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.

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

Large-scale changes in network interactions as a physiological signature of spatial neglect

PubMed Central

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.

2014-01-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028

Cluster-cluster clustering

NASA Technical Reports Server (NTRS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

The Angular Correlation Function of Galaxies from Early Sloan Digital Sky Survey Data

NASA Astrophysics Data System (ADS)

Connolly, Andrew J.; Scranton, Ryan; Johnston, David; Dodelson, Scott; Eisenstein, Daniel J.; Frieman, Joshua A.; Gunn, James E.; Hui, Lam; Jain, Bhuvnesh; Kent, Stephen; Loveday, Jon; Nichol, Robert C.; O'Connell, Liam; Postman, Marc; Scoccimarro, Roman; Sheth, Ravi K.; Stebbins, Albert; Strauss, Michael A.; Szalay, Alexander S.; Szapudi, István; Tegmark, Max; Vogeley, Michael S.; Zehavi, Idit; Annis, James; Bahcall, Neta; Brinkmann, J.; Csabai, István; Doi, Mamoru; Fukugita, Masataka; Hennessy, G. S.; Hindsley, Robert; Ichikawa, Takashi; Ivezić, Željko; Kim, Rita S. J.; Knapp, Gillian R.; Kunszt, Peter; Lamb, D. Q.; Lee, Brian C.; Lupton, Robert H.; McKay, Timothy A.; Munn, Jeff; Peoples, John; Pier, Jeff; Rockosi, Constance; Schlegel, David; Stoughton, Christopher; Tucker, Douglas L.; Yanny, Brian; York, Donald G.

2002-11-01

The Sloan Digital Sky Survey is one of the first multicolor photometric and spectroscopic surveys designed to measure the statistical properties of galaxies within the local universe. In this paper we present some of the initial results on the angular two-point correlation function measured from the early SDSS galaxy data. The form of the correlation function, over the magnitude interval 18

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.

Examining the Construct Validity of the MMPI-2-RF Interpersonal Functioning Scales Using the Computerized Adaptive Test of Personality Disorder as a Comparative Framework.

PubMed

Franz, Annabel O; Harrop, Tiffany M; McCord, David M

2017-01-01

This study aimed to examine the construct validity of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) interpersonal functioning scales (Ben-Porath & Tellegen, 2008/2011 ) using as a criterion measure the Computerized Adaptive Test of Personality Disorder-Static Form (CAT-PD-SF; Simms et al., 2011 ). Participants were college students (n = 98) recruited through the university subject pool. A series of a priori hypotheses were developed for each of the 6 interpersonal functioning scales of the MMPI-2-RF, expressed as predicted correlations with construct-relevant CAT-PD-SF scales. Of the 27 specific predictions, 21 were supported by substantial (≥ |.30|) correlations. The MMPI-2-RF Family Problems scale (FML) demonstrated the strongest correlations with CAT-PD-SF scales Anhedonia and Mistrust; Cynicism (RC3) was most highly correlated with Mistrust and Norm Violation; Interpersonal Passivity (IPP) was most highly correlated with Domineering and Rudeness; Social Avoidance (SAV) was most highly correlated with Social Withdrawal and Anhedonia; Shyness (SHY) was most highly correlated with Social Withdrawal and Anxioiusness; and Disaffiliativeness (DSF) was most highly correlated with Emotional Detachment and Mistrust. Results are largely consistent with hypotheses suggesting support for both models of constructs relevant to interpersonal functioning. Future research designed to more precisely differentiate Social Avoidance (SAV) and Shyness (SHY) is suggested.

The correlation function for density perturbations in an expanding universe. IV - The evolution of the correlation function. [galaxy distribution

NASA Technical Reports Server (NTRS)

Mcclelland, J.; Silk, J.

1979-01-01

The evolution of the two-point correlation function for the large-scale distribution of galaxies in an expanding universe is studied on the assumption that the perturbation densities lie in a Gaussian distribution centered on any given mass scale. The perturbations are evolved according to the Friedmann equation, and the correlation function for the resulting distribution of perturbations at the present epoch is calculated. It is found that: (1) the computed correlation function gives a satisfactory fit to the observed function in cosmological models with a density parameter (Omega) of approximately unity, provided that a certain free parameter is suitably adjusted; (2) the power-law slope in the nonlinear regime reflects the initial fluctuation spectrum, provided that the density profile of individual perturbations declines more rapidly than the -2.4 power of distance; and (3) both positive and negative contributions to the correlation function are predicted for cosmological models with Omega less than unity.

Large-scale changes in network interactions as a physiological signature of spatial neglect.

PubMed

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio

2014-12-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Ways to improve your correlation functions

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1993-01-01

This paper describes a number of ways to improve on the standard method for measuring the two-point correlation function of large scale structure in the Universe. Issues addressed are: (1) the problem of the mean density, and how to solve it; (2) how to estimate the uncertainty in a measured correlation function; (3) minimum variance pair weighting; (4) unbiased estimation of the selection function when magnitudes are discrete; and (5) analytic computation of angular integrals in background pair counts.

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

THREE-POINT PHASE CORRELATIONS: A NEW MEASURE OF NONLINEAR LARGE-SCALE STRUCTURE

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

Wolstenhulme, Richard; Bonvin, Camille; Obreschkow, Danail

2015-05-10

We derive an analytical expression for a novel large-scale structure observable: the line correlation function. The line correlation function, which is constructed from the three-point correlation function of the phase of the density field, is a robust statistical measure allowing the extraction of information in the nonlinear and non-Gaussian regime. We show that, in perturbation theory, the line correlation is sensitive to the coupling kernel F{sub 2}, which governs the nonlinear gravitational evolution of the density field. We compare our analytical expression with results from numerical simulations and find a 1σ agreement for separations r ≳ 30 h{sup −1} Mpc.more » Fitting formulae for the power spectrum and the nonlinear coupling kernel at small scales allow us to extend our prediction into the strongly nonlinear regime, where we find a 1σ agreement with the simulations for r ≳ 2 h{sup −1} Mpc. We discuss the advantages of the line correlation relative to standard statistical measures like the bispectrum. Unlike the latter, the line correlation is independent of the bias, in the regime where the bias is local and linear. Furthermore, the variance of the line correlation is independent of the Gaussian variance on the modulus of the density field. This suggests that the line correlation can probe more precisely the nonlinear regime of gravity, with less contamination from the power spectrum variance.« less

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

A density spike on astrophysical scales from an N-field waterfall transition

NASA Astrophysics Data System (ADS)

Halpern, Illan F.; Hertzberg, Mark P.; Joss, Matthew A.; Sfakianakis, Evangelos I.

2015-09-01

Hybrid inflation models are especially interesting as they lead to a spike in the density power spectrum on small scales, compared to the CMB, while also satisfying current bounds on tensor modes. Here we study hybrid inflation with N waterfall fields sharing a global SO (N) symmetry. The inclusion of many waterfall fields has the obvious advantage of avoiding topologically stable defects for N > 3. We find that it also has another advantage: it is easier to engineer models that can simultaneously (i) be compatible with constraints on the primordial spectral index, which tends to otherwise disfavor hybrid models, and (ii) produce a spike on astrophysically large length scales. The latter may have significant consequences, possibly seeding the formation of astrophysically large black holes. We calculate correlation functions of the time-delay, a measure of density perturbations, produced by the waterfall fields, as a convergent power series in both 1 / N and the field's correlation function Δ (x). We show that for large N, the two-point function is < δt (x) δt (0) > ∝Δ2 (| x |) / N and the three-point function is < δt (x) δt (y) δt (0) > ∝ Δ (| x - y |) Δ (| x |) Δ (| y |) /N2. In accordance with the central limit theorem, the density perturbations on the scale of the spike are Gaussian for large N and non-Gaussian for small N.

Finite-size scaling above the upper critical dimension in Ising models with long-range interactions

NASA Astrophysics Data System (ADS)

Flores-Sola, Emilio J.; Berche, Bertrand; Kenna, Ralph; Weigel, Martin

2015-01-01

The correlation length plays a pivotal role in finite-size scaling and hyperscaling at continuous phase transitions. Below the upper critical dimension, where the correlation length is proportional to the system length, both finite-size scaling and hyperscaling take conventional forms. Above the upper critical dimension these forms break down and a new scaling scenario appears. Here we investigate this scaling behaviour by simulating one-dimensional Ising ferromagnets with long-range interactions. We show that the correlation length scales as a non-trivial power of the linear system size and investigate the scaling forms. For interactions of sufficiently long range, the disparity between the correlation length and the system length can be made arbitrarily large, while maintaining the new scaling scenarios. We also investigate the behavior of the correlation function above the upper critical dimension and the modifications imposed by the new scaling scenario onto the associated Fisher relation.

Lagrangian velocity and acceleration correlations of large inertial particles in a closed turbulent flow

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

Machicoane, Nathanaël; Volk, Romain

We investigate the response of large inertial particle to turbulent fluctuations in an inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters are comparable to the flow integral scale. Both velocity and acceleration correlation functions are analyzed to compute the Lagrangian integral time and the acceleration time scale of such particles. The knowledge of how size and density affect these time scales is crucial in understanding particle dynamics and may permit stochastic process modelization using two-time models (for instance, Sawford’s). As particles are tracked over long timesmore » in the quasi-totality of a closed flow, the mean flow influences their behaviour and also biases the velocity time statistics, in particular the velocity correlation functions. By using a method that allows for the computation of turbulent velocity trajectories, we can obtain unbiased Lagrangian integral time. This is particularly useful in accessing the scale separation for such particles and to comparing it to the case of fluid particles in a similar configuration.« less

Probing the statistics of primordial fluctuations and their evolution

NASA Technical Reports Server (NTRS)

Gaztanaga, Enrique; Yokoyama, Jun'ichi

1993-01-01

The statistical distribution of fluctuations on various scales is analyzed in terms of the counts in cells of smoothed density fields, using volume-limited samples of galaxy redshift catalogs. It is shown that the distribution on large scales, with volume average of the two-point correlation function of the smoothed field less than about 0.05, is consistent with Gaussian. Statistics are shown to agree remarkably well with the negative binomial distribution, which has hierarchial correlations and a Gaussian behavior at large scales. If these observed properties correspond to the matter distribution, they suggest that our universe started with Gaussian fluctuations and evolved keeping hierarchial form.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

NASA Astrophysics Data System (ADS)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

The ellipsoidal universe in the Planck satellite era

NASA Astrophysics Data System (ADS)

Cea, Paolo

2014-06-01

Recent Planck data confirm that the cosmic microwave background displays the quadrupole power suppression together with large-scale anomalies. Progressing from previous results, that focused on the quadrupole anomaly, we strengthen the proposal that the slightly anisotropic ellipsoidal universe may account for these anomalies. We solved at large scales the Boltzmann equation for the photon distribution functions by taking into account both the effects of the inflation produced primordial scalar perturbations and the anisotropy of the geometry in the ellipsoidal universe. We showed that the low quadrupole temperature correlations allowed us to fix the eccentricity at decoupling, edec = (0.86 ± 0.14) 10-2, and to constraint the direction of the symmetry axis. We found that the anisotropy of the geometry of the universe contributes only to the large-scale temperature anisotropies without affecting the higher multipoles of the angular power spectrum. Moreover, we showed that the ellipsoidal geometry of the universe induces sizeable polarization signal at large scales without invoking the reionization scenario. We explicitly evaluated the quadrupole TE and EE correlations. We found an average large-scale polarization ΔTpol = (1.20 ± 0.38) μK. We point out that great care is needed in the experimental determination of the large-scale polarization correlations since the average temperature polarization could be misinterpreted as foreground emission leading, thereby, to a considerable underestimate of the cosmic microwave background polarization signal.

On the linearity of tracer bias around voids

NASA Astrophysics Data System (ADS)

Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro

2017-07-01

The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.

Detection of the baryon acoustic peak in the large-scale correlation function of SDSS luminous red galaxies

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

Eisenstein, Daniel J.; Zehavi, Idit; Hogg, David W.

2005-01-01

We present the large-scale correlation function measured from a spectroscopic sample of 46,748 luminous red galaxies from the Sloan Digital Sky Survey. The survey region covers 0.72h{sup -3} Gpc{sup 3} over 3816 square degrees and 0.16 < z < 0.47, making it the best sample yet for the study of large-scale structure. We find a well-detected peak in the correlation function at 100h{sup -1} Mpc separation that is an excellent match to the predicted shape and location of the imprint of the recombination-epoch acoustic oscillations on the low-redshift clustering of matter. This detection demonstrates the linear growth of structure bymore » gravitational instability between z {approx} 1000 and the present and confirms a firm prediction of the standard cosmological theory. The acoustic peak provides a standard ruler by which we can measure the ratio of the distances to z = 0.35 and z = 1089 to 4% fractional accuracy and the absolute distance to z = 0.35 to 5% accuracy. From the overall shape of the correlation function, we measure the matter density {Omega}{sub m}h{sup 2} to 8% and find agreement with the value from cosmic microwave background (CMB) anisotropies. Independent of the constraints provided by the CMB acoustic scale, we find {Omega}{sub m} = 0.273 {+-} 0.025 + 0.123(1 + w{sub 0}) + 0.137{Omega}{sub K}. Including the CMB acoustic scale, we find that the spatial curvature is {Omega}{sub K} = -0.010 {+-} 0.009 if the dark energy is a cosmological constant. More generally, our results provide a measurement of cosmological distance, and hence an argument for dark energy, based on a geometric method with the same simple physics as the microwave background anisotropies. The standard cosmological model convincingly passes these new and robust tests of its fundamental properties.« less

Detection of Baryon Acoustic Oscillation features in the large-scale 3-point correlation function of SDSS BOSS DR12 CMASS galaxies

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

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.

We present the large-scale 3-point correlation function (3PCF) of the SDSS DR12 CMASS sample of 777,202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of Baryon Acoustic Oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z=0.57 to 1.7% precision (statistical plus systematic). We find D V = 2024 ± 29Mpc (stat) ± 20Mpc(sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from themore » 2-point correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10%; reconstruction appears to lower the independence of the distance measurements. In conclusion, fitting a model including tidal tensor bias yields a moderate significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.« less

Detection of baryon acoustic oscillation features in the large-scale three-point correlation function of SDSS BOSS DR12 CMASS galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.; Brownstein, Joel R.; Chuang, Chia-Hsun; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; Percival, Will J.; Ross, Ashley J.; Rossi, Graziano; Seo, Hee-Jong; Slosar, Anže; Vargas-Magaña, Mariana

2017-08-01

We present the large-scale three-point correlation function (3PCF) of the Sloan Digital Sky Survey DR12 Constant stellar Mass (CMASS) sample of 777 202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of baryon acoustic oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z = 0.57 to 1.7 per cent precision (statistical plus systematic). We find DV = 2024 ± 29 Mpc (stat) ± 20 Mpc (sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from the two-point correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10 per cent; reconstruction appears to lower the independence of the distance measurements. Fitting a model including tidal tensor bias yields a moderate-significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.

Detection of Baryon Acoustic Oscillation features in the large-scale 3-point correlation function of SDSS BOSS DR12 CMASS galaxies

DOE PAGES

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.; ...

2017-03-01

We present the large-scale 3-point correlation function (3PCF) of the SDSS DR12 CMASS sample of 777,202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of Baryon Acoustic Oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z=0.57 to 1.7% precision (statistical plus systematic). We find D V = 2024 ± 29Mpc (stat) ± 20Mpc(sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from themore » 2-point correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10%; reconstruction appears to lower the independence of the distance measurements. In conclusion, fitting a model including tidal tensor bias yields a moderate significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.« less

Analyzing the cosmic variance limit of remote dipole measurements of the cosmic microwave background using the large-scale kinetic Sunyaev Zel'dovich effect

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

Terrana, Alexandra; Johnson, Matthew C.; Harris, Mary-Jean, E-mail: aterrana@perimeterinstitute.ca, E-mail: mharris8@perimeterinstitute.ca, E-mail: mjohnson@perimeterinstitute.ca

Due to cosmic variance we cannot learn any more about large-scale inhomogeneities from the primary cosmic microwave background (CMB) alone. More information on large scales is essential for resolving large angular scale anomalies in the CMB. Here we consider cross correlating the large-scale kinetic Sunyaev Zel'dovich (kSZ) effect and probes of large-scale structure, a technique known as kSZ tomography. The statistically anisotropic component of the cross correlation encodes the CMB dipole as seen by free electrons throughout the observable Universe, providing information about long wavelength inhomogeneities. We compute the large angular scale power asymmetry, constructing the appropriate transfer functions, andmore » estimate the cosmic variance limited signal to noise for a variety of redshift bin configurations. The signal to noise is significant over a large range of power multipoles and numbers of bins. We present a simple mode counting argument indicating that kSZ tomography can be used to estimate more modes than the primary CMB on comparable scales. A basic forecast indicates that a first detection could be made with next-generation CMB experiments and galaxy surveys. This paper motivates a more systematic investigation of how close to the cosmic variance limit it will be possible to get with future observations.« less

How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

NASA Technical Reports Server (NTRS)

Blumenthal, George R.; Johnston, Kathryn V.

1994-01-01

The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

Functional Independent Scaling Relation for ORR/OER Catalysts

DOE PAGES

Christensen, Rune; Hansen, Heine A.; Dickens, Colin F.; ...

2016-10-11

A widely used adsorption energy scaling relation between OH* and OOH* intermediates in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), has previously been determined using density functional theory and shown to dictate a minimum thermodynamic overpotential for both reactions. Here, we show that the oxygen–oxygen bond in the OOH* intermediate is, however, not well described with the previously used class of exchange-correlation functionals. By quantifying and correcting the systematic error, an improved description of gaseous peroxide species versus experimental data and a reduction in calculational uncertainty is obtained. For adsorbates, we find that the systematic error largelymore » cancels the vdW interaction missing in the original determination of the scaling relation. An improved scaling relation, which is fully independent of the applied exchange–correlation functional, is obtained and found to differ by 0.1 eV from the original. Lastly, this largely confirms that, although obtained with a method suffering from systematic errors, the previously obtained scaling relation is applicable for predictions of catalytic activity.« less

The build up of the correlation between halo spin and the large-scale structure

NASA Astrophysics Data System (ADS)

Wang, Peng; Kang, Xi

2018-01-01

Both simulations and observations have confirmed that the spin of haloes/galaxies is correlated with the large-scale structure (LSS) with a mass dependence such that the spin of low-mass haloes/galaxies tend to be parallel with the LSS, while that of massive haloes/galaxies tend to be perpendicular with the LSS. It is still unclear how this mass dependence is built up over time. We use N-body simulations to trace the evolution of the halo spin-LSS correlation and find that at early times the spin of all halo progenitors is parallel with the LSS. As time goes on, mass collapsing around massive halo is more isotropic, especially the recent mass accretion along the slowest collapsing direction is significant and it brings the halo spin to be perpendicular with the LSS. Adopting the fractional anisotropy (FA) parameter to describe the degree of anisotropy of the large-scale environment, we find that the spin-LSS correlation is a strong function of the environment such that a higher FA (more anisotropic environment) leads to an aligned signal, and a lower anisotropy leads to a misaligned signal. In general, our results show that the spin-LSS correlation is a combined consequence of mass flow and halo growth within the cosmic web. Our predicted environmental dependence between spin and large-scale structure can be further tested using galaxy surveys.

Effects of biasing on the galaxy power spectrum at large scales

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

Beltran Jimenez, Jose; Departamento de Fisica Teorica, Universidad Complutense de Madrid, 28040, Madrid; Durrer, Ruth

2011-05-15

In this paper we study the effect of biasing on the power spectrum at large scales. We show that even though nonlinear biasing does introduce a white noise contribution on large scales, the P(k){proportional_to}k{sup n} behavior of the matter power spectrum on large scales may still be visible and above the white noise for about one decade. We show, that the Kaiser biasing scheme which leads to linear bias of the correlation function on large scales, also generates a linear bias of the power spectrum on rather small scales. This is a consequence of the divergence on small scales ofmore » the pure Harrison-Zeldovich spectrum. However, biasing becomes k dependent if we damp the underlying power spectrum on small scales. We also discuss the effect of biasing on the baryon acoustic oscillations.« less

The Large Local Hole in the Galaxy Distribution: The 2MASS Galaxy Angular Power Spectrum

NASA Astrophysics Data System (ADS)

Frith, W. J.; Outram, P. J.; Shanks, T.

2005-06-01

We present new evidence for a large deficiency in the local galaxy distribution situated in the ˜4000 deg2 APM survey area. We use models guided by the 2dF Galaxy Redshift Survey (2dFGRS) n(z) as a probe of the underlying large-scale structure. We first check the usefulness of this technique by comparing the 2dFGRS n(z) model prediction with the K-band and B-band number counts extracted from the 2MASS and 2dFGRS parent catalogues over the 2dFGRS Northern and Southern declination strips, before turning to a comparison with the APM counts. We find that the APM counts in both the B and K-bands indicate a deficiency in the local galaxy distribution of ˜30% to z ≈ 0.1 over the entire APM survey area. We examine the implied significance of such a large local hole, considering several possible forms for the real-space correlation function. We find that such a deficiency in the APM survey area indicates an excess of power at large scales over what is expected from the correlation function observed in 2dFGRS correlation function or predicted from ΛCDM Hubble Volume mock catalogues. In order to check further the clustering at large scales in the 2MASS data, we have calculated the angular power spectrum for 2MASS galaxies. Although in the linear regime (l<30), ΛCDM models can give a good fit to the 2MASS angular power spectrum, over a wider range (l<100) the power spectrum from Hubble Volume mock catalogues suggests that scale-dependent bias may be needed for ΛCDM to fit. However, the modest increase in large-scale power observed in the 2MASS angular power spectrum is still not enough to explain the local hole. If the APM survey area really is 25% deficient in galaxies out to z≈0.1, explanations for the disagreement with observed galaxy clustering statistics include the possibilities that the galaxy clustering is non-Gaussian on large scales or that the 2MASS volume is still too small to represent a `fair sample' of the Universe. Extending the 2dFGRS redshift survey over the whole APM area would resolve many of the remaining questions about the existence and interpretation of this local hole.

Transition from lognormal to χ2-superstatistics for financial time series

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2016-07-01

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.

Heat perturbation spreading in the Fermi-Pasta-Ulam-β system with next-nearest-neighbor coupling: Competition between phonon dispersion and nonlinearity

NASA Astrophysics Data System (ADS)

Xiong, Daxing

2017-06-01

We employ the heat perturbation correlation function to study thermal transport in the one-dimensional Fermi-Pasta-Ulam-β lattice with both nearest-neighbor and next-nearest-neighbor couplings. We find that such a system bears a peculiar phonon dispersion relation, and thus there exists a competition between phonon dispersion and nonlinearity that can strongly affect the heat correlation function's shape and scaling property. Specifically, for small and large anharmoncities, the scaling laws are ballistic and superdiffusive types, respectively, which are in good agreement with the recent theoretical predictions; whereas in the intermediate range of the nonlinearity, we observe an unusual multiscaling property characterized by a nonmonotonic delocalization process of the central peak of the heat correlation function. To understand these multiscaling laws, we also examine the momentum perturbation correlation function and find a transition process with the same turning point of the anharmonicity as that shown in the heat correlation function. This suggests coupling between the momentum transport and the heat transport, in agreement with the theoretical arguments of mode cascade theory.

Multi-scale properties of large eddy simulations: correlations between resolved-scale velocity-field increments and subgrid-scale quantities

NASA Astrophysics Data System (ADS)

Linkmann, Moritz; Buzzicotti, Michele; Biferale, Luca

2018-06-01

We provide analytical and numerical results concerning multi-scale correlations between the resolved velocity field and the subgrid-scale (SGS) stress-tensor in large eddy simulations (LES). Following previous studies for Navier-Stokes equations, we derive the exact hierarchy of LES equations governing the spatio-temporal evolution of velocity structure functions of any order. The aim is to assess the influence of the subgrid model on the inertial range intermittency. We provide a series of predictions, within the multifractal theory, for the scaling of correlation involving the SGS stress and we compare them against numerical results from high-resolution Smagorinsky LES and from a-priori filtered data generated from direct numerical simulations (DNS). We find that LES data generally agree very well with filtered DNS results and with the multifractal prediction for all leading terms in the balance equations. Discrepancies are measured for some of the sub-leading terms involving cross-correlation between resolved velocity increments and the SGS tensor or the SGS energy transfer, suggesting that there must be room to improve the SGS modelisation to further extend the inertial range properties for any fixed LES resolution.

Computational Thermochemistry: Scale Factor Databases and Scale Factors for Vibrational Frequencies Obtained from Electronic Model Chemistries.

PubMed

Alecu, I M; Zheng, Jingjing; Zhao, Yan; Truhlar, Donald G

2010-09-14

Optimized scale factors for calculating vibrational harmonic and fundamental frequencies and zero-point energies have been determined for 145 electronic model chemistries, including 119 based on approximate functionals depending on occupied orbitals, 19 based on single-level wave function theory, three based on the neglect-of-diatomic-differential-overlap, two based on doubly hybrid density functional theory, and two based on multicoefficient correlation methods. Forty of the scale factors are obtained from large databases, which are also used to derive two universal scale factor ratios that can be used to interconvert between scale factors optimized for various properties, enabling the derivation of three key scale factors at the effort of optimizing only one of them. A reduced scale factor optimization model is formulated in order to further reduce the cost of optimizing scale factors, and the reduced model is illustrated by using it to obtain 105 additional scale factors. Using root-mean-square errors from the values in the large databases, we find that scaling reduces errors in zero-point energies by a factor of 2.3 and errors in fundamental vibrational frequencies by a factor of 3.0, but it reduces errors in harmonic vibrational frequencies by only a factor of 1.3. It is shown that, upon scaling, the balanced multicoefficient correlation method based on coupled cluster theory with single and double excitations (BMC-CCSD) can lead to very accurate predictions of vibrational frequencies. With a polarized, minimally augmented basis set, the density functionals with zero-point energy scale factors closest to unity are MPWLYP1M (1.009), τHCTHhyb (0.989), BB95 (1.012), BLYP (1.013), BP86 (1.014), B3LYP (0.986), MPW3LYP (0.986), and VSXC (0.986).

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-04-01

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

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

StePS: Stereographically Projected Cosmological Simulations

NASA Astrophysics Data System (ADS)

Rácz, Gábor; Szapudi, István; Csabai, István; Dobos, László

2018-05-01

StePS (Stereographically Projected Cosmological Simulations) compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to simulate the evolution of the large-scale structure. This eliminates the need for periodic boundary conditions, which are a numerical convenience unsupported by observation and which modifies the law of force on large scales in an unrealistic fashion. StePS uses stereographic projection for space compactification and naive O(N2) force calculation; this arrives at a correlation function of the same quality more quickly than standard (tree or P3M) algorithms with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence StePS can function as a high-speed prediction tool for modern large-scale surveys.

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

Clustering fossil from primordial gravitational waves in anisotropic inflation

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

Emami, Razieh; Firouzjahi, Hassan, E-mail: emami@ipm.ir, E-mail: firouz@ipm.ir

2015-10-01

Inflationary models can correlate small-scale density perturbations with the long-wavelength gravitational waves (GW) in the form of the Tensor-Scalar-Scalar (TSS) bispectrum. This correlation affects the mass-distribution in the Universe and leads to the off-diagonal correlations of the density field modes in the form of the quadrupole anisotropy. Interestingly, this effect survives even after the tensor mode decays when it re-enters the horizon, known as the fossil effect. As a result, the off-diagonal correlation function between different Fourier modes of the density fluctuations can be thought as a way to probe the large-scale GW and the mechanism of inflation behind themore » fossil effect. Models of single field slow roll inflation generically predict a very small quadrupole anisotropy in TSS while in models of multiple fields inflation this effect can be observable. Therefore this large scale quadrupole anisotropy can be thought as a spectroscopy for different inflationary models. In addition, in models of anisotropic inflation there exists quadrupole anisotropy in curvature perturbation power spectrum. Here we consider TSS in models of anisotropic inflation and show that the shape of quadrupole anisotropy is different than in single field models. In fact, in these models, quadrupole anisotropy is projected into the preferred direction and its amplitude is proportional to g{sub *} N{sub e} where N{sub e} is the number of e-folds and g{sub *} is the amplitude of quadrupole anisotropy in curvature perturbation power spectrum. We use this correlation function to estimate the large scale GW as well as the preferred direction and discuss the detectability of the signal in the galaxy surveys like Euclid and 21 cm surveys.« less

The large-scale correlations of multicell densities and profiles: implications for cosmic variance estimates

NASA Astrophysics Data System (ADS)

Codis, Sandrine; Bernardeau, Francis; Pichon, Christophe

2016-08-01

In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of their two-point correlation function to the two-point correlation of the underlying dark matter distribution. They describe how cell densities are spatially correlated. They are computed here via the so-called large deviation principle in the quasi-linear regime. Their large-separation limit is presented and successfully compared to simulations for density and density slopes: this regime is shown to be rapidly reached allowing to get sub-percent precision for a wide range of densities and variances. The corresponding asymptotic limit provides an estimate of the cosmic variance of standard concentric cell statistics applied to finite surveys. More generally, no assumption on the separation is required for some specific moments of the two-point statistics, for instance when predicting the generating function of cumulants containing any powers of concentric densities in one location and one power of density at some arbitrary distance from the rest. This exact `one external leg' cumulant generating function is used in particular to probe the rate of convergence of the large-separation approximation.

Non-linear scaling of oxygen consumption and heart rate in a very large cockroach species (Gromphadorhina portentosa): correlated changes with body size and temperature.

PubMed

Streicher, Jeffrey W; Cox, Christian L; Birchard, Geoffrey F

2012-04-01

Although well documented in vertebrates, correlated changes between metabolic rate and cardiovascular function of insects have rarely been described. Using the very large cockroach species Gromphadorhina portentosa, we examined oxygen consumption and heart rate across a range of body sizes and temperatures. Metabolic rate scaled positively and heart rate negatively with body size, but neither scaled linearly. The response of these two variables to temperature was similar. This correlated response to endogenous (body mass) and exogenous (temperature) variables is likely explained by a mutual dependence on similar metabolic substrate use and/or coupled regulatory pathways. The intraspecific scaling for oxygen consumption rate showed an apparent plateauing at body masses greater than about 3 g. An examination of cuticle mass across all instars revealed isometric scaling with no evidence of an ontogenetic shift towards proportionally larger cuticles. Published oxygen consumption rates of other Blattodea species were also examined and, as in our intraspecific examination of G. portentosa, the scaling relationship was found to be non-linear with a decreasing slope at larger body masses. The decreasing slope at very large body masses in both intraspecific and interspecific comparisons may have important implications for future investigations of the relationship between oxygen transport and maximum body size in insects.

Voronoi Tessellation for reducing the processing time of correlation functions

NASA Astrophysics Data System (ADS)

Cárdenas-Montes, Miguel; Sevilla-Noarbe, Ignacio

2018-01-01

The increase of data volume in Cosmology is motivating the search of new solutions for solving the difficulties associated with the large processing time and precision of calculations. This is specially true in the case of several relevant statistics of the galaxy distribution of the Large Scale Structure of the Universe, namely the two and three point angular correlation functions. For these, the processing time has critically grown with the increase of the size of the data sample. Beyond parallel implementations to overcome the barrier of processing time, space partitioning algorithms are necessary to reduce the computational load. These can delimit the elements involved in the correlation function estimation to those that can potentially contribute to the final result. In this work, Voronoi Tessellation is used to reduce the processing time of the two-point and three-point angular correlation functions. The results of this proof-of-concept show a significant reduction of the processing time when preprocessing the galaxy positions with Voronoi Tessellation.

On the universality of the two-point galaxy correlation function

NASA Technical Reports Server (NTRS)

Davis, Marc; Meiksin, Avery; Strauss, Michael A.; Da Costa, L. Nicolaci; Yahil, Amos

1988-01-01

The behavior of the two-point galaxy correlation function in volume-limited subsamples of three complete redshift surveys is investigated. The correlation length is shown to scale approximately as the square root of the distance limit in both the CfA and Southern Sky catalogs, but to be independent of the distance limit in the IRAS sample. This effect is found to be due to factors such as the large positive density fluctuations in the foreground of the optically selected catalogs biasing the correlation length estimate downward, and the brightest galaxies appearing to be more strongly clustered than the mean.

Large-Scale Phase Synchrony Reflects Clinical Status After Stroke: An EEG Study.

PubMed

Kawano, Teiji; Hattori, Noriaki; Uno, Yutaka; Kitajo, Keiichi; Hatakenaka, Megumi; Yagura, Hajime; Fujimoto, Hiroaki; Yoshioka, Tomomi; Nagasako, Michiko; Otomune, Hironori; Miyai, Ichiro

2017-06-01

Stroke-induced focal brain lesions often exert remote effects via residual neural network activity. Electroencephalographic (EEG) techniques can assess neural network modifications after brain damage. Recently, EEG phase synchrony analyses have shown associations between the level of large-scale phase synchrony of brain activity and clinical symptoms; however, few reports have assessed such associations in stroke patients. The aim of this study was to investigate the clinical relevance of hemispheric phase synchrony in stroke patients by calculating its correlation with clinical status. This cross-sectional study included 19 patients with post-acute ischemic stroke admitted for inpatient rehabilitation. Interhemispheric phase synchrony indices (IH-PSIs) were computed in 2 frequency bands (alpha [α], and beta [β]), and associations between indices and scores of the Functional Independence Measure (FIM), the National Institutes of Health Stroke Scale (NIHSS), and the Fugl-Meyer Motor Assessment (FMA) were analyzed. For further assessments of IH-PSIs, ipsilesional intrahemispheric PSIs (IntraH-PSIs) as well as IH- and IntraH-phase lag indices (PLIs) were also evaluated. IH-PSIs correlated significantly with FIM scores and NIHSS scores. In contrast, IH-PSIs did not correlate with FMA scores. IntraH-PSIs correlate with FIM scores after removal of the outlier. The results of analysis with PLIs were consistent with IH-PSIs. The PSIs correlated with performance on the activities of daily living scale but not with scores on a pure motor impairment scale. These results suggest that large-scale phase synchrony represented by IH-PSIs provides a novel surrogate marker for clinical status after stroke.

The large-scale distribution of galaxies

NASA Technical Reports Server (NTRS)

Geller, Margaret J.

1989-01-01

The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.

Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

PubMed Central

Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

2015-01-01

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

The large-scale three-point correlation function of the SDSS BOSS DR12 CMASS galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.; Beutler, Florian; Chuang, Chia-Hsun; Cuesta, Antonio J.; Ge, Jian; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; McBride, Cameron K.; Nichol, Robert C.; Percival, Will J.; Rodríguez-Torres, Sergio; Ross, Ashley J.; Scoccimarro, Román; Seo, Hee-Jong; Tinker, Jeremy; Tojeiro, Rita; Vargas-Magaña, Mariana

2017-06-01

We report a measurement of the large-scale three-point correlation function of galaxies using the largest data set for this purpose to date, 777 202 luminous red galaxies in the Sloan Digital Sky Survey Baryon Acoustic Oscillation Spectroscopic Survey (SDSS BOSS) DR12 CMASS sample. This work exploits the novel algorithm of Slepian & Eisenstein to compute the multipole moments of the 3PCF in O(N^2) time, with N the number of galaxies. Leading-order perturbation theory models the data well in a compressed basis where one triangle side is integrated out. We also present an accurate and computationally efficient means of estimating the covariance matrix. With these techniques, the redshift-space linear and non-linear bias are measured, with 2.6 per cent precision on the former if σ8 is fixed. The data also indicate a 2.8σ preference for the BAO, confirming the presence of BAO in the three-point function.

Population cycles are highly correlated over long time series and large spatial scales in two unrelated species: Greater sage-grouse and cottontail rabbits

USGS Publications Warehouse

Fedy, B.C.; Doherty, K.E.

2011-01-01

Animal species across multiple taxa demonstrate multi-annual population cycles, which have long been of interest to ecologists. Correlated population cycles between species that do not share a predator-prey relationship are particularly intriguing and challenging to explain. We investigated annual population trends of greater sage-grouse (Centrocercus urophasianus) and cottontail rabbits (Sylvilagus sp.) across Wyoming to explore the possibility of correlations between unrelated species, over multiple cycles, very large spatial areas, and relatively southern latitudes in terms of cycling species. We analyzed sage-grouse lek counts and annual hunter harvest indices from 1982 to 2007. We show that greater sage-grouse, currently listed as warranted but precluded under the US Endangered Species Act, and cottontails have highly correlated cycles (r = 0. 77). We explore possible mechanistic hypotheses to explain the synchronous population cycles. Our research highlights the importance of control populations in both adaptive management and impact studies. Furthermore, we demonstrate the functional value of these indices (lek counts and hunter harvest) for tracking broad-scale fluctuations in the species. This level of highly correlated long-term cycling has not previously been documented between two non-related species, over a long time-series, very large spatial scale, and within more southern latitudes. ?? 2010 US Government.

Redshift space clustering of galaxies and cold dark matter model

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue; Gramann, Mirt

1993-01-01

The distorting effect of peculiar velocities on the power speturm and correlation function of IRAS and optical galaxies is studied. The observed redshift space power spectra and correlation functions of IRAS and optical the galaxies over the entire range of scales are directly compared with the corresponding redshift space distributions using large-scale computer simulations of cold dark matter (CDM) models in order to study the distortion effect of peculiar velocities on the power spectrum and correlation function of the galaxies. It is found that the observed power spectrum of IRAS and optical galaxies is consistent with the spectrum of an Omega = 1 CDM model. The problems that such a model currently faces may be related more to the high value of Omega in the model than to the shape of the spectrum. A low-density CDM model is also investigated and found to be consistent with the data.

Modeling CMB lensing cross correlations with CLEFT

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

Modi, Chirag; White, Martin; Vlah, Zvonimir, E-mail: modichirag@berkeley.edu, E-mail: mwhite@berkeley.edu, E-mail: zvlah@stanford.edu

2017-08-01

A new generation of surveys will soon map large fractions of sky to ever greater depths and their science goals can be enhanced by exploiting cross correlations between them. In this paper we study cross correlations between the lensing of the CMB and biased tracers of large-scale structure at high z . We motivate the need for more sophisticated bias models for modeling increasingly biased tracers at these redshifts and propose the use of perturbation theories, specifically Convolution Lagrangian Effective Field Theory (CLEFT). Since such signals reside at large scales and redshifts, they can be well described by perturbative approaches.more » We compare our model with the current approach of using scale independent bias coupled with fitting functions for non-linear matter power spectra, showing that the latter will not be sufficient for upcoming surveys. We illustrate our ideas by estimating σ{sub 8} from the auto- and cross-spectra of mock surveys, finding that CLEFT returns accurate and unbiased results at high z . We discuss uncertainties due to the redshift distribution of the tracers, and several avenues for future development.« less

The correlation function for density perturbations in an expanding universe. III The three-point and predictions of the four-point and higher order correlation functions

NASA Technical Reports Server (NTRS)

Mcclelland, J.; Silk, J.

1978-01-01

Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.

Large Scale Cross Drive Correlation Of Digital Media

DTIC Science & Technology

2016-03-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS LARGE SCALE CROSS-DRIVE CORRELATION OF DIGITAL MEDIA by Joseph Van Bruaene March 2016 Thesis Co...CROSS-DRIVE CORRELATION OF DIGITAL MEDIA 5. FUNDING NUMBERS 6. AUTHOR(S) Joseph Van Bruaene 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...the ability to make large scale cross-drive correlations among a large corpus of digital media becomes increasingly important. We propose a

Isolating relativistic effects in large-scale structure

NASA Astrophysics Data System (ADS)

Bonvin, Camille

2014-12-01

We present a fully relativistic calculation of the observed galaxy number counts in the linear regime. We show that besides the density fluctuations and redshift-space distortions, various relativistic effects contribute to observations at large scales. These effects all have the same physical origin: they result from the fact that our coordinate system, namely the galaxy redshift and the incoming photons’ direction, is distorted by inhomogeneities in our Universe. We then discuss the impact of the relativistic effects on the angular power spectrum and on the two-point correlation function in configuration space. We show that the latter is very well adapted to isolate the relativistic effects since it naturally makes use of the symmetries of the different contributions. In particular, we discuss how the Doppler effect and the gravitational redshift distortions can be isolated by looking for a dipole in the cross-correlation function between a bright and a faint population of galaxies.

Statistical correlations in an ideal gas of particles obeying fractional exclusion statistics.

PubMed

Pellegrino, F M D; Angilella, G G N; March, N H; Pucci, R

2007-12-01

After a brief discussion of the concepts of fractional exchange and fractional exclusion statistics, we report partly analytical and partly numerical results on thermodynamic properties of assemblies of particles obeying fractional exclusion statistics. The effect of dimensionality is one focal point, the ratio mu/k_(B)T of chemical potential to thermal energy being obtained numerically as a function of a scaled particle density. Pair correlation functions are also presented as a function of the statistical parameter, with Friedel oscillations developing close to the fermion limit, for sufficiently large density.

On the distribution of local dissipation scales in turbulent flows

NASA Astrophysics Data System (ADS)

May, Ian; Morshed, Khandakar; Venayagamoorthy, Karan; Dasi, Lakshmi

2014-11-01

Universality of dissipation scales in turbulence relies on self-similar scaling and large scale independence. We show that the probability density function of dissipation scales, Q (η) , is analytically defined by the two-point correlation function, and the Reynolds number (Re). We also present a new analytical form for the two-point correlation function for the dissipation scales through a generalized definition of a directional Taylor microscale. Comparison of Q (η) predicted within this framework and published DNS data shows excellent agreement. It is shown that for finite Re no single similarity law exists even for the case of homogeneous isotropic turbulence. Instead a family of scaling is presented, defined by Re and a dimensionless local inhomogeneity parameter based on the spatial gradient of the rms velocity. For moderate Re inhomogeneous flows, we note a strong directional dependence of Q (η) dictated by the principal Reynolds stresses. It is shown that the mode of the distribution Q (η) significantly shifts to sub-Kolmogorov scales along the inhomogeneous directions, as in wall bounded turbulence. This work extends the classical Kolmogorov's theory to finite Re homogeneous isotropic turbulence as well as the case of inhomogeneous anisotropic turbulence.

Signatures of bifurcation on quantum correlations: Case of the quantum kicked top

NASA Astrophysics Data System (ADS)

Bhosale, Udaysinh T.; Santhanam, M. S.

2017-01-01

Quantum correlations reflect the quantumness of a system and are useful resources for quantum information and computational processes. Measures of quantum correlations do not have a classical analog and yet are influenced by classical dynamics. In this work, by modeling the quantum kicked top as a multiqubit system, the effect of classical bifurcations on measures of quantum correlations such as the quantum discord, geometric discord, and Meyer and Wallach Q measure is studied. The quantum correlation measures change rapidly in the vicinity of a classical bifurcation point. If the classical system is largely chaotic, time averages of the correlation measures are in good agreement with the values obtained by considering the appropriate random matrix ensembles. The quantum correlations scale with the total spin of the system, representing its semiclassical limit. In the vicinity of trivial fixed points of the kicked top, the scaling function decays as a power law. In the chaotic limit, for large total spin, quantum correlations saturate to a constant, which we obtain analytically, based on random matrix theory, for the Q measure. We also suggest that it can have experimental consequences.

Large-Angular-Scale Clustering as a Clue to the Source of UHECRs

NASA Astrophysics Data System (ADS)

Berlind, Andreas A.; Farrar, Glennys R.

We explore what can be learned about the sources of UHECRs from their large-angular-scale clustering (referred to as their "bias" by the cosmology community). Exploiting the clustering on large scales has the advantage over small-scale correlations of being insensitive to uncertainties in source direction from magnetic smearing or measurement error. In a Cold Dark Matter cosmology, the amplitude of large-scale clustering depends on the mass of the system, with more massive systems such as galaxy clusters clustering more strongly than less massive systems such as ordinary galaxies or AGN. Therefore, studying the large-scale clustering of UHECRs can help determine a mass scale for their sources, given the assumption that their redshift depth is as expected from the GZK cutoff. We investigate the constraining power of a given UHECR sample as a function of its cutoff energy and number of events. We show that current and future samples should be able to distinguish between the cases of their sources being galaxy clusters, ordinary galaxies, or sources that are uncorrelated with the large-scale structure of the universe.

Spatio-temporal coordination among functional residues in protein

NASA Astrophysics Data System (ADS)

Dutta, Sutapa; Ghosh, Mahua; Chakrabarti, J.

2017-01-01

The microscopic basis of communication among the functional sites in bio-macromolecules is a fundamental challenge in uncovering their functions. We study the communication through temporal cross-correlation among the binding sites. We illustrate via Molecular Dynamics simulations the properties of the temporal cross-correlation between the dihedrals of a small protein, ubiquitin which participates in protein degradation in eukaryotes. We show that the dihedral angles of the residues possess non-trivial temporal cross-correlations with asymmetry with respect to exchange of the dihedrals, having peaks at low frequencies with time scales in nano-seconds and an algebraic tail with a universal exponent for large frequencies. We show the existence of path for temporally correlated degrees of freedom among the functional residues. We explain the qualitative features of the cross-correlations through a general mathematical model. The generality of our analysis suggests that temporal cross-correlation functions may provide convenient theoretical framework to understand bio-molecular functions on microscopic basis.

Accelerating the two-point and three-point galaxy correlation functions using Fourier transforms

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2016-01-01

Though Fourier transforms (FTs) are a common technique for finding correlation functions, they are not typically used in computations of the anisotropy of the two-point correlation function (2PCF) about the line of sight in wide-angle surveys because the line-of-sight direction is not constant on the Cartesian grid. Here we show how FTs can be used to compute the multipole moments of the anisotropic 2PCF. We also show how FTs can be used to accelerate the 3PCF algorithm of Slepian & Eisenstein. In both cases, these FT methods allow one to avoid the computational cost of pair counting, which scales as the square of the number density of objects in the survey. With the upcoming large data sets of Dark Energy Spectroscopic Instrument, Euclid, and Large Synoptic Survey Telescope, FT techniques will therefore offer an important complement to simple pair or triplet counts.

Divergence of perturbation theory in large scale structures

NASA Astrophysics Data System (ADS)

Pajer, Enrico; van der Woude, Drian

2018-05-01

We make progress towards an analytical understanding of the regime of validity of perturbation theory for large scale structures and the nature of some non-perturbative corrections. We restrict ourselves to 1D gravitational collapse, for which exact solutions before shell crossing are known. We review the convergence of perturbation theory for the power spectrum, recently proven by McQuinn and White [1], and extend it to non-Gaussian initial conditions and the bispectrum. In contrast, we prove that perturbation theory diverges for the real space two-point correlation function and for the probability density function (PDF) of the density averaged in cells and all the cumulants derived from it. We attribute these divergences to the statistical averaging intrinsic to cosmological observables, which, even on very large and "perturbative" scales, gives non-vanishing weight to all extreme fluctuations. Finally, we discuss some general properties of non-perturbative effects in real space and Fourier space.

Low Temperature Properties for Correlation Functions in Classical N-Vector Spin Models

NASA Astrophysics Data System (ADS)

Balaban, Tadeusz; O'Carroll, Michael

We obtain convergent multi-scale expansions for the one-and two-point correlation functions of the low temperature lattice classical N- vector spin model in d>= 3 dimensions, N>= 2. The Gibbs factor is taken as where , , , are large and 0 < v<= 1. In the thermodynamic and limits, with h=e1, and Δ≡∂*∂, the expansion gives (spontaneous magnetization), , (Goldstone Bosons), , and , where , for some ρ > 0, and c0 is aprecisely determined constant.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

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.

Spatial correlations, clustering and percolation-like transitions in homicide crimes

NASA Astrophysics Data System (ADS)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

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

Dodge, D. A.; Harris, D. B.

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE PAGES

Dodge, D. A.; Harris, D. B.

2016-03-15

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

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.

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.

On the Validity of the Streaming Model for the Redshift-Space Correlation Function in the Linear Regime

NASA Astrophysics Data System (ADS)

Fisher, Karl B.

1995-08-01

The relation between the galaxy correlation functions in real-space and redshift-space is derived in the linear regime by an appropriate averaging of the joint probability distribution of density and velocity. The derivation recovers the familiar linear theory result on large scales but has the advantage of clearly revealing the dependence of the redshift distortions on the underlying peculiar velocity field; streaming motions give rise to distortions of θ(Ω0.6/b) while variations in the anisotropic velocity dispersion yield terms of order θ(Ω1.2/b2). This probabilistic derivation of the redshift-space correlation function is similar in spirit to the derivation of the commonly used "streaming" model, in which the distortions are given by a convolution of the real-space correlation function with a velocity distribution function. The streaming model is often used to model the redshift-space correlation function on small, highly nonlinear, scales. There have been claims in the literature, however, that the streaming model is not valid in the linear regime. Our analysis confirms this claim, but we show that the streaming model can be made consistent with linear theory provided that the model for the streaming has the functional form predicted by linear theory and that the velocity distribution is chosen to be a Gaussian with the correct linear theory dispersion.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Scaling properties of marathon races

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, Jose; Rodriguez, Eduardo

2006-06-01

Some regularities in popular marathon races are identified in this paper. It is found for high-performance participants (i.e., racing times in the range [2:15,3:15] h), the average velocity as a function of the marathoner's ranking behaves as a power-law, which may be suggesting the presence of critical phenomena. Elite marathoners with racing times below 2:15 h can be considered as outliers with respect to this behavior. For the main marathon pack (i.e., racing times in the range [3:00,6:00] h), the average velocity as a function of the marathoner's ranking behaves linearly. For this racing times, the interpersonal velocity, defined as the difference of velocities between consecutive runners, displays a continuum of scaling behavior ranging from uncorrelated noise for small scales to correlated 1/f-noise for large scales. It is a matter of fact that 1/f-noise is characterized by correlations extended over a wide range of scales, a clear indication of some sort of cooperative effect.

A Practical Computational Method for the Anisotropic Redshift-Space 3-Point Correlation Function

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2018-04-01

We present an algorithm enabling computation of the anisotropic redshift-space galaxy 3-point correlation function (3PCF) scaling as N2, with N the number of galaxies. Our previous work showed how to compute the isotropic 3PCF with this scaling by expanding the radially-binned density field around each galaxy in the survey into spherical harmonics and combining these coefficients to form multipole moments. The N2 scaling occurred because this approach never explicitly required the relative angle between a galaxy pair about the primary galaxy. Here we generalize this work, demonstrating that in the presence of azimuthally-symmetric anisotropy produced by redshift-space distortions (RSD) the 3PCF can be described by two triangle side lengths, two independent total angular momenta, and a spin. This basis for the anisotropic 3PCF allows its computation with negligible additional work over the isotropic 3PCF. We also present the covariance matrix of the anisotropic 3PCF measured in this basis. Our algorithm tracks the full 5-D redshift-space 3PCF, uses an accurate line of sight to each triplet, is exact in angle, and easily handles edge correction. It will enable use of the anisotropic large-scale 3PCF as a probe of RSD in current and upcoming large-scale redshift surveys.

Neural Systems Underlying Individual Differences in Intertemporal Decision-making.

PubMed

Elton, Amanda; Smith, Christopher T; Parrish, Michael H; Boettiger, Charlotte A

2017-03-01

Excessively choosing immediate over larger future rewards, or delay discounting (DD), associates with multiple clinical conditions. Individual differences in DD likely depend on variations in the activation of and functional interactions between networks, representing possible endophenotypes for associated disorders, including alcohol use disorders (AUDs). Numerous fMRI studies have probed the neural bases of DD, but investigations of large-scale networks remain scant. We addressed this gap by testing whether activation within large-scale networks during Now/Later decision-making predicts individual differences in DD. To do so, we scanned 95 social drinkers (18-40 years old; 50 women) using fMRI during hypothetical choices between small monetary amounts available "today" or larger amounts available later. We identified neural networks engaged during Now/Later choice using independent component analysis and tested the relationship between component activation and degree of DD. The activity of two components during Now/Later choice correlated with individual DD rates: A temporal lobe network positively correlated with DD, whereas a frontoparietal-striatal network negatively correlated with DD. Activation differences between these networks predicted individual differences in DD, and their negative correlation during Now/Later choice suggests functional competition. A generalized psychophysiological interactions analysis confirmed a decrease in their functional connectivity during decision-making. The functional connectivity of these two networks negatively correlates with alcohol-related harm, potentially implicating these networks in AUDs. These findings provide novel insight into the neural underpinnings of individual differences in impulsive decision-making with potential implications for addiction and related disorders in which impulsivity is a defining feature.

A quenched study of the Schrödinger functional with chirally rotated boundary conditions: Applications

NASA Astrophysics Data System (ADS)

González López, J.; Jansen, K.; Renner, D. B.; Shindler, A.

2013-02-01

In a previous paper (González López, et al., 2013) [1], we have discussed the non-perturbative tuning of the chirally rotated Schrödinger functional (χSF). This tuning is required to eliminate bulk O(a) cutoff effects in physical correlation functions. Using our tuning results obtained in González López et al. (2013) [1] we perform scaling and universality tests analyzing the residual O(a) cutoff effects of several step-scaling functions and we compute renormalization factors at the matching scale. As an example of possible application of the χSF we compute the renormalized strange quark mass using large volume data obtained from Wilson twisted mass fermions at maximal twist.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Nonmonotonic spatial structure of interneuronal correlations in prefrontal microcircuits

PubMed Central

Safavi, Shervin; Dwarakanath, Abhilash; Kapoor, Vishal; Werner, Joachim; Hatsopoulos, Nicholas G.; Logothetis, Nikos K.; Panagiotaropoulos, Theofanis I.

2018-01-01

Correlated fluctuations of single neuron discharges, on a mesoscopic scale, decrease as a function of lateral distance in early sensory cortices, reflecting a rapid spatial decay of lateral connection probability and excitation. However, spatial periodicities in horizontal connectivity and associational input as well as an enhanced probability of lateral excitatory connections in the association cortex could theoretically result in nonmonotonic correlation structures. Here, we show such a spatially nonmonotonic correlation structure, characterized by significantly positive long-range correlations, in the inferior convexity of the macaque prefrontal cortex. This functional connectivity kernel was more pronounced during wakefulness than anesthesia and could be largely attributed to the spatial pattern of correlated variability between functionally similar neurons during structured visual stimulation. These results suggest that the spatial decay of lateral functional connectivity is not a common organizational principle of neocortical microcircuits. A nonmonotonic correlation structure could reflect a critical topological feature of prefrontal microcircuits, facilitating their role in integrative processes. PMID:29588415

Fast Algorithms for Designing Unimodular Waveform(s) With Good Correlation Properties

NASA Astrophysics Data System (ADS)

Li, Yongzhe; Vorobyov, Sergiy A.

2018-03-01

In this paper, we develop new fast and efficient algorithms for designing single/multiple unimodular waveforms/codes with good auto- and cross-correlation or weighted correlation properties, which are highly desired in radar and communication systems. The waveform design is based on the minimization of the integrated sidelobe level (ISL) and weighted ISL (WISL) of waveforms. As the corresponding optimization problems can quickly grow to large scale with increasing the code length and number of waveforms, the main issue turns to be the development of fast large-scale optimization techniques. The difficulty is also that the corresponding optimization problems are non-convex, but the required accuracy is high. Therefore, we formulate the ISL and WISL minimization problems as non-convex quartic optimization problems in frequency domain, and then simplify them into quadratic problems by utilizing the majorization-minimization technique, which is one of the basic techniques for addressing large-scale and/or non-convex optimization problems. While designing our fast algorithms, we find out and use inherent algebraic structures in the objective functions to rewrite them into quartic forms, and in the case of WISL minimization, to derive additionally an alternative quartic form which allows to apply the quartic-quadratic transformation. Our algorithms are applicable to large-scale unimodular waveform design problems as they are proved to have lower or comparable computational burden (analyzed theoretically) and faster convergence speed (confirmed by comprehensive simulations) than the state-of-the-art algorithms. In addition, the waveforms designed by our algorithms demonstrate better correlation properties compared to their counterparts.

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

The Dynamical Balance of the Brain at Rest

PubMed Central

Deco, Gustavo; Corbetta, Maurizio

2014-01-01

We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530

Clustering in the SDSS Redshift Survey

NASA Astrophysics Data System (ADS)

Zehavi, I.; Blanton, M. R.; Frieman, J. A.; Weinberg, D. H.; SDSS Collaboration

2002-05-01

We present measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our current sample consists of roughly 80,000 galaxies with redshifts in the range 0.02 < z < 0.2, covering about 1200 square degrees. We measure the clustering in redshift space and in real space. The two-dimensional correlation function ξ (rp,π ) shows clear signatures of redshift distortions, both the small-scale ``fingers-of-God'' effect and the large-scale compression. The inferred real-space correlation function is well described by a power law. The SDSS is especially suitable for investigating the dependence of clustering on galaxy properties, due to the wealth of information in the photometric survey. We focus on the dependence of clustering on color and on luminosity.

Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform

NASA Astrophysics Data System (ADS)

Pando, Jesus

1997-10-01

The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)

Correlation function of the luminosity distances

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

Biern, Sang Gyu; Yoo, Jaiyul, E-mail: sgbiern@physik.uzh.ch, E-mail: jyoo@physik.uzh.ch

We present the correlation function of the luminosity distances in a flat ΛCDM universe. Decomposing the luminosity distance fluctuation into the velocity, the gravitational potential, and the lensing contributions in linear perturbation theory, we study their individual contributions to the correlation function. The lensing contribution is important at large redshift ( z ∼> 0.5) but only for small angular separation (θ ∼< 3°), while the velocity contribution dominates over the other contributions at low redshift or at larger separation. However, the gravitational potential contribution is always subdominant at all scale, if the correct gauge-invariant expression is used. The correlation functionmore » of the luminosity distances depends significantly on the matter content, especially for the lensing contribution, thus providing a novel tool of estimating cosmological parameters.« less

Spatial Correlation Function of the Chandra Selected Active Galactic Nuclei

NASA Technical Reports Server (NTRS)

Yang, Y.; Mushotzky, R. F.; Barger, A. J.; Cowie, L. L.

2006-01-01

We present the spatial correlation function analysis of non-stellar X-ray point sources in the Chandra Large Area Synoptic X-ray Survey of Lockman Hole Northwest (CLASXS). Our 9 ACIS-I fields cover a contiguous solid angle of 0.4 deg(exp 2) and reach a depth of 3 x 10(exp -15) erg/square cm/s in the 2-8 keV band. We supplement our analysis with data from the Chandra Deep Field North (CDFN). The addition of this field allows better probe of the correlation function at small scales. A total of 233 and 252 sources with spectroscopic information are used in the study of the CLASXS and CDFN fields respectively. We calculate both redshift-space and projected correlation functions in co-moving coordinates, averaged over the redshift range of 0.1 < z < 3.0, for both CLASXS and CDFN fields for a standard cosmology with Omega(sub Lambda) = 0.73,Omega(sub M) = 0.27, and h = 0.71 (H(sub 0) = 100h km/s Mpc(exp -1). The correlation function for the CLASXS field over scales of 3 Mpc< s < 200 Mpc can be modeled as a power-law of the form xi(s) = (S/SO)(exp - gamma), with gamma = 1.6(sup +0.4 sub -0.3) and S(sub o) = 8.0(sup +.14 sub -1.5) Mpc. The redshift-space correlation function for CDFN on scales of 1 Mpc< s < 100 Mpc is found to have a similar correlation length so = 8.55(sup +0.74 sub -0.74) Mpc, but a shallower slope (gamma = 1.3 +/- 0.1). The real-space correlation functions derived from the projected correlation functions, are found to be tau(sub 0 = 8.1(sup +1.2 sub -2.2) Mpc, and gamma = 2.1 +/- 0.5 for the CLASXS field, and tau(sub 0) = 5.8(sup +.1.0 sub -1.5) Mpc, gamma = 1.38(sup +0.12 sub -0.14 for the CDFN field. By comparing the real- and redshift-space correlation functions in the combined CLASXS and CDFN samples, we are able to estimate the redshift distortion parameter Beta = 0.4 +/- 0.2 at an effective redshift z = 0.94. We compare the correlation functions for hard and soft spectra sources in the CLASXS field and find no significant difference between the two groups. We have also found that the correlation between X-ray luminosity and clustering amplitude is weak, which, however, is fully consistent with the expectation using the simplest relations between X-ray luminosity, black hole mass, and dark halo mass. We study the evolution of the AGN clustering by dividing the samples into 4 redshift bins over 0.1 Mpc< z <3.0 Mpc. We find a very mild evolution in the clustering amplitude, which show the same evolution trend found in optically selected quasars in the 2dF survey. We estimate the evolution of the bias, and find that the bias increases rapidly with redshift (b(z = 0.45) = 0.95 +/- 0.15 and b(z = 2.07) = 3.03 +/- 0.83): The typical mass of the dark matter halo derived from the bias estimates show little change with redshift. The average halo mass is found to be log (M(sub halo)/M(sun))approximates 12.1. Subject headings: cosmology: observations - large-scale structure of the universe - x-rays: diffuse background - galaxies: nuclei

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

Parameter studies on the energy balance closure problem using large-eddy simulation

NASA Astrophysics Data System (ADS)

De Roo, Frederik; Banerjee, Tirtha; Mauder, Matthias

2017-04-01

The imbalance of the surface energy budget in eddy-covariance measurements is still a pending problem. A possible cause is the presence of land surface heterogeneity. Heterogeneities of the boundary layer scale or larger are most effective in influencing the boundary layer turbulence, and large-eddy simulations have shown that secondary circulations within the boundary layer can affect the surface energy budget. However, the precise influence of the surface characteristics on the energy imbalance and its partitioning is still unknown. To investigate the influence of surface variables on all the components of the flux budget under convective conditions, we set up a systematic parameter study by means of large-eddy simulation. For the study we use a virtual control volume approach, and we focus on idealized heterogeneity by considering spatially variable surface fluxes. The surface fluxes vary locally in intensity and these patches have different length scales. The main focus lies on heterogeneities of length scales of the kilometer scale and one decade smaller. For each simulation, virtual measurement towers are positioned at functionally different positions. We discriminate between the locally homogeneous towers, located within land use patches, with respect to the more heterogeneous towers, and find, among others, that the flux-divergence and the advection are strongly linearly related within each class. Furthermore, we seek correlators for the energy balance ratio and the energy residual in the simulations. Besides the expected correlation with measurable atmospheric quantities such as the friction velocity, boundary-layer depth and temperature and moisture gradients, we have also found an unexpected correlation with the temperature difference between sonic temperature and surface temperature. In additional simulations with a large number of virtual towers, we investigate higher order correlations, which can be linked to secondary circulations. In a companion presentation (EGU2017-2130) these correlations are investigated and confirmed with the help of micrometeorological measurements from the TERENO sites where the effects of landscape scale surface heterogeneities are deemed to be important.

Cold dark matter confronts the cosmic microwave background - Large-angular-scale anisotropies in Omega sub 0 + lambda 1 models

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Silk, Joseph; Vittorio, Nicola

1992-01-01

A new technique is used to compute the correlation function for large-angle cosmic microwave background anisotropies resulting from both the space and time variations in the gravitational potential in flat, vacuum-dominated, cold dark matter cosmological models. Such models with Omega sub 0 of about 0.2, fit the excess power, relative to the standard cold dark matter model, observed in the large-scale galaxy distribution and allow a high value for the Hubble constant. The low order multipoles and quadrupole anisotropy that are potentially observable by COBE and other ongoing experiments should definitively test these models.

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

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

Rosa, B., E-mail: bogdan.rosa@imgw.pl; Parishani, H.; Department of Earth System Science, University of California, Irvine, California 92697-3100

2015-01-15

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynoldsmore » number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.« less

Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2018-05-01

Spontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These "resting state networks" (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a nonstationary process which could be described as state switching. In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal. We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also report some interesting characteristics that clearly support nonstationary features in the data. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics. Copyright © 2018 Elsevier Inc. All rights reserved.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness.

PubMed

Naro, Antonino; Leo, Antonino; Manuli, Alfredo; Cannavò, Antonino; Bramanti, Alessia; Bramanti, Placido; Calabrò, Rocco Salvatore

2017-05-04

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

PubMed

Goya-Maldonado, Roberto; Brodmann, Katja; Keil, Maria; Trost, Sarah; Dechent, Peter; Gruber, Oliver

2016-02-01

Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Evaluation of the reliability and validity for X16 balance testing scale for the elderly.

PubMed

Ju, Jingjuan; Jiang, Yu; Zhou, Peng; Li, Lin; Ye, Xiaolei; Wu, Hongmei; Shen, Bin; Zhang, Jialei; He, Xiaoding; Niu, Chunjin; Xia, Qinghua

2018-05-10

Balance performance is considered as an indicator of functional status in the elderly, a large scale population screening and evaluation in the community context followed by proper interventions would be of great significance at public health level. However, there has been no suitable balance testing scale available for large scale studies in the unique community context of urban China. A balance scale named X16 balance testing scale was developed, which was composed of 3 domains and 16 items. A total of 1985 functionally independent and active community-dwelling elderly adults' balance abilities were tested using the X16 scale. The internal consistency, split-half reliability, content validity, construct validity, discriminant validity of X16 balance testing scale were evaluated. Factor analysis was performed to identify alternative factor structure. The Eigenvalues of factors 1, 2, and 3 were 8.53, 1.79, and 1.21, respectively, and their cumulative contribution to the total variance reached 72.0%. These 3 factors mainly represented domains static balance, postural stability, and dynamic balance. The Cronbach alpha coefficient for the scale was 0.933. The Spearman correlation coefficients between items and its corresponding domains were ranged from 0.538 to 0.964. The correlation coefficients between each item and its corresponding domain were higher than the coefficients between this item and other domains. With the increase of age, the scores of balance performance, domains static balance, postural stability, and dynamic balance in the elderly declined gradually (P < 0.001). With the increase of age, the proportion of the elderly with intact balance performance decreased gradually (P < 0.001). The reliability and validity of the X16 balance testing scale is both adequate and acceptable. Due to its simple and quick use features, it is practical to be used repeatedly and routinely especially in community setting and on large scale screening.

N-point statistics of large-scale structure in the Zel'dovich approximation

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

Tassev, Svetlin, E-mail: tassev@astro.princeton.edu

2014-06-01

Motivated by the results presented in a companion paper, here we give a simple analytical expression for the matter n-point functions in the Zel'dovich approximation (ZA) both in real and in redshift space (including the angular case). We present numerical results for the 2-dimensional redshift-space correlation function, as well as for the equilateral configuration for the real-space 3-point function. We compare those to the tree-level results. Our analysis is easily extendable to include Lagrangian bias, as well as higher-order perturbative corrections to the ZA. The results should be especially useful for modelling probes of large-scale structure in the linear regime,more » such as the Baryon Acoustic Oscillations. We make the numerical code used in this paper freely available.« less

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.

The formation of cosmic structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Gooding, Andrew K.; Park, Changbom; Spergel, David N.; Turok, Neil; Gott, Richard, III

1992-01-01

The growth of density fluctuations induced by global texture in an Omega = 1 cold dark matter (CDM) cosmogony is calculated. The resulting power spectra are in good agreement with each other, with more power on large scales than in the standard inflation plus CDM model. Calculation of related statistics (two-point correlation functions, mass variances, cosmic Mach number) indicates that the texture plus CDM model compares more favorably than standard CDM with observations of large-scale structure. Texture produces coherent velocity fields on large scales, as observed. Excessive small-scale velocity dispersions, and voids less empty than those observed may be remedied by including baryonic physics. The topology of the cosmic structure agrees well with observation. The non-Gaussian texture induced density fluctuations lead to earlier nonlinear object formation than in Gaussian models and may also be more compatible with recent evidence that the galaxy density field is non-Gaussian on large scales. On smaller scales the density field is strongly non-Gaussian, but this appears to be primarily due to nonlinear gravitational clustering. The velocity field on smaller scales is surprisingly Gaussian.

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

PubMed

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Determination of the Time-Space Magnetic Correlation Functions in the Solar Wind

NASA Astrophysics Data System (ADS)

Weygand, J. M.; Matthaeus, W. H.; Kivelson, M.; Dasso, S.

2013-12-01

Magnetic field data from many different intervals and 7 different solar wind spacecraft are employed to estimate the scale-dependent time decorrelation function in the interplanetary magnetic field in both the slow and fast solar wind. This estimation requires correlations varying with both space and time lags. The two point correlation function with no time lag is determined by correlating time series data from multiple spacecraft separated in space and for complete coverage of length scales relies on many intervals with different spacecraft spatial separations. In addition we employ single spacecraft time-lagged correlations, and two spacecraft time lagged correlations to access different spatial and temporal correlation data. Combining these data sets gives estimates of the scale-dependent time decorrelation function, which in principle tells us how rapidly time decorrelation occurs at a given wavelength. For static fields the scale-dependent time decorrelation function is trivially unity, but in turbulence the nonlinear cascade process induces time-decorrelation at a given length scale that occurs more rapidly with decreasing scale. The scale-dependent time decorrelation function is valuable input to theories as well as various applications such as scattering, transport, and study of predictability. It is also a fundamental element of formal turbulence theory. Our results are extension of the Eulerian correlation functions estimated in Matthaeus et al. [2010], Weygand et al [2012; 2013].

Pancreatitis Quality of Life Instrument: A Psychometric Evaluation.

PubMed

Wassef, Wahid; DeWitt, John; McGreevy, Kathleen; Wilcox, Mel; Whitcomb, David; Yadav, Dhiraj; Amann, Stephen; Mishra, Girish; Alkaade, Samer; Romagnuolo, Joseph; Stevens, Tyler; Vargo, John; Gardner, Timothy; Singh, Vikesh; Park, Walter; Hartigan, Celia; Barton, Bruce; Bova, Carol

2016-08-01

Chronic pancreatitis is a significant medical problem that impacts a large number of patients worldwide. In 2014, we developed a disease-specific instrument for the evaluation of quality of life in this group of patients: pancreatitis quality of life instrument (PANQOLI). The goal of this study was to evaluate its psychometric properties: its reliability and its construct validity. This is a cross-sectional multi-center study that involved 12 pancreatic disease centers. Patients who met the inclusion/exclusion criteria for chronic pancreatitis were invited to participate. Those who accepted were asked to complete seven questionnaires/instruments. Only patients who completed the PANQOLI were included in the study. Its reliability and its construct validity were tested. A total of 159 patients completed the PANQOLI and were included in the study. They had a mean age of 49.03, 49% were male, and 84% were Caucasian. Six of the 24 items on the scale were removed because of lack of inter-item correlation, redundancy, or lack of correlation to quality of life issues. The final 18-item scale had excellent reliability (Cronbach's alpha coefficient: 0.914) and excellent construct validity with good correlation to generic quality of life instruments (SF-12 and EORTC QLQ-C30/QLQ-PAN26) and lack of correlation to non-quality of life instruments (MAST and DAST). Through exploratory factor analysis, the PANQOLI was found to consist of four subscales: emotional function scale, role function scale, physical function scale, and "self-worth" scale. PANQOLI is the first disease-specific instrument to be developed and validated for the evaluation of quality of life in chronic pancreatitis patients. It has a unique subscale for "self-worth" that differentiates it from other generic instruments. Studies are currently under way to evaluate its use in other populations not included in this study.

Anisotropic magnification distortion of the 3D galaxy correlation. I. Real space

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

Hui, Lam; LoVerde, Marilena; Department of Physics, Columbia University, New York, New York 10027

2007-11-15

It has long been known that gravitational lensing, primarily via magnification bias, modifies the observed galaxy (or quasar) clustering. Such discussions have largely focused on the 2D angular correlation function. Here and in paper II [L. Hui, E. Gaztanaga, and M. LoVerde, arXiv:0710.4191] we explore how magnification bias distorts the 3D correlation function and power spectrum, as first considered by Matsubara [Astrophys. J. Lett. 537, L77 (2000).]. The interesting point is that the distortion is anisotropic. Magnification bias in general preferentially enhances the observed correlation in the line-of-sight (LOS) orientation, especially on large scales. For instance, at a LOS separationmore » of {approx}100 Mpc/h, where the intrinsic galaxy-galaxy correlation is rather weak, the observed correlation can be enhanced by lensing by a factor of a few, even at a modest redshift of z{approx}0.35. This effect presents an interesting opportunity as well as a challenge. The opportunity: this lensing anisotropy is distinctive, making it possible to separately measure the galaxy-galaxy, galaxy-magnification, and magnification-magnification correlations, without measuring galaxy shapes. The anisotropy is distinguishable from the well-known distortion due to peculiar motions, as will be discussed in paper II. The challenge: the magnification distortion of the galaxy correlation must be accounted for in interpreting data as precision improves. For instance, the {approx}100 Mpc/h baryon acoustic oscillation scale in the correlation function is shifted by up to {approx}3% in the LOS orientation, and up to {approx}0.6% in the monopole, depending on the galaxy bias, redshift, and number count slope. The corresponding shifts in the inferred Hubble parameter and angular diameter distance, if ignored, could significantly bias measurements of the dark energy equation of state. Lastly, magnification distortion offers a plausible explanation for the well-known excess correlations seen in pencil beam surveys.« less

Quasielastic charged-current neutrino scattering in the scaling model with relativistic effective mass

NASA Astrophysics Data System (ADS)

Ruiz Simo, I.; Martinez-Consentino, V. L.; Amaro, J. E.; Ruiz Arriola, E.

2018-06-01

We use a recent scaling analysis of the quasielastic electron scattering data from C 12 to predict the quasielastic charge-changing neutrino scattering cross sections within an uncertainty band. We use a scaling function extracted from a selection of the (e ,e') cross section data, and an effective nucleon mass inspired by the relativistic mean-field model of nuclear matter. The corresponding superscaling analysis with relativistic effective mass (SuSAM*) describes a large amount of the electron data lying inside a phenomenological quasielastic band. The effective mass incorporates the enhancement of the transverse current produced by the relativistic mean field. The scaling function incorporates nuclear effects beyond the impulse approximation, in particular meson-exchange currents and short-range correlations producing tails in the scaling function. Besides its simplicity, this model describes the neutrino data as reasonably well as other more sophisticated nuclear models.

Modelling the angular correlation function and its full covariance in photometric galaxy surveys

NASA Astrophysics Data System (ADS)

Crocce, Martín; Cabré, Anna; Gaztañaga, Enrique

2011-06-01

Near-future cosmology will see the advent of wide-area photometric galaxy surveys, such as the Dark Energy Survey (DES), that extend to high redshifts (z˜ 1-2) but give poor radial distance resolution. In such cases splitting the data into redshift bins and using the angular correlation function w(θ), or the Cℓ power spectrum, will become the standard approach to extracting cosmological information or to studying the nature of dark energy through the baryon acoustic oscillations (BAO) probe. In this work we present a detailed model for w(θ) at large scales as a function of redshift and binwidth, including all relevant effects, namely non-linear gravitational clustering, bias, redshift space distortions and photo-z uncertainties. We also present a model for the full covariance matrix, characterizing the angular correlation measurements, that takes into account the same effects as for w(θ) and also the possibility of a shot-noise component and partial sky coverage. Provided with a large-volume N-body simulation from the MICE collaboration, we built several ensembles of mock redshift bins with a sky coverage and depth typical of forthcoming photometric surveys. The model for the angular correlation and the one for the covariance matrix agree remarkably well with the mock measurements in all configurations. The prospects for a full shape analysis of w(θ) at BAO scales in forthcoming photometric surveys such as DES are thus very encouraging.

Intermittent electron density and temperature fluctuations and associated fluxes in the Alcator C-Mod scrape-off layer

NASA Astrophysics Data System (ADS)

Kube, R.; Garcia, O. E.; Theodorsen, A.; Brunner, D.; Kuang, A. Q.; LaBombard, B.; Terry, J. L.

2018-06-01

The Alcator C-Mod mirror Langmuir probe system has been used to sample data time series of fluctuating plasma parameters in the outboard mid-plane far scrape-off layer. We present a statistical analysis of one second long time series of electron density, temperature, radial electric drift velocity and the corresponding particle and electron heat fluxes. These are sampled during stationary plasma conditions in an ohmically heated, lower single null diverted discharge. The electron density and temperature are strongly correlated and feature fluctuation statistics similar to the ion saturation current. Both electron density and temperature time series are dominated by intermittent, large-amplitude burst with an exponential distribution of both burst amplitudes and waiting times between them. The characteristic time scale of the large-amplitude bursts is approximately 15 μ {{s}}. Large-amplitude velocity fluctuations feature a slightly faster characteristic time scale and appear at a faster rate than electron density and temperature fluctuations. Describing these time series as a superposition of uncorrelated exponential pulses, we find that probability distribution functions, power spectral densities as well as auto-correlation functions of the data time series agree well with predictions from the stochastic model. The electron particle and heat fluxes present large-amplitude fluctuations. For this low-density plasma, the radial electron heat flux is dominated by convection, that is, correlations of fluctuations in the electron density and radial velocity. Hot and dense blobs contribute only a minute fraction of the total fluctuation driven heat flux.

The correlation function of galaxy ellipticities produced by gravitational lensing

NASA Technical Reports Server (NTRS)

Miralda-Escude, Jordi

1991-01-01

The correlation of galaxy ellipticities produced by gravitational lensing is calculated as a function of the power spectrum of density fluctuations in the universe by generalizing an analytical method developed by Gunn (1967). The method is applied to a model where identical objects with spherically symmetric density profiles are randomly laid down in space, and to the cold dark matter model. The possibility of detecting this correlation is discussed. Although an ellipticity correlation can also be caused by an intrinsic alignment of the axes of galaxies belonging to a cluster or a supercluster, a method is suggested by which one type of correlation can be distinguished from another. The advantage of this ellipticity correlation is that it is one of the few astronomical observations that can directly probe large-scale mass fluctuations in the universe.

Dark matter, long-range forces, and large-scale structure

NASA Technical Reports Server (NTRS)

Gradwohl, Ben-Ami; Frieman, Joshua A.

1992-01-01

If the dark matter in galaxies and clusters is nonbaryonic, it can interact with additional long-range fields that are invisible to experimental tests of the equivalence principle. We discuss the astrophysical and cosmological implications of a long-range force coupled only to the dark matter and find rather tight constraints on its strength. If the force is repulsive (attractive), the masses of galaxy groups and clusters (and the mean density of the universe inferred from them) have been systematically underestimated (overestimated). We explore the consequent effects on the two-point correlation function, large-scale velocity flows, and microwave background anisotropies, for models with initial scale-invariant adiabatic perturbations and cold dark matter.

FROM FINANCE TO COSMOLOGY: THE COPULA OF LARGE-SCALE STRUCTURE

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

Scherrer, Robert J.; Berlind, Andreas A.; Mao, Qingqing

2010-01-01

Any multivariate distribution can be uniquely decomposed into marginal (one-point) distributions, and a function called the copula, which contains all of the information on correlations between the distributions. The copula provides an important new methodology for analyzing the density field in large-scale structure. We derive the empirical two-point copula for the evolved dark matter density field. We find that this empirical copula is well approximated by a Gaussian copula. We consider the possibility that the full n-point copula is also Gaussian and describe some of the consequences of this hypothesis. Future directions for investigation are discussed.

Redshift distortions of galaxy correlation functions

NASA Technical Reports Server (NTRS)

Fry, J. N.; Gaztanaga, Enrique

1994-01-01

To examine how peculiar velocities can affect the two-, three-, and four-point redshift correlation functions, we evaluate volume-average correlations for configurations that emphasize and minimize redshift distortions for four different volume-limited samples from each of the CfA, SSRS, and IRAS redshift catalogs. We present the results as the correlation length r(sub 0) and power index gamma of the two-point correlations, bar-xi(sub 0) = (r(sub 0)/r)(exp gamma), and as the hierarchical amplitudes of the three- and four-point functions, S(sub 3) = bar-xi(sub 3)/bar-xi(exp 2)(sub 2) and S(sub 4) = bar-xi(sub 4)/bar-xi(exp 3)(sub 2). We find a characteristic distortion for bar-xi(sub 2), the slope gamma is flatter and the correlation length is larger in redshift space than in real space; that is, redshift distortions 'move' correlations from small to large scales. At the largest scales (up to 12 Mpc), the extra power in the redshift distribution is compatible with Omega(exp 4/7)/b approximately equal to 1. We estimate Omega(exp 4/7)/b to be 0.53 +/- 0.15, 1.10 +/- 0.16, and 0.84 +/- 0.45 for the CfA, SSRS, and IRAS catalogs. Higher order correlations bar-xi(sub 3) and bar-xi(sub 4) suffer similar redshift distortions but in such a way that, within the accuracy of our ananlysis, the normalized amplitudes S(sub 3) and S(sub 4) are insensitive to this effect. The hierarchical amplitudes S(sub 3) and S(sub 4) are constant as a function of scale between 1 and 12 Mpc and have similar values in all samples and catalogs, S(sub 3) approximately equal to 2 and S(sub 4) approximately equal to 6, despite the fact that bar-xi(sub 2), bar-xi(sub 3), and bar-xi(sub 4) differ from one sample to another by large factors (up to a factor of 4 in bar-xi(sub 2), 8 for bar-xi(sub 3), and 12 for bar-xi(sub 4)). The agreement between the independent estimations of S(sub 3) and S(sub 4) is remarkable given the different criteria in the selection of galaxies and also the difference in the resulting range of densities, luminosities, and locations between samples.

Galaxy Clustering in Early Sloan Digital Sky Survey Redshift Data

NASA Astrophysics Data System (ADS)

Zehavi, Idit; Blanton, Michael R.; Frieman, Joshua A.; Weinberg, David H.; Mo, Houjun J.; Strauss, Michael A.; Anderson, Scott F.; Annis, James; Bahcall, Neta A.; Bernardi, Mariangela; Briggs, John W.; Brinkmann, Jon; Burles, Scott; Carey, Larry; Castander, Francisco J.; Connolly, Andrew J.; Csabai, Istvan; Dalcanton, Julianne J.; Dodelson, Scott; Doi, Mamoru; Eisenstein, Daniel; Evans, Michael L.; Finkbeiner, Douglas P.; Friedman, Scott; Fukugita, Masataka; Gunn, James E.; Hennessy, Greg S.; Hindsley, Robert B.; Ivezić, Željko; Kent, Stephen; Knapp, Gillian R.; Kron, Richard; Kunszt, Peter; Lamb, Donald Q.; Leger, R. French; Long, Daniel C.; Loveday, Jon; Lupton, Robert H.; McKay, Timothy; Meiksin, Avery; Merrelli, Aronne; Munn, Jeffrey A.; Narayanan, Vijay; Newcomb, Matt; Nichol, Robert C.; Owen, Russell; Peoples, John; Pope, Adrian; Rockosi, Constance M.; Schlegel, David; Schneider, Donald P.; Scoccimarro, Roman; Sheth, Ravi K.; Siegmund, Walter; Smee, Stephen; Snir, Yehuda; Stebbins, Albert; Stoughton, Christopher; SubbaRao, Mark; Szalay, Alexander S.; Szapudi, Istvan; Tegmark, Max; Tucker, Douglas L.; Uomoto, Alan; Vanden Berk, Dan; Vogeley, Michael S.; Waddell, Patrick; Yanny, Brian; York, Donald G.

2002-05-01

We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5700kms-1<=cz<=39,000kms-1, distributed in several long but narrow (2.5d-5°) segments, covering 690 deg2. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 h-1 Mpc. The two-dimensional correlation function ξ(rp,π) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, ξ(r)=(r/6.1+/-0.2h-1Mpc)-1.75+/-0.03, for 0.1h-1Mpc<=r<=16h-1Mpc. The galaxy pairwise velocity dispersion is σ12~600+/-100kms-1 for projected separations 0.15h-1Mpc<=rp<=5h-1Mpc. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r<~10h-1Mpc: subsamples with absolute magnitude ranges centered on M*-1.5, M*, and M*+1.5 have real-space correlation functions that are parallel power laws of slope ~-1.8 with correlation lengths of approximately 7.4, 6.3, and 4.7 h-1 Mpc, respectively.

Relation between functional mobility and dynapenia in institutionalized frail elderly.

PubMed

Soares, Antonio Vinicius; Marcelino, Elessandra; Maia, Késsia Cristina; Borges, Noé Gomes

2017-01-01

To investigate the relation between functional mobility and dynapenia in institutionalized frail elderly. A descriptive, correlational study involving 26 institutionalized elderly men and women, mean age 82.3±6 years. The instruments employed were the Mini Mental State Examination, the Geriatric Depression Scale, the International Physical Activity Questionnaire, the Timed Up and Go test, a handgrip dynamometer and a portable dynamometer for large muscle groups (shoulder, elbow and hip flexors, knee extensors and ankle dorsiflexors). Significant negative correlation between functional mobility levels assessed by the Timed Up and Go test and dynapenia was observed in all muscle groups evaluated, particularly in knee extensors (r -0.65). A significant negative correlation between muscle strength, particularly knee extensor strength, and functional mobility was found in institutionalized elderly. Data presented indicate that the higher the muscle strength, the shorter the execution time, and this could demonstrate better performance in this functional mobility test.

Large scale structure in universes dominated by cold dark matter

NASA Technical Reports Server (NTRS)

Bond, J. Richard

1986-01-01

The theory of Gaussian random density field peaks is applied to a numerical study of the large-scale structure developing from adiabatic fluctuations in models of biased galaxy formation in universes with Omega = 1, h = 0.5 dominated by cold dark matter (CDM). The angular anisotropy of the cross-correlation function demonstrates that the far-field regions of cluster-scale peaks are asymmetric, as recent observations indicate. These regions will generate pancakes or filaments upon collapse. One-dimensional singularities in the large-scale bulk flow should arise in these CDM models, appearing as pancakes in position space. They are too rare to explain the CfA bubble walls, but pancakes that are just turning around now are sufficiently abundant and would appear to be thin walls normal to the line of sight in redshift space. Large scale streaming velocities are significantly smaller than recent observations indicate. To explain the reported 700 km/s coherent motions, mass must be significantly more clustered than galaxies with a biasing factor of less than 0.4 and a nonlinear redshift at cluster scales greater than one for both massive neutrino and cold models.

Brief Report: Concurrent Validity of the Leiter-R and KBIT-2 Scales of Nonverbal Intelligence for Children with Autism and Language Impairments

ERIC Educational Resources Information Center

Scattone, Dorothy; Raggio, Donald J.; May, Warren

2012-01-01

The concurrent validity of the KBIT-2 Nonverbal IQ and Leiter-R Brief IQ was evaluated for two groups of children: those with high functioning autism and those with language impairments without autism. Fifty-three children between the ages of 4 and 13 years of age participated in the study. The correlation between the scales was large (r = 0.62)…

Galaxy clustering and the origin of large-scale flows

NASA Technical Reports Server (NTRS)

Juszkiewicz, R.; Yahil, A.

1989-01-01

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses.

PubMed

Ogawa, Takeshi; Aihara, Takatsugu; Shimokawa, Takeaki; Yamashita, Okito

2018-04-24

Creative insight occurs with an "Aha!" experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21-69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Modeling velocity space-time correlations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2016-11-01

Turbulent fluctuations of wind velocities cause power-output fluctuations in wind farms. The statistics of velocity fluctuations can be described by velocity space-time correlations in the atmospheric boundary layer. In this context, it is important to derive simple physics-based models. The so-called Tennekes-Kraichnan random sweeping hypothesis states that small-scale velocity fluctuations are passively advected by large-scale velocity perturbations in a random fashion. In the present work, this hypothesis is used with an additional mean wind velocity to derive a model for the spatial and temporal decorrelation of velocities in wind farms. It turns out that in the framework of this model, space-time correlations are a convolution of the spatial correlation function with a temporal decorrelation kernel. In this presentation, first results on the comparison to large eddy simulations will be presented and the potential of the approach to characterize power output fluctuations of wind farms will be discussed. Acknowledgements: 'Fellowships for Young Energy Scientists' (YES!) of FOM, the US National Science Foundation Grant IIA 1243482, and support by the Max Planck Society.

Large Scale Structure Studies: Final Results from a Rich Cluster Redshift Survey

NASA Astrophysics Data System (ADS)

Slinglend, K.; Batuski, D.; Haase, S.; Hill, J.

1995-12-01

The results from the COBE satellite show the existence of structure on scales on the order of 10% or more of the horizon scale of the universe. Rich clusters of galaxies from the Abell-ACO catalogs show evidence of structure on scales of 100 Mpc and hold the promise of confirming structure on the scale of the COBE result. Unfortunately, until now, redshift information has been unavailable for a large percentage of these clusters, so present knowledge of their three dimensional distribution has quite large uncertainties. Our approach in this effort has been to use the MX multifiber spectrometer on the Steward 2.3m to measure redshifts of at least ten galaxies in each of 88 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8 (estimated z<= 0.12) and zero or one measured redshifts. This work has resulted in a deeper, 95% complete and more reliable sample of 3-D positions of rich clusters. The primary intent of this survey has been to constrain theoretical models for the formation of the structure we see in the universe today through 2-pt. spatial correlation function and other analyses of the large scale structures traced by these clusters. In addition, we have obtained enough redshifts per cluster to greatly improve the quality and size of the sample of reliable cluster velocity dispersions available for use in other studies of cluster properties. This new data has also allowed the construction of an updated and more reliable supercluster candidate catalog. Our efforts have resulted in effectively doubling the volume traced by these clusters. Presented here is the resulting 2-pt. spatial correlation function, as well as density plots and several other figures quantifying the large scale structure from this much deeper and complete sample. Also, with 10 or more redshifts in most of our cluster fields, we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.

Understanding the origins of uncertainty in landscape-scale variations of emissions of nitrous oxide

NASA Astrophysics Data System (ADS)

Milne, Alice; Haskard, Kathy; Webster, Colin; Truan, Imogen; Goulding, Keith

2014-05-01

Nitrous oxide is a potent greenhouse gas which is over 300 times more radiatively effective than carbon dioxide. In the UK, the agricultural sector is estimated to be responsible for over 80% of nitrous oxide emissions, with these emissions resulting from livestock and farmers adding nitrogen fertilizer to soils. For the purposes of reporting emissions to the IPCC, the estimates are calculated using simple models whereby readily-available national or international statistics are combined with IPCC default emission factors. The IPCC emission factor for direct emissions of nitrous oxide from soils has a very large uncertainty. This is primarily because the variability of nitrous oxide emissions in space is large and this results in uncertainty that may be regarded as sample noise. To both reduce uncertainty through improved modelling, and to communicate an understanding of this uncertainty, we must understand the origins of the variation. We analysed data on nitrous oxide emission rate and some other soil properties collected from a 7.5-km transect across contrasting land uses and parent materials in eastern England. We investigated the scale-dependence and spatial uniformity of the correlations between soil properties and emission rates from farm to landscape scale using wavelet analysis. The analysis revealed a complex pattern of scale-dependence. Emission rates were strongly correlated with a process-specific function of the water-filled pore space at the coarsest scale and nitrate at intermediate and coarsest scales. We also found significant correlations between pH and emission rates at the intermediate scales. The wavelet analysis showed that these correlations were not spatially uniform and that at certain scales changes in parent material coincided with significant changes in correlation. Our results indicate that, at the landscape scale, nitrate content and water-filled pore space are key soil properties for predicting nitrous oxide emissions and should therefore be incorporated into process models and emission factors for inventory calculations.

Calculating the n-point correlation function with general and efficient python code

NASA Astrophysics Data System (ADS)

Genier, Fred; Bellis, Matthew

2018-01-01

There are multiple approaches to understanding the evolution of large-scale structure in our universe and with it the role of baryonic matter, dark matter, and dark energy at different points in history. One approach is to calculate the n-point correlation function estimator for galaxy distributions, sometimes choosing a particular type of galaxy, such as luminous red galaxies. The standard way to calculate these estimators is with pair counts (for the 2-point correlation function) and with triplet counts (for the 3-point correlation function). These are O(n2) and O(n3) problems, respectively and with the number of galaxies that will be characterized in future surveys, having efficient and general code will be of increasing importance. Here we show a proof-of-principle approach to the 2-point correlation function that relies on pre-calculating galaxy locations in coarse “voxels”, thereby reducing the total number of necessary calculations. The code is written in python, making it easily accessible and extensible and is open-sourced to the community. Basic results and performance tests using SDSS/BOSS data will be shown and we discuss the application of this approach to the 3-point correlation function.

Optical correlator using very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators

NASA Technical Reports Server (NTRS)

Turner, Richard M.; Jared, David A.; Sharp, Gary D.; Johnson, Kristina M.

1993-01-01

The use of 2-kHz 64 x 64 very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators as the input and filter planes of a VanderLugt-type optical correlator is discussed. Liquid-crystal layer thickness variations that are present in the devices are analyzed, and the effects on correlator performance are investigated through computer simulations. Experimental results from the very-large-scale-integrated / ferroelectric-liquid-crystal optical-correlator system are presented and are consistent with the level of performance predicted by the simulations.

Time-localized wavelet multiple regression and correlation

NASA Astrophysics Data System (ADS)

Fernández-Macho, Javier

2018-02-01

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

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Quadratic integrand double-hybrid made spin-component-scaled

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

Brémond, Éric, E-mail: eric.bremond@iit.it; Savarese, Marika; Sancho-García, Juan C.

2016-03-28

We propose two analytical expressions aiming to rationalize the spin-component-scaled (SCS) and spin-opposite-scaled (SOS) schemes for double-hybrid exchange-correlation density-functionals. Their performances are extensively tested within the framework of the nonempirical quadratic integrand double-hybrid (QIDH) model on energetic properties included into the very large GMTKN30 benchmark database, and on structural properties of semirigid medium-sized organic compounds. The SOS variant is revealed as a less computationally demanding alternative to reach the accuracy of the original QIDH model without losing any theoretical background.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity.

PubMed

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2014-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. © 2013.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity

PubMed Central

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2013-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. PMID:24071524

Romanticism as a function of age, sex, and ethnicity.

PubMed

Regan, Pamela C; Anguiano, Carlos

2010-12-01

This study examined the association between romanticism (operationalized as mean score on the Romantic Beliefs Scale) and age, sex, and ethnicity in a large community sample (N = 436). Age was negatively correlated with romanticism scores; as age increased, romanticism scores decreased. No sex differences were found; men and women had similar, moderate scores. Although ethnicity largely was unrelated to romanticism, Asian/Pacific Islander participants were significantly more romantic than were African-American participants.

Gravity at the horizon: on relativistic effects, CMB-LSS correlations and ultra-large scales in Horndeski's theory

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

Renk, Janina; Zumalacárregui, Miguel; Montanari, Francesco, E-mail: renk@thphys.uni-heidelberg.de, E-mail: miguel.zumalacarregui@nordita.org, E-mail: francesco.montanari@helsinki.fi

2016-07-01

We address the impact of consistent modifications of gravity on the largest observable scales, focusing on relativistic effects in galaxy number counts and the cross-correlation between the matter large scale structure (LSS) distribution and the cosmic microwave background (CMB). Our analysis applies to a very broad class of general scalar-tensor theories encoded in the Horndeski Lagrangian and is fully consistent on linear scales, retaining the full dynamics of the scalar field and not assuming quasi-static evolution. As particular examples we consider self-accelerating Covariant Galileons, Brans-Dicke theory and parameterizations based on the effective field theory of dark energy, using the himore » class code to address the impact of these models on relativistic corrections to LSS observables. We find that especially effects which involve integrals along the line of sight (lensing convergence, time delay and the integrated Sachs-Wolfe effect—ISW) can be considerably modified, and even lead to O(1000%) deviations from General Relativity in the case of the ISW effect for Galileon models, for which standard probes such as the growth function only vary by O(10%). These effects become dominant when correlating galaxy number counts at different redshifts and can lead to ∼ 50% deviations in the total signal that might be observable by future LSS surveys. Because of their integrated nature, these deep-redshift cross-correlations are sensitive to modifications of gravity even when probing eras much before dark energy domination. We further isolate the ISW effect using the cross-correlation between LSS and CMB temperature anisotropies and use current data to further constrain Horndeski models. Forthcoming large-volume galaxy surveys using multiple-tracers will search for all these effects, opening a new window to probe gravity and cosmic acceleration at the largest scales available in our universe.« less

Large-scale DCMs for resting-state fMRI.

PubMed

Razi, Adeel; Seghier, Mohamed L; Zhou, Yuan; McColgan, Peter; Zeidman, Peter; Park, Hae-Jeong; Sporns, Olaf; Rees, Geraint; Friston, Karl J

2017-01-01

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity . This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

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

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

Ko, L.F.

Calculations for the two-point correlation functions in the scaling limit for two statistical models are presented. In Part I, the Ising model with a linear defect is studied for T < T/sub c/ and T > T/sub c/. The transfer matrix method of Onsager and Kaufman is used. The energy-density correlation is given by functions related to the modified Bessel functions. The dispersion expansion for the spin-spin correlation functions are derived. The dominant behavior for large separations at T not equal to T/sub c/ is extracted. It is shown that these expansions lead to systems of Fredholm integral equations. Inmore » Part II, the electric correlation function of the eight-vertex model for T < T/sub c/ is studied. The eight vertex model decouples to two independent Ising models when the four spin coupling vanishes. To first order in the four-spin coupling, the electric correlation function is related to a three-point function of the Ising model. This relation is systematically investigated and the full dispersion expansion (to first order in four-spin coupling) is obtained. The results is a new kind of structure which, unlike those of many solvable models, is apparently not expressible in terms of linear integral equations.« less

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale

PubMed Central

Groarke, Jenny M.; Hogan, Michael J.

2018-01-01

Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML) and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants (N = 1,191, 17–66 years, M = 22.04, SD = 6.23, 326 males). Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML) scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity, and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML—the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross-sectional studies. PMID:29706916

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale.

PubMed

Groarke, Jenny M; Hogan, Michael J

2018-01-01

Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML) and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants ( N = 1,191, 17-66 years, M = 22.04, SD = 6.23, 326 males). Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML) scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity , and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML-the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross-sectional studies.

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

Scale-dependent cyclone-anticyclone asymmetry in a forced rotating turbulence experiment

NASA Astrophysics Data System (ADS)

Gallet, B.; Campagne, A.; Cortet, P.-P.; Moisy, F.

2014-03-01

We characterize the statistical and geometrical properties of the cyclone-anticyclone asymmetry in a statistically steady forced rotating turbulence experiment. Turbulence is generated by a set of vertical flaps which continuously inject velocity fluctuations towards the center of a tank mounted on a rotating platform. We first characterize the cyclone-anticyclone asymmetry from conventional single-point vorticity statistics. We propose a phenomenological model to explain the emergence of the asymmetry in the experiment, from which we predict scaling laws for the root-mean-square velocity in good agreement with the experimental data. We further quantify the cyclone-anticyclone asymmetry using a set of third-order two-point velocity correlations. We focus on the correlations which are nonzero only if the cyclone-anticyclone symmetry is broken. They offer two advantages over single-point vorticity statistics: first, they are defined from velocity measurements only, so an accurate resolution of the Kolmogorov scale is not required; second, they provide information on the scale-dependence of the cyclone-anticyclone asymmetry. We compute these correlation functions analytically for a random distribution of independent identical vortices. These model correlations describe well the experimental ones, indicating that the cyclone-anticyclone asymmetry is dominated by the large-scale long-lived cyclones.

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

NASA Astrophysics Data System (ADS)

Guesalaga, A.; Neichel, B.; Correia, C. M.; Butterley, T.; Osborn, J.; Masciadri, E.; Fusco, T.; Sauvage, J.-F.

2017-02-01

We describe an online method to estimate the wavefront outer scale profile, L0(h), for very large and future extremely large telescopes. The stratified information on this parameter impacts the estimation of the main turbulence parameters [turbulence strength, Cn2(h); Fried's parameter, r0; isoplanatic angle, θ0; and coherence time, τ0) and determines the performance of wide-field adaptive optics (AO) systems. This technique estimates L0(h) using data from the AO loop available at the facility instruments by constructing the cross-correlation functions of the slopes between two or more wavefront sensors, which are later fitted to a linear combination of the simulated theoretical layers having different altitudes and outer scale values. We analyse some limitations found in the estimation process: (I) its insensitivity to large values of L0(h) as the telescope becomes blind to outer scales larger than its diameter; (II) the maximum number of observable layers given the limited number of independent inputs that the cross-correlation functions provide and (III) the minimum length of data required for a satisfactory convergence of the turbulence parameters without breaking the assumption of statistical stationarity of the turbulence. The method is applied to the Gemini South multiconjugate AO system that comprises five wavefront sensors and two deformable mirrors. Statistics of L0(h) at Cerro Pachón from data acquired during 3 yr of campaigns show interesting resemblance to other independent results in the literature. A final analysis suggests that the impact of error sources will be substantially reduced in instruments of the next generation of giant telescopes.

The impact of galaxy formation on satellite kinematics and redshift-space distortions

NASA Astrophysics Data System (ADS)

Orsi, Álvaro A.; Angulo, Raúl E.

2018-04-01

Galaxy surveys aim to map the large-scale structure of the Universe and use redshift-space distortions to constrain deviations from general relativity and probe the existence of massive neutrinos. However, the amount of information that can be extracted is limited by the accuracy of theoretical models used to analyse the data. Here, by using the L-Galaxies semi-analytical model run over the Millennium-XXL N-body simulation, we assess the impact of galaxy formation on satellite kinematics and the theoretical modelling of redshift-space distortions. We show that different galaxy selection criteria lead to noticeable differences in the radial distributions and velocity structure of satellite galaxies. Specifically, whereas samples of stellar mass selected galaxies feature satellites that roughly follow the dark matter, emission line satellite galaxies are located preferentially in the outskirts of haloes and display net infall velocities. We demonstrate that capturing these differences is crucial for modelling the multipoles of the correlation function in redshift space, even on large scales. In particular, we show how modelling small-scale velocities with a single Gaussian distribution leads to a poor description of the measured clustering. In contrast, we propose a parametrization that is flexible enough to model the satellite kinematics and that leads to an accurate description of the correlation function down to sub-Mpc scales. We anticipate that our model will be a necessary ingredient in improved theoretical descriptions of redshift-space distortions, which together could result in significantly tighter cosmological constraints and a more optimal exploitation of future large data sets.

Effective correlator for RadioAstron project

NASA Astrophysics Data System (ADS)

Sergeev, Sergey

This paper presents the implementation of programme FX-correlator for Very Long Baseline Interferometry, adapted for the project "RadioAstron". Software correlator implemented for heterogeneous computing systems using graphics accelerators. It is shown that for the task interferometry implementation of the graphics hardware has a high efficiency. The host processor of heterogeneous computing system, performs the function of forming the data flow for graphics accelerators, the number of which corresponds to the number of frequency channels. So, for the Radioastron project, such channels is seven. Each accelerator is perform correlation matrix for all bases for a single frequency channel. Initial data is converted to the floating-point format, is correction for the corresponding delay function and computes the entire correlation matrix simultaneously. Calculation of the correlation matrix is performed using the sliding Fourier transform. Thus, thanks to the compliance of a solved problem for architecture graphics accelerators, managed to get a performance for one processor platform Kepler, which corresponds to the performance of this task, the computing cluster platforms Intel on four nodes. This task successfully scaled not only on a large number of graphics accelerators, but also on a large number of nodes with multiple accelerators.

Reduced Global Functional Connectivity of the Medial Prefrontal Cortex in Major Depressive Disorder

PubMed Central

Murrough, James W.; Abdallah, Chadi G.; Anticevic, Alan; Collins, Katherine A.; Geha, Paul; Averill, Lynnette A.; Schwartz, Jaclyn; DeWilde, Kaitlin E.; Averill, Christopher; Yang, Genevieve Jia-wei; Wong, Edmund; Tang, Cheuk Y.; Krystal, John H.; Iosifescu, Dan V.; Charney, Dennis S.

2016-01-01

Background Major depressive disorder is a disabling neuropsychiatric condition that is associated with disrupted functional connectivity across brain networks. The precise nature of altered connectivity, however, remains incompletely understood. The current study was designed to examine the coherence of large-scale connectivity in depression using a recently developed technique termed global brain connectivity. Methods A total of 82 subjects, including medication-free patients with major depression (n=57) and healthy volunteers (n=25) underwent functional magnetic resonance imaging with resting data acquisition for functional connectivity analysis. Global brain connectivity was computed as the mean of each voxel’s time series correlation with every other voxel and compared between study groups. Relationships between global connectivity and depressive symptom severity measured using the Montgomery-Åsberg Depression Rating Scale were examined by means of linear correlation. Results Relative to the healthy group, patients with depression evidenced reduced global connectivity bilaterally within multiple regions of medial and lateral prefrontal cortex. The largest between-group difference was observed within the right subgenual anterior cingulate cortex, extending into ventromedial prefrontal cortex bilaterally (Hedges’ g = −1.48, p<0.000001). Within the depressed group, patients with the lowest connectivity evidenced the highest symptom severity within ventromedial prefrontal cortex (r = −0.47, p=0.0005). Conclusions Patients with major depressive evidenced abnormal large-scale functional coherence in the brain that was centered within the subgenual cingulate cortex, and medial prefrontal cortex more broadly. These data extend prior studies of connectivity in depression and demonstrate that functional disconnection of the medial prefrontal cortex is a key pathological feature of the disorder. PMID:27144347

Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778

Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy.

PubMed

de Campos, Brunno Machado; Coan, Ana Carolina; Lin Yasuda, Clarissa; Casseb, Raphael Fernandes; Cendes, Fernando

2016-09-01

Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Disrupted coupling of large-scale networks is associated with relapse behaviour in heroin-dependent men

PubMed Central

Li, Qiang; Liu, Jierong; Wang, Wei; Wang, Yarong; Li, Wei; Chen, Jiajie; Zhu, Jia; Yan, Xuejiao; Li, Yongbin; Li, Zhe; Ye, Jianjun; Wang, Wei

2018-01-01

Background It is unknown whether impaired coupling among 3 core large-scale brain networks (salience [SN], default mode [DMN] and executive control networks [ECN]) is associated with relapse behaviour in treated heroin-dependent patients. Methods We conducted a prospective resting-state functional MRI study comparing the functional connectivity strength among healthy controls and heroin-dependent men who had either relapsed or were in early remission. Men were considered to be either relapsed or in early remission based on urine drug screens during a 3-month follow-up period. We also examined how the coupling of large-scale networks correlated with relapse behaviour among heroin-dependent men. Results We included 20 controls and 50 heroin-dependent men (26 relapsed and 24 early remission) in our analyses. The relapsed men showed greater connectivity than the early remission and control groups between the dorsal anterior cingulate cortex (key node of the SN) and the dorsomedial prefrontal cortex (included in the DMN). The relapsed men and controls showed lower connectivity than the early remission group between the left dorsolateral prefrontal cortex (key node of the left ECN) and the dorsomedial prefrontal cortex. The percentage of positive urine drug screens positively correlated with the coupling between the dorsal anterior cingulate cortex and dorsomedial prefrontal cortex, but negatively correlated with the coupling between the left dorsolateral prefrontal cortex and dorsomedial prefrontal cortex. Limitations We examined deficits in only 3 core networks leading to relapse behaviour. Other networks may also contribute to relapse. Conclusion Greater coupling between the SN and DMN and lower coupling between the left ECN and DMN is associated with relapse behaviour. These findings may shed light on the development of new treatments for heroin addiction. PMID:29252165

{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.

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.

Activity-based protein profiling for biochemical pathway discovery in cancer

PubMed Central

Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.

2011-01-01

Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252

Scaling Theory of Entanglement at the Many-Body Localization Transition.

PubMed

Dumitrescu, Philipp T; Vasseur, Romain; Potter, Andrew C

2017-09-15

We study the universal properties of eigenstate entanglement entropy across the transition between many-body localized (MBL) and thermal phases. We develop an improved real space renormalization group approach that enables numerical simulation of large system sizes and systematic extrapolation to the infinite system size limit. For systems smaller than the correlation length, the average entanglement follows a subthermal volume law, whose coefficient is a universal scaling function. The full distribution of entanglement follows a universal scaling form, and exhibits a bimodal structure that produces universal subleading power-law corrections to the leading volume law. For systems larger than the correlation length, the short interval entanglement exhibits a discontinuous jump at the transition from fully thermal volume law on the thermal side, to pure area law on the MBL side.

The role of large scale motions on passive scalar transport

NASA Astrophysics Data System (ADS)

Dharmarathne, Suranga; Araya, Guillermo; Tutkun, Murat; Leonardi, Stefano; Castillo, Luciano

2014-11-01

We study direct numerical simulation (DNS) of turbulent channel flow at Reτ = 394 to investigate effect of large scale motions on fluctuating temperature field which forms a passive scalar field. Statistical description of the large scale features of the turbulent channel flow is obtained using two-point correlations of velocity components. Two-point correlations of fluctuating temperature field is also examined in order to identify possible similarities between velocity and temperature fields. The two-point cross-correlations betwen the velocity and temperature fluctuations are further analyzed to establish connections between these two fields. In addition, we use proper orhtogonal decompotion (POD) to extract most dominant modes of the fields and discuss the coupling of large scale features of turbulence and the temperature field.

Signatures of large-scale and local climates on the demography of white-tailed ptarmigan in Rocky Mountain National Park, Colorado, USA.

PubMed

Wang, Guiming; Hobbs, N Thompson; Galbraith, Hector; Giesen, Kenneth M

2002-09-01

Global climate change may impact wildlife populations by affecting local weather patterns, which, in turn, can impact a variety of ecological processes. However, it is not clear that local variations in ecological processes can be explained by large-scale patterns of climate. The North Atlantic oscillation (NAO) is a large-scale climate phenomenon that has been shown to influence the population dynamics of some animals. Although effects of the NAO on vertebrate population dynamics have been studied, it remains uncertain whether it broadly predicts the impact of weather on species. We examined the ability of local weather data and the NAO to explain the annual variation in population dynamics of white-tailed ptarmigan ( Lagopus leucurus) in Rocky Mountain National Park, USA. We performed canonical correlation analysis on the demographic subspace of ptarmigan and local-climate subspace defined by the empirical orthogonal function (EOF) using data from 1975 to 1999. We found that two subspaces were significantly correlated on the first canonical variable. The Pearson correlation coefficient of the first EOF values of the demographic and local-climate subspaces was significant. The population density and the first EOF of local-climate subspace influenced the ptarmigan population with 1-year lags in the Gompertz model. However, the NAO index was neither related to the first two EOF of local-climate subspace nor to the first EOF of the demographic subspace of ptarmigan. Moreover, the NAO index was not a significant term in the Gompertz model for the ptarmigan population. Therefore, local climate had stronger signature on the demography of ptarmigan than did a large-scale index, i.e., the NAO index. We conclude that local responses of wildlife populations to changing climate may not be adequately explained by models that project large-scale climatic patterns.

To the horizon and beyond: Weak lensing of the CMB and binary inspirals into horizonless objects

NASA Astrophysics Data System (ADS)

Kesden, Michael

This thesis examines two predictions of general relativity: weak lensing and gravitational waves. The cosmic microwave background (CMB) is gravitationally lensed by the large-scale structure between the observer and the last- scattering surface. This weak lensing induces non-Gaussian correlations that can be used to construct estimators for the deflection field. The error and bias of these estimators are derived and used to analyze the viability of lensing reconstruction for future CMB experiments. Weak lensing also affects the one-point probability distribution function of the CMB. The skewness and kurtosis induced by lensing and the Sunayev- Zel'dovich (SZ) effect are calculated as functions of the angular smoothing scale of the map. While these functions offer the advantage of easy computability, only the skewness from lensing-SZ correlations can potentially be detected, even in the limit of the largest amplitude fluctuations allowed by observation. Lensing estimators are also essential to constrain inflation, the favored explanation for large-scale isotropy and the origin of primordial perturbations. B-mode polarization is considered to be a "smoking-gun" signature of inflation, and lensing estimators can be used to recover primordial B-modes from lensing-induced contamination. The ability of future CMB experiments to constrain inflation is assessed as functions of survey size and instrumental sensitivity. A final application of lensing estimators is to constrain a possible cutoff in primordial density perturbations on near-horizon scales. The paucity of independent modes on such scales limits the statistical certainty of such a constraint. Measurements of the deflection field can be used to constrain at the 3s level the existence of a cutoff large enough to account for current CMB observations. A final chapter of this thesis considers an independent topic: the gravitational-wave (GW) signature of a binary inspiral into a horizonless object. If the supermassive objects at galactic centers lack the horizons of traditional black holes, inspiraling objects could emit GWs after passing within their surfaces. The GWs produced by such an inspiral are calculated, revealing distinctive features potentially observable by future GW observatories.

Soil organic matter composition from correlated thermal analysis and nuclear magnetic resonance data in Australian national inventory of agricultural soils

NASA Astrophysics Data System (ADS)

Moore, T. S.; Sanderman, J.; Baldock, J.; Plante, A. F.

2016-12-01

National-scale inventories typically include soil organic carbon (SOC) content, but not chemical composition or biogeochemical stability. Australia's Soil Carbon Research Programme (SCaRP) represents a national inventory of SOC content and composition in agricultural systems. The program used physical fractionation followed by 13C nuclear magnetic resonance (NMR) spectroscopy. While these techniques are highly effective, they are typically too expensive and time consuming for use in large-scale SOC monitoring. We seek to understand if analytical thermal analysis is a viable alternative. Coupled differential scanning calorimetry (DSC) and evolved gas analysis (CO2- and H2O-EGA) yields valuable data on SOC composition and stability via ramped combustion. The technique requires little training to use, and does not require fractionation or other sample pre-treatment. We analyzed 300 agricultural samples collected by SCaRP, divided into four fractions: whole soil, coarse particulates (POM), untreated mineral associated (HUM), and hydrofluoric acid (HF)-treated HUM. All samples were analyzed by DSC-EGA, but only the POM and HF-HUM fractions were analyzed by NMR. Multivariate statistical analyses were used to explore natural clustering in SOC composition and stability based on DSC-EGA data. A partial least-squares regression (PLSR) model was used to explore correlations among the NMR and DSC-EGA data. Correlations demonstrated regions of combustion attributable to specific functional groups, which may relate to SOC stability. We are increasingly challenged with developing an efficient technique to assess SOC composition and stability at large spatial and temporal scales. Correlations between NMR and DSC-EGA may demonstrate the viability of using thermal analysis in lieu of more demanding methods in future large-scale surveys, and may provide data that goes beyond chemical composition to better approach quantification of biogeochemical stability.

Clustering on very small scales from a large, complete sample of confirmed quasar pairs

NASA Astrophysics Data System (ADS)

Eftekharzadeh, Sarah; Myers, Adam D.; Djorgovski, Stanislav G.; Graham, Matthew J.; Hennawi, Joseph F.; Mahabal, Ashish A.; Richards, Gordon T.

2016-06-01

We present by far the largest sample of spectroscopically confirmed binaryquasars with proper transverse separations of 17.0 ≤ Rprop ≤ 36.6 h-1 kpc. Our sample, whichis an order-of-magnitude larger than previous samples, is selected from Sloan Digital Sky Survey (SDSS) imaging over an area corresponding to the SDSS 6th data release (DR6). Our quasars are targeted using a Kernel Density Estimation technique (KDE), and confirmed using long-slit spectroscopy on a range of facilities.Our most complete sub-sample of 44 binary quasars with g<20.85, extends across angular scales of 2.9" < Δθ < 6.3", and is targeted from a parent sample that would be equivalent to a full spectroscopic survey of nearly 300,000 quasars.We determine the projected correlation function of quasars (\\bar Wp) over proper transverse scales of 17.0 ≤ Rprop ≤ 36.6 h-1 kpc, and also in 4 bins of scale within this complete range.To investigate the redshift evolution of quasar clustering on small scales, we make the first self-consistent measurement of the projected quasar correlation function in 4 bins of redshift over 0.4 ≤ z ≤ 2.3.

Validation of the MOS Social Support Survey 6-item (MOS-SSS-6) measure with two large population-based samples of Australian women.

PubMed

Holden, Libby; Lee, Christina; Hockey, Richard; Ware, Robert S; Dobson, Annette J

2014-12-01

This study aimed to validate a 6-item 1-factor global measure of social support developed from the Medical Outcomes Study Social Support Survey (MOS-SSS) for use in large epidemiological studies. Data were obtained from two large population-based samples of participants in the Australian Longitudinal Study on Women's Health. The two cohorts were aged 53-58 and 28-33 years at data collection (N = 10,616 and 8,977, respectively). Items selected for the 6-item 1-factor measure were derived from the factor structure obtained from unpublished work using an earlier wave of data from one of these cohorts. Descriptive statistics, including polychoric correlations, were used to describe the abbreviated scale. Cronbach's alpha was used to assess internal consistency and confirmatory factor analysis to assess scale validity. Concurrent validity was assessed using correlations between the new 6-item version and established 19-item version, and other concurrent variables. In both cohorts, the new 6-item 1-factor measure showed strong internal consistency and scale reliability. It had excellent goodness-of-fit indices, similar to those of the established 19-item measure. Both versions correlated similarly with concurrent measures. The 6-item 1-factor MOS-SSS measures global functional social support with fewer items than the established 19-item measure.

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Diagnosing Chaos Using Four-Point Functions in Two-Dimensional Conformal Field Theory.

PubMed

Roberts, Daniel A; Stanford, Douglas

2015-09-25

We study chaotic dynamics in two-dimensional conformal field theory through out-of-time-order thermal correlators of the form ⟨W(t)VW(t)V⟩. We reproduce holographic calculations similar to those of Shenker and Stanford, by studying the large c Virasoro identity conformal block. The contribution of this block to the above correlation function begins to decrease exponentially after a delay of ~t_{*}-(β/2π)logβ^{2}E_{w}E_{v}, where t_{*} is the fast scrambling time (β/2π)logc and E_{w},E_{v} are the energy scales of the W,V operators.

Probing dark energy with lensing magnification in photometric surveys.

PubMed

Schneider, Michael D

2014-02-14

I present an estimator for the angular cross correlation of two tracers of the cosmological large-scale structure that utilizes redshift information to isolate separate physical contributions. The estimator is derived by solving the Limber equation for a reweighting of the foreground tracer that nulls either clustering or lensing contributions to the cross correlation function. Applied to future photometric surveys, the estimator can enhance the measurement of gravitational lensing magnification effects to provide a competitive independent constraint on the dark energy equation of state.

Entanglement properties of boundary state and thermalization

NASA Astrophysics Data System (ADS)

Guo, Wu-zhong

2018-06-01

We discuss the regularized boundary state {e}^{-{τ}_0H}\\Big|{.B>}_a on two aspects in both 2D CFT and higher dimensional free field theory. One is its entanglement and correlation properties, which exhibit exponential decay in 2D CFT, the parameter 1 /τ 0 works as a mass scale. The other concerns with its time evolution, i.e., {e}^{-itH}{e}^{-{τ}_0H}\\Big|{.B>}_a . We investigate the Kubo-Martin-Schwinger (KMS) condition on correlation function of local operators to detect the thermal properties. Interestingly we find the correlation functions in the initial state {e}^{-{τ}_0H}\\Big|{.B>}_a also partially satisfy the KMS condition. In the limit t → ∞, the correlators will exactly satisfy the KMS condition. We generally analyse quantum quench by a pure state and obtain some constraints on the possible form of 2-point correlation function in the initial state if assuming they satisfies KMS condition in the final state. As a byproduct we find in an large τ 0 limit the thermal property of 2-point function in {e}^{-{τ}_0H}\\Big|{.B>}_a also appears.

Two-point correlation function in systems with van der Waals type interaction

NASA Astrophysics Data System (ADS)

Dantchev, D.

2001-09-01

The behavior of the bulk two-point correlation function G( r; T| d ) in d-dimensional system with van der Waals type interactions is investigated and its consequences on the finite-size scaling properties of the susceptibility in such finite systems with periodic boundary conditions is discussed within mean-spherical model which is an example of Ornstein and Zernike type theory. The interaction is supposed to decay at large distances r as r - (d + σ), with 2 < d < 4, 2 < σ < 4 and d + σ≤6. It is shown that G( r; T| d ) decays as r - (d - 2) for 1 ≪ r≪ξ, exponentially for ξ≪ r≪ r *, where r * = (σ - 2)ξlnξ, and again in a power law as r - (d + σ) for r≫ r *. The analytical form of the leading-order scaling function of G( r; T| d ) in any of these regimes is derived.

On the saturation of the refractive index structure function. II - Influence of the correlation length on astronomical 'seeing'

NASA Technical Reports Server (NTRS)

Venkatakrishnan, P.

1987-01-01

A physical length scale in the wavefront corresponding to the parameter (r sub 0) characterizing the loss in detail in a long exposure image is identified, and the influence of the correlation scale of turbulence as r sub 0 approaches this scale is shown. Allowing for the effect of 2-point correlations in the fluctuations of the refractive index, Venkatakrishnan and Chatterjee (1987) proposed a modified law for the phase structure function. It is suggested that the departure of the phase structure function from the 5/3 power law for length scales in the wavefront approaching the correlation scale of turbulence may lead to better 'seeing' at longer wavelengths.

Shock probes in a one-dimensional Katz-Lebowitz-Spohn model

NASA Astrophysics Data System (ADS)

Chatterjee, Sakuntala; Barma, Mustansir

2008-06-01

We consider shock probes in a one-dimensional driven diffusive medium with nearest-neighbor Ising interaction (KLS model). Earlier studies based on an approximate mapping of the present system to an effective zero-range process concluded that the exponents characterizing the decays of several static and dynamical correlation functions of the probes depend continuously on the strength of the Ising interaction. On the contrary, our numerical simulations indicate that over a substantial range of the interaction strength, these exponents remain constant and their values are the same as in the case of no interaction (when the medium executes an ASEP). We demonstrate this by numerical studies of several dynamical correlation functions for two probes and also for a macroscopic number of probes. Our results are consistent with the expectation that the short-ranged correlations induced by the Ising interaction should not affect the large time and large distance properties of the system, implying that scaling forms remain the same as in the medium with no interactions present.

Galaxy And Mass Assembly (GAMA): the signatures of galaxy interactions as viewed from small scale galaxy clustering

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Norberg, P.; Zehavi, I.; Farrow, D. J.; Loveday, J.; Hopkins, A. M.; Davies, L. J. M.; Wang, L.; Alpaslan, M.; Bland-Hawthorn, J.; Brough, S.; Holwerda, B. W.; Owers, M. S.; Wright, A. H.

2018-06-01

Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their interaction. In this study, we use two-point auto, cross and mark correlation functions to investigate the extent to which small-scale clustering properties of star forming galaxies can be used to gain physical insight into galaxy-galaxy interactions between galaxies of similar optical brightness and stellar mass. The Hα star formers, drawn from the highly spatially complete Galaxy And Mass Assembly (GAMA) survey, show an increase in clustering on small separations. Moreover, the clustering strength shows a strong dependence on optical brightness and stellar mass, where (1) the clustering amplitude of optically brighter galaxies at a given separation is larger than that of optically fainter systems, (2) the small scale clustering properties (e.g. the strength, the scale at which the signal relative to the fiducial power law plateaus) of star forming galaxies appear to differ as a function of increasing optical brightness of galaxies. According to cross and mark correlation analyses, the former result is largely driven by the increased dust content in optically bright star forming galaxies. The latter could be interpreted as evidence of a correlation between interaction-scale and optical brightness of galaxies, where physical evidence of interactions between optically bright star formers, likely hosted within relatively massive halos, persist over larger separations than those between optically faint star formers.

Gravitational Lensing Effect on the Two-Point Correlation of Hot Spots in the Cosmic Microwave Background.

PubMed

Takada; Komatsu; Futamase

2000-04-20

We investigate the weak gravitational lensing effect that is due to the large-scale structure of the universe on two-point correlations of local maxima (hot spots) in the two-dimensional sky map of the cosmic microwave background (CMB) anisotropy. According to the Gaussian random statistics, as most inflationary scenarios predict, the hot spots are discretely distributed, with some characteristic angular separations on the last scattering surface that are due to oscillations of the CMB angular power spectrum. The weak lensing then causes pairs of hot spots, which are separated with the characteristic scale, to be observed with various separations. We found that the lensing fairly smooths out the oscillatory features of the two-point correlation function of hot spots. This indicates that the hot spot correlations can be a new statistical tool for measuring the shape and normalization of the power spectrum of matter fluctuations from the lensing signatures.

Analysis of the two-point velocity correlations in turbulent boundary layer flows

NASA Technical Reports Server (NTRS)

Oberlack, M.

1995-01-01

The general objective of the present work is to explore the use of Rapid Distortion Theory (RDT) in analysis of the two-point statistics of the log-layer. RDT is applicable only to unsteady flows where the non-linear turbulence-turbulence interaction can be neglected in comparison to linear turbulence-mean interactions. Here we propose to use RDT to examine the structure of the large energy-containing scales and their interaction with the mean flow in the log-region. The contents of the work are twofold: First, two-point analysis methods will be used to derive the law-of-the-wall for the special case of zero mean pressure gradient. The basic assumptions needed are one-dimensionality in the mean flow and homogeneity of the fluctuations. It will be shown that a formal solution of the two-point correlation equation can be obtained as a power series in the von Karman constant, known to be on the order of 0.4. In the second part, a detailed analysis of the two-point correlation function in the log-layer will be given. The fundamental set of equations and a functional relation for the two-point correlation function will be derived. An asymptotic expansion procedure will be used in the log-layer to match Kolmogorov's universal range and the one-point correlations to the inviscid outer region valid for large correlation distances.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

NASA Astrophysics Data System (ADS)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY

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

Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.

The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less

Time dependent turbulence modeling and analytical theories of turbulence

NASA Technical Reports Server (NTRS)

Rubinstein, R.

1993-01-01

By simplifying the direct interaction approximation (DIA) for turbulent shear flow, time dependent formulas are derived for the Reynolds stresses which can be included in two equation models. The Green's function is treated phenomenologically, however, following Smith and Yakhot, we insist on the short and long time limits required by DIA. For small strain rates, perturbative evaluation of the correlation function yields a time dependent theory which includes normal stress effects in simple shear flows. From this standpoint, the phenomenological Launder-Reece-Rodi model is obtained by replacing the Green's function by its long time limit. Eddy damping corrections to short time behavior initiate too quickly in this model; in contrast, the present theory exhibits strong suppression of eddy damping at short times. A time dependent theory for large strain rates is proposed in which large scales are governed by rapid distortion theory while small scales are governed by Kolmogorov inertial range dynamics. At short times and large strain rates, the theory closely matches rapid distortion theory, but at long times it relaxes to an eddy damping model.

The influence of sub-grid scale motions on particle collision in homogeneous isotropic turbulence

NASA Astrophysics Data System (ADS)

Xiong, Yan; Li, Jing; Liu, Zhaohui; Zheng, Chuguang

2018-02-01

The absence of sub-grid scale (SGS) motions leads to severe errors in particle pair dynamics, which represents a great challenge to the large eddy simulation of particle-laden turbulent flow. In order to address this issue, data from direct numerical simulation (DNS) of homogenous isotropic turbulence coupled with Lagrangian particle tracking are used as a benchmark to evaluate the corresponding results of filtered DNS (FDNS). It is found that the filtering process in FDNS will lead to a non-monotonic variation of the particle collision statistics, including radial distribution function, radial relative velocity, and the collision kernel. The peak of radial distribution function shifts to the large-inertia region due to the lack of SGS motions, and the analysis of the local flowstructure characteristic variable at particle position indicates that the most effective interaction scale between particles and fluid eddies is increased in FDNS. Moreover, this scale shifting has an obvious effect on the odd-order moments of the probability density function of radial relative velocity, i.e. the skewness, which exhibits a strong correlation to the variance of radial distribution function in FDNS. As a whole, the radial distribution function, together with radial relative velocity, can compensate the SGS effects for the collision kernel in FDNS when the Stokes number based on the Kolmogorov time scale is greater than 3.0. However, it still leaves considerable errors for { St}_k <3.0.

Probing the largest cosmological scales with the correlation between the cosmic microwave background and peculiar velocities

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

Fosalba, Pablo; Dore, Olivier

2007-11-15

Cross correlation between the cosmic microwave background (CMB) and large-scale structure is a powerful probe of dark energy and gravity on the largest physical scales. We introduce a novel estimator, the CMB-velocity correlation, that has most of its power on large scales and that, at low redshift, delivers up to a factor of 2 higher signal-to-noise ratio than the recently detected CMB-dark matter density correlation expected from the integrated Sachs-Wolfe effect. We propose to use a combination of peculiar velocities measured from supernovae type Ia and kinetic Sunyaev-Zeldovich cluster surveys to reveal this signal and forecast dark energy constraints thatmore » can be achieved with future surveys. We stress that low redshift peculiar velocity measurements should be exploited with complementary deeper large-scale structure surveys for precision cosmology.« less

Disentangling interacting dark energy cosmologies with the three-point correlation function

NASA Astrophysics Data System (ADS)

Moresco, Michele; Marulli, Federico; Baldi, Marco; Moscardini, Lauro; Cimatti, Andrea

2014-10-01

We investigate the possibility of constraining coupled dark energy (cDE) cosmologies using the three-point correlation function (3PCF). Making use of the CODECS N-body simulations, we study the statistical properties of cold dark matter (CDM) haloes for a variety of models, including a fiducial ΛCDM scenario and five models in which dark energy (DE) and CDM mutually interact. We measure both the halo 3PCF, ζ(θ), and the reduced 3PCF, Q(θ), at different scales (2 < r [h-1 Mpc ] < 40) and redshifts (0 ≤ z ≤ 2). In all cDE models considered in this work, Q(θ) appears flat at small scales (for all redshifts) and at low redshifts (for all scales), while it builds up the characteristic V-shape anisotropy at increasing redshifts and scales. With respect to the ΛCDM predictions, cDE models show lower (higher) values of the halo 3PCF for perpendicular (elongated) configurations. The effect is also scale-dependent, with differences between ΛCDM and cDE models that increase at large scales. We made use of these measurements to estimate the halo bias, that results in fair agreement with the one computed from the two-point correlation function (2PCF). The main advantage of using both the 2PCF and 3PCF is to break the bias-σ8 degeneracy. Moreover, we find that our bias estimates are approximately independent of the assumed strength of DE coupling. This study demonstrates the power of a higher order clustering analysis in discriminating between alternative cosmological scenarios, for both present and forthcoming galaxy surveys, such as e.g. Baryon Oscillation Spectroscopic Survey and Euclid.

Baryons, universe and everything in between

NASA Astrophysics Data System (ADS)

Ho, Shirley

2008-06-01

This thesis is a tour of topics in cosmology, unified by their diversity and pursuits in better understanding of our Universe. The first chapter measures the Integrated Sachs-Wolfe effect as a function of redshift utilizing a large range of large scale structure observations and the cosmic microwave background. We combine the ISW likelihood function with weak lensing of CMB (which is described in Chapter 2) and CMB powerspectrum to constrain the equation of state of dark energy and the curvature of the Universe. The second chapter investigates the correlation of gravitational lensing of the cosmic microwave background (CMB) with several tracers of large-scale structure, and we find evidence for a positive cross-correlation at the 2.5s level. The third chapter explores the statistical properties of Luminous Red Galaxies in a sample of X-ray selected galaxy clusters, including the halo occupation distribution, how Poisson is the satellite distribution of LRGs and the radial profile of LRGs within clusters. The forth chapter explores the idea of using multiplicity of galaxies to understand their merging timescales. We find that (by using the multiplicity function of LRGs in Chapter 3) Massive halos (~ 10 14 M [Special characters omitted.] ) at low redshift have, for example, been bombarded by several ~ 10 13 M [Special characters omitted.] halos throughout their history and these accreted LRGs merge on relatively short timescales (~ 2 Gyr). The fifth chapter presents a new method for generating a template for the kinematic Sunyaev-Zel'dovich effect that can be used to detect the missing baryons. We assessed the feasibility of the method by investigating combinations of differeng galaxy surveys and CMB observations and find that we can detect the gas-momentum kSZ correlation, and thus the ionized gas, at significant signal-to-noise level.

Structure and Variability of Water Vapor in the Upper Troposphere and Lower Stratosphere

NASA Technical Reports Server (NTRS)

Salby, Murry L.

2001-01-01

Upper-tropospheric humidity (UTH) has been synoptically mapped via an algorithm that rejects small-scale undersampled variance, which is intrinsic to asymptotic measurements of water vapor, cloud, and other convective properties. Mapped distributions of UTH have been used, jointly with high-resolution Global Cloud Imagery (GCI), to study how the upper troposphere is humidified. The time-mean distribution of UTH is spatially correlated to the time-mean distribution of cold cloud fraction (eta)(sub c) (T < than 230 K). Regions of large UTH coincide with regions of large eta(sub c), which mark deep convection. They also coincide with regions of reduced vertical stability, in which the vertical gradient of theta is weakened by convective mixing. Coldest cloud cover is attended convective overshoots above the local tropopause, which is simultaneously coldest and highest. Together, these features reflect the upper-troposphere being ventilated by convection, which mixes in moist air from lower levels. Histograms of UTH and eta(sub c) have been applied to construct the joint probability density function, which quantifies the relationship between these properties. The expected value of UTH in convective regions is strongly correlated to the expected value of eta(sub c). In ensembles of asymptotic samples, the correlation between epsilon[UTH] and epsilon[eta(sub c)] exceeds 0.80. As these expectations reflect the most likely values, the strong correlation between epsilon[UTH] and epsilon[eta(sub c)] indicates that the large-scale organization of UTH is strongly shaped by convective pumping of moisture from lower levels. The same relationship holds for unsteady fields - even though, instantaneously, those fields are comprised almost entirely of small-scale convective structure. The spatial autocorrelation of UTH, constructed at high resolution from overpass data along ascending and descending tracks of the orbit, is limited to only a couple of degrees in the horizontal. This mirrors the spatial autocorrelation of eta(sub c), which likewise operates coherently on short scales. The short correlation scale of UTH, which reflects the scale of individual convective systems, is comparable to the spacing of retrievals from MLS. These scales are undersampled in the asynoptic measurements. Despite their prevalence, the mapping algorithm described above successfully recovers synoptic behavior operating coherently on large scales. It reveals eastward migration of anomalous UTH from the Indian ocean to the central Pacific, in association with the modulation of convection by the Madden-Julian oscillation. Additional information is contained in the original extended abstract.

Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

PubMed

Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

2018-02-01

One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

Relation between functional mobility and dynapenia in institutionalized frail elderly

PubMed Central

Soares, Antonio Vinicius; Marcelino, Elessandra; Maia, Késsia Cristina; Borges, Noé Gomes

2017-01-01

ABSTRACT Objective To investigate the relation between functional mobility and dynapenia in institutionalized frail elderly. Methods A descriptive, correlational study involving 26 institutionalized elderly men and women, mean age 82.3±6 years. The instruments employed were the Mini Mental State Examination, the Geriatric Depression Scale, the International Physical Activity Questionnaire, the Timed Up and Go test, a handgrip dynamometer and a portable dynamometer for large muscle groups (shoulder, elbow and hip flexors, knee extensors and ankle dorsiflexors). Results Significant negative correlation between functional mobility levels assessed by the Timed Up and Go test and dynapenia was observed in all muscle groups evaluated, particularly in knee extensors (r -0.65). Conclusion A significant negative correlation between muscle strength, particularly knee extensor strength, and functional mobility was found in institutionalized elderly. Data presented indicate that the higher the muscle strength, the shorter the execution time, and this could demonstrate better performance in this functional mobility test. PMID:29091148

PSR B0329+54: Statistics of Substructure Discovered within the Scattering Disk on RadioAstron Baselines of up to 235,000 km

NASA Astrophysics Data System (ADS)

Gwinn, C. R.; Popov, M. V.; Bartel, N.; Andrianov, A. S.; Johnson, M. D.; Joshi, B. C.; Kardashev, N. S.; Karuppusamy, R.; Kovalev, Y. Y.; Kramer, M.; Rudnitskii, A. G.; Safutdinov, E. R.; Shishov, V. I.; Smirnova, T. V.; Soglasnov, V. A.; Steinmassl, S. F.; Zensus, J. A.; Zhuravlev, V. I.

2016-05-01

We discovered fine-scale structure within the scattering disk of PSR B0329+54 in observations with the RadioAstron ground-space radio interferometer. Here we describe this phenomenon, characterize it with averages and correlation functions, and interpret it as the result of decorrelation of the impulse-response function of interstellar scattering between the widely separated antennas. This instrument included the 10 m Space Radio Telescope, the 110 m Green Bank Telescope, the 14 × 25 m Westerbork Synthesis Radio Telescope, and the 64 m Kalyazin Radio Telescope. The observations were performed at 324 MHz on baselines of up to 235,000 km in 2012 November and 2014 January. In the delay domain, on long baselines the interferometric visibility consists of many discrete spikes within a limited range of delays. On short baselines it consists of a sharp spike surrounded by lower spikes. The average envelope of correlations of the visibility function shows two exponential scales, with characteristic delays of {τ }1=4.1+/- 0.3 μ {{s}} and {τ }2=23+/- 3 μ {{s}}, indicating the presence of two scales of scattering in the interstellar medium. These two scales are present in the pulse-broadening function. The longer scale contains 0.38 times the scattered power of the shorter one. We suggest that the longer tail arises from highly scattered paths, possibly from anisotropic scattering or from substructure at large angles.

A novel computational approach towards the certification of large-scale boson sampling

NASA Astrophysics Data System (ADS)

Huh, Joonsuk

Recent proposals of boson sampling and the corresponding experiments exhibit the possible disproof of extended Church-Turning Thesis. Furthermore, the application of boson sampling to molecular computation has been suggested theoretically. Till now, however, only small-scale experiments with a few photons have been successfully performed. The boson sampling experiments of 20-30 photons are expected to reveal the computational superiority of the quantum device. A novel theoretical proposal for the large-scale boson sampling using microwave photons is highly promising due to the deterministic photon sources and the scalability. Therefore, the certification protocol of large-scale boson sampling experiments should be presented to complete the exciting story. We propose, in this presentation, a computational protocol towards the certification of large-scale boson sampling. The correlations of paired photon modes and the time-dependent characteristic functional with its Fourier component can show the fingerprint of large-scale boson sampling. This work was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(NRF-2015R1A6A3A04059773), the ICT R&D program of MSIP/IITP [2015-019, Fundamental Research Toward Secure Quantum Communication] and Mueunjae Institute for Chemistry (MIC) postdoctoral fellowship.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults.

PubMed

Shaw, Emily E; Schultz, Aaron P; Sperling, Reisa A; Hedden, Trey

2015-10-01

Intrinsic functional connectivity MRI has become a widely used tool for measuring integrity in large-scale cortical networks. This study examined multiple cortical networks using Template-Based Rotation (TBR), a method that applies a priori network and nuisance component templates defined from an independent dataset to test datasets of interest. A priori templates were applied to a test dataset of 276 older adults (ages 65-90) from the Harvard Aging Brain Study to examine the relationship between multiple large-scale cortical networks and cognition. Factor scores derived from neuropsychological tests represented processing speed, executive function, and episodic memory. Resting-state BOLD data were acquired in two 6-min acquisitions on a 3-Tesla scanner and processed with TBR to extract individual-level metrics of network connectivity in multiple cortical networks. All results controlled for data quality metrics, including motion. Connectivity in multiple large-scale cortical networks was positively related to all cognitive domains, with a composite measure of general connectivity positively associated with general cognitive performance. Controlling for the correlations between networks, the frontoparietal control network (FPCN) and executive function demonstrated the only significant association, suggesting specificity in this relationship. Further analyses found that the FPCN mediated the relationships of the other networks with cognition, suggesting that this network may play a central role in understanding individual variation in cognition during aging.

Large-scale structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Park, Changbom; Spergel, David N.; Turok, Nail

1991-01-01

This paper studies the formation of large-scale structure by global texture in a flat universe dominated by cold dark matter. A code for evolution of the texture fields was combined with an N-body code for evolving the dark matter. The results indicate some promising aspects: with only one free parameter, the observed galaxy-galaxy correlation function is reproduced, clusters of galaxies are found to be significantly clustered on a scale of 20-50/h Mpc, and coherent structures of over 50/h Mpc in the galaxy distribution were found. The large-scale streaming motions observed are in good agreement with the observations: the average magnitude of the velocity field smoothed over 30/h Mpc is 430 km/sec. Global texture produces a cosmic Mach number that is compatible with observation. Also, significant evolution of clusters at low redshift was seen. Possible problems for the theory include too high velocity dispersions in clusters, and voids which are not as empty as those observed.

Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2012-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

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

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Lensing corrections to features in the angular two-point correlation function and power spectrum

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

LoVerde, Marilena; Department of Physics, Columbia University, New York, New York 10027; Hui, Lam

2008-01-15

It is well known that magnification bias, the modulation of galaxy or quasar source counts by gravitational lensing, can change the observed angular correlation function. We investigate magnification-induced changes to the shape of the observed correlation function w({theta}), and the angular power spectrum C{sub l}, paying special attention to the matter-radiation equality peak and the baryon wiggles. Lensing effectively mixes the correlation function of the source galaxies with that of the matter correlation at the lower redshifts of the lenses distorting the observed correlation function. We quantify how the lensing corrections depend on the width of the selection function, themore » galaxy bias b, and the number count slope s. The lensing correction increases with redshift and larger corrections are present for sources with steep number count slopes and/or broad redshift distributions. The most drastic changes to C{sub l} occur for measurements at high redshifts (z > or approx. 1.5) and low multipole moment (l < or approx. 100). For the source distributions we consider, magnification bias can shift the location of the matter-radiation equality scale by 1%-6% at z{approx}1.5 and by z{approx}3.5 the shift can be as large as 30%. The baryon bump in {theta}{sup 2}w({theta}) is shifted by < or approx. 1% and the width is typically increased by {approx}10%. Shifts of > or approx. 0.5% and broadening > or approx. 20% occur only for very broad selection functions and/or galaxies with (5s-2)/b > or approx. 2. However, near the baryon bump the magnification correction is not constant but is a gently varying function which depends on the source population. Depending on how the w({theta}) data is fitted, this correction may need to be accounted for when using the baryon acoustic scale for precision cosmology.« less

Cosmic Infrared Background Sources Clustered Around Quasars

NASA Astrophysics Data System (ADS)

Hall, Kirsten R.; Zakamska, Nadia; Marriage, Tobias; Crichton, Devin; Gralla, Megan

2017-06-01

Powerful quasars can be seen out to large distances. As they reside in massive dark matter halos, they provide a useful tracer of large scale structure. We stack Herschel-SPIRE images at 250, 350, and 500 microns at the locations of 13,000 quasars in redshift bins spanning 0.5 < z < 3.5. While the detected signal is dominated on instrumental beam scales by the unresolved dust emission of the quasar and its host galaxy, at z 2 the extended emission is clearly spatially resolved on Mpc scales. This emission is due to star-forming galaxies clustered around the dark matter halos hosting quasars. We measure radial surface brightness profiles of the stacked images to compute the angular correlation function of dusty star-forming galaxies correlated with quasars. We generate a halo occupation distribution model in order to determine the masses of the dark matter halos in which dusty star forming galaxies reside. We are probing potential changes in the halo mass most efficient at hosting star forming galaxies, and assessing any evidence that this halo mass evolved with redshift in the context of "cosmic downsizing".

Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.

2014-02-01

One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.

Phase-relationships between scales in the perturbed turbulent boundary layer

NASA Astrophysics Data System (ADS)

Jacobi, I.; McKeon, B. J.

2017-12-01

The phase-relationship between large-scale motions and small-scale fluctuations in a non-equilibrium turbulent boundary layer was investigated. A zero-pressure-gradient flat plate turbulent boundary layer was perturbed by a short array of two-dimensional roughness elements, both statically, and under dynamic actuation. Within the compound, dynamic perturbation, the forcing generated a synthetic very-large-scale motion (VLSM) within the flow. The flow was decomposed by phase-locking the flow measurements to the roughness forcing, and the phase-relationship between the synthetic VLSM and remaining fluctuating scales was explored by correlation techniques. The general relationship between large- and small-scale motions in the perturbed flow, without phase-locking, was also examined. The synthetic large scale cohered with smaller scales in the flow via a phase-relationship that is similar to that of natural large scales in an unperturbed flow, but with a much stronger organizing effect. Cospectral techniques were employed to describe the physical implications of the perturbation on the relative orientation of large- and small-scale structures in the flow. The correlation and cospectral techniques provide tools for designing more efficient control strategies that can indirectly control small-scale motions via the large scales.

Validation of the XDP-MDSP rating scale for the evaluation of patients with X-linked dystonia-parkinsonism.

PubMed

Pasco, Paul Matthew D; Jamora, Roland Dominic G; Rosales, Raymond L; Diesta, Cid Czarina E; Ng, Arlene R; Teleg, Rosalia A; Go, Criscely L; Lee, Lillian; Fernandez, Hubert H

2017-01-01

X-linked dystonia-parkinsonism(XDP) is a neurodegenerative disorder endemic to the Philippines. A rating scale was developed by the authors under the guidance of the Movement Disorder Society of the Philippines (MDSP) to assess XDP severity and progression, functional impact, and response to treatment in future clinical trials. Our main objective was to validate our new scale, the XDP-MDSP scale. The initial validation process included pragmatic testing to XDP patients followed by a modified Delphi procedure with an international advisory panel of dystonia, parkinsonism and scale development experts. Pearson correlation was used to assess construct validity of our new scale versus the assess construct validity of our new scale versus standard dystonia, parkinsonism, non-motor and functional scales; and also to assess divergent validity against behavioral and cognitive scales. The 37-item XDP-MDSP scale has five parts: I-dystonia, II-parkinsonism, III-non-motor features, IV-ADL, and V-global impression. After initial validation, the scale was administered to 204 XDP patients. Inter-domain correlation for the first four parts was acceptable. The correlation between these domains and the global rating was slightly lower. Correlations between Parts I, II, III, and IV versus standard dystonia, parkinsonism, non-motor and functional scales were acceptable with values ranging from 0.323 to 0.428. For divergent validity, a significant correlation was seen with behavioral scales. No significant correlation was noted with the cognitive scale. The proposed XDP-MDSP scale is internally valid but the global rating subscale may need to be modified or eliminated. While there is convergent validity, divergent validation was successful only on cognitive and not behavioral scales. The frequent co-occurrence of anxiety and depression, and its effect on the motor and functional state, may explain this finding.

Concurrent Validity and Classification Accuracy of the Leiter and Leiter-R in Low Functioning Children with Autism.

ERIC Educational Resources Information Center

Tsatsanis, Katherine D.; Dartnall, Nancy; Cicchetti, Domenic; Sparrow, Sara S.; Klin, Ami; Volkmar, Fred R.

2003-01-01

The concurrent validity of the original and revised versions of the Leiter International Performance Scale was examined with 26 children (ages 4-16) with autism. Although the correlation between the two tests was high (.87), there were significant intra-individual discrepancies present in 10 cases, two of which were both large and clinically…

A new method to estimate local pitch angles in spiral galaxies: Application to spiral arms and feathers in M81 and M51

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

Puerari, Ivânio; Elmegreen, Bruce G.; Block, David L., E-mail: puerari@inaoep.mx

2014-12-01

We examine 8 μm IRAC images of the grand design two-arm spiral galaxies M81 and M51 using a new method whereby pitch angles are locally determined as a function of scale and position, in contrast to traditional Fourier transform spectral analyses which fit to average pitch angles for whole galaxies. The new analysis is based on a correlation between pieces of a galaxy in circular windows of (lnR,θ) space and logarithmic spirals with various pitch angles. The diameter of the windows is varied to study different scales. The result is a best-fit pitch angle to the spiral structure as amore » function of position and scale, or a distribution function of pitch angles as a function of scale for a given galactic region or area. We apply the method to determine the distribution of pitch angles in the arm and interarm regions of these two galaxies. In the arms, the method reproduces the known pitch angles for the main spirals on a large scale, but also shows higher pitch angles on smaller scales resulting from dust feathers. For the interarms, there is a broad distribution of pitch angles representing the continuation and evolution of the spiral arm feathers as the flow moves into the interarm regions. Our method shows a multiplicity of spiral structures on different scales, as expected from gas flow processes in a gravitating, turbulent and shearing interstellar medium. We also present results for M81 using classical 1D and 2D Fourier transforms, together with a new correlation method, which shows good agreement with conventional 2D Fourier transforms.« less

Constraining the optical depth of galaxies and velocity bias with cross-correlation between the kinetic Sunyaev-Zeldovich effect and the peculiar velocity field

NASA Astrophysics Data System (ADS)

Ma, Yin-Zhe; Gong, Guo-Dong; Sui, Ning; He, Ping

2018-03-01

We calculate the cross-correlation function < (Δ T/T)({v}\\cdot \\hat{n}/σ _v) > between the kinetic Sunyaev-Zeldovich (kSZ) effect and the reconstructed peculiar velocity field using linear perturbation theory, with the aim of constraining the optical depth τ and peculiar velocity bias of central galaxies with Planck data. We vary the optical depth τ and the velocity bias function bv(k) = 1 + b(k/k0)n, and fit the model to the data, with and without varying the calibration parameter y0 that controls the vertical shift of the correlation function. By constructing a likelihood function and constraining the τ, b and n parameters, we find that the quadratic power-law model of velocity bias, bv(k) = 1 + b(k/k0)2, provides the best fit to the data. The best-fit values are τ = (1.18 ± 0.24) × 10-4, b=-0.84^{+0.16}_{-0.20} and y0=(12.39^{+3.65}_{-3.66})× 10^{-9} (68 per cent confidence level). The probability of b > 0 is only 3.12 × 10-8 for the parameter b, which clearly suggests a detection of scale-dependent velocity bias. The fitting results indicate that the large-scale (k ≤ 0.1 h Mpc-1) velocity bias is unity, while on small scales the bias tends to become negative. The value of τ is consistent with the stellar mass-halo mass and optical depth relationship proposed in the literature, and the negative velocity bias on small scales is consistent with the peak background split theory. Our method provides a direct tool for studying the gaseous and kinematic properties of galaxies.

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

PubMed

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, p<0.001), with worse dystonia severity implying worse function. Secondary dystonias had worse dystonia and less function than primary dystonias (p<0.001). A longer proportion of life lived with dystonia is associated with more severe dystonia (rs =0.42, p<0.001). The BFM-M is strongly linked with the GMFCS, MACS, and CFCS, irrespective of aetiology. Each scale offers interrelated but complementary information and is applicable to all aetiologies. Movement disorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

Clustering on very small scales from a large sample of confirmed quasar pairs: does quasar clustering track from Mpc to kpc scales?

NASA Astrophysics Data System (ADS)

Eftekharzadeh, S.; Myers, A. D.; Hennawi, J. F.; Djorgovski, S. G.; Richards, G. T.; Mahabal, A. A.; Graham, M. J.

2017-06-01

We present the most precise estimate to date of the clustering of quasars on very small scales, based on a sample of 47 binary quasars with magnitudes of g < 20.85 and proper transverse separations of ˜25 h-1 kpc. Our sample of binary quasars, which is about six times larger than any previous spectroscopically confirmed sample on these scales, is targeted using a kernel density estimation (KDE) technique applied to Sloan Digital Sky Survey (SDSS) imaging over most of the SDSS area. Our sample is 'complete' in that all of the KDE target pairs with 17.0 ≲ R ≲ 36.2 h-1 kpc in our area of interest have been spectroscopically confirmed from a combination of previous surveys and our own long-slit observational campaign. We catalogue 230 candidate quasar pairs with angular separations of <8 arcsec, from which our binary quasars were identified. We determine the projected correlation function of quasars (\\bar{W}_p) in four bins of proper transverse scale over the range 17.0 ≲ R ≲ 36.2 h-1 kpc. The implied small-scale quasar clustering amplitude from the projected correlation function, integrated across our entire redshift range, is A = 24.1 ± 3.6 at ˜26.6 h-1 kpc. Our sample is the first spectroscopically confirmed sample of quasar pairs that is sufficiently large to study how quasar clustering evolves with redshift at ˜25 h-1 kpc. We find that empirical descriptions of how quasar clustering evolves with redshift at ˜25 h-1 Mpc also adequately describe the evolution of quasar clustering at ˜25 h-1 kpc.

Computing Earthquake Probabilities on Global Scales

NASA Astrophysics Data System (ADS)

Holliday, James R.; Graves, William R.; Rundle, John B.; Turcotte, Donald L.

2016-03-01

Large devastating events in systems such as earthquakes, typhoons, market crashes, electricity grid blackouts, floods, droughts, wars and conflicts, and landslides can be unexpected and devastating. Events in many of these systems display frequency-size statistics that are power laws. Previously, we presented a new method for calculating probabilities for large events in systems such as these. This method counts the number of small events since the last large event and then converts this count into a probability by using a Weibull probability law. We applied this method to the calculation of large earthquake probabilities in California-Nevada, USA. In that study, we considered a fixed geographic region and assumed that all earthquakes within that region, large magnitudes as well as small, were perfectly correlated. In the present article, we extend this model to systems in which the events have a finite correlation length. We modify our previous results by employing the correlation function for near mean field systems having long-range interactions, an example of which is earthquakes and elastic interactions. We then construct an application of the method and show examples of computed earthquake probabilities.

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

Seljak, Uroš, E-mail: useljak@berkeley.edu

On large scales a nonlinear transformation of matter density field can be viewed as a biased tracer of the density field itself. A nonlinear transformation also modifies the redshift space distortions in the same limit, giving rise to a velocity bias. In models with primordial nongaussianity a nonlinear transformation generates a scale dependent bias on large scales. We derive analytic expressions for the large scale bias, the velocity bias and the redshift space distortion (RSD) parameter β, as well as the scale dependent bias from primordial nongaussianity for a general nonlinear transformation. These biases can be expressed entirely in termsmore » of the one point distribution function (PDF) of the final field and the parameters of the transformation. The analysis shows that one can view the large scale bias different from unity and primordial nongaussianity bias as a consequence of converting higher order correlations in density into 2-point correlations of its nonlinear transform. Our analysis allows one to devise nonlinear transformations with nearly arbitrary bias properties, which can be used to increase the signal in the large scale clustering limit. We apply the results to the ionizing equilibrium model of Lyman-α forest, in which Lyman-α flux F is related to the density perturbation δ via a nonlinear transformation. Velocity bias can be expressed as an average over the Lyman-α flux PDF. At z = 2.4 we predict the velocity bias of -0.1, compared to the observed value of −0.13±0.03. Bias and primordial nongaussianity bias depend on the parameters of the transformation. Measurements of bias can thus be used to constrain these parameters, and for reasonable values of the ionizing background intensity we can match the predictions to observations. Matching to the observed values we predict the ratio of primordial nongaussianity bias to bias to have the opposite sign and lower magnitude than the corresponding values for the highly biased galaxies, but this depends on the model parameters and can also vanish or change the sign.« less

Three-Point Correlations in the COBE DMR 2 Year Anisotropy Maps

NASA Technical Reports Server (NTRS)

Hinshaw, G.; Banday, A. J.; Bennett, C. L.; Gorski, K. M.; Kogut, A.

1995-01-01

We compute the three-point temperature correlation function of the COBE Differential Microwave Radiometer (DMR) 2 year sky maps to search for evidence of non-Gaussian temperature fluctuations. We detect three-point correlations in our sky with a substantially higher signal-to-noise ratio than from the first-year data. However, the magnitude of the signal is consistent with the level of cosmic variance expected from Gaussian fluctuations, even when the low-order multipole moments, up to l = 9, are filtered from the data. These results do not strongly constrain most existing models of structure formation, but the absence of intrinsic three-point correlations on large angular scales is an important consistency test for such models.

Large-Scale, High-Resolution Neurophysiological Maps Underlying fMRI of Macaque Temporal Lobe

PubMed Central

Papanastassiou, Alex M.; DiCarlo, James J.

2013-01-01

Maps obtained by functional magnetic resonance imaging (fMRI) are thought to reflect the underlying spatial layout of neural activity. However, previous studies have not been able to directly compare fMRI maps to high-resolution neurophysiological maps, particularly in higher level visual areas. Here, we used a novel stereo microfocal x-ray system to localize thousands of neural recordings across monkey inferior temporal cortex (IT), construct large-scale maps of neuronal object selectivity at subvoxel resolution, and compare those neurophysiology maps with fMRI maps from the same subjects. While neurophysiology maps contained reliable structure at the sub-millimeter scale, fMRI maps of object selectivity contained information at larger scales (>2.5 mm) and were only partly correlated with raw neurophysiology maps collected in the same subjects. However, spatial smoothing of neurophysiology maps more than doubled that correlation, while a variety of alternative transforms led to no significant improvement. Furthermore, raw spiking signals, once spatially smoothed, were as predictive of fMRI maps as local field potential signals. Thus, fMRI of the inferior temporal lobe reflects a spatially low-passed version of neurophysiology signals. These findings strongly validate the widespread use of fMRI for detecting large (>2.5 mm) neuronal domains of object selectivity but show that a complete understanding of even the most pure domains (e.g., faces vs nonface objects) requires investigation at fine scales that can currently only be obtained with invasive neurophysiological methods. PMID:24048850

Probing features in the primordial perturbation spectrum with large-scale structure data

NASA Astrophysics Data System (ADS)

L'Huillier, Benjamin; Shafieloo, Arman; Hazra, Dhiraj Kumar; Smoot, George F.; Starobinsky, Alexei A.

2018-06-01

The form of the primordial power spectrum (PPS) of cosmological scalar (matter density) perturbations is not yet constrained satisfactorily in spite of the tremendous amount of information from the Cosmic Microwave Background (CMB) data. While a smooth power-law-like form of the PPS is consistent with the CMB data, some PPSs with small non-smooth features at large scales can also fit the CMB temperature and polarization data with similar statistical evidence. Future CMB surveys cannot help distinguish all such models due to the cosmic variance at large angular scales. In this paper, we study how well we can differentiate between such featured forms of the PPS not otherwise distinguishable using CMB data. We ran 15 N-body DESI-like simulations of these models to explore this approach. Showing that statistics such as the halo mass function and the two-point correlation function are not able to distinguish these models in a DESI-like survey, we advocate to avoid reducing the dimensionality of the problem by demonstrating that the use of a simple three-dimensional count-in-cell density field can be much more effective for the purpose of model distinction.

Leaf optical properties shed light on foliar trait variability at individual to global scales

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Serbin, S.; Dietze, M.

2017-12-01

Recent syntheses of large trait databases have contributed immensely to our understanding of drivers of plant function at the global scale. However, the global trade-offs revealed by such syntheses, such as the trade-off between leaf productivity and resilience (i.e. "leaf economics spectrum"), are often absent at smaller scales and fail to correlate with actual functional limitations. An improved understanding of how traits vary among communities, species, and individuals is critical to accurate representations of vegetation ecophysiology and ecological dynamics in ecosystem models. Spectral data from both field observations and remote sensing platforms present a rich and widely available source of information on plant traits. Here, we apply Bayesian inversion of the PROSPECT leaf radiative transfer model to a large global database of over 60,000 field spectra and plant traits to (1) comprehensively assess the accuracy of leaf trait estimation using PROSPECT spectral inversion; (2) investigate the correlations between optical traits estimable from PROSPECT and other important foliar traits such as nitrogen and lignin concentrations; and (3) identify dominant sources of variability and characterize trade-offs in optical and non-optical foliar traits. Our work provides a key methodological contribution by validating physically-based retrieval of plant traits from remote sensing observations, and provides insights about trait trade-offs related to plant acclimation, adaptation, and community assembly.

Statistical characterization of Earth’s heterogeneities from seismic scattering

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, R.

2009-12-01

The distortion of a teleseismic wavefront carries information about the heterogeneities through which the wave propagates and it is manifestited as logarithmic amplitude (logA) and phase fluctuations of the direct P wave recorded by a seismic network. By cross correlating the fluctuations (e.g., logA-logA or phase-phase), we obtain coherence functions, which depend on spatial lags between stations and incident angles between the incident waves. We have mathematically related the depth-dependent heterogeneity spectrum to the observable coherence functions using seismic scattering theory. We will show that our method has sharp depth resolution. Using the HiNet seismic network data in Japan, we have inverted power spectra for two depth ranges, ~0-120km and below ~120km depth. The coherence functions formed by different groups of stations or by different groups of earthquakes at different back azimuths are similar. This demonstrates that the method is statistically stable and the inhomogeneities are statistically stationary. In both depth intervals, the trend of the spectral amplitude decays from large scale to small scale in a power-law fashion with exceptions at ~50km for the logA data. Due to the spatial spacing of the seismometers, only information from length scale 15km to 200km is inverted. However our scattering method provides new information on small to intermediate scales that are comparable to scales of the recycled materials and thus is complimentary to the global seismic tomography which reveals mainly large-scale heterogeneities on the order of ~1000km. The small-scale heterogeneities revealed here are not likely of pure thermal origin. Therefore, the length scale and strength of heterogeneities as a function of depth may provide important constraints in mechanical mixing of various components in the mantle convection.

Metallicity fluctuation statistics in the interstellar medium and young stars - I. Variance and correlation

NASA Astrophysics Data System (ADS)

Krumholz, Mark R.; Ting, Yuan-Sen

2018-04-01

The distributions of a galaxy's gas and stars in chemical space encode a tremendous amount of information about that galaxy's physical properties and assembly history. However, present methods for extracting information from chemical distributions are based either on coarse averages measured over galactic scales (e.g. metallicity gradients) or on searching for clusters in chemical space that can be identified with individual star clusters or gas clouds on ˜1 pc scales. These approaches discard most of the information, because in galaxies gas and young stars are observed to be distributed fractally, with correlations on all scales, and the same is likely to be true of metals. In this paper we introduce a first theoretical model, based on stochastically forced diffusion, capable of predicting the multiscale statistics of metal fields. We derive the variance, correlation function, and power spectrum of the metal distribution from first principles, and determine how these quantities depend on elements' astrophysical origin sites and on the large-scale properties of galaxies. Among other results, we explain for the first time why the typical abundance scatter observed in the interstellar media of nearby galaxies is ≈0.1 dex, and we predict that this scatter will be correlated on spatial scales of ˜0.5-1 kpc, and over time-scales of ˜100-300 Myr. We discuss the implications of our results for future chemical tagging studies.

Polarized Sunyaev Zel'dovich tomography

NASA Astrophysics Data System (ADS)

Deutsch, Anne-Sylvie; Johnson, Matthew C.; Münchmeyer, Moritz; Terrana, Alexandra

2018-04-01

Secondary CMB polarization is induced by the late-time scattering of CMB photons by free electrons on our past light cone. This polarized Sunyaev Zel'dovich (pSZ) effect is sensitive to the electrons' locally observed CMB quadrupole, which is sourced primarily by long wavelength inhomogeneities. By combining the remote quadrupoles measured by free electrons throughout the Universe after reionization, the pSZ effect allows us to obtain additional information about large scale modes beyond what can be learned from our own last scattering surface. Here we determine the power of pSZ tomography, in which the pSZ effect is cross-correlated with the density field binned at several redshifts, to provide information about the long wavelength Universe. The signal we explore here is a power asymmetry in the cross-correlation between E or B mode CMB polarization and the density field. We compare this to the cosmic variance limited noise: the random chance to get a power asymmetry in the absence of a large scale quadrupole field. By computing the necessary transfer functions and cross-correlations, we compute the signal-to-noise ratio attainable by idealized next generation CMB experiments and galaxy surveys. We find that a signal-to-noise ratio of ~ 1‑10 is in principle attainable over a significant range of power multipoles, with the strongest signal coming from the first multipoles in the lowest redshift bins. These results prompt further assessment of realistically measuring the pSZ signal and the potential impact for constraining cosmology on large scales.

Dynamic functional connectivity: Promise, issues, and interpretations

PubMed Central

Hutchison, R. Matthew; Womelsdorf, Thilo; Allen, Elena A.; Bandettini, Peter A.; Calhoun, Vince D.; Corbetta, Maurizio; Penna, Stefania Della; Duyn, Jeff H.; Glover, Gary H.; Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Keilholz, Shella; Kiviniemi, Vesa; Leopold, David A.; de Pasquale, Francesco; Sporns, Olaf; Walter, Martin; Chang, Catie

2013-01-01

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations. PMID:23707587

Detectability of large-scale power suppression in the galaxy distribution

NASA Astrophysics Data System (ADS)

Gibelyou, Cameron; Huterer, Dragan; Fang, Wenjuan

2010-12-01

Suppression in primordial power on the Universe’s largest observable scales has been invoked as a possible explanation for large-angle observations in the cosmic microwave background, and is allowed or predicted by some inflationary models. Here we investigate the extent to which such a suppression could be confirmed by the upcoming large-volume redshift surveys. For definiteness, we study a simple parametric model of suppression that improves the fit of the vanilla ΛCDM model to the angular correlation function measured by WMAP in cut-sky maps, and at the same time improves the fit to the angular power spectrum inferred from the maximum likelihood analysis presented by the WMAP team. We find that the missing power at large scales, favored by WMAP observations within the context of this model, will be difficult but not impossible to rule out with a galaxy redshift survey with large-volume (˜100Gpc3). A key requirement for success in ruling out power suppression will be having redshifts of most galaxies detected in the imaging survey.

A large-scale perspective on stress-induced alterations in resting-state networks

NASA Astrophysics Data System (ADS)

Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

2016-02-01

Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

Large-scale modeling of rain fields from a rain cell deterministic model

NASA Astrophysics Data System (ADS)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

Strategies for Interactive Visualization of Large Scale Climate Simulations

NASA Astrophysics Data System (ADS)

Xie, J.; Chen, C.; Ma, K.; Parvis

2011-12-01

With the advances in computational methods and supercomputing technology, climate scientists are able to perform large-scale simulations at unprecedented resolutions. These simulations produce data that are time-varying, multivariate, and volumetric, and the data may contain thousands of time steps with each time step having billions of voxels and each voxel recording dozens of variables. Visualizing such time-varying 3D data to examine correlations between different variables thus becomes a daunting task. We have been developing strategies for interactive visualization and correlation analysis of multivariate data. The primary task is to find connection and correlation among data. Given the many complex interactions among the Earth's oceans, atmosphere, land, ice and biogeochemistry, and the sheer size of observational and climate model data sets, interactive exploration helps identify which processes matter most for a particular climate phenomenon. We may consider time-varying data as a set of samples (e.g., voxels or blocks), each of which is associated with a vector of representative or collective values over time. We refer to such a vector as a temporal curve. Correlation analysis thus operates on temporal curves of data samples. A temporal curve can be treated as a two-dimensional function where the two dimensions are time and data value. It can also be treated as a point in the high-dimensional space. In this case, to facilitate effective analysis, it is often necessary to transform temporal curve data from the original space to a space of lower dimensionality. Clustering and segmentation of temporal curve data in the original or transformed space provides us a way to categorize and visualize data of different patterns, which reveals connection or correlation of data among different variables or at different spatial locations. We have employed the power of GPU to enable interactive correlation visualization for studying the variability and correlations of a single or a pair of variables. It is desired to create a succinct volume classification that summarizes the connection among all correlation volumes with respect to various reference locations. Providing a reference location must correspond to a voxel position, the number of correlation volumes equals the total number of voxels. A brute-force solution takes all correlation volumes as the input and classifies their corresponding voxels according to their correlation volumes' distance. For large-scale time-varying multivariate data, calculating all these correlation volumes on-the-fly and analyzing the relationships among them is not feasible. We have developed a sampling-based approach for volume classification in order to reduce the computation cost of computing the correlation volumes. Users are able to employ their domain knowledge in selecting important samples. The result is a static view that captures the essence of correlation relationships; i.e., for all voxels in the same cluster, their corresponding correlation volumes are similar. This sampling-based approach enables us to obtain an approximation of correlation relations in a cost-effective manner, thus leading to a scalable solution to investigate large-scale data sets. These techniques empower climate scientists to study large data from their simulations.

The Specific Level of Functioning Scale: construct validity, internal consistency and factor structure in a large Italian sample of people with schizophrenia living in the community.

PubMed

Mucci, Armida; Rucci, Paola; Rocca, Paola; Bucci, Paola; Gibertoni, Dino; Merlotti, Eleonora; Galderisi, Silvana; Maj, Mario

2014-10-01

The study aimed to assess the construct validity, internal consistency and factor structure of the Specific Levels of Functioning Scale (SLOF), a multidimensional instrument assessing real life functioning. The study was carried out in 895 Italian people with schizophrenia, all living in the community and attending the outpatient units of 26 university psychiatric clinics and/or community mental health departments. The construct validity of the SLOF was analyzed by means of the multitrait-multimethod approach, using the Personal and Social Performance (PSP) Scale as the gold standard. The factor structure of the SLOF was examined using both an exploratory principal component analysis and a confirmatory factor analysis. The six factors identified using exploratory principal component analysis explained 57.1% of the item variance. The examination of the multitrait-multimethod matrix revealed that the SLOF factors had high correlations with PSP factors measuring the same constructs and low correlations with PSP factors measuring different constructs. The confirmatory factor analysis (CFA) corroborated the 6-factor structure reported in the original validation study. Loadings were all significant and ranged from a minimum of 0.299 to a maximum of 0.803. The CFA model was adequately powered and had satisfactory goodness of fit indices (comparative fit index=0.927, Tucker-Lewis index=0.920 and root mean square error of approximation=0.047, 95% CI 0.045-0.049). The present study confirms, in a large sample of Italian people with schizophrenia living in the community, that the SLOF is a reliable and valid instrument for the assessment of social functioning. It has good construct validity and internal consistency, and a well-defined factor structure. Copyright © 2014 Elsevier B.V. All rights reserved.

The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity

PubMed Central

Gallos, Lazaros K.; Sigman, Mariano; Makse, Hernán A.

2012-01-01

The human brain has been studied at multiple scales, from neurons, circuits, areas with well-defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. PMID:22586406

The influence of super-horizon scales on cosmological observables generated during inflation

NASA Astrophysics Data System (ADS)

Matarrese, Sabino; Musso, Marcello A.; Riotto, Antonio

2004-05-01

Using the techniques of out-of-equilibrium field theory, we study the influence on properties of cosmological perturbations generated during inflation on observable scales coming from fluctuations corresponding today to scales much bigger than the present Hubble radius. We write the effective action for the coarse grained inflaton perturbations, integrating out the sub-horizon modes, which manifest themselves as a coloured noise and lead to memory effects. Using the simple model of a scalar field with cubic self-interactions evolving in a fixed de Sitter background, we evaluate the two- and three-point correlation function on observable scales. Our basic procedure shows that perturbations do preserve some memory of the super-horizon scale dynamics, in the form of scale dependent imprints in the statistical moments. In particular, we find a blue tilt of the power spectrum on large scales, in agreement with the recent results of the WMAP collaboration which show a suppression of the lower multipoles in the cosmic microwave background anisotropies, and a substantial enhancement of the intrinsic non-Gaussianity on large scales.

Large-scale galaxy flow from a non-gravitational impulse

NASA Technical Reports Server (NTRS)

Hogan, Craig J.; Kaiser, Nick

1989-01-01

A theory is presented describing linear perturbations of an expanding universe containing multiple, independently perturbed, collisionless, gravitationally coupled constituents. Solutions are found in the limit where one initially unperturbed component dominates the total density. The theory is applied to perturbations generated by a nongravitational process in one or more of the light components, as would occur in explosive or radiation-pressure-instability theories of galaxy formation. The apparent dynamical density parameter and correlations between density and velocity amplitude for various populations, are evaluated as a function of cosmic scale factor.

Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

PubMed

Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

2017-06-27

Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

Functional Brain Networks Develop from a “Local to Distributed” Organization

PubMed Central

Power, Jonathan D.; Dosenbach, Nico U. F.; Church, Jessica A.; Miezin, Francis M.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways. PMID:19412534

Functional brain networks develop from a "local to distributed" organization.

PubMed

Fair, Damien A; Cohen, Alexander L; Power, Jonathan D; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Schlaggar, Bradley L; Petersen, Steven E

2009-05-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength) between regions close in anatomical space and 'integration' (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.

Large scale anomalies in the microwave background: causation and correlation.

PubMed

Aslanyan, Grigor; Easther, Richard

2013-12-27

Most treatments of large scale anomalies in the microwave sky are a posteriori, with unquantified look-elsewhere effects. We contrast these with physical models of specific inhomogeneities in the early Universe which can generate these apparent anomalies. Physical models predict correlations between candidate anomalies and the corresponding signals in polarization and large scale structure, reducing the impact of cosmic variance. We compute the apparent spatial curvature associated with large-scale inhomogeneities and show that it is typically small, allowing for a self-consistent analysis. As an illustrative example we show that a single large plane wave inhomogeneity can contribute to low-l mode alignment and odd-even asymmetry in the power spectra and the best-fit model accounts for a significant part of the claimed odd-even asymmetry. We argue that this approach can be generalized to provide a more quantitative assessment of potential large scale anomalies in the Universe.

Relative velocity change measurement based on seismic noise analysis in exploration geophysics

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubuq, D.

2011-12-01

Passive monitoring techniques based on noise cross-correlation analysis are still debated in exploration geophysics even if recent studies showed impressive performance in seismology at larger scale. Time evolution of complex geological structure using noise data includes localization of noise sources and measurement of relative velocity variations. Monitoring relative velocity variations only requires the measurement of phase shifts of seismic noise cross-correlation functions computed for successive time recordings. The existing algorithms, such as the Stretching and the Doublet, classically need great efforts in terms of computation time, making them not practical when continuous dataset on dense arrays are acquired. We present here an innovative technique for passive monitoring based on the measure of the instantaneous phase of noise-correlated signals. The Instantaneous Phase Variation (IPV) technique aims at cumulating the advantages of the Stretching and Doublet methods while proposing a faster measurement of the relative velocity change. The IPV takes advantage of the Hilbert transform to compute in the time domain the phase difference between two noise correlation functions. The relative velocity variation is measured through the slope of the linear regression of the phase difference curve as a function of correlation time. The large amount of noise correlation functions, classically available at exploration scale on dense arrays, allows for a statistical analysis that further improves the precision of the estimation of the velocity change. In this work, numerical tests first aim at comparing the IPV performance to the Stretching and Doublet techniques in terms of accuracy, robustness and computation time. Then experimental results are presented using a seismic noise dataset with five days of continuous recording on 397 geophones spread on a ~1 km-squared area.

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

Mouse Activity across Time Scales: Fractal Scenarios

PubMed Central

Lima, G. Z. dos Santos; Lobão-Soares, B.; do Nascimento, G. C.; França, Arthur S. C.; Muratori, L.; Ribeiro, S.; Corso, G.

2014-01-01

In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slow-wave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity - a typical 1/f complex pattern - while for large time intervals there is anti-correlation. High correlation of short intervals ( to : waking state and to : SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales ( to : waking state and to : SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anti-correlation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better understanding of neuroautonomic regulation mechanisms. PMID:25275515

Clinical Correlations of Brain Lesion Location in Multiple Sclerosis: Voxel-Based Analysis of a Large Clinical Trial Dataset.

PubMed

Altermatt, Anna; Gaetano, Laura; Magon, Stefano; Häring, Dieter A; Tomic, Davorka; Wuerfel, Jens; Radue, Ernst-Wilhelm; Kappos, Ludwig; Sprenger, Till

2018-05-29

There is a limited correlation between white matter (WM) lesion load as determined by magnetic resonance imaging and disability in multiple sclerosis (MS). The reasons for this so-called clinico-radiological paradox are diverse and may, at least partly, relate to the fact that not just the overall lesion burden, but also the exact anatomical location of lesions predict the severity and type of disability. We aimed at studying the relationship between lesion distribution and disability using a voxel-based lesion probability mapping approach in a very large dataset of MS patients. T2-weighted lesion masks of 2348 relapsing-remitting MS patients were spatially normalized to standard stereotaxic space by non-linear registration. Relations between supratentorial WM lesion locations and disability measures were assessed using a non-parametric ANCOVA (Expanded Disability Status Scale [EDSS]; Multiple Sclerosis Functional Composite, and subscores; Modified Fatigue Impact Scale) or multinomial ordinal logistic regression (EDSS functional subscores). Data from 1907 (81%) patients were included in the analysis because of successful registration. The lesion mapping showed similar areas to be associated with the different disability scales: periventricular regions in temporal, frontal, and limbic lobes were predictive, mainly affecting the posterior thalamic radiation, the anterior, posterior, and superior parts of the corona radiata. In summary, significant associations between lesion location and clinical scores were found in periventricular areas. Such lesion clusters appear to be associated with impairment of different physical and cognitive abilities, probably because they affect commissural and long projection fibers, which are relevant WM pathways supporting many different brain functions.

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

DOE PAGES

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

2017-10-26

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

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

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

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.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks

PubMed Central

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory. PMID:28736535

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

PubMed

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

Combining Density Functional Theory and Green's Function Theory: Range-Separated, Nonlocal, Dynamic, and Orbital-Dependent Hybrid Functional.

PubMed

Kananenka, Alexei A; Zgid, Dominika

2017-11-14

We present a rigorous framework which combines single-particle Green's function theory with density functional theory based on a separation of electron-electron interactions into short- and long-range components. Short-range contribution to the total energy and exchange-correlation potential is provided by a density functional approximation, while the long-range contribution is calculated using an explicit many-body Green's function method. Such a hybrid results in a nonlocal, dynamic, and orbital-dependent exchange-correlation functional of a single-particle Green's function. In particular, we present a range-separated hybrid functional called srSVWN5-lrGF2 which combines the local-density approximation and the second-order Green's function theory. We illustrate that similarly to density functional approximations, the new functional is weakly basis-set dependent. Furthermore, it offers an improved description of the short-range dynamic correlation. The many-body contribution to the functional mitigates the many-electron self-interaction error present in many density functional approximations and provides a better description of molecular properties. Additionally, we illustrate that the new functional can be used to scale down the self-energy and, therefore, introduce an additional sparsity to the self-energy matrix that in the future can be exploited in calculations for large molecules or periodic systems.

Scaling of the space-time correlation function of particle currents in a suspension of hard-sphere-like particles: exposing when the motion of particles is Brownian.

PubMed

van Megen, W; Martinez, V A; Bryant, G

2009-12-18

The current correlation function is determined from dynamic light scattering measurements of a suspension of particles with hard spherelike interactions. For suspensions in thermodynamic equilibrium we find scaling of the space and time variables of the current correlation function. This finding supports the notion that the movement of suspended particles can be described in terms of uncorrelated Brownian encounters. However, in the metastable fluid, at volume fractions above freezing, this scaling fails.

Energy transfer, pressure tensor, and heating of kinetic plasma

NASA Astrophysics Data System (ADS)

Yang, Yan; Matthaeus, William H.; Parashar, Tulasi N.; Haggerty, Colby C.; Roytershteyn, Vadim; Daughton, William; Wan, Minping; Shi, Yipeng; Chen, Shiyi

2017-07-01

Kinetic plasma turbulence cascade spans multiple scales ranging from macroscopic fluid flow to sub-electron scales. Mechanisms that dissipate large scale energy, terminate the inertial range cascade, and convert kinetic energy into heat are hotly debated. Here, we revisit these puzzles using fully kinetic simulation. By performing scale-dependent spatial filtering on the Vlasov equation, we extract information at prescribed scales and introduce several energy transfer functions. This approach allows highly inhomogeneous energy cascade to be quantified as it proceeds down to kinetic scales. The pressure work, - ( P . ∇ ) . u , can trigger a channel of the energy conversion between fluid flow and random motions, which contains a collision-free generalization of the viscous dissipation in collisional fluid. Both the energy transfer and the pressure work are strongly correlated with velocity gradients.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

USGS Publications Warehouse

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

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

Evolution of clustering length, large-scale bias, and host halo mass at 2 < z < 5 in the VIMOS Ultra Deep Survey (VUDS)⋆

NASA Astrophysics Data System (ADS)

Durkalec, A.; Le Fèvre, O.; Pollo, A.; de la Torre, S.; Cassata, P.; Garilli, B.; Le Brun, V.; Lemaux, B. C.; Maccagni, D.; Pentericci, L.; Tasca, L. A. M.; Thomas, R.; Vanzella, E.; Zamorani, G.; Zucca, E.; Amorín, R.; Bardelli, S.; Cassarà, L. P.; Castellano, M.; Cimatti, A.; Cucciati, O.; Fontana, A.; Giavalisco, M.; Grazian, A.; Hathi, N. P.; Ilbert, O.; Paltani, S.; Ribeiro, B.; Schaerer, D.; Scodeggio, M.; Sommariva, V.; Talia, M.; Tresse, L.; Vergani, D.; Capak, P.; Charlot, S.; Contini, T.; Cuby, J. G.; Dunlop, J.; Fotopoulou, S.; Koekemoer, A.; López-Sanjuan, C.; Mellier, Y.; Pforr, J.; Salvato, M.; Scoville, N.; Taniguchi, Y.; Wang, P. W.

2015-11-01

We investigate the evolution of galaxy clustering for galaxies in the redshift range 2.0

Physical Function Assessment in a Community-Dwelling Population of U.S. Chinese Older Adults

PubMed Central

Chang, E-Shien; Simon, Melissa A.

2014-01-01

Background. This report describes the levels of physical function in U.S. Chinese older adults utilizing self-reported and performance-based measures, and examines the association between sociodemographic characteristics and physical function. Methods. The Population Study of Chinese Elderly in Chicago enrolled an epidemiological cohort of 3,159 community-dwelling Chinese older adults aged 60 and older. We collected self-reported physical function using Katz activities of daily living and Lawton instrumental activities of daily living items, the Index of Mobility scale, and the Index of Basic Physical Activities scale. Participants were also asked to perform tasks in chair stand, tandem stand, and timed walk. We computed Pearson and Spearman correlation coefficients to examine the correlation between sociodemographic and physical function variables. Results. A total of 7.8% of study participants experienced activities of daily living impairment, and 50.2% experienced instrumental activities of daily living impairment. With respect to physical performance testing, 11.4% of the participants were not able to complete chair stand for five times, 8.5% of the participants were unable to do chair stands at all. Older age, female gender, lower education level, being unmarried, living with fewer people in the same household, having fewer children, living fewer years in the United States, living fewer years in the community, and worsening health status were significantly correlated with lower levels of physical function. Conclusions. Utilizing self-reported and performance-based measures of physical function in a large population-based study of U.S. Chinese older adults, our findings expand current understanding of minority older adults’ functional status. PMID:25378446

Angular correlation function of 1.5 million luminous red galaxies: clustering evolution and a search for baryon acoustic oscillations

NASA Astrophysics Data System (ADS)

Sawangwit, U.; Shanks, T.; Abdalla, F. B.; Cannon, R. D.; Croom, S. M.; Edge, A. C.; Ross, Nicholas P.; Wake, D. A.

2011-10-01

We present the angular correlation function measured from photometric samples comprising 1562 800 luminous red galaxies (LRGs). Three LRG samples were extracted from the Sloan Digital Sky Survey (SDSS) imaging data, based on colour-cut selections at redshifts, z≈ 0.35, 0.55 and 0.7 as calibrated by the spectroscopic surveys, SDSS-LRG, 2dF-SDSS LRG and QSO (quasi-stellar object) (2SLAQ) and the AAΩ-LRG survey. The galaxy samples cover ≈7600 deg2 of sky, probing a total cosmic volume of ≈5.5 h-3 Gpc3. The small- and intermediate-scale correlation functions generally show significant deviations from a single power-law fit with a well-detected break at ≈1 h-1 Mpc, consistent with the transition scale between the one- and two-halo terms in halo occupation models. For galaxy separations 1-20 h-1 Mpc and at fixed luminosity, we see virtually no evolution of the clustering with redshift and the data are consistent with a simple high peaks biasing model where the comoving LRG space density is constant with z. At fixed z, the LRG clustering amplitude increases with luminosity in accordance with the simple high peaks model, with a typical LRG dark matter halo mass 1013-1014 h-1 M⊙. For r < 1 h-1 Mpc, the evolution is slightly faster and the clustering decreases towards high redshift consistent with a virialized clustering model. However, assuming the halo occupation distribution (HOD) and Λ cold dark matter (ΛCDM) halo merger frameworks, ˜2-3 per cent/Gyr of the LRGs are required to merge in order to explain the small scales clustering evolution, consistent with previous results. At large scales, our result shows good agreement with the SDSS-LRG result of Eisenstein et al. but we find an apparent excess clustering signal beyond the baryon acoustic oscillations (BAO) scale. Angular power spectrum analyses of similar LRG samples also detect a similar apparent large-scale clustering excess but more data are required to check for this feature in independent galaxy data sets. Certainly, if the ΛCDM model were correct then we would have to conclude that this excess was caused by systematics at the level of Δw≈ 0.001-0.0015 in the photometric AAΩ-LRG sample.

Sexual function in cervical cancer patients: Psychometric properties and performance of a Chinese version of the Female Sexual Function Index.

PubMed

Liu, Huayun; Yu, Juping; Chen, Yongyi; He, Pingping; Zhou, Lianqing; Tang, Xinhui; Liu, Xiangyu; Li, Xuying; Wu, Yanping; Wang, Yuhua

2016-02-01

This study aimed to examine the psychometric properties and performance of a Chinese version of the Female Sexual Function Index (FSFI) among a sample of Chinese women with cervical cancer. A cross-sectional survey design was used. The respondents included 215 women with cervical cancer in an oncology hospital in China. A translated Chinese version of the FSFI was used to investigate their sexual functioning. Psychometric testing included internal consistency reliability (Cronbach's alpha coefficient and item-total correlations), test-retest reliability, construct validity (principal component analysis via oblique rotation and confirmatory factor analysis), and variability (floor and ceiling effects). The mean score of the total scale was 20.65 ± 4.77. The Cronbach values were .94 for the total scale, .72-.90 for the domains. Test-retest correlation coefficients over 2-4 weeks were .84 (p < .05) for the total scale, .68-.83 for the subscales. Item-total correlation coefficients ranged between .47 and .83 (p < .05). A five-factor model was identified via principal component analysis and established by confirmatory factor analysis, including desire/arousal, lubrication, orgasm, satisfaction, and pain. There was no evidence of floor or ceiling effects. With good psychometric properties similar to its original English version, this Chinese version of the FSFI is demonstrated to be a reliable and valid instrument that can be used to assess sexual functioning of women with cervical cancer in China. Future research is still needed to confirm its psychometric properties and performance among a large sample. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spanish adaptation of the internal functioning of the Work Teams Scale (QFI-22).

PubMed

Ficapal-Cusí, Pilar; Boada-Grau, Joan; Torrent-Sellens, Joan; Vigil-Colet, Andreu

2014-05-01

The aim of this article is to develop the Spanish adaptation of the internal functioning of Work Teams Scale (QFI-22). The scale was adapted from the French version, and was applied to a sample of 1,055 employees working for firms operating in Spain. The article analyses the internal structure (exploratory and confirmatory factor analysis) and internal consistency, and provides convergent validity evidence of the scale. The QFI-22 scale shows the same internal structure as the original. Factor analysis confirmed the existence of two factors: interpersonal support and team work management, with good internal consistency coefficients (α1 = .93, α2 = .92). Regarding validity evidence, the QFI-22 scale has significant correlations with other correlates and alternative scales used for comparison purposes. The two factors correlated positively with team vision, participation safety, task orientation and support for innovation (Team Climate Inventory, TCI scale), with progressive culture (Organisational Culture, X-Y scale), and with creating change, customer focus and organisational learning (Denison Organizational Culture Survey, DOCS scale). In contrast, the two factors correlated negatively with traditional culture (X-Y scale). The QFI-22 scale is a useful instrument for assessing the internal functioning of work teams.

Weak Lensing by Large-Scale Structure: A Dark Matter Halo Approach.

PubMed

Cooray; Hu; Miralda-Escudé

2000-05-20

Weak gravitational lensing observations probe the spectrum and evolution of density fluctuations and the cosmological parameters that govern them, but they are currently limited to small fields and subject to selection biases. We show how the expected signal from large-scale structure arises from the contributions from and correlations between individual halos. We determine the convergence power spectrum as a function of the maximum halo mass and so provide the means to interpret results from surveys that lack high-mass halos either through selection criteria or small fields. Since shot noise from rare massive halos is mainly responsible for the sample variance below 10&arcmin;, our method should aid our ability to extract cosmological information from small fields.

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

PubMed

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

2011-11-01

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

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

PubMed Central

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

2014-01-01

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

Spatio-temporal correlations in the Manna model in one, three and five dimensions

NASA Astrophysics Data System (ADS)

Willis, Gary; Pruessner, Gunnar

2018-02-01

Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five dimensions.

Standardization of a spinal cord lesion model and neurologic evaluation using mice

PubMed Central

Borges, Paulo Alvim; Cristante, Alexandre Fogaça; de Barros-Filho, Tarcísio Eloy Pessoa; Natalino, Renato Jose Mendonça; dos Santos, Gustavo Bispo; Marcon, Raphael Marcus

2018-01-01

OBJECTIVE: To standardize a spinal cord lesion mouse model. METHODS: Thirty BALB/c mice were divided into five groups: four experimental groups and one control group (sham). The experimental groups were subjected to spinal cord lesion by a weight drop from different heights after laminectomy whereas the sham group only underwent laminectomy. Mice were observed for six weeks, and functional behavior scales were applied. The mice were then euthanized, and histological investigations were performed to confirm and score spinal cord lesion. The findings were evaluated to prove whether the method of administering spinal cord lesion was effective and different among the groups. Additionally, we correlated the results of the functional scales with the results from the histology evaluations to identify which scale is more reliable. RESULTS: One mouse presented autophagia, and six mice died during the experiment. Because four of the mice that died were in Group 5, Group 5 was excluded from the study. All the functional scales assessed proved to be significantly different from each other, and mice presented functional evolution during the experiment. Spinal cord lesion was confirmed by histology, and the results showed a high correlation between the Basso, Beattie, Bresnahan Locomotor Rating Scale and the Basso Mouse Scale. The mouse function scale showed a moderate to high correlation with the histological findings, and the horizontal ladder test had a high correlation with neurologic degeneration but no correlation with the other histological parameters evaluated. CONCLUSION: This spinal cord lesion mouse model proved to be effective and reliable with exception of lesions caused by a 10-g drop from 50 mm, which resulted in unacceptable mortality. The Basso, Beattie, Bresnahan Locomotor Rating Scale and Basso Mouse Scale are the most reliable functional assessments, and but the horizontal ladder test is not recommended. PMID:29561931

An investigation of the validity of six measures of physical function in people awaiting joint replacement surgery of the hip or knee.

PubMed

Gill, Stephen D; de Morton, Natalie A; Mc Burney, Helen

2012-10-01

To assess and compare the validity of six physical function measures in people awaiting hip or knee joint replacement. Eighty-two people awaiting hip or knee replacement were assessed using six physical function measures including the WOMAC Function scale, SF-36 Physical Function scale, SF-36 Physical Component Summary scale, Patient Specific Functional Scale, 30-second chair stand test, and 50-foot timed walk. Validity was assessed using a head-to-head comparison design. Convergent validity was demonstrated with significant correlations between most measures (Spearman's rho 0.22 to 0.71). The Patient Specific Functional Scale had the lowest correlations with other measures of physical function. Discriminant validity was demonstrated with low correlations between mental health and physical function scores (Spearman's rho -0.12 to 0.33). Only the WOMAC Function scale, 30-second chair stand test, and 50-foot timed walk demonstrated known groups validity when scores for participants who walked with a gait aid were compared with those who did not. Standardized response means and Guyatt's responsiveness indexes indicated that the SF-36 was the least responsive measure. For those awaiting joint replacement surgery of the hip or knee, the current investigation found that the WOMAC Function scale, 30-second chair stand test, and 50-foot timed walk demonstrated the most evidence of validity. The Patient Specific Functional Scale might complement other measures by capturing a different aspect of physical function.

Statistical Analysis of Large-Scale Structure of Universe

NASA Astrophysics Data System (ADS)

Tugay, A. V.

While galaxy cluster catalogs were compiled many decades ago, other structural elements of cosmic web are detected at definite level only in the newest works. For example, extragalactic filaments were described by velocity field and SDSS galaxy distribution during the last years. Large-scale structure of the Universe could be also mapped in the future using ATHENA observations in X-rays and SKA in radio band. Until detailed observations are not available for the most volume of Universe, some integral statistical parameters can be used for its description. Such methods as galaxy correlation function, power spectrum, statistical moments and peak statistics are commonly used with this aim. The parameters of power spectrum and other statistics are important for constraining the models of dark matter, dark energy, inflation and brane cosmology. In the present work we describe the growth of large-scale density fluctuations in one- and three-dimensional case with Fourier harmonics of hydrodynamical parameters. In result we get power-law relation for the matter power spectrum.

States of mind: Emotions, body feelings, and thoughts share distributed neural networks

PubMed Central

Oosterwijk, Suzanne; Lindquist, Kristen A.; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

2012-01-01

Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. PMID:22677148

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.

A Kinematically Consistent Two-Point Correlation Function

NASA Technical Reports Server (NTRS)

Ristorcelli, J. R.

1998-01-01

A simple kinematically consistent expression for the longitudinal two-point correlation function related to both the integral length scale and the Taylor microscale is obtained. On the inner scale, in a region of width inversely proportional to the turbulent Reynolds number, the function has the appropriate curvature at the origin. The expression for two-point correlation is related to the nonlinear cascade rate, or dissipation epsilon, a quantity that is carried as part of a typical single-point turbulence closure simulation. Constructing an expression for the two-point correlation whose curvature at the origin is the Taylor microscale incorporates one of the fundamental quantities characterizing turbulence, epsilon, into a model for the two-point correlation function. The integral of the function also gives, as is required, an outer integral length scale of the turbulence independent of viscosity. The proposed expression is obtained by kinematic arguments; the intention is to produce a practically applicable expression in terms of simple elementary functions that allow an analytical evaluation, by asymptotic methods, of diverse functionals relevant to single-point turbulence closures. Using the expression devised an example of the asymptotic method by which functionals of the two-point correlation can be evaluated is given.

A marked correlation function for constraining modified gravity models

NASA Astrophysics Data System (ADS)

White, Martin

2016-11-01

Future large scale structure surveys will provide increasingly tight constraints on our cosmological model. These surveys will report results on the distance scale and growth rate of perturbations through measurements of Baryon Acoustic Oscillations and Redshift-Space Distortions. It is interesting to ask: what further analyses should become routine, so as to test as-yet-unknown models of cosmic acceleration? Models which aim to explain the accelerated expansion rate of the Universe by modifications to General Relativity often invoke screening mechanisms which can imprint a non-standard density dependence on their predictions. This suggests density-dependent clustering as a `generic' constraint. This paper argues that a density-marked correlation function provides a density-dependent statistic which is easy to compute and report and requires minimal additional infrastructure beyond what is routinely available to such survey analyses. We give one realization of this idea and study it using low order perturbation theory. We encourage groups developing modified gravity theories to see whether such statistics provide discriminatory power for their models.

Large-scale correlations in gas traced by Mg II absorbers around low-mass galaxies

NASA Astrophysics Data System (ADS)

Kauffmann, Guinevere

2018-03-01

The physical origin of the large-scale conformity in the colours and specific star formation rates of isolated low-mass central galaxies and their neighbours on scales in excess of 1 Mpc is still under debate. One possible scenario is that gas is heated over large scales by feedback from active galactic nuclei (AGNs), leading to coherent modulation of cooling and star formation between well-separated galaxies. In this Letter, the metal line absorption catalogue of Zhu & Ménard is used to probe gas out to large projected radii around a sample of a million galaxies with stellar masses ˜1010M⊙ and photometric redshifts in the range 0.4 < z < 0.8 selected from Sloan Digital Sky Survey imaging data. This galaxy sample covers an effective volume of 2.2 Gpc3. A statistically significant excess of Mg II absorbers is present around the red-low-mass galaxies compared to their blue counterparts out to projected radii of 10 Mpc. In addition, the equivalent width distribution function of Mg II absorbers around low-mass galaxies is shown to be strongly affected by the presence of a nearby (Rp < 2 Mpc) radio-loud AGNs out to projected radii of 5 Mpc.

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

PubMed

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2016-07-12

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

Sexual orientation and boyhood gender conformity: development of the Boyhood Gender Conformity Scale (BGCS)

PubMed

Hockenberry, S L; Billingham, R E

1987-12-01

Two hundred twenty-five [corrected] respondents (109 [corrected] heterosexuals and 116 [corrected] homosexuals) completed a survey containing a 20-item Boyhood Gender Conformity Scale (BGCS). This scale was largely composed of edited and abridged gender items from Part A of Freund et al.'s Feminine Gender Identity Scale (FGIS-A) and Whitam's "childhood indicators." The combined scale was developed in an attempt to obtain a reliable, valid, and potent discriminating instrument for accurately classifying adult male respondents for sexual orientation on the basis of their reported boyhood gender conformity or nonconforming behavior and identity. In addition, 33% of these respondents were administered the original FGIS-A and Whitam inventory during a 2-week test-retest analysis conducted to determine the validity and reliability of the new instrument. All the original items significantly discriminated between heterosexual and homosexual respondents. From these a 13-item function and a 5-item function proved to be the most powerful discriminators between the two groups. Significant correlations between each of the three scales and a very high test-retest correlation coefficient supported the reliability and validity assumption for the BGCS. The conclusion was made that the five-item function (playing with boys, preferring [corrected] boys' games, imagining self as sports figure, reading adventure and sports stories, considered a "sissy") was the most potent and parsimonious discriminator among adult males for sexual orientation. It was similarly noted that the absence of masculine behaviors and traits appeared to be a more powerful predictor of later homosexual orientation than the traditionally feminine or cross-sexed traits and behaviors.

Visualisation and orbital-free parametrisation of the large-Z scaling of the kinetic energy density of atoms

NASA Astrophysics Data System (ADS)

Cancio, Antonio C.; Redd, Jeremy J.

2017-03-01

The scaling of neutral atoms to large Z, combining periodicity with a gradual trend to homogeneity, is a fundamental probe of density functional theory, one that has driven recent advances in understanding both the kinetic and exchange-correlation energies. Although research focus is normally upon the scaling of integrated energies, insights can also be gained from energy densities. We visualise the scaling of the positive-definite kinetic energy density (KED) in closed-shell atoms, in comparison to invariant quantities based upon the gradient and Laplacian of the density. We notice a striking fit of the KED within the core of any atom to a gradient expansion using both the gradient and the Laplacian, appearing as an asymptotic limit around which the KED oscillates. The gradient expansion is qualitatively different from that derived from first principles for a slowly varying electron gas and is correlated with a nonzero Pauli contribution to the KED near the nucleus. We propose and explore orbital-free meta-GGA models for the kinetic energy to describe these features, with some success, but the effects of quantum oscillations in the inner shells of atoms make a complete parametrisation difficult. We discuss implications for improved orbital-free description of molecular properties.

Baryon interactions from lattice QCD with physical masses — strangeness S = -1 sector —

NASA Astrophysics Data System (ADS)

Nemura, Hidekatsu; Aoki, Sinya; Doi, Takumi; Gongyo, Shinya; Hatsuda, Tetsuo; Ikeda, Yoichi; Inoue, Takashi; Iritani, Takumi; Ishii, Noriyoshi; Miyamoto, Takaya; Sasaki, Kenji

2018-03-01

We present our recent results of baryon interactions with strangeness S = -1 based on Nambu-Bethe-Salpeter (NBS) correlation functions calculated fromlattice QCD with almost physical quark masses corresponding to (mk,mk) ≈ (146, 525) MeV and large volume (La)4 ≈ (96a)4 ≈ (8.1 fm)4. In order to perform a comprehensive study of baryon interactions, a large number of NBS correlation functions from NN to ΞΞ are calculated simultaneously by using large scale computer resources. In this contribution, we focus on the strangeness S = -1 channels of the hyperon interactions by means of HAL QCD method. Four sets of three potentials (the 3S1 - 3 D1 central, 3S1 - 3 D1 tensor, and the 1S0 central potentials) are presented for the ∑N - ∑N (the isospin I = 3/2) diagonal, the ∧N - ∧N diagonal, the ∧N → ∑N transition, and the ∑N - ∑N (I = 1/2) diagonal interactions. Scattering phase shifts for ∑N (I = 3/2) system are presented.

Brain functional network abnormality extends beyond the sensorimotor network in brachial plexus injury patients.

PubMed

Feng, Jun-Tao; Liu, Han-Qiu; Hua, Xu-Yun; Gu, Yu-Dong; Xu, Jian-Guang; Xu, Wen-Dong

2016-12-01

Brachial plexus injury (BPI) is a type of severe peripheral nerve trauma that leads to central remodeling in the brain, as revealed by functional MRI analysis. However, previously reported remodeling is mostly restricted to sensorimotor areas of the brain. Whether this disturbance in the sensorimotor network leads to larger-scale functional remodeling remains unknown. We sought to explore the higher-level brain functional abnormality pattern of BPI patients from a large-scale network function connectivity dimension in 15 right-handed BPI patients. Resting-state functional MRI data were collected and analyzed using independent component analysis methods. Five components of interest were recognized and compared between patients and healthy subjects. Patients showed significantly altered brain local functional activities in the bilateral fronto-parietal network (FPN), sensorimotor network (SMN), and executive-control network (ECN) compared with healthy subjects. Moreover, functional connectivity between SMN and ECN were significantly less in patients compared with healthy subjects, and connectivity strength between ECN and SMN was negatively correlated with patients' residual function of the affected limb. Functional connectivity between SMN and right FPN were also significantly less than in controls, although connectivity between ECN and default mode network (DMN) was greater than in controls. These data suggested that brain functional disturbance in BPI patients extends beyond the sensorimotor network and cascades serial remodeling in the brain, which significantly correlates with residual hand function of the paralyzed limb. Furthermore, functional remodeling in these higher-level functional networks may lead to cognitive alterations in complex tasks.

A spatial length scale analysis of turbulent temperature and velocity fluctuations within and above an orchard canopy

USGS Publications Warehouse

Wang, Y.S.; Miller, D.R.; Anderson, D.E.; Cionco, R.M.; Lin, J.D.

1992-01-01

Turbulent flow within and above an almond orchard was measured with three-dimensional wind sensors and fine-wire thermocouple sensors arranged in a horizontal array. The data showed organized turbulent structures as indicated by coherent asymmetric ramp patterns in the time series traces across the sensor array. Space-time correlation analysis indicated that velocity and temperature fluctuations were significantly correlated over a transverse distance more than 4m. Integral length scales of velocity and temperature fluctuations were substantially greater in unstable conditions than those in stable conditions. The coherence spectral analysis indicated that Davenport's geometric similarity hypothesis was satisfied in the lower frequency region. From the geometric similarity hypothesis, the spatial extents of large ramp structures were also estimated with the coherence functions.

Factorial structure of the locomotor disability scale in a sample of adults with mobility impairments in Bangladesh.

PubMed

Mahmud, Ilias; Clarke, Lynda; Nahar, Nazmun; Ploubidis, George B

2018-05-02

Disability does not only depend on individuals' health conditions but also the contextual factors in which individuals live. Therefore, disability measurement scales need to be developed or adapted to the context. Bangladesh lacks any locally developed or validated scales to measure disabilities in adults with mobility impairment. We developed a new Locomotor Disability Scale (LDS) in a previous qualitative study. The present study developed a shorter version of the scale and explored its factorial structure. We administered the LDS to 316 adults with mobility impairments, selected from outpatient and community-based settings of a rehabilitation centre in Bangladesh. We did exploratory factor analysis (EFA) to determine a shorter version of the LDS and explore its factorial structure. We retained 19 items from the original LDS following evaluation of response rate, floor/ceiling effects, inter-item correlations, and factor loadings in EFA. The Eigenvalues greater than one rule and the Scree test suggested a two-factor model of measuring locomotor disability (LD) in adults with mobility impairment. These two factors are 'mobility activity limitations' and 'functional activity limitations'. We named the higher order factor as 'locomotor disability'. This two-factor model explained over 68% of the total variance among the LD indicators. The reproduced correlation matrix indicated a good model fit with 14% non-redundant residuals with absolute values > 0.05. However, the Chi-square test indicated poor model fit (p < .001). The Bartlett's test of Sphericity confirmed patterned relationships amongst the LD indicators (p < .001). The Kaiser-Meyer-Olkin Measure (KMO) of sampling adequacy was .94 and the individual diagonal elements in the anti-correlation matrix were > .91. Among the retained 19 items, there was no correlation coefficient > .9 or a large number of correlation coefficients < .3. The communalities were high: between .495 and .882 with a mean of 0.684. As an evidence of convergent validity, we had all loadings above .5, except one. As an evidence of discriminant validity, we had no strong (> .3) cross loadings and the correlation between the two factors was .657. The 'mobility activity limitations' and 'functional activity limitations' sub-scales demonstrated excellent internal consistency (Cronbach's alpha were .954 and .937, respectively). The 19-item LDS was found to be a reliable and valid scale to measure the latent constructs mobility activity limitations and functional activity limitations among adults with mobility impairments in outpatient and community-based settings in Bangladesh.

Topologically associating domains are stable units of replication-timing regulation.

PubMed

Pope, Benjamin D; Ryba, Tyrone; Dileep, Vishnu; Yue, Feng; Wu, Weisheng; Denas, Olgert; Vera, Daniel L; Wang, Yanli; Hansen, R Scott; Canfield, Theresa K; Thurman, Robert E; Cheng, Yong; Gülsoy, Günhan; Dennis, Jonathan H; Snyder, Michael P; Stamatoyannopoulos, John A; Taylor, James; Hardison, Ross C; Kahveci, Tamer; Ren, Bing; Gilbert, David M

2014-11-20

Eukaryotic chromosomes replicate in a temporal order known as the replication-timing program. In mammals, replication timing is cell-type-specific with at least half the genome switching replication timing during development, primarily in units of 400-800 kilobases ('replication domains'), whose positions are preserved in different cell types, conserved between species, and appear to confine long-range effects of chromosome rearrangements. Early and late replication correlate, respectively, with open and closed three-dimensional chromatin compartments identified by high-resolution chromosome conformation capture (Hi-C), and, to a lesser extent, late replication correlates with lamina-associated domains (LADs). Recent Hi-C mapping has unveiled substructure within chromatin compartments called topologically associating domains (TADs) that are largely conserved in their positions between cell types and are similar in size to replication domains. However, TADs can be further sub-stratified into smaller domains, challenging the significance of structures at any particular scale. Moreover, attempts to reconcile TADs and LADs to replication-timing data have not revealed a common, underlying domain structure. Here we localize boundaries of replication domains to the early-replicating border of replication-timing transitions and map their positions in 18 human and 13 mouse cell types. We demonstrate that, collectively, replication domain boundaries share a near one-to-one correlation with TAD boundaries, whereas within a cell type, adjacent TADs that replicate at similar times obscure replication domain boundaries, largely accounting for the previously reported lack of alignment. Moreover, cell-type-specific replication timing of TADs partitions the genome into two large-scale sub-nuclear compartments revealing that replication-timing transitions are indistinguishable from late-replicating regions in chromatin composition and lamina association and accounting for the reduced correlation of replication timing to LADs and heterochromatin. Our results reconcile cell-type-specific sub-nuclear compartmentalization and replication timing with developmentally stable structural domains and offer a unified model for large-scale chromosome structure and function.

Environment of Submillimeter Galaxies

NASA Astrophysics Data System (ADS)

Hou, K.-c.; Chen, L.-w.

2013-10-01

To study the environment of high-redshift star-forming galaxies — submillimeter galaxies (SMGs) — and their role during large-scale structure formation, we have estimated the galaxy number density fluctuations around SMGs, and analyzed their cross correlation functions with Lyman alpha emitters (LAEs), and optical-selected galaxies with photometric redshift in the COSMOS and ECDFS fields. Only a marginal cross-correlation between SMGs and optical-selected galaxies at most redshifts intervals is found in our results, except a relatively strong correlation detected in the cases of AzTEC-detected SMGs with galaxies at z ˜2.6 and 3.6. The density fluctuations around SMGs with redshift estimated show most SMGs located in a high-density region. There is no correlation signal between LAEs and SMGs, and the galaxy density fluctuations indicate a slightly anti-correlation on a scale smaller than 2 Mpc. Furthermore, we also investigate the density fluctuations of passive and starforming galaxies selected by optical and near infrared colors at similar redshift around SMGs. Finally the implication from our results to the interconnection between high-redshift galaxy populations is discussed.

IS THE SMALL-SCALE MAGNETIC FIELD CORRELATED WITH THE DYNAMO CYCLE?

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

Karak, Bidya Binay; Brandenburg, Axel, E-mail: bbkarak@nordita.org

2016-01-01

The small-scale magnetic field is ubiquitous at the solar surface—even at high latitudes. From observations we know that this field is uncorrelated (or perhaps even weakly anticorrelated) with the global sunspot cycle. Our aim is to explore the origin, and particularly the cycle dependence, of such a phenomenon using three-dimensional dynamo simulations. We adopt a simple model of a turbulent dynamo in a shearing box driven by helically forced turbulence. Depending on the dynamo parameters, large-scale (global) and small-scale (local) dynamos can be excited independently in this model. Based on simulations in different parameter regimes, we find that, when onlymore » the large-scale dynamo is operating in the system, the small-scale magnetic field generated through shredding and tangling of the large-scale magnetic field is positively correlated with the global magnetic cycle. However, when both dynamos are operating, the small-scale field is produced from both the small-scale dynamo and the tangling of the large-scale field. In this situation, when the large-scale field is weaker than the equipartition value of the turbulence, the small-scale field is almost uncorrelated with the large-scale magnetic cycle. On the other hand, when the large-scale field is stronger than the equipartition value, we observe an anticorrelation between the small-scale field and the large-scale magnetic cycle. This anticorrelation can be interpreted as a suppression of the small-scale dynamo. Based on our studies we conclude that the observed small-scale magnetic field in the Sun is generated by the combined mechanisms of a small-scale dynamo and tangling of the large-scale field.« less

Prospective evaluation of behavioral scales in the behavioral variant of frontotemporal dementia.

PubMed

Boutoleau-Bretonnière, Claire; Lebouvier, Thibaud; Volteau, Christelle; Jaulin, Philippe; Lacomblez, Lucette; Damier, Philippe; Thomas-Anterion, Catherine; Vercelletto, Martine

2012-01-01

The Neuropsychiatric Inventory (NPI) and the Frontal Behavioral Inventory (FBI) are widely used in patients with the behavioral variant of frontotemporal dementia (bvFTD). Yet, few data are available on the long-term relevance of these scales. Based on a bvFTD population that participated in the Memantine Clinical Trial (NCT00200538), we studied the evolution and correlation between scores obtained on behavioral scales (NPI and FBI), cognitive scales [Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS)] and a burden scale [Zarit Burden Inventory (ZBI)]. The assessments were performed at 1 year in 41 patients and at 2 years in 23 patients who agreed to participate in this open-label study. The 2-year scores obtained on the FBI were significantly higher than the scores at inclusion while those obtained on the NPI did not change. There were significant correlations between the FBI, and the MDRS and MMSE, especially regarding the negative items. The ZBI correlated with behavioral scales at all stages for positive items. This study based on a large population shows that the FBI is a better tool than the NPI for the long-term assessment of bvFTD patients. Moreover, the FBI allows a distinction to be made between behavioral disturbances that involve cognitive functions from those which have an important impact on caregiver burden. Copyright © 2012 S. Karger AG, Basel.

Fourier band-power E/B-mode estimators for cosmic shear

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

Becker, Matthew R.; Rozo, Eduardo

We introduce new Fourier band-power estimators for cosmic shear data analysis and E/B-mode separation. We consider both the case where one performs E/B-mode separation and the case where one does not. The resulting estimators have several nice properties which make them ideal for cosmic shear data analysis. First, they can be written as linear combinations of the binned cosmic shear correlation functions. Secondly, they account for the survey window function in real-space. Thirdly, they are unbiased by shape noise since they do not use correlation function data at zero separation. Fourthly, the band-power window functions in Fourier space are compactmore » and largely non-oscillatory. Fifthly, they can be used to construct band-power estimators with very efficient data compression properties. In particular, we find that all of the information on the parameters Ωm, σ8 and ns in the shear correlation functions in the range of ~10–400 arcmin for single tomographic bin can be compressed into only three band-power estimates. Finally, we can achieve these rates of data compression while excluding small-scale information where the modelling of the shear correlation functions and power spectra is very difficult. Given these desirable properties, these estimators will be very useful for cosmic shear data analysis.« less

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

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

Significance of Input Correlations in Striatal Function

PubMed Central

Yim, Man Yi; Aertsen, Ad; Kumar, Arvind

2011-01-01

The striatum is the main input station of the basal ganglia and is strongly associated with motor and cognitive functions. Anatomical evidence suggests that individual striatal neurons are unlikely to share their inputs from the cortex. Using a biologically realistic large-scale network model of striatum and cortico-striatal projections, we provide a functional interpretation of the special anatomical structure of these projections. Specifically, we show that weak pairwise correlation within the pool of inputs to individual striatal neurons enhances the saliency of signal representation in the striatum. By contrast, correlations among the input pools of different striatal neurons render the signal representation less distinct from background activity. We suggest that for the network architecture of the striatum, there is a preferred cortico-striatal input configuration for optimal signal representation. It is further enhanced by the low-rate asynchronous background activity in striatum, supported by the balance between feedforward and feedback inhibitions in the striatal network. Thus, an appropriate combination of rates and correlations in the striatal input sets the stage for action selection presumably implemented in the basal ganglia. PMID:22125480

Double inflation - A possible resolution of the large-scale structure problem

NASA Technical Reports Server (NTRS)

Turner, Michael S.; Villumsen, Jens V.; Vittorio, Nicola; Silk, Joseph; Juszkiewicz, Roman

1987-01-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Omega = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of about 100 Mpc, while the small-scale structure over less than about 10 Mpc resembles that in a low-density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations.

Motor and somatosensory conversion disorder: a functional unawareness syndrome?

PubMed

Perez, David L; Barsky, Arthur J; Daffner, Kirk; Silbersweig, David A

2012-01-01

Although conversion disorder is closely connected to the origins of neurology and psychiatry, it remains poorly understood. In this article, the authors discuss neural and clinical parallels between lesional unawareness disorders and unilateral motor and somatosensory conversion disorder, emphasizing functional neuroimaging/disease correlates. Authors suggest that a functional-unawareness neurobiological framework, mediated by right hemisphere-lateralized, large-scale brain network dysfunction, may play a significant role in the neurobiology of conversion disorder. The perigenual anterior cingulate and the posterior parietal cortices are detailed as important in disease pathophysiology. Further investigations will refine the functional-unawareness concept, clarify the role of affective circuits, and delineate the process through which functional neurologic symptoms emerge.

Can cosmic shear shed light on low cosmic microwave background multipoles?

PubMed

Kesden, Michael; Kamionkowski, Marc; Cooray, Asantha

2003-11-28

The lowest multipole moments of the cosmic microwave background (CMB) are smaller than expected for a scale-invariant power spectrum. One possible explanation is a cutoff in the primordial power spectrum below a comoving scale of k(c) approximately equal to 5.0 x 10(-4) Mpc(-1). Such a cutoff would increase significantly the cross correlation between the large-angle CMB and cosmic-shear patterns. The cross correlation may be detectable at >2sigma which, combined with the low CMB moments, may tilt the balance between a 2sigma result and a firm detection of a large-scale power-spectrum cutoff. The cutoff also increases the large-angle cross correlation between the CMB and the low-redshift tracers of the mass distribution.

Predicting weak lensing statistics from halo mass reconstructions - Final Paper

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

Everett, Spencer

2015-08-20

As dark matter does not absorb or emit light, its distribution in the universe must be inferred through indirect effects such as the gravitational lensing of distant galaxies. While most sources are only weakly lensed, the systematic alignment of background galaxies around a foreground lens can constrain the mass of the lens which is largely in the form of dark matter. In this paper, I have implemented a framework to reconstruct all of the mass along lines of sight using a best-case dark matter halo model in which the halo mass is known. This framework is then used to makemore » predictions of the weak lensing of 3,240 generated source galaxies through a 324 arcmin² field of the Millennium Simulation. The lensed source ellipticities are characterized by the ellipticity-ellipticity and galaxy-mass correlation functions and compared to the same statistic for the intrinsic and ray-traced ellipticities. In the ellipticity-ellipticity correlation function, I and that the framework systematically under predicts the shear power by an average factor of 2.2 and fails to capture correlation from dark matter structure at scales larger than 1 arcminute. The model predicted galaxy-mass correlation function is in agreement with the ray-traced statistic from scales 0.2 to 0.7 arcminutes, but systematically underpredicts shear power at scales larger than 0.7 arcminutes by an average factor of 1.2. Optimization of the framework code has reduced the mean CPU time per lensing prediction by 70% to 24 ± 5 ms. Physical and computational shortcomings of the framework are discussed, as well as potential improvements for upcoming work.« less

Complex Networks, Fractals and Topology Trends for Oxidative Activity of DNA in Cells for Populations of Fluorescing Neutrophils in Medical Diagnostics

NASA Astrophysics Data System (ADS)

Galich, N. E.

A novel nonlinear statistical method of immunofluorescence data analysis is presented. The data of DNA fluorescence due to oxidative activity in neutrophils nuclei of peripheral blood is analyzed. Histograms of photon counts statistics are generated using flow cytometry method. The histograms represent the distributions of fluorescence flash frequency as functions of intensity for large populations∼104-105 of fluorescing cells. We have shown that these experiments present 3D-correlations of oxidative activity of DNA for full chromosomes set in cells with spatial resolution of measurements is about few nanometers in the flow direction the jet of blood. Detailed analysis showed that large-scale correlations in oxidative activity of DNA in cells are described as networks of small- worlds (complex systems with logarithmic scaling) with self own small-world networks for given donor at given time for all states of health. We observed changes in fractal networks of oxidative activity of DNA in neutrophils in vivo and during medical treatments for classification and diagnostics of pathologies for wide spectra of diseases. Our approach based on analysis of changes topology of networks (fractal dimension) at variation the scales of networks. We produce the general estimation of health status of a given donor in a form of yes/no of answers (healthy/sick) in the dependence on the sign of plus/minus in the trends change of fractal dimensions due to decreasing the scale of nets. We had noted the increasing biodiversity of neutrophils and stochastic (Brownian) character of intercellular correlations of different neutrophils in the blood of healthy donor. In the blood of sick people we observed the deterministic cell-cell correlations of neutrophils and decreasing their biodiversity.

On the scaling features of high-latitude geomagnetic field fluctuations during a large geomagnetic storm

NASA Astrophysics Data System (ADS)

De Michelis, Paola; Federica Marcucci, Maria; Consolini, Giuseppe

2015-04-01

Recently we have investigated the spatial distribution of the scaling features of short-time scale magnetic field fluctuations using measurements from several ground-based geomagnetic observatories distributed in the northern hemisphere. We have found that the scaling features of fluctuations of the horizontal magnetic field component at time scales below 100 minutes are correlated with the geomagnetic activity level and with changes in the currents flowing in the ionosphere. Here, we present a detailed analysis of the dynamical changes of the magnetic field scaling features as a function of the geomagnetic activity level during the well-known large geomagnetic storm occurred on July, 15, 2000 (the Bastille event). The observed dynamical changes are discussed in relationship with the changes of the overall ionospheric polar convection and potential structure as reconstructed using SuperDARN data. This work is supported by the Italian National Program for Antarctic Research (PNRA) - Research Project 2013/AC3.08 and by the European Community's Seventh Framework Programme ([FP7/2007-2013]) under Grant no. 313038/STORM and

The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2011-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

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

PubMed Central

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

2004-01-01

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

Scaled effective on-site Coulomb interaction in the DFT+U method for correlated materials

NASA Astrophysics Data System (ADS)

Nawa, Kenji; Akiyama, Toru; Ito, Tomonori; Nakamura, Kohji; Oguchi, Tamio; Weinert, M.

2018-01-01

The first-principles calculation of correlated materials within density functional theory remains challenging, but the inclusion of a Hubbard-type effective on-site Coulomb term (Ueff) often provides a computationally tractable and physically reasonable approach. However, the reported values of Ueff vary widely, even for the same ionic state and the same material. Since the final physical results can depend critically on the choice of parameter and the computational details, there is a need to have a consistent procedure to choose an appropriate one. We revisit this issue from constraint density functional theory, using the full-potential linearized augmented plane wave method. The calculated Ueff parameters for the prototypical transition-metal monoxides—MnO, FeO, CoO, and NiO—are found to depend significantly on the muffin-tin radius RMT, with variations of more than 2-3 eV as RMT changes from 2.0 to 2.7 aB. Despite this large variation in Ueff, the calculated valence bands differ only slightly. Moreover, we find an approximately linear relationship between Ueff(RMT) and the number of occupied localized electrons within the sphere, and give a simple scaling argument for Ueff; these results provide a rationalization for the large variation in reported values. Although our results imply that Ueff values are not directly transferable among different calculation methods (or even the same one with different input parameters such as RMT), use of this scaling relationship should help simplify the choice of Ueff.

A Functional Model for Management of Large Scale Assessments.

ERIC Educational Resources Information Center

Banta, Trudy W.; And Others

This functional model for managing large-scale program evaluations was developed and validated in connection with the assessment of Tennessee's Nutrition Education and Training Program. Management of such a large-scale assessment requires the development of a structure for the organization; distribution and recovery of large quantities of…

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

Okumura, Teppei; Seljak, Uroš; McDonald, Patrick

Measurement of redshift-space distortions (RSD) offers an attractive method to directly probe the cosmic growth history of density perturbations. A distribution function approach where RSD can be written as a sum over density weighted velocity moment correlators has recently been developed. In this paper we use results of N-body simulations to investigate the individual contributions and convergence of this expansion for dark matter. If the series is expanded as a function of powers of μ, cosine of the angle between the Fourier mode and line of sight, then there are a finite number of terms contributing at each order. Wemore » present these terms and investigate their contribution to the total as a function of wavevector k. For μ{sup 2} the correlation between density and momentum dominates on large scales. Higher order corrections, which act as a Finger-of-God (FoG) term, contribute 1% at k ∼ 0.015hMpc{sup −1}, 10% at k ∼ 0.05hMpc{sup −1} at z = 0, while for k > 0.15hMpc{sup −1} they dominate and make the total negative. These higher order terms are dominated by density-energy density correlations which contributes negatively to the power, while the contribution from vorticity part of momentum density auto-correlation adds to the total power, but is an order of magnitude lower. For μ{sup 4} term the dominant term on large scales is the scalar part of momentum density auto-correlation, while higher order terms dominate for k > 0.15hMpc{sup −1}. For μ{sup 6} and μ{sup 8} we find it has very little power for k < 0.15hMpc{sup −1}, shooting up by 2–3 orders of magnitude between k < 0.15hMpc{sup −1} and k < 0.4hMpc{sup −1}. We also compare the expansion to the full 2-d P{sup ss}(k,μ), as well as to the monopole, quadrupole, and hexadecapole integrals of P{sup ss}(k,μ). For these statistics an infinite number of terms contribute and we find that the expansion achieves percent level accuracy for kμ < 0.15hMpc{sup −1} at 6-th order, but breaks down on smaller scales because the series is no longer perturbative. We explore resummation of the terms into FoG kernels, which extend the convergence up to a factor of 2 in scale. We find that the FoG kernels are approximately Lorentzian with velocity dispersions around 600 km/s at z = 0.« less

Anisotropic extinction distortion of the galaxy correlation function

NASA Astrophysics Data System (ADS)

Fang, Wenjuan; Hui, Lam; Ménard, Brice; May, Morgan; Scranton, Ryan

2011-09-01

Similar to the magnification of the galaxies’ fluxes by gravitational lensing, the extinction of the fluxes by comic dust, whose existence is recently detected by [B. Ménard, R. Scranton, M. Fukugita, and G. Richards, Mon. Not. R. Astron. Soc.MNRAA40035-8711 405, 1025 (2010)DOI: 10.1111/j.1365-2966.2010.16486.x.], also modifies the distribution of a flux-selected galaxy sample. We study the anisotropic distortion by dust extinction to the 3D galaxy correlation function, including magnification bias and redshift distortion at the same time. We find the extinction distortion is most significant along the line of sight and at large separations, similar to that by magnification bias. The correction from dust extinction is negative except at sufficiently large transverse separations, which is almost always opposite to that from magnification bias (we consider a number count slope s>0.4). Hence, the distortions from these two effects tend to reduce each other. At low z (≲1), the distortion by extinction is stronger than that by magnification bias, but at high z, the reverse holds. We also study how dust extinction affects probes in real space of the baryon acoustic oscillations (BAO) and the linear redshift distortion parameter β. We find its effect on BAO is negligible. However, it introduces a positive scale-dependent correction to β that can be as large as a few percent. At the same time, we also find a negative scale-dependent correction from magnification bias, which is up to percent level at low z, but to ˜40% at high z. These corrections are non-negligible for precision cosmology, and should be considered when testing General Relativity through the scale-dependence of β.

The Large-scale Structure of the Universe: Probes of Cosmology and Structure Formation

NASA Astrophysics Data System (ADS)

Noh, Yookyung

The usefulness of large-scale structure as a probe of cosmology and structure formation is increasing as large deep surveys in multi-wavelength bands are becoming possible. The observational analysis of large-scale structure guided by large volume numerical simulations are beginning to offer us complementary information and crosschecks of cosmological parameters estimated from the anisotropies in Cosmic Microwave Background (CMB) radiation. Understanding structure formation and evolution and even galaxy formation history is also being aided by observations of different redshift snapshots of the Universe, using various tracers of large-scale structure. This dissertation work covers aspects of large-scale structure from the baryon acoustic oscillation scale, to that of large scale filaments and galaxy clusters. First, I discuss a large- scale structure use for high precision cosmology. I investigate the reconstruction of Baryon Acoustic Oscillation (BAO) peak within the context of Lagrangian perturbation theory, testing its validity in a large suite of cosmological volume N-body simulations. Then I consider galaxy clusters and the large scale filaments surrounding them in a high resolution N-body simulation. I investigate the geometrical properties of galaxy cluster neighborhoods, focusing on the filaments connected to clusters. Using mock observations of galaxy clusters, I explore the correlations of scatter in galaxy cluster mass estimates from multi-wavelength observations and different measurement techniques. I also examine the sources of the correlated scatter by considering the intrinsic and environmental properties of clusters.

Constraining the baryon-dark matter relative velocity with the large-scale 3-point correlation function of the SDSS BOSS DR12 CMASS galaxies

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

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv <0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of Baryon Acoustic Oscillation (BAO) method measurements of the cosmic distance scale using the 2-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3% rms in the distance scale inferred from the BAO feature in the BOSS 2-point clustering, well belowmore » the 1% statistical error of this measurement. In conclusion, this constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as DESI to self-protect against the relative velocity as a possible systematic.« less

Constraining the baryon-dark matter relative velocity with the large-scale 3-point correlation function of the SDSS BOSS DR12 CMASS galaxies

DOE PAGES

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.; ...

2017-10-24

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv <0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of Baryon Acoustic Oscillation (BAO) method measurements of the cosmic distance scale using the 2-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3% rms in the distance scale inferred from the BAO feature in the BOSS 2-point clustering, well belowmore » the 1% statistical error of this measurement. In conclusion, this constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as DESI to self-protect against the relative velocity as a possible systematic.« less

Constraining the baryon-dark matter relative velocity with the large-scale three-point correlation function of the SDSS BOSS DR12 CMASS galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.; Blazek, Jonathan A.; Brownstein, Joel R.; Chuang, Chia-Hsun; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; McEwen, Joseph E.; Percival, Will J.; Ross, Ashley J.; Rossi, Graziano; Seo, Hee-Jong; Slosar, Anže; Vargas-Magaña, Mariana

2018-02-01

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv < 0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of baryon acoustic oscillation (BAO) method measurements of the cosmic distance scale using the two-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3 per cent rms in the distance scale inferred from the BAO feature in the BOSS two-point clustering, well below the 1 per cent statistical error of this measurement. This constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as the Dark Energy Spectroscopic Instrument (DESI) to self-protect against the relative velocity as a possible systematic.

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

PubMed Central

Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.

2018-01-01

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352

Large-scale transport across narrow gaps in rod bundles

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

Guellouz, M.S.; Tavoularis, S.

1995-09-01

Flow visualization and how-wire anemometry were used to investigate the velocity field in a rectangular channel containing a single cylindrical rod, which could be traversed on the centreplane to form gaps of different widths with the plane wall. The presence of large-scale, quasi-periodic structures in the vicinity of the gap has been demonstrated through flow visualization, spectral analysis and space-time correlation measurements. These structures are seen to exist even for relatively large gaps, at least up to W/D=1.350 (W is the sum of the rod diameter, D, and the gap width). The above measurements appear to compatible with the fieldmore » of a street of three-dimensional, counter-rotating vortices, whose detailed structure, however, remains to be determined. The convection speed and the streamwise spacing of these vortices have been determined as functions of the gap size.« less

Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia

NASA Astrophysics Data System (ADS)

Stramaglia, S.; Pellicoro, M.; Angelini, L.; Amico, E.; Aerts, H.; Cortés, J. M.; Laureys, S.; Marinazzo, D.

2017-04-01

Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.

Holographic signatures of cosmological singularities.

PubMed

Engelhardt, Netta; Hertog, Thomas; Horowitz, Gary T

2014-09-19

To gain insight into the quantum nature of cosmological singularities, we study anisotropic Kasner solutions in gauge-gravity duality. The dual description of the bulk evolution towards the singularity involves N=4 super Yang-Mills theory on the expanding branch of deformed de Sitter space and is well defined. We compute two-point correlators of Yang-Mills operators of large dimensions using spacelike geodesics anchored on the boundary. The correlators show a strong signature of the singularity around horizon scales and decay at large boundary separation at different rates in different directions. More generally, the boundary evolution exhibits a process of particle creation similar to that in inflation. This leads us to conjecture that information on the quantum nature of cosmological singularities is encoded in long-wavelength features of the boundary wave function.

Aeration costs in stirred-tank and bubble column bioreactors

DOE PAGES

Humbird, D.; Davis, R.; McMillan, J. D.

2017-08-10

To overcome knowledge gaps in the economics of large-scale aeration for production of commodity products, Aspen Plus is used to simulate steady-state oxygen delivery in both stirred-tank and bubble column bioreactors, using published engineering correlations for oxygen mass transfer as a function of aeration rate and power input, coupled with new equipment cost estimates developed in Aspen Capital Cost Estimator and validated against vendor quotations. Here, these simulations describe the cost efficiency of oxygen delivery as a function of oxygen uptake rate and vessel size, and show that capital and operating costs for oxygen delivery drop considerably moving from standard-sizemore » (200 m 3) to world-class size (500 m 3) reactors, but only marginally in further scaling up to hypothetically large (1000 m 3) reactors. Finally, this analysis suggests bubble-column reactor systems can reduce overall costs for oxygen delivery by 10-20% relative to stirred tanks at low to moderate oxygen transfer rates up to 150 mmol/L-h.« less

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance.

PubMed

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-03-14

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance

PubMed Central

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-01-01

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization. DOI: http://dx.doi.org/10.7554/eLife.22001.001 PMID:28288700

Aeration costs in stirred-tank and bubble column bioreactors

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

Humbird, D.; Davis, R.; McMillan, J. D.

To overcome knowledge gaps in the economics of large-scale aeration for production of commodity products, Aspen Plus is used to simulate steady-state oxygen delivery in both stirred-tank and bubble column bioreactors, using published engineering correlations for oxygen mass transfer as a function of aeration rate and power input, coupled with new equipment cost estimates developed in Aspen Capital Cost Estimator and validated against vendor quotations. Here, these simulations describe the cost efficiency of oxygen delivery as a function of oxygen uptake rate and vessel size, and show that capital and operating costs for oxygen delivery drop considerably moving from standard-sizemore » (200 m 3) to world-class size (500 m 3) reactors, but only marginally in further scaling up to hypothetically large (1000 m 3) reactors. Finally, this analysis suggests bubble-column reactor systems can reduce overall costs for oxygen delivery by 10-20% relative to stirred tanks at low to moderate oxygen transfer rates up to 150 mmol/L-h.« less

Spectral fingerprints of large-scale cortical dynamics during ambiguous motion perception.

PubMed

Helfrich, Randolph F; Knepper, Hannah; Nolte, Guido; Sengelmann, Malte; König, Peter; Schneider, Till R; Engel, Andreas K

2016-11-01

Ambiguous stimuli have been widely used to study the neuronal correlates of consciousness. Recently, it has been suggested that conscious perception might arise from the dynamic interplay of functionally specialized but widely distributed cortical areas. While previous research mainly focused on phase coupling as a correlate of cortical communication, more recent findings indicated that additional coupling modes might coexist and possibly subserve distinct cortical functions. Here, we studied two coupling modes, namely phase and envelope coupling, which might differ in their origins, putative functions and dynamics. Therefore, we recorded 128-channel EEG while participants performed a bistable motion task and utilized state-of-the-art source-space connectivity analysis techniques to study the functional relevance of different coupling modes for cortical communication. Our results indicate that gamma-band phase coupling in extrastriate visual cortex might mediate the integration of visual tokens into a moving stimulus during ambiguous visual stimulation. Furthermore, our results suggest that long-range fronto-occipital gamma-band envelope coupling sustains the horizontal percept during ambiguous motion perception. Additionally, our results support the idea that local parieto-occipital alpha-band phase coupling controls the inter-hemispheric information transfer. These findings provide correlative evidence for the notion that synchronized oscillatory brain activity reflects the processing of sensory input as well as the information integration across several spatiotemporal scales. The results indicate that distinct coupling modes are involved in different cortical computations and that the rich spatiotemporal correlation structure of the brain might constitute the functional architecture for cortical processing and specific multi-site communication. Hum Brain Mapp 37:4099-4111, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Global correlation of topographic heights and gravity anomalies

NASA Technical Reports Server (NTRS)

Roufosse, M. C.

1977-01-01

The short wavelength features were obtained by subtracting a calculated 24th-degree-and-order field from observed data written in 1 deg x 1 deg squares. The correlation between the two residual fields was examined by a program of linear regression. When run on a worldwide scale over oceans and continents separately, the program did not exhibit any correlation; this can be explained by the fact that the worldwide autocorrelation function for residual gravity anomalies falls off much faster as a function of distance than does that for residual topographic heights. The situation was different when the program was used in restricted areas, of the order of 5 deg x 5 deg square. For 30% of the world,fair-to-good correlations were observed, mostly over continents. The slopes of the regression lines are proportional to apparent densities, which offer a large spectrum of values that are being interpreted in terms of features in the upper mantle consistent with available heat-flow, gravity, and seismic data.

The Fine-Scale Functional Correlation of Striate Cortex in Sighted and Blind People

PubMed Central

Butt, Omar H.; Benson, Noah C.; Datta, Ritobrato

2013-01-01

To what extent are spontaneous neural signals within striate cortex organized by vision? We examined the fine-scale pattern of striate cortex correlations within and between hemispheres in rest-state BOLD fMRI data from sighted and blind people. In the sighted, we find that corticocortico correlation is well modeled as a Gaussian point-spread function across millimeters of striate cortical surface, rather than degrees of visual angle. Blindness produces a subtle change in the pattern of fine-scale striate correlations between hemispheres. Across participants blind before the age of 18, the degree of pattern alteration covaries with the strength of long-range correlation between left striate cortex and Broca's area. This suggests that early blindness exchanges local, vision-driven pattern synchrony of the striate cortices for long-range functional correlations potentially related to cross-modal representation. PMID:24107953

Scaling and memory in volatility return intervals in financial markets

NASA Astrophysics Data System (ADS)

Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

2005-06-01

For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval [Formula] as [Formula]. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ˜ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. Author contributions: S.H. and H.E.S. designed research; K.Y., L.M., S.H., and H.E.S. performed research; A.B. contributed new reagents/analytic tools; A.B. analyzed data; and S.H. wrote the paper.Abbreviations: pdf, probability density function; S&P 500, Standard and Poor's 500 Index; USD, U.S. dollar; JPY, Japanese yen; SEK, Swedish krona.

Physical activity correlates with neurological impairment and disability in multiple sclerosis.

PubMed

Motl, Robert W; Snook, Erin M; Wynn, Daniel R; Vollmer, Timothy

2008-06-01

This study examined the correlation of physical activity with neurological impairment and disability in persons with multiple sclerosis (MS). Eighty individuals with MS wore an accelerometer for 7 days and completed the Symptom Inventory (SI), Performance Scales (PS), and Expanded Disability Status Scale. There were large negative correlations between the accelerometer and SI (r = -0.56; rho = -0.58) and Expanded Disability Status Scale (r = -0.60; rho = -0.69) and a moderate negative correlation between the accelerometer and PS (r = -0.39; rho = -0.48) indicating that physical activity was associated with reduced neurological impairment and disability. Such findings provide a preliminary basis for using an accelerometer and the SI and PS as outcome measures in large-scale prospective and experimental examinations of the effect of physical activity behavior on disability and dependence in MS.

Rank Determination of Mental Functions by 1D Wavelets and Partial Correlation.

PubMed

Karaca, Y; Aslan, Z; Cattani, C; Galletta, D; Zhang, Y

2017-01-01

The main aim of this paper is to classify mental functions by the Wechsler Adult Intelligence Scale-Revised tests with a mixed method based on wavelets and partial correlation. The Wechsler Adult Intelligence Scale-Revised is a widely used test designed and applied for the classification of the adults cognitive skills in a comprehensive manner. In this paper, many different intellectual profiles have been taken into consideration to measure the relationship between the mental functioning and psychological disorder. We propose a method based on wavelets and correlation analysis for classifying mental functioning, by the analysis of some selected parameters measured by the Wechsler Adult Intelligence Scale-Revised tests. In particular, 1-D Continuous Wavelet Analysis, 1-D Wavelet Coefficient Method and Partial Correlation Method have been analyzed on some Wechsler Adult Intelligence Scale-Revised parameters such as School Education, Gender, Age, Performance Information Verbal and Full Scale Intelligence Quotient. In particular, we will show that gender variable has a negative but a significant role on age and Performance Information Verbal factors. The age parameters also has a significant relation in its role on Performance Information Verbal and Full Scale Intelligence Quotient change.

Hierarchical drivers of reef-fish metacommunity structure.

PubMed

MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

2009-01-01

Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

The ISW effect and the lack of large-angle CMB temperature correlations

NASA Astrophysics Data System (ADS)

Copi, Craig J.; O'Dwyer, Márcio; Starkman, Glenn D.

2016-12-01

It is by now well established that the magnitude of the two-point angular-correlation function of the cosmic microwave background temperature anisotropies is anomalously low for angular separations greater than about 60°. Physics explanations of this anomaly typically focus on the properties of the Universe at the surface of last scattering, relying on the fact that large-angle temperature fluctuations are dominated by the Sachs-Wolfe effect (SW). However, these fluctuations also receive important contributions from the integrated Sachs-Wolfe effect (ISW) at both early (eISW) and late (ℓISW) times. Here, we study the correlations in those large-angle temperature fluctuations and their relative contributions to S1/2- the standard measure of the correlations on large angular scales. We find that in the best-fitting lambda cold dark matter (ΛCDM) cosmology, while the autocorrelation of the early contributions (SW plus eISW) dominates S1/2, there are also significant contributions originating from cross-terms between the early and late contributions. In particular, realizations of ΛCDM with low S1/2 are typically produced from a combination of somewhat low pure-early correlations and accidental cancellations among early-late correlations. We also find that if the pure ℓISW autocorrelations were the only contribution to S1/2 in ΛCDM, then the p-value of the observed cut-sky S1/2 would be unremarkable. This suggests that the physical mechanisms operating only at or near the last scattering surface could explain the observed lack of large-angle correlations, though this is not the typical resolution within ΛCDM.

Instantaneous phase estimation to measure weak velocity variations: application to noise correlation on seismic data at the exploration scale

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubucq, D.

2010-12-01

Passive imaging from noise cross-correlation is a consolidated analysis applied at continental and regional scale whereas its use at local scale for seismic exploration purposes is still uncertain. The development of passive imaging by cross-correlation analysis is based on the extraction of the Green’s function from seismic noise data. In a completely random field in time and space, the cross-correlation permits to retrieve the complete Green’s function whatever the complexity of the medium. At the exploration scale and at frequency above 2 Hz, the noise sources are not ideally distributed around the stations which strongly affect the extraction of the direct arrivals from the noise cross-correlation process. In order to overcome this problem, the coda waves extracted from noise correlation could be useful. Coda waves describe long and scattered paths sampling the medium in different ways such that they become sensitive to weak velocity variations without being dependent on the noise source distribution. Indeed, scatters in the medium behave as a set of secondary noise sources which randomize the spatial distribution of noise sources contributing to the coda waves in the correlation process. We developed a new technique to measure weak velocity changes based on the computation of the local phase variations (instantaneous phase variation or IPV) of the cross-correlated signals. This newly-developed technique takes advantage from the doublet and stretching techniques classically used to monitor weak velocity variation from coda waves. We apply IPV to data acquired in Northern America (Canada) on a 1-km side square seismic network laid out by 397 stations. Data used to study temporal variations are cross-correlated signals computed on 10-minutes ambient noise in the frequency band 2-5 Hz. As the data set was acquired over five days, about 660 files are processed to perform a complete temporal analysis for each stations pair. The IPV permits to estimate the phase shift all over the signal length without any assumption on the medium velocity. The instantaneous phase is computed using the Hilbert transform of the signal. For each stations pair, we measure the phase difference between successive correlation functions calculated for 10 minutes of ambient noise. We then fit the instantaneous phase shift using a first-order polynomial function. The measure of the velocity variation corresponds to the slope of this fit. Compared to other techniques, the advantage of IPV is a very fast procedure which efficiently provides the measure of velocity variation on large data sets. Both experimental results and numerical tests on synthetic signals will be presented to assess the reliability of the IPV technique, with comparison to the doublet and stretching methods.

Physical function assessment in a community-dwelling population of U.S. Chinese older adults.

PubMed

Dong, XinQi; Chang, E-Shien; Simon, Melissa A

2014-11-01

This report describes the levels of physical function in U.S. Chinese older adults utilizing self-reported and performance-based measures, and examines the association between sociodemographic characteristics and physical function. The Population Study of Chinese Elderly in Chicago enrolled an epidemiological cohort of 3,159 community-dwelling Chinese older adults aged 60 and older. We collected self-reported physical function using Katz activities of daily living and Lawton instrumental activities of daily living items, the Index of Mobility scale, and the Index of Basic Physical Activities scale. Participants were also asked to perform tasks in chair stand, tandem stand, and timed walk. We computed Pearson and Spearman correlation coefficients to examine the correlation between sociodemographic and physical function variables. A total of 7.8% of study participants experienced activities of daily living impairment, and 50.2% experienced instrumental activities of daily living impairment. With respect to physical performance testing, 11.4% of the participants were not able to complete chair stand for five times, 8.5% of the participants were unable to do chair stands at all. Older age, female gender, lower education level, being unmarried, living with fewer people in the same household, having fewer children, living fewer years in the United States, living fewer years in the community, and worsening health status were significantly correlated with lower levels of physical function. Utilizing self-reported and performance-based measures of physical function in a large population-based study of U.S. Chinese older adults, our findings expand current understanding of minority older adults' functional status. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Ten-Year Review of Rating Scales, VII: Scales Assessing Functional Impairment

ERIC Educational Resources Information Center

Winters, Nancy C.; Collett, Brent R.; Myers, Kathleen M.

2005-01-01

Objective: This is the seventh in a series of 10-year reviews of rating scales. Here the authors present scales measuring functional impairment, a sequela of mental illness. The measurement of functional impairment has assumed importance with the recognition that symptom resolution does not necessarily correlate with functional improvement.…

Intelligence or years of education: which is better correlated with memory function in normal elderly Japanese subjects?

PubMed

Murayama, Norio; Iseki, Eizo; Tagaya, Hirokuni; Ota, Kazumi; Kasanuki, Koji; Fujishiro, Hiroshige; Arai, Heii; Sato, Kiyoshi

2013-03-01

We compared differences in intelligence and memory function between normal elderly Japanese subjects with more years of education and those with fewer years of education. We also investigated clinical and neuropsychological factors that are strongly correlated with memory function. There were 118 normal elderly subjects who underwent the Mini-Mental State Examination, Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III), and Wechsler Memory Scale Revised. Subjects with at least 13 years of education were categorized as the H group, and those with 12 years of education or less were categorized as the L group. Age and Mini-Mental State Examination scores were not significantly different between the two groups. On the WAIS-III, there were significant differences between the two groups in Verbal IQ and Full Scale IQ. On the Wechsler Memory Scale Revised, there were significant differences between the two groups in Visual Memory, General Memory, and Delayed Recall. Correlation coefficients between memory function and the other factors demonstrated significant but weak correlations between years of education and General Memory (R = 0.22) and between years of education and Delayed Recall (R = 0.20). Strong correlations were found between Verbal IQ and Verbal Memory (R = 0.45), between Verbal IQ and General Memory (R = 0.49), between Full Scale IQ and General Memory (R = 0.50) and between Full Scale IQ and Delayed Recall (R = 0.48). In normal elderly Japanese subjects, years of education weakly correlated with memory function while Verbal IQ, Full Scale IQ and Verbal Comprehension on WAIS-III had stronger correlations with memory function. Verbal IQ and Verbal Comprehension on WAIS-III were found to be insusceptible to the cognitive decline characteristic of Alzheimer's disease or amnestic mild cognitive impairment. Therefore, verbal intelligence, as measured by Verbal IQ and Verbal Comprehension, may be the most useful factor for inferring premorbid memory function in Alzheimer's disease or amnestic mild cognitive impairment patients. © 2013 The Authors. Psychogeriatrics © 2013 Japanese Psychogeriatric Society.

Prospective external convergence evaluation of two different quality-of-life instruments in lung resection patients.

PubMed

Pompili, Cecilia; Brunelli, Alessandro; Xiumé, Francesco; Refai, Majed; Salati, Michele; Socci, Laura; Di Nunzio, Luca; Sabbatini, Armando

2011-07-01

The interpretation of studies on quality of life (QoL) after lung surgery is often difficult owing to the use of multiple instruments with inconsistent scales and metrics. Although a more standardized approach would be desirable, the most appropriate instrument to be used in this setting is still largely undefined. The aim of the study was to assess the respective ability of two validated QoL instruments (European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30/L13 and Short Form (36) Health Survey (SF-36)) to detect perioperative changes in QoL of patients submitted to pulmonary resection for non-small-cell lung cancer (NSCLC). A prospective study on 33 consecutive patients (May 2009-December 2009) was submitted to pulmonary resection. All patients completed both EORTC QLQ-C30 with lung module 13 and SF-36 pre- and postoperatively (3 months). Preoperative changes of all SF-36 and EORTC scales were assessed by using the Cohen's effect-size method. External convergence between different instruments (SF-36 vs EORTC) was assessed by measuring the correlation of scales evaluating the same concepts (physical, psychosocial, and emotional). The correlation coefficients between standardized perioperative changes (effect sizes) of objective functional parameters (forced expiratory volume in 1s (FEV1) and diffusion lung capacity for carbon monoxide (DLCO)) and SF-36 or EORTC scales were also investigated. A poor correlation (r < 0.5) was detected between most of the scales of the two instruments measuring the same QoL concepts, indicating that they may be complementary in investigating different aspects of QoL. Only the SF-36 and EORTC social functioning scales and the SF-36 mental health and EORTC emotional functioning scales had a correlation coefficient >0.5. In general, EORTC was more sensitive in detecting physical or emotional declines but was more conservative in detecting improvements. Both SF-36 and EORTC showed poor correlations (r < 0.5) between perioperative changes in QoL and FEV1 or DLCO, confirming that objective parameters cannot be surrogates to the subjective perception of QoL. In particular, there was a poor correlation between perceived changes in dyspnea and objective changes in FEV1 or DLCO. EORTC behaved similarly to SF-36 in assessing perioperative changes in generic QoL scales, but, with the use of its lung module, provided a more detailed evaluation of specific symptoms. For this reason, EORTC should be regarded as the instrument of choice for measuring QoL in the thoracic surgery setting. Copyright © 2010 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Leaf optical properties shed light on foliar trait variability at individual to global scales

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Serbin, S.; Dietze, M.

2016-12-01

Recent syntheses of large trait databases have contributed immensely to our understanding of drivers of plant function at the global scale. However, the global trade-offs revealed by such syntheses, such as the trade-off between leaf productivity and resilience (i.e. "leaf economics spectrum"), are often absent at smaller scales and fail to correlate with actual functional limitations. An improved understanding of how traits vary within communities, species, and individuals is critical to accurate representations of vegetation ecophysiology and ecological dynamics in ecosystem models. Spectral data from both field observations and remote sensing platforms present a potentially rich and widely available source of information on plant traits. In particular, the inversion of physically-based radiative transfer models (RTMs) is an effective and general method for estimating plant traits from spectral measurements. Here, we apply Bayesian inversion of the PROSPECT leaf RTM to a large database of field spectra and plant traits spanning tropical, temperate, and boreal forests, agricultural plots, arid shrublands, and tundra to identify dominant sources of variability and characterize trade-offs in plant functional traits. By leveraging such a large and diverse dataset, we re-calibrate the empirical absorption coefficients underlying the PROSPECT model and expand its scope to include additional leaf biochemical components, namely leaf nitrogen content. Our work provides a key methodological contribution as a physically-based retrieval of leaf nitrogen from remote sensing observations, and provides substantial insights about trait trade-offs related to plant acclimation, adaptation, and community assembly.

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

PubMed

Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

2015-01-01

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.

Instanton dominance over αs at low momenta from lattice QCD simulations at Nf = 0, Nf = 2 + 1 and Nf = 2 + 1 + 1

NASA Astrophysics Data System (ADS)

Athenodorou, Andreas; Boucaud, Philippe; de Soto, Feliciano; Rodríguez-Quintero, José; Zafeiropoulos, Savvas

2018-03-01

We report on an instanton-based analysis of the gluon Green functions in the Landau gauge for low momenta; in particular we use lattice results for αs in the symmetric momentum subtraction scheme (MOM) for large-volume lattice simulations. We have exploited quenched gauge field configurations, Nf = 0, with both Wilson and tree-level Symanzik improved actions, and unquenched ones with Nf = 2 + 1 and Nf = 2 + 1 + 1 dynamical flavors (domain wall and twisted-mass fermions, respectively). We show that the dominance of instanton correlations on the low-momenta gluon Green functions can be applied to the determination of phenomenological parameters of the instanton liquid and, eventually, to a determination of the lattice spacing. We furthermore apply the Gradient Flow to remove short-distance fluctuations. The Gradient Flow gets rid of the QCD scale, ΛQCD, and reveals that the instanton prediction extents to large momenta. For those gauge field configurations free of quantum fluctuations, the direct study of topological charge density shows the appearance of large-scale lumps that can be identified as instantons, giving access to a direct study of the instanton density and size distribution that is compatible with those extracted from the analysis of the Green functions.

Personality Assessment Inventory scale characteristics and factor structure in the assessment of alcohol dependency.

PubMed

Schinka, J A

1995-02-01

Individual scale characteristics and the inventory structure of the Personality Assessment Inventory (PAI; Morey, 1991) were examined by conducting internal consistency and factor analyses of item and scale score data from a large group (N = 301) of alcohol-dependent patients. Alpha coefficients, mean inter-item correlations, and corrected item-total scale correlations for the sample paralleled values reported by Morey for a large clinical sample. Minor differences in the scale factor structure of the inventory from Morey's clinical sample were found. Overall, the findings support the use of the PAI in the assessment of personality and psychopathology of alcohol-dependent patients.

Statistics of velocity gradients in two-dimensional Navier-Stokes and ocean turbulence.

PubMed

Schorghofer, Norbert; Gille, Sarah T

2002-02-01

Probability density functions and conditional averages of velocity gradients derived from upper ocean observations are compared with results from forced simulations of the two-dimensional Navier-Stokes equations. Ocean data are derived from TOPEX satellite altimeter measurements. The simulations use rapid forcing on large scales, characteristic of surface winds. The probability distributions of transverse velocity derivatives from the ocean observations agree with the forced simulations, although they differ from unforced simulations reported elsewhere. The distribution and cross correlation of velocity derivatives provide clear evidence that large coherent eddies play only a minor role in generating the observed statistics.

Nonextensive Entropy Approach to Space Plasma Fluctuations and Turbulence

NASA Astrophysics Data System (ADS)

Leubner, M. P.; Vörös, Z.; Baumjohann, W.

Spatial intermittency in fully developed turbulence is an established feature of astrophysical plasma fluctuations and in particular apparent in the interplanetary medium by in situ observations. In this situation, the classical Boltzmann— Gibbs extensive thermo-statistics, applicable when microscopic interactions and memory are short ranged and the environment is a continuous and differentiable manifold, fails. Upon generalization of the entropy function to nonextensivity, accounting for long-range interactions and thus for correlations in the system, it is demonstrated that the corresponding probability distribution functions (PDFs) are members of a family of specific power-law distributions. In particular, the resulting theoretical bi-κ functional reproduces accurately the observed global leptokurtic, non-Gaussian shape of the increment PDFs of characteristic solar wind variables on all scales, where nonlocality in turbulence is controlled via a multiscale coupling parameter. Gradual decoupling is obtained by enhancing the spatial separation scale corresponding to increasing κ-values in case of slow solar wind conditions where a Gaussian is approached in the limit of large scales. Contrary, the scaling properties in the high speed solar wind are predominantly governed by the mean energy or variance of the distribution, appearing as second parameter in the theory. The PDFs of solar wind scalar field differences are computed from WIND and ACE data for different time-lags and bulk speeds and analyzed within the nonextensive theory, where also a particular nonlinear dependence of the coupling parameter and variance with scale arises for best fitting theoretical PDFs. Consequently, nonlocality in fluctuations, related to both, turbulence and its large scale driving, should be related to long-range interactions in the context of nonextensive entropy generalization, providing fundamentally the physical background of the observed scale dependence of fluctuations in intermittent space plasmas.

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

PubMed

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

2001-06-01

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

Effect of Finite Computational Domain on Turbulence Scaling Law in Both Physical and Spectral Spaces

NASA Technical Reports Server (NTRS)

Hou, Thomas Y.; Wu, Xiao-Hui; Chen, Shiyi; Zhou, Ye

1998-01-01

The well-known translation between the power law of energy spectrum and that of the correlation function or the second order structure function has been widely used in analyzing random data. Here, we show that the translation is valid only in proper scaling regimes. The regimes of valid translation are different for the correlation function and the structure function. Indeed, they do not overlap. Furthermore, in practice, the power laws exist only for a finite range of scales. We show that this finite range makes the translation inexact even in the proper scaling regime. The error depends on the scaling exponent. The current findings are applicable to data analysis in fluid turbulence and other stochastic systems.

Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence

NASA Astrophysics Data System (ADS)

Elsas, José Hugo; Szalay, Alexander S.; Meneveau, Charles

2018-04-01

Motivated by interest in the geometry of high intensity events of turbulent flows, we examine the spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analysed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation and velocity gradient invariants Q and R and their joint spatial distributions, using data from a direct numerical simulation of isotropic turbulence at Reλ ≈ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus, a geometric characterisation in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behaviour. Nevertheless, the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow.

Functional transformations of odor inputs in the mouse olfactory bulb.

PubMed

Adam, Yoav; Livneh, Yoav; Miyamichi, Kazunari; Groysman, Maya; Luo, Liqun; Mizrahi, Adi

2014-01-01

Sensory inputs from the nasal epithelium to the olfactory bulb (OB) are organized as a discrete map in the glomerular layer (GL). This map is then modulated by distinct types of local neurons and transmitted to higher brain areas via mitral and tufted cells. Little is known about the functional organization of the circuits downstream of glomeruli. We used in vivo two-photon calcium imaging for large scale functional mapping of distinct neuronal populations in the mouse OB, at single cell resolution. Specifically, we imaged odor responses of mitral cells (MCs), tufted cells (TCs) and glomerular interneurons (GL-INs). Mitral cells population activity was heterogeneous and only mildly correlated with the olfactory receptor neuron (ORN) inputs, supporting the view that discrete input maps undergo significant transformations at the output level of the OB. In contrast, population activity profiles of TCs were dense, and highly correlated with the odor inputs in both space and time. Glomerular interneurons were also highly correlated with the ORN inputs, but showed higher activation thresholds suggesting that these neurons are driven by strongly activated glomeruli. Temporally, upon persistent odor exposure, TCs quickly adapted. In contrast, both MCs and GL-INs showed diverse temporal response patterns, suggesting that GL-INs could contribute to the transformations MCs undergo at slow time scales. Our data suggest that sensory odor maps are transformed by TCs and MCs in different ways forming two distinct and parallel information streams.

Exact relations for energy transfer in self-gravitating isothermal turbulence

NASA Astrophysics Data System (ADS)

Banerjee, Supratik; Kritsuk, Alexei G.

2017-11-01

Self-gravitating isothermal supersonic turbulence is analyzed in the asymptotic limit of large Reynolds numbers. Based on the inviscid invariance of total energy, an exact relation is derived for homogeneous (not necessarily isotropic) turbulence. A modified definition for the two-point energy correlation functions is used to comply with the requirement of detailed energy equipartition in the acoustic limit. In contrast to the previous relations (S. Galtier and S. Banerjee, Phys. Rev. Lett. 107, 134501 (2011), 10.1103/PhysRevLett.107.134501; S. Banerjee and S. Galtier, Phys. Rev. E 87, 013019 (2013), 10.1103/PhysRevE.87.013019), the current exact relation shows that the pressure dilatation terms play practically no role in the energy cascade. Both the flux and source terms are written in terms of two-point differences. Sources enter the relation in a form of mixed second-order structure functions. Unlike the kinetic and thermodynamic potential energies, the gravitational contribution is absent from the flux term. An estimate shows that, for the isotropic case, the correlation between density and gravitational acceleration may play an important role in modifying the energy transfer in self-gravitating turbulence. The exact relation is also written in an alternative form in terms of two-point correlation functions, which is then used to describe scale-by-scale energy budget in spectral space.

Correlated natural transition orbital framework for low-scaling excitation energy calculations (CorNFLEx).

PubMed

Baudin, Pablo; Kristensen, Kasper

2017-06-07

We present a new framework for calculating coupled cluster (CC) excitation energies at a reduced computational cost. It relies on correlated natural transition orbitals (NTOs), denoted CIS(D')-NTOs, which are obtained by diagonalizing generalized hole and particle density matrices determined from configuration interaction singles (CIS) information and additional terms that represent correlation effects. A transition-specific reduced orbital space is determined based on the eigenvalues of the CIS(D')-NTOs, and a standard CC excitation energy calculation is then performed in that reduced orbital space. The new method is denoted CorNFLEx (Correlated Natural transition orbital Framework for Low-scaling Excitation energy calculations). We calculate second-order approximate CC singles and doubles (CC2) excitation energies for a test set of organic molecules and demonstrate that CorNFLEx yields excitation energies of CC2 quality at a significantly reduced computational cost, even for relatively small systems and delocalized electronic transitions. In order to illustrate the potential of the method for large molecules, we also apply CorNFLEx to calculate CC2 excitation energies for a series of solvated formamide clusters (up to 4836 basis functions).

Preface: Introductory Remarks: Linear Scaling Methods

NASA Astrophysics Data System (ADS)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up implementation questions relating to parallelization (particularly with multi-core processors starting to dominate the market) and inherent scaling and basis sets (in both normal and linear scaling codes). For now, the answer seems to lie between 100-1,000 atoms, though this depends on the type of simulation used among other factors. Basis sets are still a problematic question in the area of electronic structure calculations. The linear scaling community has largely split into two camps: those using relatively small basis sets based on local atomic-like functions (where systematic convergence to the full basis set limit is hard to achieve); and those that use necessarily larger basis sets which allow convergence systematically and therefore are the localised equivalent of plane waves. Related to basis sets is the study of Wannier functions, on which some linear scaling methods are based and which give a good point of contact with traditional techniques; they are particularly interesting for modelling unoccupied states with linear scaling methods. There are, of course, as many approaches to linear scaling solution for the density matrix as there are groups in the area, though there are various broad areas: McWeeny-based methods, fragment-based methods, recursion methods, and combinations of these. While many ideas have been in development for several years, there are still improvements emerging, as shown by the rich variety of the talks below. Applications using O(N) DFT methods are now starting to emerge, though they are still clearly not trivial. Once systems to be simulated cross the 10,000 atom barrier, only linear scaling methods can be applied, even with the most efficient standard techniques. One of the most challenging problems remaining, now that ab initio methods can be applied to large systems, is the long timescale problem. Although much of the work presented was concerned with improving the performance of the codes, and applying them to scientificallyimportant problems, there was another important theme: extending functionality. The search for greater accuracy has given an implementation of density functional designed to model van der Waals interactions accurately as well as local correlation, TDDFT and QMC and GW methods which, while not explicitly O(N), take advantage of localisation. All speakers at the workshop were invited to contribute to this issue, but not all were able to do this. Hence it is useful to give a complete list of the talks presented, with the names of the sessions; however, many talks fell within more than one area. This is an exciting time for linear scaling methods, which are already starting to contribute significantly to important scientific problems. Applications to nanostructures and biomolecules A DFT study on the structural stability of Ge 3D nanostructures on Si(001) using CONQUEST Tsuyoshi Miyazaki, D R Bowler, M J Gillan, T Otsuka and T Ohno Large scale electronic structure calculation theory and several applications Takeo Fujiwara and Takeo Hoshi ONETEP:Linear-scaling DFT with plane waves Chris-Kriton Skylaris, Peter D Haynes, Arash A Mostofi, Mike C Payne Maximally-localised Wannier functions as building blocks for large-scale electronic structure calculations Arash A Mostofi and Nicola Marzari A linear scaling three dimensional fragment method for ab initio calculations Lin-Wang Wang, Zhengji Zhao, Juan Meza Peta-scalable reactive Molecular dynamics simulation of mechanochemical processes Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, Fuyuki Shimojo and Priya Vashishta Recent developments and applications of the real-space multigrid (RMG) method Jerzy Bernholc, M Hodak, W Lu, and F Ribeiro Energy minimisation functionals and algorithms CONQUEST: A linear scaling DFT Code David R Bowler, Tsuyoshi Miyazaki, Antonio Torralba, Veronika Brazdova, Milica Todorovic, Takao Otsuka and Mike Gillan Kernel optimisation and the physical significance of optimised local orbitals in the ONETEP code Peter Haynes, Chris-Kriton Skylaris, Arash Mostofi and Mike Payne A miscellaneous overview of SIESTA algorithms Jose M Soler Wavelets as a basis set for electronic structure calculations and electrostatic problems Stefan Goedecker Wavelets as a basis set for linear scaling electronic structure calculationsMark Rayson O(N) Krylov subspace method for large-scale ab initio electronic structure calculations Taisuke Ozaki Linear scaling calculations with the divide-and-conquer approach and with non-orthogonal localized orbitals Weitao Yang Toward efficient wavefunction based linear scaling energy minimization Valery Weber Accurate O(N) first-principles DFT calculations using finite differences and confined orbitals Jean-Luc Fattebert Linear-scaling methods in dynamics simulations or beyond DFT and ground state properties An O(N) time-domain algorithm for TDDFT Guan Hua Chen Local correlation theory and electronic delocalization Joseph Subotnik Ab initio molecular dynamics with linear scaling: foundations and applications Eiji Tsuchida Towards a linear scaling Car-Parrinello-like approach to Born-Oppenheimer molecular dynamics Thomas Kühne, Michele Ceriotti, Matthias Krack and Michele Parrinello Partial linear scaling for quantum Monte Carlo calculations on condensed matter Mike Gillan Exact embedding of local defects in crystals using maximally localized Wannier functions Eric Cancès Faster GW calculations in larger model structures using ultralocalized nonorthogonal Wannier functions Paolo Umari Other approaches for linear-scaling, including methods formetals Partition-of-unity finite element method for large, accurate electronic-structure calculations of metals John E Pask and Natarajan Sukumar Semiclassical approach to density functional theory Kieron Burke Ab initio transport calculations in defected carbon nanotubes using O(N) techniques Blanca Biel, F J Garcia-Vidal, A Rubio and F Flores Large-scale calculations with the tight-binding (screened) KKR method Rudolf Zeller Acknowledgments We gratefully acknowledge funding for the workshop from the UK CCP9 network, CECAM and the ESF through the PsiK network. DRB, PDH and CKS are funded by the Royal Society. References [1] Car R and Parrinello M 1985 Phys. Rev. Lett. 55 2471 [2] Kühne T D, Krack M, Mohamed F R and Parrinello M 2007 Phys. Rev. Lett. 98 066401 [3] Goedecker S 1999 Rev. Mod. Phys. 71 1085

Reconstruction of halo power spectrum from redshift-space galaxy distribution: cylinder-grouping method and halo exclusion effect

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Takada, Masahiro; More, Surhud; Masaki, Shogo

2017-07-01

The peculiar velocity field measured by redshift-space distortions (RSD) in galaxy surveys provides a unique probe of the growth of large-scale structure. However, systematic effects arise when including satellite galaxies in the clustering analysis. Since satellite galaxies tend to reside in massive haloes with a greater halo bias, the inclusion boosts the clustering power. In addition, virial motions of the satellite galaxies cause a significant suppression of the clustering power due to non-linear RSD effects. We develop a novel method to recover the redshift-space power spectrum of haloes from the observed galaxy distribution by minimizing the contamination of satellite galaxies. The cylinder-grouping method (CGM) we study effectively excludes satellite galaxies from a galaxy sample. However, we find that this technique produces apparent anisotropies in the reconstructed halo distribution over all the scales which mimic RSD. On small scales, the apparent anisotropic clustering is caused by exclusion of haloes within the anisotropic cylinder used by the CGM. On large scales, the misidentification of different haloes in the large-scale structures, aligned along the line of sight, into the same CGM group causes the apparent anisotropic clustering via their cross-correlation with the CGM haloes. We construct an empirical model for the CGM halo power spectrum, which includes correction terms derived using the CGM window function at small scales as well as the linear matter power spectrum multiplied by a simple anisotropic function at large scales. We apply this model to a mock galaxy catalogue at z = 0.5, designed to resemble Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies, and find that our model can predict both the monopole and quadrupole power spectra of the host haloes up to k < 0.5 {{h Mpc^{-1}}} to within 5 per cent.

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.

Experimental techniques and computational methods toward the estimation of the effective two-phase flow coefficients and multi-scale heterogeneities of soils

NASA Astrophysics Data System (ADS)

Tsakiroglou, C. D.; Aggelopoulos, C. A.; Sygouni, V.

2009-04-01

A hierarchical, network-type, dynamic simulator of the immiscible displacement of water by oil in heterogeneous porous media is developed to simulate the rate-controlled displacement of two fluids at the soil column scale. A cubic network is constructed, where each node is assigned a permeability which is chosen randomly from a distribution function. The intensity of heterogeneities is quantified by the width of the permeability distribution function. The capillary pressure at each node is calculated by combining a generalized Leverett J-function with a Corey type model. Information about the heterogeneity of soils at the pore network scale is obtained by combining mercury intrusion porosimetry (MIP) data with back-scattered scanning electron microscope (BSEM) images [1]. In order to estimate the two-phase flow properties of nodes (relative permeability and capillary pressure functions, permeability distribution function) immiscible and miscible displacement experiments are performed on undisturbed soil columns. The transient responses of measured variables (pressure drop, fluid saturation averaged over five successive segments, solute concentration averaged over three cross-sections) are fitted with models accounting for the preferential flow paths at the micro- (multi-region model) and macro-scale (multi flowpath model) because of multi-scale heterogeneities [2,3]. Simulating the immiscible displacement of water by oil (drainage) in a large netork, at each time step, the fluid saturation and pressure of each node are calculated formulating mass balances at each node, accounting for capillary, viscous and gravity forces, and solving the system of coupled equations. At each iteration of the algorithm, the pressure drop is so selected that the total flow rate of the injected fluid is kept constant. The dynamic large-scale network simulator is used (1) to examine the sensitivity of the transient responses of the axial distribution of fluid saturation and total pressure drop across the network to the permeability distribution function, spatial correlations of permeability, and capillary number, and (2) to estimate the effective (up-scaled) relative permeability functions at the soil column scale. In an attempt to clarify potential effects of the permeability distribution and spatial permeability correlations on the transient responses of the pressure drop across a soil column, signal analysis with wavelets is performed [4] on experimental and simulated results. The transient variation of signal energy and frequency of pressure drop fluctuations at the wavelet domain are correlated with macroscopic properties such as the effective water and oil relative permeabilities of the porous medium, and microscopic properties such as the variation of the permeability distribution of oil-occupied nodes. Toward the solution of the inverse problem, a general procedure is suggested to identify macro-heterogeneities from the fast analysis of pressure drop signals. References 1. Tsakiroglou, C.D. and M.A. Ioannidis, "Dual porosity modeling of the pore structure and transport properties of a contaminated soil", Eur. J. Soil Sci., 59, 744-761 (2008). 2. Aggelopoulos, C.A., and C.D. Tsakiroglou, "Quantifying the Soil Heterogeneity from Solute Dispersion Experiments", Geoderma, 146, 412-424 (2008). 3. Aggelopoulos, C.A., and C.D. Tsakiroglou, "A multi-flow path approach to model immiscible displacement in undisturbed heterogeneous soil columns", J. Contam. Hydrol., in press (2009). 4. Sygouni, V., C.D. Tsakiroglou, and A.C. Payatakes, "Using wavelets to characterize the wettability of porous materials", Phys. Rev. E, 76, 056304 (2007).

Scale-location specific relations between soil nutrients and topographic factors in the Fen River Basin, Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Zhu, Hongfen; Bi, Rutian; Duan, Yonghong; Xu, Zhanjun

2017-06-01

Understanding scale- and location-specific variations of soil nutrients in cultivated land is a crucial consideration for managing agriculture and natural resources effectively. In the present study, wavelet coherency was used to reveal the scale-location specific correlations between soil nutrients, including soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK), as well as topographic factors (elevation, slope, aspect, and wetness index) in the cultivated land of the Fen River Basin in Shanxi Province, China. The results showed that SOM, TN, AP, and AK were significantly inter-correlated, and that the scales at which soil nutrients were correlated differed in different landscapes, and were generally smaller in topographically rougher terrain. All soil nutrients but TN were significantly influenced by the wetness index at relatively large scales (32-72 km) and AK was significantly affected by the aspect at large scales at partial locations, showing localized features. The results of this study imply that the wetness index should be taken into account during farming practices to improve the soil nutrients of cultivated land in the Fen River Basin at large scales.

Turbulent statistics and intermittency enhancement in coflowing superfluid 4He

NASA Astrophysics Data System (ADS)

Biferale, L.; Khomenko, D.; L'vov, V.; Pomyalov, A.; Procaccia, I.; Sahoo, G.

2018-02-01

The large-scale turbulent statistics of mechanically driven superfluid 4He was shown experimentally to follow the classical counterpart. In this paper, we use direct numerical simulations to study the whole range of scales in a range of temperatures T ∈[1.3 ,2.1 ] K. The numerics employ self-consistent and nonlinearly coupled normal and superfluid components. The main results are that (i) the velocity fluctuations of normal and super components are well correlated in the inertial range of scales, but decorrelate at small scales. (ii) The energy transfer by mutual friction between components is particulary efficient in the temperature range between 1.8 and 2 K, leading to enhancement of small-scale intermittency for these temperatures. (iii) At low T and close to Tλ, the scaling properties of the energy spectra and structure functions of the two components are approaching those of classical hydrodynamic turbulence.

Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

NASA Technical Reports Server (NTRS)

Grujic, L. T.; Siljak, D. D.

1973-01-01

The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

Social Functioning and Self-Esteem of Substance Abuse Patients.

PubMed

Ersöğütçü, Filiz; Karakaş, Sibel Asi

2016-10-01

This descriptive study was conducted to examine the levels of social functioning and self-esteem in individuals diagnosed with substance abuse. The study was conducted at the AMATEM (Alcohol and Substance Abuse Treatment Center) service of a psychiatry clinic in the Elazığ province in eastern Turkey between September 1, 2014 and February 1, 2015. The population is comprised of 249 patients being treated in this clinic, and the sample included 203 patients who comply with the research criteria and agreed to participate in the study. A Socia-Demographic Questionnaire, Coopersmith Self-esteem Scale (CSI) and Social Functioning Scale (SFS) were used for data collection. Percentages, averages, standard deviations and Pearson's correlation were used for data analysis. This study found that the patients' mean sore on the Self-esteem Scale is 50.97±18.01. Their score on the Social Functioning Scale is 115.76±22.41. A significant correlation between the patients' self-esteem and the age of first substance use was detected (p=0.001). A significant correlation was detected between their social functioning and the duration of their substance use (p<0.005). This study found a positive significant correlation between social functioning and self-esteem (p<0.001). This study found that substance abuse patients have a medium level of self-esteem and social functioning. A significant positive correlation between social functioning and self-esteem was found. It was also found that the age of first substance use and self-esteem are directly correlated. Counseling to increase patients' levels of self-esteem and improve their social functioning is recommended. Copyright © 2016 Elsevier Inc. All rights reserved.

Accurate and Efficient Parallel Implementation of an Effective Linear-Scaling Direct Random Phase Approximation Method.

PubMed

Graf, Daniel; Beuerle, Matthias; Schurkus, Henry F; Luenser, Arne; Savasci, Gökcen; Ochsenfeld, Christian

2018-05-08

An efficient algorithm for calculating the random phase approximation (RPA) correlation energy is presented that is as accurate as the canonical molecular orbital resolution-of-the-identity RPA (RI-RPA) with the important advantage of an effective linear-scaling behavior (instead of quartic) for large systems due to a formulation in the local atomic orbital space. The high accuracy is achieved by utilizing optimized minimax integration schemes and the local Coulomb metric attenuated by the complementary error function for the RI approximation. The memory bottleneck of former atomic orbital (AO)-RI-RPA implementations ( Schurkus, H. F.; Ochsenfeld, C. J. Chem. Phys. 2016 , 144 , 031101 and Luenser, A.; Schurkus, H. F.; Ochsenfeld, C. J. Chem. Theory Comput. 2017 , 13 , 1647 - 1655 ) is addressed by precontraction of the large 3-center integral matrix with the Cholesky factors of the ground state density reducing the memory requirements of that matrix by a factor of [Formula: see text]. Furthermore, we present a parallel implementation of our method, which not only leads to faster RPA correlation energy calculations but also to a scalable decrease in memory requirements, opening the door for investigations of large molecules even on small- to medium-sized computing clusters. Although it is known that AO methods are highly efficient for extended systems, where sparsity allows for reaching the linear-scaling regime, we show that our work also extends the applicability when considering highly delocalized systems for which no linear scaling can be achieved. As an example, the interlayer distance of two covalent organic framework pore fragments (comprising 384 atoms in total) is analyzed.

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

States of mind: emotions, body feelings, and thoughts share distributed neural networks.

PubMed

Oosterwijk, Suzanne; Lindquist, Kristen A; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

2012-09-01

Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury

PubMed Central

Wu, Xuehai; Zou, Qihong; Hu, Jin; Tang, Weijun; Mao, Ying; Gao, Liang; Zhu, Jianhong; Jin, Yi; Wu, Xin; Lu, Lu; Zhang, Yaojun; Zhang, Yao; Dai, Zhengjia; Gao, Jia-Hong; Weng, Xuchu; Northoff, Georg; Giacino, Joseph T.; He, Yong

2015-01-01

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness. PMID:26377477

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

MWASTools: an R/bioconductor package for metabolome-wide association studies.

PubMed

Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel

2018-03-01

MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version  > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Functional outcome instruments used for cervical spondylotic myelopathy: interscale correlation and prediction of preference-based quality of life.

PubMed

Whitmore, Robert G; Ghogawala, Zoher; Petrov, Dmitriy; Schwartz, J Sanford; Stein, Sherman C

2013-08-01

There is limited literature comparing different functional outcome measures used for cervical spondylotic myelopathy (CSM). To determine the correlation among five functional outcome measures used in CSM patient assessment and their ability to predict preference-based quality of life (QOL). Prospective observational study. Patients, aged 40 to 85 years, with CSM and cervical spinal cord compression at two or more levels from degenerative spondylosis were enrolled from seven sites over a 2-year period. The modified Japanese Orthopedic Association scale, Oswestry neck disability index (Oswestry NDI or Oswestry), Nurick scale, norm-based short-form 36 physical component summary, and EuroQol-5D (EQ-5D) were collected. The Jean and David Wallace foundation provided funding for this study. Cervical spondylotic myelopathy patients undergoing either anterior or posterior surgery were prospectively followed with five different functional outcome measures over 1 year. Correlations among scales were tested using the Spearman rank correlation test. The sensitivity and specificity of each scale for predicting the global index of the EQ-5D were determined, and receiver-operating characteristic analysis was used to compare each scale's ability to discriminate QOL. A total of 106 patients were initially enrolled; 103 were operated on for CSM and followed for 1 year. Their ages ranged from 40 to 82 years (mean 61.9), and 61.3% were men. Correlations among the various functional outcome instruments were all highly significant (p<.001), but the degree of correlation varied greatly. Correlation between the EQ-5D scale and the Nurick scale was the least (Spearman rho 0.5539); correlation was the highest with the Oswestry NDI (Spearman rho 0.8306). The Oswestry NDI also had the greatest ability to discriminate favorable from adverse QOL compared with the other outcome instruments (p=.023). Preference-based quality-of-life instruments, such as the EQ-5D, are important measures for studying spinal disorders. Among the various commonly used outcome instruments for CSM, the Oswestry NDI is the most predictive of preference-based QOL. Copyright © 2013 Elsevier Inc. All rights reserved.

DEMNUni: massive neutrinos and the bispectrum of large scale structures

NASA Astrophysics Data System (ADS)

Ruggeri, Rossana; Castorina, Emanuele; Carbone, Carmelita; Sefusatti, Emiliano

2018-03-01

The main effect of massive neutrinos on the large-scale structure consists in a few percent suppression of matter perturbations on all scales below their free-streaming scale. Such effect is of particular importance as it allows to constraint the value of the sum of neutrino masses from measurements of the galaxy power spectrum. In this work, we present the first measurements of the next higher-order correlation function, the bispectrum, from N-body simulations that include massive neutrinos as particles. This is the simplest statistics characterising the non-Gaussian properties of the matter and dark matter halos distributions. We investigate, in the first place, the suppression due to massive neutrinos on the matter bispectrum, comparing our measurements with the simplest perturbation theory predictions, finding the approximation of neutrinos contributing at quadratic order in perturbation theory to provide a good fit to the measurements in the simulations. On the other hand, as expected, a linear approximation for neutrino perturbations would lead to Script O(fν) errors on the total matter bispectrum at large scales. We then attempt an extension of previous results on the universality of linear halo bias in neutrino cosmologies, to non-linear and non-local corrections finding consistent results with the power spectrum analysis.

Reliability and validity of simplified Chinese version of Swiss Spinal Stenosis Questionnaire for patients with degenerative lumbar spinal stenosis.

PubMed

Yi, Honglei; Wei, Xianzhao; Zhang, Wei; Chen, Ziqiang; Wang, Xinhui; Ji, Xinran; Zhu, Xiaodong; Wang, Fei; Xu, Ximing; Li, Zhikun; Fan, Jianping; Wang, Chuanfeng; Chen, Kai; Zhang, Guoyou; Zhao, Yinchuan; Li, Ming

2014-05-01

This was a prospective clinical validation study. To evaluate the reliability and validity of the adapted simplified Chinese version of Swiss Spinal Stenosis (SC-SSS) Questionnaire. The SSS Questionnaire is a reliable and valid instrument to assess the perception of function and pain for patients with degenerative lumbar spinal stenosis. However, there is no culturally adapted SSS Questionnaire for use in mainland China. This was a prospective clinical validation study. The adaption was conducted according to International Quality of Life Assessment Project guidelines. To examine the psychometric properties of the adapted SC-SSS Questionnaire, a sample of 105 patients with lumbar spinal stenosis were included. Thirty-two patients were randomly selected to evaluate the test-retest reliability. Reliability assessment of the SC-SSS Questionnaire was determined by calculating Cronbach α and intraclass coefficient values. Concurrent validity was assessed by correlating SC-SSS Questionnaire scores with relevant domains of the 36-Item Short Form Health Survey. Cronbach α of the symptom severity scale, physical function scale, patients, and satisfaction scale of SC-SSS Questionnaire are 0.89, 0.86, 0.91, respectively, which revealed very good internal consistency. The test-retest reproducibility was found to be excellent with the intraclass correlation coefficient of 0.93, 0.91, and 0.95. In terms of concurrent validity, SC-SSS Questionnaire had good correlation with physical functioning and bodily pain of 36-Item Short Form Health Survey (r = 0.663, 0.653) and low correlation with mental health (r = 0.289). The physical function scale had good correlation with physical functioning of 36-Item Short Form Health Survey (r = 0.637), whereas the rest had moderate correlation. The satisfaction scale score was highly correlated with the change in the symptom severity (r = 0.71) and physical function (r = 0.68) scale score. The SC-SSS Questionnaire showed satisfactory reliability and validity in the evaluation of functionality in patients with lumbar spinal stenosis who are experiencing neurogenic claudication. It is simple and easy to use and can be recommended in clinical and research practice in mainland China. 3.

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.

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

Columnar organization of orientation domains in V1

NASA Astrophysics Data System (ADS)

Liedtke, Joscha; Wolf, Fred

In the primary visual cortex (V1) of primates and carnivores, the functional architecture of basic stimulus selectivities appears similar across cortical layers (Hubel & Wiesel, 1962) justifying the use of two-dimensional cortical models and disregarding organization in the third dimension. Here we show theoretically that already small deviations from an exact columnar organization lead to non-trivial three-dimensional functional structures. We extend two-dimensional random field models (Schnabel et al., 2007) to a three-dimensional cortex by keeping a typical scale in each layer and introducing a correlation length in the third, columnar dimension. We examine in detail the three-dimensional functional architecture for different cortical geometries with different columnar correlation lengths. We find that (i) topological defect lines are generally curved and (ii) for large cortical curvatures closed loops and reconnecting topological defect lines appear. This theory extends the class of random field models by introducing a columnar dimension and provides a systematic statistical assessment of the three-dimensional functional architecture of V1 (see also (Tanaka et al., 2011)).

N -tag probability law of the symmetric exclusion process

NASA Astrophysics Data System (ADS)

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

2018-06-01

The symmetric exclusion process (SEP), in which particles hop symmetrically on a discrete line with hard-core constraints, is a paradigmatic model of subdiffusion in confined systems. This anomalous behavior is a direct consequence of strong spatial correlations induced by the requirement that the particles cannot overtake each other. Even if this fact has been recognized qualitatively for a long time, up to now there has been no full quantitative determination of these correlations. Here we study the joint probability distribution of an arbitrary number of tagged particles in the SEP. We determine analytically its large-time limit for an arbitrary density of particles, and its full dynamics in the high-density limit. In this limit, we obtain the time-dependent large deviation function of the problem and unveil a universal scaling form shared by the cumulants.

3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation

NASA Astrophysics Data System (ADS)

Chen, Z.; Meng, X.; Guo, L.; Liu, G.

2011-12-01

In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and comtinue to perform 3D correlation imaging for the redisual gravity data. After several iterations, we can obtain a satisfactoy results. Newly developed general purpose computing technology from Nvidia GPU (Graphics Processing Unit) has been put into practice and received widespread attention in many areas. Based on the GPU programming mode and two parallel levels, five CPU loops for the main computation of 3D correlation imaging are converted into three loops in GPU kernel functions, thus achieving GPU/CPU collaborative computing. The two inner loops are defined as the dimensions of blocks and the three outer loops are defined as the dimensions of threads, thus realizing the double loop block calculation. Theoretical and real gravity data tests show that results are reliable and the computing time is greatly reduced. Acknowledgments We acknowledge the financial support of Sinoprobe project (201011039 and 201011049-03), the Fundamental Research Funds for the Central Universities (2010ZY26 and 2011PY0183), the National Natural Science Foundation of China (41074095) and the Open Project of State Key Laboratory of Geological Processes and Mineral Resources (GPMR0945).

Multipoint propagators in cosmological gravitational instability

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

Bernardeau, Francis; Crocce, Martin; Scoccimarro, Roman

2008-11-15

We introduce the concept of multipoint propagators between linear cosmic fields and their nonlinear counterparts in the context of cosmological perturbation theory. Such functions express how a nonlinearly evolved Fourier mode depends on the full ensemble of modes in the initial density field. We identify and resum the dominant diagrams in the large-k limit, showing explicitly that multipoint propagators decay into the nonlinear regime at the same rate as the two-point propagator. These analytic results generalize the large-k limit behavior of the two-point propagator to arbitrary order. We measure the three-point propagator as a function of triangle shape in numericalmore » simulations and confirm the results of our high-k resummation. We show that any n-point spectrum can be reconstructed from multipoint propagators, which leads to a physical connection between nonlinear corrections to the power spectrum at small scales and higher-order correlations at large scales. As a first application of these results, we calculate the reduced bispectrum at one loop in renormalized perturbation theory and show that we can predict the decrease in its dependence on triangle shape at redshift zero, when standard perturbation theory is least successful.« less

Clustering analysis of high-redshift luminous red galaxies in Stripe 82

NASA Astrophysics Data System (ADS)

Nikoloudakis, N.; Shanks, T.; Sawangwit, U.

2013-03-01

We present a clustering analysis of luminous red galaxies (LRGs) in Stripe 82 from the Sloan Digital Sky Survey (SDSS). We study the angular two-point autocorrelation function, w(θ), of a selected sample of over 130 000 LRG candidates via colour-cut selections in izK with the K-band coverage coming from UKIRT (United Kingdom Infrared Telescope) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). We have used the cross-correlation technique of Newman to establish the redshift distribution of the LRGs. Cross-correlating them with SDSS quasi-stellar objects (QSOs), MegaZ-LRGs and DEEP Extragalactic Evolutionary Probe 2 (DEEP2) galaxies, implies an average redshift of the LRGs to be z ≈ 1 with space density, ng ≈ 3.20 ± 0.16 × 10-4 h3 Mpc-3. For θ ≤ 10 arcmin (corresponding to ≈10 h-1 Mpc), the LRG w(θ) significantly deviates from a conventional single power law as noted by previous clustering studies of highly biased and luminous galaxies. A double power law with a break at rb ≈ 2.4 h-1 Mpc fits the data better, with best-fitting scale length, r0, 1 = 7.63 ± 0.27 h-1 Mpc and slope γ1 = 2.01 ± 0.02 at small scales and r0, 2 = 9.92 ± 0.40 h-1 Mpc and γ2 = 1.64 ± 0.04 at large scales. Due to the flat slope at large scales, we find that a standard Λ cold dark matter (Λ CDM) linear model is accepted only at 2-3σ, with the best-fitting bias factor, b = 2.74 ± 0.07. We also fitted the halo occupation distribution (HOD) models to compare our measurements with the predictions of the dark matter clustering. The effective halo mass of Stripe 82 LRGs is estimated as Meff = 3.3 ± 0.6 × 1013 h-1 M⊙. But at large scales, the current HOD models did not help explain the power excess in the clustering signal. We then compare the w(θ) results to the results of Sawangwit et al. from three samples of photometrically selected LRGs at lower redshifts to measure clustering evolution. We find that a long-lived model may be a poorer fit than at lower redshifts, although this assumes that the Stripe 82 LRGs are luminosity-matched to the AAΩ LRGs. We find stronger evidence for evolution in the form of the z ≈ 1 LRG correlation function with the above flat two-halo slope maintaining to s ≳ 50 h- 1 Mpc. Applying the cross-correlation test of Ross et al., we find little evidence that the result is due to systematics. Otherwise, it may represent evidence for primordial non-Gaussianity in the density perturbations at early times, with flocalNL = 90 ± 30.

A correlation between the cosmic microwave background and large-scale structure in the Universe.

PubMed

Boughn, Stephen; Crittenden, Robert

2004-01-01

Observations of distant supernovae and the fluctuations in the cosmic microwave background (CMB) indicate that the expansion of the Universe may be accelerating under the action of a 'cosmological constant' or some other form of 'dark energy'. This dark energy now appears to dominate the Universe and not only alters its expansion rate, but also affects the evolution of fluctuations in the density of matter, slowing down the gravitational collapse of material (into, for example, clusters of galaxies) in recent times. Additional fluctuations in the temperature of CMB photons are induced as they pass through large-scale structures and these fluctuations are necessarily correlated with the distribution of relatively nearby matter. Here we report the detection of correlations between recent CMB data and two probes of large-scale structure: the X-ray background and the distribution of radio galaxies. These correlations are consistent with those predicted by dark energy, indicating that we are seeing the imprint of dark energy on the growth of structure in the Universe.

Measuring motivation in people with schizophrenia.

PubMed

Fervaha, Gagan; Foussias, George; Takeuchi, Hiroyoshi; Agid, Ofer; Remington, Gary

2015-12-01

Motivational deficits are a key determinant of poor functional outcomes in schizophrenia. These impairments are typically evaluated using various clinical rating scales; however, the degree of convergence between motivation scores derived from different instruments is not clear. In the present study, we measured motivational deficits in 62 patients with schizophrenia using 5 scores derived from 3 different instruments. We found that the scores from these different instruments were highly inter-correlated, and largely independent of severity of other symptom domains (e.g., depression). Our findings suggest that clinical ratings scales evaluating motivational deficits are tapping into a similar underlying construct. Copyright © 2015 Elsevier B.V. All rights reserved.

Translation, cultural adaptation and reproducibility of the Cochin Hand Functional Scale questionnaire for Brazil

PubMed Central

Chiari, Aline; de Souza Sardim, Carla Caires; Natour, Jamil

2011-01-01

OBJECTIVE: To translate, to perform a cultural adaptation of and to test the reproducibility of the Cochin Hand Functional Scale questionnaire for Brazil. METHODS: First, the Cochin Hand Functional Scale questionnaire was translated into Portuguese and was then back-translated into French. These translations were reviewed by a committee to establish a Brazilian version of the questionnaire to be tested. The validity and reproducibility of the Cochin Hand Functional Scale questionnaire was evaluated. Patients of both sexes, who were aged 18 to 60 years and presented with rheumatoid arthritis affecting their hands, were interviewed. The patients were initially interviewed by two observers and were later interviewed by a single rater. First, the Visual Analogue Scale for hand pain, the Arm, Shoulder and Hand Disability questionnaire and the Health Assessment Questionnaire were administered. The third administration of the Cochin Hand Functional Scale was performed fifteen days after the first administration. Ninety patients were assessed in the present study. RESULTS: Two questions were modified as a result of the assessment of cultural equivalence. The Cronbach's alpha value for this assessment was 0.93. The intraclass intraobserver and interobserver correlation coefficients were 0.76 and 0.96, respectively. The Spearman's coefficient indicated that there was a low level of correlation between the Cochin Hand Functional Scale and the Visual Analogue Scale for pain (0.46) and that there was a moderate level of correlation of the Cochin Scale with the Health Assessment Questionnaire (0.66) and with the Disability of the Arm, Shoulder and Hand questionnaire (0.63). The average administration time for the Cochin Scale was three minutes. CONCLUSION: The Brazilian version of the Cochin Hand Functional Scale was successfully translated and adapted, and this version exhibited good internal consistency, reliability and construct validity. PMID:21789372

Use of large-scale acoustic monitoring to assess anthropogenic pressures on Orthoptera communities.

PubMed

Penone, Caterina; Le Viol, Isabelle; Pellissier, Vincent; Julien, Jean-François; Bas, Yves; Kerbiriou, Christian

2013-10-01

Biodiversity monitoring at large spatial and temporal scales is greatly needed in the context of global changes. Although insects are a species-rich group and are important for ecosystem functioning, they have been largely neglected in conservation studies and policies, mainly due to technical and methodological constraints. Sound detection, a nondestructive method, is easily applied within a citizen-science framework and could be an interesting solution for insect monitoring. However, it has not yet been tested at a large scale. We assessed the value of a citizen-science program in which Orthoptera species (Tettigoniidae) were monitored acoustically along roads. We used Bayesian model-averaging analyses to test whether we could detect widely known patterns of anthropogenic effects on insects, such as the negative effects of urbanization or intensive agriculture on Orthoptera populations and communities. We also examined site-abundance correlations between years and estimated the biases in species detection to evaluate and improve the protocol. Urbanization and intensive agricultural landscapes negatively affected Orthoptera species richness, diversity, and abundance. This finding is consistent with results of previous studies of Orthoptera, vertebrates, carabids, and butterflies. The average mass of communities decreased as urbanization increased. The dispersal ability of communities increased as the percentage of agricultural land and, to a lesser extent, urban area increased. Despite changes in abundances over time, we found significant correlations between yearly abundances. We identified biases linked to the protocol (e.g., car speed or temperature) that can be accounted for ease in analyses. We argue that acoustic monitoring of Orthoptera along roads offers several advantages for assessing Orthoptera biodiversity at large spatial and temporal extents, particularly in a citizen science framework. © 2013 Society for Conservation Biology.

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Tissue-specific methylation differences and cognitive function in fragile X premutation females

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

Allingham-Hawkins, D.J.; Babul, R.; Chitayat, D.

1996-08-09

Tissue-specific variation in (CGG){sub n} repeat size and methylation status of the FMR1 gene was investigated in 17 female premutation carriers. Minor variation in premutation repeat size among leukocyte, lymphoblast, and fibroblast tissues was noted in some subjects. One subject exhibited a premutation size allele of (CGG){sub 64} in leukocyte and fibroblast tissues by polymerase chain reaction analysis but a normal-size allele of (CGG){sub 46} in lymphoblast cells, suggesting low-level mosaicism in blood and clonality of the lymphoblast cell line. Six subjects exhibited differences in methylation pattern between leukocytes and lymphoblasts but not between leukocytes and fibroblasts, whereas 2 subjectsmore » showed large differences in methylation pattern between leukocytes and fibroblasts. Cognitive function was studied in 14 subjects using the Wechsler Adult Intelligence Scale-Revised. Mean Verbal and Performance IQs were well within the average range as was the mean Full Scale IQ; nevertheless, a trend toward lower Performance IQ compared with Verbal IQ was observed. No significant correlation was apparent between Full Scale IQ and (CGG){sub n} repeat size; however, a significant positive correlation was observed between Full Scale IQ and the proportion of the active X carrying the normal FMR1 allele in fibroblasts but not in leukocytes or lymphoblasts. 24 refs., 1 fig., 2 tabs.« less

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. II. Linear scaling domain based pair natural orbital coupled cluster theory

NASA Astrophysics Data System (ADS)

Riplinger, Christoph; Pinski, Peter; Becker, Ute; Valeev, Edward F.; Neese, Frank

2016-01-01

Domain based local pair natural orbital coupled cluster theory with single-, double-, and perturbative triple excitations (DLPNO-CCSD(T)) is a highly efficient local correlation method. It is known to be accurate and robust and can be used in a black box fashion in order to obtain coupled cluster quality total energies for large molecules with several hundred atoms. While previous implementations showed near linear scaling up to a few hundred atoms, several nonlinear scaling steps limited the applicability of the method for very large systems. In this work, these limitations are overcome and a linear scaling DLPNO-CCSD(T) method for closed shell systems is reported. The new implementation is based on the concept of sparse maps that was introduced in Part I of this series [P. Pinski, C. Riplinger, E. F. Valeev, and F. Neese, J. Chem. Phys. 143, 034108 (2015)]. Using the sparse map infrastructure, all essential computational steps (integral transformation and storage, initial guess, pair natural orbital construction, amplitude iterations, triples correction) are achieved in a linear scaling fashion. In addition, a number of additional algorithmic improvements are reported that lead to significant speedups of the method. The new, linear-scaling DLPNO-CCSD(T) implementation typically is 7 times faster than the previous implementation and consumes 4 times less disk space for large three-dimensional systems. For linear systems, the performance gains and memory savings are substantially larger. Calculations with more than 20 000 basis functions and 1000 atoms are reported in this work. In all cases, the time required for the coupled cluster step is comparable to or lower than for the preceding Hartree-Fock calculation, even if this is carried out with the efficient resolution-of-the-identity and chain-of-spheres approximations. The new implementation even reduces the error in absolute correlation energies by about a factor of two, compared to the already accurate previous implementation.

Hospital for Special Surgery Pediatric Functional Activity Brief Scale predicts physical fitness testing performance.

PubMed

Fabricant, Peter D; Robles, Alex; McLaren, Son H; Marx, Robert G; Widmann, Roger F; Green, Daniel W

2014-05-01

An eight-item activity scale was recently developed and validated for use as a prognostic tool in clinical research in children and adolescents. It is unclear, however, if this brief questionnaire is predictive of quantitative metrics of physical activity and fitness. The purposes of this study were to prospectively administer the Hospital for Special Surgery Pediatric Functional Activity Brief Scale to a large cohort of healthy adolescents to determine (1) if the activity scale exhibits any floor or ceiling effects; (2) if scores on the activity scale are correlated with standardized physical fitness metrics; and if so, (3) to determine the discrimination ability of the activity scale to differentiate between adolescents with healthy or unhealthy levels of aerobic capacity and calculate an appropriate cutoff value for its use as a screening tool. One hundred eighty-two adolescents (mean, 15.3 years old) prospectively completed the activity scale and four standardized metrics of physical fitness: pushups, sit-ups, shuttle run exercise (Progressive Aerobic Cardiovascular Endurance Run), and calculated VO2-max. Age, sex, and body mass index were also recorded. Pearson correlations, regression analyses, and receiver operating characteristic analyses were used to evaluate activity scale performance. The activity scale did not exhibit any floor or ceiling effects. Pushups (ρ = 0.28), sit-ups (ρ = 0.23), performance on the Progressive Aerobic Cardiovascular Endurance Run (ρ = 0.44), and VO2-max (ρ = 0.43) were all positively correlated with the activity scale score (Pearson correlations, all p < 0.001). Receiver operating characteristic analysis revealed that those with an activity score of ≤ 14 were at higher risk of having low levels of aerobic capacity. In the current study, activity score was free of floor and ceiling effects and predictive of all four physical fitness metrics. An activity score of ≤ 14 was associated with at-risk aerobic capacity previously shown to be associated with an increased risk of metabolic syndrome. This study is the first to prospectively validate an activity questionnaire against quantitative physical fitness assessments and provides further evidence substantiating its use in outcomes research and screening for healthy levels of childhood activity and fitness. Level I, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Convergence between biological, behavioural and genetic determinants of obesity.

PubMed

Ghosh, Sujoy; Bouchard, Claude

2017-12-01

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.

Simple Statistical Model to Quantify Maximum Expected EMC in Spacecraft and Avionics Boxes

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Bremner, Paul

2014-01-01

This study shows cumulative distribution function (CDF) comparisons of composite a fairing electromagnetic field data obtained by computational electromagnetic 3D full wave modeling and laboratory testing. Test and model data correlation is shown. In addition, this presentation shows application of the power balance and extention of this method to predict the variance and maximum exptected mean of the E-field data. This is valuable for large scale evaluations of transmission inside cavities.

Synchrony between reanalysis-driven RCM simulations and observations: variation with time scale

NASA Astrophysics Data System (ADS)

de Elía, Ramón; Laprise, René; Biner, Sébastien; Merleau, James

2017-04-01

Unlike coupled global climate models (CGCMs) that run in a stand-alone mode, nested regional climate models (RCMs) are driven by either a CGCM or a reanalysis dataset. This feature makes high correlations between the RCM simulation and its driver possible. When the driving dataset is a reanalysis, time correlations between RCM output and observations are also common and to be expected. In certain situations time correlation between driver and driven RCM is of particular interest and techniques have been developed to increase it (e.g. large-scale spectral nudging). For such cases, a question that remains open is whether aggregating in time increases the correlation between RCM output and observations. That is, although the RCM may be unable to reproduce a given daily event, whether it will still be able to satisfactorily simulate an anomaly on a monthly or annual basis. This is a preconception that the authors of this work and others in the community have held, perhaps as a natural extension of the properties of upscaling or aggregating other statistics such as the mean squared error. Here we explore analytically four particular cases that help us partially answer this question. In addition, we use observations datasets and RCM-simulated data to illustrate our findings. Results indicate that time upscaling does not necessarily increase time correlations, and that those interested in achieving high monthly or annual time correlations between RCM output and observations may have to do so by increasing correlation as much as possible at the shortest time scale. This may indicate that even when only concerned with time correlations at large temporal scale, large-scale spectral nudging acting at the time-step level may have to be used.

Potential toxicity of graphene to cell functions via disrupting protein-protein interactions.

PubMed

Luan, Binquan; Huynh, Tien; Zhao, Lin; Zhou, Ruhong

2015-01-27

While carbon-based nanomaterials such as graphene and carbon nanotubes (CNTs) have become popular in state-of-the-art nanotechnology, their biological safety and underlying molecular mechanism is still largely unknown. Experimental studies have been focused at the cellular level and revealed good correlations between cell's death and the application of CNTs or graphene. Using large-scale all-atom molecular dynamics simulations, we theoretically investigate the potential toxicity of graphene to a biological cell at molecular level. Simulation results show that the hydrophobic protein-protein interaction (or recognition) that is essential to biological functions can be interrupted by a graphene nanosheet. Due to the hydrophobic nature of graphene, it is energetically favorable for a graphene nanosheet to enter the hydrophobic interface of two contacting proteins, such as a dimer. The forced separation of two functional proteins can disrupt the cell's metabolism and even lead to the cell's mortality.

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

PubMed

Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

2011-01-01

Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

Network-dependent modulation of brain activity during sleep.

PubMed

Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

2014-09-01

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Effects of Eddy Viscosity on Time Correlations in Large Eddy Simulation

NASA Technical Reports Server (NTRS)

He, Guowei; Rubinstein, R.; Wang, Lian-Ping; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

Subgrid-scale (SGS) models for large. eddy simulation (LES) have generally been evaluated by their ability to predict single-time statistics of turbulent flows such as kinetic energy and Reynolds stresses. Recent application- of large eddy simulation to the evaluation of sound sources in turbulent flows, a problem in which time, correlations determine the frequency distribution of acoustic radiation, suggest that subgrid models should also be evaluated by their ability to predict time correlations in turbulent flows. This paper compares the two-point, two-time Eulerian velocity correlation evaluated from direct numerical simulation (DNS) with that evaluated from LES, using a spectral eddy viscosity, for isotropic homogeneous turbulence. It is found that the LES fields are too coherent, in the sense that their time correlations decay more slowly than the corresponding time. correlations in the DNS fields. This observation is confirmed by theoretical estimates of time correlations using the Taylor expansion technique. Tile reason for the slower decay is that the eddy viscosity does not include the random backscatter, which decorrelates fluid motion at large scales. An effective eddy viscosity associated with time correlations is formulated, to which the eddy viscosity associated with energy transfer is a leading order approximation.

Statistical measures of Planck scale signal correlations in interferometers

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

Hogan, Craig J.; Kwon, Ohkyung

2015-06-22

A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of informationmore » suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. As a result, simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.« less

Image processing via VLSI: A concept paper

NASA Technical Reports Server (NTRS)

Nathan, R.

1982-01-01

Implementing specific image processing algorithms via very large scale integrated systems offers a potent solution to the problem of handling high data rates. Two algorithms stand out as being particularly critical -- geometric map transformation and filtering or correlation. These two functions form the basis for data calibration, registration and mosaicking. VLSI presents itself as an inexpensive ancillary function to be added to almost any general purpose computer and if the geometry and filter algorithms are implemented in VLSI, the processing rate bottleneck would be significantly relieved. A set of image processing functions that limit present systems to deal with future throughput needs, translates these functions to algorithms, implements via VLSI technology and interfaces the hardware to a general purpose digital computer is developed.

Mental Health Has a Stronger Association with Patient-Reported Shoulder Pain and Function Than Tear Size in Patients with Full-Thickness Rotator Cuff Tears.

PubMed

Wylie, James D; Suter, Thomas; Potter, Michael Q; Granger, Erin K; Tashjian, Robert Z

2016-02-17

Patient-reported outcome measures have increasingly accompanied objective examination findings in the evaluation of orthopaedic interventions. Our objective was to determine whether a validated measure of mental health (Short Form-36 Mental Component Summary [SF-36 MCS]) or measures of tear severity on magnetic resonance imaging were more strongly associated with self-assessed shoulder pain and function in patients with symptomatic full-thickness rotator cuff tears. One hundred and sixty-nine patients with full-thickness rotator cuff tears were prospectively enrolled. Patients completed the Short Form-36, visual analog scales for shoulder pain and function, the Simple Shoulder Test (SST), and the American Shoulder and Elbow Surgeons (ASES) instrument at the time of diagnosis. Shoulder magnetic resonance imaging examinations were reviewed to document the number of tendons involved, tear size, tendon retraction, and tear surface area. Age, sex, body mass index, number of medical comorbidities, smoking status, and Workers' Compensation status were recorded. Bivariate correlations and multivariate regression models were calculated to identify associations with baseline shoulder scores. The SF-36 MCS had the strongest correlation with the visual analog scale for shoulder pain (Pearson correlation coefficient, -0.48; p < 0.001), the visual analog scale for shoulder function (Pearson correlation coefficient, -0.33; p < 0.001), the SST (Pearson correlation coefficient, 0.37; p < 0.001), and the ASES score (Pearson correlation coefficient, 0.51; p < 0.001). Tear severity only correlated with the visual analog scale for shoulder function; the Pearson correlation coefficient was 0.19 for tear size (p = 0.018), 0.18 for tendon retraction (p = 0.025), 0.18 for tear area (p = 0.022), and 0.20 for the number of tendons involved (p = 0.011). Tear severity did not correlate with other scores in bivariate correlations (all p > 0.05). In all multivariate models, the SF-36 MCS had the strongest association with the visual analog scale for shoulder pain, the visual analog scale for shoulder function, the SST, and the ASES score (all p < 0.001). Patient mental health may play an influential role in patient-reported pain and function in patients with full-thickness rotator cuff tears. Further studies are needed to determine its effect on the outcome of the treatment of rotator cuff disease. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

Properties of the Magnitude Terms of Orthogonal Scaling Functions.

PubMed

Tay, Peter C; Havlicek, Joseph P; Acton, Scott T; Hossack, John A

2010-09-01

The spectrum of the convolution of two continuous functions can be determined as the continuous Fourier transform of the cross-correlation function. The same can be said about the spectrum of the convolution of two infinite discrete sequences, which can be determined as the discrete time Fourier transform of the cross-correlation function of the two sequences. In current digital signal processing, the spectrum of the contiuous Fourier transform and the discrete time Fourier transform are approximately determined by numerical integration or by densely taking the discrete Fourier transform. It has been shown that all three transforms share many analogous properties. In this paper we will show another useful property of determining the spectrum terms of the convolution of two finite length sequences by determining the discrete Fourier transform of the modified cross-correlation function. In addition, two properties of the magnitude terms of orthogonal wavelet scaling functions are developed. These properties are used as constraints for an exhaustive search to determine an robust lower bound on conjoint localization of orthogonal scaling functions.

Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem

USGS Publications Warehouse

Schneider, Davod C.; Piatt, John F.

1986-01-01

The distribution of piscivorous seabirds relative to schooling fish was investigated by repeated censusing of 2 intersecting transects in the Avalon Channel, which carries the Labrador Current southward along the east coast of Newfoundland. Murres (primarily common murres Uria aalge), Atlantic puffins Fratercula arctica, and schooling fish (primarily capelin Mallotus villosus) were highly aggregated at spatial scales ranging from 0.25 to 15 km. Patchiness of murres, puffins and schooling fish was scale-dependent, as indicated by significantly higher variance-to-mean ratios at large measurement distances than at the minimum distance, 0.25 km. Patch scale of puffins ranged from 2.5 to 15 km, of murres from 3 to 8.75 km, and of schooling fish from 1.25 to 15 km. Patch scale of birds and schooling fish was similar m 6 out of 9 comparisons. Correlation between seabirds and schooling birds was significant at the minimum measurement distance in 6 out of 12 comparisons. Correlation was scale-dependent, as indicated by significantly higher coefficients at large measurement distances than at the minimum distance. Tracking scale, as indicated by the maximum significant correlation between birds and schooling fish, ranged from 2 to 6 km. Our analysis showed that extended aggregations of seabirds are associated with extended aggregations of schooling fish and that correlation of these marine carnivores with their prey is scale-dependent.

CMB hemispherical asymmetry from non-linear isocurvature perturbations

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

Assadullahi, Hooshyar; Wands, David; Firouzjahi, Hassan

2015-04-01

We investigate whether non-adiabatic perturbations from inflation could produce an asymmetric distribution of temperature anisotropies on large angular scales in the cosmic microwave background (CMB). We use a generalised non-linear δ N formalism to calculate the non-Gaussianity of the primordial density and isocurvature perturbations due to the presence of non-adiabatic, but approximately scale-invariant field fluctuations during multi-field inflation. This local-type non-Gaussianity leads to a correlation between very long wavelength inhomogeneities, larger than our observable horizon, and smaller scale fluctuations in the radiation and matter density. Matter isocurvature perturbations contribute primarily to low CMB multipoles and hence can lead to a hemisphericalmore » asymmetry on large angular scales, with negligible asymmetry on smaller scales. In curvaton models, where the matter isocurvature perturbation is partly correlated with the primordial density perturbation, we are unable to obtain a significant asymmetry on large angular scales while respecting current observational constraints on the observed quadrupole. However in the axion model, where the matter isocurvature and primordial density perturbations are uncorrelated, we find it may be possible to obtain a significant asymmetry due to isocurvature modes on large angular scales. Such an isocurvature origin for the hemispherical asymmetry would naturally give rise to a distinctive asymmetry in the CMB polarisation on large scales.« less

Spatial variability and macro‐scale drivers of growth for native and introduced Flathead Catfish populations

USGS Publications Warehouse

Massie, Danielle L.; Smith, Geoffrey; Bonvechio, Timothy F.; Bunch, Aaron J.; Lucchesi, David O.; Wagner, Tyler

2018-01-01

Quantifying spatial variability in fish growth and identifying large‐scale drivers of growth are fundamental to many conservation and management decisions. Although fish growth studies often focus on a single population, it is becoming increasingly clear that large‐scale studies are likely needed for addressing transboundary management needs. This is particularly true for species with high recreational value and for those with negative ecological consequences when introduced outside of their native range, such as the Flathead Catfish Pylodictis olivaris. This study quantified growth variability of the Flathead Catfish across a large portion of its contemporary range to determine whether growth differences existed between habitat types (i.e., reservoirs and rivers) and between native and introduced populations. Additionally, we investigated whether growth parameters varied as a function of latitude and time since introduction (for introduced populations). Length‐at‐age data from 26 populations across 11 states in the USA were modeled using a Bayesian hierarchical von Bertalanffy growth model. Population‐specific growth trajectories revealed large variation in Flathead Catfish growth and relatively high uncertainty in growth parameters for some populations. Relatively high uncertainty was also evident when comparing populations and when quantifying large‐scale patterns. Growth parameters (Brody growth coefficient [K] and theoretical maximum average length [L∞]) were not different (based on overlapping 90% credible intervals) between habitat types or between native and introduced populations. For populations within the introduced range of Flathead Catfish, latitude was negatively correlated with K. For native populations, we estimated an 85% probability that L∞ estimates were negatively correlated with latitude. Contrary to predictions, time since introduction was not correlated with growth parameters in introduced populations of Flathead Catfish. Results of this study suggest that Flathead Catfish growth patterns are likely shaped more strongly by finer‐scale processes (e.g., exploitation or prey abundances) as opposed to macro‐scale drivers.

Topologically-associating domains are stable units of replication-timing regulation

PubMed Central

Pope, Benjamin D.; Ryba, Tyrone; Dileep, Vishnu; Yue, Feng; Wu, Weisheng; Denas, Olgert; Vera, Daniel L.; Wang, Yanli; Hansen, R. Scott; Canfield, Theresa K.; Thurman, Robert E.; Cheng, Yong; Gülsoy, Günhan; Dennis, Jonathan H.; Snyder, Michael P.; Stamatoyannopoulos, John A.; Taylor, James; Hardison, Ross C.; Kahveci, Tamer; Ren, Bing; Gilbert, David M.

2014-01-01

Summary Eukaryotic chromosomes replicate in a temporal order known as the replication-timing program1. During mammalian development, at least half the genome changes replication timing, primarily in units of 400–800 kb (“replication domains”; RDs), whose positions are preserved in different cell types, conserved between species, and appear to confine long-range effects of chromosome rearrangements2–7. Early and late replication correlate strongly with open and closed chromatin compartments identified by high-resolution chromosome conformation capture (Hi-C), and, to a lesser extent, lamina-associated domains (LADs)4,5,8,9. Recent Hi-C mapping has unveiled a substructure of topologically-associating domains (TADs) that are largely conserved in their positions between cell types and are similar in size to RDs8,10. However, TADs can be further sub-stratified into smaller domains, challenging the significance of structures at any particular scale11,12. Moreover, attempts to reconcile TADs and LADs to replication-timing data have not revealed a common, underlying domain structure8,9,13. Here, we localize boundaries of RDs to the early-replicating border of replication-timing transitions and map their positions in 18 human and 13 mouse cell types. We demonstrate that, collectively, RD boundaries share a near one-to-one correlation with TAD boundaries, whereas within a cell type, adjacent TADs that replicate at similar times obscure RD boundaries, largely accounting for the previously reported lack of alignment. Moreover, cell-type specific replication timing of TADs partitions the genome into two large-scale sub-nuclear compartments revealing that replication-timing transitions are indistinguishable from late-replicating regions in chromatin composition and lamina association and accounting for the reduced correlation of replication timing to LADs and heterochromatin. Our results reconcile cell type specific sub-nuclear compartmentalization with developmentally stable chromosome domains and offer a unified model for large-scale chromosome structure and function. PMID:25409831

Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

PubMed

Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

2017-08-01

Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: modelling the clustering and halo occupation distribution of BOSS CMASS galaxies in the Final Data Release

NASA Astrophysics Data System (ADS)

Rodríguez-Torres, Sergio A.; Chuang, Chia-Hsun; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Behroozi, Peter; Hahn, Chang Hoon; Comparat, Johan; Yepes, Gustavo; Montero-Dorta, Antonio D.; Brownstein, Joel R.; Maraston, Claudia; McBride, Cameron K.; Tinker, Jeremy; Gottlöber, Stefan; Favole, Ginevra; Shu, Yiping; Kitaura, Francisco-Shu; Bolton, Adam; Scoccimarro, Román; Samushia, Lado; Schlegel, David; Schneider, Donald P.; Thomas, Daniel

2016-08-01

We present a study of the clustering and halo occupation distribution of Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies in the redshift range 0.43 < z < 0.7 drawn from the Final SDSS-III Data Release. We compare the BOSS results with the predictions of a halo abundance matching (HAM) clustering model that assigns galaxies to dark matter haloes selected from the large BigMultiDark N-body simulation of a flat Λ cold dark matter Planck cosmology. We compare the observational data with the simulated ones on a light cone constructed from 20 subsequent outputs of the simulation. Observational effects such as incompleteness, geometry, veto masks and fibre collisions are included in the model, which reproduces within 1σ errors the observed monopole of the two-point correlation function at all relevant scales: from the smallest scales, 0.5 h-1 Mpc, up to scales beyond the baryon acoustic oscillation feature. This model also agrees remarkably well with the BOSS galaxy power spectrum (up to k ˜ 1 h Mpc-1), and the three-point correlation function. The quadrupole of the correlation function presents some tensions with observations. We discuss possible causes that can explain this disagreement, including target selection effects. Overall, the standard HAM model describes remarkably well the clustering statistics of the CMASS sample. We compare the stellar-to-halo mass relation for the CMASS sample measured using weak lensing in the Canada-France-Hawaii Telescope Stripe 82 Survey with the prediction of our clustering model, and find a good agreement within 1σ. The BigMD-BOSS light cone including properties of BOSS galaxies and halo properties is made publicly available.

Intrinsic alignments of galaxies in the MassiveBlack-II simulation: analysis of two-point statistics

NASA Astrophysics Data System (ADS)

Tenneti, Ananth; Singh, Sukhdeep; Mandelbaum, Rachel; di Matteo, Tiziana; Feng, Yu; Khandai, Nishikanta

2015-04-01

The intrinsic alignment of galaxies with the large-scale density field is an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated ellipticity-direction (ED) and projected shape (wg+) correlation functions for galaxies in the cosmological hydrodynamic MassiveBlack-II simulation. We carefully assess the effects on galaxy shapes, misalignment of the stellar component with the dark matter shape and two-point statistics of iterative weighted (by mass and luminosity) definitions of the (reduced and unreduced) inertia tensor. We find that iterative procedures must be adopted for a reliable measurement of the reduced tensor but that luminosity versus mass weighting has only negligible effects. Both ED and wg+ correlations increase in amplitude with subhalo mass (in the range of 1010-6.0 × 1014 h-1 M⊙), with a weak redshift dependence (from z = 1 to 0.06) at fixed mass. At z ˜ 0.3, we predict a wg+ that is in reasonable agreement with Sloan Digital Sky Survey luminous red galaxy measurements and that decreases in amplitude by a factor of ˜5-18 for galaxies in the Large Synoptic Survey Telescope survey. We also compared the intrinsic alignments of centrals and satellites, with clear detection of satellite radial alignments within their host haloes. Finally, we show that wg+ (using subhaloes as tracers of density) and wδ+ (using dark matter density) predictions from the simulations agree with that of non-linear alignment (NLA) models at scales where the two-halo term dominates in the correlations (and tabulate associated NLA fitting parameters). The one-halo term induces a scale-dependent bias at small scales which is not modelled in the NLA model.

Recovering refractive index correlation function from measurement of tissue scattering phase function (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rogers, Jeremy D.

2016-03-01

Numerous methods have been developed to quantify the light scattering properties of tissue. These properties are of interest in diagnostic and screening applications due to sensitivity to changes in tissue ultrastructure and changes associated with disease such as cancer. Tissue is considered a weak scatterer because that the mean free path is much larger than the correlation length. When this is the case, all scattering properties can be calculated from the refractive index correlation function Bn(r). Direct measurement of Bn(r) is challenging because it requires refractive index measurement at high resolution over a large tissue volume. Instead, a model is usually assumed. One particularly useful model, the Whittle-Matern function includes several realistic function types such as mass fractal and exponential. Optical scattering properties for weakly scattering media can be determined analytically from Bn(r) by applying the Rayleigh-Gans-Debye (RGD) or Born Approximation, and so measured scattering properties are used to fit parameters of the model function. Direct measurement of Bn(r) would provide confirmation that the function is a good representation of tissue or help in identifying the length scale at which changes occur. The RGD approximation relates the scattering phase function to the refractive index correlation function through a Fourier transform. This can be inverted without approximation, so goniometric measurement of the scattering can be converted to Bn(r). However, geometric constraints of the measurement of the phase function, angular resolution, and wavelength result in a band limited measurement of Bn(r). These limits are discussed and example measurements are described.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

Associations between results of post-stroke NDT-Bobath rehabilitation in gait parameters, ADL and hand functions.

PubMed

Mikołajewska, Emilia

2013-01-01

In patients after a stroke there are variable disorders. These patients often need rehabilitation in more than one area beceause of multiple limitations of the ability to perform everyday activities. The aim of the study was to assess correlations - statistical relationships between observed gait parameters, ADL and hand functions - results of rehabilitation of patients after ischaemic stroke according to the NDTBobath method for adults. The investigated group consisted of 60 patients after ischaemic stroke, who participated in the rehabilitation programme. 10 sessions of the NDT-Bobath therapy were provided in 2 weeks (10 days of the therapy). The calculation of correlations was made based on changes of parameters: Bobath Scale (to assess hand functions), Barthel Index (to assess ADL), gait velocity, cadence and stride lenght. Measurements were performed in every patient twice: on admission (before the therapy) and after last session of the therapy to assess rehabilitation effects. The main statistically relevant corellations observed in the study were as follows: in the whole group of patients: poor and moderate (negative) correlation between changes of gait parameters and Bobath Scale and Barthel Index, moderate and severe (negative) correlation between changes of gait parameters and Bobath Scale and Barthel Index in the group of women, correlation between changes in Bobath Scale and Barthel Index in the group of patients with left side of paresis, (negative) correlation between changes of gait parameters and Bobath Scale in group of patients younger than 68 years, moderate, high and very high correlations between changes in gait parameters in groups of women, men, younger than 68 years and older than 68 years. There have been observed statistically significant and favourable changes in the health status of patients, described by gait parameters, changes in hand functions and ADL. Based on the presented correlations there is an assumption that it is hard to achieve simultaneous recovery in all areas: gait parameters, hand functions and ADLs in two weeks of rehabilitation.

Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical Neurons

PubMed Central

Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

2009-01-01

Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of Vm activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the Vm reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the “effective” connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI. PMID:19779556

Network-state modulation of power-law frequency-scaling in visual cortical neurons.

PubMed

El Boustani, Sami; Marre, Olivier; Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

2009-09-01

Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m) activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m) reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI.

Lévy-stable two-pion Bose-Einstein correlations in s NN = 200 GeV Au + Au collisions

DOE PAGES

Adare, A.; Aidala, C.; Ajitanand, N. N.; ...

2018-06-14

Here, we present a detailed measurement of charged two-pion correlation functions in 0–30% centrality √ sNN = 200 GeV Au + Au collisions by the PHENIX experiment at the Relativistic Heavy Ion Collider. The data are well described by Bose-Einstein correlation functions stemming from Lévy-stable source distributions. Using a fine transverse momentum binning, we extract the correlation strength parameter λ, the Lévy index of stability α, and the Lévy length scale parameter R as a function of average transverse mass of the pair m T. We find that the positively and the negatively charged pion pairs yield consistent results, andmore » their correlation functions are represented, within uncertainties, by the same Lévy-stable source functions. The λ(m T) measurements indicate a decrease of the strength of the correlations at low m T. The Lévy length scale parameter R(m T) decreases with increasing m T, following a hydrodynamically predicted type of scaling behavior. The values of the Lévy index of stability α are found to be significantly lower than the Gaussian case of α = 2, but also significantly larger than the conjectured value that may characterize the critical point of a second-order quark-hadron phase transition.« less

Lévy-stable two-pion Bose-Einstein correlations in s NN = 200 GeV Au + Au collisions

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

Adare, A.; Aidala, C.; Ajitanand, N. N.

Here, we present a detailed measurement of charged two-pion correlation functions in 0–30% centrality √ sNN = 200 GeV Au + Au collisions by the PHENIX experiment at the Relativistic Heavy Ion Collider. The data are well described by Bose-Einstein correlation functions stemming from Lévy-stable source distributions. Using a fine transverse momentum binning, we extract the correlation strength parameter λ, the Lévy index of stability α, and the Lévy length scale parameter R as a function of average transverse mass of the pair m T. We find that the positively and the negatively charged pion pairs yield consistent results, andmore » their correlation functions are represented, within uncertainties, by the same Lévy-stable source functions. The λ(m T) measurements indicate a decrease of the strength of the correlations at low m T. The Lévy length scale parameter R(m T) decreases with increasing m T, following a hydrodynamically predicted type of scaling behavior. The values of the Lévy index of stability α are found to be significantly lower than the Gaussian case of α = 2, but also significantly larger than the conjectured value that may characterize the critical point of a second-order quark-hadron phase transition.« less

The impact of Lyman-α radiative transfer on large-scale clustering in the Illustris simulation

NASA Astrophysics Data System (ADS)

Behrens, C.; Byrohl, C.; Saito, S.; Niemeyer, J. C.

2018-06-01

Context. Lyman-α emitters (LAEs) are a promising probe of the large-scale structure at high redshift, z ≳ 2. In particular, the Hobby-Eberly Telescope Dark Energy Experiment aims at observing LAEs at 1.9 < z < 3.5 to measure the baryon acoustic oscillation (BAO) scale and the redshift-space distortion (RSD). However, it has been pointed out that the complicated radiative transfer (RT) of the resonant Lyman-α emission line generates an anisotropic selection bias in the LAE clustering on large scales, s ≳ 10 Mpc. This effect could potentially induce a systematic error in the BAO and RSD measurements. Also, there exists a recent claim to have observational evidence of the effect in the Lyman-α intensity map, albeit statistically insignificant. Aims: We aim at quantifying the impact of the Lyman-α RT on the large-scale galaxy clustering in detail. For this purpose, we study the correlations between the large-scale environment and the ratio of an apparent Lyman-α luminosity to an intrinsic one, which we call the "observed fraction", at 2 < z < 6. Methods: We apply our Lyman-α RT code by post-processing the full Illustris simulations. We simply assume that the intrinsic luminosity of the Lyman-α emission is proportional to the star formation rate of galaxies in Illustris, yielding a sufficiently large sample of LAEs to measure the anisotropic selection bias. Results: We find little correlation between large-scale environment and the observed fraction induced by the RT, and hence a smaller anisotropic selection bias than has previously been claimed. We argue that the anisotropy was overestimated in previous work due to insufficient spatial resolution; it is important to keep the resolution such that it resolves the high-density region down to the scale of the interstellar medium, that is, 1 physical kpc. We also find that the correlation can be further enhanced by assumptions in modeling intrinsic Lyman-α emission.

Phase correlation imaging of unlabeled cell dynamics

NASA Astrophysics Data System (ADS)

Ma, Lihong; Rajshekhar, Gannavarpu; Wang, Ru; Bhaduri, Basanta; Sridharan, Shamira; Mir, Mustafa; Chakraborty, Arindam; Iyer, Rajashekar; Prasanth, Supriya; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel

2016-09-01

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.

Relating drug–protein interaction network with drug side effects

PubMed Central

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

2012-01-01

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

Tunable emergent heterostructures in a prototypical correlated metal

NASA Astrophysics Data System (ADS)

Fobes, D. M.; Zhang, S.; Lin, S.-Z.; Das, Pinaki; Ghimire, N. J.; Bauer, E. D.; Thompson, J. D.; Harriger, L. W.; Ehlers, G.; Podlesnyak, A.; Bewley, R. I.; Sazonov, A.; Hutanu, V.; Ronning, F.; Batista, C. D.; Janoschek, M.

2018-05-01

At the interface between two distinct materials, desirable properties, such as superconductivity, can be greatly enhanced1, or entirely new functionalities may emerge2. Similar to in artificially engineered heterostructures, clean functional interfaces alternatively exist in electronically textured bulk materials. Electronic textures emerge spontaneously due to competing atomic-scale interactions3, the control of which would enable a top-down approach for designing tunable intrinsic heterostructures. This is particularly attractive for correlated electron materials, where spontaneous heterostructures strongly affect the interplay between charge and spin degrees of freedom4. Here we report high-resolution neutron spectroscopy on the prototypical strongly correlated metal CeRhIn5, revealing competition between magnetic frustration and easy-axis anisotropy—a well-established mechanism for generating spontaneous superstructures5. Because the observed easy-axis anisotropy is field-induced and anomalously large, it can be controlled efficiently with small magnetic fields. The resulting field-controlled magnetic superstructure is closely tied to the formation of superconducting6 and electronic nematic textures7 in CeRhIn5, suggesting that in situ tunable heterostructures can be realized in correlated electron materials.

Tunable emergent heterostructures in a prototypical correlated metal

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

Fobes, D. M.; Zhang, S.; Lin, S. -Z.

We report at the interface between two distinct materials, desirable properties, such as superconductivity, can be greatly enhanced1, or entirely new functionalities may emerge. Similar to in artificially engineered heterostructures, clean functional interfaces alternatively exist in electronically textured bulk materials. Electronic textures emerge spontaneously due to competing atomic-scale interactions, the control of which would enable a top-down approach for designing tunable intrinsic heterostructures. This is particularly attractive for correlated electron materials, where spontaneous heterostructures strongly affect the interplay between charge and spin degrees of freedom. Here we report high-resolution neutron spectroscopy on the prototypical strongly correlated metal CeRhIn 5, revealingmore » competition between magnetic frustration and easy-axis anisotropy—a well-established mechanism for generating spontaneous superstructures. Because the observed easy-axis anisotropy is field-induced and anomalously large, it can be controlled efficiently with small magnetic fields. Finally, the resulting field-controlled magnetic superstructure is closely tied to the formation of superconducting and electronic nematic textures in CeRhIn 5, suggesting that in situ tunable heterostructures can be realized in correlated electron materials.« less

Tunable emergent heterostructures in a prototypical correlated metal

DOE PAGES

Fobes, D. M.; Zhang, S.; Lin, S. -Z.; ...

2018-03-26

We report at the interface between two distinct materials, desirable properties, such as superconductivity, can be greatly enhanced1, or entirely new functionalities may emerge. Similar to in artificially engineered heterostructures, clean functional interfaces alternatively exist in electronically textured bulk materials. Electronic textures emerge spontaneously due to competing atomic-scale interactions, the control of which would enable a top-down approach for designing tunable intrinsic heterostructures. This is particularly attractive for correlated electron materials, where spontaneous heterostructures strongly affect the interplay between charge and spin degrees of freedom. Here we report high-resolution neutron spectroscopy on the prototypical strongly correlated metal CeRhIn 5, revealingmore » competition between magnetic frustration and easy-axis anisotropy—a well-established mechanism for generating spontaneous superstructures. Because the observed easy-axis anisotropy is field-induced and anomalously large, it can be controlled efficiently with small magnetic fields. Finally, the resulting field-controlled magnetic superstructure is closely tied to the formation of superconducting and electronic nematic textures in CeRhIn 5, suggesting that in situ tunable heterostructures can be realized in correlated electron materials.« less

Patterns and Variation in Benthic Biodiversity in a Large Marine Ecosystem.

PubMed

Piacenza, Susan E; Barner, Allison K; Benkwitt, Cassandra E; Boersma, Kate S; Cerny-Chipman, Elizabeth B; Ingeman, Kurt E; Kindinger, Tye L; Lee, Jonathan D; Lindsley, Amy J; Reimer, Jessica N; Rowe, Jennifer C; Shen, Chenchen; Thompson, Kevin A; Thurman, Lindsey L; Heppell, Selina S

2015-01-01

While there is a persistent inverse relationship between latitude and species diversity across many taxa and ecosystems, deviations from this norm offer an opportunity to understand the conditions that contribute to large-scale diversity patterns. Marine systems, in particular, provide such an opportunity, as marine diversity does not always follow a strict latitudinal gradient, perhaps because several hypothesized drivers of the latitudinal diversity gradient are uncorrelated in marine systems. We used a large scale public monitoring dataset collected over an eight year period to examine benthic marine faunal biodiversity patterns for the continental shelf (55-183 m depth) and slope habitats (184-1280 m depth) off the US West Coast (47°20'N-32°40'N). We specifically asked whether marine biodiversity followed a strict latitudinal gradient, and if these latitudinal patterns varied across depth, in different benthic substrates, and over ecological time scales. Further, we subdivided our study area into three smaller regions to test whether coast-wide patterns of biodiversity held at regional scales, where local oceanographic processes tend to influence community structure and function. Overall, we found complex patterns of biodiversity on both the coast-wide and regional scales that differed by taxonomic group. Importantly, marine biodiversity was not always highest at low latitudes. We found that latitude, depth, substrate, and year were all important descriptors of fish and invertebrate diversity. Invertebrate richness and taxonomic diversity were highest at high latitudes and in deeper waters. Fish richness also increased with latitude, but exhibited a hump-shaped relationship with depth, increasing with depth up to the continental shelf break, ~200 m depth, and then decreasing in deeper waters. We found relationships between fish taxonomic and functional diversity and latitude, depth, substrate, and time at the regional scale, but not at the coast-wide scale, suggesting that coast-wide patterns can obscure important correlates at smaller scales. Our study provides insight into complex diversity patterns of the deep water soft substrate benthic ecosystems off the US West Coast.

Polarization phenomena in quantum chromodynamics

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

Brodsky, S.J.

1994-12-01

The author discusses a number of interrelated hadronic spin effects which test fundamental features of perturbative and nonperturbative QCD. For example, the anomalous magnetic moment of the proton and the axial coupling g{sub A} on the nucleon are shown to be related to each other for fixed proton radius, independent of the form of the underlying three-quark relativistic quark wavefunction. The renormalization scale and scheme ambiguities for the radiative corrections to the Bjorken sum rule for the polarized structure functions can be eliminated by using commensurate scale relations with other observables. Other examples include (a) new constraints on the shapemore » and normalization of the polarized quark and gluon structure functions of the proton at large and small x{sub bj}; (b) consequences of the principle of hadron retention in high x{sub F} inclusive reactions; (c) applications of hadron helicity conservation to high momentum transfer exclusive reactions; and (d) the dependence of nuclear structure functions and shadowing on virtual photon polarization. The author also discusses the implications of a number of measurements which are in striking conflict with leading-twist perturbative QCD predictions, such as the extraordinarily large spin correlation A{sub NN} observed in large angle proton-proton scattering, the anomalously large {rho}{pi} branching ratio of the J/{psi}, and the rapidly changing polarization dependence of both J/{psi} and continuum lepton pair hadroproduction observed at large x{sub F}. The azimuthal angular dependence of the Drell-Yan process is shown to be highly sensitive to the projectile distribution amplitude, the fundamental valence light-cone wavefunction of the hadron.« less

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.

Instanton dominance over $$a_s$$ at low momenta from lattice QCD simulations at $$N_f=0$$, $$N_f=2+1$$ and $$N_f=2+1+1$$

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

Athenodorou, Andreas; Boucaud, Philippe; de Soto, Feliciano

We report on an instanton-based analysis of the gluon Green functions in the Landau gauge for low momenta; in particular we use lattice results for αs in the symmetric momentum subtraction scheme (MOM) for large-volume lattice simulations. We have exploited quenched gauge field configurations, Nf = 0, with both Wilson and tree-level Symanzik improved actions, and unquenched ones with Nf = 2 + 1 and Nf = 2 + 1 + 1 dynamical flavors (domain wall and twisted-mass fermions, respectively).We show that the dominance of instanton correlations on the low-momenta gluon Green functions can be applied to the determination ofmore » phenomenological parameters of the instanton liquid and, eventually, to a determination of the lattice spacing.We furthermore apply the Gradient Flow to remove short-distance fluctuations. The Gradient Flow gets rid of the QCD scale, ΛQCD, and reveals that the instanton prediction extents to large momenta. For those gauge field configurations free of quantum fluctuations, the direct study of topological charge density shows the appearance of large-scale lumps that can be identified as instantons, giving access to a direct study of the instanton density and size distribution that is compatible with those extracted from the analysis of the Green functions.« less

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

PubMed

Carbonell, F; Bellec, P; Shmuel, A

2014-02-01

The effect of regressing out the global average signal (GAS) in resting state fMRI data has become a concern for interpreting functional connectivity analyses. It is not clear whether the reported anti-correlations between the Default Mode and the Dorsal Attention Networks are intrinsic to the brain, or are artificially created by regressing out the GAS. Here we introduce a concept, Impact of the Global Average on Functional Connectivity (IGAFC), for quantifying the sensitivity of seed-based correlation analyses to the regression of the GAS. This voxel-wise IGAFC index is defined as the product of two correlation coefficients: the correlation between the GAS and the fMRI time course of a voxel, times the correlation between the GAS and the seed time course. This definition enables the calculation of a threshold at which the impact of regressing-out the GAS would be large enough to introduce spurious negative correlations. It also yields a post-hoc impact correction procedure via thresholding, which eliminates spurious correlations introduced by regressing out the GAS. In addition, we introduce an Artificial Negative Correlation Index (ANCI), defined as the absolute difference between the IGAFC index and the impact threshold. The ANCI allows a graded confidence scale for ranking voxels according to their likelihood of showing artificial correlations. By applying this method, we observed regions in the Default Mode and Dorsal Attention Networks that were anti-correlated. These findings confirm that the previously reported negative correlations between the Dorsal Attention and Default Mode Networks are intrinsic to the brain and not the result of statistical manipulations. Our proposed quantification of the impact that a confound may have on functional connectivity can be generalized to global effect estimators other than the GAS. It can be readily applied to other confounds, such as systemic physiological or head movement interferences, in order to quantify their impact on functional connectivity in the resting state. © 2013.

Awareness of disease in dementia: factor structure of the assessment scale of psychosocial impact of the diagnosis of dementia.

PubMed

Dourado, Marcia C N; Mograbi, Daniel C; Santos, Raquel L; Sousa, Maria Fernanda B; Nogueira, Marcela L; Belfort, Tatiana; Landeira-Fernandez, Jesus; Laks, Jerson

2014-01-01

Despite the growing understanding of the conceptual complexity of awareness, there currently exists no instrument for assessing different domains of awareness in dementia. In the current study, the psychometric properties of a multidimensional awareness scale, the Assessment Scale of Psychosocial Impact of the Diagnosis of Dementia (ASPIDD), are explored in a sample of 201 people with dementia and their family caregivers. Cronbach's alpha was high (α = 0.87), indicating excellent internal consistency. The mean of corrected item-total correlation coefficients was moderate. ASPIDD presented a four-factor solution with a well-defined structure: awareness of activities of daily living, cognitive functioning and health condition, emotional state, and social functioning and relationships. Functional disability was positively correlated with total ASPIDD, unawareness of activities of daily living, cognitive functioning, and with emotional state. Caregiver burden was correlated with total ASPIDD scores and unawareness of cognitive functioning. The results suggest that ASPIDD is indeed a multidimensional scale, providing a reliable measure of awareness of disease in dementia. Further studies should explore the risk factors associated with different dimensions of awareness in dementia.

Visual impairment, visual functioning, and quality of life assessments in patients with glaucoma.

PubMed Central

Parrish, R K

1996-01-01

BACKGROUND/PURPOSE: To determine the relation between visual impairment, visual functioning, and the global quality of life in patients with glaucoma. METHODS: Visual impairment, defined with the American Medical Association Guides to the Evaluation of Permanent Impairment; visual functioning, measured with the VF-14 and the Field Test Version of the National Eye Institute-Visual Functioning Questionnaire (NEI-VFQ); and the global quality of life, assessed with the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36), were determined in 147 consecutive patients with glaucoma. RESULTS: None of the SF-36 domains demonstrated more than a weak correlation with visual impairment. The VF-14 scores were moderately correlated with visual impairment. Of the twelve NEI-VFQ scales, distance activities and vision specific dependency were moderately correlated with visual impairment. Of the twelve NEI-VFQ scales, distance activities and vision specific dependency were moderately correlated with visual field impairment; vision specific social functioning, near activities, vision specific role difficulties, general vision, vision specific mental health, color vision, and driving were modestly correlated; visual pain was weakly correlated; and two were not significantly correlated. Correcting for visual actuity weakened the strength of the correlation coefficients. CONCLUSIONS: The SF-36 is unlikely to be useful in determining visual impairment in patients with glaucoma. Based on the moderate correlation between visual field impairment and the VF-14 score, this questionnaire may be generalizable to patients with glaucoma. Several of the NEI-VFQ scales correlate with visual field impairment scores in patients with a wide range of glaucomatous damage. PMID:8981717

Emergence of microstructure and oxygen diffusion in yttrium-stabilized cubic zirconia

NASA Astrophysics Data System (ADS)

Yang, C.; Trachenko, K.; Hull, S.; Todorov, I. T.; Dove, M. T.

2018-05-01

Large-scale molecular dynamics simulations have been used to study the microstructure in Y-doped ZrO2. From simulations performed as a function of composition the dependence of microstructure on composition is quantified, showing how it is formed from two coexisting phases, and the transformation to the stabilized cubic form is observed at higher concentrations of yttrium and higher temperatures. The effect of composition and temperature on oxygen diffusion is also studied, showing strong correlations between microstructure and diffusion.

The Center for Astrophysics Redshift Survey - Recent results

NASA Technical Reports Server (NTRS)

Geller, Margaret J.; Huchra, John P.

1989-01-01

Six strips of the CfA redshift survey extension are now complete. The data continue to support a picture in which galaxies are on thin sheets which nearly surround vast low-density voids. The largest structures are comparable with the extent of the survey. Voids like the one in Bootes are a common feature of the large-scale distribution of galaxies. The issue of fair samples of the galaxy distribution is discussed, examining statistical measures of the galaxy distribution including the two-point correlation functions.

Development and validation of a measure of pediatric oral health-related quality of life: the POQL

PubMed Central

Huntington, Noelle L; Spetter, Dante; Jones, Judith A.; Rich, Sharon E.; Garcia, Raul I.; Spiro, Avron

2011-01-01

Objective To develop a brief measure of oral health-related quality of life in children and demonstrate its reliability and validity in a diverse population. Methods We administered the initial 20-item POQL to children (Child Self-Report) and parents (Parent Report on Child) from diverse populations in both school-based and clinic-based settings. Clinical oral health status was measured on a subset of children. We used factor analysis to determine the underlying scales and then reduced the measure to 10 items based on several considerations. Multitrait analysis on the resulting 10-item POQL was used to reaffirm the discrimination of scales and assess the measure’s internal consistency and interscale correlations. We established discriminant and convergent validity with clinical status, perceived oral health and responses on the PedsQL and determined sensitivity to change with children undergoing ECC surgical repair. Results Factor analysis returned a four-scale solution for the initial items – Physical Functioning, Role Functioning, Social Functioning and Emotional Functioning. The reduced items represented the same four scales – two each on Physical and Role and three each on Social and Emotional. Good reliability and validity were shown for the POQL as a whole and for each of the scales. Conclusions The POQL is a valid and reliable measure of oral health-related quality of life for use in pre-school and school-aged children, with high utility for both clinical assessments and large-scale population studies. PMID:21972458

Development and validation of a measure of pediatric oral health-related quality of life: the POQL.

PubMed

Huntington, Noelle L; Spetter, Dante; Jones, Judith A; Rich, Sharron E; Garcia, Raul I; Spiro, Avron

2011-01-01

To develop a brief measure of oral health-related quality of life (OHQL) in children and demonstrate its reliability and validity in a diverse population. We administered the initial 20-item Pediatric Oral Health-Related Quality of Life (POQL) to children (Child Self-Report) and parents (Parent Report on Child) from diverse populations in both school-based and clinic-based settings. Clinical oral health status was measured on a subset of children. We used factor analysis to determine the underlying scales and then reduced the measure to 10 items based on several considerations. Multitrait analysis on the resulting 10-item POQL was used to reaffirm the discrimination of scales and assess the measure's internal consistency and interscale correlations. We established discriminant and convergent validity with clinical status, perceived oral health and responses on the PedsQL, and determined sensitivity to change with children undergoing ECC surgical repair. Factor analysis returned a four-scale solution for the initial items--Physical Functioning, Role Functioning, Social Functioning, and Emotional Functioning. The reduced items represented the same four scales--two each on Physical and Role and three each on Social and Emotional. Good reliability and validity were shown for the POQL as a whole and for each of the scales. The POQL is a valid and reliable measure of OHQL for use in preschool and school-aged children, with high utility for both clinical assessments and large-scale population studies.

Rating scales for dystonia in cerebral palsy: reliability and validity.

PubMed

Monbaliu, E; Ortibus, E; Roelens, F; Desloovere, K; Deklerck, J; Prinzie, P; de Cock, P; Feys, H

2010-06-01

This study investigated the reliability and validity of the Barry-Albright Dystonia Scale (BADS), the Burke-Fahn-Marsden Movement Scale (BFMMS), and the Unified Dystonia Rating Scale (UDRS) in patients with bilateral dystonic cerebral palsy (CP). Three raters independently scored videotapes of 10 patients (five males, five females; mean age 13 y 3 mo, SD 5 y 2 mo, range 5-22 y). One patient each was classified at levels I-IV in the Gross Motor Function Classification System and six patients were classified at level V. Reliability was measured by (1) intraclass correlation coefficient (ICC) for interrater reliability, (2) standard error of measurement (SEM) and smallest detectable difference (SDD), and (3) Cronbach's alpha for internal consistency. Validity was assessed by Pearson's correlations among the three scales used and by content analysis. Moderate to good interrater reliability was found for total scores of the three scales (ICC: BADS=0.87; BFMMS=0.86; UDRS=0.79). However, many subitems showed low reliability, in particular for the UDRS. SEM and SDD were respectively 6.36% and 17.72% for the BADS, 9.88% and 27.39% for the BFMMS, and 8.89% and 24.63% for the UDRS. High internal consistency was found. Pearson's correlations were high. Content validity showed insufficient accordance with the new CP definition and classification. Our results support the internal consistency and concurrent validity of the scales; however, taking into consideration the limitations in reliability, including the large SDD values and the content validity, further research on methods of assessment of dystonia is warranted.

Lattice QCD Thermodynamics and RHIC-BES Particle Production within Generic Nonextensive Statistics

NASA Astrophysics Data System (ADS)

Tawfik, Abdel Nasser

2018-05-01

The current status of implementing Tsallis (nonextensive) statistics on high-energy physics is briefly reviewed. The remarkably low freezeout-temperature, which apparently fails to reproduce the firstprinciple lattice QCD thermodynamics and the measured particle ratios, etc. is discussed. The present work suggests a novel interpretation for the so-called " Tsallis-temperature". It is proposed that the low Tsallis-temperature is due to incomplete implementation of Tsallis algebra though exponential and logarithmic functions to the high-energy particle-production. Substituting Tsallis algebra into grand-canonical partition-function of the hadron resonance gas model seems not assuring full incorporation of nonextensivity or correlations in that model. The statistics describing the phase-space volume, the number of states and the possible changes in the elementary cells should be rather modified due to interacting correlated subsystems, of which the phase-space is consisting. Alternatively, two asymptotic properties, each is associated with a scaling function, are utilized to classify a generalized entropy for such a system with large ensemble (produced particles) and strong correlations. Both scaling exponents define equivalence classes for all interacting and noninteracting systems and unambiguously characterize any statistical system in its thermodynamic limit. We conclude that the nature of lattice QCD simulations is apparently extensive and accordingly the Boltzmann-Gibbs statistics is fully fulfilled. Furthermore, we found that the ratios of various particle yields at extreme high and extreme low energies of RHIC-BES is likely nonextensive but not necessarily of Tsallis type.

Selectivity by host plants affects the distribution of arbuscular mycorrhizal fungi: evidence from ITS rDNA sequence metadata.

PubMed

Yang, Haishui; Zang, Yanyan; Yuan, Yongge; Tang, Jianjun; Chen, Xin

2012-04-12

Arbuscular mycorrhizal fungi (AMF) can form obligate symbioses with the vast majority of land plants, and AMF distribution patterns have received increasing attention from researchers. At the local scale, the distribution of AMF is well documented. Studies at large scales, however, are limited because intensive sampling is difficult. Here, we used ITS rDNA sequence metadata obtained from public databases to study the distribution of AMF at continental and global scales. We also used these sequence metadata to investigate whether host plant is the main factor that affects the distribution of AMF at large scales. We defined 305 ITS virtual taxa (ITS-VTs) among all sequences of the Glomeromycota by using a comprehensive maximum likelihood phylogenetic analysis. Each host taxonomic order averaged about 53% specific ITS-VTs, and approximately 60% of the ITS-VTs were host specific. Those ITS-VTs with wide host range showed wide geographic distribution. Most ITS-VTs occurred in only one type of host functional group. The distributions of most ITS-VTs were limited across ecosystem, across continent, across biogeographical realm, and across climatic zone. Non-metric multidimensional scaling analysis (NMDS) showed that AMF community composition differed among functional groups of hosts, and among ecosystem, continent, biogeographical realm, and climatic zone. The Mantel test showed that AMF community composition was significantly correlated with plant community composition among ecosystem, among continent, among biogeographical realm, and among climatic zone. The structural equation modeling (SEM) showed that the effects of ecosystem, continent, biogeographical realm, and climatic zone were mainly indirect on AMF distribution, but plant had strongly direct effects on AMF. The distribution of AMF as indicated by ITS rDNA sequences showed a pattern of high endemism at large scales. This pattern indicates high specificity of AMF for host at different scales (plant taxonomic order and functional group) and high selectivity from host plants for AMF. The effects of ecosystemic, biogeographical, continental and climatic factors on AMF distribution might be mediated by host plants.

Development and validation of the Vellore Occupational Therapy Evaluation Scale to assess functioning in people with mental illness.

PubMed

Samuel, Reema; Russell, Paul Ss; Paraseth, Tapan Kumar; Ernest, Sharmila; Jacob, K S

2016-08-26

Available occupational therapy assessment scales focus on specific areas of functioning. There is a need for comprehensive evaluation of diverse aspects of functioning in people with mental illness. To develop a comprehensive assessment scale to evaluate diverse aspects of functioning among people with mental illness and to assess its validity and reliability. Available instruments, which evaluate diverse aspects of functioning in people with mental illness, were retrieved. Relevant items, which evaluate specific functions, were selected by a committee of mental health experts and combined to form a comprehensive instrument. Face and content validity and feasibility were assessed and the new instrument was piloted among 60 patients with mental illness. The final version of the instrument was employed in 151 consecutive clients, between 18 and 60 years of age, who were also assessed using Global Assessment of Functioning (GAF), Occupational Therapy Task Observation Scale (OTTOS), Social Functioning Questionnaire (SFQ), Rosenberg Self Esteem Scale (RSES) and Pai and Kapur Family Burden Interview Schedule (FBIS) by two therapists. The inter-rater reliability and test-retest reliability of the new instrument (Vellore Occupational Therapy Evaluation Scale (VOTES)) were also evaluated. The new scale had good internal consistency (Cronbach's alpha = .817), inter-rater reliability .928 (.877-.958) and test-retest reliability .928 (.868-.961). The correlation between the general behaviour domain (Pearson's Correlation Coefficient [PCC] = -.763, p = .000), task behaviour (PCC = -.829, p = .000), social skills (PCC = -.351, p = .000), intrapersonal skills (PCC = -.208, p = .010), instrumental activities of daily living (IADL) (PCC = -.329, p = .038) and leisure activities (PCC = -.433, p = .005) scores of VOTES with the corresponding domains in the scales used for comparison was statistically significant. The correlation between the total score of VOTES and the total scores of OTTOS, SFQ and RSES was also statistically significant suggesting convergent validity. The correlation between the total score of VOTES with the total score of FBI is not statistically significant, implying good divergent validity. VOTES seems to be a promising tool to assess overall functioning of people with mental illness. © The Author(s) 2016.

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

Functional decline in Huntington's disease.

PubMed

Feigin, A; Kieburtz, K; Bordwell, K; Como, P; Steinberg, K; Sotack, J; Zimmerman, C; Hickey, C; Orme, C; Shoulson, I

1995-03-01

We prospectively evaluated 129 patients with manifest Huntington's disease (HD) to determine the rate of illness progression and the clinical features that correlate with functional decline. A single examiner evaluated each patient using the HD Functional Capacity Scale. Standardized motor performance was also assessed in 94 of the patients (73%) using the HD Rating Scale. Total Functional Capacity declined at a rate of 0.63 +/- 0.75 U per year. As functional capacity worsened, chorea lessened, and dystonia intensified. There was no correlation between rate of functional decline and age at onset of HD, body weight, gender of affected parent, or history of neuroleptic use.

Studies on combined model based on functional objectives of large scale complex engineering

NASA Astrophysics Data System (ADS)

Yuting, Wang; Jingchun, Feng; Jiabao, Sun

2018-03-01

As various functions were included in large scale complex engineering, and each function would be conducted with completion of one or more projects, combined projects affecting their functions should be located. Based on the types of project portfolio, the relationship of projects and their functional objectives were analyzed. On that premise, portfolio projects-technics based on their functional objectives were introduced, then we studied and raised the principles of portfolio projects-technics based on the functional objectives of projects. In addition, The processes of combined projects were also constructed. With the help of portfolio projects-technics based on the functional objectives of projects, our research findings laid a good foundation for management of large scale complex engineering portfolio management.

Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data

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

Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor

The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. We present a comprehensive search for correlations between high-energy (∼> 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (∼> 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directions andmore » unresolved Fermi -LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. No significant correlation is found in any of the analyses performed, except a weak (∼< 2σ) hint of signal with the correlation function method on scales ∼ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less

Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data

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

Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor

The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. Here, we present a comprehensive search for correlations between high-energy (≳ 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (≳ 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directionsmore » and unresolved Fermi-LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. There was no significant correlation is found in any of the analyses performed, except a weak (≲ 2σ) hint of signal with the correlation function method on scales ~ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less

Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data

DOE PAGES

Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor; ...

2016-12-13

The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. Here, we present a comprehensive search for correlations between high-energy (≳ 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (≳ 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directionsmore » and unresolved Fermi-LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. There was no significant correlation is found in any of the analyses performed, except a weak (≲ 2σ) hint of signal with the correlation function method on scales ~ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less

A simple phenomenological model for grain clustering in turbulence

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-01-01

We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.

Compactified cosmological simulations of the infinite universe

NASA Astrophysics Data System (ADS)

Rácz, Gábor; Szapudi, István; Csabai, István; Dobos, László

2018-06-01

We present a novel N-body simulation method that compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to follow the evolution of the large-scale structure. Our approach eliminates the need for periodic boundary conditions, a mere numerical convenience which is not supported by observation and which modifies the law of force on large scales in an unrealistic fashion. We demonstrate that our method outclasses standard simulations executed on workstation-scale hardware in dynamic range, it is balanced in following a comparable number of high and low k modes and, its fundamental geometry and topology match observations. Our approach is also capable of simulating an expanding, infinite universe in static coordinates with Newtonian dynamics. The price of these achievements is that most of the simulated volume has smoothly varying mass and spatial resolution, an approximation that carries different systematics than periodic simulations. Our initial implementation of the method is called StePS which stands for Stereographically projected cosmological simulations. It uses stereographic projection for space compactification and naive O(N^2) force calculation which is nevertheless faster to arrive at a correlation function of the same quality than any standard (tree or P3M) algorithm with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence our code can function as a high-speed prediction tool for modern large-scale surveys. To learn about the limits of the respective methods, we compare StePS with GADGET-2 running matching initial conditions.

Cluster galaxy dynamics and the effects of large-scale environment

NASA Astrophysics Data System (ADS)

White, Martin; Cohn, J. D.; Smit, Renske

2010-11-01

Advances in observational capabilities have ushered in a new era of multi-wavelength, multi-physics probes of galaxy clusters and ambitious surveys are compiling large samples of cluster candidates selected in different ways. We use a high-resolution N-body simulation to study how the influence of large-scale structure in and around clusters causes correlated signals in different physical probes and discuss some implications this has for multi-physics probes of clusters (e.g. richness, lensing, Compton distortion and velocity dispersion). We pay particular attention to velocity dispersions, matching galaxies to subhaloes which are explicitly tracked in the simulation. We find that not only do haloes persist as subhaloes when they fall into a larger host, but groups of subhaloes retain their identity for long periods within larger host haloes. The highly anisotropic nature of infall into massive clusters, and their triaxiality, translates into an anisotropic velocity ellipsoid: line-of-sight galaxy velocity dispersions for any individual halo show large variance depending on viewing angle. The orientation of the velocity ellipsoid is correlated with the large-scale structure, and thus velocity outliers correlate with outliers caused by projection in other probes. We quantify this orientation uncertainty and give illustrative examples. Such a large variance suggests that velocity dispersion estimators will work better in an ensemble sense than for any individual cluster, which may inform strategies for obtaining redshifts of cluster members. We similarly find that the ability of substructure indicators to find kinematic substructures is highly viewing angle dependent. While groups of subhaloes which merge with a larger host halo can retain their identity for many Gyr, they are only sporadically picked up by substructure indicators. We discuss the effects of correlated scatter on scaling relations estimated through stacking, both analytically and in the simulations, showing that the strong correlation of measures with mass and the large scatter in mass at fixed observable mitigate line-of-sight projections.

Nonlinear evolution of baryon acoustic oscillations

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

Crocce, Martin; Institut de Ciencies de l'Espai, IEEC-CSIC, Campus UAB, Facultat de Ciencies, Torre C5 par-2, Barcelona 08193; Scoccimarro, Roman

2008-01-15

We study the nonlinear evolution of baryon acoustic oscillations in the dark matter power spectrum and the correlation function using renormalized perturbation theory. In a previous paper we showed that renormalized perturbation theory successfully predicts the damping of acoustic oscillations; here we extend our calculation to the enhancement of power due to mode coupling. We show that mode coupling generates additional oscillations that are out of phase with those in the linear spectrum, leading to shifts in the scales of oscillation nodes defined with respect to a smooth spectrum. When Fourier transformed, these out-of-phase oscillations induce percent-level shifts in themore » acoustic peak of the two-point correlation function. We present predictions for these shifts as a function of redshift; these should be considered as a robust lower limit to the more realistic case that includes, in addition, redshift distortions and galaxy bias. We show that these nonlinear effects occur at very large scales, leading to a breakdown of linear theory at scales much larger than commonly thought. We discuss why virialized halo profiles are not responsible for these effects, which can be understood from basic physics of gravitational instability. Our results are in excellent agreement with numerical simulations, and can be used as a starting point for modeling baryon acoustic oscillations in future observations. To meet this end, we suggest a simple physically motivated model to correct for the shifts caused by mode coupling.« less

von Kármán-Howarth equation for three-dimensional two-fluid plasmas.

PubMed

Andrés, N; Mininni, P D; Dmitruk, P; Gómez, D O

2016-06-01

We derive the von Kármán-Howarth equation for a full three-dimensional incompressible two-fluid plasma. In the long-time limit and for very large Reynolds numbers we obtain the equivalent of the hydrodynamic "four-fifths" law. This exact law predicts the scaling of the third-order two-point correlation functions, and puts a strong constraint on the plasma turbulent dynamics. Finally, we derive a simple expression for the 4/5 law in terms of third-order structure functions, which is appropriate for comparison with in situ measurements in the solar wind at different spatial ranges.

Transverse momentum dependent (TMD) parton distribution functions: Status and prospects*

DOE PAGES

Angeles-Martinez, R.; Bacchetta, A.; Balitsky, Ian I.; ...

2015-01-01

In this study, we review transverse momentum dependent (TMD) parton distribution functions, their application to topical issues in high-energy physics phenomenology, and their theoretical connections with QCD resummation, evolution and factorization theorems. We illustrate the use of TMDs via examples of multi-scale problems in hadronic collisions. These include transverse momentum q T spectra of Higgs and vector bosons for low q T, and azimuthal correlations in the production of multiple jets associated with heavy bosons at large jet masses. We discuss computational tools for TMDs, and present the application of a new tool, TMD LIB, to parton density fits andmore » parameterizations.« less

LES, DNS, and RANS for the Analysis of High-Speed Turbulent Reacting Flows

NASA Technical Reports Server (NTRS)

Colucci, P. J.; Jaberi, F. A.; Givi, P.

1996-01-01

A filtered density function (FDF) method suitable for chemically reactive flows is developed in the context of large eddy simulation. The advantage of the FDF methodology is its inherent ability to resolve subgrid scales (SGS) scalar correlations that otherwise have to be modeled. Because of the lack of robust models to accurately predict these correlations in turbulent reactive flows, simulations involving turbulent combustion are often met with a degree of skepticism. The FDF methodology avoids the closure problem associated with these terms and treats the reaction in an exact manner. The scalar FDF approach is particularly attractive since it can be coupled with existing hydrodynamic computational fluid dynamics (CFD) codes.

Major depressive disorder: gender differences in symptoms, life quality, and sexual function.

PubMed

Lai, Chien-Han

2011-02-01

To investigate the gender differences of symptoms, life quality, functional impairment, and sexual function of patients with moderately severe major depressive disorder (MDD). One hundred forty-six outpatients with MDD were enrolled into this study with specific selection criteria (male, 57; female, 89; mean ± SD age, 38.30 ± 11.69 years). All the patients self-rated the Quick Inventory of Depressive Symptomatology--Self-Report (QIDS-SR16) and the Integral Inventory for Depression (IID) for the assessment of symptoms assessment as well as the EuroQol life quality scale (EQ5D) was for the subjective life quality, the Sheehan disability scale was for the functional impairments, and the Arizona Sexual Experience Scale was for sexual function evaluation. All data were analyzed to estimate correlation and gender difference. Female patients had higher scores of the QIDS-SR16, IID, and Arizona Sexual Experience scales. Significant gender differences of sadness, sleep, appetite, calmness, painful symptoms, and sexual functioning were observed. The female-specific sexual dysfunctions included lower sexual drive, lower sexual arousal, lower horny feelings, lower orgasms, and lower satisfaction of orgasm. The MDD episodes were related to the EuroQol life quality scale and the SDS. Interepisode years were associated with the IID. The Sheehan disability scale was correlated with QIDS-SR16 with statistical significance. Patients with MDD showed a correlation between symptoms and functional impairment. Female patients might be more sexually impaired, more vegetative, more depressed, and experiencing more sadness and physical pain.

Convergent and divergent intranetwork and internetwork connectivity patterns in patients with remitted late-life depression and amnestic mild cognitive impairment.

PubMed

Chen, Jiu; Shu, Hao; Wang, Zan; Zhan, Yafeng; Liu, Duan; Liao, Wenxiang; Xu, Lin; Liu, Yong; Zhang, Zhijun

2016-10-01

Both remitted late-life depression (rLLD) and amnesiac mild cognitive impairment (aMCI) alter brain functions in specific regions of the brain. They are also disconnection syndromes that are associated with a high risk of developing Alzheimer's disease (AD). Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) was performed to define the shared and distinct aberrant patterns in intranetwork and internetwork connectivity between rLLD and aMCI and to determine how knowledge of these differences might contribute to our essential understanding of the altered sequences involved in functional systems both inside and outside of resting-state networks. We used rs-fcMRI to investigate in five functionally well-defined brain networks in two large cohorts of subjects at high risk for AD (55 rLLD and 87 aMCI) and 114 healthy controls (HC). A reduced degree of functional connectivity was observed in the bilateral inferior temporal cortex and supplemental motor area, and reduced correlations were observed within the sensory-motor network (SMN) and in the default mode network (DMN)-control network (CON) pair in the rLLD group than the HC group. The aMCI group showed only focal functional changes in regions of interest pairs, a trend toward increased correlations within the salience network and SMN, and a trend toward a reduced correlation in the DMN-CON pair. Furthermore, the rLLD group exhibited more severely altered functional connectivity than the aMCI group. Interestingly, these altered connectivities were associated with specific multi-domain cognitive and behavioral functions in both rLLD and aMCI. The degree of functional connectivity in the right primary auditory areas was negatively correlated with Hamilton Depression Scale scores in rLLD. Notably, altered connectivity between the right middle temporal cortex and the posterior cerebellum was negatively correlated with Mattis Dementia Rating Scale scores in both rLLD and aMCI. These results demonstrate that rLLD and aMCI may share convergent and divergent aberrant intranetwork and internetwork connectivity patterns as a potential continuous spectrum of the same disease. They further suggest that dysfunctions in the right specific temporal-cerebellum neural circuit may contribute to the similarities observed in rLLD and aMCI conversion to AD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cosmological measurements with general relativistic galaxy correlations

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

Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxymore » bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.« less

Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity

PubMed Central

Wang, Lubin; Zhai, Tianye; Zou, Feng; Ye, Enmao; Jin, Xiao; Li, Wuju; Qi, Jianlin; Yang, Zheng

2015-01-01

Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation. PMID:26218521

Relationship Between Resilience, Adjustment, and Psychological Functioning After Traumatic Brain Injury: A Preliminary Report.

PubMed

Lukow, Herman R; Godwin, Emilie E; Marwitz, Jennifer H; Mills, Ana; Hsu, Nancy H; Kreutzer, Jeffrey S

2015-01-01

To examine the relationship between resilience, psychological distress, adjustment, and community participation after traumatic brain injury (TBI). Large university health system. Adult survivors of mild to severe TBI (N = 96). Descriptive, preliminary. The Connor-Davidson Resilience Scale (10-item version) was used to assess resilience, the Brief Symptom Inventory (BSI-18) was used to characterize psychological distress, and the Mayo-Portland Adaptability Index (MPAI-4) was used to measure ability, adjustment, and participation. Resilience scores were substantially lower than those of the general population. Significant relationships were found between resilience, psychological distress, and adjustment. Partial correlations (adjusting for the other MPAI-4 indices) showed significant correlation (P < .05) between MPAI-4 Adjustment and resilience. Partial correlations (adjusting for the other BSI-18 scales) also showed significance for Depression (P < .01) and resilience. Resilience scores differed significantly (P < .001) between individuals meeting BSI-18 caseness criteria for psychological distress (n = 55) and those not meeting criteria (n = 41). Individuals with TBI are at risk for low resilience, which was found to correlate with psychological distress and psychosocial maladjustment. Developing interventions to strengthen resilience skills has the potential to improve postinjury psychosocial adjustment, an important area for future research.

Dominant modes of variability in large-scale Birkeland currents

NASA Astrophysics Data System (ADS)

Cousins, E. D. P.; Matsuo, Tomoko; Richmond, A. D.; Anderson, B. J.

2015-08-01

Properties of variability in large-scale Birkeland currents are investigated through empirical orthogonal function (EOF) analysis of 1 week of data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Mean distributions and dominant modes of variability are identified for both the Northern and Southern Hemispheres. Differences in the results from the two hemispheres are observed, which are attributed to seasonal differences in conductivity (the study period occurred near solstice). A universal mean and set of dominant modes of variability are obtained through combining the hemispheric results, and it is found that the mean and first three modes of variability (EOFs) account for 38% of the total observed squared magnetic perturbations (δB2) from both hemispheres. The mean distribution represents a standard Region 1/Region 2 (R1/R2) morphology of currents and EOF 1 captures the strengthening/weakening of the average distribution and is well correlated with the north-south component of the interplanetary magnetic field (IMF). EOF 2 captures a mixture of effects including the expansion/contraction and rotation of the (R1/R2) currents; this mode correlates only weakly with possible external driving parameters. EOF 3 captures changes in the morphology of the currents in the dayside cusp region and is well correlated with the dawn-dusk component of the IMF. The higher-order EOFs capture more complex, smaller-scale variations in the Birkeland currents and appear generally uncorrelated with external driving parameters. The results of the EOF analysis described here are used for describing error covariance in a data assimilation procedure utilizing AMPERE data, as described in a companion paper.

Quantum spin chains with multiple dynamics

NASA Astrophysics Data System (ADS)

Chen, Xiao; Fradkin, Eduardo; Witczak-Krempa, William

2017-11-01

Many-body systems with multiple emergent time scales arise in various contexts, including classical critical systems, correlated quantum materials, and ultracold atoms. We investigate such nontrivial quantum dynamics in a different setting: a spin-1 bilinear-biquadratic chain. It has a solvable entangled ground state, but a gapless excitation spectrum that is poorly understood. By using large-scale density matrix renormalization group simulations, we find that the lowest excitations have a dynamical exponent z that varies from 2 to 3.2 as we vary a coupling in the Hamiltonian. We find an additional gapless mode with a continuously varying exponent 2 ≤z <2.7 , which establishes the presence of multiple dynamics. In order to explain these striking properties, we construct a continuum wave function for the ground state, which correctly describes the correlations and entanglement properties. We also give a continuum parent Hamiltonian, but show that additional ingredients are needed to capture the excitations of the chain. By using an exact mapping to the nonequilibrium dynamics of a classical spin chain, we find that the large dynamical exponent is due to subdiffusive spin motion. Finally, we discuss the connections to other spin chains and to a family of quantum critical models in two dimensions.

Scaling and memory in volatility return intervals in financial markets

PubMed Central

Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

2005-01-01

For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}{\\bar {{\\tau}}}\\end{equation*}\\end{document} as \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}P_{q}({\\tau})={\\bar {{\\tau}}}^{-1}f({\\tau}/{\\bar {{\\tau}}})\\end{equation*}\\end{document}. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ∼ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. PMID:15980152

Galilean invariant resummation schemes of cosmological perturbations

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

Peloso, Marco; Pietroni, Massimo, E-mail: peloso@physics.umn.edu, E-mail: massimo.pietroni@unipr.it

2017-01-01

Many of the methods proposed so far to go beyond Standard Perturbation Theory break invariance under time-dependent boosts (denoted here as extended Galilean Invariance, or GI). This gives rise to spurious large scale effects which spoil the small scale predictions of these approximation schemes. By using consistency relations we derive fully non-perturbative constraints that GI imposes on correlation functions. We then introduce a method to quantify the amount of GI breaking of a given scheme, and to correct it by properly tailored counterterms. Finally, we formulate resummation schemes which are manifestly GI, discuss their general features, and implement them inmore » the so called Time-Flow, or TRG, equations.« less

Lower Limb Function in Elderly Korean Adults Is Related to Cognitive Function.

PubMed

Kim, A-Sol; Ko, Hae-Jin

2018-05-01

Patients with cognitive impairment have decreased lower limb function. Therefore, we aimed to investigate the relationship between lower limb function and cognitive disorders to determine whether lower limb function can be screened to identify cognitive decline. Using Korean National Health Insurance Service-National Sample Cohort database data, we assessed the cognitive and lower limb functioning of 66-year-olds who underwent national health screening between 2010 and 2014. Cognitive function was assessed via a questionnaire. Timed Up-and-Go (TUG) and one-leg-standing (OLS) tests were performed to evaluate lower limb function. Associations between cognitive and lower limb functions were analyzed, and optimal cut-off points for these tests to screen for cognitive decline, were determined. Cognitive function was significantly correlated with TUG interval ( r = 0.414, p < 0.001) and OLS duration ( r = −0.237, p < 0.001). Optimal cut-off points for screening cognitive disorders were >11 s and ≤12 s for TUG interval and OLS duration, respectively. Among 66-year-olds who underwent national health screening, a significant correlation between lower limb and cognitive function was demonstrated. The TUG and OLS tests are useful screening tools for cognitive disorders in elderly patients. A large-scale prospective cohort study should be conducted to investigate the causal relationship between cognitive and lower limb function.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors.

PubMed

Ma, Xiaolei; Luan, Sen; Du, Bowen; Yu, Bin

2017-09-21

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.

Low-frequency connectivity is associated with mild traumatic brain injury.

PubMed

Dunkley, B T; Da Costa, L; Bethune, A; Jetly, R; Pang, E W; Taylor, M J; Doesburg, S M

2015-01-01

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

PubMed

Zhou, Hang; Yang, Yang; Shen, Hong-Bin

2017-03-15

Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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.

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

Vlah, Zvonimir; Seljak, Uroš; Okumura, Teppei

Numerical simulations show that redshift space distortions (RSD) introduce strong scale dependence in the power spectra of halos, with ten percent deviations relative to linear theory predictions even on relatively large scales (k < 0.1h/Mpc) and even in the absence of satellites (which induce Fingers-of-God, FoG, effects). If unmodeled these effects prevent one from extracting cosmological information from RSD surveys. In this paper we use Eulerian perturbation theory (PT) and Eulerian halo biasing model and apply it to the distribution function approach to RSD, in which RSD is decomposed into several correlators of density weighted velocity moments. We model eachmore » of these correlators using PT and compare the results to simulations over a wide range of halo masses and redshifts. We find that with an introduction of a physically motivated halo biasing, and using dark matter power spectra from simulations, we can reproduce the simulation results at a percent level on scales up to k ∼ 0.15h/Mpc at z = 0, without the need to have free FoG parameters in the model.« less

Laser Speckle Rheology for evaluating the viscoelastic properties of hydrogel scaffolds

PubMed Central

Hajjarian, Zeinab; Nia, Hadi Tavakoli; Ahn, Shawn; Grodzinsky, Alan J.; Jain, Rakesh K.; Nadkarni, Seemantini K.

2016-01-01

Natural and synthetic hydrogel scaffolds exhibit distinct viscoelastic properties at various length scales and deformation rates. Laser Speckle Rheology (LSR) offers a novel, non-contact optical approach for evaluating the frequency-dependent viscoelastic properties of hydrogels. In LSR, a coherent laser beam illuminates the specimen and a high-speed camera acquires the time-varying speckle images. Cross-correlation analysis of frames returns the speckle intensity autocorrelation function, g2(t), from which the frequency-dependent viscoelastic modulus, G*(ω), is deduced. Here, we establish the capability of LSR for evaluating the viscoelastic properties of hydrogels over a large range of moduli, using conventional mechanical rheometry and atomic force microscopy (AFM)-based indentation as reference-standards. Results demonstrate a strong correlation between |G*(ω)| values measured by LSR and mechanical rheometry (r = 0.95, p < 10−9), and z-test analysis reports that moduli values measured by the two methods are identical (p > 0.08) over a large range (47 Pa – 36 kPa). In addition, |G*(ω)| values measured by LSR correlate well with indentation moduli, E, reported by AFM (r = 0.92, p < 10−7). Further, spatially-resolved moduli measurements in micro-patterned substrates demonstrate that LSR combines the strengths of conventional rheology and micro-indentation in assessing hydrogel viscoelastic properties at multiple frequencies and small length-scales. PMID:27905494

Laser Speckle Rheology for evaluating the viscoelastic properties of hydrogel scaffolds.

PubMed

Hajjarian, Zeinab; Nia, Hadi Tavakoli; Ahn, Shawn; Grodzinsky, Alan J; Jain, Rakesh K; Nadkarni, Seemantini K

2016-12-01

Natural and synthetic hydrogel scaffolds exhibit distinct viscoelastic properties at various length scales and deformation rates. Laser Speckle Rheology (LSR) offers a novel, non-contact optical approach for evaluating the frequency-dependent viscoelastic properties of hydrogels. In LSR, a coherent laser beam illuminates the specimen and a high-speed camera acquires the time-varying speckle images. Cross-correlation analysis of frames returns the speckle intensity autocorrelation function, g 2 (t), from which the frequency-dependent viscoelastic modulus, G*(ω), is deduced. Here, we establish the capability of LSR for evaluating the viscoelastic properties of hydrogels over a large range of moduli, using conventional mechanical rheometry and atomic force microscopy (AFM)-based indentation as reference-standards. Results demonstrate a strong correlation between |G*(ω)| values measured by LSR and mechanical rheometry (r = 0.95, p < 10 -9 ), and z-test analysis reports that moduli values measured by the two methods are identical (p > 0.08) over a large range (47 Pa - 36 kPa). In addition, |G*(ω)| values measured by LSR correlate well with indentation moduli, E, reported by AFM (r = 0.92, p < 10 -7 ). Further, spatially-resolved moduli measurements in micro-patterned substrates demonstrate that LSR combines the strengths of conventional rheology and micro-indentation in assessing hydrogel viscoelastic properties at multiple frequencies and small length-scales.

Large-Scale Cubic-Scaling Random Phase Approximation Correlation Energy Calculations Using a Gaussian Basis.

PubMed

Wilhelm, Jan; Seewald, Patrick; Del Ben, Mauro; Hutter, Jürg

2016-12-13

We present an algorithm for computing the correlation energy in the random phase approximation (RPA) in a Gaussian basis requiring [Formula: see text] operations and [Formula: see text] memory. The method is based on the resolution of the identity (RI) with the overlap metric, a reformulation of RI-RPA in the Gaussian basis, imaginary time, and imaginary frequency integration techniques, and the use of sparse linear algebra. Additional memory reduction without extra computations can be achieved by an iterative scheme that overcomes the memory bottleneck of canonical RPA implementations. We report a massively parallel implementation that is the key for the application to large systems. Finally, cubic-scaling RPA is applied to a thousand water molecules using a correlation-consistent triple-ζ quality basis.

Impact of spatially correlated pore-scale heterogeneity on drying porous media

NASA Astrophysics Data System (ADS)

Borgman, Oshri; Fantinel, Paolo; Lühder, Wieland; Goehring, Lucas; Holtzman, Ran

2017-07-01

We study the effect of spatially-correlated heterogeneity on isothermal drying of porous media. We combine a minimal pore-scale model with microfluidic experiments with the same pore geometry. Our simulated drying behavior compares favorably with experiments, considering the large sensitivity of the emergent behavior to the uncertainty associated with even small manufacturing errors. We show that increasing the correlation length in particle sizes promotes preferential drying of clusters of large pores, prolonging liquid connectivity and surface wetness and thus higher drying rates for longer periods. Our findings improve our quantitative understanding of how pore-scale heterogeneity impacts drying, which plays a role in a wide range of processes ranging from fuel cells to curing of paints and cements to global budgets of energy, water and solutes in soils.

Validity of patient-reported swallowing and speech outcomes in relation to objectively measured oral function among patients treated for oral or oropharyngeal cancer.

PubMed

Rinkel, R N P M; Verdonck-de Leeuw, I M; de Bree, R; Aaronson, N K; Leemans, C R

2015-04-01

The objective of this study was to test the construct validity of the patient-reported outcomes Swallowing Quality of Life Questionnaire (SWAL-QOL) and Speech Handicap Index (SHI) in relation to objectively measured oral function among patients treated for oral or oropharyngeal cancer. The study sample consisted of patients treated for oral or oropharyngeal cancer. Outcome measures were the SWAL-QOL and the SHI, and the Functional Rehabilitation Outcomes Grade (FROG), a test to measure oral and shoulder function. Spearman's rank correlation coefficient was used to test associations between the SHI and SWAL-QOL scales, and the FROG scales. During a study period of 3 months, 38 patients (21 males, 17 females; mean age 54 years) were included who visited the outpatient clinic for follow-up care 6-155 months after surgical treatment (n = 14) or combined surgery and radiotherapy (n = 24) for oral (n = 21) or oropharyngeal cancer (n = 17). Most SWAL-QOL and SHI scales (except the SWAL-QOL Fatigue scale) correlated significantly with one or more FROG oral function scales. None of the SWAL-QOL and SHI scales correlated significantly with the FROG shoulder function scale. These results support the construct validity of the SWAL-QOL and SHI questionnaires for assessing speech and swallowing problems in daily life that are moderately but significantly related to oral function. A multidimensional assessment protocol is recommended for use in clinical practice and for research purposes for measuring oral function and swallowing- and speech-related problems in daily life among head and neck cancer patients.

Aspects of AdS/CFT: Conformal Deformations and the Goldstone Equivalence Theorem

NASA Astrophysics Data System (ADS)

Cantrell, Sean Andrew

The AdS/CFT correspondence provides a map from the states of theories situated in AdSd+1 to those in dual conformal theories in a d-dimensional space. The correspondence can be used to establish certain universal properties of some theories in one space by examining the behave of general objects in the other. In this thesis, we develop various formal aspects of AdS/CFT. Conformal deformations manifest in the AdS/CFT correspondence as boundary conditions on the AdS field. Heretofore, double-trace deformations have been the primary focus in this context. To better understand multitrace deformations, we revisit the relationship between the generating AdS partition function for a free bulk theory and the boundary CFT partition function subject to arbitrary conformal deformations. The procedure leads us to a formalism that constructs bulk fields from boundary operators. We independently replicate the holographic RG flow narrative to go on to interpret the brane used to regulate the AdS theory as a renormalization scale. The scale-dependence of the dilatation spectrum of a boundary theory in the presence of general deformations can be thus understood on the AdS side using this formalism. The Goldstone equivalence theorem allows one to relate scattering amplitudes of massive gauge fields to those of scalar fields in the limit of large scattering energies. We generalize this theorem under the framework of the AdS/CFT correspondence. First, we obtain an expression of the equivalence theorem in terms of correlation functions of creation and annihilation operators by using an AdS wave function approach to the AdS/CFT dictionary. It is shown that the divergence of the non-conserved conformal current dual to the bulk gauge field is approximately primary when computing correlators for theories in which the masses of all the exchanged particles are sufficiently large. The results are then generalized to higher spin fields. We then go on to generalize the theorem using conformal blocks in two and four-dimensional CFTs. We show that when the scaling dimensions of the exchanged operators are large compared to both their spins and the dimension of the current, the conformal blocks satisfy an equivalence theorem.

Seemingly unrelated intervention time series models for effectiveness evaluation of large scale environmental remediation.

PubMed

Ip, Ryan H L; Li, W K; Leung, Kenneth M Y

2013-09-15

Large scale environmental remediation projects applied to sea water always involve large amount of capital investments. Rigorous effectiveness evaluations of such projects are, therefore, necessary and essential for policy review and future planning. This study aims at investigating effectiveness of environmental remediation using three different Seemingly Unrelated Regression (SUR) time series models with intervention effects, including Model (1) assuming no correlation within and across variables, Model (2) assuming no correlation across variable but allowing correlations within variable across different sites, and Model (3) allowing all possible correlations among variables (i.e., an unrestricted model). The results suggested that the unrestricted SUR model is the most reliable one, consistently having smallest variations of the estimated model parameters. We discussed our results with reference to marine water quality management in Hong Kong while bringing managerial issues into consideration. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatio-temporal variability of dryness/wetness in the middle and lower reaches of the Yangtze River Basin and correlation with large-scale climatic factors

NASA Astrophysics Data System (ADS)

Chen, Xinchi; Zhang, Liping; Zou, Lei; Shan, Lijie; She, Dunxian

2018-02-01

The middle and lower reaches of the Yangtze River Basin (MLYR) are greatly affected by frequent drought/flooding events and abrupt alternations of these events in China. The purpose of this study is to analyze the spatial and temporal variability of dryness/wetness based on the data obtained from 75 meteorological stations in the MLYR for the period 1960-2015 and investigate the correlations between dryness/wetness and atmospheric circulation factors. The empirical orthogonal function method was applied in this study based on the monthly Standardized Precipitation Index at a 12-month time scale. The first leading pattern captured the same characteristics of dryness/wetness over the entire MLYR area and accounted for 40.87% of the total variance. Both the second and third leading patterns manifested as regional features of variability over the entire MLYR. The cross-wavelet transform method was applied to explore the potential relationship between the three leading patterns and the large-scale climate factors, and finally the relationships between drought/wetness events and climate factors were also analyzed. Our results indicated that the main patterns of dryness/wetness were primarily associated with the Niño 3.4, Indian Ocean Dipole, Southern Oscillation Index and Northern Oscillation Index, with the first pattern exhibiting noticeable periods and remarkable changes in phase with the indices.

Large-scale clustering as a probe of the origin and the host environment of fast radio bursts

NASA Astrophysics Data System (ADS)

Shirasaki, Masato; Kashiyama, Kazumi; Yoshida, Naoki

2017-04-01

We propose to use degree-scale angular clustering of fast radio bursts (FRBs) to identify their origin and the host galaxy population. We study the information content in autocorrelation of the angular positions and dispersion measures (DM) and in cross-correlation with galaxies. We show that the cross-correlation with Sloan Digital Sky Survey (SDSS) galaxies will place stringent constraints on the mean physical quantities associated with FRBs. If ˜10 ,000 FRBs are detected with ≲deg resolution in the SDSS field, the clustering analysis with the intrinsic DM scatter of 100 pc /cm3 can constrain the global abundance of free electrons at z ≲1 and the large-scale bias of FRB host galaxies (the statistical relation between the distribution of host galaxies and cosmic matter density field) with fractional errors (with a 68% confidence level) of ˜10 % and ˜20 %, respectively. The mean near-source dispersion measure and the delay-time distribution of FRB rates relative to the global star forming rate can be also determined by combining the clustering and the probability distribution function of DM. Our approach will be complementary to high-resolution (≪deg ) event localization using e.g., VLA and VLBI for identifying the origin of FRBs and the source environment. We strongly encourage future observational programs such as CHIME, UTMOST, and HIRAX to survey FRBs in the SDSS field.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

PubMed Central

Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida

2016-01-01

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637

Femtoscopy with identified charged pions in proton-lead collisions at s NN = 5.02 TeV with ATLAS

DOE PAGES

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

2017-12-28

Bose-Einsmore » tein correlations between identified charged pions are measured for p+Pb collisions at s NN =5.02 TeV using data recorded by the ATLAS detector at the CERN Large Hadron Collider corresponding to a total integrated luminosity of 28nb-1. Pions are identified using ionization energy loss measured in the pixel detector. Two-particle correlation functions and the extracted source radii are presented as a function of collision centrality as well as the average transverse momentum (kT) and rapidity (yππ) of the pair. Pairs are selected with a rapidity -2 < yππ < 1 and with an average transverse momentum 0.1 < kT < 0.8GeV. The effect of jet fragmentation on the two-particle correlation function is studied, and a method using opposite-charge pair data to constrain its contributions to the measured correlations is described. The measured source sizes are substantially larger in more central collisions and are observed to decrease with increasing pair kT. A correlation of the radii with the local charged-particle density is demonstrated. The scaling of the extracted radii with the mean number of participating nucleons is also used to compare a selection of initial-geometry models. The cross term Rol is measured as a function of rapidity, and a nonzero value is observed with 5.1σ combined significance for -1 < yππ < 1 in the most central events.« less

Femtoscopy with identified charged pions in proton-lead collisions at s NN = 5.02 TeV with ATLAS

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

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

Bose-Einsmore » tein correlations between identified charged pions are measured for p+Pb collisions at s NN =5.02 TeV using data recorded by the ATLAS detector at the CERN Large Hadron Collider corresponding to a total integrated luminosity of 28nb-1. Pions are identified using ionization energy loss measured in the pixel detector. Two-particle correlation functions and the extracted source radii are presented as a function of collision centrality as well as the average transverse momentum (kT) and rapidity (yππ) of the pair. Pairs are selected with a rapidity -2 < yππ < 1 and with an average transverse momentum 0.1 < kT < 0.8GeV. The effect of jet fragmentation on the two-particle correlation function is studied, and a method using opposite-charge pair data to constrain its contributions to the measured correlations is described. The measured source sizes are substantially larger in more central collisions and are observed to decrease with increasing pair kT. A correlation of the radii with the local charged-particle density is demonstrated. The scaling of the extracted radii with the mean number of participating nucleons is also used to compare a selection of initial-geometry models. The cross term Rol is measured as a function of rapidity, and a nonzero value is observed with 5.1σ combined significance for -1 < yππ < 1 in the most central events.« less

Femtoscopy with identified charged pions in proton-lead collisions at √{sNN}=5.02 TeV with ATLAS

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconadaâ Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarezâ Gonzalez, B.; Álvarezâ Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaralâ Coutinho, Y.; Amelung, C.; Amidei, D.; Amorâ Dosâ Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperioâ Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. 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O.; Dewhurst, A.; Dhaliwal, S.; Diâ Ciaccio, A.; Diâ Ciaccio, L.; Diâ Clemente, W. K.; Diâ Donato, C.; Diâ Girolamo, A.; Diâ Girolamo, B.; Diâ Micco, B.; Diâ Nardo, R.; Diâ Simone, A.; Diâ Sipio, R.; Diâ Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díezâ Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Doâ Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duranâ Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. 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B.; Feremenga, L.; Fernandezâ Martinez, P.; Fernandezâ Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreiraâ Deâ Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferrettoâ Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Floresâ Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullanaâ Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y.; Gao, Y. S.; Garayâ Walls, F. M.; García, C.; Garcíaâ Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gasconâ Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. 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M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoalehâ Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solansâ Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapiaâ Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavaresâ Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temple, D.; Tenâ Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticseâ Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torróâ Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdesâ Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallsâ Ferrer, J. A.; Vanâ Denâ Wollenberg, W.; Vanâ Derâ Deijl, P. C.; Vanâ Derâ Graaf, H.; Vanâ Eldik, N.; Vanâ Gemmeren, P.; Vanâ Nieuwkoop, J.; Vanâ Vulpen, I.; Vanâ Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquezâ Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickeyâ Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplanaâ Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; Vonâ Derâ Schmitt, H.; Vonâ Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjesâ Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yauâ Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zurâ Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-12-01

Bose-Einstein correlations between identified charged pions are measured for p +Pb collisions at √{sNN}=5.02 TeV using data recorded by the ATLAS detector at the CERN Large Hadron Collider corresponding to a total integrated luminosity of 28 nb-1 . Pions are identified using ionization energy loss measured in the pixel detector. Two-particle correlation functions and the extracted source radii are presented as a function of collision centrality as well as the average transverse momentum (kT) and rapidity (yππ ★) of the pair. Pairs are selected with a rapidity -2

Is There Any Real Observational Contradictoty To The Lcdm Model?

NASA Astrophysics Data System (ADS)

Ma, Yin-Zhe

2011-01-01

In this talk, I am going to question the two apparent observational contradictories to LCDM cosmology---- the lack of large angle correlations in the cosmic microwave background, and the very large bulk flow of galaxy peculiar velocities. On the super-horizon scale, "Copi etal. (2009)” have been arguing that the lack of large angular correlations of the CMB temperature field provides strong evidence against the standard, statistically isotropic, LCDM cosmology. I am going to argue that the "ad-hoc” discrepancy is due to the sub-optimal estimator of the low-l multipoles, and a posteriori statistics, which exaggerates the statistical significance. On Galactic scales, "Watkins et al. (2008)” shows that the very large bulk flow prefers a very large density fluctuation, which seems to contradict to the LCDM model. I am going to show that these results are due to their underestimation of the small scale velocity dispersion, and an arbitrary way of combining catalogues. With the appropriate way of combining catalogue data, as well as the treating the small scale velocity dispersion as a free parameter, the peculiar velocity field provides unconvincing evidence against LCDM cosmology.

Real- and redshift-space halo clustering in f(R) cosmologies

NASA Astrophysics Data System (ADS)

Arnalte-Mur, Pablo; Hellwing, Wojciech A.; Norberg, Peder

2017-05-01

We present two-point correlation function statistics of the mass and the haloes in the chameleon f(R) modified gravity scenario using a series of large-volume N-body simulations. Three distinct variations of f(R) are considered (F4, F5 and F6) and compared to a fiducial Λ cold dark matter (ΛCDM) model in the redshift range z ∈ [0, 1]. We find that the matter clustering is indistinguishable for all models except for F4, which shows a significantly steeper slope. The ratio of the redshift- to real-space correlation function at scales >20 h-1 Mpc agrees with the linear General Relativity (GR) Kaiser formula for the viable f(R) models considered. We consider three halo populations characterized by spatial abundances comparable to that of luminous red galaxies and galaxy clusters. The redshift-space halo correlation functions of F4 and F5 deviate significantly from ΛCDM at intermediate and high redshift, as the f(R) halo bias is smaller than or equal to that of the ΛCDM case. Finally, we introduce a new model-independent clustering statistic to distinguish f(R) from GR: the relative halo clustering ratio - R. The sampling required to adequately reduce the scatter in R will be available with the advent of the next-generation galaxy redshift surveys. This will foster a prospective avenue to obtain largely model-independent cosmological constraints on this class of modified gravity models.

Sporadic Inclusion Body Myositis: MRI Findings and Correlation With Clinical and Functional Parameters.

PubMed

Guimaraes, Julio Brandao; Zanoteli, Edmar; Link, Thomas M; de Camargo, Leonardo V; Facchetti, Luca; Nardo, Lorenzo; Fernandes, Artur da Rocha Correa

2017-12-01

The purpose of this prospective study is to assess MRI findings in patients with sporadic inclusion body myositis (IBM) and correlate them with clinical and functional parameters. This study included 12 patients with biopsy-proven sporadic IBM. All patients underwent MRI of the bilateral upper and lower extremities. The images were scored for muscle atrophy, fatty infiltration, and edema pattern. Clinical data included onset and duration of disease. Muscle strength was measured using the Medical Research Council (MRC) scale, and functional status was assessed using the Modified Rankin Scale. Correlation between MRI and different clinical and functional parameters was calculated using the Spearman rank test and Pearson correlation. All patients showed MRI abnormalities, which were more severe within the lower limbs and the distal segments. The most prevalent MRI finding was fat infiltration. There was a statistically significant correlation between disease duration and number of muscles infiltrated by fat (r = 0.65; p = 0.04). The number of muscles with fat infiltration correlated with the sum of the scores of MRC (r = -0.60; p = 0.04) and with the Modified Rankin Scale (r = 0.48; p = 0.03). Our findings suggest that most patients with biopsy-proven sporadic IBM present with a typical pattern of muscle involvement at MRI, more extensively in the lower extremities. Moreover, MRI findings strongly correlated with clinical and functional parameters, because both the extent and severity of muscle involvement assessed by MRI and clinical and functional parameters are associated with the early onset of the disease and its duration.

Hill functions for stochastic gene regulatory networks from master equations with split nodes and time-scale separation

NASA Astrophysics Data System (ADS)

Lipan, Ovidiu; Ferwerda, Cameron

2018-02-01

The deterministic Hill function depends only on the average values of molecule numbers. To account for the fluctuations in the molecule numbers, the argument of the Hill function needs to contain the means, the standard deviations, and the correlations. Here we present a method that allows for stochastic Hill functions to be constructed from the dynamical evolution of stochastic biocircuits with specific topologies. These stochastic Hill functions are presented in a closed analytical form so that they can be easily incorporated in models for large genetic regulatory networks. Using a repressive biocircuit as an example, we show by Monte Carlo simulations that the traditional deterministic Hill function inaccurately predicts time of repression by an order of two magnitudes. However, the stochastic Hill function was able to capture the fluctuations and thus accurately predicted the time of repression.

Decoupling processes and scales of shoreline morphodynamics

USGS Publications Warehouse

Hapke, Cheryl J.; Plant, Nathaniel G.; Henderson, Rachel E.; Schwab, William C.; Nelson, Timothy R.

2016-01-01

Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.

Scaling up the diversity-resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire.

PubMed

Spasojevic, Marko J; Bahlai, Christie A; Bradley, Bethany A; Butterfield, Bradley J; Tuanmu, Mao-Ning; Sistla, Seeta; Wiederholt, Ruscena; Suding, Katharine N

2016-04-01

Understanding the mechanisms underlying ecosystem resilience - why some systems have an irreversible response to disturbances while others recover - is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large-scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small-scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four-corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local-scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues. © 2015 John Wiley & Sons Ltd.

Cosmological Constraints from the Redshift Dependence of the Volume Effect Using the Galaxy 2-point Correlation Function across the Line of Sight

NASA Astrophysics Data System (ADS)

Li, Xiao-Dong; Park, Changbom; Sabiu, Cristiano G.; Park, Hyunbae; Cheng, Cheng; Kim, Juhan; Hong, Sungwook E.

2017-08-01

We develop a methodology to use the redshift dependence of the galaxy 2-point correlation function (2pCF) across the line of sight, ξ ({r}\\perp ), as a probe of cosmological parameters. The positions of galaxies in comoving Cartesian space varies under different cosmological parameter choices, inducing a redshift-dependent scaling in the galaxy distribution. This geometrical distortion can be observed as a redshift-dependent rescaling in the measured ξ ({r}\\perp ). We test this methodology using a sample of 1.75 billion mock galaxies at redshifts 0, 0.5, 1, 1.5, and 2, drawn from the Horizon Run 4 N-body simulation. The shape of ξ ({r}\\perp ) can exhibit a significant redshift evolution when the galaxy sample is analyzed under a cosmology differing from the true, simulated one. Other contributions, including the gravitational growth of structure, galaxy bias, and the redshift space distortions, do not produce large redshift evolution in the shape. We show that one can make use of this geometrical distortion to constrain the values of cosmological parameters governing the expansion history of the universe. This method could be applicable to future large-scale structure surveys, especially photometric surveys such as DES and LSST, to derive tight cosmological constraints. This work is a continuation of our previous works as a strategy to constrain cosmological parameters using redshift-invariant physical quantities.

Quality of life in smokers: focus on functional limitations rather than on lung function?

PubMed Central

Geijer, Roeland MM; Sachs, Alfred PE; Verheij, Theo JM; Kerstjens, Huib AM; Kuyvenhoven, Marijke M; Hoes, Arno W

2007-01-01

Background The Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification of severity of chronic obstructive pulmonary disease (COPD) is based solely on obstruction and does not capture physical functioning. The hypothesis that the Medical Research Council (MRC) dyspnoea scale would correlate better with quality of life than the level of airflow limitation was examined. Aim To study the associations between quality of life in smokers and limitations in physical functioning (MRC dyspnoea scale) and, quality of life and airflow limitation (GOLD COPD stages). Design Cross-sectional study. Setting The city of IJsselstein, a small town in the centre of The Netherlands. Method Male smokers aged 40–65 years without a prior diagnosis of COPD and enlisted with a general practice, participated in this study. Quality of life was assessed by means of a generic (SF–36) and a disease-specific, questionnaire (QOLRIQ). Results A total of 395 subjects (mean age 55.4 years, pack years 27.1) performed adequate spirometry and completed the questionnaires. Limitations of physical functioning according to the MRC dyspnoea scale were found in 25.1 % (99/395) of the participants and airflow limitation in 40.2% (159/395). The correlations of limitations of physical functioning with all quality-of-life components were stronger than the correlations of all quality-of-life subscales with the severity of airflow limitation. Conclusion In middle-aged smokers the correlation of limitations of physical functioning (MRC dyspnoea scale) with quality of life was stronger than the correlation of the severity of airflow limitation with quality of life. Future staging systems of severity of COPD should capture this and not rely on forced expiratory volume in one second (FEV1) alone. PMID:17550673

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations

PubMed Central

Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-01-01

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427

Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations.

PubMed

Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-07-03

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Testing gravity using large-scale redshift-space distortions

NASA Astrophysics Data System (ADS)

Raccanelli, Alvise; Bertacca, Daniele; Pietrobon, Davide; Schmidt, Fabian; Samushia, Lado; Bartolo, Nicola; Doré, Olivier; Matarrese, Sabino; Percival, Will J.

2013-11-01

We use luminous red galaxies from the Sloan Digital Sky Survey (SDSS) II to test the cosmological structure growth in two alternatives to the standard Λ cold dark matter (ΛCDM)+general relativity (GR) cosmological model. We compare observed three-dimensional clustering in SDSS Data Release 7 (DR7) with theoretical predictions for the standard vanilla ΛCDM+GR model, unified dark matter (UDM) cosmologies and the normal branch Dvali-Gabadadze-Porrati (nDGP). In computing the expected correlations in UDM cosmologies, we derive a parametrized formula for the growth factor in these models. For our analysis we apply the methodology tested in Raccanelli et al. and use the measurements of Samushia et al. that account for survey geometry, non-linear and wide-angle effects and the distribution of pair orientation. We show that the estimate of the growth rate is potentially degenerate with wide-angle effects, meaning that extremely accurate measurements of the growth rate on large scales will need to take such effects into account. We use measurements of the zeroth and second-order moments of the correlation function from SDSS DR7 data and the Large Suite of Dark Matter Simulations (LasDamas), and perform a likelihood analysis to constrain the parameters of the models. Using information on the clustering up to rmax = 120 h-1 Mpc, and after marginalizing over the bias, we find, for UDM models, a speed of sound c∞ ≤ 6.1e-4, and, for the nDGP model, a cross-over scale rc ≥ 340 Mpc, at 95 per cent confidence level.

Asymptotic coincidence of the statistics for degenerate and non-degenerate correlated real Wishart ensembles

NASA Astrophysics Data System (ADS)

Wirtz, Tim; Kieburg, Mario; Guhr, Thomas

2017-06-01

The correlated Wishart model provides the standard benchmark when analyzing time series of any kind. Unfortunately, the real case, which is the most relevant one in applications, poses serious challenges for analytical calculations. Often these challenges are due to square root singularities which cannot be handled using common random matrix techniques. We present a new way to tackle this issue. Using supersymmetry, we carry out an anlaytical study which we support by numerical simulations. For large but finite matrix dimensions, we show that statistical properties of the fully correlated real Wishart model generically approach those of a correlated real Wishart model with doubled matrix dimensions and doubly degenerate empirical eigenvalues. This holds for the local and global spectral statistics. With Monte Carlo simulations we show that this is even approximately true for small matrix dimensions. We explicitly investigate the k-point correlation function as well as the distribution of the largest eigenvalue for which we find a surprisingly compact formula in the doubly degenerate case. Moreover we show that on the local scale the k-point correlation function exhibits the sine and the Airy kernel in the bulk and at the soft edges, respectively. We also address the positions and the fluctuations of the possible outliers in the data.

Variation in carbon isotope discrimination in Cleistogenes squarrosa (Trin.) Keng: patterns and drivers at tiller, local, catchment, and regional scales

PubMed Central

Yang, Hao; Auerswald, Karl; Bai, Yongfei; Wittmer, Maximilian H. O. M.; Schnyder, Hans

2011-01-01

Understanding the patterns and drivers of carbon isotope discrimination in C4 species is critical for predicting the effects of global change on C3/C4 ratio of plant community and consequently on ecosystem functioning and services. Cleistogenes squarrosa (Trin.) Keng is a dominant C4 perennial bunchgrass of arid and semi-arid ecosystems across the Mongolian plateau of the Eurasian steppe. Its carbon isotope discrimination (13Δ) during photosynthesis is relatively large among C4 species and it is variable. Here the 13Δ of C. squarrosa and its potential drivers at a nested set of scales were examined. Within cohorts of tillers, 13Δ of leaves increased from 5.1‰ to 8.1‰ from old to young leaves. At the local scale, 13Δ of mature leaves varied from 5.8‰ to 8.4‰, increasing with decreasing grazing intensity. At the catchment scale, 13Δ of mature leaves varied from 6.2‰ to 8.5‰ and increased with topsoil silt content. At the regional scale, 13Δ of mature leaves varied from 5.5‰ to 8.9‰, increasing with growing-season precipitation. At all scales, 13Δ decreased with increasing leaf nitrogen content (Nleaf). Nleaf was positively correlated with grazing intensity and leaf position along tillers, but negatively correlated with precipitation. The presence of the correlations across a range of different environmental contexts strongly implicates Nleaf as a major driver of 13Δ in C. squarrosa and, possibly, other C4 species. PMID:21527626

Correspondence between large-scale ictal and interictal epileptic networks revealed by single photon emission computed tomography (SPECT) and electroencephalography (EEG)-functional magnetic resonance imaging (fMRI).

PubMed

Tousseyn, Simon; Dupont, Patrick; Goffin, Karolien; Sunaert, Stefan; Van Paesschen, Wim

2015-03-01

Epilepsy is increasingly recognized as a network disorder, but the spatial relationship between ictal and interictal networks is still largely unexplored. In this work, we compared hemodynamic changes related to seizures and interictal spikes on a whole brain scale. Twenty-eight patients with refractory focal epilepsy (14 temporal and 14 extratemporal lobe) underwent both subtraction ictal single photon emission computed tomography (SPECT) coregistered to magnetic resonance imaging (MRI) (SISCOM) and spike-related electroencephalography (EEG-functional MRI (fMRI). SISCOM visualized relative perfusion changes during seizures, whereas EEG-fMRI mapped blood oxygen level-dependent (BOLD) changes related to spikes. Similarity between statistical maps of both modalities was analyzed per patient using the following two measures: (1) correlation between unthresholded statistical maps (Pearson's correlation coefficient) and (2) overlap between thresholded images (Dice coefficient). Overlap was evaluated at a regional level, for hyperperfusions and activations and for hypoperfusions and deactivations separately, using different thresholds. Nonparametric permutation tests were applied to assess statistical significance (p ≤ 0.05). We found significant and positive correlations between hemodynamic changes related to seizures and spikes in 27 (96%) of 28 cases (median correlation coefficient 0.29 [range -0.12 to 0.62]). In 20 (71%) of 28 cases, spatial overlap between hyperperfusion on SISCOM and activation on EEG-fMRI was significantly larger than expected by chance. Congruent changes were not restricted to the territory of the presumed epileptogenic zone, but could be seen at distant sites (e.g., cerebellum and basal ganglia). Overlap between ictal hypoperfusion and interictal deactivation was statistically significant in 22 (79%) of 28 patients. Despite the high rate of congruence, discrepancies were observed for both modalities. We conclude that hemodynamic changes related to seizures and spikes varied spatially with the same sign and within a common network. Overlap was present in regions nearby and distant from discharge origin. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Scale dependence of deuteron electrodisintegration

NASA Astrophysics Data System (ADS)

More, S. N.; Bogner, S. K.; Furnstahl, R. J.

2017-11-01

Background: Isolating nuclear structure properties from knock-out reactions in a process-independent manner requires a controlled factorization, which is always to some degree scale and scheme dependent. Understanding this dependence is important for robust extractions from experiment, to correctly use the structure information in other processes, and to understand the impact of approximations for both. Purpose: We seek insight into scale dependence by exploring a model calculation of deuteron electrodisintegration, which provides a simple and clean theoretical laboratory. Methods: By considering various kinematic regions of the longitudinal structure function, we can examine how the components—the initial deuteron wave function, the current operator, and the final-state interactions (FSIs)—combine at different scales. We use the similarity renormalization group to evolve each component. Results: When evolved to different resolutions, the ingredients are all modified, but how they combine depends strongly on the kinematic region. In some regions, for example, the FSIs are largely unaffected by evolution, while elsewhere FSIs are greatly reduced. For certain kinematics, the impulse approximation at a high renormalization group resolution gives an intuitive picture in terms of a one-body current breaking up a short-range correlated neutron-proton pair, although FSIs distort this simple picture. With evolution to low resolution, however, the cross section is unchanged but a very different and arguably simpler intuitive picture emerges, with the evolved current efficiently represented at low momentum through derivative expansions or low-rank singular value decompositions. Conclusions: The underlying physics of deuteron electrodisintegration is scale dependent and not just kinematics dependent. As a result, intuition about physics such as the role of short-range correlations or D -state mixing in particular kinematic regimes can be strongly scale dependent. Understanding this dependence is crucial in making use of extracted properties.

Implications of the IRAS data for galactic gamma-ray astronomy and EGRET

NASA Technical Reports Server (NTRS)

Stecker, F. W.

1990-01-01

Using the results of gamma-ray, millimeter wave and far infrared surveys of the galaxy, one can derive a logically consistent picture of the large scale distribution of galactic gas and cosmic rays, one tied to the overall processes of stellar birth and destruction on a galactic scale. Using the results of the IRAS far-infrared survey of the galaxy, the large scale radial distribution of galactic far-infrared emission were obtained independently for both the Northern and Southern Hemisphere sides of the Galaxy. It was found that the dominant feature in these distributions to be a broad peak coincident with the 5 kpc molecular gas cloud ring. Also found was evidence of spiral arm features. Strong correlations are evident between the large scale galactic distributions of far infrared emission, gamma-ray emission and total CO emission. There is a particularly tight correlation between the distribution of warm molecular clouds and far-infrared emission on a galactic scale.

A cosmic superfluid phase

NASA Technical Reports Server (NTRS)

Gradwohl, Ben-Ami

1991-01-01

The universe may have undergone a superfluid-like phase during its evolution, resulting from the injection of nontopological charge into the spontaneously broken vacuum. In the presence of vortices this charge is identified with angular momentum. This leads to turbulent domains on the scale of the correlation length. By restoring the symmetry at low temperatures, the vortices dissociate and push the charges to the boundaries of these domains. The model can be scaled (phenomenologically) to very low energies, it can be incorporated in a late time phase transition and form large scale structure in the boundary layers of the correlation volumes. The novel feature of the model lies in the fact that the dark matter is endowed with coherent motion. The possibilities of identifying this flow around superfluid vortices with the observed large scale bulk motion is discussed. If this identification is possible, then the definite prediction can be made that a more extended map of peculiar velocities would have to reveal large scale circulations in the flow pattern.

Bioinspired Wood Nanotechnology for Functional Materials.

PubMed

Berglund, Lars A; Burgert, Ingo

2018-05-01

It is a challenging task to realize the vision of hierarchically structured nanomaterials for large-scale applications. Herein, the biomaterial wood as a large-scale biotemplate for functionalization at multiple scales is discussed, to provide an increased property range to this renewable and CO 2 -storing bioresource, which is available at low cost and in large quantities. The Progress Report reviews the emerging field of functional wood materials in view of the specific features of the structural template and novel nanotechnological approaches for the development of wood-polymer composites and wood-mineral hybrids for advanced property profiles and new functions. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Validity of the stroke rehabilitation assessment of movement scale in acute rehabilitation: a comparison with the functional independence measure and stroke impact scale-16.

PubMed

Ward, Irene; Pivko, Susan; Brooks, Gary; Parkin, Kate

2011-11-01

To demonstrate sensitivity to change of the Stroke Rehabilitation Assessment of Movement (STREAM) as well as the concurrent and predictive validity of the STREAM in an acute rehabilitation setting. Prospective cohort study. Acute, in-patient rehabilitation department within a tertiary-care teaching hospital in the United States. Thirty adults with a newly diagnosed, first ischemic stroke. Clinical assessments were conducted on admission and then again on discharge from the rehabilitation hospital with the STREAM (total STREAM and upper extremity, lower extremity, and mobility subscales), Functional Independence Measure (FIM), and Stroke Impact Scale-16 (SIS-16). Sensitivity to change was determined with the Wilcoxon signed rank test and by the calculation of standardized response means. Spearman correlations were used to assess concurrent validity of the total STREAM and STREAM subscales with the FIM and SIS-16 on admission and discharge. We determined predictive validity for all instruments by correlating admission scores with actual and predicted length of stay and by testing associations between admission scores and discharge destination (home vs subacute facility). Not applicable. For all instruments, there was statistically significant improvement from admission to discharge. The standardized response means for the total STREAM and STREAM subscales were large. Spearman correlations between the total STREAM and STREAM subscales and the FIM and SIS-16 were moderate to excellent, both on admission and discharge. Among change scores, only the SIS-16 correlated with the total STREAM. All 3 instruments were significantly associated with discharge destination; however, the associations were strongest for the total STREAM and STREAM subscales. All instruments showed moderate-to-excellent correlations with predicted and actual length of stay. The STREAM is sensitive to change and demonstrates good concurrent and predictive validity as compared with the FIM and SIS-16 in the acute inpatient rehabilitation population. Copyright © 2011 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Generalized extended Navier-Stokes theory: correlations in molecular fluids with intrinsic angular momentum.

PubMed

Hansen, J S; Daivis, Peter J; Dyre, Jeppe C; Todd, B D; Bruus, Henrik

2013-01-21

The extended Navier-Stokes theory accounts for the coupling between the translational and rotational molecular degrees of freedom. In this paper, we generalize this theory to non-zero frequencies and wavevectors, which enables a new study of spatio-temporal correlation phenomena present in molecular fluids. To discuss these phenomena in detail, molecular dynamics simulations of molecular chlorine are performed for three different state points. In general, the theory captures the behavior for small wavevector and frequencies as expected. For example, in the hydrodynamic regime and for molecular fluids with small moment of inertia like chlorine, the theory predicts that the longitudinal and transverse intrinsic angular velocity correlation functions are almost identical, which is also seen in the molecular dynamics simulations. However, the theory fails at large wavevector and frequencies. To account for the correlations at these scales, we derive a phenomenological expression for the frequency dependent rotational viscosity and wavevector and frequency dependent longitudinal spin viscosity. From this we observe a significant coupling enhancement between the molecular angular velocity and translational velocity for large frequencies in the gas phase; this is not observed for the supercritical fluid and liquid state points.

Time-dependent vibrational spectral analysis of first principles trajectory of methylamine with wavelet transform.

PubMed

Biswas, Sohag; Mallik, Bhabani S

2017-04-12

The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated. The instantaneous stretching frequencies of amine groups were obtained by wavelet transform of the trajectory obtained from FPMD simulations. The frequency-structure correlation reveals that the amine stretching frequency is weakly correlated with the nearest nitrogen-deuterium distance. The frequency-frequency correlation function has a short time scale of around 110 fs and a longer time scale of about 1.15 ps. It was found that the short time scale originates from the underdamped motion of intact hydrogen bonds of MA pairs. However, the long time scale of the vibrational spectral diffusion of N-D modes is determined by the overall dynamics of hydrogen bonds as well as the dangling ND groups and the inertial rotation of the amine group of the molecule.

Approximate Bayesian computation in large-scale structure: constraining the galaxy-halo connection

NASA Astrophysics Data System (ADS)

Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Campbell, Duncan

2017-08-01

Standard approaches to Bayesian parameter inference in large-scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as approximate Bayesian computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter haloes with galaxies. Using specific implementation of ABC supplemented with population Monte Carlo importance sampling, a generative forward model using HOD and a distance metric based on galaxy number density, two-point correlation function and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected 'true' HOD parameters. The parameter constraints we obtain from ABC are consistent with the 'true' HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately, our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

Correspondence Between Aberrant Intrinsic Network Connectivity and Gray-Matter Volume in the Ventral Brain of Preterm Born Adults.

PubMed

Bäuml, Josef G; Daamen, Marcel; Meng, Chun; Neitzel, Julia; Scheef, Lukas; Jaekel, Julia; Busch, Barbara; Baumann, Nicole; Bartmann, Peter; Wolke, Dieter; Boecker, Henning; Wohlschläger, Afra M; Sorg, Christian

2015-11-01

Widespread brain changes are present in preterm born infants, adolescents, and even adults. While neurobiological models of prematurity facilitate powerful explanations for the adverse effects of preterm birth on the developing brain at microscale, convincing linking principles at large-scale level to explain the widespread nature of brain changes are still missing. We investigated effects of preterm birth on the brain's large-scale intrinsic networks and their relation to brain structure in preterm born adults. In 95 preterm and 83 full-term born adults, structural and functional magnetic resonance imaging at-rest was used to analyze both voxel-based morphometry and spatial patterns of functional connectivity in ongoing blood oxygenation level-dependent activity. Differences in intrinsic functional connectivity (iFC) were found in cortical and subcortical networks. Structural differences were located in subcortical, temporal, and cingulate areas. Critically, for preterm born adults, iFC-network differences were overlapping and correlating with aberrant regional gray-matter (GM) volume specifically in subcortical and temporal areas. Overlapping changes were predicted by prematurity and in particular by neonatal medical complications. These results provide evidence that preterm birth has long-lasting effects on functional connectivity of intrinsic networks, and these changes are specifically related to structural alterations in ventral brain GM. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval.

PubMed

Xu, Xing; Shen, Fumin; Yang, Yang; Shen, Heng Tao; Li, Xuelong

2017-05-01

Hashing based methods have attracted considerable attention for efficient cross-modal retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to learn compact binary codes that construct the underlying correlations between heterogeneous features from different modalities. A majority of recent approaches aim at learning hash functions to preserve the pairwise similarities defined by given class labels. However, these methods fail to explicitly explore the discriminative property of class labels during hash function learning. In addition, they usually discard the discrete constraints imposed on the to-be-learned binary codes, and compromise to solve a relaxed problem with quantization to obtain the approximate binary solution. Therefore, the binary codes generated by these methods are suboptimal and less discriminative to different classes. To overcome these drawbacks, we propose a novel cross-modal hashing method, termed discrete cross-modal hashing (DCH), which directly learns discriminative binary codes while retaining the discrete constraints. Specifically, DCH learns modality-specific hash functions for generating unified binary codes, and these binary codes are viewed as representative features for discriminative classification with class labels. An effective discrete optimization algorithm is developed for DCH to jointly learn the modality-specific hash function and the unified binary codes. Extensive experiments on three benchmark data sets highlight the superiority of DCH under various cross-modal scenarios and show its state-of-the-art performance.

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

Ground-based Remote Sensing for Quantifying Subsurface and Surface Co-variability to Scale Arctic Ecosystem Functioning

NASA Astrophysics Data System (ADS)

Oktem, R.; Wainwright, H. M.; Curtis, J. B.; Dafflon, B.; Peterson, J.; Ulrich, C.; Hubbard, S. S.; Torn, M. S.

2016-12-01

Predicting carbon cycling in Arctic requires quantifying tightly coupled surface and subsurface processes including permafrost, hydrology, vegetation and soil biogeochemistry. The challenge has been a lack of means to remotely sense key ecosystem properties in high resolution and over large areas. A particular challenge has been characterizing soil properties that are known to be highly heterogeneous. In this study, we exploit tightly-coupled above/belowground ecosystem functioning (e.g., the correlations among soil moisture, vegetation and carbon fluxes) to estimate subsurface and other key properties over large areas. To test this concept, we have installed a ground-based remote sensing platform - a track-mounted tram system - along a 70 m transect in the ice-wedge polygonal tundra near Barrow, Alaska. The tram carries a suite of near-surface remote sensing sensors, including sonic depth, thermal IR, NDVI and multispectral sensors. Joint analysis with multiple ground-based measurements (soil temperature, active layer soil moisture, and carbon fluxes) was performed to quantify correlations and the dynamics of above/belowground processes at unprecedented resolution, both temporally and spatially. We analyzed the datasets with particular focus on correlating key subsurface and ecosystem properties with surface properties that can be measured by satellite/airborne remote sensing over a large area. Our results provided several new insights about system behavior and also opens the door for new characterization approaches. We documented that: (1) soil temperature (at >5 cm depth; critical for permafrost thaw) was decoupled from soil surface temperature and was influenced strongly by soil moisture, (2) NDVI and greenness index were highly correlated with both soil moisture and gross primary productivity (based on chamber flux data), and (3) surface deformation (which can be measured by InSAR) was a good proxy for thaw depth dynamics at non-inundated locations.

Disconnecting Consciousness: Is There a Common Anesthetic End Point?

PubMed

Hudetz, Anthony G; Mashour, George A

2016-11-01

A quest for a systems-level neuroscientific basis of anesthetic-induced loss and return of consciousness has been in the forefront of research for the past 2 decades. Recent advances toward the discovery of underlying mechanisms have been achieved using experimental electrophysiology, multichannel electroencephalography, magnetoencephalography, and functional magnetic resonance imaging. By the careful dosing of various volatile and IV anesthetic agents to the level of behavioral unresponsiveness, both specific and common changes in functional and effective connectivity across large-scale brain networks have been discovered and interpreted in the context of how the synthesis of neural information might be affected during anesthesia. The results of most investigations to date converge toward the conclusion that a common neural correlate of anesthetic-induced unresponsiveness is a consistent depression or functional disconnection of lateral frontoparietal networks, which are thought to be critical for consciousness of the environment. A reduction in the repertoire of brain states may contribute to the anesthetic disruption of large-scale information integration leading to unconsciousness. In future investigations, a systematic delineation of connectivity changes with multiple anesthetics using the same experimental design, and the same analytical method will be desirable. The critical neural events that account for the transition between responsive and unresponsive states should be assessed at similar anesthetic doses just below and above the loss or return of responsiveness. There will also be a need to identify a robust, sensitive, and reliable measure of information transfer. Ultimately, finding a behavior-independent measure of subjective experience that can track covert cognition in unresponsive subjects and a delineation of causal factors versus correlated events will be essential to understand the neuronal basis of human consciousness and unconsciousness.

Disconnecting Consciousness: Is There a Common Anesthetic End-Point?

PubMed Central

Hudetz, Anthony G.; Mashour, George A.

2016-01-01

A quest for a systems-level neuroscientific basis of anesthetic-induced loss and return of consciousness has been in the forefront of research of the last two decades. Recent advances toward the discovery of underlying mechanisms have been achieved using experimental electrophysiology, multichannel electroencephalography, magnetoencephalography, and functional magnetic resonance imaging. By the careful dosing of various volatile and IV anesthetic agents to the level of behavioral unresponsiveness, both specific and common changes in functional and effective connectivity across large-scale brain networks have been discovered and interpreted in the context of how the synthesis of neural information might be affected during anesthesia. The results of most investigations to date converge toward the conclusion that a common neural correlate of anesthetic-induced unresponsiveness is a consistent depression or functional disconnection of lateral frontoparietal networks, which are thought to be critical for consciousness of the environment. A reduction in the repertoire of brain states may contribute to the anesthetic disruption of large-scale information integration leading to unconsciousness. In future investigations, a systematic delineation of connectivity changes with multiple anesthetics using the same experimental design and the same analytical method will be desirable. The critical neural events that account for the transition between responsive and unresponsive states should be assessed at similar anesthetic doses just below and above the loss or return of responsiveness. There will also be a need to identify a robust, sensitive, and reliable measure of information transfer. Ultimately, finding a behavior-independent measure of subjective experience that can track covert cognition in unresponsive subjects and a delineation of causal factors vs. correlated events will be essential to understand the neuronal basis of human consciousness and unconsciousness. PMID:27331780

Robustness of Oscillatory Behavior in Correlated Networks

PubMed Central

Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki

2015-01-01

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

NASA Astrophysics Data System (ADS)

Guo, Yang; Sivalingam, Kantharuban; Valeev, Edward F.; Neese, Frank

2016-03-01

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling "partially contracted" NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient "electron pair prescreening" that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Function and disability in late life: comparison of the Late-Life Function and Disability Instrument to the Short-Form-36 and the London Handicap Scale.

PubMed

Dubuc, Nicole; Haley, Stephen; Ni, Pengsheng; Kooyoomjian, Jill; Jette, Alan

2004-03-18

We evaluated the Late-Life Function and Disability Instrument's (LLFDI) concurrent validity, comprehensiveness and precision by comparing it with the Short-Form-36 physical functioning (PF-10) and the London Handicap Scale (LHS). We administered the LLFDI, PF-10 and LHS to 75 community-dwelling adults (> 60 years of age). We used Pearson correlation coefficients to examine concurrent validity and Rasch analysis to compare the item hierarchies, content ranges and precision of the PF-10 and LLFDI function domains, and the LHS and the LLFDI disability domains. LLFDI Function (lower extremity scales) and PF-10 scores were highly correlated (r = 0.74 - 0.86, p > 0.001); moderate correlations were found between the LHS and the LLFDI Disability limitation (r = 0.66, p < 0.0001) and Disability frequency (r = 0.47, p < 0.001) scores. The LLFDI had a wider range of content coverage, less ceiling effects and better relative precision across the spectrum of function and disability than the PF-10 and the LHS. The LHS had slightly more content range and precision in the lower end of the disability scale than the LLFDI. The LLFDI is a more comprehensive and precise instrument compared to the PF-10 and LHS for assessing function and disability in community-dwelling older adults.

The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306

Renormalizable Quantum Field Theories in the Large -n Limit

NASA Astrophysics Data System (ADS)

Guruswamy, Sathya

1995-01-01

In this thesis, we study two examples of renormalizable quantum field theories in the large-N limit. Chapter one is a general introduction describing physical motivations for studying such theories. In chapter two, we describe the large-N method in field theory and discuss the pioneering work of 't Hooft in large-N two-dimensional Quantum Chromodynamics (QCD). In chapter three we study a spherically symmetric approximation to four-dimensional QCD ('spherical QCD'). We recast spherical QCD into a bilocal (constrained) theory of hadrons which in the large-N limit is equivalent to large-N spherical QCD for all energy scales. The linear approximation to this theory gives an eigenvalue equation which is the analogue of the well-known 't Hooft's integral equation in two dimensions. This eigenvalue equation is a scale invariant one and therefore leads to divergences in the theory. We give a non-perturbative renormalization prescription to cure this and obtain a beta function which shows that large-N spherical QCD is asymptotically free. In chapter four, we review the essentials of conformal field theories in two and higher dimensions, particularly in the context of critical phenomena. In chapter five, we study the O(N) non-linear sigma model on three-dimensional curved spaces in the large-N limit and show that there is a non-trivial ultraviolet stable critical point at which it becomes conformally invariant. We study this model at this critical point on examples of spaces of constant curvature and compute the mass gap in the theory, the free energy density (which turns out to be a universal function of the information contained in the geometry of the manifold) and the two-point correlation functions. The results we get give an indication that this model is an example of a three-dimensional analogue of a rational conformal field theory. A conclusion with a brief summary and remarks follows at the end.

A clinicopathological approach to the diagnosis of dementia

PubMed Central

Elahi, Fanny M.; Miller, Bruce L.

2018-01-01

The most definitive classification systems for dementia are based on the underlying pathology which, in turn, is categorized largely according to the observed accumulation of abnormal protein aggregates in neurons and glia. These aggregates perturb molecular processes, cellular functions and, ultimately, cell survival, with ensuing disruption of large-scale neural networks subserving cognitive, behavioural and sensorimotor functions. The functional domains affected and the evolution of deficits in these domains over time serve as footprints that the clinician can trace back with various levels of certainty to the underlying neuropathology. The process of phenotyping and syndromic classification has substantially improved over decades of careful clinicopathological correlation, and through the discovery of in vivo biomarkers of disease. Here, we present an overview of the salient features of the most common dementia subtypes — Alzheimer disease, vascular dementia, frontotemporal dementia and related syndromes, Lewy body dementias, and prion diseases — with an emphasis on neuropathology, relevant epidemiology, risk factors, and signature signs and symptoms. PMID:28708131

Halo histories versus Galaxy properties at z = 0 - I. The quenching of star formation

NASA Astrophysics Data System (ADS)

Tinker, Jeremy L.; Wetzel, Andrew R.; Conroy, Charlie; Mao, Yao-Yuan

2017-12-01

We test whether halo age and galaxy age are correlated at fixed halo and galaxy mass. The formation histories, and thus ages, of dark matter haloes correlate with their large-scale density ρ, an effect known as assembly bias. We test whether this correlation extends to galaxies by measuring the dependence of galaxy stellar age on ρ. To clarify the comparison between theory and observation, and to remove the strong environmental effects on satellites, we use galaxy group catalogues to identify central galaxies and measure their quenched fraction, fQ, as a function of large-scale environment. Models that match halo age to central galaxy age predict a strong positive correlation between fQ and ρ. However, we show that the amplitude of this effect depends on the definition of halo age: assembly bias is significantly reduced when removing the effects of splashback haloes - those haloes that are central but have passed through a larger halo or experienced strong tidal encounters. Defining age using halo mass at its peak value rather than current mass removes these effects. In Sloan Digital Sky Survey data, at M* ≳ 1010 M⊙ h-2, there is a ∼5 per cent increase in fQ from low-to-high densities, which is in agreement with predictions of dark matter haloes using peak halo mass. At lower stellar mass there is little to no correlation of fQ with ρ. For these galaxies, age matching is inconsistent with the data across the range of halo formation metrics that we tested. This implies that halo formation history has a small but statistically significant impact on quenching of star formation at high masses, while the quenching process in low-mass central galaxies is uncorrelated with halo formation history.

Concise calculation of the scaling function, exponents, and probability functional of the Edwards-Wilkinson equation with correlated noise

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

Yu, Y.; Pang, N.; Halpin-Healy, T.

1994-12-01

The linear Langevin equation proposed by Edwards and Wilkinson [Proc. R. Soc. London A 381, 17 (1982)] is solved in closed form for noise of arbitrary space and time correlation. Furthermore, the temporal development of the full probability functional describing the height fluctuations is derived exactly, exhibiting an interesting evolution between two distinct Gaussian forms. We determine explicitly the dynamic scaling function for the interfacial width for any given initial condition, isolate the early-time behavior, and discover an invariance that was unsuspected in this problem of arbitrary spatiotemporal noise.

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Large-eddy simulations of a forced homogeneous isotropic turbulence with polymer additives

NASA Astrophysics Data System (ADS)

Wang, Lu; Cai, Wei-Hua; Li, Feng-Chen

2014-03-01

Large-eddy simulations (LES) based on the temporal approximate deconvolution model were performed for a forced homogeneous isotropic turbulence (FHIT) with polymer additives at moderate Taylor Reynolds number. Finitely extensible nonlinear elastic in the Peterlin approximation model was adopted as the constitutive equation for the filtered conformation tensor of the polymer molecules. The LES results were verified through comparisons with the direct numerical simulation results. Using the LES database of the FHIT in the Newtonian fluid and the polymer solution flows, the polymer effects on some important parameters such as strain, vorticity, drag reduction, and so forth were studied. By extracting the vortex structures and exploring the flatness factor through a high-order correlation function of velocity derivative and wavelet analysis, it can be found that the small-scale vortex structures and small-scale intermittency in the FHIT are all inhibited due to the existence of the polymers. The extended self-similarity scaling law in the polymer solution flow shows no apparent difference from that in the Newtonian fluid flow at the currently simulated ranges of Reynolds and Weissenberg numbers.

Measuring fatigue in people living with HIV/AIDS: psychometric characteristics of the HIV-Related Fatigue Scale

PubMed Central

BW, Pence; Barroso, J.; Leserman, J.; Harmon, J.L.; Salahuddin, N.

2008-01-01

In the era of life-prolonging antiretroviral therapy, chronic fatigue is one of the most prevalent and disabling symptoms of people living with HIV/AIDS, yet its measurement remains challenging. No instruments have been developed specifically to describe HIV-related fatigue. We assessed the reliability and construct validity of the HIV-Related Fatigue Scale (HRFS), a 56-item self-report instrument developed through formative qualitative research and designed to measure the intensity and consequences of fatigue as well as the circumstances surrounding fatigue in people living with HIV. The HRFS has three main scales, which measure fatigue intensity, the responsiveness of fatigue to circumstances and fatigue-related impairment of functioning. The functioning scale can be further divided into subscales measuring impairment of activities of daily living, impairment of mental functioning and impairment of social functioning. Each scale demonstrated high internal consistency (Cronbach’s alpha=0.93, 0.91 and 0.97 for the intensity, responsiveness and functioning scales, respectively). The HRFS scales also demonstrated satisfactory convergent validity when compared to other fatigue measures. HIV-Related Fatigue Scales were moderately correlated with quality of nighttime sleep (rho = 0.46, 0.47 and 0.35) but showed only weak correlations with daytime sleepiness (rho = 0.20, 0.33 and 0.18). The scales were also moderately correlated with general mental and physical health as measured by the SF-36 Health Survey (rho ranged from 0.30 to 0.68 across the 8 SF-36 subscales with most >0.40). The HRFS is a promising tool to help facilitate research on the prevalence, etiology and consequences of fatigue in people living with HIV. PMID:18608084

Measuring fatigue in people living with HIV/AIDS: psychometric characteristics of the HIV-related fatigue scale.

PubMed

Pence, B W; Barroso, J; Leserman, J; Harmon, J L; Salahuddin, N

2008-08-01

In the era of life-prolonging antiretroviral therapy, chronic fatigue is one of the most prevalent and disabling symptoms of people living with HIV/AIDS, yet its measurement remains challenging. No instruments have been developed specifically to describe HIV-related fatigue. We assessed the reliability and construct validity of the HIV-Related Fatigue Scale (HRFS), a 56-item self-report instrument developed through formative qualitative research and designed to measure the intensity and consequences of fatigue as well as the circumstances surrounding fatigue in people living with HIV. The HRFS has three main scales, which measure fatigue intensity, the responsiveness of fatigue to circumstances and fatigue-related impairment of functioning. The functioning scale can be further divided into subscales measuring impairment of activities of daily living, impairment of mental functioning and impairment of social functioning. Each scale demonstrated high internal consistency (Cronbach's alpha=0.93, 0.91 and 0.97 for the intensity, responsiveness and functioning scales, respectively). The HRFS scales also demonstrated satisfactory convergent validity when compared to other fatigue measures. HIV-Related Fatigue Scales were moderately correlated with quality of nighttime sleep (rho=0.46, 0.47 and 0.35) but showed only weak correlations with daytime sleepiness (rho=0.20, 0.33 and 0.18). The scales were also moderately correlated with general mental and physical health as measured by the SF-36 Health Survey (rho ranged from 0.30 to 0.68 across the 8 SF-36 subscales with most >0.40). The HRFS is a promising tool to help facilitate research on the prevalence, etiology and consequences of fatigue in people living with HIV.

Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system

NASA Astrophysics Data System (ADS)

Chen, Ligang; Liang, Xin-Zhong; DeWitt, David; Samel, Arthur N.; Wang, Julian X. L.

2016-02-01

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.

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