Analyses of multi-pion Hanbury Brown–Twiss correlations for the pion-emitting sources with Bose–Einstein condensation

NASA Astrophysics Data System (ADS)

Bary, Ghulam; Ru, Peng; Zhang, Wei-Ning

2018-06-01

We calculate the three- and four-particle correlations of identical pions in an evolving pion gas (EPG) model with Bose–Einstein condensation. The multi-pion correlation functions in the EPG model are analyzed in different momentum intervals and compared with the experimental data for Pb–Pb collisions at \\sqrt{{s}{NN}}=2.76 {TeV}. It is found that the multi-pion correlation functions and cumulant correlation functions are sensitive to the condensation fraction of the EPG sources in the low average transverse-momentum intervals of the three and four pions. The model results of the multi-pion correlations are consistent with the experimental data in a considerable degree, which gives a source condensation fraction between 16% and 47%.

Exact thermal density functional theory for a model system: Correlation components and accuracy of the zero-temperature exchange-correlation approximation

DOE PAGES

Smith, J. C.; Pribram-Jones, A.; Burke, K.

2016-06-14

Thermal density functional theory calculations often use the Mermin-Kohn-Sham scheme, but employ ground-state approximations to the exchange-correlation (XC) free energy. In the simplest solvable nontrivial model, an asymmetric Hubbard dimer, we calculate the exact many-body energies and the exact Mermin-Kohn-Sham functionals for this system and extract the exact XC free energy. For moderate temperatures and weak correlation, we find this approximation to be excellent. Here we extract various exact free-energy correlation components and the exact adiabatic connection formula.

Exact thermal density functional theory for a model system: Correlation components and accuracy of the zero-temperature exchange-correlation approximation

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

Smith, J. C.; Pribram-Jones, A.; Burke, K.

Thermal density functional theory calculations often use the Mermin-Kohn-Sham scheme, but employ ground-state approximations to the exchange-correlation (XC) free energy. In the simplest solvable nontrivial model, an asymmetric Hubbard dimer, we calculate the exact many-body energies and the exact Mermin-Kohn-Sham functionals for this system and extract the exact XC free energy. For moderate temperatures and weak correlation, we find this approximation to be excellent. Here we extract various exact free-energy correlation components and the exact adiabatic connection formula.

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.

Joint statistics of strongly correlated neurons via dimensionality reduction

NASA Astrophysics Data System (ADS)

Deniz, Taşkın; Rotter, Stefan

2017-06-01

The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input.

Plasma fluctuations as Markovian noise.

PubMed

Li, B; Hazeltine, R D; Gentle, K W

2007-12-01

Noise theory is used to study the correlations of stationary Markovian fluctuations that are homogeneous and isotropic in space. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations of random fluctuations are modeled by the exponential decay. Based on these models, the temporal correlations of random fluctuations, such as the correlation function and the power spectrum, are calculated. We find that the diffusion process can give rise to the decay of the correlation function and a broad frequency spectrum of random fluctuations. We also find that the transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from the tokamak and helimak experiments.

Rotational Invariance of the 2d Spin - Spin Correlation Function

NASA Astrophysics Data System (ADS)

Pinson, Haru

2012-09-01

At the critical temperature in the 2d Ising model on the square lattice, we establish the rotational invariance of the spin-spin correlation function using the asymptotics of the spin-spin correlation function along special directions (McCoy and Wu in the two dimensional Ising model. Harvard University Press, Cambridge, 1973) and the finite difference Hirota equation for which the spin-spin correlation function is shown to satisfy (Perk in Phys Lett A 79:3-5, 1980; Perk in Proceedings of III international symposium on selected topics in statistical mechanics, Dubna, August 22-26, 1984, JINR, vol II, pp 138-151, 1985).

Effects of soot absorption coefficient-Planck function correlation on radiative heat transfer in oxygen-enriched propane turbulent diffusion flame

NASA Astrophysics Data System (ADS)

Consalvi, J. L.; Nmira, F.

2016-03-01

The main objective of this article is to quantify the influence of the soot absorption coefficient-Planck function correlation on radiative loss and flame structure in an oxygen-enhanced propane turbulent diffusion flame. Calculations were run with and without accounting for this correlation by using a standard k-ε model and the steady laminar flamelet model (SLF) coupled to a joint Probability Density Function (PDF) of mixture fraction, enthalpy defect, scalar dissipation rate, and soot quantities. The PDF transport equation is solved by using a Stochastic Eulerian Field (SEF) method. The modeling of soot production is carried out by using a flamelet-based semi-empirical acetylene/benzene soot model. Radiative heat transfer is modeled by using a wide band correlated-k model and turbulent radiation interactions (TRI) are accounted for by using the Optically-Thin Fluctuation Approximation (OTFA). Predicted soot volume fraction, radiant wall heat flux distribution and radiant fraction are in good agreement with the available experimental data. Model results show that soot absorption coefficient and Planck function are negatively correlated in the region of intense soot emission. Neglecting this correlation is found to increase significantly the radiative loss leading to a substantial impact on flame structure in terms of mean and rms values of temperature. In addition mean and rms values of soot volume fraction are found to be less sensitive to the correlation than temperature since soot formation occurs mainly in a region where its influence is low.

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

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

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

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

From quantum affine groups to the exact dynamical correlation function of the Heisenberg model

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

Bougourzi, A.H.; Couture, M.; Kacir, M.

1997-01-20

The exact form factors of the Heisenberg models XXX and XXZ have been recently computed through the quantum affine symmetry of XXZ model in the thermodynamic limit. The authors use them to derive an exact formula for the contribution of two spinons to the dynamical correlation function of XXX model at zero temperature.

Bacterial genomes lacking long-range correlations may not be modeled by low-order Markov chains: the role of mixing statistics and frame shift of neighboring genes.

PubMed

Cocho, Germinal; Miramontes, Pedro; Mansilla, Ricardo; Li, Wentian

2014-12-01

We examine the relationship between exponential correlation functions and Markov models in a bacterial genome in detail. Despite the well known fact that Markov models generate sequences with correlation function that decays exponentially, simply constructed Markov models based on nearest-neighbor dimer (first-order), trimer (second-order), up to hexamer (fifth-order), and treating the DNA sequence as being homogeneous all fail to predict the value of exponential decay rate. Even reading-frame-specific Markov models (both first- and fifth-order) could not explain the fact that the exponential decay is very slow. Starting with the in-phase coding-DNA-sequence (CDS), we investigated correlation within a fixed-codon-position subsequence, and in artificially constructed sequences by packing CDSs with out-of-phase spacers, as well as altering CDS length distribution by imposing an upper limit. From these targeted analyses, we conclude that the correlation in the bacterial genomic sequence is mainly due to a mixing of heterogeneous statistics at different codon positions, and the decay of correlation is due to the possible out-of-phase between neighboring CDSs. There are also small contributions to the correlation from bases at the same codon position, as well as by non-coding sequences. These show that the seemingly simple exponential correlation functions in bacterial genome hide a complexity in correlation structure which is not suitable for a modeling by Markov chain in a homogeneous sequence. Other results include: use of the (absolute value) second largest eigenvalue to represent the 16 correlation functions and the prediction of a 10-11 base periodicity from the hexamer frequencies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling of two-particle femtoscopic correlations at top RHIC energy

NASA Astrophysics Data System (ADS)

Ermakov, N.; Nigmatkulov, G.

2017-01-01

The spatial and temporal characteristics of particle emitting source produced in particle and/or nuclear collisions can be measured by using two-particle femtoscopic correlations. These correlations arise due to quantum statistics, Coulomb and strong final state interactions. In this paper we report on the calculations of like-sign pion femtoscopic correlations produced in p+p, p+Au, d+Au, Au+Au at top RHIC energy using Ultra Relativistic Quantum Molecular Dynamics Model (UrQMD). Three-dimensional correlation functions are constructed using the Bertsch-Pratt parametrization of the two-particle relative momentum. The correlation functions are studied in several transverse mass ranges. The emitting source radii of charged pions, Rout, Rside, Rlong , are obtained from Gaussian fit to the correlation functions and compared to data from the STAR and PHENIX experiments.

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

NASA Astrophysics Data System (ADS)

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

2006-04-01

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

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

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

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

2006-04-15

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

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

Williams, Brian J.; Marcy, Peter W.

We will investigate the use of derivative information in complex computer model emulation when the correlation function is of the compactly supported Bohman class. To this end, a Gaussian process model similar to that used by Kaufman et al. (2011) is extended to a situation where first partial derivatives in each dimension are calculated at each input site (i.e. using gradients). A simulation study in the ten-dimensional case is conducted to assess the utility of the Bohman correlation function against strictly positive correlation functions when a high degree of sparsity is induced.

Compact two-electron wave function for bond dissociation and Van der Waals interactions: a natural amplitude assessment.

PubMed

Giesbertz, Klaas J H; van Leeuwen, Robert

2014-05-14

Electron correlations in molecules can be divided in short range dynamical correlations, long range Van der Waals type interactions, and near degeneracy static correlations. In this work, we analyze for a one-dimensional model of a two-electron system how these three types of correlations can be incorporated in a simple wave function of restricted functional form consisting of an orbital product multiplied by a single correlation function f (r12) depending on the interelectronic distance r12. Since the three types of correlations mentioned lead to different signatures in terms of the natural orbital (NO) amplitudes in two-electron systems, we make an analysis of the wave function in terms of the NO amplitudes for a model system of a diatomic molecule. In our numerical implementation, we fully optimize the orbitals and the correlation function on a spatial grid without restrictions on their functional form. Due to this particular form of the wave function, we can prove that none of the amplitudes vanishes and moreover that it displays a distinct sign pattern and a series of avoided crossings as a function of the bond distance in agreement with the exact solution. This shows that the wave function ansatz correctly incorporates the long range Van der Waals interactions. We further show that the approximate wave function gives an excellent binding curve and is able to describe static correlations. We show that in order to do this the correlation function f (r12) needs to diverge for large r12 at large internuclear distances while for shorter bond distances it increases as a function of r12 to a maximum value after which it decays exponentially. We further give a physical interpretation of this behavior.

On the effect of velocity gradients on the depth of correlation in μPIV

NASA Astrophysics Data System (ADS)

Mustin, B.; Stoeber, B.

2016-03-01

The present work revisits the effect of velocity gradients on the depth of the measurement volume (depth of correlation) in microscopic particle image velocimetry (μPIV). General relations between the μPIV weighting functions and the local correlation function are derived from the original definition of the weighting functions. These relations are used to investigate under which circumstances the weighting functions are related to the curvature of the local correlation function. Furthermore, this work proposes a modified definition of the depth of correlation that leads to more realistic results than previous definitions for the case when flow gradients are taken into account. Dimensionless parameters suitable to describe the effect of velocity gradients on μPIV cross correlation are derived and visual interpretations of these parameters are proposed. We then investigate the effect of the dimensionless parameters on the weighting functions and the depth of correlation for different flow fields with spatially constant flow gradients and with spatially varying gradients. Finally this work demonstrates that the results and dimensionless parameters are not strictly bound to a certain model for particle image intensity distributions but are also meaningful when other models for particle images are used.

Exchange and correlation in positronium-molecule scattering

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Cumulants and correlation functions versus the QCD phase diagram

DOE PAGES

Bzdak, Adam; Koch, Volker; Strodthoff, Nils

2017-05-12

Here, we discuss the relation of particle number cumulants and correlation functions. It is argued that measuring couplings of the genuine multiparticle correlation functions could provide cleaner information on possible nontrivial dynamics in heavy-ion collisions. We also extract integrated multiproton correlation functions from the presently available experimental data on proton cumulants. We find that the STAR data contain significant four-proton correlations, at least at the lower energies, with indication of changing dynamics in central collisions. We also find that these correlations are rather long ranged in rapidity. Finally, using the Ising model, we demonstrate how the signs of the multiprotonmore » correlation functions may be used to exclude certain regions of the phase diagram close to the critical point.« less

Cumulants and correlation functions versus the QCD phase diagram

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

Bzdak, Adam; Koch, Volker; Strodthoff, Nils

Here, we discuss the relation of particle number cumulants and correlation functions. It is argued that measuring couplings of the genuine multiparticle correlation functions could provide cleaner information on possible nontrivial dynamics in heavy-ion collisions. We also extract integrated multiproton correlation functions from the presently available experimental data on proton cumulants. We find that the STAR data contain significant four-proton correlations, at least at the lower energies, with indication of changing dynamics in central collisions. We also find that these correlations are rather long ranged in rapidity. Finally, using the Ising model, we demonstrate how the signs of the multiprotonmore » correlation functions may be used to exclude certain regions of the phase diagram close to the critical point.« less

A cumulant functional for static and dynamic correlation

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

Hollett, Joshua W., E-mail: j.hollett@uwinnipeg.ca; Department of Chemistry, University of Manitoba, Winnipeg, Manitoba R3T 2N2; Hosseini, Hessam

A functional for the cumulant energy is introduced. The functional is composed of a pair-correction and static and dynamic correlation energy components. The pair-correction and static correlation energies are functionals of the natural orbitals and the occupancy transferred between near-degenerate orbital pairs, rather than the orbital occupancies themselves. The dynamic correlation energy is a functional of the statically correlated on-top two-electron density. The on-top density functional used in this study is the well-known Colle-Salvetti functional. Using the cc-pVTZ basis set, the functional effectively models the bond dissociation of H{sub 2}, LiH, and N{sub 2} with equilibrium bond lengths and dissociationmore » energies comparable to those provided by multireference second-order perturbation theory. The performance of the cumulant functional is less impressive for HF and F{sub 2}, mainly due to an underestimation of the dynamic correlation energy by the Colle-Salvetti functional.« less

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

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

Morse, David C.

2006-10-15

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

Higher order correlations of IRAS galaxies

NASA Technical Reports Server (NTRS)

Meiksin, Avery; Szapudi, Istvan; Szalay, Alexander

1992-01-01

The higher order irreducible angular correlation functions are derived up to the eight-point function, for a sample of 4654 IRAS galaxies, flux-limited at 1.2 Jy in the 60 microns band. The correlations are generally found to be somewhat weaker than those for the optically selected galaxies, consistent with the visual impression of looser clusters in the IRAS sample. It is found that the N-point correlation functions can be expressed as the symmetric sum of products of N - 1 two-point functions, although the correlations above the four-point function are consistent with zero. The coefficients are consistent with the hierarchical clustering scenario as modeled by Hamilton and by Schaeffer.

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

PubMed

Chen, Yongsheng; Persaud, Bhagwant

2014-09-01

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

Black holes from large N singlet models

NASA Astrophysics Data System (ADS)

Amado, Irene; Sundborg, Bo; Thorlacius, Larus; Wintergerst, Nico

2018-03-01

The emergent nature of spacetime geometry and black holes can be directly probed in simple holographic duals of higher spin gravity and tensionless string theory. To this end, we study time dependent thermal correlation functions of gauge invariant observables in suitably chosen free large N gauge theories. At low temperature and on short time scales the correlation functions encode propagation through an approximate AdS spacetime while interesting departures emerge at high temperature and on longer time scales. This includes the existence of evanescent modes and the exponential decay of time dependent boundary correlations, both of which are well known indicators of bulk black holes in AdS/CFT. In addition, a new time scale emerges after which the correlation functions return to a bulk thermal AdS form up to an overall temperature dependent normalization. A corresponding length scale was seen in equal time correlation functions in the same models in our earlier work.

Cross-section fluctuations in chaotic scattering systems.

PubMed

Ericson, Torleif E O; Dietz, Barbara; Richter, Achim

2016-10-01

Exact analytical expressions for the cross-section correlation functions of chaotic scattering systems have hitherto been derived only under special conditions. The objective of the present article is to provide expressions that are applicable beyond these restrictions. The derivation is based on a statistical model of Breit-Wigner type for chaotic scattering amplitudes which has been shown to describe the exact analytical results for the scattering (S)-matrix correlation functions accurately. Our results are given in the energy and in the time representations and apply in the whole range from isolated to overlapping resonances. The S-matrix contributions to the cross-section correlations are obtained in terms of explicit irreducible and reducible correlation functions. Consequently, the model can be used for a detailed exploration of the key features of the cross-section correlations and the underlying physical mechanisms. In the region of isolated resonances, the cross-section correlations contain a dominant contribution from the self-correlation term. For narrow states the self-correlations originate predominantly from widely spaced states with exceptionally large partial width. In the asymptotic region of well-overlapping resonances, the cross-section autocorrelation functions are given in terms of the S-matrix autocorrelation functions. For inelastic correlations, in particular, the Ericson fluctuations rapidly dominate in that region. Agreement with known analytical and experimental results is excellent.

Frequency and Wavevector Dependence of the Atomic Level Stress-Stress Correlation Function in a Model Supercooled Liquid

NASA Astrophysics Data System (ADS)

Levashov, Valentin A.; Morris, James R.; Egami, Takeshi

2012-02-01

Temporal and spatial correlations among the local atomic level shear stresses were studied for a model liquid iron by molecular dynamics simulation [PRL 106,115703]. Integration over time and space of the shear stress correlation function F(r,t) yields viscosity via Green-Kubo relation. The stress correlation function in time and space F(r,t) was Fourier transformed to study the dependence on frequency, E, and wave vector, Q. The results, F(Q,E), showed damped shear stress waves propagating in the liquid for small Q at high and low temperatures. We also observed additional diffuse feature that appears as temperature is reduced below crossover temperature of potential energy landscape at relatively low frequencies at small Q. We suggest that this additional feature might be related to dynamic heterogeneity and boson peaks. We also discuss a relation between the time-scale of the stress-stress correlation function and the alpha-relaxation time of the intermediate self-scattering function S(Q,E).

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.

Characterization of impulse noise and analysis of its effect upon correlation receivers

NASA Technical Reports Server (NTRS)

Houts, R. C.; Moore, J. D.

1971-01-01

A noise model is formulated to describe the impulse noise in many digital systems. A simplified model, which assumes that each noise burst contains a randomly weighted version of the same basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. A procedure is established for extending the results for the simplified noise model to the general model. Unlike the performance results for Gaussian noise, it is shown that for impulse noise the error performance is affected by the choice of signal-set basis functions and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy.

Optical Implementation Of The Synthetic Discrimination Function

NASA Astrophysics Data System (ADS)

Butler, Steve; Riggins, James

1985-01-01

Computer-generated holograms of geometrical shape and synthetic discriminant function (SDF) matched filters are modeled and produced. The models include ideal correlations and Allebach-Keegan binary holograms. A distinction between Phase-Only-Information and Phase-Only-Material Filters is demonstrated. Signal-to-noise and efficiency measurements were made on the resultant correlation planes.

Hepatic function imaging using dynamic Gd-EOB-DTPA enhanced MRI and pharmacokinetic modeling.

PubMed

Ning, Jia; Yang, Zhiying; Xie, Sheng; Sun, Yongliang; Yuan, Chun; Chen, Huijun

2017-10-01

To determine whether pharmacokinetic modeling parameters with different output assumptions of dynamic contrast-enhanced MRI (DCE-MRI) using Gd-EOB-DTPA correlate with serum-based liver function tests, and compare the goodness of fit of the different output assumptions. A 6-min DCE-MRI protocol was performed in 38 patients. Four dual-input two-compartment models with different output assumptions and a published one-compartment model were used to calculate hepatic function parameters. The Akaike information criterion fitting error was used to evaluate the goodness of fit. Imaging-based hepatic function parameters were compared with blood chemistry using correlation with multiple comparison correction. The dual-input two-compartment model assuming venous flow equals arterial flow plus portal venous flow and no bile duct output better described the liver tissue enhancement with low fitting error and high correlation with blood chemistry. The relative uptake rate Kir derived from this model was found to be significantly correlated with direct bilirubin (r = -0.52, P = 0.015), prealbumin concentration (r = 0.58, P = 0.015), and prothrombin time (r = -0.51, P = 0.026). It is feasible to evaluate hepatic function by proper output assumptions. The relative uptake rate has the potential to serve as a biomarker of function. Magn Reson Med 78:1488-1495, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Two-particle correlation function and dihadron correlation approach

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

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

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

Construction of exchange-correlation functionals through interpolation between the non-interacting and the strong-correlation limit

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

Zhou, Yongxi; Ernzerhof, Matthias, E-mail: Matthias.Ernzerhof@UMontreal.ca; Bahmann, Hilke

Drawing on the adiabatic connection of density functional theory, exchange-correlation functionals of Kohn-Sham density functional theory are constructed which interpolate between the extreme limits of the electron-electron interaction strength. The first limit is the non-interacting one, where there is only exchange. The second limit is the strong correlated one, characterized as the minimum of the electron-electron repulsion energy. The exchange-correlation energy in the strong-correlation limit is approximated through a model for the exchange-correlation hole that is referred to as nonlocal-radius model [L. O. Wagner and P. Gori-Giorgi, Phys. Rev. A 90, 052512 (2014)]. Using the non-interacting and strong-correlated extremes, variousmore » interpolation schemes are presented that yield new approximations to the adiabatic connection and thus to the exchange-correlation energy. Some of them rely on empiricism while others do not. Several of the proposed approximations yield the exact exchange-correlation energy for one-electron systems where local and semi-local approximations often fail badly. Other proposed approximations generalize existing global hybrids by using a fraction of the exchange-correlation energy in the strong-correlation limit to replace an equal fraction of the semi-local approximation to the exchange-correlation energy in the strong-correlation limit. The performance of the proposed approximations is evaluated for molecular atomization energies, total atomic energies, and ionization potentials.« less

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

Representing uncertainty in objective functions: extension to include the influence of serial correlation

NASA Astrophysics Data System (ADS)

Croke, B. F.

2008-12-01

The role of performance indicators is to give an accurate indication of the fit between a model and the system being modelled. As all measurements have an associated uncertainty (determining the significance that should be given to the measurement), performance indicators should take into account uncertainties in the observed quantities being modelled as well as in the model predictions (due to uncertainties in inputs, model parameters and model structure). In the presence of significant uncertainty in observed and modelled output of a system, failure to adequately account for variations in the uncertainties means that the objective function only gives a measure of how well the model fits the observations, not how well the model fits the system being modelled. Since in most cases, the interest lies in fitting the system response, it is vital that the objective function(s) be designed to account for these uncertainties. Most objective functions (e.g. those based on the sum of squared residuals) assume homoscedastic uncertainties. If model contribution to the variations in residuals can be ignored, then transformations (e.g. Box-Cox) can be used to remove (or at least significantly reduce) heteroscedasticity. An alternative which is more generally applicable is to explicitly represent the uncertainties in the observed and modelled values in the objective function. Previous work on this topic addressed the modifications to standard objective functions (Nash-Sutcliffe efficiency, RMSE, chi- squared, coefficient of determination) using the optimal weighted averaging approach. This paper extends this previous work; addressing the issue of serial correlation. A form for an objective function that includes serial correlation will be presented, and the impact on model fit discussed.

A flexible model for correlated medical costs, with application to medical expenditure panel survey data.

PubMed

Chen, Jinsong; Liu, Lei; Shih, Ya-Chen T; Zhang, Daowen; Severini, Thomas A

2016-03-15

We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method. Copyright © 2015 John Wiley & Sons, Ltd.

Discriminative analysis of early Alzheimer's disease based on two intrinsically anti-correlated networks with resting-state fMRI.

PubMed

Wang, Kun; Jiang, Tianzi; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Liu, Zhening

2006-01-01

In this work, we proposed a discriminative model of Alzheimer's disease (AD) on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model used the correlation/anti-correlation coefficients of two intrinsically anti-correlated networks in resting brains, which have been suggested by two recent studies, as the feature of classification. Pseudo-Fisher Linear Discriminative Analysis (pFLDA) was then performed on the feature space and a linear classifier was generated. Using leave-one-out (LOO) cross validation, our results showed a correct classification rate of 83%. We also compared the proposed model with another one based on the whole brain functional connectivity. Our proposed model outperformed the other one significantly, and this implied that the two intrinsically anti-correlated networks may be a more susceptible part of the whole brain network in the early stage of AD.

Interferometry correlations in central p+Pb collisions

NASA Astrophysics Data System (ADS)

Bożek, Piotr; Bysiak, Sebastian

2018-01-01

We present results on interferometry correlations for pions emitted in central p+Pb collisions at √{s_{NN}}=5.02 TeV in a 3+1-dimensional viscous hydrodynamic model with initial conditions from the Glauber Monte Carlo model. The correlation function is calculated as a function of the pion pair rapidity. The extracted interferometry radii show a weak rapidity dependence, reflecting the lack of boost invariance of the pion distribution. A cross term between the out and long directions is found to be nonzero. The results obtained in the hydrodynamic model are in fair agreement with recent data of the ATLAS Collaboration.

Accurate calculation and modeling of the adiabatic connection in density functional theory

NASA Astrophysics Data System (ADS)

Teale, A. M.; Coriani, S.; Helgaker, T.

2010-04-01

Using a recently implemented technique for the calculation of the adiabatic connection (AC) of density functional theory (DFT) based on Lieb maximization with respect to the external potential, the AC is studied for atoms and molecules containing up to ten electrons: the helium isoelectronic series, the hydrogen molecule, the beryllium isoelectronic series, the neon atom, and the water molecule. The calculation of AC curves by Lieb maximization at various levels of electronic-structure theory is discussed. For each system, the AC curve is calculated using Hartree-Fock (HF) theory, second-order Møller-Plesset (MP2) theory, coupled-cluster singles-and-doubles (CCSD) theory, and coupled-cluster singles-doubles-perturbative-triples [CCSD(T)] theory, expanding the molecular orbitals and the effective external potential in large Gaussian basis sets. The HF AC curve includes a small correlation-energy contribution in the context of DFT, arising from orbital relaxation as the electron-electron interaction is switched on under the constraint that the wave function is always a single determinant. The MP2 and CCSD AC curves recover the bulk of the dynamical correlation energy and their shapes can be understood in terms of a simple energy model constructed from a consideration of the doubles-energy expression at different interaction strengths. Differentiation of this energy expression with respect to the interaction strength leads to a simple two-parameter doubles model (AC-D) for the AC integrand (and hence the correlation energy of DFT) as a function of the interaction strength. The structure of the triples-energy contribution is considered in a similar fashion, leading to a quadratic model for the triples correction to the AC curve (AC-T). From a consideration of the structure of a two-level configuration-interaction (CI) energy expression of the hydrogen molecule, a simple two-parameter CI model (AC-CI) is proposed to account for the effects of static correlation on the AC. When parametrized in terms of the same input data, the AC-CI model offers improved performance over the corresponding AC-D model, which is shown to be the lowest-order contribution to the AC-CI model. The utility of the accurately calculated AC curves for the analysis of standard density functionals is demonstrated for the BLYP exchange-correlation functional and the interaction-strength-interpolation (ISI) model AC integrand. From the results of this analysis, we investigate the performance of our proposed two-parameter AC-D and AC-CI models when a simple density functional for the AC at infinite interaction strength is employed in place of information at the fully interacting point. The resulting two-parameter correlation functionals offer a qualitatively correct behavior of the AC integrand with much improved accuracy over previous attempts. The AC integrands in the present work are recommended as a basis for further work, generating functionals that avoid spurious error cancellations between exchange and correlation energies and give good accuracy for the range of densities and types of correlation contained in the systems studied here.

Higher-Order Statistical Correlations and Mutual Information Among Particles in a Quantum Well

NASA Astrophysics Data System (ADS)

Yépez, V. S.; Sagar, R. P.; Laguna, H. G.

2017-12-01

The influence of wave function symmetry on statistical correlation is studied for the case of three non-interacting spin-free quantum particles in a unidimensional box, in position and in momentum space. Higher-order statistical correlations occurring among the three particles in this quantum system is quantified via higher-order mutual information and compared to the correlation between pairs of variables in this model, and to the correlation in the two-particle system. The results for the higher-order mutual information show that there are states where the symmetric wave functions are more correlated than the antisymmetric ones with same quantum numbers. This holds in position as well as in momentum space. This behavior is opposite to that observed for the correlation between pairs of variables in this model, and the two-particle system, where the antisymmetric wave functions are in general more correlated. These results are also consistent with those observed in a system of three uncoupled oscillators. The use of higher-order mutual information as a correlation measure, is monitored and examined by considering a superposition of states or systems with two Slater determinants.

Peculiar velocity effect on galaxy correlation functions in nonlinear clustering regime

NASA Astrophysics Data System (ADS)

Matsubara, Takahiko

1994-03-01

We studied the distortion of the apparent distribution of galaxies in redshift space contaminated by the peculiar velocity effect. Specifically we obtained the expressions for N-point correlation functions in redshift space with given functional form for velocity distribution f(v) and evaluated two- and three-point correlation functions quantitatively. The effect of velocity correlations is also discussed. When the two-point correlation function in real space has a power-law form, Xir(r) is proportional to r(-gamma), the redshift-space counterpart on small scales also has a power-law form but with an increased power-law index: Xis(s) is proportional to s(1-gamma). When the three-point correlation function has the hierarchical form and the two-point correlation function has the power-law form in real space, the hierarchical form of the three-point correlation function is almost preserved in redshift space. The above analytic results are compared with the direct analysis based on N-body simulation data for cold dark matter models. Implications on the hierarchical clustering ansatz are discussed in detail.

Functional Additive Mixed Models

PubMed Central

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

2014-01-01

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

Functional Additive Mixed Models.

PubMed

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

2015-04-01

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

Nuclear relaxation and critical fluctuations in membranes containing cholesterol

NASA Astrophysics Data System (ADS)

McConnell, Harden

2009-04-01

Nuclear resonance frequencies in bilayer membranes depend on lipid composition. Our calculations describe the combined effects of composition fluctuations and diffusion on nuclear relaxation near a miscibility critical point. Both tracer and gradient diffusion are included. The calculations involve correlation functions and a correlation length ξ =ξ0T/(T -Tc), where T -Tc is temperature above the critical temperature and ξ0 is a parameter of molecular length. Several correlation functions are examined, each of which is related in some degree to the Ising model correlation function. These correlation functions are used in the calculation of transverse deuterium relaxation rates in magic angle spinning and quadrupole echo experiments. The calculations are compared with experiments that report maxima in deuterium and proton nuclear relaxation rates at the critical temperature [Veatch et al., Proc. Nat. Acad. Sci. U.S.A. 104, 17650 (2007)]. One Ising-model-related correlation function yields a maximum 1/T2 relaxation rate at the critical temperature for both magic angle spinning and quadrupole echo experiments. The calculated rates at the critical temperature are close to the experimental rates. The rate maxima involve relatively rapid tracer diffusion in a static composition gradient over distances of up to 10-100 nm.

Statistical microeconomics and commodity prices: theory and empirical results.

PubMed

Baaquie, Belal E

2016-01-13

A review is made of the statistical generalization of microeconomics by Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)), where the market price of every traded commodity, at each instant of time, is considered to be an independent random variable. The dynamics of commodity market prices is given by the unequal time correlation function and is modelled by the Feynman path integral based on an action functional. The correlation functions of the model are defined using the path integral. The existence of the action functional for commodity prices that was postulated to exist in Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)) has been empirically ascertained in Baaquie et al. (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). The model's action functionals for different commodities has been empirically determined and calibrated using the unequal time correlation functions of the market commodity prices using a perturbation expansion (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). Nine commodities drawn from the energy, metal and grain sectors are empirically studied and their auto-correlation for up to 300 days is described by the model to an accuracy of R(2)>0.90-using only six parameters. © 2015 The Author(s).

Inter-species activity correlations reveal functional correspondences between monkey and human brain areas

PubMed Central

Mantini, Dante; Hasson, Uri; Betti, Viviana; Perrucci, Mauro G.; Romani, Gian Luca; Corbetta, Maurizio; Orban, Guy A.; Vanduffel, Wim

2012-01-01

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. In cases where functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assess similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by means of temporal correlation. Using natural vision data, we reveal regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This novel framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models. PMID:22306809

Describing a Strongly Correlated Model System with Density Functional Theory.

PubMed

Kong, Jing; Proynov, Emil; Yu, Jianguo; Pachter, Ruth

2017-07-06

The linear chain of hydrogen atoms, a basic prototype for the transition from a metal to Mott insulator, is studied with a recent density functional theory model functional for nondynamic and strong correlation. The computed cohesive energy curve for the transition agrees well with accurate literature results. The variation of the electronic structure in this transition is characterized with a density functional descriptor that yields the atomic population of effectively localized electrons. These new methods are also applied to the study of the Peierls dimerization of the stretched even-spaced Mott insulator to a chain of H 2 molecules, a different insulator. The transitions among the two insulating states and the metallic state of the hydrogen chain system are depicted in a semiquantitative phase diagram. Overall, we demonstrate the capability of studying strongly correlated materials with a mean-field model at the fundamental level, in contrast to the general pessimistic view on such a feasibility.

Interpersonal Features and Functions of Nonsuicidal Self-Injury

ERIC Educational Resources Information Center

Muehlenkamp, Jennifer; Brausch, Amy; Quigley, Katherine; Whitlock, Janis

2013-01-01

Etiological models of nonsuicidal self-injury (NSSI) suggest interpersonal features may be important to understand this behavior, but social functions and correlates have not been extensively studied. This study addresses existing limitations by examining interpersonal correlates and functions of NSSI within a stratified random sample of 1,243…

Mapping the current–current correlation function near a quantum critical point

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

Prodan, Emil, E-mail: prodan@yu.edu; Bellissard, Jean

2016-05-15

The current–current correlation function is a useful concept in the theory of electron transport in homogeneous solids. The finite-temperature conductivity tensor as well as Anderson’s localization length can be computed entirely from this correlation function. Based on the critical behavior of these two physical quantities near the plateau–insulator or plateau–plateau transitions in the integer quantum Hall effect, we derive an asymptotic formula for the current–current correlation function, which enables us to make several theoretical predictions about its generic behavior. For the disordered Hofstadter model, we employ numerical simulations to map the current–current correlation function, obtain its asymptotic form near amore » critical point and confirm the theoretical predictions.« less

Nonequilibrium fluctuations in metaphase spindles: polarized light microscopy, image registration, and correlation functions

NASA Astrophysics Data System (ADS)

Brugués, Jan; Needleman, Daniel J.

2010-02-01

Metaphase spindles are highly dynamic, nonequilibrium, steady-state structures. We study the internal fluctuations of spindles by computing spatio-temporal correlation functions of movies obtained from quantitative polarized light microscopy. These correlation functions are only physically meaningful if corrections are made for the net motion of the spindle. We describe our image registration algorithm in detail and we explore its robustness. Finally, we discuss the expression used for the estimation of the correlation function in terms of the nematic order of the microtubules which make up the spindle. Ultimately, studying the form of these correlation functions will provide a quantitative test of the validity of coarse-grained models of spindle structure inspired from liquid crystal physics.

Spatial distribution of nuclei in progressive nucleation: Modeling and application

NASA Astrophysics Data System (ADS)

Tomellini, Massimo

2018-04-01

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

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

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

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

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

PubMed Central

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Kozlowski, Karol K.; Ragoucy, Eric

2016-05-01

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

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.

Extracting p Λ scattering lengths from heavy ion collisions

NASA Astrophysics Data System (ADS)

Shapoval, V. M.; Erazmus, B.; Lednicky, R.; Sinyukov, Yu. M.

2015-09-01

The source radii previously extracted by the STAR Collaboration from the p -Λ ⊕p ¯-Λ ¯ and p ¯-Λ ⊕p -Λ ¯ correlation functions measured in 10% most central Au+Au collisions at top Relativistic Heavy Ion Collider (RHIC) energy, √{sN N}=200 GeV, differ by a factor of 2. The probable reason for this is the neglect of residual correlation effect in the STAR analysis. In the present paper we analyze baryon correlation functions within the Lednický and Lyuboshitz analytical model, extended to effectively account for the residual correlation contribution. Different analytical approximations for such a contribution are considered. We also use the averaged source radii extracted from hydrokinetic model (HKM) simulations to fit the experimental data. In contrast to the STAR experimental study, the calculations in HKM show both p Λ and p Λ ¯ radii to be quite close, as expected from theoretical considerations. Using the effective Gaussian parametrization of residual correlations we obtain a satisfactory fit to the measured baryon-antibaryon correlation function with the HKM source radius value 3.28 fm. The baryon-antibaryon spin-averaged strong interaction scattering length is also extracted from the fit to the experimental correlation function.

Exact solution of matricial Φ23 quantum field theory

NASA Astrophysics Data System (ADS)

Grosse, Harald; Sako, Akifumi; Wulkenhaar, Raimar

2017-12-01

We apply a recently developed method to exactly solve the Φ3 matrix model with covariance of a two-dimensional theory, also known as regularised Kontsevich model. Its correlation functions collectively describe graphs on a multi-punctured 2-sphere. We show how Ward-Takahashi identities and Schwinger-Dyson equations lead in a special large- N limit to integral equations that we solve exactly for all correlation functions. The solved model arises from noncommutative field theory in a special limit of strong deformation parameter. The limit defines ordinary 2D Schwinger functions which, however, do not satisfy reflection positivity.

A pilot study examining correlates of body image among women living with SCI.

PubMed

Bassett, R L; Martin Ginis, K A; Buchholz, A C

2009-06-01

Cross-sectional pilot study. To explore correlates of body image among women with spinal cord injury (SCI), within the framework of Cash's cognitive behavioral model of body image. Hamilton, Ontario, Canada. Women with SCI (N=11, 64% with tetraplegia) reported their functional and appearance body image (Adult Body Satisfaction Questionnaire). A 3-day recall of leisure time physical activity (LTPA), three measures of body composition (that is, weight, waist circumference, body fat) and several demographic variables were assessed as potential correlates. Appearance satisfaction was negatively correlated with all three measures of body composition and positively correlated with years postinjury. Functional satisfaction was positively correlated with years postinjury, and negatively correlated with various LTPA variables. Functional and appearance body image may improve with time following SCI. Body composition may impact satisfaction with physical appearance for some women. The negative relationship between LTPA and functional satisfaction merits further examination, as functional dissatisfaction may motivate individuals to engage in certain types and intensities of LTPA. Correlates of body image differ between appearance and functional satisfaction. Future research should examine appearance and functional satisfaction separately among women with SCI.

Calculation of phonon dispersion relation using new correlation functional

NASA Astrophysics Data System (ADS)

Jitropas, Ukrit; Hsu, Chung-Hao

2017-06-01

To extend the use of Local Density Approximation (LDA), a new analytical correlation functional is introduced. Correlation energy is an essential ingredient within density functional theory and used to determine ground state energy and other properties including phonon dispersion relation. Except for high and low density limit, the general expression of correlation energy is unknown. The approximation approach is therefore required. The accuracy of the modelling system depends on the quality of correlation energy approximation. Typical correlation functionals used in LDA such as Vosko-Wilk-Nusair (VWN) and Perdew-Wang (PW) were obtained from parameterizing the near-exact quantum Monte Carlo data of Ceperley and Alder. These functionals are presented in complex form and inconvenient to implement. Alternatively, the latest published formula of Chachiyo correlation functional provides a comparable result for those much more complicated functionals. In addition, it provides more predictive power based on the first principle approach, not fitting functionals. Nevertheless, the performance of Chachiyo formula for calculating phonon dispersion relation (a key to the thermal properties of materials) has not been tested yet. Here, the implementation of new correlation functional to calculate phonon dispersion relation is initiated. The accuracy and its validity will be explored.

Structural characterization/correlation of calorimetric properties of coal fluids: Final report, September 1, 1985--August 31, 1988

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

Starling, K.E.; Mallinson, R.G.; Li, M.H.

The objective of this research is to examine the relationship between the calorimetric properties of coal fluids and their molecular functional group composition. Coal fluid samples which have had their calorimetric properties measured are characterized using proton NMR, IR, and elemental analysis. These characterizations are then used in a chemical structural model to determine the composition of the coal fluid in terms of the important molecular functional groups. These functional groups are particularly important in determining the intramolecular based properties of a fluid, such as ideal gas heat capacities. Correlational frameworks for ideal gas heat capacities are then examined withinmore » an existing equation of state methodology to determine an optimal correlation. The optimal correlation for obtaining the characterization/chemical structure information and the sensitivity of the correlation to the characterization and structural model is examined. 8 refs.« less

Structural characterization/correlation of calorimetric properties of coal fluids: Second annual report, September 1, 1986-August 31, 1987

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

Starling, K.E.; Mallinson, R.G.; Li, M.H.

The objective of this research is to examine the relationship between the calorimetric properties of coal fluids and their molecular functional group composition. Coal fluid samples which have had their calorimetric properties measured are characterized using proton NMR, ir, and elemental analysis. These characterizations are then used in a chemical structural model to determine the composition of the coal fluid in terms of the important molecular functional groups. These functional groups are particularly important in determining the intramolecular based properties of a fluid, such as ideal gas heat capacities. Correlational frameworks for ideal gas heat capacities are then examined withinmore » an existing equation of state methodology to determine an optimal correlation. The optimal correlation for obtaining the characterization/chemical structure information and the sensitivity of the correlation to the characterization and structural model is examined.« less

Coarse-grained hydrodynamics from correlation functions

NASA Astrophysics Data System (ADS)

Palmer, Bruce

2018-02-01

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.

Exact Asymptotics of the Freezing Transition of a Logarithmically Correlated Random Energy Model

NASA Astrophysics Data System (ADS)

Webb, Christian

2011-12-01

We consider a logarithmically correlated random energy model, namely a model for directed polymers on a Cayley tree, which was introduced by Derrida and Spohn. We prove asymptotic properties of a generating function of the partition function of the model by studying a discrete time analogy of the KPP-equation—thus translating Bramson's work on the KPP-equation into a discrete time case. We also discuss connections to extreme value statistics of a branching random walk and a rescaled multiplicative cascade measure beyond the critical point.

Two-point correlation functions in inhomogeneous and anisotropic cosmologies

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

Marcori, Oton H.; Pereira, Thiago S., E-mail: otonhm@hotmail.com, E-mail: tspereira@uel.br

Two-point correlation functions are ubiquitous tools of modern cosmology, appearing in disparate topics ranging from cosmological inflation to late-time astrophysics. When the background spacetime is maximally symmetric, invariance arguments can be used to fix the functional dependence of this function as the invariant distance between any two points. In this paper we introduce a novel formalism which fixes this functional dependence directly from the isometries of the background metric, thus allowing one to quickly assess the overall features of Gaussian correlators without resorting to the full machinery of perturbation theory. As an application we construct the CMB temperature correlation functionmore » in one inhomogeneous (namely, an off-center LTB model) and two spatially flat and anisotropic (Bianchi) universes, and derive their covariance matrices in the limit of almost Friedmannian symmetry. We show how the method can be extended to arbitrary N -point correlation functions and illustrate its use by constructing three-point correlation functions in some simple geometries.« less

Pulmonary function tests correlated with thoracic volumes in adolescent idiopathic scoliosis.

PubMed

Ledonio, Charles Gerald T; Rosenstein, Benjamin E; Johnston, Charles E; Regelmann, Warren E; Nuckley, David J; Polly, David W

2017-01-01

Scoliosis deformity has been linked with deleterious changes in the thoracic cavity that affect pulmonary function. The causal relationship between spinal deformity and pulmonary function has yet to be fully defined. It has been hypothesized that deformity correction improves pulmonary function by restoring both respiratory muscle efficiency and increasing the space available to the lungs. This research aims to correlate pulmonary function and thoracic volume before and after scoliosis correction. Retrospective correlational analysis between thoracic volume modeling from plain x-rays and pulmonary function tests was conducted. Adolescent idiopathic scoliosis patients enrolled in a multicenter database were sorted by pre-operative Total Lung Capacities (TLC) % predicted values from their Pulmonary Function Tests (PFT). Ten patients with the best and ten patients with the worst TLC values were included. Modeled thoracic volume and TLC values were compared before and 2 years after surgery. Scoliosis correction resulted in an increase in the thoracic volume for patients with the worst initial TLCs (11.7%) and those with the best initial TLCs (12.5%). The adolescents with the most severe pulmonary restriction prior to surgery strongly correlated with post-operative change in total lung capacity and thoracic volume (r 2  = 0.839; p < 0.001). The mean increase in thoracic volume in this group was 373.1 cm 3 (11.7%) which correlated with a 21.2% improvement in TLC. Scoliosis correction in adolescents was found to increase thoracic volume and is strongly correlated with improved TLC in cases with severe restrictive pulmonary function, but no correlation was found in cases with normal pulmonary function. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:175-182, 2017. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

Kim, Seung-Yeon; Kwak, Wooseop

2018-03-01

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

Analytical fitting model for rough-surface BRDF.

PubMed

Renhorn, Ingmar G E; Boreman, Glenn D

2008-08-18

A physics-based model is developed for rough surface BRDF, taking into account angles of incidence and scattering, effective index, surface autocovariance, and correlation length. Shadowing is introduced on surface correlation length and reflectance. Separate terms are included for surface scatter, bulk scatter and retroreflection. Using the FindFit function in Mathematica, the functional form is fitted to BRDF measurements over a wide range of incident angles. The model has fourteen fitting parameters; once these are fixed, the model accurately describes scattering data over two orders of magnitude in BRDF without further adjustment. The resulting analytical model is convenient for numerical computations.

Testing modified gravity using a marked correlation function

NASA Astrophysics Data System (ADS)

Armijo, Joaquí n.; Cai, Yan-Chuan; Padilla, Nelson; Li, Baojiu; Peacock, John A.

2018-05-01

In theories of modified gravity with the chameleon screening mechanism, the strength of the fifth force depends on environment. This induces an environment dependence of structure formation, which differs from ΛCDM. We show that these differences can be captured by the marked correlation function. With the galaxy correlation functions and number densities calibrated to match between f(R) and ΛCDM models in simulations, we show that the marked correlation functions from using either the local galaxy number density or halo mass as the marks encode extra information, which can be used to test these theories. We discuss possible applications of these statistics in observations.

Functional and Physical Outcomes following Use of a Flexible CO2 Laser Fiber and Bipolar Electrocautery in Close Proximity to the Rat Sciatic Nerve with Correlation to an In Vitro Thermal Profile Model

PubMed Central

Robinson, A. M.; Fishman, A. J.; Bendok, B. R.; Richter, C.-P.

2015-01-01

This study compared functional and physical collateral damage to a nerve when operating a Codman MALIS Bipolar Electrosurgical System CMC-III or a CO2 laser coupled to a laser, with correlation to an in vitro model of heating profiles created by the devices in thermochromic ink agarose. Functional damage of the rat sciatic nerve after operating the MALIS or CO2 laser at various power settings and proximities to the nerve was measured by electrically evoked nerve action potentials, and histology of the nerve was used to assess physical damage. Thermochromic ink dissolved in agarose was used to model the spatial and temporal profile of the collateral heating zone of the electrosurgical system and the laser ablation cone. We found that this laser can be operated at 2 W directly above the nerve with minimal damage, while power settings of 5 W and 10 W resulted in acute functional and physical nerve damage, correlating with the maximal heating cone in the thermochromic ink model. MALIS settings up to 40 (11 W) did not result in major functional or physical nerve damage until the nerve was between the forceps tips, correlating with the hottest zone, localized discretely between the tips. PMID:25699266

Two-time correlation function of an open quantum system in contact with a Gaussian reservoir

NASA Astrophysics Data System (ADS)

Ban, Masashi; Kitajima, Sachiko; Shibata, Fumiaki

2018-05-01

An exact formula of a two-time correlation function is derived for an open quantum system which interacts with a Gaussian thermal reservoir. It is provided in terms of functional derivative with respect to fictitious fields. A perturbative expansion and its diagrammatic representation are developed, where the small expansion parameter is related to a correlation time of the Gaussian thermal reservoir. The two-time correlation function of the lowest order is equivalent to that calculated by means of the quantum regression theorem. The result clearly shows that the violation of the quantum regression theorem is caused by a finiteness of the reservoir correlation time. By making use of an exactly solvable model consisting of a two-level system and a set of harmonic oscillators, it is shown that the two-time correlation function up to the first order is a good approximation to the exact one.

Coarse-grained hydrodynamics from correlation functions

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

Palmer, Bruce

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configuration from a molecular dynamics simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilbrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is applied to some simple hydrodynamic cases to determine the feasibility of applying this to realistic nanoscale systems.

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

PubMed

Dean, Roger T; Dunsmuir, William T M

2016-06-01

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

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Nonlocal correlations in the orbital selective Mott phase of a one-dimensional multiorbital Hubbard model

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

Li, S.; Kaushal, N.; Wang, Y.

Here, we study nonlocal correlations in a three-orbital Hubbard model defined on an extended one-dimensional chain using determinant quantum Monte Carlo and density matrix renormalization group methods. We focus on a parameter regime with robust Hund's coupling, which produces an orbital selective Mott phase (OSMP) at intermediate values of the Hubbard U, as well as an orbitally ordered ferromagnetic insulating state at stronger coupling. An examination of the orbital- and spin-correlation functions indicates that the orbital ordering occurs before the onset of magnetic correlations in this parameter regime as a function of temperature. In the OSMP, we find that themore » self-energy for the itinerant electrons is momentum dependent, indicating a degree of nonlocal correlations while the localized electrons have largely momentum independent self-energies. These nonlocal correlations also produce relative shifts of the holelike and electronlike bands within our model. The overall momentum dependence of these quantities is strongly suppressed in the orbitally ordered insulating phase.« less

Nonlocal correlations in the orbital selective Mott phase of a one-dimensional multiorbital Hubbard model

DOE PAGES

Li, S.; Kaushal, N.; Wang, Y.; ...

2016-12-12

Here, we study nonlocal correlations in a three-orbital Hubbard model defined on an extended one-dimensional chain using determinant quantum Monte Carlo and density matrix renormalization group methods. We focus on a parameter regime with robust Hund's coupling, which produces an orbital selective Mott phase (OSMP) at intermediate values of the Hubbard U, as well as an orbitally ordered ferromagnetic insulating state at stronger coupling. An examination of the orbital- and spin-correlation functions indicates that the orbital ordering occurs before the onset of magnetic correlations in this parameter regime as a function of temperature. In the OSMP, we find that themore » self-energy for the itinerant electrons is momentum dependent, indicating a degree of nonlocal correlations while the localized electrons have largely momentum independent self-energies. These nonlocal correlations also produce relative shifts of the holelike and electronlike bands within our model. The overall momentum dependence of these quantities is strongly suppressed in the orbitally ordered insulating phase.« less

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

PubMed

Levashov, V A; Stepanov, M G

2016-01-01

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

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.

Anisotropy of stress correlation in two-dimensional liquids and a pseudospin model

DOE PAGES

Wu, Bin; Iwashita, Takuya; Egami, Takeshi

2015-11-04

Liquids are condensed matter in which atoms are strongly correlated in position and momentum. The atomic pair density function (PDF) is used often in describing such correlation. However, elucidation of many properties requires higher degrees of correlation than the pair correlation. For instance, viscosity depends upon the stress correlations in space and time. We examine the cross correlation between the stress correlation at the atomic level and the PDF for two-dimensional liquids. We introduce the concept of the stress-resolved pair distribution function (SRPDF) that uses the sign of atomic-level stress as a selection rule to include particles from density correlations.more » The connection between SRPDFs and stress correlation function is explained through an approximation in which the shear stress is replaced by a pseudospin. Lastly, we further assess the possibility of interpreting the long-range stress correlation as a consequence of short-range Ising-like pseudospin interactions.« less

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Structure-Function Modeling of Optical Coherence Tomography and Standard Automated Perimetry in the Retina of Patients with Autosomal Dominant Retinitis Pigmentosa

PubMed Central

Smith, Travis B.; Parker, Maria; Steinkamp, Peter N.; Weleber, Richard G.; Smith, Ning; Wilson, David J.

2016-01-01

Purpose To assess relationships between structural and functional biomarkers, including new topographic measures of visual field sensitivity, in patients with autosomal dominant retinitis pigmentosa. Methods Spectral domain optical coherence tomography line scans and hill of vision (HOV) sensitivity surfaces from full-field standard automated perimetry were semi-automatically aligned for 60 eyes of 35 patients. Structural biomarkers were extracted from outer retina b-scans along horizontal and vertical midlines. Functional biomarkers were extracted from local sensitivity profiles along the b-scans and from the full visual field. These included topographic measures of functional transition such as the contour of most rapid sensitivity decline around the HOV, herein called HOV slope for convenience. Biomarker relationships were assessed pairwise by coefficients of determination (R2) from mixed-effects analysis with automatic model selection. Results Structure-function relationships were accurately modeled (conditional R2>0.8 in most cases). The best-fit relationship models and correlation patterns for horizontally oriented biomarkers were different than vertically oriented ones. The structural biomarker with the largest number of significant functional correlates was the ellipsoid zone (EZ) width, followed by the total photoreceptor layer thickness. The strongest correlation observed was between EZ width and HOV slope distance (marginal R2 = 0.85, p<10−10). The mean sensitivity defect at the EZ edge was 7.6 dB. Among all functional biomarkers, the HOV slope mean value, HOV slope mean distance, and maximum sensitivity along the b-scan had the largest number of significant structural correlates. Conclusions Topographic slope metrics show promise as functional biomarkers relevant to the transition zone. EZ width is strongly associated with the location of most rapid HOV decline. PMID:26845445

Structure-Function Modeling of Optical Coherence Tomography and Standard Automated Perimetry in the Retina of Patients with Autosomal Dominant Retinitis Pigmentosa.

PubMed

Smith, Travis B; Parker, Maria; Steinkamp, Peter N; Weleber, Richard G; Smith, Ning; Wilson, David J

2016-01-01

To assess relationships between structural and functional biomarkers, including new topographic measures of visual field sensitivity, in patients with autosomal dominant retinitis pigmentosa. Spectral domain optical coherence tomography line scans and hill of vision (HOV) sensitivity surfaces from full-field standard automated perimetry were semi-automatically aligned for 60 eyes of 35 patients. Structural biomarkers were extracted from outer retina b-scans along horizontal and vertical midlines. Functional biomarkers were extracted from local sensitivity profiles along the b-scans and from the full visual field. These included topographic measures of functional transition such as the contour of most rapid sensitivity decline around the HOV, herein called HOV slope for convenience. Biomarker relationships were assessed pairwise by coefficients of determination (R2) from mixed-effects analysis with automatic model selection. Structure-function relationships were accurately modeled (conditional R(2)>0.8 in most cases). The best-fit relationship models and correlation patterns for horizontally oriented biomarkers were different than vertically oriented ones. The structural biomarker with the largest number of significant functional correlates was the ellipsoid zone (EZ) width, followed by the total photoreceptor layer thickness. The strongest correlation observed was between EZ width and HOV slope distance (marginal R(2) = 0.85, p<10(-10)). The mean sensitivity defect at the EZ edge was 7.6 dB. Among all functional biomarkers, the HOV slope mean value, HOV slope mean distance, and maximum sensitivity along the b-scan had the largest number of significant structural correlates. Topographic slope metrics show promise as functional biomarkers relevant to the transition zone. EZ width is strongly associated with the location of most rapid HOV decline.

Generalized hydrodynamic correlations and fractional memory functions

NASA Astrophysics Data System (ADS)

Rodríguez, Rosalio F.; Fujioka, Jorge

2015-12-01

A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.

Random medium model for cusping of plane waves.

PubMed

Li, Jia; Korotkova, Olga

2017-09-01

We introduce a model for a three-dimensional (3D) Schell-type stationary medium whose degree of potential's correlation satisfies the Fractional Multi-Gaussian (FMG) function. Compared with the scattered profile produced by the Gaussian Schell-model (GSM) medium, the Fractional Multi-Gaussian Schell-model (FMGSM) medium gives rise to a sharp concave intensity apex in the scattered field. This implies that the FMGSM medium also accounts for a larger than Gaussian's power in the bucket (PIB) in the forward scattering direction, hence being a better candidate than the GSM medium for generating highly-focused (cusp-like) scattered profiles in the far zone. Compared to other mathematical models for the medium's correlation function which can produce similar cusped scattered profiles the FMG function offers unprecedented tractability being the weighted superposition of Gaussian functions. Our results provide useful applications to energy counter problems and particle manipulation by weakly scattered fields.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data.

PubMed

Duan, L L; Szczesniak, R D; Wang, X

2017-11-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data

PubMed Central

Duan, L. L.; Szczesniak, R. D.; Wang, X.

2018-01-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization. PMID:29576735

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.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

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.

Four-body correlation embedded in antisymmetrized geminal power wave function.

PubMed

Kawasaki, Airi; Sugino, Osamu

2016-12-28

We extend the Coleman's antisymmetrized geminal power (AGP) to develop a wave function theory that can incorporate up to four-body correlation in a region of strong correlation. To facilitate the variational determination of the wave function, the total energy is rewritten in terms of the traces of geminals. This novel trace formula is applied to a simple model system consisting of one dimensional Hubbard ring with a site of strong correlation. Our scheme significantly improves the result obtained by the AGP-configuration interaction scheme of Uemura et al. and also achieves more efficient compression of the degrees of freedom of the wave function. We regard the result as a step toward a first-principles wave function theory for a strongly correlated point defect or adsorbate embedded in an AGP-based mean-field medium.

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

PubMed Central

Carbonell, Felix; Bellec, Pierre

2011-01-01

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

Orientational Dynamics of a Functionalized Alkyl Planar Monolayer Probed by Polarization-Selective Angle-Resolved Infrared Pump-Probe Spectroscopy.

PubMed

Nishida, Jun; Yan, Chang; Fayer, Michael D

2016-10-12

Polarization-selective angle-resolved infrared pump-probe spectroscopy was developed and used to study the orientational dynamics of a planar alkylsiloxane monolayer functionalized with a rhenium metal carbonyl headgroup on an SiO 2 surface. The technique, together with a time-averaged infrared linear dichroism measurement, characterized picosecond orientational relaxation of the headgroup occurring at the monolayer-air interface by employing several sets of incident angles of the infrared pulses relative to the sample surface. By application of this method and using a recently developed theory, it was possible to extract both the out-of-plane and "mainly"-in-plane orientational correlation functions in a model-independent manner. The observed correlation functions were compared with theoretically derived correlation functions based on several dynamical models. The out-of-plane correlation function reveals the highly restricted out-of-plane motions of the head groups and also suggests that the angular distribution of the transition dipole moments is bimodal. The mainly-in-plane correlation function, for the sample studied here with the strongly restricted out-of-plane motions, essentially arises from the purely in-plane dynamics. In contrast to the out-of-plane dynamics, significant in-plane motions occurring over various time scales were observed including an inertial motion, a restricted wobbling motion of ∼3 ps, and complete randomization occurring in ∼25 ps.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The Hubbard Dimer: A Complete DFT Solution to a Many-Body Problem

NASA Astrophysics Data System (ADS)

Smith, Justin; Carrascal, Diego; Ferrer, Jaime; Burke, Kieron

2015-03-01

In this work we explain the relationship between density functional theory and strongly correlated models using the simplest possible example, the two-site asymmetric Hubbard model. We discuss the connection between the lattice and real-space and how this is a simple model for stretched H2. We can solve this elementary example analytically, and with that we can illuminate the underlying logic and aims of DFT. While the many-body solution is analytic, the density functional is given only implicitly. We overcome this difficulty by creating a highly accurate parameterization of the exact function. We use this parameterization to perform benchmark calculations of correlation kinetic energy, the adiabatic connection, etc. We also test Hartree-Fock and the Bethe Ansatz Local Density Approximation. We also discuss and illustrate the derivative discontinuity in the exchange-correlation energy and the infamous gap problem in DFT. DGE-1321846, DE-FG02-08ER46496.

The influences of delay time on the stability of a market model with stochastic volatility

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Mei, Dong-Cheng

2013-02-01

The effects of the delay time on the stability of a market model are investigated, by using a modified Heston model with a cubic nonlinearity and cross-correlated noise sources. These results indicate that: (i) There is an optimal delay time τo which maximally enhances the stability of the stock price under strong demand elasticity of stock price, and maximally reduces the stability of the stock price under weak demand elasticity of stock price; (ii) The cross correlation coefficient of noises and the delay time play an opposite role on the stability for the case of the delay time <τo and the same role for the case of the delay time >τo. Moreover, the probability density function of the escape time of stock price returns, the probability density function of the returns and the correlation function of the returns are compared with other literatures.

Influence of the exchange and correlation functional on the structure of amorphous InSb and In3SbTe2 compounds

NASA Astrophysics Data System (ADS)

Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H.; Kühne, Thomas D.; Bernasconi, Marco

2016-05-01

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.

Influence of the exchange and correlation functional on the structure of amorphous InSb and In3SbTe2 compounds.

PubMed

Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H; Kühne, Thomas D; Bernasconi, Marco

2016-05-28

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.

Nontrivial thermodynamics in 't Hooft's large-N limit

NASA Astrophysics Data System (ADS)

Cubero, Axel Cortés

2015-05-01

We study the finite volume/temperature correlation functions of the (1 +1 )-dimensional SU (N ) principal chiral sigma model in the planar limit. The exact S-matrix of the sigma model is known to simplify drastically at large N , and this leads to trivial thermodynamic Bethe ansatz (TBA) equations. The partition function, if derived using the TBA, can be shown to be that of free particles. We show that the correlation functions and expectation values of operators at finite volume/temperature are not those of the free theory, and that the TBA does not give enough information to calculate them. Our analysis is done using the Leclair-Mussardo formula for finite-volume correlators, and knowledge of the exact infinite-volume form factors. We present analytical results for the one-point function of the energy-momentum tensor, and the two-point function of the renormalized field operator. The results for the energy-momentum tensor can be used to define a nontrivial partition function.

On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

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

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

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

Structural characterization/correlation of calorimetric properties of coal fluids. First annual report, September 1, 1985-August 31, 1986

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

Starling, K.E.; Mallinson, R.G.; Li, M.H.

The objective of this research is to examine the relationship between the calorimetric properties of coal liquids and their molecular functional group composition. Coal liquid samples which have had their calorimetric properties measured are characterized using proton NMR, ir and elemental analysis. These characterizations are then used in a chemical structural model to determine the composition of the coal liquid in terms of the important molecular functional groups. These functional groups are particularly important in determining the intramolecular based properties of a fluid, such as ideal gas heat capacities. Correlational frameworks for heat capacities will then be examined within anmore » existing equation of state methodology to determine an optimal correlation. Also, the optimal recipe for obtaining the characterization/chemical structure information and the sensitivity of the correlation to the characterization and structural model will be examined and determined. 7 refs.« less

Modeling the Collisional-Plastic Stress Transition for Bin Discharge of Granular Material

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

Pannala, Sreekanth; Daw, C Stuart; FINNEY, Charles E A

2009-01-01

We propose a heuristic model for the transition between collisional and frictional/plastic stresses in the flow of granular material. Our approach is based on a physically motivated, nonlinear blending function that produces a weighted average of the limiting stresses, depending on the local void fraction in the flow field. Previously published stress models are utilized to describe the behavior in the collisional (Lun et al., 1984) and quasi-static limits (Schaeffer, 1987 and Syamlal et al., 1993). Sigmoidal and hyperbolic tangent functions are used to mimic the observed smooth yet rapid transition between the collisional and plastic stress zones. We implementmore » our stress transition model in an opensource multiphase flow solver, MFIX (Multiphase Flow with Interphase eXchanges, www.mfix.org) and demonstrate its application to a standard bin discharge problem. The model s effectiveness is illustrated by comparing computational predictions to the experimentally derived Beverloo correlation. With the correct choice of function parameters, the model predicts bin discharge rates within the error margins of the Beverloo correlation and is more accurate than one of the alternative granular stress models proposed in the literature. Although a second granular stress model in the literature is also reasonably consistent with the Beverloo correlation, we propose that our alternative blending function is likely to be more adaptable to situations with more complex solids properties (e.g., sticky solids).« less

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

NASA Astrophysics Data System (ADS)

Joubert, D. P.

2012-09-01

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

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

PubMed

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

An external validation study reporting poor correlation between the claims-based index for rheumatoid arthritis severity and the disease activity score.

PubMed

Desai, Rishi J; Solomon, Daniel H; Weinblatt, Michael E; Shadick, Nancy; Kim, Seoyoung C

2015-04-13

We conducted an external validation study to examine the correlation of a previously published claims-based index for rheumatoid arthritis severity (CIRAS) with disease activity score in 28 joints calculated by using C-reactive protein (DAS28-CRP) and the multi-dimensional health assessment questionnaire (MD-HAQ) physical function score. Patients enrolled in the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS) and Medicare were identified and their data from these two sources were linked. For each patient, DAS28-CRP measurement and MD-HAQ physical function scores were extracted from BRASS, and CIRAS was calculated from Medicare claims for the period of 365 days prior to the DAS28-CRP measurement. Pearson correlation coefficient between CIRAS and DAS28-CRP as well as MD-HAQ physical function scores were calculated. Furthermore, we considered several additional pharmacy and medical claims-derived variables as predictors for DAS28-CRP in a multivariable linear regression model in order to assess improvement in the performance of the original CIRAS algorithm. In total, 315 patients with enrollment in both BRASS and Medicare were included in this study. The majority (81%) of the cohort was female, and the mean age was 70 years. The correlation between CIRAS and DAS28-CRP was low (Pearson correlation coefficient = 0.07, P = 0.24). The correlation between the calculated CIRAS and MD-HAQ physical function scores was also found to be low (Pearson correlation coefficient = 0.08, P = 0.17). The linear regression model containing additional claims-derived variables yielded model R(2) of 0.23, suggesting limited ability of this model to explain variation in DAS28-CRP. In a cohort of Medicare-enrolled patients with established RA, CIRAS showed low correlation with DAS28-CRP as well as MD-HAQ physical function scores. Claims-based algorithms for disease activity should be rigorously tested in distinct populations in order to establish their generalizability before widespread adoption.

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.

Simulation of random road microprofile based on specified correlation function

NASA Astrophysics Data System (ADS)

Rykov, S. P.; Rykova, O. A.; Koval, V. S.; Vlasov, V. G.; Fedotov, K. V.

2018-03-01

The paper aims to develop a numerical simulation method and an algorithm for a random microprofile of special roads based on the specified correlation function. The paper used methods of correlation, spectrum and numerical analysis. It proves that the transfer function of the generating filter for known expressions of spectrum input and output filter characteristics can be calculated using a theorem on nonnegative and fractional rational factorization and integral transformation. The model of the random function equivalent of the real road surface microprofile enables us to assess springing system parameters and identify ranges of variations.

Analysis/forecast experiments with a flow-dependent correlation function using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.

1986-01-01

The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.

Triplet correlation functions in liquid water

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

Dhabal, Debdas; Chakravarty, Charusita, E-mail: charus@chemistry.iitd.ac.in; Singh, Murari

Triplet correlations have been shown to play a crucial role in the transformation of simple liquids to anomalous tetrahedral fluids [M. Singh, D. Dhabal, A. H. Nguyen, V. Molinero, and C. Chakravarty, Phys. Rev. Lett. 112, 147801 (2014)]. Here we examine triplet correlation functions for water, arguably the most important tetrahedral liquid, under ambient conditions, using configurational ensembles derived from molecular dynamics (MD) simulations and reverse Monte Carlo (RMC) datasets fitted to experimental scattering data. Four different RMC data sets with widely varying hydrogen-bond topologies fitted to neutron and x-ray scattering data are considered [K. T. Wikfeldt, M. Leetmaa, M.more » P. Ljungberg, A. Nilsson, and L. G. M. Pettersson, J. Phys. Chem. B 113, 6246 (2009)]. Molecular dynamics simulations are performed for two rigid-body effective pair potentials (SPC/E and TIP4P/2005) and the monatomic water (mW) model. Triplet correlation functions are compared with other structural measures for tetrahedrality, such as the O–O–O angular distribution function and the local tetrahedral order distributions. In contrast to the pair correlation functions, which are identical for all the RMC ensembles, the O–O–O triplet correlation function can discriminate between ensembles with different degrees of tetrahedral network formation with the maximally symmetric, tetrahedral SYM dataset displaying distinct signatures of tetrahedrality similar to those obtained from atomistic simulations of the SPC/E model. Triplet correlations from the RMC datasets conform closely to the Kirkwood superposition approximation, while those from MD simulations show deviations within the first two neighbour shells. The possibilities for experimental estimation of triplet correlations of water and other tetrahedral liquids are discussed.« less

Wave Propagation in Non-Stationary Statistical Mantle Models at the Global Scale

NASA Astrophysics Data System (ADS)

Meschede, M.; Romanowicz, B. A.

2014-12-01

We study the effect of statistically distributed heterogeneities that are smaller than the resolution of current tomographic models on seismic waves that propagate through the Earth's mantle at teleseismic distances. Current global tomographic models are missing small-scale structure as evidenced by the failure of even accurate numerical synthetics to explain enhanced coda in observed body and surface waveforms. One way to characterize small scale heterogeneity is to construct random models and confront observed coda waveforms with predictions from these models. Statistical studies of the coda typically rely on models with simplified isotropic and stationary correlation functions in Cartesian geometries. We show how to construct more complex random models for the mantle that can account for arbitrary non-stationary and anisotropic correlation functions as well as for complex geometries. Although this method is computationally heavy, model characteristics such as translational, cylindrical or spherical symmetries can be used to greatly reduce the complexity such that this method becomes practical. With this approach, we can create 3D models of the full spherical Earth that can be radially anisotropic, i.e. with different horizontal and radial correlation functions, and radially non-stationary, i.e. with radially varying model power and correlation functions. Both of these features are crucial for a statistical description of the mantle in which structure depends to first order on the spherical geometry of the Earth. We combine different random model realizations of S velocity with current global tomographic models that are robust at long wavelengths (e.g. Meschede and Romanowicz, 2014, GJI submitted), and compute the effects of these hybrid models on the wavefield with a spectral element code (SPECFEM3D_GLOBE). We finally analyze the resulting coda waves for our model selection and compare our computations with observations. Based on these observations, we make predictions about the strength of unresolved small-scale structure and extrinsic attenuation.

Experimental characterization of a quantum many-body system via higher-order correlations.

PubMed

Schweigler, Thomas; Kasper, Valentin; Erne, Sebastian; Mazets, Igor; Rauer, Bernhard; Cataldini, Federica; Langen, Tim; Gasenzer, Thomas; Berges, Jürgen; Schmiedmayer, Jörg

2017-05-17

Quantum systems can be characterized by their correlations. Higher-order (larger than second order) correlations, and the ways in which they can be decomposed into correlations of lower order, provide important information about the system, its structure, its interactions and its complexity. The measurement of such correlation functions is therefore an essential tool for reading, verifying and characterizing quantum simulations. Although higher-order correlation functions are frequently used in theoretical calculations, so far mainly correlations up to second order have been studied experimentally. Here we study a pair of tunnel-coupled one-dimensional atomic superfluids and characterize the corresponding quantum many-body problem by measuring correlation functions. We extract phase correlation functions up to tenth order from interference patterns and analyse whether, and under what conditions, these functions factorize into correlations of lower order. This analysis characterizes the essential features of our system, the relevant quasiparticles, their interactions and topologically distinct vacua. From our data we conclude that in thermal equilibrium our system can be seen as a quantum simulator of the sine-Gordon model, relevant for diverse disciplines ranging from particle physics to condensed matter. The measurement and evaluation of higher-order correlation functions can easily be generalized to other systems and to study correlations of any other observable such as density, spin and magnetization. It therefore represents a general method for analysing quantum many-body systems from experimental data.

Anomalous scaling of a passive scalar advected by the Navier-Stokes velocity field: two-loop approximation.

PubMed

Adzhemyan, L Ts; Antonov, N V; Honkonen, J; Kim, T L

2005-01-01

The field theoretic renormalization group and operator-product expansion are applied to the model of a passive scalar quantity advected by a non-Gaussian velocity field with finite correlation time. The velocity is governed by the Navier-Stokes equation, subject to an external random stirring force with the correlation function proportional to delta(t- t')k(4-d-2epsilon). It is shown that the scalar field is intermittent already for small epsilon, its structure functions display anomalous scaling behavior, and the corresponding exponents can be systematically calculated as series in epsilon. The practical calculation is accomplished to order epsilon2 (two-loop approximation), including anisotropic sectors. As for the well-known Kraichnan rapid-change model, the anomalous scaling results from the existence in the model of composite fields (operators) with negative scaling dimensions, identified with the anomalous exponents. Thus the mechanism of the origin of anomalous scaling appears similar for the Gaussian model with zero correlation time and the non-Gaussian model with finite correlation time. It should be emphasized that, in contrast to Gaussian velocity ensembles with finite correlation time, the model and the perturbation theory discussed here are manifestly Galilean covariant. The relevance of these results for real passive advection and comparison with the Gaussian models and experiments are briefly discussed.

Elucidating Dimensions of Posttraumatic Stress Symptoms and their Functional Correlates in Disaster-Exposed Adolescents

PubMed Central

Sumner, Jennifer A.; Pietrzak, Robert H.; Danielson, Carla Kmett; Adams, Zachary W.; Ruggiero, Kenneth J.

2014-01-01

The aim of this study was to elucidate the dimensional structure of posttraumatic stress disorder (PTSD) and potential moderators and functional correlates of this structure in disaster-affected adolescents. A population-based sample of 2,000 adolescents aged 12–17 years (M=14.5 years; 51% female) completed interviews on post-tornado PTSD symptoms, substance use, and parent-adolescent conflict between 4 and 13 months (M=8.8, SD=2.6) after tornado exposure. Confirmatory factor analyses revealed that all models fit well but a 5-factor dysphoric arousal model provided a statistically significantly better representation of adolescent PTSD symptoms compared to 4-factor dysphoria and emotional numbing models. There was evidence of measurement invariance of the dysphoric arousal model across gender and age, although girls and older adolescents aged 15–17 years had higher mean scores than boys and younger adolescents aged 12–14 years, respectively, on some PTSD dimensions. Differential magnitudes of association between PTSD symptom dimensions and functional correlates were observed, with emotional numbing symptoms most strongly positively associated with problematic substance use since the tornado, and dysphoric arousal symptoms most strongly positively associated with parent-adolescent conflict; both correlations were significantly larger than the corresponding correlations with anxious arousal. Taken together, these results suggest that the dimensional structure of tornado-related PTSD symptomatology in adolescents is optimally characterized by five separate clusters of re-experiencing, avoidance, numbing, dysphoric arousal, and anxious arousal symptoms, which showed unique associations with functional correlates. Findings emphasize that PTSD in disaster-exposed adolescents is not best conceptualized as a homogeneous construct and highlight potential differential targets for post-disaster assessment and intervention. PMID:25248557

Elucidating dimensions of posttraumatic stress symptoms and their functional correlates in disaster-exposed adolescents.

PubMed

Sumner, Jennifer A; Pietrzak, Robert H; Danielson, Carla Kmett; Adams, Zachary W; Ruggiero, Kenneth J

2014-12-01

The aim of this study was to elucidate the dimensional structure of posttraumatic stress disorder (PTSD) and potential moderators and functional correlates of this structure in disaster-affected adolescents. A population-based sample of 2000 adolescents aged 12-17 years (M = 14.5 years; 51% female) completed interviews on post-tornado PTSD symptoms, substance use, and parent-adolescent conflict between 4 and 13 months (M = 8.8, SD = 2.6) after tornado exposure. Confirmatory factor analyses revealed that all models fit well but a 5-factor dysphoric arousal model provided a statistically significantly better representation of adolescent PTSD symptoms compared to 4-factor dysphoria and emotional numbing models. There was evidence of measurement invariance of the dysphoric arousal model across gender and age, although girls and older adolescents aged 15-17 years had higher mean scores than boys and younger adolescents aged 12-14 years, respectively, on some PTSD dimensions. Differential magnitudes of association between PTSD symptom dimensions and functional correlates were observed, with emotional numbing symptoms most strongly positively associated with problematic substance use since the tornado, and dysphoric arousal symptoms most strongly positively associated with parent-adolescent conflict; both correlations were significantly larger than the corresponding correlations with anxious arousal. Taken together, these results suggest that the dimensional structure of tornado-related PTSD symptomatology in adolescents is optimally characterized by five separate clusters of re-experiencing, avoidance, numbing, dysphoric arousal, and anxious arousal symptoms, which showed unique associations with functional correlates. Findings emphasize that PTSD in disaster-exposed adolescents is not best conceptualized as a homogenous construct and highlight potential differential targets for post-disaster assessment and intervention. Copyright © 2014 Elsevier Ltd. All rights reserved.

Vector and Axial-Vector Correlators in AN Instanton-Like Quark Model

NASA Astrophysics Data System (ADS)

Dorokhov, Alexander E.

The behavior of the vector Adler function at spacelike momenta is studied in the framework of a covariant chiral quark model with instanton-like quark-quark interaction. This function describes the transition between the high energy asymptotically free region of almost massless current quarks to the low energy hadronized regime with massive constituent quarks. The model reproduces the Adler function and V-A correlator extracted from the ALEPH and OPAL data on hadronic τ lepton decays, transformed into the Euclidean domain via dispersion relations. The leading order contribution from hadronic part of the photon vacuum polarization to the anomalous magnetic moment of the muon, aμ hvp(1), is estimated.

Correlation of hard X-ray and type 3 bursts in solar flares

NASA Technical Reports Server (NTRS)

Petrosian, V.; Leach, J.

1982-01-01

Correlations between X-ray and type 3 radio emission of solar bursts are described through a bivariate distribution function. Procedures for determining the form of this distribution are described. A model is constructed to explain the correlation between the X-ray spectral index and the ratio of X-ray to radio intensities. Implications of the model are discussed.

Fatigue reliability of deck structures subjected to correlated crack growth

NASA Astrophysics Data System (ADS)

Feng, G. Q.; Garbatov, Y.; Guedes Soares, C.

2013-12-01

The objective of this work is to analyse fatigue reliability of deck structures subjected to correlated crack growth. The stress intensity factors of the correlated cracks are obtained by finite element analysis and based on which the geometry correction functions are derived. The Monte Carlo simulations are applied to predict the statistical descriptors of correlated cracks based on the Paris-Erdogan equation. A probabilistic model of crack growth as a function of time is used to analyse the fatigue reliability of deck structures accounting for the crack propagation correlation. A deck structure is modelled as a series system of stiffened panels, where a stiffened panel is regarded as a parallel system composed of plates and are longitudinal. It has been proven that the method developed here can be conveniently applied to perform the fatigue reliability assessment of structures subjected to correlated crack growth.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

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

Entropy of finite random binary sequences with weak long-range correlations.

PubMed

Melnik, S S; Usatenko, O V

2014-11-01

We study the N-step binary stationary ergodic Markov chain and analyze its differential entropy. Supposing that the correlations are weak we express the conditional probability function of the chain through the pair correlation function and represent the entropy as a functional of the pair correlator. Since the model uses the two-point correlators instead of the block probability, it makes it possible to calculate the entropy of strings at much longer distances than using standard methods. A fluctuation contribution to the entropy due to finiteness of random chains is examined. This contribution can be of the same order as its regular part even at the relatively short lengths of subsequences. A self-similar structure of entropy with respect to the decimation transformations is revealed for some specific forms of the pair correlation function. Application of the theory to the DNA sequence of the R3 chromosome of Drosophila melanogaster is presented.

Entropy of finite random binary sequences with weak long-range correlations

NASA Astrophysics Data System (ADS)

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

2014-11-01

We study the N -step binary stationary ergodic Markov chain and analyze its differential entropy. Supposing that the correlations are weak we express the conditional probability function of the chain through the pair correlation function and represent the entropy as a functional of the pair correlator. Since the model uses the two-point correlators instead of the block probability, it makes it possible to calculate the entropy of strings at much longer distances than using standard methods. A fluctuation contribution to the entropy due to finiteness of random chains is examined. This contribution can be of the same order as its regular part even at the relatively short lengths of subsequences. A self-similar structure of entropy with respect to the decimation transformations is revealed for some specific forms of the pair correlation function. Application of the theory to the DNA sequence of the R3 chromosome of Drosophila melanogaster is presented.

Aspects of the RVB Luttinger Liquid Theory of the High Temperature Superconductivity

NASA Astrophysics Data System (ADS)

Ren, Yong

1992-01-01

This thesis describes work on a large-U Hubbard model theory for high temperature superconductors. After an introduction to the Hubbard model and the normal state properties of the high T_{rm c} superconductors, we briefly examine the definition of the Fermi liquid and its breakdown. Then we explain why the 1D Hubbard model is the best starting point to approach our problem. In one dimension, the exact Lieb-Wu solution is available. We discuss the Lieb-Wu solution, and calculate various asymptotic correlation functions in the ground state. This clarifies the nature of the ground state which has not been known before. Instead of simply getting the exponents of the correlation functions from the Bethe Ansatz integral equations, we establish the connection between phase shifts at different Fermi points and the asymptotic correlation functions. We believe that this connection contains the most important physics and it can be readily generalized into higher dimensions. We then discuss bosonization in two dimensions and define the 2D RVB-Luttinger liquid theory, proposing that the ground state of the 2D Hubbard model belongs to a different fixed point than the Landau Fermi liquid-Luttinger liquid. Finally we apply the understanding of the 1D result to explain the normal state properties of the high T_ {c} superconductors, putting emphasis on how the non-Fermi liquid correlation functions explain the "anomalous" experimental results. In the Appendix, several issues related to the 1D and 2D Hubbard model are discussed.

Correlations and Functional Connections in a Population of Grid Cells

PubMed Central

Roudi, Yasser

2015-01-01

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

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.

Understanding the determinants of volatility clustering in terms of stationary Markovian processes

NASA Astrophysics Data System (ADS)

Miccichè, S.

2016-11-01

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ-β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock's volatility is a linear function of the average correlation of such stock's volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still keep some of the original volatility stylized facts. As a result, the diagonalized volatilities result to share with the original volatilities either the power-law decay of the probability density function and the power-law decay of the autocorrelation function. This would indicate that volatility clustering is already present in the diagonalized un-correlated volatilities. We therefore present a parsimonious univariate model based on a non-linear Langevin equation that well reproduces these two stylized facts of volatility. The model helps us in understanding that the main source of volatility clustering, once volatilities have been diagonalized, is that the economic forces driving volatility can be modeled in terms of a Smoluchowski potential with logarithmic tails.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2011-09-01

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multiresolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low-resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model, which may introduce artifacts in regions where no significant correlation exists between anatomical and functional details. A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present, the new model outperformed the 2D global approach, avoiding artifacts and significantly improving quality of the corrected images and their quantitative accuracy. A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multiresolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information.

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

PubMed Central

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

2011-01-01

Purpose Partial volume effects (PVE) are consequences of the limited spatial resolution in emission tomography leading to under-estimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multi-resolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model which may introduce artefacts in regions where no significant correlation exists between anatomical and functional details. Methods A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Results Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present the new model outperformed the 2D global approach, avoiding artefacts and significantly improving quality of the corrected images and their quantitative accuracy. Conclusions A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multi-resolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information. PMID:21978037

A stochastic-dynamic model for global atmospheric mass field statistics

NASA Technical Reports Server (NTRS)

Ghil, M.; Balgovind, R.; Kalnay-Rivas, E.

1981-01-01

A model that yields the spatial correlation structure of atmospheric mass field forecast errors was developed. The model is governed by the potential vorticity equation forced by random noise. Expansion in spherical harmonics and correlation function was computed analytically using the expansion coefficients. The finite difference equivalent was solved using a fast Poisson solver and the correlation function was computed using stratified sampling of the individual realization of F(omega) and hence of phi(omega). A higher order equation for gamma was derived and solved directly in finite differences by two successive applications of the fast Poisson solver. The methods were compared for accuracy and efficiency and the third method was chosen as clearly superior. The results agree well with the latitude dependence of observed atmospheric correlation data. The value of the parameter c sub o which gives the best fit to the data is close to the value expected from dynamical considerations.

Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

PubMed

Yoo, Kwangsun; Rosenberg, Monica D; Hsu, Wei-Ting; Zhang, Sheng; Li, Chiang-Shan R; Scheinost, Dustin; Constable, R Todd; Chun, Marvin M

2018-02-15

Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square [PLS] regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with correlations between predicted and observed measures of attention as high as 0.9 for internal validation, and 0.6 for external validation (all p's < 0.05). Models trained on task data outperformed models trained on rest data. Pearson's correlation and accordance features generally showed a small numerical advantage over discordance features, while PLS regression models were usually better than linear regression models. Overall, in addition to correlation features combined with linear models (Rosenberg et al., 2016a), it is useful to consider accordance features and PLS regression for CPM. Copyright © 2017 Elsevier Inc. All rights reserved.

An Examination of Lower Extremity Function and its Correlates in Older African American and White Men.

PubMed

Clay, Olivio J; Thorpe, Roland J; Wilkinson, Larrell L; Plaisance, Eric P; Crowe, Michael; Sawyer, Patricia; Brown, Cynthia J

2015-08-07

Maintaining functional status and reducing/eliminating health disparities in late life are key priorities. Older African Americans have been found to have worse lower extremity functioning than Whites, but little is known about potential differences in correlates between African American and White men. The goal of this investigation was to examine measures that could explain this racial difference and to identify race-specific correlates of lower extremity function. Data were analyzed for a sample of community-dwelling men. Linear regression models examined demographics, medical conditions, health behaviors, and perceived discrimination and mental health as correlates of an objective measure of lower extremity function, the Short Physical Performance Battery (SPPB). Scores on the SPPB have a potential range of 0 to 12 with higher scores corresponding to better functioning. The mean age of all men was 74.9 years (SD=6.5), and the sample was 50% African American and 53% rural. African American men had scores on the SPPB that were significantly lower than White men after adjusting for age, rural residence, marital status, education, and income difficulty (P<.01). Racial differences in cognitive functioning accounted for approximately 41% of the race effect on physical function. Additional models stratified by race revealed a pattern of similar correlates of the SPPB among African American and White men. The results of this investigation can be helpful for researchers and clinicians to aid in identifying older men who are at-risk for poor lower extremity function and in planning targeted interventions to help reduce disparities.

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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

PubMed

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

2016-07-01

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

Angular resolution and range of dipole-dipole correlations in water

NASA Astrophysics Data System (ADS)

Mathias, Gerald; Tavan, Paul

2004-03-01

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

A Short Note on the Scaling Function Constant Problem in the Two-Dimensional Ising Model

NASA Astrophysics Data System (ADS)

Bothner, Thomas

2018-02-01

We provide a simple derivation of the constant factor in the short-distance asymptotics of the tau-function associated with the 2-point function of the two-dimensional Ising model. This factor was first computed by Tracy (Commun Math Phys 142:297-311, 1991) via an exponential series expansion of the correlation function. Further simplifications in the analysis are due to Tracy and Widom (Commun Math Phys 190:697-721, 1998) using Fredholm determinant representations of the correlation function and Wiener-Hopf approximation results for the underlying resolvent operator. Our method relies on an action integral representation of the tau-function and asymptotic results for the underlying Painlevé-III transcendent from McCoy et al. (J Math Phys 18:1058-1092, 1977).

Field theoretic approach to roughness corrections

NASA Astrophysics Data System (ADS)

Wu, Hua Yao; Schaden, Martin

2012-02-01

We develop a systematic field theoretic description of roughness corrections to the Casimir free energy of a massless scalar field in the presence of parallel plates with mean separation a. Roughness is modeled by specifying a generating functional for correlation functions of the height profile. The two-point correlation function being characterized by its variance, σ2, and correlation length, ℓ. We obtain the partition function of a massless scalar quantum field interacting with the height profile of the surface via a δ-function potential. The partition function is given by a holographic reduction of this model to three coupled scalar fields on a two-dimensional plane. The original three-dimensional space with a flat parallel plate at a distance a from the rough plate is encoded in the nonlocal propagators of the surface fields on its boundary. Feynman rules for this equivalent 2+1-dimensional model are derived and its counterterms constructed. The two-loop contribution to the free energy of this model gives the leading roughness correction. The effective separation, aeff, to a rough plate is measured to a plane that is displaced a distance ρ∝σ2/ℓ from the mean of its profile. This definition of the separation eliminates corrections to the free energy of order 1/a4 and results in unitary scattering matrices. We obtain an effective low-energy model in the limit ℓ≪a. It determines the scattering matrix and equivalent planar scattering surface of a very rough plate in terms of the single length scale ρ. The Casimir force on a rough plate is found to always weaken with decreasing correlation length ℓ. The two-loop approximation to the free energy interpolates between the free energy of the effective low-energy model and that of the proximity force approximation - the force on a very rough plate with σ≳0.5ℓ being weaker than on a planar Dirichlet surface at any separation.

Empirical microeconomics action functionals

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Du, Xin; Tanputraman, Winson

2015-06-01

A statistical generalization of microeconomics has been made in Baaquie (2013), where the market price of every traded commodity, at each instant of time, is considered to be an independent random variable. The dynamics of commodity market prices is modeled by an action functional-and the focus of this paper is to empirically determine the action functionals for different commodities. The correlation functions of the model are defined using a Feynman path integral. The model is calibrated using the unequal time correlation of the market commodity prices as well as their cubic and quartic moments using a perturbation expansion. The consistency of the perturbation expansion is verified by a numerical evaluation of the path integral. Nine commodities drawn from the energy, metal and grain sectors are studied and their market behavior is described by the model to an accuracy of over 90% using only six parameters. The paper empirically establishes the existence of the action functional for commodity prices that was postulated to exist in Baaquie (2013).

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

Free-energy functional of the Debye-Hückel model of simple fluids

NASA Astrophysics Data System (ADS)

Piron, R.; Blenski, T.

2016-12-01

The Debye-Hückel approximation to the free energy of a simple fluid is written as a functional of the pair correlation function. This functional can be seen as the Debye-Hückel equivalent to the functional derived in the hypernetted chain framework by Morita and Hiroike, as well as by Lado. It allows one to obtain the Debye-Hückel integral equation through a minimization with respect to the pair correlation function, leads to the correct form of the internal energy, and fulfills the virial theorem.

Bose--Einstein Correlations and Thermal Cluster Formation in High-energy Collisions

NASA Astrophysics Data System (ADS)

Bialas, A.; Florkowski, W.; Zalewski, K.

The blast wave model is generalized to include the production of thermal clusters, as suggested by the apparent success of the statistical model of particle production at high energies. The formulae for the HBT correlation functions and the corresponding HBT radii are derived.

A Semi-Empirical Model for Forecasting Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.

Understanding the atomic-level Green-Kubo stress correlation function for a liquid through phonons in a model crystal

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2014-11-01

In order to gain insight into the connection between the vibrational dynamics and the atomic-level Green-Kubo stress correlation function in liquids, we consider this connection in a model crystal instead. Of course, vibrational dynamics in liquids and crystals are quite different and it is not expected that the results obtained on a model crystal should be valid for liquids. However, these considerations provide a benchmark to which the results of the previous molecular dynamics simulations can be compared. Thus, assuming that vibrations are plane waves, we derive analytical expressions for the atomic-level stress correlation functions in the classical limit and analyze them. These results provide, in particular, a recipe for analysis of the atomic-level stress correlation functions in Fourier space and extraction of the wave-vector and frequency-dependent information. We also evaluate the energies of the atomic-level stresses. The energies obtained are significantly smaller than the energies previously determined in molecular dynamics simulations of several model liquids. This result suggests that the average energies of the atomic-level stresses in liquids and glasses are largely determined by the structural disorder. We discuss this result in the context of equipartition of the atomic-level stress energies. Analysis of the previously published data suggests that it is possible to speak about configurational and vibrational contributions to the average energies of the atomic-level stresses in a glass state. However, this separation in a liquid state is problematic. We also introduce and briefly consider the atomic-level transverse current correlation function. Finally, we address the broadening of the peaks in the pair distribution function with increase of distance. We find that the peaks' broadening (by ≈40 % ) occurs due to the transverse vibrational modes, while contribution from the longitudinal modes does not change with distance.

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.

Mechanism for subgap optical conductivity in honeycomb Kitaev materials

NASA Astrophysics Data System (ADS)

Bolens, Adrien; Katsura, Hosho; Ogata, Masao; Miyashita, Seiji

2018-04-01

Motivated by recent terahertz absorption measurements in α -RuCl3 , we develop a theory for the electromagnetic absorption of materials described by the Kitaev model on the honeycomb lattice. We derive a mechanism for the polarization operator at second order in the nearest-neighbor hopping Hamiltonian. Using the exact results of the Kitaev honeycomb model, we then calculate the polarization dynamical correlation function corresponding to electric dipole transitions in addition to the spin dynamical correlation function corresponding to magnetic dipole transitions.

Data Analysis Techniques for Physical Scientists

NASA Astrophysics Data System (ADS)

Pruneau, Claude A.

2017-10-01

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

Inhomogeneity induced and appropriately parameterized semilocal exchange and correlation energy functionals in two-dimensions.

PubMed

Patra, Abhilash; Jana, Subrata; Samal, Prasanjit

2018-04-07

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate techniques to design semilocal exchange energy functionals in two-dimensional density functional formalism. The exchange holes modeled using DME possess unique features that make it a superior entity. Parameterized semilocal exchange energy functionals based on the DME are proposed. The use of different forms of the momentum and flexible parameters is to subsume the non-uniform effects of the density in the newly constructed semilocal functionals. In addition to the exchange functionals, a suitable correlation functional is also constructed by working upon the local correlation functional developed for 2D homogeneous electron gas. The non-local effects are induced into the correlation functional by a parametric form of one of the newly constructed exchange energy functionals. The proposed functionals are applied to the parabolic quantum dots with a varying number of confined electrons and the confinement strength. The results obtained with the aforementioned functionals are quite satisfactory, which indicates why these are suitable for two-dimensional quantum systems.

Inhomogeneity induced and appropriately parameterized semilocal exchange and correlation energy functionals in two-dimensions

NASA Astrophysics Data System (ADS)

Patra, Abhilash; Jana, Subrata; Samal, Prasanjit

2018-04-01

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate techniques to design semilocal exchange energy functionals in two-dimensional density functional formalism. The exchange holes modeled using DME possess unique features that make it a superior entity. Parameterized semilocal exchange energy functionals based on the DME are proposed. The use of different forms of the momentum and flexible parameters is to subsume the non-uniform effects of the density in the newly constructed semilocal functionals. In addition to the exchange functionals, a suitable correlation functional is also constructed by working upon the local correlation functional developed for 2D homogeneous electron gas. The non-local effects are induced into the correlation functional by a parametric form of one of the newly constructed exchange energy functionals. The proposed functionals are applied to the parabolic quantum dots with a varying number of confined electrons and the confinement strength. The results obtained with the aforementioned functionals are quite satisfactory, which indicates why these are suitable for two-dimensional quantum systems.

Modeling multivariate time series on manifolds with skew radial basis functions.

PubMed

Jamshidi, Arta A; Kirby, Michael J

2011-01-01

We present an approach for constructing nonlinear empirical mappings from high-dimensional domains to multivariate ranges. We employ radial basis functions and skew radial basis functions for constructing a model using data that are potentially scattered or sparse. The algorithm progresses iteratively, adding a new function at each step to refine the model. The placement of the functions is driven by a statistical hypothesis test that accounts for correlation in the multivariate range variables. The test is applied on training and validation data and reveals nonstatistical or geometric structure when it fails. At each step, the added function is fit to data contained in a spatiotemporally defined local region to determine the parameters--in particular, the scale of the local model. The scale of the function is determined by the zero crossings of the autocorrelation function of the residuals. The model parameters and the number of basis functions are determined automatically from the given data, and there is no need to initialize any ad hoc parameters save for the selection of the skew radial basis functions. Compactly supported skew radial basis functions are employed to improve model accuracy, order, and convergence properties. The extension of the algorithm to higher-dimensional ranges produces reduced-order models by exploiting the existence of correlation in the range variable data. Structure is tested not just in a single time series but between all pairs of time series. We illustrate the new methodologies using several illustrative problems, including modeling data on manifolds and the prediction of chaotic time series.

Virasoro constraints for D 2n + 1 -, E 6 -, E 7 -, E 8 -type minimal models coupled to 2D gravity

NASA Astrophysics Data System (ADS)

Yen, Tim

1990-12-01

We find Virasoro constraints for D 2 n + 1 -, E 6 -, E 7 -, E 8 -type models analogous to the recently discovered Virasoro constraints for A n-type models by Fukuma et al., and Dijkgraaf et al. We verify that the proposed Virasoro constraints give operator scaling dimensions identical to those found by Kostov. We check that these Virasoro constraints and, more generally, W-algebra constraints can be used to express correlation functions with non-primary operator in terms of correlation functions of primary operators only.

Virial Coefficients for the Liquid Argon

NASA Astrophysics Data System (ADS)

Korth, Micheal; Kim, Saesun

2014-03-01

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

[Relationship between cognitive function and physical activities: a longitudinal study among community-dwelling elderly].

PubMed

Konagaya, Yoko; Watanabe, Tomoyuki; Ohta, Toshiki

2012-01-01

The purpose of this study was to evaluate whether physical activities reduce the risk of cognitive decline in community-dwelling elderly. We investigated correlations between cognitive functions at baseline and physical activities, correlations between cognitive functions at baseline and cognitive decline over 4 years, as well as correlations between physical activity at baseline and cognitive decline over 4 years. At baseline, 2,431 community-dwelling elderly completed the cognitive screening by telephone (TICS-J), and answered the questionnaires about physical activities. Of these, 1,040 subjects again completed the TICS-J over 4 years. Physical activities contained moving ability, walking frequency, walking speed, the exercise frequency. At baseline, 870 elderly (age 75.87±4.96 (mean±SD) years, duration of education 11.05±2.41) showed normal cognitive functions and 170 (79.19±6.22, 9.61±2.23) showed cognitive impairment. The total TICS-J score was significantly higher in cognitive normal subjects compared with that of cognitive impaired subjects (36.02±1.89, 30.19±2.25, respectively, p<0.001). Logistic regression analyses showed that moving ability significantly reduced the risk of cognitive impairment in an unadjusted model, and walking speed also reduced the risk of cognitive impairment at baseline even in an adjusted model. Cognitive function at baseline might be a predictor of cognitive function over 4 years. The longitudinal study revealed that walking speed and exercise frequency significantly correlate with maintenance of cognitive function over 4 years. This study provides that physical activities, especially walking speed have significant correlation with cognitive function.

Nonparametric Transfer Function Models

PubMed Central

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Positive association of free triiodothyronine with pancreatic β-cell function in people with prediabetes.

PubMed

Oda, T; Taneichi, H; Takahashi, K; Togashi, H; Hangai, M; Nakagawa, R; Ono, M; Matsui, M; Sasai, T; Nagasawa, K; Honma, H; Kajiwara, T; Takahashi, Y; Takebe, N; Ishigaki, Y; Satoh, J

2015-02-01

To analyse the effects of thyroid hormones on β-cell function and glucose metabolism in people with prediabetes who are euthyroid. A total of 111 people who were euthyroid underwent 75-g oral glucose tolerance tests, of whom 52 were assigned to the normal glucose tolerance and 59 to the prediabetes groups. Homeostatic model assessment of β-cell function, insulinogenic index and areas under the curve for insulin and glucose were evaluated as indices of pancreatic β-cell function. In both groups, BMI, fasting insulin, homeostasis model assessment ratio and HDL cholesterol correlated significantly with all indices of pancreatic β-cell function. Free triiodothyronine correlated positively with all insulin secretion indices in the prediabetes group. Multiple linear regression analysis showed that free triiodothyronine was an independent variable that had a positive correlation with all indices of β-cell function in the prediabetes group. By contrast, no such correlation was found in the normal glucose tolerance group. Free triiodothyronine is associated with both basal and glucose-stimulated insulin secretion in people with prediabetes who are euthyroid; therefore, the regulation of insulin secretion by thyroid hormones is a potentially novel therapeutic target for the treatment of diabetes. © 2014 The Authors. Diabetic Medicine © 2014 Diabetes UK.

[Correlations Between Joint Proprioception, Muscle Strength, and Functional Ability in Patients with Knee Osteoarthritis].

PubMed

Chen, Yoa; Yu, Yong; He, Cheng-qi

2015-11-01

To establish correlations between joint proprioception, muscle flexion and extension peak torque, and functional ability in patients with knee osteoarthritis (OA). Fifty-six patients with symptomatic knee OA were recruited in this study. Both proprioceptive acuity and muscle strength were measured using the isomed-2000 isokinetic dynamometer. Proprioceptive acuity was evaluated by establishing the joint motion detection threshold (JMDT). Muscle strength was evaluated by Max torque (Nm) and Max torque/weight (Nm/ kg). Functional ability was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlational analyses were performed between proprioception, muscle strength, and functional ability. A multiple stepwise regression model was established, with WOMAC-PF as dependent variable and patient age, body mass index (BMI), visual analogue scale (VAS)-score, mean grade for Kellgren-Lawrance of both knees, mean strength for quadriceps and hamstring muscles of both knees, and mean JMDT of both knees as independent variables. Poor proprioception (high JMDT) was negatively correlated with muscle strength (P<0.05). There was no significant correlation between knee proprioception (high JMDT) and joint pain (WOMAC pain score), and between knee proprioception (high JMDT) and joint stiffness (WOMAC stiffness score). Poor proprioception (high JMDT) was correlated with limitation in functional ability (WOMAC physical function score r=0.659, P<0.05). WOMAC score was correlated with poor muscle strength (quadriceps muscle strength r = -0.511, P<0.05, hamstring muscle strength r = -0.408, P<0.05). The multiple stepwise regression model showed that high JMDT C standard partial regression coefficient (B) = 0.385, P<0.50 and high VAS-scale score (B=0.347, P<0.05) were significant predictors of WOMAC-PF score. Patients with poor proprioception is associated with poor muscle strength and limitation in functional ability. Patients with symptomatic OA of knees commonly endure with moderate to considerable dysfunction, which is associated with poor proprioception (high JMDT) and high VAS-scale score.

Site-occupation embedding theory using Bethe ansatz local density approximations

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Nakatani, Naoki; Tsuchiizu, Masahisa; Fromager, Emmanuel

2018-06-01

Site-occupation embedding theory (SOET) is an alternative formulation of density functional theory (DFT) for model Hamiltonians where the fully interacting Hubbard problem is mapped, in principle exactly, onto an impurity-interacting (rather than a noninteracting) one. It provides a rigorous framework for combining wave-function (or Green function)-based methods with DFT. In this work, exact expressions for the per-site energy and double occupation of the uniform Hubbard model are derived in the context of SOET. As readily seen from these derivations, the so-called bath contribution to the per-site correlation energy is, in addition to the latter, the key density functional quantity to model in SOET. Various approximations based on Bethe ansatz and perturbative solutions to the Hubbard and single-impurity Anderson models are constructed and tested on a one-dimensional ring. The self-consistent calculation of the embedded impurity wave function has been performed with the density-matrix renormalization group method. It has been shown that promising results are obtained in specific regimes of correlation and density. Possible further developments have been proposed in order to provide reliable embedding functionals and potentials.

Influence of the exchange and correlation functional on the structure of amorphous InSb and In{sub 3}SbTe{sub 2} compounds

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

Gabardi, Silvia; Caravati, Sebastiano; Bernasconi, Marco, E-mail: marco.bernasconi@mater.unimib.it

2016-05-28

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In{sub 3}SbTe{sub 2} compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtainedmore » with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge{sub 2}Sb{sub 2}Te{sub 5} phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.« less

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

NASA Astrophysics Data System (ADS)

Rose, F.; Dupuis, N.

2018-05-01

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

2D Echocardiographic Evaluation of Right Ventricular Function Correlates With 3D Volumetric Models in Cardiac Surgery Patients.

PubMed

Magunia, Harry; Schmid, Eckhard; Hilberath, Jan N; Häberle, Leo; Grasshoff, Christian; Schlensak, Christian; Rosenberger, Peter; Nowak-Machen, Martina

2017-04-01

The early diagnosis and treatment of right ventricular (RV) dysfunction are of critical importance in cardiac surgery patients and impact clinical outcome. Two-dimensional (2D) transesophageal echocardiography (TEE) can be used to evaluate RV function using surrogate parameters due to complex RV geometry. The aim of this study was to evaluate whether the commonly used visual evaluation of RV function and size using 2D TEE correlated with the calculated three-dimensional (3D) volumetric models of RV function. Retrospective study, single center, University Hospital. Seventy complete datasets were studied consisting of 2D 4-chamber view loops (2-3 beats) and the corresponding 4-chamber view 3D full-volume loop of the right ventricle. RV function and RV size of the 2D loops then were assessed retrospectively purely qualitatively individually by 4 clinician echocardiographers certified in perioperative TEE. Corresponding 3D volumetric models calculating RV ejection fraction and RV end-diastolic volumes then were established and compared with the 2D assessments. 2D assessment of RV function correlated with 3D volumetric calculations (Spearman's rho -0.5; p<0.0001). No correlation could be established between 2D estimates of RV size and actual 3D volumetric end-diastolic volumes (Spearman's rho 0.15; p = 0.25). The 2D assessment of right ventricular function based on visual estimation as frequently used in clinical practice appeared to be a reliable method of RV functional evaluation. However, 2D assessment of RV size seemed unreliable and should be used with caution. Copyright © 2017 Elsevier Inc. All rights reserved.

Method of model reduction and multifidelity models for solute transport in random layered porous media

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

Xu, Zhijie; Tartakovsky, Alexandre M.

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a known velocity covariance function. In the hierarchical model, we represent (random) concentration in terms of its cross-sectional average and a variation function. We derive a one-dimensional stochastic advection-dispersion-type equation for the average concentration and a stochastic Poisson equation for the variation function, as well as expressions for the effective velocity and dispersion coefficient. We observe that velocity fluctuations enhance dispersion in a non-monotonic fashion: the dispersionmore » initially increases with correlation length λ, reaches a maximum, and decreases to zero at infinity. Maximum enhancement can be obtained at the correlation length about 0.25 the size of the porous media perpendicular to flow.« less

Spatiotemporal correlation buildup after an interaction quench in the Luttinger model

NASA Astrophysics Data System (ADS)

Abeling, Nils O.; Kehrein, Stefan

We study the evolution of density-density correlations at different times and distances in the exactly solvable Luttinger model after a sudden quench from the ground state. We discuss the difference between correlations and susceptibilities, and how these results can be interpreted from the point of view of Lieb-Robinson bounds. For the correlation functions we specifically show that pre-quench entanglement in the ground state leads to algebraically decaying long distance tails outside the light cone.

High-redshift Luminous Red Galaxies clustering analysis in SDSS Stripe82

NASA Astrophysics Data System (ADS)

Nikoloudakis, N.

2012-01-01

We have measured the clustering of Luminous Red Galaxies in Stripe 82 using the angular correlation function. We have selected 130000 LRGs via colour cuts in R-I:I-K with the K band data coming from UKIDSS LAS. We have used the cross-correlation technique of Newman (2008) to establish the redshift distribution of the LRGs as a function of colour cut, cross-correlating the LRGs with SDSS QSOs, DEEP2 and VVDS galaxies. We also used the AUS LRG redshift survey to establish the n(z) at z<1. We then compare the w(theta) results to the results of Sawangwit et al (2010) from 3 samples of SDSS LRGs at lower redshift to measure the dependence of clustering on redshift and LRG luminosity. We have compared the results for luminosity-matched LRG samples with simple evolutionary models, such as those expected from long-lived, passive models for LRGs and for the HOD models of Wake et al (2009) and find that the long-lived model may be a poorer fit than at lower redshifts. We find some evidence for evolution in the LRG correlation function slope in that the 2-halo term appears to flatten in slope at z>1. We present arguments that this is not caused by systematics.

Phase transition in 2-d system of quadrupoles on square lattice with anisotropic field

NASA Astrophysics Data System (ADS)

Sallabi, A. K.; Alkhttab, M.

2014-12-01

Monte Carlo method is used to study a simple model of two-dimensional interacting quadrupoles on ionic square lattice with anisotropic strength provided by the ionic lattice. Order parameter, susceptibility and correlation function data, show that this system form an ordered structure with p(2×1) symmetry at low temperature. The p(2×1) structure undergoes an order-disorder phase transition into disordered (1×1) phase at 8.3K. The two-point correlation function show exponential dependence on distance both above and below the transition temperature. At Tc the two-point correlation function shows a power law dependence on distance, e.g. C(r) ~ 1η. The value of the exponent η at Tc shows small deviation from the Ising value and indicates that this system falls into the same universality class as the XY model with cubic anisotropy. This model can be applied to prototypical quadrupoles physisorbed systems as N2 on NaCl(100).

Statistical theory of correlations in random packings of hard particles.

PubMed

Jin, Yuliang; Puckett, James G; Makse, Hernán A

2014-05-01

A random packing of hard particles represents a fundamental model for granular matter. Despite its importance, analytical modeling of random packings remains difficult due to the existence of strong correlations which preclude the development of a simple theory. Here, we take inspiration from liquid theories for the n-particle angular correlation function to develop a formalism of random packings of hard particles from the bottom up. A progressive expansion into a shell of particles converges in the large layer limit under a Kirkwood-like approximation of higher-order correlations. We apply the formalism to hard disks and predict the density of two-dimensional random close packing (RCP), ϕ(rcp) = 0.85 ± 0.01, and random loose packing (RLP), ϕ(rlp) = 0.67 ± 0.01. Our theory also predicts a phase diagram and angular correlation functions that are in good agreement with experimental and numerical data.

Gaussian statistics of the cosmic microwave background: Correlation of temperature extrema in the COBE DMR two-year sky maps

NASA Technical Reports Server (NTRS)

Kogut, A.; Banday, A. J.; Bennett, C. L.; Hinshaw, G.; Lubin, P. M.; Smoot, G. F.

1995-01-01

We use the two-point correlation function of the extrema points (peaks and valleys) in the Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) 2 year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background anisotropy. A maximum-likelihood analysis compares the DMR data to n = 1 toy models whose random-phase spherical harmonic components a(sub lm) are drawn from either Gaussian, chi-square, or log-normal parent populations. The likelihood of the 53 GHz (A+B)/2 data is greatest for the exact Gaussian model. There is less than 10% chance that the non-Gaussian models tested describe the DMR data, limited primarily by type II errors in the statistical inference. The extrema correlation function is a stronger test for this class of non-Gaussian models than topological statistics such as the genus.

Noninvasive measurement of dynamic correlation functions

NASA Astrophysics Data System (ADS)

Uhrich, Philipp; Castrignano, Salvatore; Uys, Hermann; Kastner, Michael

2017-08-01

The measurement of dynamic correlation functions of quantum systems is complicated by measurement backaction. To facilitate such measurements we introduce a protocol, based on weak ancilla-system couplings, that is applicable to arbitrary (pseudo)spin systems and arbitrary equilibrium or nonequilibrium initial states. Different choices of the coupling operator give access to the real and imaginary parts of the dynamic correlation function. This protocol reduces disturbances due to the early-time measurements to a minimum, and we quantify the deviation of the measured correlation functions from the theoretical, unitarily evolved ones. Implementations of the protocol in trapped ions and other experimental platforms are discussed. For spin-1 /2 models and single-site observables we prove that measurement backaction can be avoided altogether, allowing for the use of ancilla-free protocols.

Rigorous proof for the nonlocal correlation function in the transverse Ising model with ring frustration.

PubMed

Dong, Jian-Jun; Zheng, Zhen-Yu; Li, Peng

2018-01-01

An unusual correlation function was conjectured by Campostrini et al. [Phys. Rev. E 91, 042123 (2015)PLEEE81539-375510.1103/PhysRevE.91.042123] for the ground state of a transverse Ising chain with geometrical frustration. Later, we provided a rigorous proof for it and demonstrated its nonlocal nature based on an evaluation of a Toeplitz determinant in the thermodynamic limit [J. Stat. Mech. (2016) 11310210.1088/1742-5468/2016/11/113102]. In this paper, we further prove that all the low excited energy states forming the gapless kink phase share the same asymptotic correlation function with the ground state. As a consequence, the thermal correlation function almost remains constant at low temperatures if one assumes a canonical ensemble.

Aggregation models on hypergraphs

NASA Astrophysics Data System (ADS)

Alberici, Diego; Contucci, Pierluigi; Mingione, Emanuele; Molari, Marco

2017-01-01

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer-dimer case. After translating those relations into structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.

Passive advection of a vector field: Anisotropy, finite correlation time, exact solution, and logarithmic corrections to ordinary scaling

NASA Astrophysics Data System (ADS)

Antonov, N. V.; Gulitskiy, N. M.

2015-10-01

In this work we study the generalization of the problem considered in [Phys. Rev. E 91, 013002 (2015), 10.1103/PhysRevE.91.013002] to the case of finite correlation time of the environment (velocity) field. The model describes a vector (e.g., magnetic) field, passively advected by a strongly anisotropic turbulent flow. Inertial-range asymptotic behavior is studied by means of the field theoretic renormalization group and the operator product expansion. The advecting velocity field is Gaussian, with finite correlation time and preassigned pair correlation function. Due to the presence of distinguished direction n , all the multiloop diagrams in this model vanish, so that the results obtained are exact. The inertial-range behavior of the model is described by two regimes (the limits of vanishing or infinite correlation time) that correspond to the two nontrivial fixed points of the RG equations. Their stability depends on the relation between the exponents in the energy spectrum E ∝k⊥1 -ξ and the dispersion law ω ∝k⊥2 -η . In contrast to the well-known isotropic Kraichnan's model, where various correlation functions exhibit anomalous scaling behavior with infinite sets of anomalous exponents, here the corrections to ordinary scaling are polynomials of logarithms of the integral turbulence scale L .

Modelling nematode movement using time-fractional dynamics.

PubMed

Hapca, Simona; Crawford, John W; MacMillan, Keith; Wilson, Mike J; Young, Iain M

2007-09-07

We use a correlated random walk model in two dimensions to simulate the movement of the slug parasitic nematode Phasmarhabditis hermaphrodita in homogeneous environments. The model incorporates the observed statistical distributions of turning angle and speed derived from time-lapse studies of individual nematode trails. We identify strong temporal correlations between the turning angles and speed that preclude the case of a simple random walk in which successive steps are independent. These correlated random walks are appropriately modelled using an anomalous diffusion model, more precisely using a fractional sub-diffusion model for which the associated stochastic process is characterised by strong memory effects in the probability density function.

Why Are Experts Correlated? Decomposing Correlations between Judges

ERIC Educational Resources Information Center

Broomell, Stephen B.; Budescu, David V.

2009-01-01

We derive an analytic model of the inter-judge correlation as a function of five underlying parameters. Inter-cue correlation and the number of cues capture our assumptions about the environment, while differentiations between cues, the weights attached to the cues, and (un)reliability describe assumptions about the judges. We study the relative…

The ACS Survey of Galactic Globular Clusters. VIII. Effects of Environment on Globular Cluster Global Mass Functions

NASA Astrophysics Data System (ADS)

Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael

2010-02-01

We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, H.

2017-12-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, some studies suggested possible links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their mechanisms, we need an accurate 3D crustal wavespeed model for North Texas and Oklahoma. Considering the uneven distribution of earthquakes in this region, seismic tomography with local earthquake records have difficulties to achieve good illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. 25 preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model M25 correlates with geological units in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front. In addition, these seismic anomalies correlate with gravity and magnetic observations. This new model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location and moment tensor solutions, which are important for investigating potential relations between seismicity and unconventional oil and gas exploration.

A Patch Density Recommendation based on Convergence Studies for Vehicle Panel Vibration Response resulting from Excitation by a Diffuse Acoustic Field

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Waldon, James; Hunt, Ron

2013-01-01

Producing fluid structural interaction estimates of panel vibration from an applied pressure field excitation are quite dependent on the spatial correlation of the pressure field. There is a danger of either over estimating a low frequency response or under predicting broad band panel response in the more modally dense bands if the pressure field spatial correlation is not accounted for adequately. It is a useful practice to simulate the spatial correlation of the applied pressure field over a 2d surface using a matrix of small patch area regions on a finite element model (FEM). Use of a fitted function for the spatial correlation between patch centers can result in an error if the choice of patch density is not fine enough to represent the more continuous spatial correlation function throughout the intended frequency range of interest. Several patch density assumptions to approximate the fitted spatial correlation function are first evaluated using both qualitative and quantitative illustrations. The actual response of a typical vehicle panel system FEM is then examined in a convergence study where the patch density assumptions are varied over the same model. The convergence study results illustrate the impacts possible from a poor choice of patch density on the analytical response estimate. The fitted correlation function used in this study represents a diffuse acoustic field (DAF) excitation of the panel to produce vibration response.

Spatial Correlation in the Ambient Core Noise Field of a Turbofan Engine

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2012-01-01

An acoustic transfer function relating combustion noise and turbine exit noise in the presence of enclosed ambient core noise is investigated using a dynamic system model and an acoustic system model for the particular turbofan engine studied and for a range of operating conditions. Measurements of cross-spectra magnitude and phase between the combustor and turbine exit and auto-spectra at the turbine exit and combustor are used to show the presence of indirect and direct combustion noise over the frequency range of 0 400 Hz. The procedure used evaluates the ratio of direct to indirect combustion noise. The procedure used also evaluates the post-combustion residence time in the combustor which is a factor in the formation of thermal NOx and soot in this region. These measurements are masked by the ambient core noise sound field in this frequency range which is observable since the transducers are situated within an acoustic wavelength of one another. An ambient core noise field model based on one and two dimensional spatial correlation functions is used to replicate the spatially correlated response of the pair of transducers. The spatial correlation function increases measured attenuation due to destructive interference and masks the true attenuation of the turbine.

The Generation, Radiation and Prediction of Supersonic Jet Noise. Volume 1

DTIC Science & Technology

1978-10-01

standard, Gaussian correlation function model can yield a good noise spectrum prediction (at 900), but the corresponding axial source distributions do not...forms for the turbulence cross-correlation function. Good agreement was obtained between measured and calculated far- field noise spectra. However, the...complementary error function profile (3.63) was found to provide a good fit to the axial velocity distribution tor a wide range of Mach numbers in the Initial

Stringy horizons and generalized FZZ duality in perturbation theory

NASA Astrophysics Data System (ADS)

Giribet, Gaston

2017-02-01

We study scattering amplitudes in two-dimensional string theory on a black hole bakground. We start with a simple derivation of the Fateev-Zamolodchikov-Zamolodchikov (FZZ) duality, which associates correlation functions of the sine-Liouville integrable model on the Riemann sphere to tree-level string amplitudes on the Euclidean two-dimensional black hole. This derivation of FZZ duality is based on perturbation theory, and it relies on a trick originally due to Fateev, which involves duality relations between different Selberg type integrals. This enables us to rewrite the correlation functions of sine-Liouville theory in terms of a special set of correlators in the gauged Wess-Zumino-Witten (WZW) theory, and use this to perform further consistency checks of the recently conjectured Generalized FZZ (GFZZ) duality. In particular, we prove that n-point correlation functions in sine-Liouville theory involving n - 2 winding modes actually coincide with the correlation functions in the SL(2,R)/U(1) gauged WZW model that include n - 2 oscillator operators of the type described by Giveon, Itzhaki and Kutasov in reference [1]. This proves the GFZZ duality for the case of tree level maximally winding violating n-point amplitudes with arbitrary n. We also comment on the connection between GFZZ and other marginal deformations previously considered in the literature.

Performance of correlation receivers in the presence of impulse noise.

NASA Technical Reports Server (NTRS)

Moore, J. D.; Houts, R. C.

1972-01-01

An impulse noise model, which assumes that each noise burst contains a randomly weighted version of a basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. Unlike the performance results for additive white Gaussian noise, it is shown that the error performance for impulse noise is affected by the choice of signal-set basis function, and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy. Furthermore, it is demonstrated that the correlation-receiver error performance can be improved by inserting a properly specified nonlinear device prior to the receiver input.

A general psychopathology factor in early adolescence.

PubMed

Patalay, Praveetha; Fonagy, Peter; Deighton, Jessica; Belsky, Jay; Vostanis, Panos; Wolpert, Miranda

2015-07-01

Recently, a general psychopathology dimension reflecting common aspects among disorders has been identified in adults. This has not yet been considered in children and adolescents, where the focus has been on externalising and internalising dimensions. To examine the existence, correlates and predictive value of a general psychopathology dimension in young people. Alternative factor models were estimated using self-reports of symptoms in a large community-based sample aged 11-13.5 years (N = 23 477), and resulting dimensions were assessed in terms of associations with external correlates and future functioning. Both a traditional two-factor model and a bi-factor model with a general psychopathology bi-factor fitted the data well. The general psychopathology bi-factor best predicted future psychopathology and academic attainment. Associations with correlates and factor loadings are discussed. A general psychopathology factor, which is equal across genders, can be identified in young people. Its associations with correlates and future functioning indicate that investigating this factor can increase our understanding of the aetiology, risk and correlates of psychopathology. © The Royal College of Psychiatrists 2015.

Exact diagonalization library for quantum electron models

NASA Astrophysics Data System (ADS)

Iskakov, Sergei; Danilov, Michael

2018-04-01

We present an exact diagonalization C++ template library (EDLib) for solving quantum electron models, including the single-band finite Hubbard cluster and the multi-orbital impurity Anderson model. The observables that can be computed using EDLib are single particle Green's functions and spin-spin correlation functions. This code provides three different types of Hamiltonian matrix storage that can be chosen based on the model.

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

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

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

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

On the Power of Multivariate Latent Growth Curve Models to Detect Correlated Change

ERIC Educational Resources Information Center

Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von

2006-01-01

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…

Genetic and Environmental Influences on Pulmonary Function and Muscle Strength: The Chinese Twin Study of Aging.

PubMed

Tian, Xiaocao; Xu, Chunsheng; Wu, Yili; Sun, Jianping; Duan, Haiping; Zhang, Dongfeng; Jiang, Baofa; Pang, Zengchang; Li, Shuxia; Tan, Qihua

2017-02-01

Genetic and environmental influences on predictors of decline in daily functioning, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), handgrip, and five-times-sit-to-stand test (FTSST), have not been addressed in the aging Chinese population. We performed classical twin modeling on FEV1, FVC, handgrip, and FTSST in 379 twin pairs (240 MZ and 139 DZ) with median age of 50 years (40-80 years). Data were analyzed by fitting univariate and bivariate twin models to estimate the genetic and environmental influences on these measures of physical function. Heritability was moderate for FEV1, handgrip, and FTSST (55-60%) but insignificant for FVC. Only FVC showed moderate control, with shared environmental factors accounting for about 50% of the total variance. In contrast, all measures of pulmonary function and muscle strength showed modest influences from the unique environment (40-50%). Bivariate analysis showed highly positive genetic correlations between FEV1 and FVC (r G = 1.00), and moderately negative genetic correlations between FTSST and FEV1 (r G = -0.33) and FVC (r G = -0.42). FEV1 and FVC, as well as FEV1 and handgrip, displayed high common environmental correlations (r C = 1.00), and there were moderate correlations between FVC and handgrip (r C = 0.44). FEV1 and FVC showed high unique environmental correlations (r E = 0.76) and low correlations between handgrip and FEV1 (r E = 0.17), FVC (r E = 0.14), and FTSST (r E = -0.13) with positive or negative direction. We conclude that genetic factors contribute significantly to the individual differences in common indicators of daily functioning (FEV1, handgrip, and FTSST). FEV1 and FVC were genetically and environmentally correlated. Pulmonary function and FTSST may share similar sets of genes but in the negative direction. Pulmonary function and muscle strength may have a shared environmental background.

Prediction Model for Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Relativistic Electrons at Geostationary Orbit: Modeling Results

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Electron Correlation from the Adiabatic Connection for Multireference Wave Functions

NASA Astrophysics Data System (ADS)

Pernal, Katarzyna

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

Chrétien, S.; Salahub, D. R.

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

Modeling lactation curves and estimation of genetic parameters in Holstein cows using multiple-trait random regression models.

PubMed

Kheirabadi, Khabat; Rashidi, Amir; Alijani, Sadegh; Imumorin, Ikhide

2014-11-01

We compared the goodness of fit of three mathematical functions (including: Legendre polynomials, Lidauer-Mäntysaari function and Wilmink function) for describing the lactation curve of primiparous Iranian Holstein cows by using multiple-trait random regression models (MT-RRM). Lactational submodels provided the largest daily additive genetic (AG) and permanent environmental (PE) variance estimates at the end and at the onset of lactation, respectively, as well as low genetic correlations between peripheral test-day records. For all models, heritability estimates were highest at the end of lactation (245 to 305 days) and ranged from 0.05 to 0.26, 0.03 to 0.12 and 0.04 to 0.24 for milk, fat and protein yields, respectively. Generally, the genetic correlations between traits depend on how far apart they are or whether they are on the same day in any two traits. On average, genetic correlations between milk and fat were the lowest and those between fat and protein were intermediate, while those between milk and protein were the highest. Results from all criteria (Akaike's and Schwarz's Bayesian information criterion, and -2*logarithm of the likelihood function) suggested that a model with 2 and 5 coefficients of Legendre polynomials for AG and PE effects, respectively, was the most adequate for fitting the data. © 2014 Japanese Society of Animal Science.

Quantum critical singularities in two-dimensional metallic XY ferromagnets

NASA Astrophysics Data System (ADS)

Varma, Chandra M.; Gannon, W. J.; Aronson, M. C.; Rodriguez-Rivera, J. A.; Qiu, Y.

2018-02-01

An important problem in contemporary physics concerns quantum-critical fluctuations in metals. A scaling function for the momentum, frequency, temperature, and magnetic field dependence of the correlation function near a 2D-ferromagnetic quantum-critical point (QCP) is constructed, and its singularities are determined by comparing to the recent calculations of the correlation functions of the dissipative quantum XY model (DQXY). The calculations are motivated by the measured properties of the metallic compound YFe2Al10 , which is a realization of the DQXY model in 2D. The frequency, temperature, and magnetic field dependence of the scaling function as well as the singularities measured in the experiments are given by the theory without adjustable exponents. The same model is applicable to the superconductor-insulator transitions, classes of metallic AFM-QCPs, and as fluctuations of the loop-current ordered state in hole-doped cuprates. The results presented here lend credence to the solution found for the 2D-DQXY model and its applications in understanding quantum-critical properties of diverse systems.

Exchange-Correlation Effects for Noncovalent Interactions in Density Functional Theory.

PubMed

Otero-de-la-Roza, A; DiLabio, Gino A; Johnson, Erin R

2016-07-12

In this article, we develop an understanding of how errors from exchange-correlation functionals affect the modeling of noncovalent interactions in dispersion-corrected density-functional theory. Computed CCSD(T) reference binding energies for a collection of small-molecule clusters are decomposed via a molecular many-body expansion and are used to benchmark density-functional approximations, including the effect of semilocal approximation, exact-exchange admixture, and range separation. Three sources of error are identified. Repulsion error arises from the choice of semilocal functional approximation. This error affects intermolecular repulsions and is present in all n-body exchange-repulsion energies with a sign that alternates with the order n of the interaction. Delocalization error is independent of the choice of semilocal functional but does depend on the exact exchange fraction. Delocalization error misrepresents the induction energies, leading to overbinding in all induction n-body terms, and underestimates the electrostatic contribution to the 2-body energies. Deformation error affects only monomer relaxation (deformation) energies and behaves similarly to bond-dissociation energy errors. Delocalization and deformation errors affect systems with significant intermolecular orbital interactions (e.g., hydrogen- and halogen-bonded systems), whereas repulsion error is ubiquitous. Many-body errors from the underlying exchange-correlation functional greatly exceed in general the magnitude of the many-body dispersion energy term. A functional built to accurately model noncovalent interactions must contain a dispersion correction, semilocal exchange, and correlation components that minimize the repulsion error independently and must also incorporate exact exchange in such a way that delocalization error is absent.

Parity oscillations and photon correlation functions in the Z2-U (1 ) Dicke model at a finite number of atoms or qubits

NASA Astrophysics Data System (ADS)

Yi-Xiang, Yu; Ye, Jinwu; Zhang, CunLin

2016-08-01

Four standard quantum optics models, that is, the Rabi, Dicke, Jaynes-Cummings, and Tavis-Cummings models, were proposed by physicists many decades ago. Despite their relative simple forms and many previous theoretical works, their physics at a finite N , especially inside the superradiant regime, remain unknown. In this work, by using the strong-coupling expansion and exact diagonalization (ED), we study the Z2-U(1 ) Dicke model with independent rotating-wave coupling g and counterrotating-wave coupling g' at a finite N . This model includes the four standard quantum optics models as its various special limits. We show that in the superradiant phase, the system's energy levels are grouped into doublets with even and odd parity. Any anisotropy β =g'/g ≠1 leads to the oscillation of parities in both the ground and excited doublets as the atom-photon coupling strength increases. The oscillations will be pushed to the infinite coupling strength in the isotropic Z2 limit β =1 . We find nearly perfect agreement between the strong-coupling expansion and the ED in the superradiant regime when β is not too small. We also compute the photon correlation functions, squeezing spectrum, and number correlation functions that can be measured by various standard optical techniques.

Dannie Heineman Prize for Mathematical Physics Prize Lecture: Correlation Functions in Integrable Models II: The Role of Quantum Affine Symmetry

NASA Astrophysics Data System (ADS)

Jimbo, Michio

2013-03-01

Since the beginning of 1980s, hidden infinite dimensional symmetries have emerged as the origin of integrability: first in soliton theory and then in conformal field theory. Quest for symmetries in quantum integrable models has led to the discovery of quantum groups. On one hand this opened up rapid mathematical developments in representation theory, combinatorics and other fields. On the other hand it has advanced understanding of correlation functions of lattice models, leading to multiple integral formulas in integrable spin chains. We shall review these developments which continue up to the present time.

Shot noise cross-correlation functions and cross spectra - Implications for models of QPO X-ray sources

NASA Technical Reports Server (NTRS)

Shibazaki, N.; Elsner, R. F.; Bussard, R. W.; Ebisuzaki, T.; Weisskopf, M. C.

1988-01-01

The cross-correlation functions (CCFs) and cross spectra expected for quasi-periodic oscillation (QPO) shot noise models are calculated under various assumptions, and the results are compared to observations. Effects due to possible coherence of the QPO oscillations are included. General formulas for the cross spectrum, the cross-phase spectrum, and the time-delay spectrum for QPO shot models are calculated and discussed. It is shown that the CCFs, cross spectra, and power spectra observed for Cyg X-e2 imply that the spectrum of the shots evolves with time, with important implications for the interpretation of these functions as well as of observed average energy spectra. The possible origins for the observed hard lags are discussed, and some physical difficulties for the Comptonization model are described. Classes of physical models for QPO sources are briefly addressed, and it is concluded that models involving shot formation at the surface of neutron stars are favored by observation.

Multivariate η-μ fading distribution with arbitrary correlation model

NASA Astrophysics Data System (ADS)

Ghareeb, Ibrahim; Atiani, Amani

2018-03-01

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

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

Percolation analysis for cosmic web with discrete points

NASA Astrophysics Data System (ADS)

Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung

2018-01-01

Percolation analysis has long been used to quantify the connectivity of the cosmic web. Most of the previous work is based on density fields on grids. By smoothing into fields, we lose information about galaxy properties like shape or luminosity. The lack of mathematical modeling also limits our understanding for the percolation analysis. To overcome these difficulties, we have studied percolation analysis based on discrete points. Using a friends-of-friends (FoF) algorithm, we generate the S -b b relation, between the fractional mass of the largest connected group (S ) and the FoF linking length (b b ). We propose a new model, the probability cloud cluster expansion theory to relate the S -b b relation with correlation functions. We show that the S -b b relation reflects a combination of all orders of correlation functions. Using N-body simulation, we find that the S -b b relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with halo abundance matching (HAM), we have generated a mock galaxy catalog. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalog with the latest galaxy catalog from Sloan Digital Sky Survey (SDSS) Data Release (DR)12, we have found significant differences in their S -b b relations. This indicates that the mock galaxy catalog cannot accurately retain higher-order correlation functions than the two-point correlation function, which reveals the limit of the HAM method. As a new measurement, the S -b b relation is applicable to a wide range of data types, fast to compute, and robust against redshift distortion and incompleteness and contains information of all orders of correlation functions.

Basis set and electron correlation effects on the polarizability and second hyperpolarizability of model open-shell π-conjugated systems

NASA Astrophysics Data System (ADS)

Champagne, Benoı̂t; Botek, Edith; Nakano, Masayoshi; Nitta, Tomoshige; Yamaguchi, Kizashi

2005-03-01

The basis set and electron correlation effects on the static polarizability (α) and second hyperpolarizability (γ) are investigated ab initio for two model open-shell π-conjugated systems, the C5H7 radical and the C6H8 radical cation in their doublet state. Basis set investigations evidence that the linear and nonlinear responses of the radical cation necessitate the use of a less extended basis set than its neutral analog. Indeed, double-zeta-type basis sets supplemented by a set of d polarization functions but no diffuse functions already provide accurate (hyper)polarizabilities for C6H8 whereas diffuse functions are compulsory for C5H7, in particular, p diffuse functions. In addition to the 6-31G*+pd basis set, basis sets resulting from removing not necessary diffuse functions from the augmented correlation consistent polarized valence double zeta basis set have been shown to provide (hyper)polarizability values of similar quality as more extended basis sets such as augmented correlation consistent polarized valence triple zeta and doubly augmented correlation consistent polarized valence double zeta. Using the selected atomic basis sets, the (hyper)polarizabilities of these two model compounds are calculated at different levels of approximation in order to assess the impact of including electron correlation. As a function of the method of calculation antiparallel and parallel variations have been demonstrated for α and γ of the two model compounds, respectively. For the polarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset methods bracket the reference value obtained at the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples level whereas the projected unrestricted second-order Møller-Plesset results are in much closer agreement with the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples values than the projected unrestricted Hartree-Fock results. Moreover, the differences between the restricted open-shell Hartree-Fock and restricted open-shell second-order Møller-Plesset methods are small. In what concerns the second hyperpolarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset values remain of similar quality while using spin-projected schemes fails for the charged system but performs nicely for the neutral one. The restricted open-shell schemes, and especially the restricted open-shell second-order Møller-Plesset method, provide for both compounds γ values close to the results obtained at the unrestricted coupled cluster level including singles and doubles with a perturbative inclusion of the triples. Thus, to obtain well-converged α and γ values at low-order electron correlation levels, the removal of spin contamination is a necessary but not a sufficient condition. Density-functional theory calculations of α and γ have also been carried out using several exchange-correlation functionals. Those employing hybrid exchange-correlation functionals have been shown to reproduce fairly well the reference coupled cluster polarizability and second hyperpolarizability values. In addition, inclusion of Hartree-Fock exchange is of major importance for determining accurate polarizability whereas for the second hyperpolarizability the gradient corrections are large.

ΛΛ correlation function in Au + Au collisions at √ sNN = 200 GeV

DOE PAGES

Adamczyk, L.

2015-01-12

In this study, we present ΛΛ correlation measurements in heavy-ion collisions for Au+Au collisions at √ sNN = 200 GeV using the STAR experiment at the Relativistic Heavy-Ion Collider (RHIC). The Lednický-Lyuboshitz analytical model has been used to fit the data to obtain a source size, a scattering length and an effective range. Implications of the measurement of the ΛΛ correlation function and interaction parameters for di-hyperon searches are discussed.

Clinical Components of Borderline Personality Disorder and Personality Functioning.

PubMed

Ferrer, Marc; Andión, Óscar; Calvo, Natalia; Hörz, Susanne; Fischer-Kern, Melitta; Kapusta, Nestor D; Schneider, Gudrun; Clarkin, John F; Doering, Stephan

2018-01-01

Impairment in personality functioning (PF) represents a salient criterion of the DSM-5 alternative diagnostic model for personality disorders (AMPD). The main goal of this study is to analyze the relationship of the borderline personality disorder (BPD) clinical components derived from the DSM-5 categorical diagnostic model (affective dysregulation, behavioral dysregulation, and disturbed relatedness) with personality organization (PO), i.e., PF, assessed by the Structured Interview of Personality Organization (STIPO). STIPO and the Structured Clinical Interviews for DSM-IV (SCID-I and -II) were administered to 206 BPD patients. The relationship between PO and BPD components were studied using Spearman correlations and independent linear regression analyses. Significant positive correlations were observed between STIPO scores and several DSM-5 BPD criteria and comorbid psychiatric disorders. STIPO dimensions mainly correlated with disturbed relatedness and, to a lesser extent, affective dysregulation components. Each BPD clinical component was associated with specific STIPO dimensions. Both diagnostic models, DSM-5 BPD criteria and PO, are not only related but complementary concepts. The results of this study particularly recommend STIPO for the assessment of relational functioning, which is a major domain of the Personality Functioning Scale Levels of the DSM-5 AMPD. © 2018 S. Karger AG, Basel.

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Local density approximation in site-occupation embedding theory

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Tsuchiizu, Masahisa; Robert, Vincent; Fromager, Emmanuel

2017-01-01

Site-occupation embedding theory (SOET) is a density functional theory (DFT)-based method which aims at modelling strongly correlated electrons. It is in principle exact and applicable to model and quantum chemical Hamiltonians. The theory is presented here for the Hubbard Hamiltonian. In contrast to conventional DFT approaches, the site (or orbital) occupations are deduced in SOET from a partially interacting system consisting of one (or more) impurity site(s) and non-interacting bath sites. The correlation energy of the bath is then treated implicitly by means of a site-occupation functional. In this work, we propose a simple impurity-occupation functional approximation based on the two-level (2L) Hubbard model which is referred to as two-level impurity local density approximation (2L-ILDA). Results obtained on a prototypical uniform eight-site Hubbard ring are promising. The extension of the method to larger systems and more sophisticated model Hamiltonians is currently in progress.

Aggregation models on hypergraphs

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

Alberici, Diego, E-mail: diego.alberici2@unibo.it; Contucci, Pierluigi, E-mail: pierluigi.contucci@unibo.it; Mingione, Emanuele, E-mail: emanuele.mingione2@unibo.it

2017-01-15

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer–dimer case. After translating those relations intomore » structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.« less

Temporal correlation functions of concentration fluctuations: an anomalous case.

PubMed

Lubelski, Ariel; Klafter, Joseph

2008-10-09

We calculate, within the framework of the continuous time random walk (CTRW) model, multiparticle temporal correlation functions of concentration fluctuations (CCF) in systems that display anomalous subdiffusion. The subdiffusion stems from the nonstationary nature of the CTRW waiting times, which also lead to aging and ergodicity breaking. Due to aging, a system of diffusing particles tends to slow down as time progresses, and therefore, the temporal correlation functions strongly depend on the initial time of measurement. As a consequence, time averages of the CCF differ from ensemble averages, displaying therefore ergodicity breaking. We provide a simple example that demonstrates the difference between these two averages, a difference that might be amenable to experimental tests. We focus on the case of ensemble averaging and assume that the preparation time of the system coincides with the starting time of the measurement. Our analytical calculations are supported by computer simulations based on the CTRW model.

Finite-size effects on current correlation functions

NASA Astrophysics Data System (ADS)

Chen, Shunda; Zhang, Yong; Wang, Jiao; Zhao, Hong

2014-02-01

We study why the calculation of current correlation functions (CCFs) still suffers from finite-size effects even when the periodic boundary condition is taken. Two important one-dimensional, momentum-conserving systems are investigated as examples. Intriguingly, it is found that the state of a system recurs in the sense of microcanonical ensemble average, and such recurrence may result in oscillations in CCFs. Meanwhile, we find that the sound mode collisions induce an extra time decay in a current so that its correlation function decays faster (slower) in a smaller (larger) system. Based on these two unveiled mechanisms, a procedure for correctly evaluating the decay rate of a CCF is proposed, with which our analysis suggests that the global energy CCF decays as ˜t-2/3 in the diatomic hard-core gas model and in a manner close to ˜t-1/2 in the Fermi-Pasta-Ulam-β model.

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

2017-04-01

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

(Small) Resonant non-Gaussianities: Signatures of a Discrete Shift Symmetry in the Effective Field Theory of Inflation

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

Behbahani, Siavosh R.; /SLAC /Stanford U., Phys. Dept. /Boston U.; Dymarsky, Anatoly

2012-06-06

We apply the Effective Field Theory of Inflation to study the case where the continuous shift symmetry of the Goldstone boson {pi} is softly broken to a discrete subgroup. This case includes and generalizes recently proposed String Theory inspired models of Inflation based on Axion Monodromy. The models we study have the property that the 2-point function oscillates as a function of the wavenumber, leading to oscillations in the CMB power spectrum. The non-linear realization of time diffeomorphisms induces some self-interactions for the Goldstone boson that lead to a peculiar non-Gaussianity whose shape oscillates as a function of the wavenumber.more » We find that in the regime of validity of the effective theory, the oscillatory signal contained in the n-point correlation functions, with n > 2, is smaller than the one contained in the 2-point function, implying that the signature of oscillations, if ever detected, will be easier to find first in the 2-point function, and only then in the higher order correlation functions. Still the signal contained in higher-order correlation functions, that we study here in generality, could be detected at a subleading level, providing a very compelling consistency check for an approximate discrete shift symmetry being realized during inflation.« less

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

PubMed

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

2011-01-01

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

Uncertainty quantification for optical model parameters

DOE PAGES

Lovell, A. E.; Nunes, F. M.; Sarich, J.; ...

2017-02-21

Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of our work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fitmore » and create corresponding 95% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. Here, we study a number of reactions involving neutron and deuteron projectiles with energies in the range of 5–25 MeV/u, on targets with mass A=12–208. We investigate the correlations between the parameters in the fit. The case of deuterons on 12C is discussed in detail: the elastic-scattering fit and the prediction of 12C(d,p) 13C transfer angular distributions, using both uncorrelated and correlated χ 2 minimization functions. The general features for all cases are compiled in a systematic manner to identify trends. This work shows that, in many cases, the correlated χ 2 functions (in comparison to the uncorrelated χ 2 functions) provide a more natural parameterization of the process. These correlated functions do, however, produce broader confidence bands. Further optimization may require improvement in the models themselves and/or more information included in the fit.« less

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Li, Xuxu; Li, Xinyang; wang, Caixia

2018-03-01

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

Experimental and Analytical Investigation of the Coolant Flow Characteristics in Cooled Turbine Airfoils

NASA Technical Reports Server (NTRS)

Damerow, W. P.; Murtaugh, J. P.; Burggraf, F.

1972-01-01

The flow characteristics of turbine airfoil cooling system components were experimentally investigated. Flow models representative of leading edge impingement, impingement with crossflow (midchord cooling), pin fins, feeder supply tube, and a composite model of a complete airfoil flow system were tested. Test conditions were set by varying pressure level to cover the Mach number and Reynolds number range of interest in advanced turbine applications. Selected geometrical variations were studied on each component model to determine these effects. Results of these tests were correlated and compared with data available in the literature. Orifice flow was correlated in terms of discharge coefficients. For the leading edge model this was found to be a weak function of hole Mach number and orifice-to-impinged wall spacing. In the impingement with crossflow tests, the discharge coefficient was found to be constant and thus independent of orifice Mach number, Reynolds number, crossflow rate, and impingement geometry. Crossflow channel pressure drop showed reasonable agreement with a simple one-dimensional momentum balance. Feeder tube orifice discharge coefficients correlated as a function of orifice Mach number and the ratio of the orifice-to-approach velocity heads. Pin fin data was correlated in terms of equivalent friction factor, which was found to be a function of Reynolds number and pin spacing but independent of pin height in the range tested.

Theory of inhomogeneous quantum systems. III. Variational wave functions for Fermi fluids

NASA Astrophysics Data System (ADS)

Krotscheck, E.

1985-04-01

We develop a general variational theory for inhomogeneous Fermi systems such as the electron gas in a metal surface, the surface of liquid 3He, or simple models of heavy nuclei. The ground-state wave function is expressed in terms of two-body correlations, a one-body attenuation factor, and a model-system Slater determinant. Massive partial summations of cluster expansions are performed by means of Born-Green-Yvon and hypernetted-chain techniques. An optimal single-particle basis is generated by a generalized Hartree-Fock equation in which the two-body correlations screen the bare interparticle interaction. The optimization of the pair correlations leads to a state-averaged random-phase-approximation equation and a strictly microscopic determination of the particle-hole interaction.

Accurate Semilocal Density Functional for Condensed-Matter Physics and Quantum Chemistry.

PubMed

Tao, Jianmin; Mo, Yuxiang

2016-08-12

Most density functionals have been developed by imposing the known exact constraints on the exchange-correlation energy, or by a fit to a set of properties of selected systems, or by both. However, accurate modeling of the conventional exchange hole presents a great challenge, due to the delocalization of the hole. Making use of the property that the hole can be made localized under a general coordinate transformation, here we derive an exchange hole from the density matrix expansion, while the correlation part is obtained by imposing the low-density limit constraint. From the hole, a semilocal exchange-correlation functional is calculated. Our comprehensive test shows that this functional can achieve remarkable accuracy for diverse properties of molecules, solids, and solid surfaces, substantially improving upon the nonempirical functionals proposed in recent years. Accurate semilocal functionals based on their associated holes are physically appealing and practically useful for developing nonlocal functionals.

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

PubMed

Johnson, Erin R; Contreras-García, Julia

2011-08-28

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

Dynamical Correlation In Some Liquid Alkaline Earth Metals Near Melting

NASA Astrophysics Data System (ADS)

Thakore, B. Y.; Suthar, P. H.; Khambholja, S. G.; Gajjar, P. N.; Jani, A. R.

2010-12-01

The study of dynamical variables: velocity autocorrelation function (VACF) and power spectrum of liquid alkaline earth metals (Ca, Sr, and Ba) have been presented based on the static harmonic well approximation. The effective interatomic potential for liquid metals is computed using our well recognized model potential with the exchange correlation functions due to Hartree, Taylor, Ichimaru and Utsumi, Farid et al. and Sarkar et al. It is observed that the VACF computed using Sarkar et al. gives the good agreement with available molecular dynamics simulation (MD) results [Phys Rev. B 62, 14818 (2000)]. The shoulder of the power spectrum depends upon the type of local field correlation function used.

Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function

USGS Publications Warehouse

Foglia, L.; Hill, Mary C.; Mehl, Steffen W.; Burlando, P.

2009-01-01

We evaluate the utility of three interrelated means of using data to calibrate the fully distributed rainfall‐runoff model TOPKAPI as applied to the Maggia Valley drainage area in Switzerland. The use of error‐based weighting of observation and prior information data, local sensitivity analysis, and single‐objective function nonlinear regression provides quantitative evaluation of sensitivity of the 35 model parameters to the data, identification of data types most important to the calibration, and identification of correlations among parameters that contribute to nonuniqueness. Sensitivity analysis required only 71 model runs, and regression required about 50 model runs. The approach presented appears to be ideal for evaluation of models with long run times or as a preliminary step to more computationally demanding methods. The statistics used include composite scaled sensitivities, parameter correlation coefficients, leverage, Cook's D, and DFBETAS. Tests suggest predictive ability of the calibrated model typical of hydrologic models.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, Hejun

2018-04-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, numerous studies suggested links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their triggering mechanisms, we need an accurate 3D crustal wavespeed model for the study region. Considering the uneven distribution of earthquakes in this area, seismic tomography with local earthquake records have difficulties achieving even illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. Twenty five preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model TO25 correlates well with geological provinces in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front, etc. In addition, there are relatively good correlations between seismic results with gravity and magnetic observations. This new crustal model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location as well as moment tensor solutions, which are important for investigating triggering mechanisms between these induced earthquakes and unconventional oil and gas exploration activities.

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

NASA Astrophysics Data System (ADS)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

Long-Term Functional Outcomes and Correlation with Regional Brain Connectivity by MRI Diffusion Tractography Metrics in a Near-Term Rabbit Model of Intrauterine Growth Restriction

PubMed Central

Illa, Miriam; Eixarch, Elisenda; Batalle, Dafnis; Arbat-Plana, Ariadna; Muñoz-Moreno, Emma; Figueras, Francesc; Gratacos, Eduard

2013-01-01

Background Intrauterine growth restriction (IUGR) affects 5–10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity. Methodology At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers. Principal Findings The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome. Conclusions The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis. PMID:24143189

Long-term functional outcomes and correlation with regional brain connectivity by MRI diffusion tractography metrics in a near-term rabbit model of intrauterine growth restriction.

PubMed

Illa, Miriam; Eixarch, Elisenda; Batalle, Dafnis; Arbat-Plana, Ariadna; Muñoz-Moreno, Emma; Figueras, Francesc; Gratacos, Eduard

2013-01-01

Intrauterine growth restriction (IUGR) affects 5-10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity. At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers. The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome. The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis.

Functional correlates of the therapeutic and adverse effects evoked by thalamic stimulation for essential tremor

PubMed Central

Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki

2016-01-01

Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768

Negative Correlations in Visual Cortical Networks

PubMed Central

Chelaru, Mircea I.; Dragoi, Valentin

2016-01-01

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive. We addressed this issue by performing multiple-electrode recording in the superficial layers of the primary visual cortex (V1) of alert monkey. Despite the fact that positive noise correlations decayed exponentially with the difference in the orientation preference between cells, negative correlations were uniformly distributed across the population. Using a statistical model for Fisher Information estimation, we found that a mild increase in negative correlations causes a sharp increase in network accuracy even when mean correlations were held constant. To examine the variables controlling the strength of negative correlations, we implemented a recurrent spiking network model of V1. We found that increasing local inhibition and reducing excitation causes a decrease in the firing rates of neurons while increasing the negative noise correlations, which in turn increase the population signal-to-noise ratio and network accuracy. Altogether, these results contribute to our understanding of the neuronal mechanism involved in the generation of negative correlations and their beneficial impact on cortical circuit function. PMID:25217468

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

PubMed

Tao, Guohua; Miller, William H

2011-07-14

An efficient time-dependent importance sampling method is developed for the Monte Carlo calculation of time correlation functions via the initial value representation (IVR) of semiclassical (SC) theory. A prefactor-free time-dependent sampling function weights the importance of a trajectory based on the magnitude of its contribution to the time correlation function, and global trial moves are used to facilitate the efficient sampling the phase space of initial conditions. The method can be generally applied to sampling rare events efficiently while avoiding being trapped in a local region of the phase space. Results presented in the paper for two system-bath models demonstrate the efficiency of this new importance sampling method for full SC-IVR calculations.

The calculation of the viscosity from the autocorrelation function using molecular and atomic stress tensors

NASA Astrophysics Data System (ADS)

Cui, S. T.

The stress-stress correlation function and the viscosity of a united-atom model of liquid decane are studied by equilibrium molecular dynamics simulation using two different formalisms for the stress tensor: the atomic and the molecular formalisms. The atomic and molecular correlation functions show dramatic difference in short-time behaviour. The integrals of the two correlation functions, however, become identical after a short transient period whichis significantly shorter than the rotational relaxation time of the molecule. Both reach the same plateau value in a time period corresponding to this relaxation time. These results provide a convenient guide for the choice of the upper integral time limit in calculating the viscosity by the Green-Kubo formula.

Combining symmetry collective states with coupled-cluster theory: Lessons from the Agassi model Hamiltonian

NASA Astrophysics Data System (ADS)

Hermes, Matthew R.; Dukelsky, Jorge; Scuseria, Gustavo E.

2017-06-01

The failures of single-reference coupled-cluster theory for strongly correlated many-body systems is flagged at the mean-field level by the spontaneous breaking of one or more physical symmetries of the Hamiltonian. Restoring the symmetry of the mean-field determinant by projection reveals that coupled-cluster theory fails because it factorizes high-order excitation amplitudes incorrectly. However, symmetry-projected mean-field wave functions do not account sufficiently for dynamic (or weak) correlation. Here we pursue a merger of symmetry projection and coupled-cluster theory, following previous work along these lines that utilized the simple Lipkin model system as a test bed [J. Chem. Phys. 146, 054110 (2017), 10.1063/1.4974989]. We generalize the concept of a symmetry-projected mean-field wave function to the concept of a symmetry projected state, in which the factorization of high-order excitation amplitudes in terms of low-order ones is guided by symmetry projection and is not exponential, and combine them with coupled-cluster theory in order to model the ground state of the Agassi Hamiltonian. This model has two separate channels of correlation and two separate physical symmetries which are broken under strong correlation. We show how the combination of symmetry collective states and coupled-cluster theory is effective in obtaining correlation energies and order parameters of the Agassi model throughout its phase diagram.

Double-scaling limits of random matrices and minimal (2m, 1) models: the merging of two cuts in a degenerate case

NASA Astrophysics Data System (ADS)

Marchal, O.; Cafasso, M.

2011-04-01

In this paper, we show that the double-scaling-limit correlation functions of a random matrix model when two cuts merge with degeneracy 2m (i.e. when y ~ x2m for arbitrary values of the integer m) are the same as the determinantal formulae defined by conformal (2m, 1) models. Our approach follows the one developed by Bergère and Eynard in (2009 arXiv:0909.0854) and uses a Lax pair representation of the conformal (2m, 1) models (giving a Painlevé II integrable hierarchy) as suggested by Bleher and Eynard in (2003 J. Phys. A: Math. Gen. 36 3085). In particular we define Baker-Akhiezer functions associated with the Lax pair in order to construct a kernel which is then used to compute determinantal formulae giving the correlation functions of the double-scaling limit of a matrix model near the merging of two cuts.

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.

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

CorAL is a software Library designed to aid in the analysis of femtoscipic data. Femtoscopic data are a class of measured quantities used in heavy-ion collisions to characterize particle emitting source sizes. The most common type of this data is two-particle correleations induced by the Hanbury-Brown/Twiss (HBT) Effect, but can also include correlations induced by final-state interactions between pairs of emitted particles in a heavy-ion collision. Because heavy-ion collisions are complex many particle systems, modeling hydrodynamical models or hybrid techniques. Using the CRAB module, CorAL can turn the output from these models into something that can be directley compared tomore » experimental data. CorAL can also take the raw experimentally measured correlation functions and image them by inverting the Koonin-Pratt equation to extract the space-time emission profile of the particle emitting source. This source function can be further analyzed or directly compared to theoretical calculations.« less

Modeling electrochemical resistance with coal surface properties in a direct carbon fuel cell based on molten carbonate

NASA Astrophysics Data System (ADS)

Eom, Seongyong; Ahn, Seongyool; Kang, Kijoong; Choi, Gyungmin

2017-12-01

In this study, a numerical model of activation and ohmic polarization is modified, taking into account the correlation function between surface properties and inner resistance. To investigate the correlation function, the surface properties of coal are changed by acid treatment, and the correlations between the inner resistance measured by half-cell tests and the surface characteristics are analyzed. A comparison between the model and experimental results demonstrates that the absolute average deviations for each fuel are less than 10%. The numerical results show that the sensitivities of the coal surface properties affecting polarization losses change depending on the operating temperature. The surface oxygen concentrations affect the activation polarization and the sensitivity decreased with increasing temperature. The surface ash of coal is an additional index to be considered along with ohmic polarization and it has the greatest effect on the surface properties at 973 K.

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

PubMed

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

2011-02-14

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

Genetic and Environmental Basis in Phenotype Correlation Between Physical Function and Cognition in Aging Chinese Twins.

PubMed

Xu, Chunsheng; Zhang, Dongfeng; Tian, Xiaocao; Wu, Yili; Pang, Zengchang; Li, Shuxia; Tan, Qihua

2017-02-01

Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), handgrip strength, five-times-sit-to-stand test (FTSST), near visual acuity, and number of teeth lost in 379 complete twin pairs. Bivariate twin models were fitted to estimate the genetic and environmental correlation between physical and cognitive function. Bivariate analysis showed mildly positively genetic correlations between cognition and FEV1, r G = 0.23 [95% CI: 0.03, 0.62], as well as FVC, r G = 0.35 [95% CI: 0.06, 1.00]. We found that FTSST and cognition presented very high common environmental correlation, r C = -1.00 [95% CI: -1.00, -0.57], and low but significant unique environmental correlation, r E = -0.11 [95% CI: -0.22, -0.01], all in the negative direction. Meanwhile, near visual acuity and cognition also showed unique environmental correlation, r E = 0.16 [95% CI: 0.03, 0.27]. We found no significantly genetic correlation for cognition with handgrip strength, FTSST, near visual acuity, and number of teeth lost. Cognitive function was genetically related to pulmonary function. The FTSST and cognition shared almost the same common environmental factors but only part of the unique environmental factors, both with negative correlation. In contrast, near visual acuity and cognition may positively share part of the unique environmental factors.

Game-Theoretic strategies for systems of components using product-form utilities

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

Rao, Nageswara S; Ma, Cheng-Yu; Hausken, K.

Many critical infrastructures are composed of multiple systems of components which are correlated so that disruptions to one may propagate to others. We consider such infrastructures with correlations characterized in two ways: (i) an aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) a pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. We formulate a game for ensuring the resilience of the infrastructure, wherein the utility functions of the provider and attacker are products of an infrastructuremore » survival probability term and a cost term, both expressed in terms of the numbers of system components attacked and reinforced. The survival probabilities of individual systems satisfy first-order differential conditions that lead to simple Nash Equilibrium conditions. We then derive sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to simplified models of distributed cloud computing and energy grid infrastructures.« less

Heat transfer and flow friction correlations for perforated plate matrix heat exchangers

NASA Astrophysics Data System (ADS)

Ratna Raju, L.; Kumar, S. Sunil; Chowdhury, K.; Nandi, T. K.

2017-02-01

Perforated plate matrix heat exchangers (MHE) are constructed of high conductivity perforated plates stacked alternately with low conductivity spacers. They are being increasingly used in many cryogenic applications including Claude cycle or Reversed Brayton cycle cryo-refrigerators and liquefiers. Design of high NTU (number of (heat) transfer unit) cryogenic MHEs requires accurate heat transfer coefficient and flow friction factor. Thermo-hydraulic behaviour of perforated plates strongly depends on the geometrical parameters. Existing correlations, however, are mostly expressed as functions of Reynolds number only. This causes, for a given configuration, significant variations in coefficients from one correlation to the other. In this paper we present heat transfer and flow friction correlations as functions of all geometrical and other controlling variables. A FluentTM based numerical model has been developed for heat transfer and pressure drop studies over a stack of alternately arranged perforated plates and spacers. The model is validated with the data from literature. Generalized correlations are obtained through regression analysis over a large number of computed data.

Dynamics of a spin-boson model with structured spectral density

NASA Astrophysics Data System (ADS)

Kurt, Arzu; Eryigit, Resul

2018-05-01

We report the results of a study of the dynamics of a two-state system coupled to an environment with peaked spectral density. An exact analytical expression for the bath correlation function is obtained. Validity range of various approximations to the correlation function for calculating the population difference of the system is discussed as function of tunneling splitting, oscillator frequency, coupling constant, damping rate and the temperature of the bath. An exact expression for the population difference, for a limited range of parameters, is derived.

Soft Functionals for Hard Matter

NASA Astrophysics Data System (ADS)

Cooper, Valentino R.; Yuk, Simuck F.; Krogel, Jaron T.

Theory and computation are critical to the materials discovery process. While density functional theory (DFT) has become the standard for predicting materials properties, it is often plagued by inaccuracies in the underlying exchange-correlation functionals. Using high-throughput DFT calculations we explore the accuracy of various exchange-correlation functionals for modeling the structural and thermodynamic properties of a wide range of complex oxides. In particular, we examine the feasibility of using the nonlocal van der Waals density correlation functional with C09 exchange (C09x), which was designed for sparsely packed soft matter, for investigating the properties of hard matter like bulk oxides. Preliminary results show unprecedented performance for some prototypical bulk ferroelectrics, which can be correlated with similarities between C09x and PBEsol. This effort lays the groundwork for understanding how these soft functionals can be employed as general purpose functionals for studying a wide range of materials where strong internal bonds and nonlocal interactions coexist. Research was sponsored by the US DOE, Office of Science, BES, MSED and Early Career Research Programs and used resources at NERSC.

Fulde-Ferrell-Larkin-Ovchinnikov correlation and free fluids in the one-dimensional attractive Hubbard model

NASA Astrophysics Data System (ADS)

Cheng, Song; Yu, Yi-Cong; Batchelor, M. T.; Guan, Xi-Wen

2018-03-01

In this Rapid Communication, we show that low-energy macroscopic properties of the one-dimensional (1D) attractive Hubbard model exhibit two fluids of bound pairs and of unpaired fermions. Using the thermodynamic Bethe ansatz equations of the model, we first determine the low-temperature phase diagram and analytically calculate the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) pairing correlation function for the partially polarized phase. We then show that for such an FFLO-like state in the low-density regime the effective chemical potentials of bound pairs and unpaired fermions behave like two free fluids. Consequently, the susceptibility, compressibility, and specific heat obey simple additivity rules, indicating the "free" particle nature of interacting fermions on a 1D lattice. In contrast to the continuum Fermi gases, the correlation critical exponents and thermodynamics of the attractive Hubbard model essentially depend on two lattice interacting parameters. Finally, we study scaling functions, the Wilson ratio and susceptibility, which provide universal macroscopic properties and dimensionless constants of interacting fermions at low energy.

Effectiveness of back-to-back testing

NASA Technical Reports Server (NTRS)

Vouk, Mladen A.; Mcallister, David F.; Eckhardt, David E.; Caglayan, Alper; Kelly, John P. J.

1987-01-01

Three models of back-to-back testing processes are described. Two models treat the case where there is no intercomponent failure dependence. The third model describes the more realistic case where there is correlation among the failure probabilities of the functionally equivalent components. The theory indicates that back-to-back testing can, under the right conditions, provide a considerable gain in software reliability. The models are used to analyze the data obtained in a fault-tolerant software experiment. It is shown that the expected gain is indeed achieved, and exceeded, provided the intercomponent failure dependence is sufficiently small. However, even with the relatively high correlation the use of several functionally equivalent components coupled with back-to-back testing may provide a considerable reliability gain. Implications of this finding are that the multiversion software development is a feasible and cost effective approach to providing highly reliable software components intended for fault-tolerant software systems, on condition that special attention is directed at early detection and elimination of correlated faults.

Interatomic potentials in condensed matter via the maximum-entropy principle

NASA Astrophysics Data System (ADS)

Carlsson, A. E.

1987-09-01

A general method is described for the calculation of interatomic potentials in condensed-matter systems by use of a maximum-entropy Ansatz for the interatomic correlation functions. The interatomic potentials are given explicitly in terms of statistical correlation functions involving the potential energy and the structure factor of a ``reference medium.'' Illustrations are given for Al-Cu alloys and a model transition metal.

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

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

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

Electromagnetic Compatibility Testing Studies

NASA Technical Reports Server (NTRS)

Trost, Thomas F.; Mitra, Atindra K.

1996-01-01

This report discusses the results on analytical models and measurement and simulation of statistical properties from a study of microwave reverberation (mode-stirred) chambers performed at Texas Tech University. Two analytical models of power transfer vs. frequency in a chamber, one for antenna-to-antenna transfer and the other for antenna to D-dot sensor, were experimentally validated in our chamber. Two examples are presented of the measurement and calculation of chamber Q, one for each of the models. Measurements of EM power density validate a theoretical probability distribution on and away from the chamber walls and also yield a distribution with larger standard deviation at frequencies below the range of validity of the theory. Measurements of EM power density at pairs of points which validate a theoretical spatial correlation function on the chamber walls and also yield a correlation function with larger correlation length, R(sub corr), at frequencies below the range of validity of the theory. A numerical simulation, employing a rectangular cavity with a moving wall shows agreement with the measurements. The determination that the lowest frequency at which the theoretical spatial correlation function is valid in our chamber is considerably higher than the lowest frequency recommended by current guidelines for utilizing reverberation chambers in EMC testing. Two suggestions have been made for future studies related to EMC testing.

Spatial correlation in the ambient core noise field of a turbofan engine.

PubMed

Miles, Jeffrey Hilton

2012-06-01

An acoustic transfer function relating combustion noise and turbine exit noise in the presence of enclosed ambient core noise is investigated using a dynamic system model and an acoustic system model for the particular turbofan engine studied and for a range of operating conditions. Measurements of cross-spectra magnitude and phase between the combustor and turbine exit and auto-spectra at the turbine exit and combustor are used to show the presence of indirect and direct combustion noise over the frequency range of 0-400 Hz. The procedure used evaluates the ratio of direct to indirect combustion noise. The procedure used also evaluates the post-combustion residence time in the combustor which is a factor in the formation of thermal NO(x) and soot in this region. These measurements are masked by the ambient core noise sound field in this frequency range which is observable since the transducers are situated within an acoustic wavelength of one another. An ambient core noise field model based on one and two dimensional spatial correlation functions is used to replicate the spatially correlated response of the pair of transducers. The spatial correlation function increases measured attenuation due to destructive interference and masks the true attenuation of the turbine.

Ab initio DFT+U study of He atom incorporation into UO(2) crystals.

PubMed

Gryaznov, Denis; Heifets, Eugene; Kotomin, Eugene

2009-09-07

We present and discuss results of the density functional theory (DFT) for perfect UO(2) crystals with He atoms in octahedral interstitial positions therein. We have calculated basic bulk crystal properties and He incorporation energies into the low temperature anti-ferromagnetic UO(2) phase using several exchange-correlation functionals within the spin-polarized local density (LDA) and generalized gradient (GGA) approximations. In all DFT calculations we included the on-site correlation corrections using the Hubbard model (DFT+U approach). We analysed a potential crystalline symmetry reduction from tetragonal down to orthorhombic structure and confirmed the presence of the Jahn-Teller effect in a perfect UO(2). We discuss also the problem of a conducting electronic state arising when He is placed into a tetragonal antiferromagnetic phase of UO(2) commonly used in defect modelling. Consequently, we found a specific monoclinic lattice distortion which allowed us to restore the semiconducting state and properly estimate He incorporation energies. Unlike the bulk properties, the He incorporation energy strongly depends on several factors, including the supercell size, the use of spin polarization, the exchange-correlation functionals and on-site correlation corrections. We compare our results for the He incorporation with the previous shell model and ab initio DFT calculations.

Structure of amplitude correlations in open chaotic systems

NASA Astrophysics Data System (ADS)

Ericson, Torleif E. O.

2013-02-01

The Verbaarschot-Weidenmüller-Zirnbauer (VWZ) model is believed to correctly represent the correlations of two S-matrix elements for an open quantum chaotic system, but the solution has considerable complexity and is presently only accessed numerically. Here a procedure is developed to deduce its features over the full range of the parameter space in a transparent and simple analytical form preserving accuracy to a considerable degree. The bulk of the VWZ correlations are described by the Gorin-Seligman expression for the two-amplitude correlations of the Ericson-Gorin-Seligman model. The structure of the remaining correction factors for correlation functions is discussed with special emphasis of the rôle of the level correlation hole both for inelastic and elastic correlations.

Reliability measures in item response theory: manifest versus latent correlation functions.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Verbeke, Geert; De Boeck, Paul

2015-02-01

For item response theory (IRT) models, which belong to the class of generalized linear or non-linear mixed models, reliability at the scale of observed scores (i.e., manifest correlation) is more difficult to calculate than latent correlation based reliability, but usually of greater scientific interest. This is not least because it cannot be calculated explicitly when the logit link is used in conjunction with normal random effects. As such, approximations such as Fisher's information coefficient, Cronbach's α, or the latent correlation are calculated, allegedly because it is easy to do so. Cronbach's α has well-known and serious drawbacks, Fisher's information is not meaningful under certain circumstances, and there is an important but often overlooked difference between latent and manifest correlations. Here, manifest correlation refers to correlation between observed scores, while latent correlation refers to correlation between scores at the latent (e.g., logit or probit) scale. Thus, using one in place of the other can lead to erroneous conclusions. Taylor series based reliability measures, which are based on manifest correlation functions, are derived and a careful comparison of reliability measures based on latent correlations, Fisher's information, and exact reliability is carried out. The latent correlations are virtually always considerably higher than their manifest counterparts, Fisher's information measure shows no coherent behaviour (it is even negative in some cases), while the newly introduced Taylor series based approximations reflect the exact reliability very closely. Comparisons among the various types of correlations, for various IRT models, are made using algebraic expressions, Monte Carlo simulations, and data analysis. Given the light computational burden and the performance of Taylor series based reliability measures, their use is recommended. © 2014 The British Psychological Society.

A cross-correlation-based estimate of the galaxy luminosity function

NASA Astrophysics Data System (ADS)

van Daalen, Marcel P.; White, Martin

2018-06-01

We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased redshift distributions and, for the first time, redshift-dependent luminosity functions, using only clustering information and the apparent magnitudes of the galaxies as input. In contrast to many existing techniques for recovering unbiased redshift distributions, the output of our method is not degenerate with the galaxy bias b(z), which is achieved by modelling the shape of the luminosity bias. We successfully apply our method to a mock galaxy survey and discuss improvements to be made before applying our model to real data.

Statistics of voids in hierarchical universes

NASA Technical Reports Server (NTRS)

Fry, J. N.

1986-01-01

As one alternative to the N-point galaxy correlation function statistics, the distribution of holes or the probability that a volume of given size and shape be empty of galaxies can be considered. The probability of voids resulting from a variety of hierarchical patterns of clustering is considered, and these are compared with the results of numerical simulations and with observations. A scaling relation required by the hierarchical pattern of higher order correlation functions is seen to be obeyed in the simulations, and the numerical results show a clear difference between neutrino models and cold-particle models; voids are more likely in neutrino universes. Observational data do not yet distinguish but are close to being able to distinguish between models.

On two-point boundary correlations in the six-vertex model with domain wall boundary conditions

NASA Astrophysics Data System (ADS)

Colomo, F.; Pronko, A. G.

2005-05-01

The six-vertex model with domain wall boundary conditions on an N × N square lattice is considered. The two-point correlation function describing the probability of having two vertices in a given state at opposite (top and bottom) boundaries of the lattice is calculated. It is shown that this two-point boundary correlator is expressible in a very simple way in terms of the one-point boundary correlators of the model on N × N and (N - 1) × (N - 1) lattices. In alternating sign matrix (ASM) language this result implies that the doubly refined x-enumerations of ASMs are just appropriate combinations of the singly refined ones.

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

PubMed

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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.

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

PubMed Central

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

2014-01-01

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

Correlation singularities in partially coherent electromagnetic beams.

PubMed

Raghunathan, Shreyas B; Schouten, Hugo F; Visser, Taco D

2012-10-15

We demonstrate that coherence vortices, singularities of the correlation function, generally occur in partially coherent electromagnetic beams. In successive cross sections of Gaussian Schell-model beams, their locus is found to be a closed string. These coherence singularities have implications for both interference experiments and correlation of intensity fluctuation measurements performed with such beams.

Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data

PubMed Central

Hu, Jianhua; Wang, Peng; Qu, Annie

2014-01-01

Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433

A generative spike train model with time-structured higher order correlations.

PubMed

Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

2013-01-01

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.

A Method for the Alignment of Heterogeneous Macromolecules from Electron Microscopy

PubMed Central

Shatsky, Maxim; Hall, Richard J.; Brenner, Steven E.; Glaeser, Robert M.

2009-01-01

We propose a feature-based image alignment method for single-particle electron microscopy that is able to accommodate various similarity scoring functions while efficiently sampling the two-dimensional transformational space. We use this image alignment method to evaluate the performance of a scoring function that is based on the Mutual Information (MI) of two images rather than one that is based on the cross-correlation function. We show that alignment using MI for the scoring function has far less model-dependent bias than is found with cross-correlation based alignment. We also demonstrate that MI improves the alignment of some types of heterogeneous data, provided that the signal to noise ratio is relatively high. These results indicate, therefore, that use of MI as the scoring function is well suited for the alignment of class-averages computed from single particle images. Our method is tested on data from three model structures and one real dataset. PMID:19166941

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

PubMed

Melnik, S S; Usatenko, O V

2017-07-01

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

Decomposition of conditional probability for high-order symbolic Markov chains

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Correlation functions of net-proton multiplicity distributions in Au + Au collisions at energies available at the BNL Relativistic Heavy Ion Collider from a multiphase transport model

NASA Astrophysics Data System (ADS)

Lin, Yufu; Chen, Lizhu; Li, Zhiming

2017-10-01

Fluctuations of conserved quantities are believed to be sensitive observables to probe the signature of the QCD phase transition and critical point. It was argued recently that measuring the genuine correlation functions (CFs) could provide cleaner information on possible nontrivial dynamics in heavy-ion collisions. With the AMPT (a multiphase transport) model, the centrality and energy dependence of various orders of CFs of net protons in Au + Au collisions at √{sN N}=7.7 , 11.5, 19.6, 27, 39, 62.4, and 200 GeV are investigated. The model results show that the number of antiprotons is important and should be taken into account in the calculation of CFs at high energy and/or in peripheral collisions. It is also found that the contribution of antiprotons is more important for higher order correlations than for lower ones. The CFs of antiprotons and mixed correlations play roles comparable to those of protons at high energies. Finally, we make comparisons between the model calculation and experimental data measured in the STAR experiment at the BNL Relativistic Heavy Ion Collider.

Higher-Order Squeezing in a Boson Coupled Two-Mode System

NASA Technical Reports Server (NTRS)

Chizhov, A. V.; Haus, J. W.; Yeong, K. C.

1996-01-01

We consider a model for nondegenerate cavity fields interacting through an intervening Boson field. The quantum correlations introduced in this manner are manifest through their higher-order correlation functions where a type of squeezed state is identified.

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

PubMed Central

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

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

Universal spatial correlation functions for describing and reconstructing soil microstructure.

PubMed

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

2015-01-01

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

Are the Correlates of Children's Internal Working Models of Attachment Gender Specific?

ERIC Educational Resources Information Center

Broberg, Anders G.; Wiberg, Charlotta; Gyland, Patrik; Ramsby, Louise; Bohlin, Gunilla; Rydell, Ann-Margret

Noting that gender may be an important issue when studying relations between attachment and social functioning, four studies explored whether the relationship between children's internal working models of attachment and their general functioning was gender specific. A total of 246 children, ages 5 to 10 years, were given the Separation Anxiety…

Exploring the critical quality attributes and models of smart homes.

PubMed

Ted Luor, Tainyi; Lu, Hsi-Peng; Yu, Hueiju; Lu, Yinshiu

2015-12-01

Research on smart homes has significantly increased in recent years owing to their considerably improved affordability and simplicity. However, the challenge is that people have different needs (or attitudes toward smart homes), and provision should be tailored to individuals. A few studies have classified the functions of smart homes. Therefore, the Kano model is first adopted as a theoretical base to explore whether the functional classifications of smart homes are attractive or necessary, or both. Second, three models and test user attitudes toward three function types of smart homes are proposed. Based on the Kano model, the principal results, namely, two "Attractive Quality" and nine "Indifferent Quality" items, are found. Verification of the hypotheses also indicates that the entertainment, security, and automation functions are significantly correlated with the variables "perceive useful" and "attitude." Cost consideration is negatively correlated with attitudes toward entertainment and automation. Results suggest that smart home providers should survey user needs for their product instead of merely producing smart homes based on the design of the builder or engineer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Magnetic helicity generation in the frame of Kazantsev model

NASA Astrophysics Data System (ADS)

Yushkov, Egor V.; Lukin, Alexander S.

2017-11-01

Using a magnetic dynamo model, suggested by Kazantsev (J. Exp. Theor. Phys. 1968, vol. 26, p. 1031), we study the small-scale helicity generation in a turbulent electrically conducting fluid. We obtain the asymptotic dependencies of dynamo growth rate and magnetic correlation functions on magnetic Reynolds numbers. Special attention is devoted to the comparison of a longitudinal correlation function and a function of magnetic helicity for various conditions of asymmetric turbulent flows. We compare the analytical solutions on small scales with numerical results, calculated by an iterative algorithm on non-uniform grids. We show that the exponential growth of current helicity is simultaneous with the magnetic energy for Reynolds numbers larger than some critical value and estimate this value for various types of asymmetry.

Symptom clusters in patients with high-grade glioma.

PubMed

Fox, Sherry W; Lyon, Debra; Farace, Elana

2007-01-01

To describe the co-occurring symptoms (depression, fatigue, pain, sleep disturbance, and cognitive impairment), quality of life (QoL), and functional status in patients with high-grade glioma. Correlational, descriptive study of 73 participants with high-grade glioma in the U.S. Nine brief measures were obtained with a mailed survey. Participants were recruited from the online message board of The Healing Exchange BRAIN TRUST, a nonprofit organization dedicated to improving quality of life for people with brain tumors. Two symptom cluster models were examined. Four co-occurring symptoms were significantly correlated with each other and explained 29% of the variance in QoL: depression, fatigue, sleep disturbance, and cognitive impairment. Depression, fatigue, sleep disturbance, cognitive impairment, and pain were significantly correlated with each other and explained 62% of the variance in functional status. The interrelationships of the symptoms examined in this study and their relationships with QoL and functional status meet the criteria for defining a symptom cluster. The differences in the models of QoL and functional status indicates that symptom clusters may have unique characteristics in patients with gliomas.

Topological electronic liquids: Electronic physics of one dimension beyond the one spatial dimension

NASA Astrophysics Data System (ADS)

Wiegmann, P. B.

1999-06-01

There is a class of electronic liquids in dimensions greater than 1 that shows all essential properties of one-dimensional electronic physics. These are topological liquids-correlated electronic systems with a spectral flow. Compressible topological electronic liquids are superfluids. In this paper we present a study of a conventional model of a topological superfluid in two spatial dimensions. This model is thought to be relevant to a doped Mott insulator. We show how the spectral flow leads to the superfluid hydrodynamics and how the orthogonality catastrophe affects off-diagonal matrix elements. We also compute the major electronic correlation functions. Among them are the spectral function, the pair wave function, and various tunneling amplitudes. To compute correlation functions we develop a method of current algebra-an extension of the bosonization technique of one spatial dimension. In order to emphasize a similarity between electronic liquids in one dimension and topological liquids in dimensions greater than 1, we first review the Fröhlich-Peierls mechanism of ideal conductivity in one dimension and then extend the physics and the methods into two spatial dimensions.

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)).

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Binder model system to be used for determination of prepolymer functionality

NASA Technical Reports Server (NTRS)

Martinelli, F. J.; Hodgkin, J. H.

1971-01-01

Development of a method for determining the functionality distribution of prepolymers used for rocket binders is discussed. Research has been concerned with accurately determining the gel point of a model polyester system containing a single trifunctional crosslinker, and the application of these methods to more complicated model systems containing a second trifunctional crosslinker, monofunctional ingredients, or a higher functionality crosslinker. Correlations of observed with theoretical gel points for these systems would allow the methods to be applied directly to prepolymers.

Studying flow close to an interface by total internal reflection fluorescence cross-correlation spectroscopy: Quantitative data analysis

NASA Astrophysics Data System (ADS)

Schmitz, R.; Yordanov, S.; Butt, H. J.; Koynov, K.; Dünweg, B.

2011-12-01

Total internal reflection fluorescence cross-correlation spectroscopy (TIR-FCCS) has recently [S. Yordanov , Optics ExpressOPEXFF1094-408710.1364/OE.17.021149 17, 21149 (2009)] been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence occurs only for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions provide only rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. First, Brownian dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Second, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.

Large-N and Bethe Ansatz

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

We describe an integrable model, related to the Gaudin magnet, and its relation to the matrix model of Brézin, Itzykson, Parisi and Zuber. Relation is based on Bethe ansatz for the integrable model and its interpretation using orthogonal polynomials and saddle point approximation. Large-N limit of the matrix model corresponds to the thermodynamic limit of the integrable system. In this limit (functional) Bethe ansatz is the same as the generating function for correlators of the matrix models.

Density matrix embedding in an antisymmetrized geminal power bath

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

Tsuchimochi, Takashi; Welborn, Matthew; Van Voorhis, Troy, E-mail: tvan@mit.edu

2015-07-14

Density matrix embedding theory (DMET) has emerged as a powerful tool for performing wave function-in-wave function embedding for strongly correlated systems. In traditional DMET, an accurate calculation is performed on a small impurity embedded in a mean field bath. Here, we extend the original DMET equations to account for correlation in the bath via an antisymmetrized geminal power (AGP) wave function. The resulting formalism has a number of advantages. First, it allows one to properly treat the weak correlation limit of independent pairs, which DMET is unable to do with a mean-field bath. Second, it associates a size extensive correlationmore » energy with a given density matrix (for the models tested), which AGP by itself is incapable of providing. Third, it provides a reasonable description of charge redistribution in strongly correlated but non-periodic systems. Thus, AGP-DMET appears to be a good starting point for describing electron correlation in molecules, which are aperiodic and possess both strong and weak electron correlation.« less

Tracer kinetics of forearm endothelial function: comparison of an empirical method and a quantitative modeling technique.

PubMed

Zhao, Xueli; Arsenault, Andre; Lavoie, Kim L; Meloche, Bernard; Bacon, Simon L

2007-01-01

Forearm Endothelial Function (FEF) is a marker that has been shown to discriminate patients with cardiovascular disease (CVD). FEF has been assessed using several parameters: the Rate of Uptake Ratio (RUR), EWUR (Elbow-to-Wrist Uptake Ratio) and EWRUR (Elbow-to-Wrist Relative Uptake Ratio). However, the modeling functions of FEF require more robust models. The present study was designed to compare an empirical method with quantitative modeling techniques to better estimate the physiological parameters and understand the complex dynamic processes. The fitted time activity curves of the forearms, estimating blood and muscle components, were assessed using both an empirical method and a two-compartment model. Although correlational analyses suggested a good correlation between the methods for RUR (r=.90) and EWUR (r=.79), but not EWRUR (r=.34), Altman-Bland plots found poor agreement between the methods for all 3 parameters. These results indicate that there is a large discrepancy between the empirical and computational method for FEF. Further work is needed to establish the physiological and mathematical validity of the 2 modeling methods.

Toward ab initio molecular dynamics modeling for sum-frequency generation spectra; an efficient algorithm based on surface-specific velocity-velocity correlation function.

PubMed

Ohto, Tatsuhiko; Usui, Kota; Hasegawa, Taisuke; Bonn, Mischa; Nagata, Yuki

2015-09-28

Interfacial water structures have been studied intensively by probing the O-H stretch mode of water molecules using sum-frequency generation (SFG) spectroscopy. This surface-specific technique is finding increasingly widespread use, and accordingly, computational approaches to calculate SFG spectra using molecular dynamics (MD) trajectories of interfacial water molecules have been developed and employed to correlate specific spectral signatures with distinct interfacial water structures. Such simulations typically require relatively long (several nanoseconds) MD trajectories to allow reliable calculation of the SFG response functions through the dipole moment-polarizability time correlation function. These long trajectories limit the use of computationally expensive MD techniques such as ab initio MD and centroid MD simulations. Here, we present an efficient algorithm determining the SFG response from the surface-specific velocity-velocity correlation function (ssVVCF). This ssVVCF formalism allows us to calculate SFG spectra using a MD trajectory of only ∼100 ps, resulting in the substantial reduction of the computational costs, by almost an order of magnitude. We demonstrate that the O-H stretch SFG spectra at the water-air interface calculated by using the ssVVCF formalism well reproduce those calculated by using the dipole moment-polarizability time correlation function. Furthermore, we applied this ssVVCF technique for computing the SFG spectra from the ab initio MD trajectories with various density functionals. We report that the SFG responses computed from both ab initio MD simulations and MD simulations with an ab initio based force field model do not show a positive feature in its imaginary component at 3100 cm(-1).

Sparse dictionary learning of resting state fMRI networks.

PubMed

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

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

PubMed

Straka, Michal; Lantto, Perttu; Vaara, Juha

2008-03-27

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

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.

Multiscale Models of Melting Arctic Sea Ice

DTIC Science & Technology

2014-09-30

from weakly to highly correlated, or Poissonian toward Wigner -Dyson, as a function of system connectedness. This provides a mechanism for explaining...eluded us. Court Strong found such a method. It creates an optimal fit of a hyperbolic tangent model for the fractal dimension as a function of log A...actual melt pond images, and have made significant advances in the underlying functional and numerical analysis needed for these computations

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease.

PubMed

Lin, Qi; Rosenberg, Monica D; Yoo, Kwangsun; Hsu, Tiffany W; O'Connell, Thomas P; Chun, Marvin M

2018-01-01

Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV) significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Spatial correlations and exact solution of the problem of the boson peak profile in amorphous media

NASA Astrophysics Data System (ADS)

Kirillov, Sviatoslav A.; A. Voyiatzis, George; Kolomiyets, Tatiana M.; H. Anastasiadis, Spiros

1999-11-01

Based on a model correlation function which covers spatial correlations from Gaussian to exponential, we have arrived at an exact analytic solution of the problem of the Boson peak profile in amorphous media. Probe fits made for polyisoprene and triacetin prove the working ability of the formulae obtained.

On the origins of the ‘global signal’ determined by functional magnetic resonance imaging in the resting state

NASA Astrophysics Data System (ADS)

Bennett, Maxwell R.; Farnell, Les; Gibson, William; Lagopoulos, Jim

2016-02-01

Objective. Functional magnetic resonance imaging blood oxygen level dependent (BOLD) determinations of correlations between ‘resting-state’ neuronal activity in different regions of cortex have generated much interest. Determination of these correlations requires regressing out signals that are correlated in all parts of the cortex and are taken to be artefactual, such as those due to movement, respiration and cardiovascular activity. However when these are removed there still remains a ‘global signal’ (GS), which is taken to be of unknown physiological origin, and is regressed out by some researchers but not by others. Approach. We have investigated the origin of this GS using cortical models consisting of coupled networks of modules representing regions of interest. Main results. We show that the GS has an amplitude that is linearly related to the average correlation between the modules/voxels in the network over a large range of such correlations. The GS arises as a consequence of feedback between the modules/voxels leading to correlations in their BOLD signals. Given the relationship between the GS and the average correlations it might be anticipated that regressing out the GS during preprocessing will significantly modify the correlations subsequently determined. This is shown to be the case when comparing the connections of individual modules with that predicted by the correlations. Significance. The present model shows that such correlations can arise as a consequence of the intermodular feedback connectivity without recourse to imposing a GS independent of the connectivity. Our model indicates that the GS reflects the extent of feedback pathways provided by the intermodular/inter-regional connections and hence the average correlation between modules or regions of cortex. However the model has not been used to elucidate the possible contributions of a GS independent of the connectivity, which might indeed contribute to the GS of the cortex.

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

PubMed

Janecek, Jirí; Netz, Roland R

2009-02-21

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

A new class of ensemble conserving algorithms for approximate quantum dynamics: Theoretical formulation and model problems.

PubMed

Smith, Kyle K G; Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J

2015-06-28

We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.

Evaluation of methods to produce an image library for automatic patient model localization for dose mapping during fluoroscopically guided procedures

NASA Astrophysics Data System (ADS)

Kilian-Meneghin, Josh; Xiong, Z.; Rudin, S.; Oines, A.; Bednarek, D. R.

2017-03-01

The purpose of this work is to evaluate methods for producing a library of 2D-radiographic images to be correlated to clinical images obtained during a fluoroscopically-guided procedure for automated patient-model localization. The localization algorithm will be used to improve the accuracy of the skin-dose map superimposed on the 3D patient- model of the real-time Dose-Tracking-System (DTS). For the library, 2D images were generated from CT datasets of the SK-150 anthropomorphic phantom using two methods: Schmid's 3D-visualization tool and Plastimatch's digitally-reconstructed-radiograph (DRR) code. Those images, as well as a standard 2D-radiographic image, were correlated to a 2D-fluoroscopic image of a phantom, which represented the clinical-fluoroscopic image, using the Corr2 function in Matlab. The Corr2 function takes two images and outputs the relative correlation between them, which is fed into the localization algorithm. Higher correlation means better alignment of the 3D patient-model with the patient image. In this instance, it was determined that the localization algorithm will succeed when Corr2 returns a correlation of at least 50%. The 3D-visualization tool images returned 55-80% correlation relative to the fluoroscopic-image, which was comparable to the correlation for the radiograph. The DRR images returned 61-90% correlation, again comparable to the radiograph. Both methods prove to be sufficient for the localization algorithm and can be produced quickly; however, the DRR method produces more accurate grey-levels. Using the DRR code, a library at varying angles can be produced for the localization algorithm.

Thresholding functional connectomes by means of mixture modeling.

PubMed

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

2018-05-01

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

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

Influence of model errors in optimal sensor placement

NASA Astrophysics Data System (ADS)

Vincenzi, Loris; Simonini, Laura

2017-02-01

The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

PubMed

Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A

2017-10-01

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ 2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

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

PubMed

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

2017-04-01

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

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.

Redshift-space distortions of group and galaxy correlations in the Updated Zwicky Catalog

NASA Astrophysics Data System (ADS)

Padilla, N. D.; Merchán, M.; García Lambas, D.; Maia, M. G.

We calculate two-point correlation functions of galaxies and groups of galaxies selected in three dimensions from the Updated Zwicky Galaxy Catalog - (UZC). The redshift space distortion of the correlation function ξ(σ,π) in the directions parallel and perpendicular to the line of sight, induced by pairwise group peculiar velocities is evaluated. Two methods are used to characterize the pairwise velocity field. The first method consists in fitting the observed ξ(σ,π) with a distorted model with an exponential pairwise velocity distribution, in fixed σ bins. The second method compares the contours of constant predicted correlation function of this model with the data. The results are consistent with a one-dimensional pairwise rms velocity dispersion of groups 1/2=250 ± 110 km/s. We find that UZC galaxy pairwise velocity dispersion is 1/2 = 460 ± 35 km/s. Such findings point towards a smoothly varying peculiar velocity field from galaxies to systems of galaxies, a expected in a hierarchical scenario of structure formation. We estimate the real-space correlation function in the power-law approximation ξ(r)=(r/r0)γ for groups and galaxies in UZC. We obtain the correlation length, r0, from the projected correlation function W(σ)=∫- ∞∞ξ(σ,π)dπ= 2 ∫0∞ ξ(σ,π) dπ using the values of γ derived from the correlation function in projected separations ω(σ). The best fitting parameters are γ=-1.89 ± 0.17 and r0=9.7 ± 4.5 Mpc h-1 for groups, and γ=-2.00 ± 0.03, r0=5.29 ± 0.21 Mpc h-1 for galaxies. We carried out an estimate of the parameter β= Ω0.6/b for groups and galaxies using the linear approximation regime relating the real and the redshift-space correlation functions. We find βgalaxies=0.51 ± 0.15 for galaxies, in agreement with previous works, while for groups we obtain a noisy estimate β < 1.5. We have tested our methods on mock UZC catalogs taken from N-body simulations. The results of these tests show that the conclusions derived from the application of our methods to the observations are reliable and provide a suitable characterization of the spatial correlation and pairwise velocities of groups and galaxies. We also find that the second method, developed in this work, provides more stable and precise results.

Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models

NASA Astrophysics Data System (ADS)

Yuan, Sihan; Eisenstein, Daniel J.; Garrison, Lehman H.

2018-04-01

We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND-HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescriptions that are nearly degenerate in the projected 2PCF and demonstrate that these degeneracies are broken in the redshift-space anisotropic 2PCF and the squeezed 3PCF. We also discuss the possibility of identifying degeneracies in the anisotropic 2PCF and further demonstrate the extra constraining power of the squeezed 3PCF on galaxy-halo connection models. We find that within our current HOD framework, the anisotropic 2PCF can predict the squeezed 3PCF better than its statistical error. This implies that a discordant squeezed 3PCF measurement could falsify the particular HOD model space. Alternatively, it is possible that further generalizations of the HOD model would open opportunities for the squeezed 3PCF to provide novel parameter measurements. The GRAND-HOD Python package is publicly available at https://github.com/SandyYuan/GRAND-HOD.

An approach for generating trajectory-based dynamics which conserves the canonical distribution in the phase space formulation of quantum mechanics. II. Thermal correlation functions.

PubMed

Liu, Jian; Miller, William H

2011-03-14

We show the exact expression of the quantum mechanical time correlation function in the phase space formulation of quantum mechanics. The trajectory-based dynamics that conserves the quantum canonical distribution-equilibrium Liouville dynamics (ELD) proposed in Paper I is then used to approximately evaluate the exact expression. It gives exact thermal correlation functions (of even nonlinear operators, i.e., nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits. Various methods have been presented for the implementation of ELD. Numerical tests of the ELD approach in the Wigner or Husimi phase space have been made for a harmonic oscillator and two strongly anharmonic model problems, for each potential autocorrelation functions of both linear and nonlinear operators have been calculated. It suggests ELD can be a potentially useful approach for describing quantum effects for complex systems in condense phase.

Assessing the role of Hartree-Fock exchange, correlation energy and long range corrections in evaluating ionization potential, and electron affinity in density functional theory.

PubMed

Vikramaditya, Talapunur; Lin, Shiang-Tai

2017-06-05

Accurate determination of ionization potentials (IPs), electron affinities (EAs), fundamental gaps (FGs), and HOMO, LUMO energy levels of organic molecules play an important role in modeling and predicting the efficiencies of organic photovoltaics, OLEDs etc. In this work, we investigate the effects of Hartree Fock (HF) Exchange, correlation energy, and long range corrections in predicting IP and EA in Hybrid Functionals. We observe increase in percentage of HF exchange results in increase of IPs and decrease in EAs. Contrary to the general expectations inclusion of both HF exchange and correlation energy (from the second order perturbation theory MP2) leads to poor prediction. Range separated Hybrid Functionals are found to be more reliable among various DFT Functionals investigated. DFT Functionals predict accurate IPs whereas post HF methods predict accurate EAs. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Using Utility Functions to Control a Distributed Storage System

DTIC Science & Technology

2008-05-01

Pinheiro et al. [2007] suggest this is not an accurate assumption. Nicola and Goyal [1990] examined correlated failures across multiversion software...F. and Goyal, A. (1990). Modeling of correlated failures and community error recovery in multiversion software. IEEE Transactions on Software

Theory of correlation in a network with synaptic depression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato

2012-01-01

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

Molecular Modeling of Heme Proteins Using MOE: Bio-Inorganic and Structure-Function Activity for Undergraduates

ERIC Educational Resources Information Center

Ray, Gigi B.; Cook, J. Whitney

2005-01-01

A biochemical molecular modeling project on heme proteins suitable for an introductory Biochemistry I class has been designed with a 2-fold objective: i) to reinforce the correlation between protein three-dimensional structure and function through a discovery oriented project, and ii) to introduce students to the fields of bioinorganic and…

Percolation analysis for cosmic web with discrete points

NASA Astrophysics Data System (ADS)

Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung

2016-03-01

Percolation analysis has long been used to quantify the connectivity of the cosmic web. Unlike most of the previous works using density field on grids, we have studied percolation analysis based on discrete points. Using a Friends-of-Friends (FoF) algorithm, we generate the S-bb relation, between the fractional mass of the largest connected group (S) and the FoF linking length (bb). We propose a new model, the Probability Cloud Cluster Expansion Theory (PCCET) to relate the S-bb relation with correlation functions. We show that the S-bb relation reflects a combination of all orders of correlation functions. We have studied the S-bb relation with simulation and find that the S-bb relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with Halo Abundance Matching (HAM), we have generated a mock galaxy catalogue. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalogue with the latest galaxy catalogue from SDSS DR12, we have found significant differences in their S-bb relations. This indicates that the mock catalogue cannot accurately recover higher order correlation functions than the two-point correlation function, which reveals the limit of HAM method.

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

NASA Astrophysics Data System (ADS)

Ziń, Paweł; Wasak, Tomasz

2018-04-01

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

The significance of the choice of radiobiological (NTCP) models in treatment plan objective functions.

PubMed

Miller, J; Fuller, M; Vinod, S; Suchowerska, N; Holloway, L

2009-06-01

A Clinician's discrimination between radiation therapy treatment plans is traditionally a subjective process, based on experience and existing protocols. A more objective and quantitative approach to distinguish between treatment plans is to use radiobiological or dosimetric objective functions, based on radiobiological or dosimetric models. The efficacy of models is not well understood, nor is the correlation of the rank of plans resulting from the use of models compared to the traditional subjective approach. One such radiobiological model is the Normal Tissue Complication Probability (NTCP). Dosimetric models or indicators are more accepted in clinical practice. In this study, three radiobiological models, Lyman NTCP, critical volume NTCP and relative seriality NTCP, and three dosimetric models, Mean Lung Dose (MLD) and the Lung volumes irradiated at 10Gy (V10) and 20Gy (V20), were used to rank a series of treatment plans using, harm to normal (Lung) tissue as the objective criterion. None of the models considered in this study showed consistent correlation with the Radiation Oncologists plan ranking. If radiobiological or dosimetric models are to be used in objective functions for lung treatments, based on this study it is recommended that the Lyman NTCP model be used because it will provide most consistency with traditional clinician ranking.

Depression and resilience mediates the effect of family function on quality of life of the elderly.

PubMed

Lu, Canjie; Yuan, Lexin; Lin, Weiquan; Zhou, Ying; Pan, Shengmao

2017-07-01

Family function, which improves individual resilience and strongly link to quality of life (QOL) among the elderly, increases the risk of depression. Because of these demonstrated relationships, it can be hypothesized that both depression and resilience are mediators of the association between family function and QOL. To test this hypothesis, the structural equation model (SEM) constructed by Amos 21.0 was employed to assess the indirect effect of depression (Geriatric Depression Scale, GDS) and resilience (Connor-Davidson Resilience Scale, CD-RISC) on the relationship between family function (Family APGAR Score, APGAR) and QOL (12-item Short Form health survey, SF-12) in 474 elderly adults from three communities in Guangzhou, China. Correlation matrix showed that depression is significantly negatively correlated with family functioning (r=-0.54, P<0.01), resilience (r=-0.46, P<0.01) and QOL (r=-0.63, P<0.01), while resilience is significantly positively correlated with family functioning (r=0.35, P<0.01) and QOL (r=0.40, P<0.01). SEM indicated that Family functioning appeared to have significant indirect effects through resilience (β=0.089) and depression (β=0.307; combined β=0.056) on QOL (R 2 =0.55). The model fit indices showed a good fit of the model of the data (χ 2 /df=1.362, P>0.05, SRMR=0.023, RMSEA=0.028, GFI=0.985, NFI=0.987, TLI=0.993, CFI=0.996). The finding supports the assumption that depression and resilience are consistent intermediary factors of the relationship between family function and QOL among the elderly. Copyright © 2017 Elsevier B.V. All rights reserved.

Quenched dynamics and spin-charge separation in an interacting topological lattice

NASA Astrophysics Data System (ADS)

Barbiero, L.; Santos, L.; Goldman, N.

2018-05-01

We analyze the static and dynamical properties of a one-dimensional topological lattice, the fermionic Su-Schrieffer-Heeger model, in the presence of on-site interactions. Based on a study of charge and spin correlation functions, we elucidate the nature of the topological edge modes, which, depending on the sign of the interactions, either display particles of opposite spin on opposite edges, or a pair and a holon. This study of correlation functions also highlights the strong entanglement that exists between the opposite edges of the system. This last feature has remarkable consequences upon subjecting the system to a quench, where an instantaneous edge-to-edge signal appears in the correlation functions characterizing the edge modes. Besides, other correlation functions are shown to propagate in the bulk according to the light cone imposed by the Lieb-Robinson bound. Our study reveals how one-dimensional lattices exhibiting entangled topological edge modes allow for a nontrivial correlation spreading, while providing an accessible platform to detect spin-charge separation using state-of-the-art experimental techniques.

A second-order closure analysis of turbulent diffusion flames. [combustion physics

NASA Technical Reports Server (NTRS)

Varma, A. K.; Fishburne, E. S.; Beddini, R. A.

1977-01-01

A complete second-order closure computer program for the investigation of compressible, turbulent, reacting shear layers was developed. The equations for the means and the second order correlations were derived from the time-averaged Navier-Stokes equations and contain third order and higher order correlations, which have to be modeled in terms of the lower-order correlations to close the system of equations. In addition to fluid mechanical turbulence models and parameters used in previous studies of a variety of incompressible and compressible shear flows, a number of additional scalar correlations were modeled for chemically reacting flows, and a typical eddy model developed for the joint probability density function for all the scalars. The program which is capable of handling multi-species, multistep chemical reactions, was used to calculate nonreacting and reacting flows in a hydrogen-air diffusion flame.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

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

Lu, Fengbin, E-mail: fblu@amss.ac.cn

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relationsmore » evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.« less

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

PubMed

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Theory of nonstationary Hawkes processes

NASA Astrophysics Data System (ADS)

Tannenbaum, Neta Ravid; Burak, Yoram

2017-12-01

We expand the theory of Hawkes processes to the nonstationary case, in which the mutually exciting point processes receive time-dependent inputs. We derive an analytical expression for the time-dependent correlations, which can be applied to networks with arbitrary connectivity, and inputs with arbitrary statistics. The expression shows how the network correlations are determined by the interplay between the network topology, the transfer functions relating units within the network, and the pattern and statistics of the external inputs. We illustrate the correlation structure using several examples in which neural network dynamics are modeled as a Hawkes process. In particular, we focus on the interplay between internally and externally generated oscillations and their signatures in the spike and rate correlation functions.

Low Temperature Analysis of Correlation Functions of the Blume-Emery-Griffiths Model at the Antiquadrupolar-Disordered Interface

NASA Astrophysics Data System (ADS)

Lima, Paulo C.

2016-11-01

We show that at low temperatures the d dimensional Blume-Emery-Griffiths model in the antiquadrupolar-disordered interface has all its infinite volume correlation functions < prod _{iin A}σ _i^{n_i}rangle _{τ }, where Asubset Z^d is finite and sum _{iin A}n_i is odd, equal zero, regardless of the boundary condition τ . In particular, the magnetization < σ _irangle _{τ } is zero, for all τ . We also show that the infinite volume mean magnetization lim _{Λ → ∞}Big < 1/|Λ |sum _{iin Λ }σ _iBig rangle _{Λ ,τ } is zero, for all τ.

Correlation and nonlocality measures as indicators of quantum phase transitions in several critical systems

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

Altintas, Ferdi, E-mail: ferdialtintas@ibu.edu.tr; Eryigit, Resul, E-mail: resul@ibu.edu.tr

2012-12-15

We have investigated the quantum phase transitions in the ground states of several critical systems, including transverse field Ising and XY models as well as XY with multiple spin interactions, XXZ and the collective system Lipkin-Meshkov-Glick models, by using different quantumness measures, such as entanglement of formation, quantum discord, as well as its classical counterpart, measurement-induced disturbance and the Clauser-Horne-Shimony-Holt-Bell function. Measurement-induced disturbance is found to detect the first and second order phase transitions present in these critical systems, while, surprisingly, it is found to fail to signal the infinite-order phase transition present in the XXZ model. Remarkably, the Clauser-Horne-Shimony-Holt-Bellmore » function is found to detect all the phase transitions, even when quantum and classical correlations are zero for the relevant ground state. - Highlights: Black-Right-Pointing-Pointer The ability of correlation measures to detect quantum phase transitions has been studied. Black-Right-Pointing-Pointer Measurement induced disturbance fails to detect the infinite order phase transition. Black-Right-Pointing-Pointer CHSH-Bell function detects all phase transitions even when the bipartite density matrix is uncorrelated.« less

Response properties in the adsorption-desorption model on a triangular lattice

NASA Astrophysics Data System (ADS)

Šćepanović, J. R.; Stojiljković, D.; Jakšić, Z. M.; Budinski-Petković, Lj.; Vrhovac, S. B.

2016-06-01

The out-of-equilibrium dynamical processes during the reversible random sequential adsorption (RSA) of objects of various shapes on a two-dimensional triangular lattice are studied numerically by means of Monte Carlo simulations. We focused on the influence of the order of symmetry axis of the shape on the response of the reversible RSA model to sudden perturbations of the desorption probability Pd. We provide a detailed discussion of the significance of collective events for governing the time coverage behavior of shapes with different rotational symmetries. We calculate the two-time density-density correlation function C(t ,tw) for various waiting times tw and show that longer memory of the initial state persists for the more symmetrical shapes. Our model displays nonequilibrium dynamical effects such as aging. We find that the correlation function C(t ,tw) for all objects scales as a function of single variable ln(tw) / ln(t) . We also study the short-term memory effects in two-component mixtures of extended objects and give a detailed analysis of the contribution to the densification kinetics coming from each mixture component. We observe the weakening of correlation features for the deposition processes in multicomponent systems.

Effects of cross-correlated noises on the relaxation time of the bistable system

NASA Astrophysics Data System (ADS)

Xie, Chong-Wei; Mei, Dong-Cheng

2003-11-01

The stationary correlation function and the associated relaxation time for a general system driven by cross-correlated white noises are derived, by virtue of a Stratonovich-like ansatz. The effects of correlated noises on the relaxation time of a bistable kinetic model coupled to an additive and a multiplicative white noises are studied. It is proved that for small fluctuations the relaxation time Tc as a function of lambda (the correlated intensity between noises) exhibits very different behaviours for alphaD (alpha and D, respectively, stand for the intensities of additive and multiplicative noises). When alpha>D, Tc increases with increasing lambda. But when alpha

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

NASA Astrophysics Data System (ADS)

Hsieh, Chang-Yu; Cao, Jianshu

2018-01-01

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

Modeling Ability Differentiation in the Second-Order Factor Model

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

2011-01-01

In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

Extended screened exchange functional derived from transcorrelated density functional theory.

PubMed

Umezawa, Naoto

2017-09-14

We propose a new formulation of the correlation energy functional derived from the transcorrelated method in use in density functional theory (TC-DFT). An effective Hamiltonian, H TC , is introduced by a similarity transformation of a many-body Hamiltonian, H, with respect to a complex function F: H TC =1FHF. It is proved that an expectation value of H TC for a normalized single Slater determinant, D n , corresponds to the total energy: E[n] = ⟨Ψ n |H|Ψ n ⟩/⟨Ψ n |Ψ n ⟩ = ⟨D n |H TC |D n ⟩ under the two assumptions: (1) The electron density nr associated with a trial wave function Ψ n = D n F is v-representable and (2) Ψ n and D n give rise to the same electron density nr. This formulation, therefore, provides an alternative expression of the total energy that is useful for the development of novel correlation energy functionals. By substituting a specific function for F, we successfully derived a model correlation energy functional, which resembles the functional form of the screened exchange method. The proposed functional, named the extended screened exchange (ESX) functional, is described within two-body integrals and is parametrized for a numerically exact correlation energy of the homogeneous electron gas. The ESX functional does not contain any ingredients of (semi-)local functionals and thus is totally free from self-interactions. The computational cost for solving the self-consistent-field equation is comparable to that of the Hartree-Fock method. We apply the ESX functional to electronic structure calculations for a solid silicon, H - ion, and small atoms. The results demonstrate that the TC-DFT formulation is promising for the systematic improvement of the correlation energy functional.

Lieb-Robinson bounds for spin-boson lattice models and trapped ions.

PubMed

Jünemann, J; Cadarso, A; Pérez-García, D; Bermudez, A; García-Ripoll, J J

2013-12-06

We derive a Lieb-Robinson bound for the propagation of spin correlations in a model of spins interacting through a bosonic lattice field, which satisfies a Lieb-Robinson bound in the absence of spin-boson couplings. We apply these bounds to a system of trapped ions and find that the propagation of spin correlations, as mediated by the phonons of the ion crystal, can be faster than the regimes currently explored in experiments. We propose a scheme to test the bounds by measuring retarded correlation functions via the crystal fluorescence.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors

PubMed Central

Ma, Xiaolei; Du, Bowen; Yu, Bin

2017-01-01

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. PMID:28934164

Confronting species distribution model predictions with species functional traits.

PubMed

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

Assessment of long-range correlation in animal behavior time series: The temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)

NASA Astrophysics Data System (ADS)

Kembro, Jackelyn M.; Flesia, Ana Georgina; Gleiser, Raquel M.; Perillo, María A.; Marin, Raul H.

2013-12-01

Detrended Fluctuation Analysis (DFA) is a method that has been frequently used to determine the presence of long-range correlations in human and animal behaviors. However, according to previous authors using statistical model systems, in order to correctly use DFA different aspects should be taken into account such as: (1) the establishment by hypothesis testing of the absence of short term correlation, (2) an accurate estimation of a straight line in the log-log plot of the fluctuation function, (3) the elimination of artificial crossovers in the fluctuation function, and (4) the length of the time series. Taking into consideration these factors, herein we evaluated the presence of long-range correlation in the temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus). In our study, modeling the data with the general autoregressive integrated moving average (ARFIMA) model, we rejected the hypothesis of short-range correlations (d=0) in all cases. We also observed that DFA was able to distinguish between the artificial crossover observed in the temporal pattern of locomotion of Japanese quail and the crossovers in the correlation behavior observed in mosquito larvae locomotion. Although the test duration can slightly influence the parameter estimation, no qualitative differences were observed between different test durations.

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

Oberkampf, William Louis; Tucker, W. Troy; Zhang, Jianzhong

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Correlates of the categories of adolescent attachment styles: Perceived rearing, family function, early life events, and personality.

PubMed

Tanaka, Nao; Hasui, Chieko; Uji, Masayo; Hiramura, Hidetoshi; Chen, Zi; Shikai, Noriko; Kitamura, Toshinori

2008-02-01

To identify the psychosocial correlates of adolescents. Unmarried university students (n = 4226) aged 18-23 years were examined in a questionnaire survey. Four clusters of people (indifferent, secure, fearful, and preoccupied) identified by cluster analysis were plotted in 2-D using discriminant function analysis with the first function (father's and mother's Care, Cooperativeness, and family Cohesion on the positive end and Harm Avoidance and father's and mother's Overprotection on the negative end) representing the Self-model and the second function (Reward Dependence and experience of Peer Victimization on the positive end and Self-directedness on the negative end) representing the Other model. These findings partially support Bartholomew's notion that adult attachment is based on the good versus bad representations of the self and the other and that it is influenced by psychosocial environments experienced over the course of development.

Nonperturbative Series Expansion of Green's Functions: The Anatomy of Resonant Inelastic X-Ray Scattering in the Doped Hubbard Model

NASA Astrophysics Data System (ADS)

Lu, Yi; Haverkort, Maurits W.

2017-12-01

We present a nonperturbative, divergence-free series expansion of Green's functions using effective operators. The method is especially suited for computing correlators of complex operators as a series of correlation functions of simpler forms. We apply the method to study low-energy excitations in resonant inelastic x-ray scattering (RIXS) in doped one- and two-dimensional single-band Hubbard models. The RIXS operator is expanded into polynomials of spin, density, and current operators weighted by fundamental x-ray spectral functions. These operators couple to different polarization channels resulting in simple selection rules. The incident photon energy dependent coefficients help to pinpoint main RIXS contributions from different degrees of freedom. We show in particular that, with parameters pertaining to cuprate superconductors, local spin excitation dominates the RIXS spectral weight over a wide doping range in the cross-polarization channel.

Probing the triplet correlation function in liquid water by experiments and molecular simulations.

PubMed

Dhabal, Debdas; Wikfeldt, Kjartan Thor; Skinner, Lawrie B; Chakravarty, Charusita; Kashyap, Hemant K

2017-01-25

Despite very significant developments in scattering experiments like X-ray and neutron diffraction, it has been challenging to elucidate the nature of tetrahedral molecular configurations in liquid water. A key question is whether the pair correlation functions, which can be obtained from scattering experiments, are sufficient to describe the tetrahedral ordering of water molecules. In our previous study (Dhabal et al., J. Chem. Phys., 2014, 141, 174504), using data-sets generated from reverse Monte Carlo and molecular dynamics simulations, we showed that the triplet correlation functions contain important information on the tetrahedrality of water in the liquid state. In the present study, X-ray scattering experiments and molecular dynamics (MD) simulations are used to link the isothermal pressure derivative of the structure factor with the triplet correlation functions for water. Triplet functions are determined for water up to 3.3 kbar at 298 K to display the effect of pressure on the water structure. The results suggest that triplet functions (H[combining tilde](q)) obtained using a rigid-body TIP4P/2005 water model are consistent with the experimental results. The triplet functions obtained in experiment as well as in simulations evince that in the case of tetrahedral liquids, exertion of higher pressure leads to a better agreement with the Kirkwood superposition approximation (KSA). We further validate this observation using the triplet correlation functions (g (3) (r,s,t)) calculated directly from simulation trajectory, revealing that both H[combining tilde](q) in q-space and g (3) (r,s,t) in real-space contain similar information on the tetrahedrality of liquids. This study demonstrates that the structure factor, even though it has only pair correlation information of the liquid structure, can shed light on three-body correlations in liquid water through its isothermal pressure derivative term.

Universal RCFT correlators from the holomorphic bootstrap

NASA Astrophysics Data System (ADS)

Mukhi, Sunil; Muralidhara, Girish

2018-02-01

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

Modelling the large-scale redshift-space 3-point correlation function of galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2017-08-01

We present a configuration-space model of the large-scale galaxy 3-point correlation function (3PCF) based on leading-order perturbation theory and including redshift-space distortions (RSD). This model should be useful in extracting distance-scale information from the 3PCF via the baryon acoustic oscillation method. We include the first redshift-space treatment of biasing by the baryon-dark matter relative velocity. Overall, on large scales the effect of RSD is primarily a renormalization of the 3PCF that is roughly independent of both physical scale and triangle opening angle; for our adopted Ωm and bias values, the rescaling is a factor of ˜1.8. We also present an efficient scheme for computing 3PCF predictions from our model, important for allowing fast exploration of the space of cosmological parameters in future analyses.

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

PubMed

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

2017-07-01

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

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.

On the scatter in the relation between stellar mass and halo mass: random or halo formation time dependent?

NASA Astrophysics Data System (ADS)

Wang, Lan; De Lucia, Gabriella; Weinmann, Simone M.

2013-05-01

The empirical traditional halo occupation distribution (HOD) model of Wang et al. fits, by construction, both the stellar mass function and correlation function of galaxies in the local Universe. In contrast, the semi-analytical models of De Lucia & Blazoit (hereafter DLB07) and Guo et al. (hereafter Guo11), built on the same dark matter halo merger trees than the empirical model, still have difficulties in reproducing these observational data simultaneously. We compare the relations between the stellar mass of galaxies and their host halo mass in the three models, and find that they are different. When the relations are rescaled to have the same median values and the same scatter as in Wang et al., the rescaled DLB07 model can fit both the measured galaxy stellar mass function and the correlation function measured in different galaxy stellar mass bins. In contrast, the rescaled Guo11 model still overpredicts the clustering of low-mass galaxies. This indicates that the detail of how galaxies populate the scatter in the stellar mass-halo mass relation does play an important role in determining the correlation functions of galaxies. While the stellar mass of galaxies in the Wang et al. model depends only on halo mass and is randomly distributed within the scatter, galaxy stellar mass depends also on the halo formation time in semi-analytical models. At fixed value of infall mass, galaxies that lie above the median stellar mass-halo mass relation reside in haloes that formed earlier, while galaxies that lie below the median relation reside in haloes that formed later. This effect is much stronger in Guo11 than in DLB07, which explains the overclustering of low mass galaxies in Guo11. Assembly bias in Guo11 model might be overly strong. Nevertheless, in case that a significant assembly bias indeed exists in the real Universe, one needs to use caution when applying current HOD and abundance matching models that employ the assumption of random scatter in the relation between stellar and halo mass.

A simple microstructure return model explaining microstructure noise and Epps effects

NASA Astrophysics Data System (ADS)

Saichev, A.; Sornette, D.

2014-01-01

We present a novel simple microstructure model of financial returns that combines (i) the well-known ARFIMA process applied to tick-by-tick returns, (ii) the bid-ask bounce effect, (iii) the fat tail structure of the distribution of returns and (iv) the non-Poissonian statistics of inter-trade intervals. This model allows us to explain both qualitatively and quantitatively important stylized facts observed in the statistics of both microstructure and macrostructure returns, including the short-ranged correlation of returns, the long-ranged correlations of absolute returns, the microstructure noise and Epps effects. According to the microstructure noise effect, volatility is a decreasing function of the time-scale used to estimate it. The Epps effect states that cross correlations between asset returns are increasing functions of the time-scale at which the returns are estimated. The microstructure noise is explained as the result of the negative return correlations inherent in the definition of the bid-ask bounce component (ii). In the presence of a genuine correlation between the returns of two assets, the Epps effect is due to an average statistical overlap of the momentum of the returns of the two assets defined over a finite time-scale in the presence of the long memory process (i).

Statistical model of a flexible inextensible polymer chain: The effect of kinetic energy.

PubMed

Pergamenshchik, V M; Vozniak, A B

2017-01-01

Because of the holonomic constraints, the kinetic energy contribution in the partition function of an inextensible polymer chain is difficult to find, and it has been systematically ignored. We present the first thermodynamic calculation incorporating the kinetic energy of an inextensible polymer chain with the bending energy. To explore the effect of the translation-rotation degrees of freedom, we propose and solve a statistical model of a fully flexible chain of N+1 linked beads which, in the limit of smooth bending, is equivalent to the well-known wormlike chain model. The partition function with the kinetic and bending energies and correlations between orientations of any pair of links and velocities of any pair of beads are found. This solution is precise in the limits of small and large rigidity-to-temperature ratio b/T. The last exact solution is essential as even very "harmless" approximation results in loss of the important effects when the chain is very rigid. For very high b/T, the orientations of different links become fully correlated. Nevertheless, the chain does not go over into a hard rod even in the limit b/T→∞: While the velocity correlation length diverges, the correlations themselves remain weak and tend to the value ∝T/(N+1). The N dependence of the partition function is essentially determined by the kinetic energy contribution. We demonstrate that to obtain the correct energy and entropy in a constrained system, the T derivative of the partition function has to be applied before integration over the constraint-setting variable.

Statistical model of a flexible inextensible polymer chain: The effect of kinetic energy

NASA Astrophysics Data System (ADS)

Pergamenshchik, V. M.; Vozniak, A. B.

2017-01-01

Because of the holonomic constraints, the kinetic energy contribution in the partition function of an inextensible polymer chain is difficult to find, and it has been systematically ignored. We present the first thermodynamic calculation incorporating the kinetic energy of an inextensible polymer chain with the bending energy. To explore the effect of the translation-rotation degrees of freedom, we propose and solve a statistical model of a fully flexible chain of N +1 linked beads which, in the limit of smooth bending, is equivalent to the well-known wormlike chain model. The partition function with the kinetic and bending energies and correlations between orientations of any pair of links and velocities of any pair of beads are found. This solution is precise in the limits of small and large rigidity-to-temperature ratio b /T . The last exact solution is essential as even very "harmless" approximation results in loss of the important effects when the chain is very rigid. For very high b /T , the orientations of different links become fully correlated. Nevertheless, the chain does not go over into a hard rod even in the limit b /T →∞ : While the velocity correlation length diverges, the correlations themselves remain weak and tend to the value ∝T /(N +1 ). The N dependence of the partition function is essentially determined by the kinetic energy contribution. We demonstrate that to obtain the correct energy and entropy in a constrained system, the T derivative of the partition function has to be applied before integration over the constraint-setting variable.

Logarithmic violation of scaling in anisotropic kinematic dynamo model

NASA Astrophysics Data System (ADS)

Antonov, N. V.; Gulitskiy, N. M.

2016-01-01

Inertial-range asymptotic behavior of a vector (e.g., magnetic) field, passively advected by a strongly anisotropic turbulent flow, is studied by means of the field theoretic renormalization group and the operator product expansion. The advecting velocity field is Gaussian, not correlated in time, with the pair correlation function of the form ∝δ (t -t')/k⊥d-1 +ξ , where k⊥ = |k⊥| and k⊥ is the component of the wave vector, perpendicular to the distinguished direction. The stochastic advection-diffusion equation for the transverse (divergence-free) vector field includes, as special cases, the kinematic dynamo model for magnetohydrodynamic turbulence and the linearized Navier-Stokes equation. In contrast to the well known isotropic Kraichnan's model, where various correlation functions exhibit anomalous scaling behavior with infinite sets of anomalous exponents, here the dependence on the integral turbulence scale L has a logarithmic behavior: instead of power-like corrections to ordinary scaling, determined by naive (canonical) dimensions, the anomalies manifest themselves as polynomials of logarithms of L.

Interactions between different EEG frequency bands and their effect on alpha-fMRI correlations.

PubMed

de Munck, J C; Gonçalves, S I; Mammoliti, R; Heethaar, R M; Lopes da Silva, F H

2009-08-01

In EEG/fMRI correlation studies it is common to consider the fMRI BOLD as filtered version of the EEG alpha power. Here the question is addressed whether other EEG frequency components may affect the correlation between alpha and BOLD. This was done comparing the statistical parametric maps (SPMs) of three different filter models wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. EEG and fMRI were co-registered in a 30 min resting state condition in 15 healthy young subjects. Power variations in the delta, theta, alpha, beta and gamma bands were extracted from the EEG and used as regressors in a general linear model. Statistical parametric maps (SPMs) were computed using three different filter models, wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. Results show that the SPMs of different EEG frequency bands, when significant, are very similar to that of the alpha rhythm. This is true in particular for the beta band, despite the fact that the alpha harmonics were discarded. It is shown that inclusion of EEG frequency bands as confounder in the fMRI-alpha correlation model has a large effect on the resulting SPM, in particular when for each frequency band the HRF is extracted from the data. We conclude that power fluctuations of different EEG frequency bands are mutually highly correlated, and that a multi frequency model is required to extract the SPM of the frequency of interest from EEG/fMRI data. When no constraints are put on the shapes of the HRFs of the nuisance frequencies, the correlation model looses so much statistical power that no correlations can be detected.

Finite size of hadrons and Bose-Einstein correlations in pp collisions at 7 TeV

NASA Astrophysics Data System (ADS)

Bialas, Andrzej; Florkowski, Wojciech; Zalewski, Kacper

2015-09-01

Space-time correlations between produced particles, induced by the composite nature of hadrons, imply specific changes in the properties of the correlation functions for identical particles. The expected magnitude of these effects is evaluated using the recently published blast-wave model analysis of the data for pp collisions at √{ s} = 7 TeV.

Generalized interferometry - I: theory for interstation correlations

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Collaborations between CpG sites in DNA methylation

NASA Astrophysics Data System (ADS)

Song, You; Ren, Honglei; Lei, Jinzhi

2017-08-01

DNA methylation patterns have profound impacts on genome stability, gene expression and development. The molecular base of DNA methylation patterns has long been focused at single CpG sites level. Here, we construct a kinetic model of DNA methylation with collaborations between CpG sites, from which a correlation function was established based on experimental data. The function consists of three parts that suggest three possible sources of the correlation: movement of enzymes along DNA, collaboration between DNA methylation and nucleosome modification, and global enzyme concentrations within a cell. Moreover, the collaboration strength between DNA methylation and nucleosome modification is universal for mouse early embryo cells. The obtained correlation function provides insightful understanding for the mechanisms of inheritance of DNA methylation patterns.

Dependence of the atomic level Green-Kubo stress correlation function on wavevector and frequency: molecular dynamics results from a model liquid.

PubMed

Levashov, V A

2014-09-28

We report on a further investigation of a new method that can be used to address vibrational dynamics and propagation of stress waves in liquids. The method is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the atomic level stress correlation functions. This decomposition, as was demonstrated previously for a model liquid studied in molecular dynamics simulations, reveals the presence of stress waves propagating over large distances and a structure that resembles the pair density function. In this paper, by performing the Fourier transforms of the atomic level stress correlation functions, we elucidate how the lifetimes of the stress waves and the ranges of their propagation depend on their frequency, wavevector, and temperature. These results relate frequency and wavevector dependence of the generalized viscosity to the character of propagation of the shear stress waves. In particular, the results suggest that an increase in the value of the frequency dependent viscosity at low frequencies with decrease of temperature is related to the increase in the ranges of propagation of the stress waves of the corresponding low frequencies. We found that the ranges of propagation of the shear stress waves of frequencies less than half of the Einstein frequency extend well beyond the nearest neighbor shell even above the melting temperature. The results also show that the crossover from quasilocalized to propagating behavior occurs at frequencies usually associated with the Boson peak.

On the role of structure-dynamic relationship in determining the excess entropy of mixing and chemical ordering in binary square-well liquid alloys

NASA Astrophysics Data System (ADS)

Lalneihpuii, R.; Shrivastava, Ruchi; Mishra, Raj Kumar

2018-05-01

Using statistical mechanical model with square-well (SW) interatomic potential within the frame work of mean spherical approximation, we determine the composition dependent microscopic correlation functions, interdiffusion coefficients, surface tension and chemical ordering in Ag-Cu melts. Further Dzugutov universal scaling law of normalized diffusion is verified with SW potential in binary mixtures. We find that the excess entropy scaling law is valid for SW binary melts. The partial and total structure factors in the attractive and repulsive regions of the interacting potential are evaluated and then Fourier transformed to get partial and total radial distribution functions. A good agreement between theoretical and experimental values for total structure factor and the reduced radial distribution function are observed, which consolidates our model calculations. The well-known Bhatia-Thornton correlation functions are also computed for Ag-Cu melts. The concentration-concentration correlations in the long wavelength limit in liquid Ag-Cu alloys have been analytically derived through the long wavelength limit of partial correlation functions and apply it to demonstrate the chemical ordering and interdiffusion coefficients in binary liquid alloys. We also investigate the concentration dependent viscosity coefficients and surface tension using the computed diffusion data in these alloys. Our computed results for structure, transport and surface properties of liquid Ag-Cu alloys obtained with square-well interatomic interaction are fully consistent with their corresponding experimental values.

Constraints on the nuclear equation of state from nuclear masses and radii in a Thomas-Fermi meta-modeling approach

NASA Astrophysics Data System (ADS)

Chatterjee, D.; Gulminelli, F.; Raduta, Ad. R.; Margueron, J.

2017-12-01

The question of correlations among empirical equation of state (EoS) parameters constrained by nuclear observables is addressed in a Thomas-Fermi meta-modeling approach. A recently proposed meta-modeling for the nuclear EoS in nuclear matter is augmented with a single finite size term to produce a minimal unified EoS functional able to describe the smooth part of the nuclear ground state properties. This meta-model can reproduce the predictions of a large variety of models, and interpolate continuously between them. An analytical approximation to the full Thomas-Fermi integrals is further proposed giving a fully analytical meta-model for nuclear masses. The parameter space is sampled and filtered through the constraint of nuclear mass reproduction with Bayesian statistical tools. We show that this simple analytical meta-modeling has a predictive power on masses, radii, and skins comparable to full Hartree-Fock or extended Thomas-Fermi calculations with realistic energy functionals. The covariance analysis on the posterior distribution shows that no physical correlation is present between the different EoS parameters. Concerning nuclear observables, a strong correlation between the slope of the symmetry energy and the neutron skin is observed, in agreement with previous studies.

Log-correlated random-energy models with extensive free-energy fluctuations: Pathologies caused by rare events as signatures of phase transitions

NASA Astrophysics Data System (ADS)

Cao, Xiangyu; Fyodorov, Yan V.; Le Doussal, Pierre

2018-02-01

We address systematically an apparent nonphysical behavior of the free-energy moment generating function for several instances of the logarithmically correlated models: the fractional Brownian motion with Hurst index H =0 (fBm0) (and its bridge version), a one-dimensional model appearing in decaying Burgers turbulence with log-correlated initial conditions and, finally, the two-dimensional log-correlated random-energy model (logREM) introduced in Cao et al. [Phys. Rev. Lett. 118, 090601 (2017), 10.1103/PhysRevLett.118.090601] based on the two-dimensional Gaussian free field with background charges and directly related to the Liouville field theory. All these models share anomalously large fluctuations of the associated free energy, with a variance proportional to the log of the system size. We argue that a seemingly nonphysical vanishing of the moment generating function for some values of parameters is related to the termination point transition (i.e., prefreezing). We study the associated universal log corrections in the frozen phase, both for logREMs and for the standard REM, filling a gap in the literature. For the above mentioned integrable instances of logREMs, we predict the nontrivial free-energy cumulants describing non-Gaussian fluctuations on the top of the Gaussian with extensive variance. Some of the predictions are tested numerically.

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.

Density-functional theory applied to d- and f-electron systems

NASA Astrophysics Data System (ADS)

Wu, Xueyuan

Density functional theory (DFT) has been applied to study the electronic and geometric structures of prototype d- and f-electron systems. For the d-electron system, all electron DFT with gradient corrections to the exchange and correlation functionals has been used to investigate the properties of small neutral and cationic vanadium clusters. Results are in good agreement with available experimental and other theoretical data. For the f-electron system, a hybrid DFT, namely, B3LYP (Becke's 3-parameter hybrid functional using the correlation functional of Lee, Yang and Parr) with relativistic effective core potentials and cluster models has been applied to investigate the nature of chemical bonding of both the bulk and the surfaces of plutonium monoxide and dioxide. Using periodic models, the electronic and geometric structures of PuO2 and its (110) surface, as well as water adsorption on this surface have also been investigated using DFT in both local density approximation (LDA) and generalized gradient approximation (GGA) formalisms.

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

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

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

Exact results for quench dynamics and defect production in a two-dimensional model.

PubMed

Sengupta, K; Sen, Diptiman; Mondal, Shreyoshi

2008-02-22

We show that for a d-dimensional model in which a quench with a rate tau(-1) takes the system across a (d-m)-dimensional critical surface, the defect density scales as n approximately 1/tau(mnu/(znu+1)), where nu and z are the correlation length and dynamical critical exponents characterizing the critical surface. We explicitly demonstrate that the Kitaev model provides an example of such a scaling with d = 2 and m = nu = z = 1. We also provide the first example of an exact calculation of some multispin correlation functions for a two-dimensional model that can be used to determine the correlation between the defects. We suggest possible experiments to test our theory.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

Simulation of synthetic discriminant function optical implementation

NASA Astrophysics Data System (ADS)

Riggins, J.; Butler, S.

1984-12-01

The optical implementation of geometrical shape and synthetic discriminant function matched filters is computer modeled. The filter implementation utilizes the Allebach-Keegan computer-generated hologram algorithm. Signal-to-noise and efficiency measurements were made on the resultant correlation planes.

A Parametric Study of Fine-scale Turbulence Mixing Noise

NASA Technical Reports Server (NTRS)

Khavaran, Abbas; Bridges, James; Freund, Jonathan B.

2002-01-01

The present paper is a study of aerodynamic noise spectra from model functions that describe the source. The study is motivated by the need to improve the spectral shape of the MGBK jet noise prediction methodology at high frequency. The predicted spectral shape usually appears less broadband than measurements and faster decaying at high frequency. Theoretical representation of the source is based on Lilley's equation. Numerical simulations of high-speed subsonic jets as well as some recent turbulence measurements reveal a number of interesting statistical properties of turbulence correlation functions that may have a bearing on radiated noise. These studies indicate that an exponential spatial function may be a more appropriate representation of a two-point correlation compared to its Gaussian counterpart. The effect of source non-compactness on spectral shape is discussed. It is shown that source non-compactness could well be the differentiating factor between the Gaussian and exponential model functions. In particular, the fall-off of the noise spectra at high frequency is studied and it is shown that a non-compact source with an exponential model function results in a broader spectrum and better agreement with data. An alternate source model that represents the source as a covariance of the convective derivative of fine-scale turbulence kinetic energy is also examined.

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

Predictive Models for Regional Hepatic Function Based on 99mTc-IDA SPECT and Local Radiation Dose for Physiologic Adaptive Radiation Therapy

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

Wang, Hesheng, E-mail: hesheng@umich.edu; Feng, Mary; Frey, Kirk A.

2013-08-01

Purpose: High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Methods and Materials: Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF)more » images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose–response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. Results: The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=−0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). Conclusions: 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage.« less

Predictive models for regional hepatic function based on 99mTc-IDA SPECT and local radiation dose for physiologic adaptive radiation therapy.

PubMed

Wang, Hesheng; Feng, Mary; Frey, Kirk A; Ten Haken, Randall K; Lawrence, Theodore S; Cao, Yue

2013-08-01

High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF) images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose-response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=-0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage. Published by Elsevier Inc.

Relationships between mastitis and functional longevity in Danish Black and White dairy cattle estimated using survival analysis.

PubMed

Neerhof, H J; Madsen, P; Ducrocq, V P; Vollema, A R; Jensen, J; Korsgaard, I R

2000-05-01

The relationship between mastitis and functional longevity was assessed with survival analysis on data of Danish Black and White dairy cows. Different methods of including the effect of mastitis treatment on the culling decision by a farmer in the model were compared. The model in which mastitis treatment was assumed to have an effect on functional longevity until the end of the lactation had the highest likelihood, and the model in which mastitis treatment had an effect for only a short period had the lowest likelihood. A cow with mastitis had 1.69 times greater risk of being culled than did a healthy herdmate with all other effects being the same. A model without mastitis treatment was used to predict transmitting abilities of bulls for risk of being culled, based on longevity records of their daughters, and was expressed in terms of risk of being culled. The correlation between the risk of being culled and the national evaluations of the bulls for mastitis resistance was approximately -0.4, indicating that resistance against mastitis was genetically correlated with a lower risk of being culled and, thus, a longer functional length of productive life.

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

Impact of Autocorrelation on Functional Connectivity

PubMed Central

Arbabshirani, Mohammad R.; Damaraju, Eswar; Phlypo, Ronald; Plis, Sergey; Allen, Elena; Ma, Sai; Mathalon, Daniel; Preda, Adrian; Vaidya, Jatin G.; Adali, Tülay; Calhoun, Vince D.

2014-01-01

Although the impact of serial correlation (autocorrelation) in residuals of general linear models for fMRI time-series has been studied extensively, the effect of autocorrelation on functional connectivity studies has been largely neglected until recently. Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results in “spurious” correlation coefficients. In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. To our knowledge this is the first work comprehensively investigating the effect of autocorrelation on functional connectivity estimates. Our results show that although FC values are altered, even following correction for autocorrelation, results of hypothesis testing on FC values remain very similar to those before correction. In real data we show this is true for main effects and also for group difference testing between healthy controls and schizophrenia patients. We further discuss model order selection in the context of autoregressive processes, effects of frequency filtering and propose a preprocessing pipeline for connectivity studies. PMID:25072392

Molecular basis of crystal morphology-dependent adhesion behavior of mefenamic acid during tableting.

PubMed

Waknis, Vrushali; Chu, Elza; Schlam, Roxana; Sidorenko, Alexander; Badawy, Sherif; Yin, Shawn; Narang, Ajit S

2014-01-01

The molecular basis of crystal surface adhesion leading to sticking was investigated by exploring the correlation of crystal adhesion to oxidized iron coated atomic force microscope (AFM) tips and bulk powder sticking behavior during tableting of two morphologically different crystals of a model drug, mefenamic acid (MA), to differences in their surface functional group orientation and energy. MA was recrystallized into two morphologies (plates and needles) of the same crystalline form. Crystal adhesion to oxidized iron coated AFM tips and bulk powder sticking to tablet punches was assessed using a direct compression formulation. Surface functional group orientation and energies on crystal faces were modeled using Accelrys Material Studio software. Needle-shaped morphology showed higher sticking tendency than plates despite similar particle size. This correlated with higher crystal surface adhesion of needle-shaped morphology to oxidized iron coated AFM probe tips, and greater surface energy and exposure of polar functional groups. Higher surface exposure of polar functional groups correlates with higher tendency to stick to metal surfaces and AFM tips, indicating involvement of specific polar interactions in the adhesion behavior. In addition, an AFM method is identified to prospectively assess the risk of sticking during the early stages of drug development.

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.

Cardiac function in muscular dystrophy associates with abdominal muscle pathology.

PubMed

Gardner, Brandon B; Swaggart, Kayleigh A; Kim, Gene; Watson, Sydeaka; McNally, Elizabeth M

The muscular dystrophies target muscle groups differentially. In mouse models of muscular dystrophy, notably the mdx model of Duchenne Muscular Dystrophy, the diaphragm muscle shows marked fibrosis and at an earlier age than other muscle groups, more reflective of the histopathology seen in human muscular dystrophy. Using a mouse model of limb girdle muscular dystrophy, the Sgcg mouse, we compared muscle pathology across different muscle groups and heart. A cohort of nearly 200 Sgcg mice were studied using multiple measures of pathology including echocardiography, Evans blue dye uptake and hydroxyproline content in multiple muscle groups. Spearman rank correlations were determined among echocardiographic and pathological parameters. The abdominal muscles were found to have more fibrosis than other muscle groups, including the diaphragm muscle. The abdominal muscles also had more Evans blue dye uptake than other muscle groups. The amount of diaphragm fibrosis was found to correlate positively with fibrosis in the left ventricle, and abdominal muscle fibrosis correlated with impaired left ventricular function. Fibrosis in the abdominal muscles negatively correlated with fibrosis in the diaphragm and right ventricles. Together these data reflect the recruitment of abdominal muscles as respiratory muscles in muscular dystrophy, a finding consistent with data from human patients.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Coherent model of L-band radar scattering by soybean plants: model development, validation and retrieval

USDA-ARS?s Scientific Manuscript database

An improved coherent branching model for L-band radar remote sensing of soybean is proposed by taking into account the correlated scattering among scatterers. The novel feature of the analytic coherent model consists of conditional probability functions to eliminate the overlapping effects of branc...

Reflex-based grasping, skilled forelimb reaching, and electrodiagnostic evaluation for comprehensive analysis of functional recovery-The 7-mm rat median nerve gap repair model revisited.

PubMed

Stößel, Maria; Rehra, Lena; Haastert-Talini, Kirsten

2017-10-01

The rat median nerve injury and repair model gets increasingly important for research on novel bioartificial nerve grafts. It allows follow-up evaluation of the recovery of the forepaw functional ability with several sensitive techniques. The reflex-based grasping test, the skilled forelimb reaching staircase test, as well as electrodiagnostic recordings have been described useful in this context. Currently, no standard values exist, however, for comparison or comprehensive correlation of results obtained in each of the three methods after nerve gap repair in adult rats. Here, we bilaterally reconstructed 7-mm median nerve gaps with autologous nerve grafts (ANG) or autologous muscle-in-vein grafts (MVG), respectively. During 8 and 12 weeks of observation, functional recovery of each paw was separately monitored using the grasping test (weekly), the staircase test, and noninvasive electrophysiological recordings from the thenar muscles (both every 4 weeks). Evaluation was completed by histomorphometrical analyses at 8 and 12 weeks postsurgery. The comprehensive evaluation detected a significant difference in the recovery of forepaw functional motor ability between the ANG and MVG groups. The correlation between the different functional tests evaluated precisely displayed the recovery of distinct levels of forepaw functional ability over time. Thus, this multimodal evaluation model represents a valuable preclinical model for peripheral nerve reconstruction approaches.

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

PubMed

Levashov, V A

2017-11-14

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

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

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2017-11-01

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

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

PubMed Central

Sverdlov, Serge; Thompson, Elizabeth A.

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Identification of AR(I)MA processes for modelling temporal correlations of GPS observations

NASA Astrophysics Data System (ADS)

Luo, X.; Mayer, M.; Heck, B.

2009-04-01

In many geodetic applications observations of the Global Positioning System (GPS) are routinely processed by means of the least-squares method. However, this algorithm delivers reliable estimates of unknown parameters und realistic accuracy measures only if both the functional and stochastic models are appropriately defined within GPS data processing. One deficiency of the stochastic model used in many GPS software products consists in neglecting temporal correlations of GPS observations. In practice the knowledge of the temporal stochastic behaviour of GPS observations can be improved by analysing time series of residuals resulting from the least-squares evaluation. This paper presents an approach based on the theory of autoregressive (integrated) moving average (AR(I)MA) processes to model temporal correlations of GPS observations using time series of observation residuals. A practicable integration of AR(I)MA models in GPS data processing requires the determination of the order parameters of AR(I)MA processes at first. In case of GPS, the identification of AR(I)MA processes could be affected by various factors impacting GPS positioning results, e.g. baseline length, multipath effects, observation weighting, or weather variations. The influences of these factors on AR(I)MA identification are empirically analysed based on a large amount of representative residual time series resulting from differential GPS post-processing using 1-Hz observation data collected within the permanent SAPOS® (Satellite Positioning Service of the German State Survey) network. Both short and long time series are modelled by means of AR(I)MA processes. The final order parameters are determined based on the whole residual database; the corresponding empirical distribution functions illustrate that multipath and weather variations seem to affect the identification of AR(I)MA processes much more significantly than baseline length and observation weighting. Additionally, the modelling results of temporal correlations using high-order AR(I)MA processes are compared with those by means of first order autoregressive (AR(1)) processes and empirically estimated autocorrelation functions.

Modelling population distribution using remote sensing imagery and location-based data

NASA Astrophysics Data System (ADS)

Song, J.; Prishchepov, A. V.

2017-12-01

Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models, confirming that GWR models demonstrate better prediction accuracy. So this method provide detailed population density information for microscale citizen studies.

The Angular Three-Point Correlation Function in the Quasi-linear Regime

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

Buchalter, Ari; Kamionkowski, Marc; Jaffe, Andrew H.

2000-02-10

We calculate the normalized angular three-point correlation function (3PCF), q, as well as the normalized angular skewness, s{sub 3}, assuming the small-angle approximation, for a biased mass distribution in flat and open cold dark matter (CDM) models with Gaussian initial conditions. The leading-order perturbative results incorporate the explicit dependence on the cosmological parameters, the shape of the CDM transfer function, the linear evolution of the power spectrum, the form of the assumed redshift distribution function, and linear and nonlinear biasing, which may be evolving. Results are presented for different redshift distributions, including that appropriate for the APM Galaxy Survey, asmore » well as for a survey with a mean redshift of z{approx_equal}1 (such as the VLA FIRST Survey). Qualitatively, many of the results found for s{sub 3} and q are similar to those obtained in a related treatment of the spatial skewness and 3PCF, such as a leading-order correction to the standard result for s{sub 3} in the case of nonlinear bias (as defined for unsmoothed density fields), and the sensitivity of the configuration dependence of q to both cosmological and biasing models. We show that since angular correlation functions (CFs) are sensitive to clustering over a range of redshifts, the various evolutionary dependences included in our predictions imply that measurements of q in a deep survey might better discriminate between models with different histories, such as evolving versus nonevolving bias, that can have similar spatial CFs at low redshift. Our calculations employ a derived equation, valid for open, closed, and flat models, to obtain the angular bispectrum from the spatial bispectrum in the small-angle approximation. (c) (c) 2000. The American Astronomical Society.« less

Reconciling mass functions with the star-forming main sequence via mergers

NASA Astrophysics Data System (ADS)

Steinhardt, Charles L.; Yurk, Dominic; Capak, Peter

2017-06-01

We combine star formation along the 'main sequence', quiescence and clustering and merging to produce an empirical model for the evolution of individual galaxies. Main-sequence star formation alone would significantly steepen the stellar mass function towards low redshift, in sharp conflict with observation. However, a combination of star formation and merging produces a consistent result for correct choice of the merger rate function. As a result, we are motivated to propose a model in which hierarchical merging is disconnected from environmentally independent star formation. This model can be tested via correlation functions and would produce new constraints on clustering and merging.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Communication: importance sampling including path correlation in semiclassical initial value representation calculations for time correlation functions.

PubMed

Pan, Feng; Tao, Guohua

2013-03-07

Full semiclassical (SC) initial value representation (IVR) for time correlation functions involves a double phase space average over a set of two phase points, each of which evolves along a classical path. Conventionally, the two initial phase points are sampled independently for all degrees of freedom (DOF) in the Monte Carlo procedure. Here, we present an efficient importance sampling scheme by including the path correlation between the two initial phase points for the bath DOF, which greatly improves the performance of the SC-IVR calculations for large molecular systems. Satisfactory convergence in the study of quantum coherence in vibrational relaxation has been achieved for a benchmark system-bath model with up to 21 DOF.

Comparison of high pressure transient PVT measurements and model predictions. Part I.

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

Felver, Todd G.; Paradiso, Nicholas Joseph; Evans, Gregory Herbert

2010-07-01

A series of experiments consisting of vessel-to-vessel transfers of pressurized gas using Transient PVT methodology have been conducted to provide a data set for optimizing heat transfer correlations in high pressure flow systems. In rapid expansions such as these, the heat transfer conditions are neither adiabatic nor isothermal. Compressible flow tools exist, such as NETFLOW that can accurately calculate the pressure and other dynamical mechanical properties of such a system as a function of time. However to properly evaluate the mass that has transferred as a function of time these computational tools rely on heat transfer correlations that must bemore » confirmed experimentally. In this work new data sets using helium gas are used to evaluate the accuracy of these correlations for receiver vessel sizes ranging from 0.090 L to 13 L and initial supply pressures ranging from 2 MPa to 40 MPa. The comparisons show that the correlations developed in the 1980s from sparse data sets perform well for the supply vessels but are not accurate for the receivers, particularly at early time during the transfers. This report focuses on the experiments used to obtain high quality data sets that can be used to validate computational models. Part II of this report discusses how these data were used to gain insight into the physics of gas transfer and to improve vessel heat transfer correlations. Network flow modeling and CFD modeling is also discussed.« less

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

PubMed

Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

2017-12-01

Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

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

Modeling and prediction of relaxation of polar order in high-activity nonlinear optical polymers

NASA Astrophysics Data System (ADS)

Guenthner, Andrew J.; Lindsay, Geoffrey A.; Wright, Michael E.; Fallis, Stephen; Ashley, Paul R.; Sanghadasa, Mohan

2007-09-01

Mach-Zehnder optical modulators were fabricated using the CLD and FTC chromophores in polymer-on-silicon optical waveguides. Up to 17 months of oven-ageing stability are reported for the poled polymer films. Modulators containing an FTC-polyimide had the best over all aging performance. To model and extrapolate the ageing data, a relaxation correlation function attributed to A. K. Jonscher was compared to the well-established stretched exponential correlation function. Both models gave a good fit to the data. The Jonscher model predicted a slower relaxation rate in the out years. Analysis showed that collecting data for a longer period relative to the relaxation time was more important for generating useful predictions than the precision with which individual model parameters could be estimated. Thus from a practical standpoint, time-temperature superposition must be assumed in order to generate meaningful predictions. For this purpose, Arrhenius-type expressions were found to relate the model time constants to the ageing temperatures.

Phase demodulation method from a single fringe pattern based on correlation with a polynomial form.

PubMed

Robin, Eric; Valle, Valéry; Brémand, Fabrice

2005-12-01

The method presented extracts the demodulated phase from only one fringe pattern. Locally, this method approaches the fringe pattern morphology with the help of a mathematical model. The degree of similarity between the mathematical model and the real fringe is estimated by minimizing a correlation function. To use an optimization process, we have chosen a polynomial form such as a mathematical model. However, the use of a polynomial form induces an identification procedure with the purpose of retrieving the demodulated phase. This method, polynomial modulated phase correlation, is tested on several examples. Its performance, in terms of speed and precision, is presented on very noised fringe patterns.

Space-time correlations of fluctuating velocities in turbulent shear flows

NASA Astrophysics Data System (ADS)

Zhao, Xin; He, Guo-Wei

2009-04-01

Space-time correlations or Eulerian two-point two-time correlations of fluctuating velocities are analytically and numerically investigated in turbulent shear flows. An elliptic model for the space-time correlations in the inertial range is developed from the similarity assumptions on the isocorrelation contours: they share a uniform preference direction and a constant aspect ratio. The similarity assumptions are justified using the Kolmogorov similarity hypotheses and verified using the direct numerical simulation (DNS) of turbulent channel flows. The model relates the space-time correlations to the space correlations via the convection and sweeping characteristic velocities. The analytical expressions for the convection and sweeping velocities are derived from the Navier-Stokes equations for homogeneous turbulent shear flows, where the convection velocity is represented by the mean velocity and the sweeping velocity is the sum of the random sweeping velocity and the shear-induced velocity. This suggests that unlike Taylor’s model where the convection velocity is dominating and Kraichnan and Tennekes’ model where the random sweeping velocity is dominating, the decorrelation time scales of the space-time correlations in turbulent shear flows are determined by the convection velocity, the random sweeping velocity, and the shear-induced velocity. This model predicts a universal form of the space-time correlations with the two characteristic velocities. The DNS of turbulent channel flows supports the prediction: the correlation functions exhibit a fair good collapse, when plotted against the normalized space and time separations defined by the elliptic model.

Synthesis of geophysical data with space-acquired imagery: a review

USGS Publications Warehouse

Hastings, David A.

1983-01-01

Statistical correlation has been used to determine the applicability of specific data sets to the development of geologic or exploration models. Various arithmetic functions have proven useful in developing models from such data sets.

Interaction quantum quenches in the one-dimensional Fermi-Hubbard model

NASA Astrophysics Data System (ADS)

Heidrich-Meisner, Fabian; Bauer, Andreas; Dorfner, Florian; Riegger, Luis; Orso, Giuliano

2016-05-01

We discuss the nonequilibrium dynamics in two interaction quantum quenches in the one-dimensional Fermi-Hubbard model. First, we study the decay of the Néel state as a function of interaction strength. We observe a fast charge dynamics over which double occupancies are built up, while the long-time decay of the staggered moment is controlled by spin excitations, corroborated by the analysis of the entanglement dynamics. Second, we investigate the formation of Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) correlations in a spin-imbalanced system in quenches from the noninteracting case to attractive interactions. Even though the quench puts the system at a finite energy density, peaks at the characteristic FFLO quasimomenta are visible in the quasi-momentum distribution function, albeit with an exponential decay of s-wave pairing correlations. We also discuss the imprinting of FFLO correlations onto repulsively bound pairs and their rapid decay in ramps. Supported by the DFG (Deutsche Forschungsgemeinschaft) via FOR 1807.

RG flow from Φ 4 theory to the 2D Ising model

DOE PAGES

Anand, Nikhil; Genest, Vincent X.; Katz, Emanuel; ...

2017-08-16

We study 1+1 dimensional Φ 4 theory using the recently proposed method of conformal truncation. Starting in the UV CFT of free field theory, we construct a complete basis of states with definite conformal Casimir, C. We use these states to express the Hamiltonian of the full interacting theory in lightcone quantization. After truncating to states with C≤C max, we numerically diagonalize the Hamiltonian at strong coupling and study the resulting IR dynamics. We compute non-perturbative spectral densities of several local operators, which are equivalent to real-time, infinite-volume correlation functions. These spectral densities, which include the Zamolodchikov C-function along themore » full RG flow, are calculable at any value of the coupling. Near criticality, our numerical results reproduce correlation functions in the 2D Ising model.« less

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

PubMed

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

2014-04-01

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

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.

Time dependence of correlation functions following a quantum quench.

PubMed

Calabrese, Pasquale; Cardy, John

2006-04-07

We show that the time dependence of correlation functions in an extended quantum system in d dimensions, which is prepared in the ground state of some Hamiltonian and then evolves without dissipation according to some other Hamiltonian, may be extracted using methods of boundary critical phenomena in d + 1 dimensions. For d = 1 particularly powerful results are available using conformal field theory. These are checked against those available from solvable models. They may be explained in terms of a picture, valid more generally, whereby quasiparticles, entangled over regions of the order of the correlation length in the initial state, then propagate classically through the system.

Kinetic theory of coupled oscillators.

PubMed

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

2007-02-02

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

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior

PubMed Central

Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-01-01

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information. PMID:29513219

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

PubMed

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Generalized multi-Gaussian correlated Schell-model beam: from theory to experiment.

PubMed

Wang, Fei; Liang, Chunhao; Yuan, Yangsheng; Cai, Yangjian

2014-09-22

A new kind of partially coherent beam with non-conventional correlation function named generalized multi-Gaussian correlated Schell-model (GMGCSM) beam is proposed. The GMGCSM beam of the first or second kind is capable of producing dark hollow or flat-topped beam profile in the focal plane (or in the far field). Furthermore, we carry out experimental generation of a GMGCSM beam of the first or second kind, and measure its focused intensity. Our experimental results verify theoretical predictions. The GMGCSM beam will be useful for free-space optical communications, material thermal processing, particle or atom trapping.

Probability theory for 3-layer remote sensing in ideal gas law environment.

PubMed

Ben-David, Avishai; Davidson, Charles E

2013-08-26

We extend the probability model for 3-layer radiative transfer [Opt. Express 20, 10004 (2012)] to ideal gas conditions where a correlation exists between transmission and temperature of each of the 3 layers. The effect on the probability density function for the at-sensor radiances is surprisingly small, and thus the added complexity of addressing the correlation can be avoided. The small overall effect is due to (a) small perturbations by the correlation on variance population parameters and (b) cancellation of perturbation terms that appear with opposite signs in the model moment expressions.

The stochastic resonance for the incidence function model of metapopulation

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei

2017-06-01

A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.

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

PubMed

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

2007-12-20

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

Role of theory of mind and executive function in explaining social intelligence: a structural equation modeling approach.

PubMed

Yeh, Zai-Ting

2013-01-01

Social intelligence is the ability to understand others and the social context effectively and thus to interact with people successfully. Research has suggested that the theory of mind (ToM) and executive function may play important roles in explaining social intelligence. The specific aim of the present study was to test with structural equation modeling (SEM) the hypothesis that performance on ToM tasks is more associated with social intelligence in the elderly than is performance on executive functions. One hundred and seventy-seven participants (age 56-96) completed ToM, executive function, and other basic cognition tasks, and were rated with social intelligence scales. The SEM results showed that ToM and executive function were strongly correlated (0.54); however, only the path coefficient from ToM to social intelligence, and not from executive function, was significant (0.37). ToM performance, but not executive function, was strongly correlated with social intelligence among elderly individuals. ToM and executive function might play different roles in social behavior during normal aging; however, based on the present results, it is possible that ToM might play an important role in social intelligence.

A Patch Density Recommendation based on Convergence Studies for Vehicle Panel Vibration Response resulting from Excitation by a Diffuse Acoustic Field

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Hunt, Ron

2013-01-01

Fluid structural interaction problems that estimate panel vibration from an applied pressure field excitation are quite dependent on the spatial correlation of the pressure field. There is a danger of either over estimating a low frequency response or under predicting broad band panel response in the more modally dense bands if the pressure field spatial correlation is not accounted for adequately. Even when the analyst elects to use a fitted function for the spatial correlation an error may be introduced if the choice of patch density is not fine enough to represent the more continuous spatial correlation function throughout the intended frequency range of interest. Both qualitative and quantitative illustrations evaluating the adequacy of different patch density assumptions to approximate the fitted spatial correlation function are provided. The actual response of a typical vehicle panel system is then evaluated in a convergence study where the patch density assumptions are varied over the same finite element model. The convergence study results are presented illustrating the impact resulting from a poor choice of patch density. The fitted correlation function used in this study represents a Diffuse Acoustic Field (DAF) excitation of the panel to produce vibration response.

Mechanistic simulation of normal-tissue damage in radiotherapy—implications for dose-volume analyses

NASA Astrophysics Data System (ADS)

Rutkowska, Eva; Baker, Colin; Nahum, Alan

2010-04-01

A radiobiologically based 3D model of normal tissue has been developed in which complications are generated when 'irradiated'. The aim is to provide insight into the connection between dose-distribution characteristics, different organ architectures and complication rates beyond that obtainable with simple DVH-based analytical NTCP models. In this model the organ consists of a large number of functional subunits (FSUs), populated by stem cells which are killed according to the LQ model. A complication is triggered if the density of FSUs in any 'critical functioning volume' (CFV) falls below some threshold. The (fractional) CFV determines the organ architecture and can be varied continuously from small (series-like behaviour) to large (parallel-like). A key feature of the model is its ability to account for the spatial dependence of dose distributions. Simulations were carried out to investigate correlations between dose-volume parameters and the incidence of 'complications' using different pseudo-clinical dose distributions. Correlations between dose-volume parameters and outcome depended on characteristics of the dose distributions and on organ architecture. As anticipated, the mean dose and V20 correlated most strongly with outcome for a parallel organ, and the maximum dose for a serial organ. Interestingly better correlation was obtained between the 3D computer model and the LKB model with dose distributions typical for serial organs than with those typical for parallel organs. This work links the results of dose-volume analyses to dataset characteristics typical for serial and parallel organs and it may help investigators interpret the results from clinical studies.

Free-Suspension Residual Flexibility Testing of Space Station Pathfinder: Comparison to Fixed-Base Results

NASA Technical Reports Server (NTRS)

Tinker, Michael L.

1998-01-01

Application of the free-suspension residual flexibility modal test method to the International Space Station Pathfinder structure is described. The Pathfinder, a large structure of the general size and weight of Space Station module elements, was also tested in a large fixed-base fixture to simulate Shuttle Orbiter payload constraints. After correlation of the Pathfinder finite element model to residual flexibility test data, the model was coupled to a fixture model, and constrained modes and frequencies were compared to fixed-base test. modes. The residual flexibility model compared very favorably to results of the fixed-base test. This is the first known direct comparison of free-suspension residual flexibility and fixed-base test results for a large structure. The model correlation approach used by the author for residual flexibility data is presented. Frequency response functions (FRF) for the regions of the structure that interface with the environment (a test fixture or another structure) are shown to be the primary tools for model correlation that distinguish or characterize the residual flexibility approach. A number of critical issues related to use of the structure interface FRF for correlating the model are then identified and discussed, including (1) the requirement of prominent stiffness lines, (2) overcoming problems with measurement noise which makes the antiresonances or minima in the functions difficult to identify, and (3) the use of interface stiffness and lumped mass perturbations to bring the analytical responses into agreement with test data. It is shown that good comparison of analytical-to-experimental FRF is the key to obtaining good agreement of the residual flexibility values.

Anti-correlated Networks, Global Signal Regression, and the Effects of Caffeine in Resting-State Functional MRI

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T.

2012-01-01

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. PMID:22743194

Full waveform inversion using envelope-based global correlation norm

NASA Astrophysics Data System (ADS)

Oh, Ju-Won; Alkhalifah, Tariq

2018-05-01

To increase the feasibility of full waveform inversion on real data, we suggest a new objective function, which is defined as the global correlation of the envelopes of modelled and observed data. The envelope-based global correlation norm has the advantage of the envelope inversion that generates artificial low-frequency information, which provides the possibility to recover long-wavelength structure in an early stage. In addition, the envelope-based global correlation norm maintains the advantage of the global correlation norm, which reduces the sensitivity of the misfit to amplitude errors so that the performance of inversion on real data can be enhanced when the exact source wavelet is not available and more complex physics are ignored. Through the synthetic example for 2-D SEG/EAGE overthrust model with inaccurate source wavelet, we compare the performance of four different approaches, which are the least-squares waveform inversion, least-squares envelope inversion, global correlation norm and envelope-based global correlation norm. Finally, we apply the envelope-based global correlation norm on the 3-D Ocean Bottom Cable (OBC) data from the North Sea. The envelope-based global correlation norm captures the strong reflections from the high-velocity caprock and generates artificial low-frequency reflection energy that helps us recover long-wavelength structure of the model domain in the early stages. From this long-wavelength model, the conventional global correlation norm is sequentially applied to invert for higher-resolution features of the model.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

PubMed

Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel

2011-01-01

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

Large-angle correlations in the cosmic microwave background

NASA Astrophysics Data System (ADS)

Efstathiou, George; Ma, Yin-Zhe; Hanson, Duncan

2010-10-01

It has been argued recently by Copi et al. 2009 that the lack of large angular correlations of the CMB temperature field provides strong evidence against the standard, statistically isotropic, inflationary Lambda cold dark matter (ΛCDM) cosmology. We compare various estimators of the temperature correlation function showing how they depend on assumptions of statistical isotropy and how they perform on the Wilkinson Microwave Anisotropy Probe (WMAP) 5-yr Internal Linear Combination (ILC) maps with and without a sky cut. We show that the low multipole harmonics that determine the large-scale features of the temperature correlation function can be reconstructed accurately from the data that lie outside the sky cuts. The reconstructions are only weakly dependent on the assumed statistical properties of the temperature field. The temperature correlation functions computed from these reconstructions are in good agreement with those computed from the ILC map over the whole sky. We conclude that the large-scale angular correlation function for our realization of the sky is well determined. A Bayesian analysis of the large-scale correlations is presented, which shows that the data cannot exclude the standard ΛCDM model. We discuss the differences between our results and those of Copi et al. Either there exists a violation of statistical isotropy as claimed by Copi et al., or these authors have overestimated the significance of the discrepancy because of a posteriori choices of estimator, statistic and sky cut.

An estimate for the thermal photon rate from lattice QCD

NASA Astrophysics Data System (ADS)

Brandt, Bastian B.; Francis, Anthony; Harris, Tim; Meyer, Harvey B.; Steinberg, Aman

2018-03-01

We estimate the production rate of photons by the quark-gluon plasma in lattice QCD. We propose a new correlation function which provides better control over the systematic uncertainty in estimating the photon production rate at photon momenta in the range πT/2 to 2πT. The relevant Euclidean vector current correlation functions are computed with Nf = 2 Wilson clover fermions in the chirally-symmetric phase. In order to estimate the photon rate, an ill-posed problem for the vector-channel spectral function must be regularized. We use both a direct model for the spectral function and a modelindependent estimate from the Backus-Gilbert method to give an estimate for the photon rate.

Total Scattering Analysis of Disordered Nanosheet Materials

NASA Astrophysics Data System (ADS)

Metz, Peter C.

Two dimensional materials are of increasing interest as building blocks for functional coatings, catalysts, and electrochemical devices. While increasingly sophisticated processing routes have been designed to obtain high-quality exfoliated nanosheets and controlled, self-assembled mesostructures, structural characterization of these materials remains challenging. This work presents a novel method of analyzing pair distribution function (PDF) data for disordered nanosheet ensembles, where supercell stacking models are used to infer atom correlations over as much as 50 A. Hierarchical models are used to reduce the parameter space of the refined model and help eliminate strongly correlated parameters. Three data sets for restacked nanosheet assemblies with stacking disorder are analyzed using these methods: simulated data for graphene-like layers, experimental data for 1 nm thick perovskite layers, and experimental data for highly defective delta-MnO2 layers. In each case, the sensitivity of the PDF to the real-space distribution of layer positions is demonstrated by exploring the fit residual as a function of stacking vectors. The refined models demonstrate that nanosheets tend towards local interlayer ordering, which is hypothesized to be driven by the electrostatic potential of the layer surfaces. Correctly accounting for interlayer atom correlations permits more accurate refinement of local structural details including local structure perturbations and defect site occupancies. In the delta-MnO2 nanosheet material, the new modeling approach identified 14% Mn vacancies while application of 3D periodic crystalline models to the < 7 A PDF region suggests a 25% vacancy concentration. In contrast, the perovskite nanosheet material is demonstrated to exhibit almost negligible structural relaxation in contrast with the bulk crystalline material from which it is derived.

A Solution Space for a System of Null-State Partial Differential Equations: Part 1

NASA Astrophysics Data System (ADS)

Flores, Steven M.; Kleban, Peter

2015-01-01

This article is the first of four that completely and rigorously characterize a solution space for a homogeneous system of 2 N + 3 linear partial differential equations (PDEs) in 2 N variables that arises in conformal field theory (CFT) and multiple Schramm-Löwner evolution (SLE). In CFT, these are null-state equations and conformal Ward identities. They govern partition functions for the continuum limit of a statistical cluster or loop-gas model, such as percolation, or more generally the Potts models and O( n) models, at the statistical mechanical critical point. (SLE partition functions also satisfy these equations.) For such a lattice model in a polygon with its 2 N sides exhibiting a free/fixed side-alternating boundary condition , this partition function is proportional to the CFT correlation function where the w i are the vertices of and where is a one-leg corner operator. (Partition functions for "crossing events" in which clusters join the fixed sides of in some specified connectivity are linear combinations of such correlation functions.) When conformally mapped onto the upper half-plane, methods of CFT show that this correlation function satisfies the system of PDEs that we consider. In this first article, we use methods of analysis to prove that the dimension of this solution space is no more than C N , the Nth Catalan number. While our motivations are based in CFT, our proofs are completely rigorous. This proof is contained entirely within this article, except for the proof of Lemma 14, which constitutes the second article (Flores and Kleban, in Commun Math Phys, arXiv:1404.0035, 2014). In the third article (Flores and Kleban, in Commun Math Phys, arXiv:1303.7182, 2013), we use the results of this article to prove that the solution space of this system of PDEs has dimension C N and is spanned by solutions constructed with the CFT Coulomb gas (contour integral) formalism. In the fourth article (Flores and Kleban, in Commun Math Phys, arXiv:1405.2747, 2014), we prove further CFT-related properties about these solutions, some useful for calculating cluster-crossing probabilities of critical lattice models in polygons.

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Determinants of Objectively Measured Physical Functional Performance in Early to Mid-stage Parkinson Disease

PubMed Central

Kluger, Benzi M.; Brown, R. Preston; Aerts, Shanae; Schenkman, Margaret

2014-01-01

Background Parkinson disease (PD) may lead to functional limitations through both motor and non-motor symptoms. While patients with advanced disease have well-documented and profound functional limitations, less is known about the determinants of function in early to mid-stage disease where interventions may be more likely to benefit and preserve function. Objective The objective of the current study was to identify motor, cognitive and gait determinants of physical functional performance in patients with early to mid-stage PD. Design Secondary analysis of cross-sectional baseline data from a randomized clinical trial of exercise. Setting Tertiary academic medical center. Participants 121 patients with early to mid-stage PD. Methods Our functional performance outcomes included: 1) the Continuous Scale Functional Performance Test (CS-PFP; primary outcome); 2) the timed up and go (TUG) tests; and Section 2 (Activities of Daily Living) of the Unified Parkinson's Disease Rating Scale (UPDRS). Explanatory variables included measures of disease severity, motor function, cognitive function, balance and gait. Step-wise linear regression models were used to determine correlations between explanatory variables and outcome measures. Results In our regression models the CS-PFP significantly correlated with walking endurance (six minute walk; r2 = 0.12, p < .0001), turning ability (360 degree turn; r2 = .03, p = .002), attention (brief test of attention; r2 = .01, p = .03), overall cognitive status (Mini-mental State Examination; r2 = .01, p = .04) and bradykinesia (timed tapping; r2 = .02, p = .02). The TUG significantly correlated with walking speed (5 meter walk; r2 = 0.33, p <.0001), stride length (r2 = 0.25, p <.0001), turning ability (360 turn r2 = .05, p = .0003) and attention (r2 = .016, p = .03). Section 2 of the UPDRS was significantly correlated with endurance (r2 = .09, p < .0001), turning ability (r2 = .03, p = .001) and attention (r2 = .01, p = .03). Conclusions Gait, motor and cognitive function all contribute to objectively measured global functional ability in mild to moderate PD. Subjectively measured functional activity outcomes may underestimate the impact of both motor and non-motor symptoms. PMID:24880056

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

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

Ferson, Scott; Nelsen, Roger B.; Hajagos, Janos

2015-05-01

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Ground-state properties of rare-earth metals: an evaluation of density-functional theory.

PubMed

Söderlind, Per; Turchi, P E A; Landa, A; Lordi, V

2014-10-15

The rare-earth metals have important technological applications due to their magnetic properties, but are scarce and expensive. Development of high-performance magnetic materials with less rare-earth content is desired, but theoretical modeling is hampered by complexities of the rare earths electronic structure. The existence of correlated (atomic-like) 4f electrons in the vicinity of the valence band makes any first-principles theory challenging. Here, we apply and evaluate the efficacy of density-functional theory for the series of lanthanides (rare earths), investigating the influence of the electron exchange and correlation functional, spin-orbit interaction, and orbital polarization. As a reference, the results are compared with those of the so-called 'standard model' of the lanthanides in which electrons are constrained to occupy 4f core states with no hybridization with the valence electrons. Some comparisons are also made with models designed for strong electron correlations. Our results suggest that spin-orbit coupling and orbital polarization are important, particularly for the magnitude of the magnetic moments, and that calculated equilibrium volumes, bulk moduli, and magnetic moments show correct trends overall. However, the precision of the calculated properties is not at the level of that found for simpler metals in the Periodic Table of Elements, and the electronic structures do not accurately reproduce x-ray photoemission spectra.

Quantum mechanics and the psyche

NASA Astrophysics Data System (ADS)

Galli Carminati, G.; Martin, F.

2008-07-01

In this paper we apply the last developments of the theory of measurement in quantum mechanics to the phenomenon of consciousness and especially to the awareness of unconscious components. Various models of measurement in quantum mechanics can be distinguished by the fact that there is, or there is not, a collapse of the wave function. The passive aspect of consciousness seems to agree better with models in which there is no collapse of the wave function, whereas in the active aspect of consciousness—i.e., that which goes together with an act or a choice—there seems to be a collapse of the wave function. As an example of the second possibility we study in detail the photon delayed-choice experiment and its consequences for subjective or psychological time. We apply this as an attempt to explain synchronicity phenomena. As a model of application of the awareness of unconscious components we study the mourning process. We apply also the quantum paradigm to the phenomenon of correlation at a distance between minds, as well as to group correlations that appear during group therapies or group training. Quantum entanglement leads to the formation of group unconscious or collective unconscious. Finally we propose to test the existence of such correlations during sessions of group training.

The three-point function as a probe of models for large-scale structure

NASA Astrophysics Data System (ADS)

Frieman, Joshua A.; Gaztanaga, Enrique

1994-04-01

We analyze the consequences of models of structure formation for higher order (n-point) galaxy correlation functions in the mildly nonlinear regime. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations have recently been introduced to obtain more power on large scales, Rp is approximately 20/h Mpc, e.g., low matter-density (nonzero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower et al. We show that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale dependence leads to a dramatic decrease of the the hierarchical amplitudes QJ at large scales, r is greater than or approximately Rp. Current observational constraints on the three-point amplitudes Q3 and S3 can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

Determining accurate measurements of the growth rate from the galaxy correlation function in simulations

NASA Astrophysics Data System (ADS)

Contreras, Carlos; Blake, Chris; Poole, Gregory B.; Marin, Felipe

2013-04-01

We use high-resolution N-body simulations to develop a new, flexible empirical approach for measuring the growth rate from redshift-space distortions in the 2-point galaxy correlation function. We quantify the systematic error in measuring the growth rate in a 1 h-3 Gpc3 volume over a range of redshifts, from the dark matter particle distribution and a range of halo-mass catalogues with a number density comparable to the latest large-volume galaxy surveys such as the WiggleZ Dark Energy Survey and the Baryon Oscillation Spectroscopic Survey. Our simulations allow us to span halo masses with bias factors ranging from unity (probed by emission-line galaxies) to more massive haloes hosting luminous red galaxies. We show that the measured growth rate is sensitive to the model adopted for the small-scale real-space correlation function, and in particular that the `standard' assumption of a power-law correlation function can result in a significant systematic error in the growth-rate determination. We introduce a new, empirical fitting function that produces results with a lower (5-10 per cent) amplitude of systematic error. We also introduce a new technique which permits the galaxy pairwise velocity distribution, the quantity which drives the non-linear growth of structure, to be measured as a non-parametric stepwise function. Our (model-independent) results agree well with an exponential pairwise velocity distribution, expected from theoretical considerations, and are consistent with direct measurements of halo velocity differences from the parent catalogues. In a companion paper, we present the application of our new methodology to the WiggleZ Survey data set.

Evaluating the use of electronegativity in band alignment models through the experimental slope parameter of lanthanum aluminate heterostructures

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

Liu, Z. Q.; Chim, W. K.; Chiam, S. Y

2011-11-01

In this work, photoelectron spectroscopy is used to characterize the band alignment of lanthanum aluminate heterostructures which possess a wide range of potential applications. It is found that our experimental slope parameter agrees with theory using the metal-induced gap states model while the interface induced gap states (IFIGS) model yields unsatisfactory results. We show that this discrepancy can be attributed to the correlation between the dielectric work function and the electronegativity in the IFIGS model. It is found that the original trend, as established largely by metals, may not be accurate for larger band gap materials. By using a newmore » correlation, our experimental data shows good agreement of the slope parameter using the IFIGS model. This correlation, therefore, plays a crucial role in heterostructures involving wider bandgap materials for accurate band alignment prediction using the IFIGS model.« less

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

PubMed

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

2002-05-01

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

Radii of neutron drops probed via the neutron skin thickness of nuclei

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

Zhao, P. W.; Gandolfi, S.

Multineutron systems are crucial to understanding the physics of neutron-rich nuclei and neutron stars. Neutron drops, neutrons confined in an external field, are investigated systematically in both nonrelativistic and relativistic density functional theories and with ab initio calculations. Here, we demonstrate a new strong linear correlation, which is universal in the realm of mean-field models, between the rms radii of neutron drops and the neutron skin thickness of 208 Pb and 48 Ca , i.e., the difference between the neutron and proton rms radii of a nucleus. This correlation can be used to deduce the radii of neutron drops frommore » the measured neutron skin thickness in a model-independent way, and the radii obtained for neutron drops can provide a useful constraint for realistic three-neutron forces, due to its high quality. Furthermore, we present a new correlation between the slope L of the symmetry energy and the radii of neutron drops, and provide the first validation of such a correlation by using density-functional models and ab initio calculations. These newly established correlations, together with more precise measurements of the neutron skin thicknesses of 208 Pb and 48 Ca and/or accurate determinations of L , will have an enduring impact on the understanding of multineutron interactions, neutron-rich nuclei, neutron stars, etc.« less

Radii of neutron drops probed via the neutron skin thickness of nuclei

DOE PAGES

Zhao, P. W.; Gandolfi, S.

2016-10-10

Multineutron systems are crucial to understanding the physics of neutron-rich nuclei and neutron stars. Neutron drops, neutrons confined in an external field, are investigated systematically in both nonrelativistic and relativistic density functional theories and with ab initio calculations. Here, we demonstrate a new strong linear correlation, which is universal in the realm of mean-field models, between the rms radii of neutron drops and the neutron skin thickness of 208 Pb and 48 Ca , i.e., the difference between the neutron and proton rms radii of a nucleus. This correlation can be used to deduce the radii of neutron drops frommore » the measured neutron skin thickness in a model-independent way, and the radii obtained for neutron drops can provide a useful constraint for realistic three-neutron forces, due to its high quality. Furthermore, we present a new correlation between the slope L of the symmetry energy and the radii of neutron drops, and provide the first validation of such a correlation by using density-functional models and ab initio calculations. These newly established correlations, together with more precise measurements of the neutron skin thicknesses of 208 Pb and 48 Ca and/or accurate determinations of L , will have an enduring impact on the understanding of multineutron interactions, neutron-rich nuclei, neutron stars, etc.« less

Noise correlations in cosmic microwave background experiments

NASA Technical Reports Server (NTRS)

Dodelson, Scott; Kosowsky, Arthur; Myers, Steven T.

1995-01-01

Many analysis of microwave background experiments neglect the correlation of noise in different frequency of polarization channels. We show that these correlations, should they be present, can lead to serve misinterpretation of an experiment. In particular, correlated noise arising from either electronics or atmosphere may mimic a cosmic signal. We quantify how the likelihood function for a given experiment varies with noise correlation, using both simple analytic models and actual data. For a typical microwave background anisotropy experiment, noise correlations at the level of 1% of the overall noise can seriously reduce the significance of a given detection.

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Anesthesia modifies subthreshold critical slowing down in a stochastic Hodgkin-Huxley-like model with inhibitory synaptic input

NASA Astrophysics Data System (ADS)

Bukoski, Alex; Steyn-Ross, D. A.; Pickett, Ashley F.; Steyn-Ross, Moira L.

2018-06-01

The dynamics of a stochastic type-I Hodgkin-Huxley-like point neuron model exposed to inhibitory synaptic noise are investigated as a function of distance from spiking threshold and the inhibitory influence of the general anesthetic agent propofol. The model is biologically motivated and includes the effects of intrinsic ion-channel noise via a stochastic differential equation description as well as inhibitory synaptic noise modeled as multiple Poisson-distributed impulse trains with saturating response functions. The effect of propofol on these synapses is incorporated through this drug's principal influence on fast inhibitory neurotransmission mediated by γ -aminobutyric acid (GABA) type-A receptors via reduction of the synaptic response decay rate. As the neuron model approaches spiking threshold from below, we track membrane voltage fluctuation statistics of numerically simulated stochastic trajectories. We find that for a given distance from spiking threshold, increasing the magnitude of anesthetic-induced inhibition is associated with augmented signatures of critical slowing: fluctuation amplitudes and correlation times grow as spectral power is increasingly focused at 0 Hz. Furthermore, as a function of distance from threshold, anesthesia significantly modifies the power-law exponents for variance and correlation time divergences observable in stochastic trajectories. Compared to the inverse square root power-law scaling of these quantities anticipated for the saddle-node bifurcation of type-I neurons in the absence of anesthesia, increasing anesthetic-induced inhibition results in an observable exponent <-0.5 for variance and >-0.5 for correlation time divergences. However, these behaviors eventually break down as distance from threshold goes to zero with both the variance and correlation time converging to common values independent of anesthesia. Compared to the case of no synaptic input, linearization of an approximating multivariate Ornstein-Uhlenbeck model reveals these effects to be the consequence of an additional slow eigenvalue associated with synaptic activity that competes with those of the underlying point neuron in a manner that depends on distance from spiking threshold.

Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks

PubMed Central

Lyamzin, Dmitry R.; Barnes, Samuel J.; Donato, Roberta; Garcia-Lazaro, Jose A.; Keck, Tara

2015-01-01

Signal and noise correlations, a prominent feature of cortical activity, reflect the structure and function of networks during sensory processing. However, in addition to reflecting network properties, correlations are also shaped by intrinsic neuronal mechanisms. Here we show that spike threshold transforms correlations by creating nonlinear interactions between signal and noise inputs; even when input noise correlation is constant, spiking noise correlation varies with both the strength and correlation of signal inputs. We characterize these effects systematically in vitro in mice and demonstrate their impact on sensory processing in vivo in gerbils. We also find that the effects of nonlinear correlation transfer on cortical responses are stronger in the synchronized state than in the desynchronized state, and show that they can be reproduced and understood in a model with a simple threshold nonlinearity. Since these effects arise from an intrinsic neuronal property, they are likely to be present across sensory systems and, thus, our results are a critical step toward a general understanding of how correlated spiking relates to the structure and function of cortical networks. PMID:26019325

Synthesizing trait correlations and functional relationships across multiple scales: A Hierarchical Bayes approach

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Cowdery, E.; Dietze, M.

2016-12-01

Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

An infinite set of Ward identities for adiabatic modes in cosmology

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

Hinterbichler, Kurt; Hui, Lam; Khoury, Justin, E-mail: khinterbichler@perimeterinstitute.ca, E-mail: lh399@columbia.edu, E-mail: jkhoury@sas.upenn.edu

2014-01-01

We show that the correlation functions of any single-field cosmological model with constant growing-modes are constrained by an infinite number of novel consistency relations, which relate N+1-point correlation functions with a soft-momentum scalar or tensor mode to a symmetry transformation on N-point correlation functions of hard-momentum modes. We derive these consistency relations from Ward identities for an infinite tower of non-linearly realized global symmetries governing scalar and tensor perturbations. These symmetries can be labeled by an integer n. At each order n, the consistency relations constrain — completely for n = 0,1, and partially for n ≥ 2 — themore » q{sup n} behavior of the soft limits. The identities at n = 0 recover Maldacena's original consistency relations for a soft scalar and tensor mode, n = 1 gives the recently-discovered conformal consistency relations, and the identities for n ≥ 2 are new. As a check, we verify directly that the n = 2 identity is satisfied by known correlation functions in slow-roll inflation.« less

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

PubMed

Neipert, Christine; Space, Brian

2006-12-14

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

Signals of dynamical and statistical process from IMF-IMF correlation function

NASA Astrophysics Data System (ADS)

Pagano, E. V.; Acosta, L.; Auditore, L.; Baran, V.; Cap, T.; Cardella, G.; Colonna, M.; De Luca, S.; De Filippo, E.; Dell'Aquila, D.; Francalanza, L.; Gnoffo, B.; Lanzalone, G.; Lombardo, I.; Maiolino, C.; Martorana, N. S.; Norella, S.; Pagano, A.; Papa, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Porto, F.; Quattrocchi, L.; Rizzo, F.; Rosato, E.; Russotto, P.; Siwek-Wilczyńska, K.; Trifiro, A.; Trimarchi, M.; Verde, G.; Vigilante, M.; Wilczyńsky, J.

2017-11-01

In this paper we briefly discuss about a novel application of the IMF-IMF correlation function to the physical case of binary massive projectile-like (PLF) splitting for dynamical and statistical breakup/fission in heavy ion collisions at Fermi energy. Theoretical simulations are also shown for comparisons with the data. These preliminary results have been obtained for the reverse kinematics reaction 124Sn + 64Ni at 35 AMeV that was studied using the forward part of CHIMERA detector. In that reaction a strong competition between a dynamical and a statistical components and its evolution with the charge asymmetry of the binary break up was already shown. In this work we show that the IMF-IMF correlation function can be used to pin down the timescale of the fragments production in binary fission-like phenomena. We also made simulations with the CoMDII model in order to compare to the experimental IMF-IMF correlation function. In future we plan to extend these studies to different reaction mechanisms and nuclear systems and to compare with different theoretical transport simulations.

Theoretical analysis of oscillatory terms in lattice heat-current time correlation functions and their contributions to thermal conductivity

NASA Astrophysics Data System (ADS)

Pereverzev, Andrey; Sewell, Tommy

2018-03-01

Lattice heat-current time correlation functions for insulators and semiconductors obtained using molecular dynamics (MD) simulations exhibit features of both pure exponential decay and oscillatory-exponential decay. For some materials the oscillatory terms contribute significantly to the lattice heat conductivity calculated from the correlation functions. However, the origin of the oscillatory terms is not well understood, and their contribution to the heat conductivity is accounted for by fitting them to empirical functions. Here, a translationally invariant expression for the heat current in terms of creation and annihilation operators is derived. By using this full phonon-picture definition of the heat current and applying the relaxation-time approximation we explain, at least in part, the origin of the oscillatory terms in the lattice heat-current correlation function. We discuss the relationship between the crystal Hamiltonian and the magnitude of the oscillatory terms. A solvable one-dimensional model is used to illustrate the potential importance of terms that are omitted in the commonly used phonon-picture expression for the heat current. While the derivations are fully quantum mechanical, classical-limit expressions are provided that enable direct contact with classical quantities obtainable from MD.

Modelling thermal radiation from one-meter diameter methane pool fires

NASA Astrophysics Data System (ADS)

Consalvi, J. L.; Demarco, R.

2012-06-01

The first objective of this article is to implement a comprehensive radiation model in order to predict the radiant fractions and radiative fluxes on remote surfaces in large-scale methane pool fires. The second aim is to quantify the importance of Turbulence-Radiation Interactions (TRIs) in such buoyant flames. The fire-induced flow is modelled by using a buoyancy-modified k-ɛ model and the Steady Laminar Flamelet (SLF) model coupled with a presumed probability density function (pdf) approach. Spectral radiation is modelled by using the Full-Spectrum Correlated-k (FSCK) method. TRIs are taken into account by considering the Optically-Thin Fluctuation Approximation (OTFA). The emission term and the mean absorption coefficient are closed by using a presumed pdf of the mixture fraction, scalar dissipation rate and enthalpy defect. Two 1m-diameter fires with Heat Release Rates (HRR) of 49 kW and 162 kW were simulated. Predicted radiant fractions and radiative heat fluxes are found in reasonable agreement with experimental data. The importance of TRIs is evidenced, computed radiant fractions and radiative heat fluxes being considerably higher than those obtained from calculations based on mean properties. Finally, model results show that the complete absorption coefficient-Planck function correlation should be considered in order to properly take into account the influence of TRIs on the emission term, whereas the absorption coefficient self-correlation in the absorption term reduces significantly the radiant fractions.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

PubMed

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

NASA Astrophysics Data System (ADS)

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

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.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

A battery of tests for assessing cognitive function in U.S. Chinese older adults--findings from the PINE Study.

PubMed

Chang, E-Shien; Dong, XinQi

2014-11-01

Existing methodological challenges in aging research has dampened our assessment of cognitive function among minority older adults. We aim to report the composite scores of five cognitive function tests among U.S. Chinese older adults, and examine the association between cognitive function and key sociodemographic characteristics. The Population Study of Chinese Elderly in Chicago Study enrolled an epidemiological cohort of 3,159 community-dwelling Chinese older adults. We administered five cognitive function tests, including the Chinese Mini-Mental State Examination, the immediate and delayed recall of the East Boston Memory Test, the Digit Span Backwards assessment, and the Symbol Digit Modalities Test. We used Spearman correlation coefficients to examine the correlation between cognitive function and sociodemographic variables. Linear regression models were used to report the effect of sociodemographic and health variables including age, sex, education on cognitive function. Our multivariate analysis suggested that performance in each domain of cognitive function was inversely associated with age and positively related to education. With respect to sex, after adjusted for age, education and all key variables presented in the model, being male was positively related to global cognitive score and working memory. Being married, having fewer children, having been in the United States for fewer years, having been in the community for fewer years, and better self-reported health were positively correlated with all cognitive function domains. This population-based study of U.S. Chinese older adults is among the first to examine a battery of five cognitive function tests, which in aggregate enables researchers to capture a wide range of cognitive performance. © 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.

Measurement of the correlation between flow harmonics of different order in lead-lead collisions at √s NN = 2.76 TeV with the ATLAS detector

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

Aad, G.

2015-09-14

Correlations between the elliptic or triangular flow coefficients v m (m=2 or 3) and other flow harmonics v n (n=2 to 5) are measured using √s NN=2.76 TeV Pb+Pb collision data collected in 2010 by the ATLAS experiment at the LHC, corresponding to an integrated luminosity of 7 μb -1. The v m-v n correlations are measured in midrapidity as a function of centrality, and, for events within the same centrality interval, as a function of event ellipticity or triangularity defined in a forward rapidity region. For events within the same centrality interval, v 3 is found to be anticorrelatedmore » with v 2 and this anticorrelation is consistent with similar anticorrelations between the corresponding eccentricities, ε 2 and ε 3. However, it is observed that v 4 increases strongly with v 2, and v 5 increases strongly with both v 2 and v 3. The trend and strength of the vm-vn correlations for n=4 and 5 are found to disagree with ε m-ε n correlations predicted by initial-geometry models. Instead, these correlations are found to be consistent with the combined effects of a linear contribution to vn and a nonlinear term that is a function of v 2 2 or of v 2v 3, as predicted by hydrodynamic models. A simple two-component fit is used to separate these two contributions. The extracted linear and nonlinear contributions to v 4 and v 5 are found to be consistent with previously measured event-plane correlations.« less

Clustering of galaxies in a hierarchical universe - I. Methods and results at z=0

NASA Astrophysics Data System (ADS)

Kauffmann, Guinevere; Colberg, Jorg M.; Diaferio, Antonaldo; White, Simon D. M.

1999-02-01

We introduce a new technique for following the formation and evolution of galaxies in cosmological N-body simulations. Dissipationless simulations are used to track the formation and merging of dark matter haloes as a function of redshift. Simple prescriptions, taken directly from semi-analytic models of galaxy formation, are adopted for gas cooling, star formation, supernova feedback and the merging of galaxies within the haloes. This scheme enables us to explore the clustering properties of galaxies, and to investigate how selection by luminosity, colour or type influences the results. In this paper we study the properties of the galaxy distribution at z=0. These include B- and K-band luminosity functions, two-point correlation functions, pairwise peculiar velocities, cluster mass-to-light ratios, B-V colours, and star formation rates. We focus on two variants of a cold dark matter (CDM) cosmology: a high-density (Omega =1) model with shape-parameter Gamma =0.21 (tau CDM), and a low-density model with Omega =0.3 and Lambda =0.7 (Lambda CDM). Both models are normalized to reproduce the I-band Tully-Fisher relation of Giovanelli et al. near a circular velocity of 220 km s^-1. Our results depend strongly both on this normalization and on the adopted prescriptions for star formation and feedback. Very different assumptions are required to obtain an acceptable model in the two cases. For tau CDM, efficient feedback is required to suppress the growth of galaxies, particularly in low-mass field haloes. Without it, there are too many galaxies and the correlation function exhibits a strong turnover on scales below 1 Mpc. For Lambda CDM, feedback must be weaker, otherwise too few L_* galaxies are produced and the correlation function is too steep. Although neither model is perfect, both come close to reproducing most of the data. Given the uncertainties in modelling some of the critical physical processes, we conclude that it is not yet possible to draw firm conclusions about the values of cosmological parameters from studies of this kind. Further observational work on global star formation and feedback effects is required to narrow the range of possibilities.

Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

NASA Astrophysics Data System (ADS)

Guo, Yongfeng; Shen, Yajun; Tan, Jianguo

2016-09-01

The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.

Wilson loops and chiral correlators on squashed spheres

NASA Astrophysics Data System (ADS)

Fucito, F.; Morales, J. F.; Poghossian, R.

2015-11-01

We study chiral deformations of N=2 and N=4 supersymmetric gauge theories obtained by turning on τ J tr Φ J interactions with Φ the N=2 superfield. Using localization, we compute the deformed gauge theory partition function Z(overrightarrow{τ}|q) and the expectation value of circular Wilson loops W on a squashed four-sphere. In the case of the deformed {N}=4 theory, exact formulas for Z and W are derived in terms of an underlying U( N) interacting matrix model replacing the free Gaussian model describing the {N}=4 theory. Using the AGT correspondence, the τ J -deformations are related to the insertions of commuting integrals of motion in the four-point CFT correlator and chiral correlators are expressed as τ-derivatives of the gauge theory partition function on a finite Ω-background. In the so called Nekrasov-Shatashvili limit, the entire ring of chiral relations is extracted from the ɛ-deformed Seiberg-Witten curve. As a byproduct of our analysis we show that SU(2) gauge theories on rational Ω-backgrounds are dual to CFT minimal models.

Foetal Ureaplasma parvum bacteraemia as a function of gestation-dependent complement insufficiency: Evidence from a sheep model of pregnancy.

PubMed

Kemp, Matthew W; Ahmed, Shatha; Beeton, Michael L; Payne, Matthew S; Saito, Masatoshi; Miura, Yuichiro; Usuda, Haruo; Kallapur, Suhas G; Kramer, Boris W; Stock, Sarah J; Jobe, Alan H; Newnham, John P; Spiller, Owen B

2017-01-01

Complement is a central defence against sepsis, and increasing complement insufficiency in neonates of greater prematurity may predispose to increased sepsis. Ureaplasma spp. are the most frequently cultured bacteria from preterm blood samples. A sheep model of intrauterine Ureaplasma parvum infection was used to examine in vivo Ureaplasma bacteraemia at early and late gestational ages. Complement function and Ureaplasma killing assays were used to determine the correlation between complement potency and bactericidal activity of sera ex vivo. Ureaplasma was cultured from 50% of 95-day gestation lamb cord blood samples compared to 10% of 125-day gestation lambs. Bactericidal activity increased with increased gestational age, and a direct correlation between functional complement activity and bactericidal activity (R 2 =.86; P<.001) was found for 95-day gestational lambs. Ureaplasma bacteraemia in vivo was confined to early preterm lambs with low complement function, but Ureaplasma infection itself did not diminish complement levels. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

Chowdhury, R.; Adhikari, S.

2012-10-01

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

Electron-mediated relaxation following ultrafast pumping of strongly correlated materials: model evidence of a correlation-tuned crossover between thermal and nonthermal states.

PubMed

Moritz, B; Kemper, A F; Sentef, M; Devereaux, T P; Freericks, J K

2013-08-16

We examine electron-electron mediated relaxation following ultrafast electric field pump excitation of the fermionic degrees of freedom in the Falicov-Kimball model for correlated electrons. The results reveal a dichotomy in the temporal evolution of the system as one tunes through the Mott metal-to-insulator transition: in the metallic regime relaxation can be characterized by evolution toward a steady state well described by Fermi-Dirac statistics with an increased effective temperature; however, in the insulating regime this quasithermal paradigm breaks down with relaxation toward a nonthermal state with a complicated electronic distribution as a function of momentum. We characterize the behavior by studying changes in the energy, photoemission response, and electronic distribution as functions of time. This relaxation may be observable qualitatively on short enough time scales that the electrons behave like an isolated system not in contact with additional degrees of freedom which would act as a thermal bath, especially when using strong driving fields and studying materials whose physics may manifest the effects of correlations.

Solar energy potential in the United Arab Emirates

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

Khalil, A.; Alnajjar, A.

1995-12-31

In the present study, the global, direct and diffuse components of solar radiation as well as temperature, relative humidity and wind speed have been continuously monitored and analyzed on hourly, daily and monthly basis. Experimental data is compared to the predictions of different theoretical models as functions of declination and hour angles. Correlations are obtained describing the variation of hourly, daily and monthly averages of total and diffuse solar radiation using polynomial expressions. Empirical correlations describing the dependence of the daily average diffuse to total radiation ratio on the clearness index are also obtained. Data of daily diffuse to totalmore » radiation ratio is compared to correlations obtained by other investigators. The comparison shows a reasonable agreement with some scatter due to the seasonal dependence of the correlation. Comparison of calculations with experimental measurements under clear sky conditions show excellent agreement with a maximum error of 8%. The measured ratio of hourly to daily insolation is in excellent agreement with the model of Hottel which is expressed as a function of the clearness index, hour and the sunset hour angles.« less

Edgeworth streaming model for redshift space distortions

NASA Astrophysics Data System (ADS)

Uhlemann, Cora; Kopp, Michael; Haugg, Thomas

2015-09-01

We derive the Edgeworth streaming model (ESM) for the redshift space correlation function starting from an arbitrary distribution function for biased tracers of dark matter by considering its two-point statistics and show that it reduces to the Gaussian streaming model (GSM) when neglecting non-Gaussianities. We test the accuracy of the GSM and ESM independent of perturbation theory using the Horizon Run 2 N -body halo catalog. While the monopole of the redshift space halo correlation function is well described by the GSM, higher multipoles improve upon including the leading order non-Gaussian correction in the ESM: the GSM quadrupole breaks down on scales below 30 Mpc /h whereas the ESM stays accurate to 2% within statistical errors down to 10 Mpc /h . To predict the scale-dependent functions entering the streaming model we employ convolution Lagrangian perturbation theory (CLPT) based on the dust model and local Lagrangian bias. Since dark matter halos carry an intrinsic length scale given by their Lagrangian radius, we extend CLPT to the coarse-grained dust model and consider two different smoothing approaches operating in Eulerian and Lagrangian space, respectively. The coarse graining in Eulerian space features modified fluid dynamics different from dust while the coarse graining in Lagrangian space is performed in the initial conditions with subsequent single-streaming dust dynamics, implemented by smoothing the initial power spectrum in the spirit of the truncated Zel'dovich approximation. Finally, we compare the predictions of the different coarse-grained models for the streaming model ingredients to N -body measurements and comment on the proper choice of both the tracer distribution function and the smoothing scale. Since the perturbative methods we considered are not yet accurate enough on small scales, the GSM is sufficient when applied to perturbation theory.

Adler function and hadronic contribution to the muon g-2 in a nonlocal chiral quark model

NASA Astrophysics Data System (ADS)

Dorokhov, Alexander E.

2004-11-01

The behavior of the vector Adler function at spacelike momenta is studied in the framework of a covariant chiral quark model with instantonlike quark-quark interaction. This function describes the transition between the high-energy asymptotically free region of almost massless current quarks to the low-energy hadronized regime with massive constituent quarks. The model reproduces the Adler function and V-A correlator extracted from the ALEPH and OPAL data on hadronic τ lepton decays, transformed into the Euclidean domain via dispersion relations. The leading order contribution from the hadronic part of the photon vacuum polarization to the anomalous magnetic moment of the muon, ahvp(1)μ, is estimated.

Psychosocial functioning, quality of life and clinical correlates of comorbid alcohol and drug dependence syndromes in people with schizophrenia across Europe.

PubMed

Carrà, Giuseppe; Johnson, Sonia; Crocamo, Cristina; Angermeyer, Matthias C; Brugha, Traolach; Azorin, Jean-Michel; Toumi, Mondher; Bebbington, Paul E

2016-05-30

Little is known about the correlates of comorbid drug and alcohol dependence in people with schizophrenia outside the USA. We tested hypotheses that dependence on alcohol/drugs would be associated with more severe symptoms, and poorer psychosocial functioning and quality of life. The EuroSC Cohort study (N=1204), based in France, Germany and the UK, used semi-structured clinical interviews for diagnoses, and standardized tools to assess correlates. We used mixed models to compare outcomes between past-year comorbid dependence on alcohol/drugs, controlling for covariates and modelling both subject and country-level effects. Participants dependent on alcohol or drugs had fewer negative symptoms on PANSS than their non-dependent counterparts. However, those dependent on alcohol scored higher on PANSS general psychopathology than those who were not, or dependent only on drugs. People with schizophrenia dependent on drugs had poorer quality of life, more extrapyramidal side effects, and scored worse on Global Assessment of Functioning (GAF) than those without dependence. People with alcohol dependence reported more reasons for non-compliance with medication, and poorer functioning on GAF, though not on Global Assessment of Relational Functioning. In people with schizophrenia, comorbid dependence on alcohol or drugs is associated with impaired clinical and psychosocial adjustment, and poorer quality of life. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Cross-correlation between EMG and center of gravity during quiet stance: theory and simulations.

PubMed

Kohn, André Fabio

2005-11-01

Several signal processing tools have been employed in the experimental study of the postural control system in humans. Among them, the cross-correlation function has been used to analyze the time relationship between signals such as the electromyogram and the horizontal projection of the center of gravity. The common finding is that the electromyogram precedes the biomechanical signal, a result that has been interpreted in different ways, for example, the existence of feedforward control or the preponderance of a velocity feedback. It is shown here, analytically and by simulation, that the cross-correlation function is dependent in a complicated way on system parameters and on noise spectra. Results similar to those found experimentally, e.g., electromyogram preceding the biomechanical signal may be obtained in a postural control model without any feedforward control and without any velocity feedback. Therefore, correct interpretations of experimentally obtained cross-correlation functions may require additional information about the system. The results extend to other biomedical applications where two signals from a closed loop system are cross-correlated.

Co-variation of tests commonly used in stroke rehabilitation.

PubMed

Langhammer, Birgitta; Stanghelle, Johan Kvalvik

2006-12-01

The aim of the present study was to analyse the co-variation of different tests commonly used in stroke rehabilitation, and specifically used in a recent randomized, controlled study of two different physiotherapy models in stroke rehabilitation. Correlations of the performed tests and recordings from previous work were studied. The test results from three-month, one-year and four-year follow-up were analysed in an SPSS Version 11 statistical package with Pearson and Spearman correlations. There was an expected high correlation between the motor function tests, both based on partial and total scores. The correlations between Nottingham Health Profile Part 1 and Motor Assessment Scale (MAS), Sødring Motor Evaluation Scale (SMES), the Berg Balance Scale (BBS) and Barthel Activities of Daily Living (ADL) index were low for all items except physical condition. The correlations between registered living conditions, assistive devices, recurrent stroke, motor function (MAS, SMES), ADL (Barthel ADL index) and balance (BBS) were high. The same variables showed weak or poor correlation to the Nottingham Health Profile (NHP). The co-variations of motor function tests and functional tests were high, but the co-variations of motor, functional and self-reported life-quality tests were poor. The patients rated themselves on a higher functional level in the self-reported tests than was observed objectively in the performance-based tests. A possible reason for this is that the patients may have been unaware they modified their performance to adjust for physical decline, and consequently overestimate their physical condition. This result underlines the importance of both performance-based and self-reported tests as complementary tools in a rehabilitation process.

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

Genomic Model with Correlation Between Additive and Dominance Effects.

PubMed

Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

2018-05-09

Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant deviations performed similarly for prediction. Copyright © 2018, Genetics.

Stochastic reconstructions of spectral functions: Application to lattice QCD

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

The standard mean-field treatment of inter-particle attraction in classical DFT is better than one might expect

NASA Astrophysics Data System (ADS)

Archer, Andrew J.; Chacko, Blesson; Evans, Robert

2017-07-01

In classical density functional theory (DFT), the part of the Helmholtz free energy functional arising from attractive inter-particle interactions is often treated in a mean-field or van der Waals approximation. On the face of it, this is a somewhat crude treatment as the resulting functional generates the simple random phase approximation (RPA) for the bulk fluid pair direct correlation function. We explain why using standard mean-field DFT to describe inhomogeneous fluid structure and thermodynamics is more accurate than one might expect based on this observation. By considering the pair correlation function g(x) and structure factor S(k) of a one-dimensional model fluid, for which exact results are available, we show that the mean-field DFT, employed within the test-particle procedure, yields results much superior to those from the RPA closure of the bulk Ornstein-Zernike equation. We argue that one should not judge the quality of a DFT based solely on the approximation it generates for the bulk pair direct correlation function.

Quantum Critical Point revisited by the Dynamical Mean Field Theory

NASA Astrophysics Data System (ADS)

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei

Dynamical mean field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low energy kink and the high energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high energy antiferromagnetic paramagnons. We use the frequency dependent four-point correlation function of spin operators to calculate the momentum dependent correction to the electron self energy. Our results reveal a substantial difference with the calculations based on the Spin-Fermion model which indicates that the frequency dependence of the the quasiparitcle-paramagnon vertices is an important factor. The authors are supported by Center for Computational Design of Functional Strongly Correlated Materials and Theoretical Spectroscopy under DOE Grant DE-FOA-0001276.

Phase transition in conjugated oligomers suspended in chloroform

NASA Astrophysics Data System (ADS)

Dwivedi, Shikha; Kumar, Anupam; Yadav, S. N. S.; Mishra, Pankaj

2015-08-01

Density functional theory (DFT) has been used to investigate the isotropic-nematic (I-N) phase transition in a system of high aspect ratio conjugated oligomers suspended in chloroform. The interaction between the oligomers is modeled using Gay-Berne potential in which effect of solvent is implicit. Percus-Yevick integral equation theory has been used to evaluate the pair correlation functions of the fluid phase at several temperatures and densities. These pair correlation function has been used in the DFT to evaluate the I-N freezing parameters. Highly oriented nematic is found to stabilize at low density. The results obtained are in qualitative agreement with the simulation and are verifiable.

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

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

Diaw, A.; Murillo, M. S.

2016-09-20

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

Depression and pain impair daily functioning and quality of life in patients with major depressive disorder.

PubMed

Lin, Ching-Hua; Yen, Yung-Chieh; Chen, Ming-Chao; Chen, Cheng-Chung

2014-09-01

Depression and pain frequently occur together. The objective of this study was to investigate the effects of depression and pain on the impairment of daily functioning and quality of life (QOL) of depressed patients. We enrolled 131 acutely ill inpatients with major depressive disorder. Depression, pain, and daily functioning were assessed using the 17-item Hamilton Depression Rating Scale, the Short-Form 36 (SF-36) Body Pain Index, and the Work and Social Adjustment Scale. Health-related QOL was assessed using three primary domains of the SF-36: social functioning, vitality, and general health perceptions. Pearson׳s correlation and structural equation modeling were used to examine relationships among the study variables. Five models were proposed. In all, 129 patients completed all the measures. Model 5, both depression and pain impaired daily functioning and QOL, was the most fitted structural equation model (χ(2)=9.2, df=8, p=0.33, GFI=0.98, AGFI=0.94, TLI=0.99, CFI=0.99, RMSEA=0.03). The correlation between pain and depression was weak (r=-0.27, z=-2.95, p=0.003). This was a cross-sectional study with a small sample size. Depression and pain exert a direct influence on the impairment of daily functioning and QOL of depressed patients; this impairment could be expected regardless of increased pain, depression, or both pain and depression. Pain had a somewhat separate entity from depression. Copyright © 2014. Published by Elsevier B.V.

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Treesearch

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Modeling the pressure-strain correlation of turbulence: An invariant dynamical systems approach

NASA Technical Reports Server (NTRS)

Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

1990-01-01

The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

Modelling the pressure-strain correlation of turbulence - An invariant dynamical systems approach

NASA Technical Reports Server (NTRS)

Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

1991-01-01

The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

Novel prediction model of renal function after nephrectomy from automated renal volumetry with preoperative multidetector computed tomography (MDCT).

PubMed

Isotani, Shuji; Shimoyama, Hirofumi; Yokota, Isao; Noma, Yasuhiro; Kitamura, Kousuke; China, Toshiyuki; Saito, Keisuke; Hisasue, Shin-ichi; Ide, Hisamitsu; Muto, Satoru; Yamaguchi, Raizo; Ukimura, Osamu; Gill, Inderbir S; Horie, Shigeo

2015-10-01

The predictive model of postoperative renal function may impact on planning nephrectomy. To develop the novel predictive model using combination of clinical indices with computer volumetry to measure the preserved renal cortex volume (RCV) using multidetector computed tomography (MDCT), and to prospectively validate performance of the model. Total 60 patients undergoing radical nephrectomy from 2011 to 2013 participated, including a development cohort of 39 patients and an external validation cohort of 21 patients. RCV was calculated by voxel count using software (Vincent, FUJIFILM). Renal function before and after radical nephrectomy was assessed via the estimated glomerular filtration rate (eGFR). Factors affecting postoperative eGFR were examined by regression analysis to develop the novel model for predicting postoperative eGFR with a backward elimination method. The predictive model was externally validated and the performance of the model was compared with that of the previously reported models. The postoperative eGFR value was associated with age, preoperative eGFR, preserved renal parenchymal volume (RPV), preserved RCV, % of RPV alteration, and % of RCV alteration (p < 0.01). The significant correlated variables for %eGFR alteration were %RCV preservation (r = 0.58, p < 0.01) and %RPV preservation (r = 0.54, p < 0.01). We developed our regression model as follows: postoperative eGFR = 57.87 - 0.55(age) - 15.01(body surface area) + 0.30(preoperative eGFR) + 52.92(%RCV preservation). Strong correlation was seen between postoperative eGFR and the calculated estimation model (r = 0.83; p < 0.001). The external validation cohort (n = 21) showed our model outperformed previously reported models. Combining MDCT renal volumetry and clinical indices might yield an important tool for predicting postoperative renal function.

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

PubMed

Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

PubMed Central

Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

Abstract In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline “DMN-like” network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans. PMID:23919836

Diffusivity anomaly in modified Stillinger-Weber liquids

NASA Astrophysics Data System (ADS)

Sengupta, Shiladitya; Vasisht, Vishwas V.; Sastry, Srikanth

2014-01-01

By modifying the tetrahedrality (the strength of the three body interactions) in the well-known Stillinger-Weber model for silicon, we study the diffusivity of a series of model liquids as a function of tetrahedrality and temperature at fixed pressure. Previous work has shown that at constant temperature, the diffusivity exhibits a maximum as a function of tetrahedrality, which we refer to as the diffusivity anomaly, in analogy with the well-known anomaly in water upon variation of pressure at constant temperature. We explore to what extent the structural and thermodynamic changes accompanying changes in the interaction potential can help rationalize the diffusivity anomaly, by employing the Rosenfeld relation between diffusivity and the excess entropy (over the ideal gas reference value), and the pair correlation entropy, which provides an approximation to the excess entropy in terms of the pair correlation function. We find that in the modified Stillinger-Weber liquids, the Rosenfeld relation works well above the melting temperatures but exhibits deviations below, with the deviations becoming smaller for smaller tetrahedrality. Further we find that both the excess entropy and the pair correlation entropy at constant temperature go through maxima as a function of the tetrahedrality, thus demonstrating the close relationship between structural, thermodynamic, and dynamical anomalies in the modified Stillinger-Weber liquids.

Dynamical correlation functions of the quadratic coupling spin-Boson model

NASA Astrophysics Data System (ADS)

Zheng, Da-Chuan; Tong, Ning-Hua

2017-06-01

The spin-boson model with quadratic coupling is studied using the bosonic numerical renormalization group method. We focus on the dynamical auto-correlation functions {C}O(ω ), with the operator \\hat{O} taken as {\\hat{{{σ }}}}x, {\\hat{{{σ }}}}z, and \\hat{X}, respectively. In the weak-coupling regime α < {α }{{c}}, these functions show power law ω-dependence in the small frequency limit, with the powers 1+2s, 1+2s, and s, respectively. At the critical point α ={α }{{c}} of the boson-unstable quantum phase transition, the critical exponents y O of these correlation functions are obtained as {y}{{{σ }}x}={y}{{{σ }}z}=1-2s and {y}X=-s, respectively. Here s is the bath index and X is the boson displacement operator. Close to the spin flip point, the high frequency peak of {C}{{{σ }}x}(ω ) is broadened significantly and the line shape changes qualitatively, showing enhanced dephasing at the spin flip point. Project supported by the National Key Basic Research Program of China (Grant No. 2012CB921704), the National Natural Science Foundation of China (Grant No. 11374362), the Fundamental Research Funds for the Central Universities, China, and the Research Funds of Renmin University of China (Grant No. 15XNLQ03).

Comparison of Regression Analysis and Transfer Function in Estimating the Parameters of Central Pulse Waves from Brachial Pulse Wave.

PubMed

Chai, Rui; Xu, Li-Sheng; Yao, Yang; Hao, Li-Ling; Qi, Lin

2017-01-01

This study analyzed ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad) and systolic area (As) diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO), and peripheral resistance (RS) of central pulse wave invasively and non-invasively measured. Invasively measured parameters were compared with parameters measured from brachial pulse waves by regression model and transfer function model. Accuracy of parameters estimated by regression and transfer function model, was compared too. Findings showed that k value, central pulse wave and brachial pulse wave parameters invasively measured, correlated positively. Regression model parameters including A_slope, DBP, SEVR, and transfer function model parameters had good consistency with parameters invasively measured. They had same effect of consistency. SBP, PP, SV, and CO could be calculated through the regression model, but their accuracies were worse than that of transfer function model.

Modeling of Momentum Correlations in Heavy Ion Collisions

NASA Astrophysics Data System (ADS)

Pruneau, Claude; Sharma, Monika

2010-02-01

Measurements of transverse momentum (pt) correlations and fluctuations in heavy ion collisions (HIC) are of interest because they provide information on the collision dynamics not readily available from number correlations. For instance, pt fluctuations are expected to diverge for a system near its tri-critical point [1]. Integral momentum correlations may also be used to estimate the shear viscosity of the quark gluon plasma produced in HIC [2]. Integral correlations measured over large fractions of the particle phase space average out several dynamical contributions and as such may be difficult to interpret. It is thus of interest to seek extensions of integral correlation variables that may provide more detailed information about the collision dynamics. We introduce a variety of differential momentum correlations and discuss their basic properties in the light of simple toy models. We also present theoretical predictions based on the PYTHIA, HIJING, AMPT, and EPOS models. Finally, we discuss the interplay of various dynamical effects that may play a role in the determination of the shear viscosity based on the broadening of momentum correlations measured as function of collision centrality. [1] L. Stodolsky, Phys. Rev. Lett. 75 (1995) 1044. [2] S. Gavin and M. A. Aziz, Phys. Rev. Lett. 97 (2006) 162302. )

Scalable properties of metal clusters: A comparative study of modern exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Koitz, Ralph; Soini, Thomas M.; Genest, Alexander; Trickey, S. B.; Rösch, Notker

2012-07-01

The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pdn with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Aun (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.

Mitigating the impact of the DESI fiber assignment on galaxy clustering

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

Burden, Angela; Padmanabhan, Nikhil; Cahn, Robert N.

2017-03-01

We present a simple strategy to mitigate the impact of an incomplete spectroscopic redshift galaxy sample as a result of fiber assignment and survey tiling. The method has been designed for the Dark Energy Spectroscopic Instrument (DESI) galaxy survey but may have applications beyond this. We propose a modification to the usual correlation function that nulls the almost purely angular modes affected by survey incompleteness due to fiber assignment. Predictions of this modified statistic can be calculated given a model of the two point correlation function. The new statistic can be computed with a slight modification to the data cataloguesmore » input to the standard correlation function code and does not incur any additional computational time. Finally we show that the spherically averaged baryon acoustic oscillation signal is not biased by the new statistic.« less

Functional selectivity of G-protein-coupled receptors: from recombinant systems to native human cells.

PubMed

Seifert, Roland

2013-10-01

In the mid 1990s, it was assumed that a two-state model, postulating an inactive (R) state and an active (R*) state provides the molecular basis for GPCR activation. However, it became clear that this model could not accommodate many experimental observations. Accordingly, the two-state model was superseded by a multi-state model according to which any given ligand stabilizes a unique receptor conformation with distinct capabilities of activating down-stream G-proteins and β-arrestin. Much of this research was conducted with the β2-adrenoceptor in recombinant systems. At the molecular level, there is now no doubt anymore that ligand-specific receptor conformations, also referred to as functional selectivity, exist. This concept holds great potential for drug discovery in terms of developing drugs with higher selectivity for specific cells and/or cell functions and fewer side effects. A major challenge is the analysis for functional selectivity in native cells. Here, I discuss our current knowledge on functional selectivity of three representative GPCRs, the β2-adrenoceptor and the histamine H2- and H4-receptors, in recombinant systems and native human cells. Studies with human neutrophils and eosinophils support the concept of functional selectivity. A major strategy for the analysis of functional selectivity in native cells is to generate complete concentration/response curves with a large set of structurally diverse ligands for multiple parameters. Next, correlations of potencies and efficacies are analyzed, and deviations of the correlations from linearity are indicative for functional selectivity. Additionally, pharmacological inhibitors are used to dissect cell functions from each other. Copyright © 2013 Elsevier Inc. All rights reserved.

Water adsorption on a copper formate paddlewheel model of CuBTC: A comparative MP2 and DFT study

NASA Astrophysics Data System (ADS)

Toda, Jordi; Fischer, Michael; Jorge, Miguel; Gomes, José R. B.

2013-11-01

Simultaneous adsorption of two water molecules on open metal sites of the HKUST-1 metal-organic framework (MOF), modeled with a Cu2(HCOO)4 cluster, was studied by means of density functional theory (DFT) and second-order Moller-Plesset (MP2) approaches together with correlation consistent basis sets. Experimental geometries and MP2 energetic data extrapolated to the complete basis set limit were used as benchmarks for testing the accuracy of several different exchange-correlation functionals in the correct description of the water-MOF interaction. M06-L and some LC-DFT methods arise as the most appropriate in terms of the quality of geometrical data, energetic data and computational resources needed.

A Bayes linear Bayes method for estimation of correlated event rates.

PubMed

Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim

2013-12-01

Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.

Are executive functions related to emotional intelligence? A correlational study in schizophrenia and borderline personality disorder.

PubMed

Hurtado, M M; Triviño, M; Arnedo, M; Roldán, G; Tudela, P

2016-12-30

This research explored the relationship between executive functions (working memory and reasoning subtests of the Wechsler Adult Intelligence Scale, Trail Making and Stroop tests, fluency and planning tasks, and Wisconsin Card Sorting Test) and emotional intelligence measured by the Mayer-Salovey-Caruso Emotional Intelligence Test in patients with schizophrenia or borderline personality disorder compared to a control group. As expected, both clinical groups performed worse than the control group in executive functions and emotional intelligence, although the impairment was greater in the borderline personality disorder group. Executive functions significantly correlated with social functioning. Results are discussed in relation to the brain circuits that mediate executive functions and emotional intelligence and the findings obtained with other models of social cognition. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

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

NASA Astrophysics Data System (ADS)

Karpishkov, Anton; Nefedov, Maxim; Saleev, Vladimir

2017-10-01

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

Asset surveillance system: apparatus and method

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor)

2007-01-01

System and method for providing surveillance of an asset comprised of numerically fitting at least one mathematical model to obtained residual data correlative to asset operation; storing at least one mathematical model in a memory; obtaining a current set of signal data from the asset; retrieving at least one mathematical model from the memory, using the retrieved mathematical model in a sequential hypothesis test for determining if the current set of signal data is indicative of a fault condition; determining an asset fault cause correlative to a determined indication of a fault condition; providing an indication correlative to a determined fault cause, and an action when warranted. The residual data can be mode partitioned, a current mode of operation can be determined from the asset, and at least one mathematical model can be retrieved from the memory as a function of the determined mode of operation.

Rasch Mixture Models for DIF Detection: A Comparison of Old and New Score Specifications

ERIC Educational Resources Information Center

Frick, Hannah; Strobl, Carolin; Zeileis, Achim

2015-01-01

Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly correlated with the manifest covariates available. Unlike in single Rasch models, estimation of Rasch…

Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model

ERIC Educational Resources Information Center

Jeon, Minjeong; Rijmen, Frank; Rabe-Hesketh, Sophia

2013-01-01

The authors present a generalization of the multiple-group bifactor model that extends the classical bifactor model for categorical outcomes by relaxing the typical assumption of independence of the specific dimensions. In addition to the means and variances of all dimensions, the correlations among the specific dimensions are allowed to differ…

Scattering from Colloid-Polymer Conjugates with Excluded Volume Effect

DOE PAGES

Li, Xin; Sanchez-Diaz, Luis E.; Smith, Gregory Scott; ...

2015-01-13

This work presents scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain as a model for protein-polymer conjugates and nanoparticle-polymer conjugates in solution. The model is directly derived from the two-point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shape of the colloid and polymer stiffness is investigated. The model is able to describe the experimental scattering signature of the solutions of suspending hard particle-polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugatemore » and the microstructure of its constituent components.« less

Structure-Function Correlations using Scanning Laser Polarimetry in Primary Angle-Closure Glaucoma and Primary Open Angle Glaucoma

PubMed Central

Lee, Pei-Jung; Liu, Catherine Jui-Ling.; Wojciechowski, Robert; Bailey-Wilson, Joan E.; Cheng, Ching-Yu

2010-01-01

Purpose To assess the correlations between retinal nerve fiber layer (RNFL) thickness measured with scanning laser polarimetry (SLP) and visual field (VF) sensitivity in primary open angle glaucoma (POAG) and primary angle-closure glaucoma (PACG). Design Prospective, comparative, observational cases series Methods Fifty patients with POAG and 56 with PACG were examined using SLP with variable corneal compensation (GDx VCC) and Humphrey VF analyzer between August 2005 and July 2006 at Taipei Veterans General Hospital. Correlations between RNFL thickness and VF sensitivity, expressed as mean sensitivity (MS) in both decibel (dB) and 1/Lambert (L) scales, were estimated by Spearman's rank correlation coefficient (rs) and multivariate median regression models (pseudo R2). The correlations were determined globally and for six RNFL sectors and their corresponding VF regions. Results The correlation between RNFL thickness and MS (in dB) was weaker in the PACG group (rs = 0.38, P = 0.004, pseudo R2 = 0.17) than in the POAG group (rs = 0.51, P <0.001, pseudo R2 = 0.31), but the difference in the magnitude of correlation was not significant (P = 0.42).With Bonferroni correction, the structure-function correlation was significant in the superotemporal (rs = 0.62), superonasal (rs = 0.56), inferonasal (rs = 0.53), and inferotemporal (rs = 0.50) sectors in the POAG group (all P <0.001), while it was significant only in the superotemporal (rs = 0.53) and inferotemporal (rs = 0.48) sectors in the PACG group (both P <0.001). The results were similar when MS was expressed as 1/L scale. Conclusions Both POAG and PACG eyes had moderate structure-function correlations using SLP. Compared to eyes with POAG, fewer RNFL sectors have significant structure-function correlations in eyes with PACG. PMID:20202618

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

Correlates of Susceptibility to Scams in Older Adults Without Dementia

PubMed Central

James, Bryan D.; Boyle, Patricia A.; Bennett, David A.

2013-01-01

This study examined correlates of susceptibility to scams in 639 community-dwelling older adults without dementia from a cohort study of aging. Regression models adjusted for age, sex, education, and income were used to examine associations between susceptibility to scams, measured by 5-item self-report measure, and a number of potential correlates. Susceptibility was positively associated with age and negatively associated with income, cognition, psychological well being, social support, and literacy. Fully adjusted models indicated that older age and lower levels of cognitive function, decreased psychological well-being, and lower literacy in particular may be markers of susceptibility to financial victimization in old age. PMID:24499279

Log-gamma linear-mixed effects models for multiple outcomes with application to a longitudinal glaucoma study

PubMed Central

Zhang, Peng; Luo, Dandan; Li, Pengfei; Sharpsten, Lucie; Medeiros, Felipe A.

2015-01-01

Glaucoma is a progressive disease due to damage in the optic nerve with associated functional losses. Although the relationship between structural and functional progression in glaucoma is well established, there is disagreement on how this association evolves over time. In addressing this issue, we propose a new class of non-Gaussian linear-mixed models to estimate the correlations among subject-specific effects in multivariate longitudinal studies with a skewed distribution of random effects, to be used in a study of glaucoma. This class provides an efficient estimation of subject-specific effects by modeling the skewed random effects through the log-gamma distribution. It also provides more reliable estimates of the correlations between the random effects. To validate the log-gamma assumption against the usual normality assumption of the random effects, we propose a lack-of-fit test using the profile likelihood function of the shape parameter. We apply this method to data from a prospective observation study, the Diagnostic Innovations in Glaucoma Study, to present a statistically significant association between structural and functional change rates that leads to a better understanding of the progression of glaucoma over time. PMID:26075565

Dynamic modeling of GMA fillet welding using cross-correlation

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

Hellinga, M.; Huissoon, J.; Kerr, H.

1996-12-31

The feasibility of employing the cross-correlation system identification technique as a dynamic modeling method for the GMAW process was examined. This approach has the advantages of modeling speed, the ability to operate in low signal to noise environments, the ease of digital implementation, and the lack of model order assumption, making it ideal in a welding application. The width of the weld pool was the parameter investigated as a function of torch travel speed. Both on-line and off-line width measurements were used to identify the impulse response. Experimental results are presented and comparisons made with both step and ramp response.

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

PubMed

Zhang, Dawei; Liu, Chungen

2016-04-12

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

Cosmological Constraints from Fourier Phase Statistics

NASA Astrophysics Data System (ADS)

Ali, Kamran; Obreschkow, Danail; Howlett, Cullan; Bonvin, Camille; Llinares, Claudio; Oliveira Franco, Felipe; Power, Chris

2018-06-01

Most statistical inference from cosmic large-scale structure relies on two-point statistics, i.e. on the galaxy-galaxy correlation function (2PCF) or the power spectrum. These statistics capture the full information encoded in the Fourier amplitudes of the galaxy density field but do not describe the Fourier phases of the field. Here, we quantify the information contained in the line correlation function (LCF), a three-point Fourier phase correlation function. Using cosmological simulations, we estimate the Fisher information (at redshift z = 0) of the 2PCF, LCF and their combination, regarding the cosmological parameters of the standard ΛCDM model, as well as a Warm Dark Matter (WDM) model and the f(R) and Symmetron modified gravity models. The galaxy bias is accounted for at the level of a linear bias. The relative information of the 2PCF and the LCF depends on the survey volume, sampling density (shot noise) and the bias uncertainty. For a volume of 1h^{-3}Gpc^3, sampled with points of mean density \\bar{n} = 2× 10^{-3} h3 Mpc^{-3} and a bias uncertainty of 13%, the LCF improves the parameter constraints by about 20% in the ΛCDM cosmology and potentially even more in alternative models. Finally, since a linear bias only affects the Fourier amplitudes (2PCF), but not the phases (LCF), the combination of the 2PCF and the LCF can be used to break the degeneracy between the linear bias and σ8, present in 2-point statistics.

Sperm function and assisted reproduction technology

PubMed Central

MAAß, GESA; BÖDEKER, ROLF‐HASSO; SCHEIBELHUT, CHRISTINE; STALF, THOMAS; MEHNERT, CLAAS; SCHUPPE, HANS‐CHRISTIAN; JUNG, ANDREAS; SCHILL, WOLF‐BERNHARD

2005-01-01

The evaluation of different functional sperm parameters has become a tool in andrological diagnosis. These assays determine the sperm's capability to fertilize an oocyte. It also appears that sperm functions and semen parameters are interrelated and interdependent. Therefore, the question arose whether a given laboratory test or a battery of tests can predict the outcome in in vitro fertilization (IVF). One‐hundred and sixty‐one patients who underwent an IVF treatment were selected from a database of 4178 patients who had been examined for male infertility 3 months before or after IVF. Sperm concentration, motility, acrosin activity, acrosome reaction, sperm morphology, maternal age, number of transferred embryos, embryo score, fertilization rate and pregnancy rate were determined. In addition, logistic regression models to describe fertilization rate and pregnancy were developed. All the parameters in the models were dichotomized and intra‐ and interindividual variability of the parameters were assessed. Although the sperm parameters showed good correlations with IVF when correlated separately, the only essential parameter in the multivariate model was morphology. The enormous intra‐ and interindividual variability of the values was striking. In conclusion, our data indicate that the andrological status at the end of the respective treatment does not necessarily represent the status at the time of IVF. Despite a relatively low correlation coefficient in the logistic regression model, it appears that among the parameters tested, the most reliable parameter to predict fertilization is normal sperm morphology. (Reprod Med Biol 2005; 4: 7–30) PMID:29699207

A statistical mechanical theory of proton transport kinetics in hydrogen-bonded networks based on population correlation functions with applications to acids and bases.

PubMed

Tuckerman, Mark E; Chandra, Amalendu; Marx, Dominik

2010-09-28

Extraction of relaxation times, lifetimes, and rates associated with the transport of topological charge defects in hydrogen-bonded networks from molecular dynamics simulations is a challenge because proton transfer reactions continually change the identity of the defect core. In this paper, we present a statistical mechanical theory that allows these quantities to be computed in an unbiased manner. The theory employs a set of suitably defined indicator or population functions for locating a defect structure and their associated correlation functions. These functions are then used to develop a chemical master equation framework from which the rates and lifetimes can be determined. Furthermore, we develop an integral equation formalism for connecting various types of population correlation functions and derive an iterative solution to the equation, which is given a graphical interpretation. The chemical master equation framework is applied to the problems of both hydronium and hydroxide transport in bulk water. For each case it is shown that the theory establishes direct links between the defect's dominant solvation structures, the kinetics of charge transfer, and the mechanism of structural diffusion. A detailed analysis is presented for aqueous hydroxide, examining both reorientational time scales and relaxation of the rotational anisotropy, which is correlated with recent experimental results for these quantities. Finally, for OH(-)(aq) it is demonstrated that the "dynamical hypercoordination mechanism" is consistent with available experimental data while other mechanistic proposals are shown to fail. As a means of going beyond the linear rate theory valid from short up to intermediate time scales, a fractional kinetic model is introduced in the Appendix in order to describe the nonexponential long-time behavior of time-correlation functions. Within the mathematical framework of fractional calculus the power law decay ∼t(-σ), where σ is a parameter of the model and depends on the dimensionality of the system, is obtained from Mittag-Leffler functions due to their long-time asymptotics, whereas (stretched) exponential behavior is found for short times.

Assessment of tropospheric delay mapping function models in Egypt: Using PTD database model

NASA Astrophysics Data System (ADS)

Abdelfatah, M. A.; Mousa, Ashraf E.; El-Fiky, Gamal S.

2018-06-01

For space geodetic measurements, estimates of tropospheric delays are highly correlated with site coordinates and receiver clock biases. Thus, it is important to use the most accurate models for the tropospheric delay to reduce errors in the estimates of the other parameters. Both the zenith delay value and mapping function should be assigned correctly to reduce such errors. Several mapping function models can treat the troposphere slant delay. The recent models were not evaluated for the Egyptian local climate conditions. An assessment of these models is needed to choose the most suitable one. The goal of this paper is to test the quality of global mapping function which provides high consistency with precise troposphere delay (PTD) mapping functions. The PTD model is derived from radiosonde data using ray tracing, which consider in this paper as true value. The PTD mapping functions were compared, with three recent total mapping functions model and another three separate dry and wet mapping function model. The results of the research indicate that models are very close up to zenith angle 80°. Saastamoinen and 1/cos z model are behind accuracy. Niell model is better than VMF model. The model of Black and Eisner is a good model. The results also indicate that the geometric range error has insignificant effect on slant delay and the fluctuation of azimuth anti-symmetric is about 1%.

Report on 3 and 4-point correlation statistics in the COBE DMR anisotrophy maps

NASA Technical Reports Server (NTRS)

Hinshaw, Gary (Principal Investigator); Gorski, Krzystof M.; Banday, Anthony J.; Bennett, Charles L.

1996-01-01

As part of the work performed under NASA contract # NAS5-32648, we have computed the 3-point and 4-point correlation functions of the COBE-DNIR 2-year and 4-year anisotropy maps. The motivation for this study was to search for evidence of non-Gaussian statistical fluctuations in the temperature maps: skewness or asymmetry in the case of the 3-point function, kurtosis in the case of the 4-point function. Such behavior would have very significant implications for our understanding of the processes of galaxy formation, because our current models of galaxy formation predict that non-Gaussian features should not be present in the DMR maps. The results of our work showed that the 3-point correlation function is consistent with zero and that the 4-point function is not a very sensitive probe of non-Gaussian behavior in the COBE-DMR data. Our computation and analysis of 3-point correlations in the 2-year DMR maps was published in the Astrophysical Journal Letters, volume 446, page L67, 1995. Our computation and analysis of 3-point correlations in the 4-year DMR maps will be published, together with some additional tests, in the June 10, 1996 issue of the Astrophysical Journal Letters. Copies of both of these papers are attached as an appendix to this report.