of independent magnitude and sign series. These surrogate series can be considered as a zero-order approximation to the analysis of the coupling of magnitude and sign in real data, a problem still open in many fields. We find analytical results for the scaling behavior of the composed series as a function of the correlation exponents of the magnitude and sign series used in the composition, and we determine the ranges of magnitude and sign correlation exponents leading to either single scaling or to crossover behaviors. Finally, we obtain how the linear and nonlinear properties of the composed series depend on the correlation exponents of their magnitude and sign series. Based on this information we propose a method to generate surrogate series with controlled correlation exponent and multifractal spectrum.

Physical functioning in patients with ankylosing spondylitis: comparing approaches of experienced ability with self-reported and objectively measured physical activity.

PubMed

van Genderen, Simon; van den Borne, Carlie; Geusens, Piet; van der Linden, Sjef; Boonen, Annelies; Plasqui, Guy

2014-04-01

Physical functioning can be assessed by different approaches that are characterized by increasing levels of individual appraisal. There is insufficient insight into which approach is the most informative in patients with ankylosing spondylitis (AS) compared with control subjects. The objective of this study was to compare patients with AS and control subjects regarding 3 approaches of functioning: experienced ability to perform activities (Bath Ankylosing Spondylitis Functional Index [BASFI]), self-reported amount of physical activity (PA) (Baecke questionnaire), and the objectively measured amount of PA (triaxial accelerometer). This case-control study included 24 AS patients and 24 control subjects (matched for age, gender, and body mass index). Subjects completed the BASFI and Baecke questionnaire and wore a triaxial accelerometer. Subjects also completed other self-reported measures on disease activity (Bath AS Disease Activity Index), fatigue (Multidimensional Fatigue Inventory), and overall health (EuroQol visual analog scale). Both groups included 14 men (58%), and the mean age was 48 years. Patients scored significantly worse on the BASFI (3.9 vs 0.2) than their healthy peers, whereas PA assessed by Baecke and the accelerometer did not differ between groups. Correlations between approaches of physical functioning were low to moderate. Bath Ankylosing Spondylitis Functional Index was associated with disease activity (r = 0.49) and physical fatigue (0.73) and Baecke with physical and activity related fatigue (r = 0.54 and r = 0.54), but total PA assessed by accelerometer was not associated with any of these experience-based health outcomes. Different approaches of the concept physical functioning in patients with AS provide different information. Compared with matched control subjects, patients with AS report more difficulties but report and objectively perform the same amount of PA.

Disrupted brain network functional dynamics and hyper-correlation of structural and functional connectome topology in patients with breast cancer prior to treatment.

PubMed

Kesler, Shelli R; Adams, Marjorie; Packer, Melissa; Rao, Vikram; Henneghan, Ashley M; Blayney, Douglas W; Palesh, Oxana

2017-03-01

Several previous studies have demonstrated that cancer chemotherapy is associated with brain injury and cognitive dysfunction. However, evidence suggests that cancer pathogenesis alone may play a role, even in non-CNS cancers. Using a multimodal neuroimaging approach, we measured structural and functional connectome topology as well as functional network dynamics in newly diagnosed patients with breast cancer. Our study involved a novel, pretreatment assessment that occurred prior to the initiation of any cancer therapies, including surgery with anesthesia. We enrolled 74 patients with breast cancer age 29-65 and 50 frequency-matched healthy female controls who underwent anatomic and resting-state functional MRI as well as cognitive testing. Compared to controls, patients with breast cancer demonstrated significantly lower functional network dynamics ( p  = .046) and cognitive functioning ( p  < .02, corrected). The breast cancer group also showed subtle alterations in structural local clustering and functional local clustering ( p  < .05, uncorrected) as well as significantly increased correlation between structural global clustering and functional global clustering compared to controls ( p  = .03). This hyper-correlation between structural and functional topologies was significantly associated with cognitive dysfunction ( p  = .005). Our findings could not be accounted for by psychological distress and suggest that non-CNS cancer may directly and/or indirectly affect the brain via mechanisms such as tumor-induced neurogenesis, inflammation, and/or vascular changes, for example. Our results also have broader implications concerning the importance of the balance between structural and functional connectome properties as a potential biomarker of general neurologic deficit.

Functional connectivity change as shared signal dynamics

PubMed Central

Cole, Michael W.; Yang, Genevieve J.; Murray, John D.; Repovš, Grega; Anticevic, Alan

2015-01-01

Background An increasing number of neuroscientific studies gain insights by focusing on differences in functional connectivity – between groups, individuals, temporal windows, or task conditions. We found using simulations that additional insights into such differences can be gained by forgoing variance normalization, a procedure used by most functional connectivity measures. Simulations indicated that these functional connectivity measures are sensitive to increases in independent fluctuations (unshared signal) in time series, consistently reducing functional connectivity estimates (e.g., correlations) even though such changes are unrelated to corresponding fluctuations (shared signal) between those time series. This is inconsistent with the common notion of functional connectivity as the amount of inter-region interaction. New Method Simulations revealed that a version of correlation without variance normalization – covariance – was able to isolate differences in shared signal, increasing interpretability of observed functional connectivity change. Simulations also revealed cases problematic for non-normalized methods, leading to a “covariance conjunction” method combining the benefits of both normalized and non-normalized approaches. Results We found that covariance and covariance conjunction methods can detect functional connectivity changes across a variety of tasks and rest in both clinical and non-clinical functional MRI datasets. Comparison with Existing Method(s) We verified using a variety of tasks and rest in both clinical and non-clinical functional MRI datasets that it matters in practice whether correlation, covariance, or covariance conjunction methods are used. Conclusions These results demonstrate the practical and theoretical utility of isolating changes in shared signal, improving the ability to interpret observed functional connectivity change. PMID:26642966

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

Accurate density functional prediction of molecular electron affinity with the scaling corrected Kohn–Sham frontier orbital energies

NASA Astrophysics Data System (ADS)

Zhang, DaDi; Yang, Xiaolong; Zheng, Xiao; Yang, Weitao

2018-04-01

Electron affinity (EA) is the energy released when an additional electron is attached to an atom or a molecule. EA is a fundamental thermochemical property, and it is closely pertinent to other important properties such as electronegativity and hardness. However, accurate prediction of EA is difficult with density functional theory methods. The somewhat large error of the calculated EAs originates mainly from the intrinsic delocalisation error associated with the approximate exchange-correlation functional. In this work, we employ a previously developed non-empirical global scaling correction approach, which explicitly imposes the Perdew-Parr-Levy-Balduz condition to the approximate functional, and achieve a substantially improved accuracy for the calculated EAs. In our approach, the EA is given by the scaling corrected Kohn-Sham lowest unoccupied molecular orbital energy of the neutral molecule, without the need to carry out the self-consistent-field calculation for the anion.

Functional consortium for denitrifying sulfide removal process.

PubMed

Chen, Chuan; Ren, Nanqi; Wang, Aijie; Liu, Lihong; Lee, Duu-Jong

2010-03-01

Denitrifying sulfide removal (DSR) process simultaneously converts sulfide, nitrate, and chemical oxygen demand from industrial wastewaters to elemental sulfur, nitrogen gas, and carbon dioxide, respectively. This investigation utilizes a dilution-to-extinction approach at 10(-2) to 10(-6) dilutions to elucidate the correlation between the composition of the microbial community and the DSR performance. In the original suspension and in 10(-2) dilution, the strains Stenotrophomonas sp., Thauera sp., and Azoarcus sp. are the heterotrophic denitrifiers and the strains Paracoccus sp. and Pseudomonas sp. are the sulfide-oxidizing denitrifers. The 10(-4) dilution is identified as the functional consortium for the present DSR system, which comprises two functional strains, Stenotrophomonas sp. strain Paracoccus sp. At 10(-6) dilution, all DSR performance was lost. The functions of the constituent cells in the DSR granules were discussed based on data obtained using the dilution-to-extinction approach.

Extension of the KLI approximation toward the exact optimized effective potential.

PubMed

Iafrate, G J; Krieger, J B

2013-03-07

The integral equation for the optimized effective potential (OEP) is utilized in a compact form from which an accurate OEP solution for the spin-unrestricted exchange-correlation potential, Vxcσ, is obtained for any assumed orbital-dependent exchange-correlation energy functional. The method extends beyond the Krieger-Li-Iafrate (KLI) approximation toward the exact OEP result. The compact nature of the OEP equation arises by replacing the integrals involving the Green's function terms in the traditional OEP equation by an equivalent first-order perturbation theory wavefunction often referred to as the "orbital shift" function. Significant progress is then obtained by solving the equation for the first order perturbation theory wavefunction by use of Dalgarno functions which are determined from well known methods of partial differential equations. The use of Dalgarno functions circumvents the need to explicitly address the Green's functions and the associated problems with "sum over states" numerics; as well, the Dalgarno functions provide ease in dealing with inherent singularities arising from the origin and the zeros of the occupied orbital wavefunctions. The Dalgarno approach for finding a solution to the OEP equation is described herein, and a detailed illustrative example is presented for the special case of a spherically symmetric exchange-correlation potential. For the case of spherical symmetry, the relevant Dalgarno function is derived by direct integration of the appropriate radial equation while utilizing a user friendly method which explicitly treats the singular behavior at the origin and at the nodal singularities arising from the zeros of the occupied states. The derived Dalgarno function is shown to be an explicit integral functional of the exact OEP Vxcσ, thus allowing for the reduction of the OEP equation to a self-consistent integral equation for the exact exchange-correlation potential; the exact solution to this integral equation can be determined by iteration with the natural zeroth order correction given by the KLI exchange-correlation potential. Explicit analytic results are provided to illustrate the first order iterative correction beyond the KLI approximation. The derived correction term to the KLI potential explicitly involves spatially weighted products of occupied orbital densities in any assumed orbital-dependent exchange-correlation energy functional; as well, the correction term is obtained with no adjustable parameters. Moreover, if the equation for the exact optimized effective potential is further iterated, one can obtain the OEP as accurately as desired.

Extension of the KLI approximation toward the exact optimized effective potential

NASA Astrophysics Data System (ADS)

Iafrate, G. J.; Krieger, J. B.

2013-03-01

The integral equation for the optimized effective potential (OEP) is utilized in a compact form from which an accurate OEP solution for the spin-unrestricted exchange-correlation potential, Vxcσ, is obtained for any assumed orbital-dependent exchange-correlation energy functional. The method extends beyond the Krieger-Li-Iafrate (KLI) approximation toward the exact OEP result. The compact nature of the OEP equation arises by replacing the integrals involving the Green's function terms in the traditional OEP equation by an equivalent first-order perturbation theory wavefunction often referred to as the "orbital shift" function. Significant progress is then obtained by solving the equation for the first order perturbation theory wavefunction by use of Dalgarno functions which are determined from well known methods of partial differential equations. The use of Dalgarno functions circumvents the need to explicitly address the Green's functions and the associated problems with "sum over states" numerics; as well, the Dalgarno functions provide ease in dealing with inherent singularities arising from the origin and the zeros of the occupied orbital wavefunctions. The Dalgarno approach for finding a solution to the OEP equation is described herein, and a detailed illustrative example is presented for the special case of a spherically symmetric exchange-correlation potential. For the case of spherical symmetry, the relevant Dalgarno function is derived by direct integration of the appropriate radial equation while utilizing a user friendly method which explicitly treats the singular behavior at the origin and at the nodal singularities arising from the zeros of the occupied states. The derived Dalgarno function is shown to be an explicit integral functional of the exact OEP Vxcσ, thus allowing for the reduction of the OEP equation to a self-consistent integral equation for the exact exchange-correlation potential; the exact solution to this integral equation can be determined by iteration with the natural zeroth order correction given by the KLI exchange-correlation potential. Explicit analytic results are provided to illustrate the first order iterative correction beyond the KLI approximation. The derived correction term to the KLI potential explicitly involves spatially weighted products of occupied orbital densities in any assumed orbital-dependent exchange-correlation energy functional; as well, the correction term is obtained with no adjustable parameters. Moreover, if the equation for the exact optimized effective potential is further iterated, one can obtain the OEP as accurately as desired.

ADHD classification using bag of words approach on network features

NASA Astrophysics Data System (ADS)

Solmaz, Berkan; Dey, Soumyabrata; Rao, A. Ravishankar; Shah, Mubarak

2012-02-01

Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.

Automated, quantitative measures of grey and white matter lesion burden correlates with motor and cognitive function in children with unilateral cerebral palsy.

PubMed

Pagnozzi, Alex M; Dowson, Nicholas; Doecke, James; Fiori, Simona; Bradley, Andrew P; Boyd, Roslyn N; Rose, Stephen

2016-01-01

White and grey matter lesions are the most prevalent type of injury observable in the Magnetic Resonance Images (MRIs) of children with cerebral palsy (CP). Previous studies investigating the impact of lesions in children with CP have been qualitative, limited by the lack of automated segmentation approaches in this setting. As a result, the quantitative relationship between lesion burden has yet to be established. In this study, we perform automatic lesion segmentation on a large cohort of data (107 children with unilateral CP and 18 healthy children) with a new, validated method for segmenting both white matter (WM) and grey matter (GM) lesions. The method has better accuracy (94%) than the best current methods (73%), and only requires standard structural MRI sequences. Anatomical lesion burdens most predictive of clinical scores of motor, cognitive, visual and communicative function were identified using the Least Absolute Shrinkage and Selection operator (LASSO). The improved segmentations enabled identification of significant correlations between regional lesion burden and clinical performance, which conform to known structure-function relationships. Model performance was validated in an independent test set, with significant correlations observed for both WM and GM regional lesion burden with motor function (p < 0.008), and between WM and GM lesions alone with cognitive and visual function respectively (p < 0.008). The significant correlation of GM lesions with functional outcome highlights the serious implications GM lesions, in addition to WM lesions, have for prognosis, and the utility of structural MRI alone for quantifying lesion burden and planning therapy interventions.

Constraints on the nuclear equation of state from nuclear masses and radii in a Thomas-Fermi meta-modeling approach

NASA Astrophysics Data System (ADS)

Chatterjee, D.; Gulminelli, F.; Raduta, Ad. R.; Margueron, J.

2017-12-01

The question of correlations among empirical equation of state (EoS) parameters constrained by nuclear observables is addressed in a Thomas-Fermi meta-modeling approach. A recently proposed meta-modeling for the nuclear EoS in nuclear matter is augmented with a single finite size term to produce a minimal unified EoS functional able to describe the smooth part of the nuclear ground state properties. This meta-model can reproduce the predictions of a large variety of models, and interpolate continuously between them. An analytical approximation to the full Thomas-Fermi integrals is further proposed giving a fully analytical meta-model for nuclear masses. The parameter space is sampled and filtered through the constraint of nuclear mass reproduction with Bayesian statistical tools. We show that this simple analytical meta-modeling has a predictive power on masses, radii, and skins comparable to full Hartree-Fock or extended Thomas-Fermi calculations with realistic energy functionals. The covariance analysis on the posterior distribution shows that no physical correlation is present between the different EoS parameters. Concerning nuclear observables, a strong correlation between the slope of the symmetry energy and the neutron skin is observed, in agreement with previous studies.

On the examination of Darcy permeability of soft fibrous porous media; New correlations

NASA Astrophysics Data System (ADS)

Zhu, Zenghao; Wang, Qiuyun; Wu, Qianhong

2017-11-01

In this presentation, we report a novel experimental approach to investigate the compression-dependent Darcy permeability of soft porous media. Especially, we are proposing new correlations that describe the change of the permeability of random fibrous porous media as a function of its compression. A special device was developed that consisted of a rectangular flow channel with adjustable gap thickness ranging from 3 mm to 20 mm. Air was forced through the thin gap filled with testing fibrous materials. By measuring the flow rate and the pressure gradient, we have successfully obtained the Darcy permeability of different fibrous porous materials at different compression ratios. Theoretical or semi-empirical models have been compared with the experimental results, indicating various degrees of disagreement. The new correlations were then proposed which fit with experimental data very well. The study presented herein provides a useful approach to evaluate the change of the permeability of fibrous porous media as a function of its compression. It will be valuable for examining fluid flow in fibrous porous media where the permeability is difficult to be measured directly. This kind of porous media widely exists in biological systems. This research was supported by the National Science Foundation under Award No. 1511096.

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

Accounting for binaural detection as a function of masker interaural correlation: effects of center frequency and bandwidth.

PubMed

Bernstein, Leslie R; Trahiotis, Constantine

2014-12-01

Binaural detection was measured as a function of the center frequency, bandwidth, and interaural correlation of masking noise. Thresholds were obtained for 500-Hz or 125-Hz Sπ tonal signals and for the latter stimuli (noise or signal-plus-noise) transposed to 4 kHz. A primary goal was assessment of the generality of van der Heijden and Trahiotis' [J. Acoust. Soc. Am. 101, 1019-1022 (1997)] hypothesis that thresholds could be accounted for by the "additive" masking effects of the underlying No and Nπ components of a masker having an interaural correlation of ρ. Results indicated that (1) the overall patterning of the data depended neither upon center frequency nor whether information was conveyed via the waveform or by its envelope; (2) thresholds for transposed stimuli improved relative to their low-frequency counterparts as bandwidth of the masker was increased; (3) the additivity approach accounted well for the data across stimulus conditions but consistently overestimated MLDs, especially for narrowband maskers; (4) a quantitative approach explicitly taking into account the distributions of time-varying ITD-based lateral positions produced by masker-alone and signal-plus-masker waveforms proved more successful, albeit while employing a larger set of assumptions, parameters, and computational complexity.

Random field assessment of nanoscopic inhomogeneity of bone

PubMed Central

Dong, X. Neil; Luo, Qing; Sparkman, Daniel M.; Millwater, Harry R.; Wang, Xiaodu

2010-01-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to present the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. PMID:20817128

Understanding the determinants of volatility clustering in terms of stationary Markovian processes

NASA Astrophysics Data System (ADS)

Miccichè, S.

2016-11-01

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ-β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock's volatility is a linear function of the average correlation of such stock's volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still keep some of the original volatility stylized facts. As a result, the diagonalized volatilities result to share with the original volatilities either the power-law decay of the probability density function and the power-law decay of the autocorrelation function. This would indicate that volatility clustering is already present in the diagonalized un-correlated volatilities. We therefore present a parsimonious univariate model based on a non-linear Langevin equation that well reproduces these two stylized facts of volatility. The model helps us in understanding that the main source of volatility clustering, once volatilities have been diagonalized, is that the economic forces driving volatility can be modeled in terms of a Smoluchowski potential with logarithmic tails.

Jet-Track Correlation Studies in PbPb and pp at 5.02 TeV

NASA Astrophysics Data System (ADS)

Trauger, Hallie Causey; CMS Collaboration

2017-11-01

Jet-track correlations are used to extend measurements of the properties of jets beyond classic fixed-R jet reconstruction. New measurements with PbPb and pp collision data at √{sNN} = 5.02 TeV, recorded by CMS, are carried out using a statistical approach that allows for a reliable subtraction of the underlying event beyond the typical distance parameters of jet reconstruction. Measurements of correlated particle densities are extended out to ±1.5 units of relative azimuth and pseudorapidity. Double-differential measurements of jet fragmentation functions and jet shapes are presented up to radial distance of R=1 from the jet axis.

The Data Box and Within-Subject Analyses: A Comment on Nesselroade and Molenaar (2016).

PubMed

Revelle, William; Wilt, Joshua

2016-01-01

Nesselroade and Molenaar suggest that it is the relationships between latent variables within subjects that are invariant across subjects and thus the appropriate unit of analysis. We disagree and take the view that between-factor correlations may differ systematically across subjects. Further, individual differences in these correlations may be an important source of information about each unique individual. Following from this premise, analyses of consistencies and differences between subjects of the within-subject pattern of interfactor correlations is a step toward an integrative science of behavior. We give several examples demonstrating how this approach has the potential to yield novel insights into personality functioning.

Heterogeneous dynamics of ionic liquids: A four-point time correlation function approach

NASA Astrophysics Data System (ADS)

Liu, Jiannan; Willcox, Jon A. L.; Kim, Hyung J.

2018-05-01

Many ionic liquids show behavior similar to that of glassy systems, e.g., large and long-lasted deviations from Gaussian dynamics and clustering of "mobile" and "immobile" groups of ions. Herein a time-dependent four-point density correlation function—typically used to characterize glassy systems—is implemented for the ionic liquids, choline acetate, and 1-butyl-3-methylimidazolium acetate. Dynamic correlation beyond the first ionic solvation shell on the time scale of nanoseconds is found in the ionic liquids, revealing the cooperative nature of ion motions. The traditional solvent, acetonitrile, on the other hand, shows a much shorter length-scale that decays after a few picoseconds.

Two-body Schrödinger wave functions in a plane-wave basis via separation of dimensions

NASA Astrophysics Data System (ADS)

Jerke, Jonathan; Poirier, Bill

2018-03-01

Using a combination of ideas, the ground and several excited electronic states of the helium atom and the hydrogen molecule are computed to chemical accuracy—i.e., to within 1-2 mhartree or better. The basic strategy is very different from the standard electronic structure approach in that the full two-electron six-dimensional (6D) problem is tackled directly, rather than starting from a single-electron Hartree-Fock approximation. Electron correlation is thus treated exactly, even though computational requirements remain modest. The method also allows for exact wave functions to be computed, as well as energy levels. From the full-dimensional 6D wave functions computed here, radial distribution functions and radial correlation functions are extracted—as well as a 2D probability density function exhibiting antisymmetry for a single Cartesian component. These calculations support a more recent interpretation of Hund's rule, which states that the lower energy of the higher spin-multiplicity states is actually due to reduced screening, rather than reduced electron-electron repulsion. Prospects for larger systems and/or electron dynamics applications appear promising.

Two-body Schrödinger wave functions in a plane-wave basis via separation of dimensions.

PubMed

Jerke, Jonathan; Poirier, Bill

2018-03-14

Using a combination of ideas, the ground and several excited electronic states of the helium atom and the hydrogen molecule are computed to chemical accuracy-i.e., to within 1-2 mhartree or better. The basic strategy is very different from the standard electronic structure approach in that the full two-electron six-dimensional (6D) problem is tackled directly, rather than starting from a single-electron Hartree-Fock approximation. Electron correlation is thus treated exactly, even though computational requirements remain modest. The method also allows for exact wave functions to be computed, as well as energy levels. From the full-dimensional 6D wave functions computed here, radial distribution functions and radial correlation functions are extracted-as well as a 2D probability density function exhibiting antisymmetry for a single Cartesian component. These calculations support a more recent interpretation of Hund's rule, which states that the lower energy of the higher spin-multiplicity states is actually due to reduced screening, rather than reduced electron-electron repulsion. Prospects for larger systems and/or electron dynamics applications appear promising.

The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.

PubMed

Calhoun, Vince D; Miller, Robyn; Pearlson, Godfrey; Adalı, Tulay

2014-10-22

Recent years have witnessed a rapid growth of interest in moving functional magnetic resonance imaging (fMRI) beyond simple scan-length averages and into approaches that capture time-varying properties of connectivity. In this Perspective we use the term "chronnectome" to describe metrics that allow a dynamic view of coupling. In the chronnectome, coupling refers to possibly time-varying levels of correlated or mutually informed activity between brain regions whose spatial properties may also be temporally evolving. We primarily focus on multivariate approaches developed in our group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component analysis. We also discuss the potential these approaches offer to improve characterization and understanding of brain function. There are a number of methodological directions that need to be developed further, but chronnectome approaches already show great promise for the study of both the healthy and the diseased brain.

Linking plant and ecosystem functional biogeography.

PubMed

Reichstein, Markus; Bahn, Michael; Mahecha, Miguel D; Kattge, Jens; Baldocchi, Dennis D

2014-09-23

Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere-atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.

Linking plant and ecosystem functional biogeography

PubMed Central

Reichstein, Markus; Bahn, Michael; Mahecha, Miguel D.; Kattge, Jens; Baldocchi, Dennis D.

2014-01-01

Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere–atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches. PMID:25225392

Coulomb branch operators and mirror symmetry in three dimensions

NASA Astrophysics Data System (ADS)

Dedushenko, Mykola; Fan, Yale; Pufu, Silviu S.; Yacoby, Ran

2018-04-01

We develop new techniques for computing exact correlation functions of a class of local operators, including certain monopole operators, in three-dimensional N=4 abelian gauge theories that have superconformal infrared limits. These operators are position-dependent linear combinations of Coulomb branch operators. They form a one-dimensional topological sector that encodes a deformation quantization of the Coulomb branch chiral ring, and their correlation functions completely fix the ( n ≤ 3)-point functions of all half-BPS Coulomb branch operators. Using these results, we provide new derivations of the conformal dimension of half-BPS monopole operators as well as new and detailed tests of mirror symmetry. Our main approach involves supersymmetric localization on a hemisphere HS 3 with half-BPS boundary conditions, where operator insertions within the hemisphere are represented by certain shift operators acting on the HS 3 wavefunction. By gluing a pair of such wavefunctions, we obtain correlators on S 3 with an arbitrary number of operator insertions. Finally, we show that our results can be recovered by dimensionally reducing the Schur index of 4D N=2 theories decorated by BPS 't Hooft-Wilson loops.

Normalization methods in time series of platelet function assays

PubMed Central

Van Poucke, Sven; Zhang, Zhongheng; Roest, Mark; Vukicevic, Milan; Beran, Maud; Lauwereins, Bart; Zheng, Ming-Hua; Henskens, Yvonne; Lancé, Marcus; Marcus, Abraham

2016-01-01

Abstract Platelet function can be quantitatively assessed by specific assays such as light-transmission aggregometry, multiple-electrode aggregometry measuring the response to adenosine diphosphate (ADP), arachidonic acid, collagen, and thrombin-receptor activating peptide and viscoelastic tests such as rotational thromboelastometry (ROTEM). The task of extracting meaningful statistical and clinical information from high-dimensional data spaces in temporal multivariate clinical data represented in multivariate time series is complex. Building insightful visualizations for multivariate time series demands adequate usage of normalization techniques. In this article, various methods for data normalization (z-transformation, range transformation, proportion transformation, and interquartile range) are presented and visualized discussing the most suited approach for platelet function data series. Normalization was calculated per assay (test) for all time points and per time point for all tests. Interquartile range, range transformation, and z-transformation demonstrated the correlation as calculated by the Spearman correlation test, when normalized per assay (test) for all time points. When normalizing per time point for all tests, no correlation could be abstracted from the charts as was the case when using all data as 1 dataset for normalization. PMID:27428217

Producing data-based sensitivity kernels from convolution and correlation in exploration geophysics.

NASA Astrophysics Data System (ADS)

Chmiel, M. J.; Roux, P.; Herrmann, P.; Rondeleux, B.

2016-12-01

Many studies have shown that seismic interferometry can be used to estimate surface wave arrivals by correlation of seismic signals recorded at a pair of locations. In the case of ambient noise sources, the convergence towards the surface wave Green's functions is obtained with the criterion of equipartitioned energy. However, seismic acquisition with active, controlled sources gives more possibilities when it comes to interferometry. The use of controlled sources makes it possible to recover the surface wave Green's function between two points using either correlation or convolution. We investigate the convolutional and correlational approaches using land active-seismic data from exploration geophysics. The data were recorded on 10,710 vertical receivers using 51,808 sources (seismic vibrator trucks). The sources spacing is the same in both X and Y directions (30 m) which is known as a "carpet shooting". The receivers are placed in parallel lines with a spacing 150 m in the X direction and 30 m in the Y direction. Invoking spatial reciprocity between sources and receivers, correlation and convolution functions can thus be constructed between either pairs of receivers or pairs of sources. Benefiting from the dense acquisition, we extract sensitivity kernels from correlation and convolution measurements of the seismic data. These sensitivity kernels are subsequently used to produce phase-velocity dispersion curves between two points and to separate the higher mode from the fundamental mode for surface waves. Potential application to surface wave cancellation is also envisaged.

[Comparative anatomy of the mandible. Functional aspects].

PubMed

Denoix, J M

1983-12-01

The structural morphology of the mandibula is presented and correlated to various types of mastication in several Mammalian species. The latter include: Carnivores (Dog, Cat, Cheetah, Lion); Omnivores (Man, Chimpanzee, Hog); Herbivores (Horse, Ox, Goat, Camel, Rabbit). While the mandibula is studied as a composite unit, a more analytical, segmental approach has been included, and both are illustrated by X-rays. The aspects presented underline the distribution as well as the local modifications of compact bone, and in addition, the arrangement and the development of spongy bone trabeculae. A preliminary classification with respect to structural elements has been suggested from two viewpoints: that of tension, the other of compression. Are also presented those variations linked to diet and alimentary intake, as well as their functional correlates.

Matrix elements of N-particle explicitly correlated Gaussian basis functions with complex exponential parameters

NASA Astrophysics Data System (ADS)

Bubin, Sergiy; Adamowicz, Ludwik

2006-06-01

In this work we present analytical expressions for Hamiltonian matrix elements with spherically symmetric, explicitly correlated Gaussian basis functions with complex exponential parameters for an arbitrary number of particles. The expressions are derived using the formalism of matrix differential calculus. In addition, we present expressions for the energy gradient that includes derivatives of the Hamiltonian integrals with respect to the exponential parameters. The gradient is used in the variational optimization of the parameters. All the expressions are presented in the matrix form suitable for both numerical implementation and theoretical analysis. The energy and gradient formulas have been programed and used to calculate ground and excited states of the He atom using an approach that does not involve the Born-Oppenheimer approximation.

Matrix elements of N-particle explicitly correlated Gaussian basis functions with complex exponential parameters.

PubMed

Bubin, Sergiy; Adamowicz, Ludwik

2006-06-14

In this work we present analytical expressions for Hamiltonian matrix elements with spherically symmetric, explicitly correlated Gaussian basis functions with complex exponential parameters for an arbitrary number of particles. The expressions are derived using the formalism of matrix differential calculus. In addition, we present expressions for the energy gradient that includes derivatives of the Hamiltonian integrals with respect to the exponential parameters. The gradient is used in the variational optimization of the parameters. All the expressions are presented in the matrix form suitable for both numerical implementation and theoretical analysis. The energy and gradient formulas have been programmed and used to calculate ground and excited states of the He atom using an approach that does not involve the Born-Oppenheimer approximation.

Water adsorption on a copper formate paddlewheel model of CuBTC: A comparative MP2 and DFT study

NASA Astrophysics Data System (ADS)

Toda, Jordi; Fischer, Michael; Jorge, Miguel; Gomes, José R. B.

2013-11-01

Simultaneous adsorption of two water molecules on open metal sites of the HKUST-1 metal-organic framework (MOF), modeled with a Cu2(HCOO)4 cluster, was studied by means of density functional theory (DFT) and second-order Moller-Plesset (MP2) approaches together with correlation consistent basis sets. Experimental geometries and MP2 energetic data extrapolated to the complete basis set limit were used as benchmarks for testing the accuracy of several different exchange-correlation functionals in the correct description of the water-MOF interaction. M06-L and some LC-DFT methods arise as the most appropriate in terms of the quality of geometrical data, energetic data and computational resources needed.

Scalable Methods for Electronic Excitations and Optical Responses of Nanostructures: Mathematics to Algorithms to Observables

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

Carter, Emily A

2013-02-02

Kohn-Sham density functional theory (DFT) is a powerful, well-established tool for the study of condensed phase electronic structure. However, there are still a number of situations where its applicability is limited. The basic theme of our research is the development of first principles electronic structure approaches for condensed matter that goes beyond what can currently be done with standard implementations ofKohn-Sham DFT. Our efforts to this end have focused on two classes or' methods. The first addresses the well-lmown inability of DFT to handle strong, many-body electron correlation effects. Our approach is a DFT -based embedding theory, to treat localizedmore » features (e.g. impurity, adsorbate, vacancy, etc.) embedded in a periodic, metallic crystal. A description for the embedded region is provided by explicitly correlated, ab initio wave function methods. DFT, as a fo1n1ally ground state theory, does not give a good description of excited states; an additional feature of our approach is the ability to obtain excitations localized in this region. We apply our method to a first-principles study of the adsorption of a single magnetic Co ada tom on non-magnetic Cu( 111 ), a known Kondo system whose behavior is governed by strong electron correlation. The second class of methods that we are developing is an orbital-free density functional theory (OFDFT), which addresses the speed limitations ofKohn-Sham DFT. OFDFT is a powerful, O(N) scaling method for electronic structure calculations. Unlike Kohn-Sham DFT, OFDFT goes back to the original Hohenberg-Kohn idea of directly optimizing an energy functional which is an explicit functional of the density, without invoking an orbital description. This eliminates the need to manipulate orbitals, which leads to O(N{sup 3}) scaling in the Kahn-Sham approach. The speed of OFDFT allows direct electronic structure calculations on large systems on the order of thousands to tens of thousands of atoms, an expensive feat within Kohn-Sham. Due to our incomplete knowledge of the exact, universal energy density functional, this speedup comes at the cost of some accuracy with respect to Kohn-Sham methods. However, OFDFT has been shown to be remarkably accurate with respect to Kohn-Sham when used in the study of nearly-free-electron-like metals, e.g., AI, for which good density functionals have been derived. Examples of past applications of OFDFT include the prediction of properties of bulk crystals, surfaces, vacancies, vacancy clusters, nanoclusters, and dislocations, as well as OFDFT -based multiscale simulations of nanoindentation in AI and Al-Mg alloys.« less

Signals of strong electronic correlation in ion scattering processes

NASA Astrophysics Data System (ADS)

Bonetto, F.; Gonzalez, C.; Goldberg, E. C.

2016-05-01

Previous measurements of neutral atom fractions for S r+ scattered by gold polycrystalline surfaces show a singular dependence with the target temperature. There is still not a theoretical model that can properly describe the magnitude and the temperature dependence of the neutralization probabilities found. Here, we applied a first-principles quantum-mechanical theoretical formalism to describe the time-dependent scattering process. Three different electronic correlation approaches consistent with the system analyzed are used: (i) the spinless approach, where two charge channels are considered (S r0 and S r+ ) and the spin degeneration is neglected; (ii) the infinite-U approach, with the same charge channels (S r0 and S r+ ) but considering the spin degeneration; and (iii) the finite-U approach, where the first ionization and second ionization energy levels are considered very, but finitely, separated. Neutral fraction magnitudes and temperature dependence are better described by the finite-U approach, indicating that e -correlation plays a significant role in charge-transfer processes. However, none of them is able to explain the nonmonotonous temperature dependence experimentally obtained. Here, we suggest that small changes in the surface work function introduced by the target heating, and possibly not detected by experimental standard methods, could be responsible for that singular behavior. Additionally, we apply the same theoretical model using the infinite-U approximation for the Mg-Au system, obtaining an excellent description of the experimental neutral fractions measured.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

Ecosystem Services in Conservation Planning: Targeted Benefits vs. Co-Benefits or Costs?

PubMed Central

Chan, Kai M. A.; Hoshizaki, Lara; Klinkenberg, Brian

2011-01-01

There is growing support for characterizing ecosystem services in order to link conservation and human well-being. However, few studies have explicitly included ecosystem services within systematic conservation planning, and those that have follow two fundamentally different approaches: ecosystem services as intrinsically-important targeted benefits vs. substitutable co-benefits. We present a first comparison of these two approaches in a case study in the Central Interior of British Columbia. We calculated and mapped economic values for carbon storage, timber production, and recreational angling using a geographical information system (GIS). These ‘marginal’ values represent the difference in service-provision between conservation and managed forestry as land uses. We compared two approaches to including ecosystem services in the site-selection software Marxan: as Targeted Benefits, and as Co-Benefits/Costs (in Marxan's cost function); we also compared these approaches with a Hybrid approach (carbon and angling as targeted benefits, timber as an opportunity cost). For this analysis, the Co-Benefit/Cost approach yielded a less costly reserve network than the Hybrid approach (1.6% cheaper). Including timber harvest as an opportunity cost in the cost function resulted in a reserve network that achieved targets equivalently, but at 15% lower total cost. We found counter-intuitive results for conservation: conservation-compatible services (carbon, angling) were positively correlated with each other and biodiversity, whereas the conservation-incompatible service (timber) was negatively correlated with all other networks. Our findings suggest that including ecosystem services within a conservation plan may be most cost-effective when they are represented as substitutable co-benefits/costs, rather than as targeted benefits. By explicitly valuing the costs and benefits associated with services, we may be able to achieve meaningful biodiversity conservation at lower cost and with greater co-benefits. PMID:21915318

Role of theory of mind and executive function in explaining social intelligence: a structural equation modeling approach.

PubMed

Yeh, Zai-Ting

2013-01-01

Social intelligence is the ability to understand others and the social context effectively and thus to interact with people successfully. Research has suggested that the theory of mind (ToM) and executive function may play important roles in explaining social intelligence. The specific aim of the present study was to test with structural equation modeling (SEM) the hypothesis that performance on ToM tasks is more associated with social intelligence in the elderly than is performance on executive functions. One hundred and seventy-seven participants (age 56-96) completed ToM, executive function, and other basic cognition tasks, and were rated with social intelligence scales. The SEM results showed that ToM and executive function were strongly correlated (0.54); however, only the path coefficient from ToM to social intelligence, and not from executive function, was significant (0.37). ToM performance, but not executive function, was strongly correlated with social intelligence among elderly individuals. ToM and executive function might play different roles in social behavior during normal aging; however, based on the present results, it is possible that ToM might play an important role in social intelligence.

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

[The contribution made by neurophysiological and ultrasound imaging studies to the diagnosis of carpal tunnel syndrome. Surgical correlation].

PubMed

de Pablos, C; Velasco-Zarzosa, M; Landeras-Alvaro, R; Rubio-Lorenzo, M; Martínez-Zubieta, P

Electrophysiological study has been for long time the elected approach for the diagnosis and clinical evaluation of carpal tunnel syndrome (CTS). More recently, echography and other imaging techniques have been introduced in current medicine for their potential in the anatomical evaluation of the neural compression. To asses the usefulness of both diagnostic procedures we have compared the findings obtained by electrophysiological and echographic approaches in a group of 60 CTS patients with different degrees of the disease. In all patients the conduction velocity was evaluated in the median and cubital nerves using surface electrodes. For echography lineal transductors of 5-10 Hz and 5-12.5 MHz were employed. The patients were distributed for each test on a scale depending of the severity of the alterations detected by the corresponding technique and both files were subsequently compared by regression analysis, Pearson test and paired-test. No correlation was detected in any of the statistical test. The lack of correlation between the results of both proofs emphasizes the usefulness of the two diagnostic approaches in CTS. While electrophysiological study provides information about nerve function, ecography unravels the morphological alterations accounting for the syndrome, therefore being non-excluding complementary approaches.

A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components.

PubMed

Ackerly, D D; Cornwell, W K

2007-02-01

Plant functional traits vary both along environmental gradients and among species occupying similar conditions, creating a challenge for the synthesis of functional and community ecology. We present a trait-based approach that provides an additive decomposition of species' trait values into alpha and beta components: beta values refer to a species' position along a gradient defined by community-level mean trait values; alpha values are the difference between a species' trait values and the mean of co-occurring taxa. In woody plant communities of coastal California, beta trait values for specific leaf area, leaf size, wood density and maximum height all covary strongly, reflecting species distributions across a gradient of soil moisture availability. Alpha values, on the other hand, are generally not significantly correlated, suggesting several independent axes of differentiation within communities. This trait-based framework provides a novel approach to integrate functional ecology and gradient analysis with community ecology and coexistence theory.

Modeling Fractal Structure of City-Size Distributions Using Correlation Functions

PubMed Central

Chen, Yanguang

2011-01-01

Zipf's law is one the most conspicuous empirical facts for cities, however, there is no convincing explanation for the scaling relation between rank and size and its scaling exponent. Using the idea from general fractals and scaling, I propose a dual competition hypothesis of city development to explain the value intervals and the special value, 1, of the power exponent. Zipf's law and Pareto's law can be mathematically transformed into one another, but represent different processes of urban evolution, respectively. Based on the Pareto distribution, a frequency correlation function can be constructed. By scaling analysis and multifractals spectrum, the parameter interval of Pareto exponent is derived as (0.5, 1]; Based on the Zipf distribution, a size correlation function can be built, and it is opposite to the first one. By the second correlation function and multifractals notion, the Pareto exponent interval is derived as [1, 2). Thus the process of urban evolution falls into two effects: one is the Pareto effect indicating city number increase (external complexity), and the other the Zipf effect indicating city size growth (internal complexity). Because of struggle of the two effects, the scaling exponent varies from 0.5 to 2; but if the two effects reach equilibrium with each other, the scaling exponent approaches 1. A series of mathematical experiments on hierarchical correlation are employed to verify the models and a conclusion can be drawn that if cities in a given region follow Zipf's law, the frequency and size correlations will follow the scaling law. This theory can be generalized to interpret the inverse power-law distributions in various fields of physical and social sciences. PMID:21949753

Experimental and theoretical investigation of thermal conductivity of ethylene glycol containing functionalized single walled carbon nanotubes

NASA Astrophysics Data System (ADS)

Hemmat Esfe, Mohammad; Firouzi, Masoumeh; Afrand, Masoud

2018-01-01

In this paper, functionalized single walled carbon nanotubes (FSWCNTs) were suspended in Ethylene Glycol (EG) at different volume fractions. A KD2 pro thermal conductivity meter was used to measure the thermal conductivity in the temperature range from 30 to 50 °C. Nanofluids were prepared in solid volume fraction of 0.02, 0.05, 0.075, 0.1, 0.25, 0.5 and, 0.75%. Experimental results revealed that the thermal conductivity of the nanofluid is a non-linear function of temperature and SWCNTs volume fraction in the range of this investigation. Thermal conductivity increases with temperature and nanoparticles volume fraction as usual for this type of nanofluid. Maximum increment in thermal conductivity of the nanofluids was found to be about 45% at 0.75 vol fractions loading at 50 °C. Finally, a new correlation based on artificial neural network (ANN) approach has been proposed for SWCNT-EG thermal conductivity in terms of nanoparticles volume fraction and temperature using the experimental data. Used ANN approach has estimated the experimental values of thermal conductivity with the absolute average relative deviation lower than 0.9%, mean square error of 3.67 × 10-5 and regression coefficient of 0.9989. Comparison between the suggested techniques with various used correlation in the literatures established that the ANN approach is better to other presented methods and therefore can be proposed as a useful means for predicting of the nanofluids thermal conductivity.

Single station monitoring of volcanoes using seismic ambient noise

NASA Astrophysics Data System (ADS)

De Plaen, R. S.; Lecocq, T.; Caudron, C.; Ferrazzini, V.; Francis, O.

2016-12-01

During volcanic eruptions, magma transport causes gas release, pressure perturbations and fracturing in the plumbing system. The potential subsequent surface deformation that can be detected using geodetic techniques and deep mechanical processes associated with magma pressurization and/or migration and their spatial-temporal evolution can be monitored with volcanic seismicity. However, these techniques respectively suffer from limited sensitivity to deep changes and a too short-term temporal distribution to expose early aseismic processes such as magma pressurisation. Seismic ambient noise cross-correlation uses the multiple scattering of seismic vibrations by heterogeneities in the crust to retrieves the Green's function for surface waves between two stations by cross-correlating these diffuse wavefields. Seismic velocity changes are then typically measured from the cross-correlation functions with applications for volcanoes, large magnitude earthquakes in the far field and smaller magnitude earthquakes at smaller distances. This technique is increasingly used as a non-destructive way to continuously monitor small seismic velocity changes ( 0.1%) associated with volcanic activity, although it is usually limited to volcanoes equipped with large and dense networks of broadband stations. The single-station approach may provide a powerful and reliable alternative to the classical "cross-stations" approach when measuring variation of seismic velocities. We implemented it on the Piton de la Fournaise in Reunion Island, a very active volcano with a remarkable multi-disciplinary continuous monitoring. Over the past decade, this volcano was increasingly studied using the traditional cross-station approach and therefore represents a unique laboratory to validate our approach. Our results, tested on stations located up to 3.5 km from the eruptive site, performed as well as the classical approach to detect the volcanic eruption in the 1-2 Hz frequency band. This opens new perspectives to successfully forecast volcanic activity at volcanoes equipped with a single 3-component seismometer.

Exact hierarchical clustering in one dimension. [in universe

NASA Technical Reports Server (NTRS)

Williams, B. G.; Heavens, A. F.; Peacock, J. A.; Shandarin, S. F.

1991-01-01

The present adhesion model-based one-dimensional simulations of gravitational clustering have yielded bound-object catalogs applicable in tests of analytical approaches to cosmological structure formation. Attention is given to Press-Schechter (1974) type functions, as well as to their density peak-theory modifications and the two-point correlation function estimated from peak theory. The extent to which individual collapsed-object locations can be predicted by linear theory is significant only for objects of near-characteristic nonlinear mass.

ERP Energy and Cognitive Activity Correlates

NASA Astrophysics Data System (ADS)

Schillaci, Michael Jay; Vendemia, Jennifer M. C.

2014-03-01

We propose a novel analysis approach for high-density event related scalp potential (ERP) data where the integrated channel-power is used to attain an energy density functional state for channel-clusters of neurophysiological significance. The method is applied to data recorded during a two-stimulus, directed lie paradigm and shows that deceptive responses emit between 8% and 10% less power. A time course analysis of these cognitive activity measures over posterior and anterior regions of the cortex suggests that neocortical interactions, reflecting the differing workload demands during executive and semantic processes, take about 50% longer for the case of deception. These results suggest that the proposed method may provide a useful tool for the analysis of ERP correlates of high-order cognitive functioning. We also report on a possible equivalence between the energy functional distribution and near-infrared signatures that have been measured with other modalities.

Local density approximation in site-occupation embedding theory

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Tsuchiizu, Masahisa; Robert, Vincent; Fromager, Emmanuel

2017-01-01

Site-occupation embedding theory (SOET) is a density functional theory (DFT)-based method which aims at modelling strongly correlated electrons. It is in principle exact and applicable to model and quantum chemical Hamiltonians. The theory is presented here for the Hubbard Hamiltonian. In contrast to conventional DFT approaches, the site (or orbital) occupations are deduced in SOET from a partially interacting system consisting of one (or more) impurity site(s) and non-interacting bath sites. The correlation energy of the bath is then treated implicitly by means of a site-occupation functional. In this work, we propose a simple impurity-occupation functional approximation based on the two-level (2L) Hubbard model which is referred to as two-level impurity local density approximation (2L-ILDA). Results obtained on a prototypical uniform eight-site Hubbard ring are promising. The extension of the method to larger systems and more sophisticated model Hamiltonians is currently in progress.

Role of scaffold network in controlling strain and functionalities of nanocomposite films

DOE PAGES

Chen, Aiping; Hu, Jia -Mian; Lu, Ping; ...

2016-06-10

One novel approach to manipulating functionalities in correlated complex oxides is strain. However, significant epitaxial strain can only be achieved in ultrathin layers. We show that, under direct lattice matching framework, large and uniform vertical strain up to 2% can be achieved to significantly modify the magnetic anisotropy, magnetism, and magnetotransport properties in heteroepitaxial nanoscaffold films, over a few hundred nanometers in thickness. Comprehensive designing principles of large vertical strain have been proposed. Phase-field simulations not only reveal the strain distribution but also suggest that the ultimate strain is related to the vertical interfacial area and interfacial dislocation density. Moreover,more » by changing the nanoscaffold density and dimension, the strain and the magnetic properties can be tuned. The established correlation among the vertical interface—strain—properties in nanoscaffold films can consequently be used to tune other functionalities in a broad range of complex oxide films far beyond critical thickness.« less

Accurate Calculation of Oscillator Strengths for CI II Lines Using Non-orthogonal Wavefunctions

NASA Technical Reports Server (NTRS)

Tayal, S. S.

2004-01-01

Non-orthogonal orbitals technique in the multiconfiguration Hartree-Fock approach is used to calculate oscillator strengths and transition probabilities for allowed and intercombination lines in Cl II. The relativistic corrections are included through the Breit-Pauli Hamiltonian. The Cl II wave functions show strong term dependence. The non-orthogonal orbitals are used to describe the term dependence of radial functions. Large sets of spectroscopic and correlation functions are chosen to describe adequately strong interactions in the 3s(sup 2)3p(sup 3)nl (sup 3)Po, (sup 1)Po and (sup 3)Do Rydberg series and to properly account for the important correlation and relaxation effects. The length and velocity forms of oscillator strength show good agreement for most transitions. The calculated radiative lifetime for the 3s3p(sup 5) (sup 3)Po state is in good agreement with experiment.

Four-time 7Li stimulated-echo spectroscopy for the study of dynamic heterogeneities: Application to lithium borate glass.

PubMed

Storek, M; Tilly, J F; Jeffrey, K R; Böhmer, R

2017-09-01

To study the nature of the nonexponential ionic hopping in solids a pulse sequence was developed that yields four-time stimulated-echo functions of previously inaccessible spin-3/2-nuclei such as 7 Li. It exploits combined Zeeman and octupolar order as longitudinal carrier state. Higher-order correlation functions were successfully generated for natural-abundance and isotopically-enriched lithium diborate glasses. Four-time 7 Li measurements are presented and compared with two-time correlation functions. The results are discussed with reference to approaches devised to quantify the degree of nonexponentiality in glass forming systems and evidence for the occurrence of dynamic heterogeneities and dynamic exchange were found. Additional experiments using the 6 Li species illustrate the challenge posed by subensemble selection when the dipolar interactions are not very much smaller than the quadrupolar ones. Copyright © 2017 Elsevier Inc. All rights reserved.

Role of scaffold network in controlling strain and functionalities of nanocomposite films

PubMed Central

Chen, Aiping; Hu, Jia-Mian; Lu, Ping; Yang, Tiannan; Zhang, Wenrui; Li, Leigang; Ahmed, Towfiq; Enriquez, Erik; Weigand, Marcus; Su, Qing; Wang, Haiyan; Zhu, Jian-Xin; MacManus-Driscoll, Judith L.; Chen, Long-Qing; Yarotski, Dmitry; Jia, Quanxi

2016-01-01

Strain is a novel approach to manipulating functionalities in correlated complex oxides. However, significant epitaxial strain can only be achieved in ultrathin layers. We show that, under direct lattice matching framework, large and uniform vertical strain up to 2% can be achieved to significantly modify the magnetic anisotropy, magnetism, and magnetotransport properties in heteroepitaxial nanoscaffold films, over a few hundred nanometers in thickness. Comprehensive designing principles of large vertical strain have been proposed. Phase-field simulations not only reveal the strain distribution but also suggest that the ultimate strain is related to the vertical interfacial area and interfacial dislocation density. By changing the nanoscaffold density and dimension, the strain and the magnetic properties can be tuned. The established correlation among the vertical interface—strain—properties in nanoscaffold films can consequently be used to tune other functionalities in a broad range of complex oxide films far beyond critical thickness. PMID:27386578

Aggregation models on hypergraphs

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

Alberici, Diego, E-mail: diego.alberici2@unibo.it; Contucci, Pierluigi, E-mail: pierluigi.contucci@unibo.it; Mingione, Emanuele, E-mail: emanuele.mingione2@unibo.it

2017-01-15

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer–dimer case. After translating those relations intomore » structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.« less

Kubo formulas for the shear and bulk viscosity relaxation times and the scalar field theory shear τπ calculation

NASA Astrophysics Data System (ADS)

Czajka, Alina; Jeon, Sangyong

2017-06-01

In this paper we provide a quantum field theoretical study on the shear and bulk relaxation times. First, we find Kubo formulas for the shear and the bulk relaxation times, respectively. They are found by examining response functions of the stress-energy tensor. We use general properties of correlation functions and the gravitational Ward identity to parametrize analytical structures of the Green functions describing both sound and diffusion mode. We find that the hydrodynamic limits of the real parts of the respective energy-momentum tensor correlation functions provide us with the method of computing both the shear and bulk viscosity relaxation times. Next, we calculate the shear viscosity relaxation time using the diagrammatic approach in the Keldysh basis for the massless λ ϕ4 theory. We derive a respective integral equation which enables us to compute η τπ and then we extract the shear relaxation time. The relaxation time is shown to be inversely related to the thermal width as it should be.

The mechanics of state dependent neural correlations

PubMed Central

Doiron, Brent; Litwin-Kumar, Ashok; Rosenbaum, Robert; Ocker, Gabriel K.; Josić, Krešimir

2016-01-01

Simultaneous recordings from large neural populations are becoming increasingly common. An important feature of the population activity are the trial-to-trial correlated fluctuations of the spike train outputs of recorded neuron pairs. Like the firing rate of single neurons, correlated activity can be modulated by a number of factors, from changes in arousal and attentional state to learning and task engagement. However, the network mechanisms that underlie these changes are not fully understood. We review recent theoretical results that identify three separate biophysical mechanisms that modulate spike train correlations: changes in input correlations, internal fluctuations, and the transfer function of single neurons. We first examine these mechanisms in feedforward pathways, and then show how the same approach can explain the modulation of correlations in recurrent networks. Such mechanistic constraints on the modulation of population activity will be important in statistical analyses of high dimensional neural data. PMID:26906505

Stochastic Gravity: Theory and Applications.

PubMed

Hu, Bei Lok; Verdaguer, Enric

2004-01-01

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operatorvalued) stress-energy bi-tensor which describes the fluctuations of quantum matter fields in curved spacetimes. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open systems concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise, and decoherence. We then focus on the properties of the stress-energy bi-tensor. We obtain a general expression for the noise kernel of a quantum field defined at two distinct points in an arbitrary curved spacetime as products of covariant derivatives of the quantum field's Green function. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime. We offer an analytical solution of the Einstein-Langevin equation and compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a quasi-static black hole (enclosed in a box). We derive a fluctuation-dissipation relation between the fluctuations in the radiation and the dissipative dynamics of metric fluctuations.

Electronic Excitations in Solution: The Interplay between State Specific Approaches and a Time-Dependent Density Functional Theory Description.

PubMed

Guido, Ciro A; Jacquemin, Denis; Adamo, Carlo; Mennucci, Benedetta

2015-12-08

We critically analyze the performances of continuum solvation models when coupled to time-dependent density functional theory (TD-DFT) to predict solvent effects on both absorption and emission energies of chromophores in solution. Different polarization schemes of the polarizable continuum model (PCM), such as linear response (LR) and three different state specific (SS) approaches, are considered and compared. We show the necessity of introducing a SS model in cases where large electron density rearrangements are involved in the excitations, such as charge-transfer transitions in both twisted and quadrupolar compounds, and underline the very delicate interplay between the selected polarization method and the chosen exchange-correlation functional. This interplay originates in the different descriptions of the transition and ground/excited state multipolar moments by the different functionals. As a result, the choice of both the DFT functional and the solvent polarization scheme has to be consistent with the nature of the studied electronic excitation.

Cross-correlation of instantaneous phase increments in pressure-flow fluctuations: Applications to cerebral autoregulation

NASA Astrophysics Data System (ADS)

Chen, Zhi; Hu, Kun; Stanley, H. Eugene; Novak, Vera; Ivanov, Plamen Ch.

2006-03-01

We investigate the relationship between the blood flow velocities (BFV) in the middle cerebral arteries and beat-to-beat blood pressure (BP) recorded from a finger in healthy and post-stroke subjects during the quasisteady state after perturbation for four different physiologic conditions: supine rest, head-up tilt, hyperventilation, and CO2 rebreathing in upright position. To evaluate whether instantaneous BP changes in the steady state are coupled with instantaneous changes in the BFV, we compare dynamical patterns in the instantaneous phases of these signals, obtained from the Hilbert transform, as a function of time. We find that in post-stroke subjects the instantaneous phase increments of BP and BFV exhibit well-pronounced patterns that remain stable in time for all four physiologic conditions, while in healthy subjects these patterns are different, less pronounced, and more variable. We propose an approach based on the cross-correlation of the instantaneous phase increments to quantify the coupling between BP and BFV signals. We find that the maximum correlation strength is different for the two groups and for the different conditions. For healthy subjects the amplitude of the cross-correlation between the instantaneous phase increments of BP and BFV is small and attenuates within 3-5 heartbeats. In contrast, for post-stroke subjects, this amplitude is significantly larger and cross-correlations persist up to 20 heartbeats. Further, we show that the instantaneous phase increments of BP and BFV are cross-correlated even within a single heartbeat cycle. We compare the results of our approach with three complementary methods: direct BP-BFV cross-correlation, transfer function analysis, and phase synchronization analysis. Our findings provide insight into the mechanism of cerebral vascular control in healthy subjects, suggesting that this control mechanism may involve rapid adjustments (within a heartbeat) of the cerebral vessels, so that BFV remains steady in response to changes in peripheral BP.

Cross-correlation of instantaneous phase increments in pressure-flow fluctuations: applications to cerebral autoregulation.

PubMed

Chen, Zhi; Hu, Kun; Stanley, H Eugene; Novak, Vera; Ivanov, Plamen Ch

2006-03-01

We investigate the relationship between the blood flow velocities (BFV) in the middle cerebral arteries and beat-to-beat blood pressure (BP) recorded from a finger in healthy and post-stroke subjects during the quasisteady state after perturbation for four different physiologic conditions: supine rest, head-up tilt, hyperventilation, and CO2 rebreathing in upright position. To evaluate whether instantaneous BP changes in the steady state are coupled with instantaneous changes in the BFV, we compare dynamical patterns in the instantaneous phases of these signals, obtained from the Hilbert transform, as a function of time. We find that in post-stroke subjects the instantaneous phase increments of BP and BFV exhibit well-pronounced patterns that remain stable in time for all four physiologic conditions, while in healthy subjects these patterns are different, less pronounced, and more variable. We propose an approach based on the cross-correlation of the instantaneous phase increments to quantify the coupling between BP and BFV signals. We find that the maximum correlation strength is different for the two groups and for the different conditions. For healthy subjects the amplitude of the cross-correlation between the instantaneous phase increments of BP and BFV is small and attenuates within 3-5 heartbeats. In contrast, for post-stroke subjects, this amplitude is significantly larger and cross-correlations persist up to 20 heartbeats. Further, we show that the instantaneous phase increments of BP and BFV are cross-correlated even within a single heartbeat cycle. We compare the results of our approach with three complementary methods: direct BP-BFV cross-correlation, transfer function analysis, and phase synchronization analysis. Our findings provide insight into the mechanism of cerebral vascular control in healthy subjects, suggesting that this control mechanism may involve rapid adjustments (within a heartbeat) of the cerebral vessels, so that BFV remains steady in response to changes in peripheral BP.

Subspace techniques to remove artifacts from EEG: a quantitative analysis.

PubMed

Teixeira, A R; Tome, A M; Lang, E W; Martins da Silva, A

2008-01-01

In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.

Differentiation and Characterization of Excitatory and Inhibitory Synapses by Cryo-electron Tomography and Correlative Microscopy.

PubMed

Tao, Chang-Lu; Liu, Yun-Tao; Sun, Rong; Zhang, Bin; Qi, Lei; Shivakoti, Sakar; Tian, Chong-Li; Zhang, Peijun; Lau, Pak-Ming; Zhou, Z Hong; Bi, Guo-Qiang

2018-02-07

As key functional units in neural circuits, different types of neuronal synapses play distinct roles in brain information processing, learning, and memory. Synaptic abnormalities are believed to underlie various neurological and psychiatric disorders. Here, by combining cryo-electron tomography and cryo-correlative light and electron microscopy, we distinguished intact excitatory and inhibitory synapses of cultured hippocampal neurons, and visualized the in situ 3D organization of synaptic organelles and macromolecules in their native state. Quantitative analyses of >100 synaptic tomograms reveal that excitatory synapses contain a mesh-like postsynaptic density (PSD) with thickness ranging from 20 to 50 nm. In contrast, the PSD in inhibitory synapses assumes a thin sheet-like structure ∼12 nm from the postsynaptic membrane. On the presynaptic side, spherical synaptic vesicles (SVs) of 25-60 nm diameter and discus-shaped ellipsoidal SVs of various sizes coexist in both synaptic types, with more ellipsoidal ones in inhibitory synapses. High-resolution tomograms obtained using a Volta phase plate and electron filtering and counting reveal glutamate receptor-like and GABA A receptor-like structures that interact with putative scaffolding and adhesion molecules, reflecting details of receptor anchoring and PSD organization. These results provide an updated view of the ultrastructure of excitatory and inhibitory synapses, and demonstrate the potential of our approach to gain insight into the organizational principles of cellular architecture underlying distinct synaptic functions. SIGNIFICANCE STATEMENT To understand functional properties of neuronal synapses, it is desirable to analyze their structure at molecular resolution. We have developed an integrative approach combining cryo-electron tomography and correlative fluorescence microscopy to visualize 3D ultrastructural features of intact excitatory and inhibitory synapses in their native state. Our approach shows that inhibitory synapses contain uniform thin sheet-like postsynaptic densities (PSDs), while excitatory synapses contain previously known mesh-like PSDs. We discovered "discus-shaped" ellipsoidal synaptic vesicles, and their distributions along with regular spherical vesicles in synaptic types are characterized. High-resolution tomograms further allowed identification of putative neurotransmitter receptors and their heterogeneous interaction with synaptic scaffolding proteins. The specificity and resolution of our approach enables precise in situ analysis of ultrastructural organization underlying distinct synaptic functions. Copyright © 2018 Tao, Liu et al.

Polychaete functional diversity in shallow habitats: Shelter from the storm

NASA Astrophysics Data System (ADS)

Wouters, Julia M.; Gusmao, Joao B.; Mattos, Gustavo; Lana, Paulo

2018-05-01

Innovative approaches are needed to help understanding how species diversity is related to the latitudinal gradient at large or small scales. We have applied a novel approach, by combining morphological and biological traits, to assess the relative importance of the large scale latitudinal gradient and regional morphodynamic drivers in shaping the functional diversity of polychaete assemblages in shallow water habitats, from exposed to estuarine sandy beaches. We used literature data on polychaetes from beaches along the southern and southeastern Brazilian coast together with data on beach types, slope, grain size, temperature, salinity, and chlorophyll a concentration. Generalized linear models on the FDis index for functional diversity calculated for each site and a combined RLQ and fourth-corner analysis were used to investigate relationships between functional traits and environmental variables. Functional diversity was not related to the latitudinal gradient but negatively correlated with grain size and beach slope. Functional diversity was highest in flat beaches with small grain size, little wave exposure and enhanced primary production, indicating that small scale morphodynamic conditions are the primary drivers of polychaete functional diversity.