Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results
Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul
1992-01-01
The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.
Correlated binomial models and correlation structures
International Nuclear Information System (INIS)
Hisakado, Masato; Kitsukawa, Kenji; Mori, Shintaro
2006-01-01
We discuss a general method to construct correlated binomial distributions by imposing several consistent relations on the joint probability function. We obtain self-consistency relations for the conditional correlations and conditional probabilities. The beta-binomial distribution is derived by a strong symmetric assumption on the conditional correlations. Our derivation clarifies the 'correlation' structure of the beta-binomial distribution. It is also possible to study the correlation structures of other probability distributions of exchangeable (homogeneous) correlated Bernoulli random variables. We study some distribution functions and discuss their behaviours in terms of their correlation structures
MARS-LMR modeling for the post-test analysis of Phenix End-of-Life natural circulation
International Nuclear Information System (INIS)
Jeong, Hae Yong; Ha, Kwi Seok; Chang, Won Pyo; Lee, Kwi Lim
2011-01-01
For a successful design and analysis of Sodium cooled Fast Reactor (SFR), it is required to have a reliable and well-proven system analysis code. To achieve this purpose, KAERI is enhancing the modeling capability of MARS code by adding the SFR-specific models such as pressure drop model, heat transfer model and reactivity feedback model. This version of MARS-LMR will be used as a basic tool in the design and analysis of future SFR systems in Korea. Before wide application of MARS-LMR code, it is required to verify and validate the code models through analyses for appropriate experimental data or analytical results. The end-of-life test of Phenix reactor performed by the CEA provided a unique opportunity to have reliable test data which is very valuable in the validation and verification of a SFR system analysis code. The KAERI joined this international program of the analysis of Phenix end-of-life natural circulation test coordinated by the IAEA from 2008. The main test of natural circulation was completed in 2009. Before the test the KAERI performed the pre-test analysis based on the design condition provided by the CEA. Then, the blind post-test analysis was also performed based on the test conditions measured during the test before the CEA provide the final test results. Finally, the final post-test analysis was performed recently to predict the test results as accurate as possible. This paper introduces the modeling approach of the MARS-LMR used in the final post-test analysis and summarizes the major results of the analysis
Directory of Open Access Journals (Sweden)
Pengcheng Liu
2016-06-01
Full Text Available Skin factor is often regarded as a constant in most of the mathematical model for well test analysis in oilfields, but this is only a kind of simplified treatment with the actual skin factor changeable. This paper defined the average permeability of a damaged area as a function of time by using the definition of skin factor. Therefore a relationship between a variable skin factor and time was established. The variable skin factor derived was introduced into existing traditional models rather than using a constant skin factor, then, this newly derived mathematical model for well test analysis considering variable skin factor was solved by Laplace transform. The dimensionless wellbore pressure and its derivative changed with dimensionless time were plotted with double logarithm and these plots can be used for type curve fitting. The effects of all the parameters in the expression of variable skin factor were analyzed based on the dimensionless wellbore pressure and its derivative. Finally, actual well testing data were used to fit the type curves developed which validates the applicability of the mathematical model from Sheng-2 Block, Shengli Oilfield, China.
Pre-test analysis results of a PWR steel lined pre-stressed concrete containment model
International Nuclear Information System (INIS)
Basha, S.M.; Ghosh, Barnali; Patnaik, R.; Ramanujam, S.; Singh, R.K.; Kushwaha, H.S.; Venkat Raj, V.
2000-02-01
Pre-stressed concrete nuclear containment serves as the ultimate barrier against the release of radioactivity to the environment. This ultimate barrier must be checked for its ultimate load carrying capacity. BARC participated in a Round Robin analysis activity which is co-sponsored by Sandia National Laboratory, USA and Nuclear Power Engineering Corporation Japan for the pre-test prediction of a 1:4 size Pre-stressed Concrete Containment Vessel. In house finite element code ULCA was used to make the test predictions of displacements and strains at the standard output locations. The present report focuses on the important landmarks of the pre-test results, in sequential terms of first crack appearance, loss of pre-stress, first through thickness crack, rebar and liner yielding and finally liner tearing at the ultimate load. Global and local failure modes of the containment have been obtained from the analysis. Finally sensitivity of the numerical results with respect to different types of liners and different constitutive models in terms of bond strength between concrete and steel and tension-stiffening parameters are examined. The report highlights the important features which could be observed during the test and guidelines are given for improving the prediction in the post test computation after the test data is available. (author)
Correlation Structures of Correlated Binomial Models and Implied Default Distribution
S. Mori; K. Kitsukawa; M. Hisakado
2006-01-01
We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution h...
Cluster Correlation in Mixed Models
Gardini, A.; Bonometto, S. A.; Murante, G.; Yepes, G.
2000-10-01
We evaluate the dependence of the cluster correlation length, rc, on the mean intercluster separation, Dc, for three models with critical matter density, vanishing vacuum energy (Λ=0), and COBE normalization: a tilted cold dark matter (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos, yielding Ωh=0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of σ8 (and hence the observed cluster abundance) and are consistent with the observed abundance of damped Lyα systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio σ8/σ25, yielding the spectral slope parameter Γ, and nicely fit Las Campanas Redshift Survey (LCRS) reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (of side 360 h-1 Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow us to cover the same Dc interval inspected through Automatic Plate Measuring Facility (APM) and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit to cluster clustering data.
Correlation Structures of Correlated Binomial Models and Implied Default Distribution
Mori, Shintaro; Kitsukawa, Kenji; Hisakado, Masato
2008-11-01
We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.
Correlation Models for Temperature Fields
North, Gerald R.
2011-05-16
This paper presents derivations of some analytical forms for spatial correlations of evolving random fields governed by a white-noise-driven damped diffusion equation that is the analog of autoregressive order 1 in time and autoregressive order 2 in space. The study considers the two-dimensional plane and the surface of a sphere, both of which have been studied before, but here time is introduced to the problem. Such models have a finite characteristic length (roughly the separation at which the autocorrelation falls to 1/e) and a relaxation time scale. In particular, the characteristic length of a particular temporal Fourier component of the field increases to a finite value as the frequency of the particular component decreases. Some near-analytical formulas are provided for the results. A potential application is to the correlation structure of surface temperature fields and to the estimation of large area averages, depending on how the original datastream is filtered into a distribution of Fourier frequencies (e.g., moving average, low pass, or narrow band). The form of the governing equation is just that of the simple energy balance climate models, which have a long history in climate studies. The physical motivation provided by the derivation from a climate model provides some heuristic appeal to the approach and suggests extensions of the work to nonuniform cases.
Correlation Models for Temperature Fields
North, Gerald R.; Wang, Jue; Genton, Marc G.
2011-01-01
This paper presents derivations of some analytical forms for spatial correlations of evolving random fields governed by a white-noise-driven damped diffusion equation that is the analog of autoregressive order 1 in time and autoregressive order 2 in space. The study considers the two-dimensional plane and the surface of a sphere, both of which have been studied before, but here time is introduced to the problem. Such models have a finite characteristic length (roughly the separation at which the autocorrelation falls to 1/e) and a relaxation time scale. In particular, the characteristic length of a particular temporal Fourier component of the field increases to a finite value as the frequency of the particular component decreases. Some near-analytical formulas are provided for the results. A potential application is to the correlation structure of surface temperature fields and to the estimation of large area averages, depending on how the original datastream is filtered into a distribution of Fourier frequencies (e.g., moving average, low pass, or narrow band). The form of the governing equation is just that of the simple energy balance climate models, which have a long history in climate studies. The physical motivation provided by the derivation from a climate model provides some heuristic appeal to the approach and suggests extensions of the work to nonuniform cases.
RAYLEIGH SCATTERING MODELS WITH CORRELATION INTEGRAL
Directory of Open Access Journals (Sweden)
S. F. Kolomiets
2014-01-01
Full Text Available This article offers one of possible approaches to the use of the classical correlation concept in Rayleigh scattering models. Classical correlation in contrast to three types of correlations corresponding to stochastic point flows opens the door to the efficient explanation of the interaction between periodical structure of incident radiation and discreet stochastic structure of distributed scatters typical for Rayleigh problems.
Modeling conditional correlations of asset returns
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
2015-01-01
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is d......In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM......-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five...
Model validation: Correlation for updating
Indian Academy of Sciences (India)
In this paper, a review is presented of the various methods which ... to make a direct and objective comparison of specific dynamic properties, measured ..... stiffness matrix is available from the analytical model, is that of reducing or condensing.
Correlations and Non-Linear Probability Models
DEFF Research Database (Denmark)
Breen, Richard; Holm, Anders; Karlson, Kristian Bernt
2014-01-01
the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....
Correlators in tensor models from character calculus
Directory of Open Access Journals (Sweden)
A. Mironov
2017-11-01
Full Text Available We explain how the calculations of [20], which provided the first evidence for non-trivial structures of Gaussian correlators in tensor models, are efficiently performed with the help of the (Hurwitz character calculus. This emphasizes a close similarity between technical methods in matrix and tensor models and supports a hope to understand the emerging structures in very similar terms. We claim that the 2m-fold Gaussian correlators of rank r tensors are given by r-linear combinations of dimensions with the Young diagrams of size m. The coefficients are made from the characters of the symmetric group Sm and their exact form depends on the choice of the correlator and on the symmetries of the model. As the simplest application of this new knowledge, we provide simple expressions for correlators in the Aristotelian tensor model as tri-linear combinations of dimensions.
Boundary correlators in supergroup WZNW models
Energy Technology Data Exchange (ETDEWEB)
Creutzig, T.; Schomerus, V.
2008-04-15
We investigate correlation functions for maximally symmetric boundary conditions in the WZNW model on GL(11). Special attention is payed to volume filling branes. Generalizing earlier ideas for the bulk sector, we set up a Kac-Wakimotolike formalism for the boundary model. This first order formalism is then used to calculate bulk-boundary 2-point functions and the boundary 3-point functions of the model. The note ends with a few comments on correlation functions of atypical fields, point-like branes and generalizations to other supergroups. (orig.)
RELAP5/MOD2 models and correlations
International Nuclear Information System (INIS)
Dimenna, R.A.; Larson, J.R.; Johnson, R.W.; Larson, T.K.; Miller, C.S.; Streit, J.E.; Hanson, R.G.; Kiser, D.M.
1988-08-01
A review of the RELAP5/MOD2 computer code has been performed to assess the basis for the models and correlations comprising the code. The review has included verification of the original data base, including thermodynamic, thermal-hydraulic, and geothermal conditions; simplifying assumptions in implementation or application; and accuracy of implementation compared to documented descriptions of each of the models. An effort has been made to provide the reader with an understanding of what is in the code and why it is there and to provide enough information that an analyst can assess the impact of the correlation or model on the ability of the code to represent the physics of a reactor transient. Where assessment of the implemented versions of the models or correlations has been accomplished and published, the assessment results have been included
Bose-Einstein correlation in Landau's model
International Nuclear Information System (INIS)
Hama, Y.; Padula, S.S.
1986-01-01
Bose-Einstein correlation is studied by taking an expanding fluid given by Landau's model as the source, where each space-time point is considered as an independent and chaotic emitting center with Planck's spectral distribution. As expected, the correlation depends on the relative angular positions as well as on the overall localization of the measuring system and it turns out that the average dimension of the source increases with the multiplicity N/sub ch/
Spin chain model for correlated quantum channels
Energy Technology Data Exchange (ETDEWEB)
Rossini, Davide [International School for Advanced Studies SISSA/ISAS, via Beirut 2-4, I-34014 Trieste (Italy); Giovannetti, Vittorio; Montangero, Simone [NEST-CNR-INFM and Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa (Italy)], E-mail: monta@sns.it
2008-11-15
We analyze the quality of the quantum information transmission along a correlated quantum channel by studying the average fidelity between input and output states and the average output purity, giving bounds for the entropy of the channel. Noise correlations in the channel are modeled by the coupling of each channel use with an element of a one-dimensional interacting quantum spin chain. Criticality of the environment chain is seen to emerge in the changes of the fidelity and of the purity.
Nonparametric correlation models for portfolio allocation
DEFF Research Database (Denmark)
Aslanidis, Nektarios; Casas, Isabel
2013-01-01
This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....
Correlation functions of two-matrix models
International Nuclear Information System (INIS)
Bonora, L.; Xiong, C.S.
1993-11-01
We show how to calculate correlation functions of two matrix models without any approximation technique (except for genus expansion). In particular we do not use any continuum limit technique. This allows us to find many solutions which are invisible to the latter technique. To reach our goal we make full use of the integrable hierarchies and their reductions which were shown in previous papers to naturally appear in multi-matrix models. The second ingredient we use, even though to a lesser extent, are the W-constraints. In fact an explicit solution of the relevant hierarchy, satisfying the W-constraints (string equation), underlies the explicit calculation of the correlation functions. The correlation functions we compute lend themselves to a possible interpretation in terms of topological field theories. (orig.)
Electron Correlation Models for Optical Activity
DEFF Research Database (Denmark)
Höhn, E. G.; O. E. Weigang, Jr.
1968-01-01
A two-system no-overlap model for rotatory strength is developed for electric-dipole forbidden as well as allowed transitions. General equations which allow for full utilization of symmetry in the chromophore and in the environment are obtained. The electron correlation terms are developed in full...
International Space Station Model Correlation Analysis
Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael
2018-01-01
This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.
Directory of Open Access Journals (Sweden)
Gómez Susana
2014-07-01
Full Text Available The aim of this work is to study the automatic characterization of Naturally Fractured Vuggy Reservoirs via well test analysis, using a triple porosity-dual permeability model. The inter-porosity flow parameters, the storativity ratios, as well as the permeability ratio, the wellbore storage effect, the skin and the total permeability will be identified as parameters of the model. In this work, we will perform the well test interpretation in Laplace space, using numerical algorithms to transfer the discrete real data given in fully dimensional time to Laplace space. The well test interpretation problem in Laplace space has been posed as a nonlinear least squares optimization problem with box constraints and a linear inequality constraint, which is usually solved using local Newton type methods with a trust region. However, local methods as the one used in our work called TRON or the well-known Levenberg-Marquardt method, are often not able to find an optimal solution with a good fit of the data. Also well test analysis with the triple porosity-double permeability model, like most inverse problems, can yield multiple solutions with good match to the data. To deal with these specific characteristics, we will use a global optimization algorithm called the Tunneling Method (TM. In the design of the algorithm, we take into account issues of the problem like the fact that the parameter estimation has to be done with high precision, the presence of noise in the measurements and the need to solve the problem computationally fast. We demonstrate that the use of the TM in this study, showed to be an efficient and robust alternative to solve the well test characterization, as several optimal solutions, with very good match to the data were obtained.
Fluctuation correlation models for receptor immobilization
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.
IFCI 7.0 Models and Correlations
Energy Technology Data Exchange (ETDEWEB)
Reed, A.W.; Schmidt, R.C.; Young, M.F.
1999-05-01
The Integrated Fuel-Coolant Interaction Code (IFCI) is a best-estimate computer program for analysis of phenomena related to mixing of molten nuclear reactor core material with reactor coolant (water). The stand-alone version of the code, IFCI 7.0, has been designed for analysis of small- and intermediate-scale experiments in order to gain insight into the physics (including scaling effects) of molten fuel-coolant interactions. The code's methods, models, and correlations are being assessed. This report describes the flow regime, friction factor, and heat-transfer models used in the current version of IFCI (IFCI 7.0).
IFCI 7.0 Models and Correlations
International Nuclear Information System (INIS)
Reed, A.W.; Schmidt, R.C.; Young, M.F.
1999-01-01
The Integrated Fuel-Coolant Interaction Code (IFCI) is a best-estimate computer program for analysis of phenomena related to mixing of molten nuclear reactor core material with reactor coolant (water). The stand-alone version of the code, IFCI 7.0, has been designed for analysis of small- and intermediate-scale experiments in order to gain insight into the physics (including scaling effects) of molten fuel-coolant interactions. The code's methods, models, and correlations are being assessed. This report describes the flow regime, friction factor, and heat-transfer models used in the current version of IFCI (IFCI 7.0)
Modeling CMB lensing cross correlations with CLEFT
Energy Technology Data Exchange (ETDEWEB)
Modi, Chirag; White, Martin [Department of Physics, University of California, Berkeley, CA 94720 (United States); Vlah, Zvonimir, E-mail: modichirag@berkeley.edu, E-mail: mwhite@berkeley.edu, E-mail: zvlah@stanford.edu [Stanford Institute for Theoretical Physics and Department of Physics, Stanford University, Stanford, CA 94306 (United States)
2017-08-01
A new generation of surveys will soon map large fractions of sky to ever greater depths and their science goals can be enhanced by exploiting cross correlations between them. In this paper we study cross correlations between the lensing of the CMB and biased tracers of large-scale structure at high z . We motivate the need for more sophisticated bias models for modeling increasingly biased tracers at these redshifts and propose the use of perturbation theories, specifically Convolution Lagrangian Effective Field Theory (CLEFT). Since such signals reside at large scales and redshifts, they can be well described by perturbative approaches. We compare our model with the current approach of using scale independent bias coupled with fitting functions for non-linear matter power spectra, showing that the latter will not be sufficient for upcoming surveys. We illustrate our ideas by estimating σ{sub 8} from the auto- and cross-spectra of mock surveys, finding that CLEFT returns accurate and unbiased results at high z . We discuss uncertainties due to the redshift distribution of the tracers, and several avenues for future development.
Correlation Functions in Holographic Minimal Models
Papadodimas, Kyriakos
2012-01-01
We compute exact three and four point functions in the W_N minimal models that were recently conjectured to be dual to a higher spin theory in AdS_3. The boundary theory has a large number of light operators that are not only invisible in the bulk but grow exponentially with N even at small conformal dimensions. Nevertheless, we provide evidence that this theory can be understood in a 1/N expansion since our correlators look like free-field correlators corrected by a power series in 1/N . However, on examining these corrections we find that the four point function of the two bulk scalar fields is corrected at leading order in 1/N through the contribution of one of the additional light operators in an OPE channel. This suggests that, to correctly reproduce even tree-level correlators on the boundary, the bulk theory needs to be modified by the inclusion of additional fields. As a technical by-product of our analysis, we describe two separate methods -- including a Coulomb gas type free-field formalism -- that ...
Numerical Simulation of the Heston Model under Stochastic Correlation
Directory of Open Access Journals (Sweden)
Long Teng
2017-12-01
Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.
Macwilkinson, D. G.; Blackerby, W. T.; Paterson, J. H.
1974-01-01
The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.
Correlations in the Parton Recombination Model
Energy Technology Data Exchange (ETDEWEB)
Bass, S.A. [Department of Physics, Duke University, Durham, NC 27708-0305 (United States); RIKEN BNL Research Center, Brookhaven Nat. Lab., Upton, NY 11973 (United States); Fries, R.J. [School of Physics and Astronomy, Univ. of Minnesota, Minneapolis, MN 55455 (United States); Mueller, B. [Department of Physics, Duke University, Durham, NC 27708-0305 (United States)
2006-08-07
We describe how parton recombination can address the recent measurement of dynamical jet-like two particle correlations. In addition we discuss the possible effect realistic light-cone wave-functions including higher Fock-states may have on the well-known elliptic flow valence-quark number scaling law.
Modelling conditional correlations of asset returns: A smooth transition approach
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is d......In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM......-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of ve...
Testing Cross-Sectional Correlation in Large Panel Data Models with Serial Correlation
Directory of Open Access Journals (Sweden)
Badi H. Baltagi
2016-11-01
Full Text Available This paper considers the problem of testing cross-sectional correlation in large panel data models with serially-correlated errors. It finds that existing tests for cross-sectional correlation encounter size distortions with serial correlation in the errors. To control the size, this paper proposes a modification of Pesaran’s Cross-sectional Dependence (CD test to account for serial correlation of an unknown form in the error term. We derive the limiting distribution of this test as N , T → ∞ . The test is distribution free and allows for unknown forms of serial correlation in the errors. Monte Carlo simulations show that the test has good size and power for large panels when serial correlation in the errors is present.
Modified Regression Correlation Coefficient for Poisson Regression Model
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Correlation of Fukushima data with SSI models
International Nuclear Information System (INIS)
Miller, C.A.; Costantino, C.J.; Philippacopoulos, A.J.
1985-01-01
The seismic response of nuclear power plant structures is often calculated using lumped parameter methods. A finite element model of the structure is coupled to the soil with a spring-dashpot system used to represent the interaction process. The parameters of the interaction model are based on analytic solutions to simple problems which are idealizations of the actual problem. The objective of this work is to compare predicted response using the standard lumped parameter models with experimental data. These comparisons are shown to be good for fairly uniform soil systems. (orig.)
A Note on the Correlated Random Coefficient Model
DEFF Research Database (Denmark)
Kolodziejczyk, Christophe
In this note we derive the bias of the OLS estimator for a correlated random coefficient model with one random coefficient, but which is correlated with a binary variable. We provide set-identification to the parameters of interest of the model. We also show how to reduce the bias of the estimator...
A Model for Positively Correlated Count Variables
DEFF Research Database (Denmark)
Møller, Jesper; Rubak, Ege Holger
2010-01-01
An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....
Effects of Perfectly Correlated and Anti-Correlated Noise in a Logistic Growth Model
International Nuclear Information System (INIS)
Zhang Li; Cao Li
2011-01-01
The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to analyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in both cases, the increase of the multiplicative noise intensity cause tumor cell extinction. In the perfectly anti-correlated case, the stationary probability distribution as a function of tumor cell population exhibit two extrema. (general)
Analytic uncertainty and sensitivity analysis of models with input correlations
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
Correlation length estimation in a polycrystalline material model
International Nuclear Information System (INIS)
Simonovski, I.; Cizelj, L.
2005-01-01
This paper deals with the correlation length estimated from a mesoscopic model of a polycrystalline material. The correlation length can be used in some macroscopic material models as a material parameter that describes the internal length. It can be estimated directly from the strain and stress fields calculated from a finite-element model, which explicitly accounts for the selected mesoscopic features such as the random orientation, shape and size of the grains. A crystal plasticity material model was applied in the finite-element analysis. Different correlation lengths were obtained depending on the used set of crystallographic orientations. We determined that the different sets of crystallographic orientations affect the general level of the correlation length, however, as the external load is increased the behaviour of correlation length is similar in all the analyzed cases. The correlation lengths also changed with the macroscopic load. If the load is below the yield strength the correlation lengths are constant, and are slightly higher than the average grain size. The correlation length can therefore be considered as an indicator of first plastic deformations in the material. Increasing the load above the yield strength creates shear bands that temporarily increase the values of the correlation lengths calculated from the strain fields. With a further load increase the correlation lengths decrease slightly but stay above the average grain size. (author)
Connecting single-stock assessment models through correlated survival
DEFF Research Database (Denmark)
Albertsen, Christoffer Moesgaard; Nielsen, Anders; Thygesen, Uffe Høgsbro
2017-01-01
times. We propose a simple alternative. In three case studies each with two stocks, we improve the single-stock models, as measured by Akaike information criterion, by adding correlation in the cohort survival. To limit the number of parameters, the correlations are parameterized through...... the corresponding partial correlations. We consider six models where the partial correlation matrix between stocks follows a band structure ranging from independent assessments to complex correlation structures. Further, a simulation study illustrates the importance of handling correlated data sufficiently...... by investigating the coverage of confidence intervals for estimated fishing mortality. The results presented will allow managers to evaluate stock statuses based on a more accurate evaluation of model output uncertainty. The methods are directly implementable for stocks with an analytical assessment and do...
Unidimensional factor models imply weaker partial correlations than zero-order correlations.
van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J
2018-06-01
In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.
A Summary of Interfacial Heat Transfer Models and Correlations
Energy Technology Data Exchange (ETDEWEB)
Bae, Sung Won; Cho, Hyung Kyu; Lee, Young Jin; Kim, Hee Chul; Jung, Young Jong; Kim, K. D. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2007-10-15
A long term project has been launched in October 2006 to develop a plant safety analysis code. 5 organizations are joining together for the harmonious coworking to build up the code. In this project, KAERI takes the charge of the building up the physical models and correlations about the transport phenomena. The momentum and energy transfer terms as well as the mass are surveyed from the RELAP5/MOD3, RELAP5-3D, CATHARE, and TRAC-M does. Also the recent papers are surveyed. Among these resources, most of the CATHARE models are based on their own experiment and test results. Thus, the CATHARE models are only used as the comparison purposes. In this paper, a summary of the models and the correlations about the interfacial heat transfer are represented. These surveyed models and correlations will be tested numerically and one correlation is selected finally.
A model relating Eulerian spatial and temporal velocity correlations
Cholemari, Murali R.; Arakeri, Jaywant H.
2006-03-01
In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.
K correlations and facet models in diffuse scattering
Hoenders, B.J.; Jakeman, E.; Baltes, H.P.; Steinle, B.
1979-01-01
The angular intensity distribution of radiation scattered by a wide range of random media can be accounted for by assuming effective source amplitude correlations involving modified Bessel functions Kv. We investigate how such correlations can be derived from physical models of stochastic scattering
Correlation-regression model for physico-chemical quality of ...
African Journals Online (AJOL)
abusaad
areas, suggesting that groundwater quality in urban areas is closely related with land use ... the ground water, with correlation and regression model is also presented. ...... WHO (World Health Organization) (1985). Health hazards from nitrates.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei; Holbrook, Andrew; Fortin, Norbert J.; Ombao, Hernando; Shahbaba, Babak
2017-01-01
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Weak diffusion limits of dynamic conditional correlation models
DEFF Research Database (Denmark)
Hafner, Christian M.; Laurent, Sebastien; Violante, Francesco
The properties of dynamic conditional correlation (DCC) models are still not entirely understood. This paper fills one of the gaps by deriving weak diffusion limits of a modified version of the classical DCC model. The limiting system of stochastic differential equations is characterized...... by a diffusion matrix of reduced rank. The degeneracy is due to perfect collinearity between the innovations of the volatility and correlation dynamics. For the special case of constant conditional correlations, a non-degenerate diffusion limit can be obtained. Alternative sets of conditions are considered...
Gaussian graphical modeling reveals specific lipid correlations in glioblastoma cells
Mueller, Nikola S.; Krumsiek, Jan; Theis, Fabian J.; Böhm, Christian; Meyer-Bäse, Anke
2011-06-01
Advances in high-throughput measurements of biological specimens necessitate the development of biologically driven computational techniques. To understand the molecular level of many human diseases, such as cancer, lipid quantifications have been shown to offer an excellent opportunity to reveal disease-specific regulations. The data analysis of the cell lipidome, however, remains a challenging task and cannot be accomplished solely based on intuitive reasoning. We have developed a method to identify a lipid correlation network which is entirely disease-specific. A powerful method to correlate experimentally measured lipid levels across the various samples is a Gaussian Graphical Model (GGM), which is based on partial correlation coefficients. In contrast to regular Pearson correlations, partial correlations aim to identify only direct correlations while eliminating indirect associations. Conventional GGM calculations on the entire dataset can, however, not provide information on whether a correlation is truly disease-specific with respect to the disease samples and not a correlation of control samples. Thus, we implemented a novel differential GGM approach unraveling only the disease-specific correlations, and applied it to the lipidome of immortal Glioblastoma tumor cells. A large set of lipid species were measured by mass spectrometry in order to evaluate lipid remodeling as a result to a combination of perturbation of cells inducing programmed cell death, while the other perturbations served solely as biological controls. With the differential GGM, we were able to reveal Glioblastoma-specific lipid correlations to advance biomedical research on novel gene therapies.
Higher genus correlators from the hermitian one-matrix model
International Nuclear Information System (INIS)
Ambjoern, J.; Chekhov, L.; Makeenko, Yu.
1992-01-01
We develop an iterative algorithm for the genus expansion of the hermitian NxN one-matrix model (is the Penner model in an external field). By introducing moments of the external field, we prove that the genus g contribution to the m-loop correlator depends only on 3g-2+m lower moments (3g-2 for the partition function). We present the explicit results for the partition function and the one-loop correlator in genus one. We compare the correlators for the hermitian one-matrix model with those at zero momenta for c=1 CFT and show an agreement of the one-loop correlators for genus zero. (orig.)
Spreading of correlations in the Falicov-Kimball model
Herrmann, Andreas J.; Antipov, Andrey E.; Werner, Philipp
2018-04-01
We study dynamical properties of the one- and two-dimensional Falicov-Kimball model using lattice Monte Carlo simulations. In particular, we calculate the spreading of charge correlations in the equilibrium model and after an interaction quench. The results show a reduction of the light-cone velocity with interaction strength at low temperature, while the phase velocity increases. At higher temperature, the initial spreading is determined by the Fermi velocity of the noninteracting system and the maximum range of the correlations decreases with increasing interaction strength. Charge order correlations in the disorder potential enhance the range of the correlations. We also use the numerically exact lattice Monte Carlo results to benchmark the accuracy of equilibrium and nonequilibrium dynamical cluster approximation calculations. It is shown that the bias introduced by the mapping to a periodized cluster is substantial, and that from a numerical point of view, it is more efficient to simulate the lattice model directly.
Modeling correlated bursts by the bursty-get-burstier mechanism
Jo, Hang-Hyun
2017-12-01
Temporal correlations of time series or event sequences in natural and social phenomena have been characterized by power-law decaying autocorrelation functions with decaying exponent γ . Such temporal correlations can be understood in terms of power-law distributed interevent times with exponent α and/or correlations between interevent times. The latter, often called correlated bursts, has recently been studied by measuring power-law distributed bursty trains with exponent β . A scaling relation between α and γ has been established for the uncorrelated interevent times, while little is known about the effects of correlated interevent times on temporal correlations. In order to study these effects, we devise the bursty-get-burstier model for correlated bursts, by which one can tune the degree of correlations between interevent times, while keeping the same interevent time distribution. We numerically find that sufficiently strong correlations between interevent times could violate the scaling relation between α and γ for the uncorrelated case. A nontrivial dependence of γ on β is also found for some range of α . The implication of our results is discussed in terms of the hierarchical organization of bursty trains at various time scales.
Spin delocalization phase transition in a correlated electrons model
International Nuclear Information System (INIS)
Huerta, L.
1990-11-01
In a simplified one-site model for correlated electrons systems we show the existence of a phase transition corresponding to spin delocalization. The system becomes a solvable model and zero-dimensional functional techniques are used. (author). 7 refs, 3 figs
Correlated Hopping in the 1D Falicov--Kimball Model
Gajek, Z.; Lemanski, R.
2001-10-01
Ground state phase diagrams in the canonical ensemble of the one-dimensional Falicov-Kimball Model (FKM) with the correlated hopping are presented for several values of the model parameters. As compare to the conventional FKM, the diagrams exhibit a loss of the particle--hole symmetry.
Correlated Hopping in the 1d Falicov-Kimball Model
International Nuclear Information System (INIS)
Gajek, Z.; Lemanski, R.
2001-01-01
Ground state phase diagrams in the canonical ensemble of the one-dimensional Falicov-Kimball Model FKM) with the correlated hopping are presented for several values of the model parameters. As compare to the conventional FKM, the diagrams exhibit a loss of the particle-hole symmetry. (author)
Bose-Einstein correlation in the Lund model
International Nuclear Information System (INIS)
Anderson, B.
1998-01-01
I will present the Lund Model fragmentation in a somewhat different way than what is usually done. It is true that the formulas are derived from (semi-)classical probability arguments, but they can be motivated in a quantum mechanical setting and it is in particular possible to derive a transition matrix element. I will present two scenarios, one based upon Schwinger tunneling and one upon Wilson loop operators. The results will coincide and throw some light upon the sizes of the three main phenomenological parameters which occur in the Lund Model. After that I will show that in this way it is possible to obtain a model for the celebrated Bose-Einstein correlations between two bosons with small relative momenta. This model will exhibit non-trivial two- and three-particle BE correlations, influence the observed p-spectrum and finally be different for charged and neutral pion correlations. (author)
Correlation functions and Schwinger-Dyson equations for Penner's model
International Nuclear Information System (INIS)
Chair, N.; Panda, S.
1991-05-01
The free energy of Penner's model exhibits logarithmic singularity in the continuum limit. We show, however, that the one and two point correlators of the usual loop-operators do not exhibit logarithmic singularity. The continuum Schwinger-Dyson equations involving these correlation functions are derived and it is found that within the space of the corresponding couplings, the resulting constraints obey a Virasoro algebra. The puncture operator having the correct (logarithmic) scaling behaviour is identified. (author). 13 refs
Transverse momentum correlations of quarks in recursive jet models
Artru, X.; Belghobsi, Z.; Redouane-Salah, E.
2016-08-01
In the symmetric string fragmentation recipe adopted by PYTHIA for jet simulations, the transverse momenta of successive quarks are uncorrelated. This is a simplification but has no theoretical basis. Transverse momentum correlations are naturally expected, for instance, in a covariant multiperipheral model of quark hadronization. We propose a simple recipe of string fragmentation which leads to such correlations. The definition of the jet axis and its relation with the primordial transverse momentum of the quark is also discussed.
The singular multiparticle correlation function and the α-model
International Nuclear Information System (INIS)
Bozek, P.; Ploszajczak, M.
1991-01-01
The comparison is made between the two descriptions of multiparticle correlations using either the α-model or the scale-invariant distribution functions. The case of the strong and weak intermittency is discussed. These two descriptions show similar results for both the scaled factorial moments and the scaled factorial correlators. It is shown that the dimensional projection does not alter this similarity and moreover, it explains an experimentally observed difference between the slopes of factorial moments and factorial correlators. (author) 8 refs.; 3 figs
Intersite electron correlations in a Hubbard model on inhomogeneous lattices
International Nuclear Information System (INIS)
Takemori, Nayuta; Koga, Akihisa; Hafermann, Hartmut
2016-01-01
We study intersite electron correlations in the half-filled Hubbard model on square lattices with periodic and open boundary conditions by means of a real-space dual fermion approach. By calculating renormalization factors, we clarify that nearest-neighbor intersite correlations already significantly reduce the critical interaction. The Mott transition occurs at U/t ∼ 6.4, where U is the interaction strength and t is the hopping integral. This value is consistent with quantum Monte Carlo results. It shows the importance of short-range intersite correlations, which are taken into account in the framework of the real-space dual fermion approach. (paper)
Application of Multilevel Models to Morphometric Data. Part 2. Correlations
Directory of Open Access Journals (Sweden)
O. Tsybrovskyy
2003-01-01
Full Text Available Multilevel organization of morphometric data (cells are “nested” within patients requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance matrices are produced for every level in the hierarchy. In karyometric research, the cell‐level (i.e., within‐tumor correlations seem to be of major interest. Beside their biological importance, these correlation coefficients (CC are compulsory when dimensionality reduction is required. Using MLwiN, a dedicated program for multilevel modeling, we show how to use multivariate multilevel models (MMM to obtain and interpret CC in each of the levels. A comparison with two usual, “single‐level” statistics shows that MMM represent the only way to obtain correct cell‐level correlation coefficients. The summary statistics method (take average values across each patient produces patient‐level CC only, and the “pooling” method (merge all cells together and ignore patients as units of analysis yields incorrect CC at all. We conclude that multilevel modeling is an indispensable tool for studying correlations between morphometric variables.
Correlation of spacecraft thermal mathematical models to reference data
Torralbo, Ignacio; Perez-Grande, Isabel; Sanz-Andres, Angel; Piqueras, Javier
2018-03-01
Model-to-test correlation is a frequent problem in spacecraft-thermal control design. The idea is to determine the values of the parameters of the thermal mathematical model (TMM) that allows reaching a good fit between the TMM results and test data, in order to reduce the uncertainty of the mathematical model. Quite often, this task is performed manually, mainly because a good engineering knowledge and experience is needed to reach a successful compromise, but the use of a mathematical tool could facilitate this work. The correlation process can be considered as the minimization of the error of the model results with regard to the reference data. In this paper, a simple method is presented suitable to solve the TMM-to-test correlation problem, using Jacobian matrix formulation and Moore-Penrose pseudo-inverse, generalized to include several load cases. Aside, in simple cases, this method also allows for analytical solutions to be obtained, which helps to analyze some problems that appear when the Jacobian matrix is singular. To show the implementation of the method, two problems have been considered, one more academic, and the other one the TMM of an electronic box of PHI instrument of ESA Solar Orbiter mission, to be flown in 2019. The use of singular value decomposition of the Jacobian matrix to analyze and reduce these models is also shown. The error in parameter space is used to assess the quality of the correlation results in both models.
Quark model calculations of current correlators in the nonperturbative domain
International Nuclear Information System (INIS)
Celenza, L.S.; Shakin, C.M.; Sun, W.D.
1995-01-01
The authors study the vector-isovector current correlator in this work, making use of a generalized Nambu-Jona-Lasinio (NJL) model. In their work, the original NJL model is extended to describe the coupling of the quark-antiquark states to the two-pion continuum. Further, a model for confinement is introduced that is seen to remove the nonphysical cuts that appear in various amplitudes when the quark and antiquark go on mass shell. Quite satisfactory results are obtained for the correlator. The authors also use the correlator to define a T-matrix for confined quarks and discuss a rho-dominance model for that T-matrix. It is also seen that the Bethe-Salpeter equation that determines the rho mass (in the absence of the coupling to the two-pion continuum) has more satisfactory behavior in the generalized model than in the model without confinement. That improved behavior is here related to the absence of the q bar q cut in the basic quark-loop integral of the generalized model. In this model, it is seen how one may work with both quark and hadron degrees of freedom, with only the hadrons appearing as physical particles. 12 refs., 16 figs., 1 tab
Energy Technology Data Exchange (ETDEWEB)
Xie, Linjun [Zhejiang Univ. of Technology, Hangzhou (China). College of Mechanical Engineering; Xue, Guohong; Zhang, Ming [Shanghai Nuclear Engineering Research and Design Institute, Shanghai (China)
2017-11-15
The friction force between the contact surfaces of a reactor internal hold-down spring (HDS) and core barrel flanges can directly influence the axial stiffness of an HDS. However, friction coefficient cannot be obtained through theoretical analysis. This study performs a mathematical deduction of the physical model of an HDS. Moreover, a mathematical model of axial load P, displacement δ, and flexibility coefficient is established, and a set of test apparatuses is designed to simulate the preloading process of the HDS. According to the experimental research and theoretical analysis, P-δ curves and the flexibility coefficient λ are obtained in the loading processes of the HDS. The friction coefficient f of the M1000 HDS is further calculated as 0.224. The displacement limit load value (4,638 kN) can be obtained through a displacement limit experiment. With the friction coefficient considered, the theoretical load is 4,271 kN, which is relatively close to the experimental result. Thus, the friction coefficient exerts an influence on the displacement limit load P. The friction coefficient should be considered in the design analysis for HDS.
International Nuclear Information System (INIS)
Xie, Linjun
2017-01-01
The friction force between the contact surfaces of a reactor internal hold-down spring (HDS) and core barrel flanges can directly influence the axial stiffness of an HDS. However, friction coefficient cannot be obtained through theoretical analysis. This study performs a mathematical deduction of the physical model of an HDS. Moreover, a mathematical model of axial load P, displacement δ, and flexibility coefficient is established, and a set of test apparatuses is designed to simulate the preloading process of the HDS. According to the experimental research and theoretical analysis, P-δ curves and the flexibility coefficient λ are obtained in the loading processes of the HDS. The friction coefficient f of the M1000 HDS is further calculated as 0.224. The displacement limit load value (4,638 kN) can be obtained through a displacement limit experiment. With the friction coefficient considered, the theoretical load is 4,271 kN, which is relatively close to the experimental result. Thus, the friction coefficient exerts an influence on the displacement limit load P. The friction coefficient should be considered in the design analysis for HDS.
Correlation models for waste tank sludges and slurries
International Nuclear Information System (INIS)
Mahoney, L.A.; Trent, D.S.
1995-07-01
This report presents the results of work conducted to support the TEMPEST computer modeling under the Flammable Gas Program (FGP) and to further the comprehension of the physical processes occurring in the Hanford waste tanks. The end products of this task are correlation models (sets of algorithms) that can be added to the TEMPEST computer code to improve the reliability of its simulation of the physical processes that occur in Hanford tanks. The correlation models can be used to augment, not only the TEMPEST code, but other computer codes that can simulate sludge motion and flammable gas retention. This report presents the correlation models, also termed submodels, that have been developed to date. The submodel-development process is an ongoing effort designed to increase our understanding of sludge behavior and improve our ability to realistically simulate the sludge fluid characteristics that have an impact on safety analysis. The effort has employed both literature searches and data correlation to provide an encyclopedia of tank waste properties in forms that are relatively easy to use in modeling waste behavior. These properties submodels will be used in other tasks to simulate waste behavior in the tanks. Density, viscosity, yield strength, surface tension, heat capacity, thermal conductivity, salt solubility, and ammonia and water vapor pressures were compiled for solutions and suspensions of sodium nitrate and other salts (where data were available), and the data were correlated by linear regression. In addition, data for simulated Hanford waste tank supernatant were correlated to provide density, solubility, surface tension, and vapor pressure submodels for multi-component solutions containing sodium hydroxide, sodium nitrate, sodium nitrite, and sodium aluminate
Universality of correlation functions in random matrix models of QCD
International Nuclear Information System (INIS)
Jackson, A.D.; Sener, M.K.; Verbaarschot, J.J.M.
1997-01-01
We demonstrate the universality of the spectral correlation functions of a QCD inspired random matrix model that consists of a random part having the chiral structure of the QCD Dirac operator and a deterministic part which describes a schematic temperature dependence. We calculate the correlation functions analytically using the technique of Itzykson-Zuber integrals for arbitrary complex supermatrices. An alternative exact calculation for arbitrary matrix size is given for the special case of zero temperature, and we reproduce the well-known Laguerre kernel. At finite temperature, the microscopic limit of the correlation functions are calculated in the saddle-point approximation. The main result of this paper is that the microscopic universality of correlation functions is maintained even though unitary invariance is broken by the addition of a deterministic matrix to the ensemble. (orig.)
Double parton correlations in Light-Front constituent quark models
Directory of Open Access Journals (Sweden)
Rinaldi Matteo
2015-01-01
Full Text Available Double parton distribution functions (dPDF represent a tool to explore the 3D proton structure. They can be measured in high energy proton-proton and proton nucleus collisions and encode information on how partons inside a proton are correlated among each other. dPFDs are studied here in the valence quark region, by means of a constituent quark model, where two particle correlations are present without any additional prescription. This framework allows to understand the dynamical origin of the correlations and to clarify which, among the features of the results, are model independent. Use will be made of a relativistic light-front scheme, able to overcome some drawbacks of the previous calculation. Transverse momentum correlations, due to the exact treatment of the boosts, are predicted and analyzed. The role of spin correlations is also shown. Due to the covariance of the approach, some symmetries of the dPDFs are seen unambigously. For the valence sector, also the study of the QCD evolution of the model results, which can be performed safely thanks to the property of good support, has been also completed.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei
2017-11-08
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix into variance and correlation matrices. The highlight is that the correlations are represented as products of vectors on unit spheres. We propose a variety of distributions on spheres (e.g. the squared-Dirichlet distribution) to induce flexible prior distributions for covariance matrices that go beyond the commonly used inverse-Wishart prior. To handle the intractability of the resulting posterior, we introduce the adaptive $\\\\Delta$-Spherical Hamiltonian Monte Carlo. We also extend our structured framework to dynamic cases and introduce unit-vector Gaussian process priors for modeling the evolution of correlation among multiple time series. Using an example of Normal-Inverse-Wishart problem, a simulated periodic process, and an analysis of local field potential data (collected from the hippocampus of rats performing a complex sequence memory task), we demonstrated the validity and effectiveness of our proposed framework for (dynamic) modeling covariance and correlation matrices.
Electron correlations in narrow energy bands: modified polar model approach
Directory of Open Access Journals (Sweden)
L. Didukh
2008-09-01
Full Text Available The electron correlations in narrow energy bands are examined within the framework of the modified form of polar model. This model permits to analyze the effect of strong Coulomb correlation, inter-atomic exchange and correlated hopping of electrons and explain some peculiarities of the properties of narrow-band materials, namely the metal-insulator transition with an increase of temperature, nonlinear concentration dependence of Curie temperature and peculiarities of transport properties of electronic subsystem. Using a variant of generalized Hartree-Fock approximation, the single-electron Green's function and quasi-particle energy spectrum of the model are calculated. Metal-insulator transition with the change of temperature is investigated in a system with correlated hopping. Processes of ferromagnetic ordering stabilization in the system with various forms of electronic DOS are studied. The static conductivity and effective spin-dependent masses of current carriers are calculated as a function of electron concentration at various DOS forms. The correlated hopping is shown to cause the electron-hole asymmetry of transport and ferromagnetic properties of narrow band materials.
Modeling Correlation Effects in Nickelates with Slave Particles
Georgescu, Alexandru Bogdan; Ismail-Beigi, Sohrab
Nickelate interfaces display interesting electronic properties including orbital ordering similar to that of cuprate superconductors and thickness dependent metal-insulator transitions. One-particle band theory calculations do not include dynamic localized correlation effects on the nickel sites and thus often incorrectly predict metallic systems or incorrect ARPES spectra. Building on two previous successful slave-particle treatments of local correlations, we present a generalized slave-particle method that includes prior models and allows us to produce new intermediate models. The computational efficiency of these slave-boson methods means that one can readily study correlation effects in complex heterostructures. We show some predictions of these methods for the electronic structure of bulk and thin film nickelates. Work supported by NSF Grant MRSEC DMR-1119826.
K-correlation power spectral density and surface scatter model
Dittman, Michael G.
2006-08-01
The K-Correlation or ABC model for surface power spectral density (PSD) and BRDF has been around for years. Eugene Church and John Stover, in particular, have published descriptions of its use in describing smooth surfaces. The model has, however, remained underused in the optical analysis community partially due to the lack of a clear summary tailored toward that application. This paper provides the K-Correlation PSD normalized to σ(λ) and BRDF normalized to TIS(σ,λ) in a format intended to be used by stray light analysts. It is hoped that this paper will promote use of the model by analysts and its incorporation as a standard tool into stray light modeling software.
Universal correlators for multi-arc complex matrix models
International Nuclear Information System (INIS)
Akemann, G.
1997-01-01
The correlation functions of the multi-arc complex matrix model are shown to be universal for any finite number of arcs. The universality classes are characterized by the support of the eigenvalue density and are conjectured to fall into the same classes as the ones recently found for the Hermitian model. This is explicitly shown to be true for the case of two arcs, apart from the known result for one arc. The basic tool is the iterative solution of the loop equation for the complex matrix model with multiple arcs, which provides all multi-loop correlators up to an arbitrary genus. Explicit results for genus one are given for any number of arcs. The two-arc solution is investigated in detail, including the double-scaling limit. In addition universal expressions for the string susceptibility are given for both the complex and Hermitian model. (orig.)
Process correlation analysis model for process improvement identification.
Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong
2014-01-01
Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.
Correlation effects in the Ising model in an external field
International Nuclear Information System (INIS)
Borges, H.E.; Silva, P.R.
1983-01-01
The thermodynamic properties of the spin-1/2 Ising Model in an external field are evaluated through the use of the exponential differential operator method and Callen's exact relations. The correlations effects are treated in a phenomenological approach and the results are compared with other treatments. (Author) [pt
A shell-model calculation in terms of correlated subsystems
International Nuclear Information System (INIS)
Boisson, J.P.; Silvestre-Brac, B.
1979-01-01
A method for solving the shell-model equations in terms of a basis which includes correlated subsystems is presented. It is shown that the method allows drastic truncations of the basis to be made. The corresponding calculations are easy to perform and can be carried out rapidly
Modelling Bose-Einstein correlations at LEP-2
International Nuclear Information System (INIS)
Loennblad, L.
1998-01-01
Some pros and cons of different strategies for modelling Bose-Einstein correlations in event generators for fully hadronic WW events at LEP-2 are discussed. A few new algorithms based on shifting final-state momenta of identical bosons in WW events generated by PYTHIA are also presented and the resulting predictions for the effects on the W mass measurement are discussed. (author)
Density-correlation functions in Calogero-Sutherland models
International Nuclear Information System (INIS)
Minahan, J.A.; Polychronakos, A.P.
1994-01-01
Using arguments from two-dimensional Yang-Mills theory and the collective coordinate formulation of the Calogero-Sutherland model, we conjecture the dynamical density-correlation function for coupling l and 1/l, where l is an integer. We present overwhelming evidence that the conjecture is indeed correct
Density correlation functions in Calogero-Sutherland models
Minahan, Joseph A.; Joseph A Minahan; Alexios P Polychronakos
1994-01-01
Using arguments from two dimensional Yang-Mills theory and the collective coordinate formulation of the Calogero-Sutherland model, we conjecture the dynamical density correlation function for coupling l and 1/l, where l is an integer. We present overwhelming evidence that the conjecture is indeed correct.
Model-independent analysis with BPM correlation matrices
International Nuclear Information System (INIS)
Irwin, J.; Wang, C.X.; Yan, Y.T.; Bane, K.; Cai, Y.; Decker, F.; Minty, M.; Stupakov, G.; Zimmermann, F.
1998-06-01
The authors discuss techniques for Model-Independent Analysis (MIA) of a beamline using correlation matrices of physical variables and Singular Value Decomposition (SVD) of a beamline BPM matrix. The beamline matrix is formed from BPM readings for a large number of pulses. The method has been applied to the Linear Accelerator of the SLAC Linear Collider (SLC)
A model for correlating burnout in round tubes
International Nuclear Information System (INIS)
Kirby, G.J.
1966-09-01
A model is presented which represents the film flow rate in the climbing film regime of boiling two phase flow. By calculating the dryout point burnout heat fluxes for round tubes both uniformly and non-uniformly heated axially have been predicted with accuracies as good as the best empirical correlations. The model is used to investigate the effect of varying flux profile as well as the other system describing parameters. (author)
The Potts model and flows. 1. The pair correlation function
International Nuclear Information System (INIS)
Essam, J.W.; Tsallis, C.
1985-01-01
It is shown that the partition function for the lambda-state Potts model with pair-interactions is related to the expected number of integer mod-lambda flows in a percolation model. The relation is generalised to the pair correlation function. The resulting high temperature expansion coefficients are shown to be the flow polynomials of graph theory. An observation of Tsallis and Levy concerning the equivalent transmissivity of a cluster is also proved. (Author) [pt
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Ter¨asvirta (2005) by including...... another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition......, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. The model is applied to a selection of world stock indices, and it is found that time is an important factor affecting...
Hall Thruster Thermal Modeling and Test Data Correlation
Myers, James; Kamhawi, Hani; Yim, John; Clayman, Lauren
2016-01-01
The life of Hall Effect thrusters are primarily limited by plasma erosion and thermal related failures. NASA Glenn Research Center (GRC) in cooperation with the Jet Propulsion Laboratory (JPL) have recently completed development of a Hall thruster with specific emphasis to mitigate these limitations. Extending the operational life of Hall thursters makes them more suitable for some of NASA's longer duration interplanetary missions. This paper documents the thermal model development, refinement and correlation of results with thruster test data. Correlation was achieved by minimizing uncertainties in model input and recognizing the relevant parameters for effective model tuning. Throughout the thruster design phase the model was used to evaluate design options and systematically reduce component temperatures. Hall thrusters are inherently complex assemblies of high temperature components relying on internal conduction and external radiation for heat dispersion and rejection. System solutions are necessary in most cases to fully assess the benefits and/or consequences of any potential design change. Thermal model correlation is critical since thruster operational parameters can push some components/materials beyond their temperature limits. This thruster incorporates a state-of-the-art magnetic shielding system to reduce plasma erosion and to a lesser extend power/heat deposition. Additionally a comprehensive thermal design strategy was employed to reduce temperatures of critical thruster components (primarily the magnet coils and the discharge channel). Long term wear testing is currently underway to assess the effectiveness of these systems and consequently thruster longevity.
Sample selection and taste correlation in discrete choice transport modelling
DEFF Research Database (Denmark)
Mabit, Stefan Lindhard
2008-01-01
explain counterintuitive results in value of travel time estimation. However, the results also point at the difficulty of finding suitable instruments for the selection mechanism. Taste heterogeneity is another important aspect of discrete choice modelling. Mixed logit models are designed to capture...... the question for a broader class of models. It is shown that the original result may be somewhat generalised. Another question investigated is whether mode choice operates as a self-selection mechanism in the estimation of the value of travel time. The results show that self-selection can at least partly...... of taste correlation in willingness-to-pay estimation are presented. The first contribution addresses how to incorporate taste correlation in the estimation of the value of travel time for public transport. Given a limited dataset the approach taken is to use theory on the value of travel time as guidance...
Higher genus correlators for the complex matrix model
International Nuclear Information System (INIS)
Ambjorn, J.; Kristhansen, C.F.; Makeenko, Y.M.
1992-01-01
In this paper, the authors describe an iterative scheme which allows us to calculate any multi-loop correlator for the complex matrix model to any genus using only the first in the chain of loop equations. The method works for a completely general potential and the results contain no explicit reference to the couplings. The genus g contribution to the m-loop correlator depends on a finite number of parameters, namely at most 4g - 2 + m. The authors find the generating functional explicitly up to genus three. The authors show as well that the model is equivalent to an external field problem for the complex matrix model with a logarithmic potential
Long-range correlations in Boltzmann-Langevin model
International Nuclear Information System (INIS)
Ayik, S.
1994-01-01
The average phase-space density described by the Boltzmann-Langevin model can largely deviate from the one provided by the Boltzmann-Uhling-Uhlenbeck model, due to the non-linear evolution of density fluctuations. This aspect is investigated for long-wavelength, small density fluctuations in the framework of a memory incorporated Boltzmann-Langevin model. It is shown that the correlations associated with density fluctuations yield a collision term describing coupling between the collective vibrations and the single-particle degrees of freedom, which may play an important role in damping of collective motion in both the stable and unstable regions. (orig.)
Distributing Correlation Coefficients of Linear Structure-Activity/Property Models
Directory of Open Access Journals (Sweden)
Sorana D. BOLBOACA
2011-12-01
Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.
Uncertainty importance measure for models with correlated normal variables
International Nuclear Information System (INIS)
Hao, Wenrui; Lu, Zhenzhou; Wei, Pengfei
2013-01-01
In order to explore the contributions by correlated input variables to the variance of the model output, the contribution decomposition of the correlated input variables based on Mara's definition is investigated in detail. By taking the quadratic polynomial output without cross term as an illustration, the solution of the contribution decomposition is derived analytically using the statistical inference theory. After the correction of the analytical solution is validated by the numerical examples, they are employed to two engineering examples to show their wide application. The derived analytical solutions can directly be used to recognize the contributions by the correlated input variables in case of the quadratic or linear polynomial output without cross term, and the analytical inference method can be extended to the case of higher order polynomial output. Additionally, the origins of the interaction contribution of the correlated inputs are analyzed, and the comparisons of the existing contribution indices are completed, on which the engineer can select the suitable indices to know the necessary information. At last, the degeneration of the correlated inputs to the uncorrelated ones and some computational issues are discussed in concept
Approximate models for the analysis of laser velocimetry correlation functions
International Nuclear Information System (INIS)
Robinson, D.P.
1981-01-01
Velocity distributions in the subchannels of an eleven pin test section representing a slice through a Fast Reactor sub-assembly were measured with a dual beam laser velocimeter system using a Malvern K 7023 digital photon correlator for signal processing. Two techniques were used for data reduction of the correlation function to obtain velocity and turbulence values. Whilst both techniques were in excellent agreement on the velocity, marked discrepancies were apparent in the turbulence levels. As a consequence of this the turbulence data were not reported. Subsequent investigation has shown that the approximate technique used as the basis of Malvern's Data Processor 7023V is restricted in its range of application. In this note alternative approximate models are described and evaluated. The objective of this investigation was to develop an approximate model which could be used for on-line determination of the turbulence level. (author)
Describing a Strongly Correlated Model System with Density Functional Theory.
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.
Angular correlations in top quark decays in standard model extensions
International Nuclear Information System (INIS)
Batebi, S.; Etesami, S. M.; Mohammadi-Najafabadi, M.
2011-01-01
The CMS Collaboration at the CERN LHC has searched for the t-channel single top quark production using the spin correlation of the t-channel. The signal extraction and cross section measurement rely on the angular distribution of the charged lepton in the top quark decays, the angle between the charged lepton momentum and top spin in the top rest frame. The behavior of the angular distribution is a distinct slope for the t-channel single top (signal) while it is flat for the backgrounds. In this Brief Report, we investigate the contributions which this spin correlation may receive from a two-Higgs doublet model, a top-color assisted technicolor (TC2) and the noncommutative extension of the standard model.
Spin-spin correlations in the tt'-Hubbard model
International Nuclear Information System (INIS)
Husslein, T.; Newns, D.M.; Mattutis, H.G.; Pattnaik, P.C.; Morgenstern, I.; Singer, J.M.; Fettes, W.; Baur, C.
1994-01-01
We present calculations of the tt'-Hubbard model using Quantum Monte Carlo techniques. The parameters are chosen so that the van Hove Singularity in the density of states and the Fermi level coincide. We study the behaviour of the system with increasing Hubbard interaction U. Special emphasis is on the spin-spin correlation (SSC). Unusual behaviour for large U is observed there and in the momentum distribution function (n(q)). (orig.)
Genomic Model with Correlation Between Additive and Dominance Effects.
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
Proton-neutron correlations in a broken-pair model
International Nuclear Information System (INIS)
Akkermans, J.N.L.
1981-01-01
In this thesis nuclear-structure calculations are reported which were performed with the broken-pair model. The model which is developed, is an extension of existing broken-pair models in so far that it includes both proton and neutron valence pairs. The relevant formalisms are presented. In contrast to the number-non-conserving model, a proton-neutron broken-pair model is well suited to study the correlations which are produced by the proton-neutron interaction. It is shown that the proton-neutron force has large matrix elements which mix the proton- with neutron broken-pair configurations. This occurs especially for Jsup(PI)=2 + and 3 - pairs. This property of the proton-neutron force is used to improve the spectra of single-closed shell nuclei, where particle-hole excitations of the closed shell are a special case of broken-pair configurations. Using Kr and Te isotopes it is demonstrated that the proton-neutron force gives rise to correlated pair structures, which remain remarkably constant with varying nucleon numbers. (Auth.)
Correlation-based Transition Modeling for External Aerodynamic Flows
Medida, Shivaji
Conventional turbulence models calibrated for fully turbulent boundary layers often over-predict drag and heat transfer on aerodynamic surfaces with partially laminar boundary layers. A robust correlation-based model is developed for use in Reynolds-Averaged Navier-Stokes simulations to predict laminar-to-turbulent transition onset of boundary layers on external aerodynamic surfaces. The new model is derived from an existing transition model for the two-equation k-omega Shear Stress Transport (SST) turbulence model, and is coupled with the one-equation Spalart-Allmaras (SA) turbulence model. The transition model solves two transport equations for intermittency and transition momentum thickness Reynolds number. Experimental correlations and local mean flow quantities are used in the model to account for effects of freestream turbulence level and pressure gradients on transition onset location. Transition onset is triggered by activating intermittency production using a vorticity Reynolds number criterion. In the new model, production and destruction terms of the intermittency equation are modified to improve consistency in the fully turbulent boundary layer post-transition onset, as well as ensure insensitivity to freestream eddy viscosity value specified in the SA model. In the original model, intermittency was used to control production and destruction of turbulent kinetic energy. Whereas, in the new model, only the production of eddy viscosity in SA model is controlled, and the destruction term is not altered. Unlike the original model, the new model does not use an additional correction to intermittency for separation-induced transition. Accuracy of drag predictions are improved significantly with the use of the transition model for several two-dimensional single- and multi-element airfoil cases over a wide range of Reynolds numbers. The new model is able to predict the formation of stable and long laminar separation bubbles on low-Reynolds number airfoils that
Copula-based modeling of degree-correlated networks
International Nuclear Information System (INIS)
Raschke, Mathias; Schläpfer, Markus; Trantopoulos, Konstantinos
2014-01-01
Dynamical processes on complex networks such as information exchange, innovation diffusion, cascades in financial networks or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree–degree correlations. Here, we introduce the concept of copulas in order to generate random networks with an arbitrary degree distribution and a rich a priori degree–degree correlation (or ‘association’) structure. The accuracy of the proposed formalism and corresponding algorithm is numerically confirmed, while the method is tested on a real-world network of yeast protein–protein interactions. The derived network ensembles can be systematically deployed as proper null models, in order to unfold the complex interplay between the topology of real-world networks and the dynamics on top of them. (paper)
Modeling binary correlated responses using SAS, SPSS and R
Wilson, Jeffrey R
2015-01-01
Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Researchers and graduate stu...
Rapidity correlations at fixed multiplicity in cluster emission models
Berger, M C
1975-01-01
Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...
Correlation mediated superconductivity in a 'High-Tsub(c)' model
International Nuclear Information System (INIS)
Long, M.W.
1987-08-01
A simple model is presented to account for the High-Tsub(c) perovskite superconductors. The superconducting mechanism is purely electronic and comes from local Hubbard correlations. The model comprises a Hubbard model for the copper sites with a single particle oxygen band between the two copper Hubbard bands. The electrons move only between nearest neighbour atoms which are of different types. Using two very different approximation schemes, one related to 'Slave-Boson' mean field theory and the other based on an exact local Fermion transformation, the possibility of copper-oxygen or a mixture of copper-oxygen and oxygen-oxygen pairing is shown. The author believes that the most promising situation for superconductivity is with the Oxygen band over half-filled and closer in energy to the lower Hubbard band. (author)
FASTSAT-HSV01 Thermal Math Model Correlation
McKelvey, Callie
2011-01-01
This paper summarizes the thermal math model correlation effort for the Fast Affordable Science and Technology SATellite (FASTSAT-HSV01), which was designed, built and tested by NASA's Marshall Space Flight Center (MSFC) and multiple partners. The satellite launched in November 2010 on a Minotaur IV rocket from the Kodiak Launch Complex in Kodiak, Alaska. It carried three Earth science experiments and two technology demonstrations into a low Earth circular orbit with an inclination of 72deg and an altitude of 650 kilometers. The mission has been successful to date with science experiment activities still taking place daily. The thermal control system on this spacecraft was a passive design relying on thermo-optical properties and six heaters placed on specific components. Flight temperature data is being recorded every minute from the 48 Resistance Temperature Devices (RTDs) onboard the satellite structure and many of its avionics boxes. An effort has been made to correlate the thermal math model to the flight temperature data using Cullimore and Ring's Thermal Desktop and by obtaining Earth and Sun vector data from the Attitude Control System (ACS) team to create an "as-flown" orbit. Several model parameters were studied during this task to understand the spacecraft's sensitivity to these changes. Many "lessons learned" have been noted from this activity that will be directly applicable to future small satellite programs.
Multimodal correlation and intraoperative matching of virtual models in neurosurgery
Ceresole, Enrico; Dalsasso, Michele; Rossi, Aldo
1994-01-01
The multimodal correlation between different diagnostic exams, the intraoperative calibration of pointing tools and the correlation of the patient's virtual models with the patient himself, are some examples, taken from the biomedical field, of a unique problem: determine the relationship linking representation of the same object in different reference frames. Several methods have been developed in order to determine this relationship, among them, the surface matching method is one that gives the patient minimum discomfort and the errors occurring are compatible with the required precision. The surface matching method has been successfully applied to the multimodal correlation of diagnostic exams such as CT, MR, PET and SPECT. Algorithms for automatic segmentation of diagnostic images have been developed to extract the reference surfaces from the diagnostic exams, whereas the surface of the patient's skull has been monitored, in our approach, by means of a laser sensor mounted on the end effector of an industrial robot. An integrated system for virtual planning and real time execution of surgical procedures has been realized.
Correlation of breast image alignment using biomechanical modelling
Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.
2009-02-01
Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.
Two general models that generate long range correlation
Gan, Xiaocong; Han, Zhangang
2012-06-01
In this paper we study two models that generate sequences with LRC (long range correlation). For the IFT (inverse Fourier transform) model, our conclusion is the low frequency part leads to LRC, while the high frequency part tends to eliminate it. Therefore, a typical method to generate a sequence with LRC is multiplying the spectrum of a white noise sequence by a decaying function. A special case is analyzed: the linear combination of a smooth curve and a white noise sequence, in which the DFA plot consists of two line segments. For the patch model, our conclusion is long subsequences leads to LRC, while short subsequences tend to eliminate it. Therefore, we can generate a sequence with LRC by using a fat-tailed PDF (probability distribution function) of the length of the subsequences. A special case is also analyzed: if a patch model with long subsequences is mixed with a white noise sequence, the DFA plot will consist of two line segments. We have checked known models and actual data, and found they are all consistent with this study.
A new Expert Finding model based on Term Correlation Matrix
Directory of Open Access Journals (Sweden)
Ehsan Pornour
2015-09-01
Full Text Available Due to the enormous volume of unstructured information available on the Web and inside organization, finding an answer to the knowledge need in a short time is difficult. For this reason, beside Search Engines which don’t consider users individual characteristics, Recommender systems were created which use user’s previous activities and other individual characteristics to help users find needed knowledge. Recommender systems usage is increasing every day. Expert finder systems also by introducing expert people instead of recommending information to users have provided this facility for users to ask their questions form experts. Having relation with experts not only causes information transition, but also with transferring experiences and inception causes knowledge transition. In this paper we used university professors academic resume as expert people profile and then proposed a new expert finding model that recommends experts to users query. We used Term Correlation Matrix, Vector Space Model and PageRank algorithm and proposed a new hybrid model which outperforms conventional methods. This model can be used in internet environment, organizations and universities that experts have resume dataset.
A marked correlation function for constraining modified gravity models
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.
A marked correlation function for constraining modified gravity models
Energy Technology Data Exchange (ETDEWEB)
White, Martin, E-mail: mwhite@berkeley.edu [Department of Physics, University of California, Berkeley, CA 94720 (United States)
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.
Analysis of correlations between sites in models of protein sequences
International Nuclear Information System (INIS)
Giraud, B.G.; Lapedes, A.; Liu, L.C.
1998-01-01
A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society
Granular filtration for airborne particles : correlation between experiments and models
Energy Technology Data Exchange (ETDEWEB)
Golshahi, L.; Tan, Z. [Calgary Univ., AB (Canada). Schulich School of Engineering, Mechanical and Manufacturing Dept.; Abedi, J. [Calgary Univ., AB (Canada). Schulich School of Engineering, Chemical and Petroleum Engineering Dept.
2009-10-15
A new design for a packed bed granular filter was presented. The cylindrical packed bed was designed to filter particles in the range of approximately 10 nm to 15 {mu}m in diameter in different kinetic conditions and configurations. The aim of the study was to develop a precise empirical model to predict the filtration efficiency of the packed beds. A collision-type atomizer was used to generate polydisperse sodium chloride aerosol particles. The effect of flow rates was studied using a thermal mass flow meter. A regression analysis technique was used to determine the correlation between single granule and total packed bed efficiency for the entire granular filter. The experimental data were then compared with results obtained from the theoretical analysis. The least square method was used to correlate experimental data and to develop generalized equations for single granule efficiency. The study showed that the granular filter media has a high filtration efficiency for both micron and submicron particles. It was concluded that the effect of media thickness was more significant at higher flow rates than at lower flow rates. 10 refs., 3 figs.
Twist operator correlation functions in O(n) loop models
International Nuclear Information System (INIS)
Simmons, Jacob J H; Cardy, John
2009-01-01
Using conformal field theoretic methods we calculate correlation functions of geometric observables in the loop representation of the O(n) model at the critical point. We focus on correlation functions containing twist operators, combining these with anchored loops, boundaries with SLE processes and with double SLE processes. We focus further upon n = 0, representing self-avoiding loops, which corresponds to a logarithmic conformal field theory (LCFT) with c = 0. In this limit the twist operator plays the role of a 0-weight indicator operator, which we verify by comparison with known examples. Using the additional conditions imposed by the twist operator null states, we derive a new explicit result for the probabilities that an SLE 8/3 winds in various ways about two points in the upper half-plane, e.g. that the SLE passes to the left of both points. The collection of c = 0 logarithmic CFT operators that we use deriving the winding probabilities is novel, highlighting a potential incompatibility caused by the presence of two distinct logarithmic partners to the stress tensor within the theory. We argue that both partners do appear in the theory, one in the bulk and one on the boundary and that the incompatibility is resolved by restrictive bulk-boundary fusion rules
MARS CODE MANUAL VOLUME V: Models and Correlations
International Nuclear Information System (INIS)
Chung, Bub Dong; Bae, Sung Won; Lee, Seung Wook; Yoon, Churl; Hwang, Moon Kyu; Kim, Kyung Doo; Jeong, Jae Jun
2010-02-01
Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-Of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This models and correlations manual provides a complete list of detailed information of the thermal-hydraulic models used in MARS, so that this report would be very useful for the code users. The overall structure of the manual is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS3.1. MARS3.1 development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible
Six-Tube Freezable Radiator Testing and Model Correlation
Lilibridge, Sean T.; Navarro, Moses
2012-01-01
Freezable Radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft?s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recov ering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TM) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested: MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.
Correlation functions of the Ising model and the eight-vertex model
International Nuclear Information System (INIS)
Ko, L.F.
1986-01-01
Calculations for the two-point correlation functions in the scaling limit for two statistical models are presented. In Part I, the Ising model with a linear defect is studied for T T/sub c/. The transfer matrix method of Onsager and Kaufman is used. The energy-density correlation is given by functions related to the modified Bessel functions. The dispersion expansion for the spin-spin correlation functions are derived. The dominant behavior for large separations at T not equal to T/sub c/ is extracted. It is shown that these expansions lead to systems of Fredholm integral equations. In Part II, the electric correlation function of the eight-vertex model for T < T/sub c/ is studied. The eight vertex model decouples to two independent Ising models when the four spin coupling vanishes. To first order in the four-spin coupling, the electric correlation function is related to a three-point function of the Ising model. This relation is systematically investigated and the full dispersion expansion (to first order in four-spin coupling) is obtained. The results is a new kind of structure which, unlike those of many solvable models, is apparently not expressible in terms of linear integral equations
Gluon field strength correlation functions within a constrained instanton model
International Nuclear Information System (INIS)
Dorokhov, A.E.; Esaibegyan, S.V.; Maximov, A.E.; Mikhailov, S.V.
2000-01-01
We suggest a constrained instanton (CI) solution in the physical QCD vacuum which is described by large-scale vacuum field fluctuations. This solution decays exponentially at large distances. It is stable only if the interaction of the instanton with the background vacuum field is small and additional constraints are introduced. The CI solution is explicitly constructed in the ansatz form, and the two-point vacuum correlator of the gluon field strengths is calculated in the framework of the effective instanton vacuum model. At small distances the results are qualitatively similar to the single instanton case; in particular, the D 1 invariant structure is small, which is in agreement with the lattice calculations. (orig.)
Two-point boundary correlation functions of dense loop models
Directory of Open Access Journals (Sweden)
Alexi Morin-Duchesne, Jesper Lykke Jacobsen
2018-06-01
Full Text Available We investigate six types of two-point boundary correlation functions in the dense loop model. These are defined as ratios $Z/Z^0$ of partition functions on the $m\\times n$ square lattice, with the boundary condition for $Z$ depending on two points $x$ and $y$. We consider: the insertion of an isolated defect (a and a pair of defects (b in a Dirichlet boundary condition, the transition (c between Dirichlet and Neumann boundary conditions, and the connectivity of clusters (d, loops (e and boundary segments (f in a Neumann boundary condition. For the model of critical dense polymers, corresponding to a vanishing loop weight ($\\beta = 0$, we find determinant and pfaffian expressions for these correlators. We extract the conformal weights of the underlying conformal fields and find $\\Delta = -\\frac18$, $0$, $-\\frac3{32}$, $\\frac38$, $1$, $\\tfrac \\theta \\pi (1+\\tfrac{2\\theta}\\pi$, where $\\theta$ encodes the weight of one class of loops for the correlator of type f. These results are obtained by analysing the asymptotics of the exact expressions, and by using the Cardy-Peschel formula in the case where $x$ and $y$ are set to the corners. For type b, we find a $\\log|x-y|$ dependence from the asymptotics, and a $\\ln (\\ln n$ term in the corner free energy. This is consistent with the interpretation of the boundary condition of type b as the insertion of a logarithmic field belonging to a rank two Jordan cell. For the other values of $\\beta = 2 \\cos \\lambda$, we use the hypothesis of conformal invariance to predict the conformal weights and find $\\Delta = \\Delta_{1,2}$, $\\Delta_{1,3}$, $\\Delta_{0,\\frac12}$, $\\Delta_{1,0}$, $\\Delta_{1,-1}$ and $\\Delta_{\\frac{2\\theta}\\lambda+1,\\frac{2\\theta}\\lambda+1}$, extending the results of critical dense polymers. With the results for type f, we reproduce a Coulomb gas prediction for the valence bond entanglement entropy of Jacobsen and Saleur.
International Nuclear Information System (INIS)
Clifton, P.M.
1985-03-01
This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis
Biochemical correlates in an animal model of depression
International Nuclear Information System (INIS)
Johnson, J.O.
1986-01-01
A valid animal model of depression was used to explore specific adrenergic receptor differences between rats exhibiting aberrant behavior and control groups. Preliminary experiments revealed a distinct upregulation of hippocampal beta-receptors (as compared to other brain regions) in those animals acquiring a response deficit as a result of exposure to inescapable footshock. Concurrent studies using standard receptor binding techniques showed no large changes in the density of alpha-adrenergic, serotonergic, or dopaminergic receptor densities. This led to the hypothesis that the hippocampal beta-receptor in responses deficient animals could be correlated with the behavioral changes seen after exposure to the aversive stimulus. Normalization of the behavior through the administration of antidepressants could be expected to reverse the biochemical changes if these are related to the mechanism of action of antidepressant drugs. This study makes three important points: (1) there is a relevant biochemical change in the hippocampus of response deficient rats which occurs in parallel to a well-defined behavior, (2) the biochemical and behavioral changes are normalized by antidepressant treatments exhibiting both serotonergic and adrenergic mechanisms of action, and (3) the mode of action of antidepressants in this model is probably a combination of serotonergic and adrenergic influences modulating the hippocampal beta-receptor. These results are discussed in relation to anatomical and biochemical aspects of antidepressant action
Modal Analysis and Model Correlation of the Mir Space Station
Kim, Hyoung M.; Kaouk, Mohamed
2000-01-01
This paper will discuss on-orbit dynamic tests, modal analysis, and model refinement studies performed as part of the Mir Structural Dynamics Experiment (MiSDE). Mir is the Russian permanently manned Space Station whose construction first started in 1986. The MiSDE was sponsored by the NASA International Space Station (ISS) Phase 1 Office and was part of the Shuttle-Mir Risk Mitigation Experiment (RME). One of the main objectives for MiSDE is to demonstrate the feasibility of performing on-orbit modal testing on large space structures to extract modal parameters that will be used to correlate mathematical models. The experiment was performed over a one-year span on the Mir-alone and Mir with a Shuttle docked. A total of 45 test sessions were performed including: Shuttle and Mir thruster firings, Shuttle-Mir and Progress-Mir dockings, crew exercise and pushoffs, and ambient noise during night-to-day and day-to-night orbital transitions. Test data were recorded with a variety of existing and new instrumentation systems that included: the MiSDE Mir Auxiliary Sensor Unit (MASU), the Space Acceleration Measurement System (SAMS), the Russian Mir Structural Dynamic Measurement System (SDMS), the Mir and Shuttle Inertial Measurement Units (IMUs), and the Shuttle payload bay video cameras. Modal analysis was performed on the collected test data to extract modal parameters, i.e. frequencies, damping factors, and mode shapes. A special time-domain modal identification procedure was used on free-decay structural responses. The results from this study show that modal testing and analysis of large space structures is feasible within operational constraints. Model refinements were performed on both the Mir alone and the Shuttle-Mir mated configurations. The design sensitivity approach was used for refinement, which adjusts structural properties in order to match analytical and test modal parameters. To verify the refinement results, the analytical responses calculated using
Correlation model to analyze dependent failures for probabilistic risk assessment
International Nuclear Information System (INIS)
Dezfuli, H.
1985-01-01
A methodology is formulated to study the dependent (correlated) failures of various abnormal events in nuclear power plants. This methodology uses correlation analysis is a means for predicting and quantifying the dependent failures. Appropriate techniques are also developed to incorporate the dependent failure in quantifying fault trees and accident sequences. The uncertainty associated with each estimation in all of the developed techniques is addressed and quantified. To identify the relative importance of the degree of dependency (correlation) among events and to incorporate these dependencies in the quantification phase of PRA, the interdependency between a pair of events in expressed with the aid of the correlation coefficient. For the purpose of demonstrating the methodology, the data base used in the Accident Sequence Precursor Study (ASP) was adopted and simulated to obtain distributions for the correlation coefficients. A computer program entitled Correlation Coefficient Generator (CCG) was developed to generate a distribution for each correlation coefficient. The method of bootstrap technique was employed in the CCG computer code to determine confidence limits of the estimated correlation coefficients. A second computer program designated CORRELATE was also developed to obtain probability intervals for both fault trees and accident sequences with statistically correlated failure data
Effect of Correlated Noises in a Genetic Model
International Nuclear Information System (INIS)
Li, Zhang; Li, Cao
2010-01-01
The Stratonovich stochastic differential equation is used to analyze genotype selection in the presence of correlated Gaussian white noises. We study the steady state properties of the genotype selection and discuss the effects of the correlated noises. It is found that the degree of correlation of the noises can be used to select one type of genes from another type of mixing genes. The strong selection of genes caused by a large value of multiplicative noise intensity can be weakened by the intensive negative correlation. (general)
Projection of Anthropometric Correlation for Virtual Population Modelling
DEFF Research Database (Denmark)
Rasmussen, John; Waagepetersen, Rasmus Plenge; Rasmussen, Kasper Pihl
2018-01-01
, and therefore the correlations between parameters, are not accessible. This problem is solved by projecting correlation from a data set for which raw data are provided. The method is tested and validated by generation of pseudo females from males in the ANSUR anthropometric dataset. Results show...
Multivariate η-μ fading distribution with arbitrary correlation model
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.
Forward-backward correlations in pp interactions in a dual model
International Nuclear Information System (INIS)
Fialkowsky, K.; Kotanski, A.; Uniwersytet Jagiellonski, Krakow
1982-01-01
Forward-backward correlations in lepton and hadron induced processes are compared according to the dual model. It is indicated that the effect of the chain energy spread in hadron processes is important. After including this effect the model is shown to explain the forward-backward correlations in pp data assuming no dynamical correlations within a single chain. (orig.)
Correlation between the model accuracy and model-based SOC estimation
International Nuclear Information System (INIS)
Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing
2017-01-01
State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.
Coherent manipulation of spin correlations in the Hubbard model
Wurz, N.; Chan, C. F.; Gall, M.; Drewes, J. H.; Cocchi, E.; Miller, L. A.; Pertot, D.; Brennecke, F.; Köhl, M.
2018-05-01
We coherently manipulate spin correlations in a two-component atomic Fermi gas loaded into an optical lattice using spatially and time-resolved Ramsey spectroscopy combined with high-resolution in situ imaging. This technique allows us not only to imprint spin patterns but also to probe the static magnetic structure factor at an arbitrary wave vector, in particular, the staggered structure factor. From a measurement along the diagonal of the first Brillouin zone of the optical lattice, we determine the magnetic correlation length and the individual spatial spin correlators. At half filling, the staggered magnetic structure factor serves as a sensitive thermometer, which we employ to study the equilibration in the spin and density sector during a slow quench of the lattice depth.
The quark-recombination model and correlations between hard and soft hadronic processes
International Nuclear Information System (INIS)
Ranft, J.
1978-07-01
Proceeding from the fact that quark and gluon recombination models make definite predictions for correlations between hard and soft processes, the following experiments are briefly discussed: (i) correlations between deep inelastic antineutrino-proton scattering and particle production in the proton fragmentation region, (ii) correlations between massive lepton pairs and particles produced in the fragmentation regions, and (iii) correlations between large transverse momentum particles and leading protons. In order to present the large transverse momentum - leading proton correlation, a divided correlation function similar to that used for studying short-range correlations of low transverse momentum particles is defined
WES: A well test analysis expert system
International Nuclear Information System (INIS)
Mensch, A.
1988-06-01
This report describes part of the development of an expert system in the domain of well-test analysis. This work has been done during my final internship, completed at the Lawrence Berkeley Laboratory. The report is divided in three parts: the first one gives a description of the state of the project at the time I first began to work on it, and raises some problems that have to be solved. The second section shows the results that have been reached, and the last one draws conclusions from these results and proposes extensions that would be useful in the future
Modeling correlated information change: from conditional beliefs to quantum conditionals
Baltag, A.; Smets, S.
In this paper, we propose a unified logical framework for representing and analyzing various forms of correlated information change. Our main thesis is that “logical dynamics,” in the sense of van Benthem (Exploring logical dynamics. CSLI Publications, Stanford, 1996; Logical dynamics of information
Comment on ``Correlated noise in a logistic growth model''
Behera, Anita; O'Rourke, S. Francesca C.
2008-01-01
We argue that the results published by Ai [Phys. Rev. E 67, 022903 (2003)] on “correlated noise in logistic growth” are not correct. Their conclusion that, for larger values of the correlation parameter λ , the cell population is peaked at x=0 , which denotes a high extinction rate, is also incorrect. We find the reverse behavior to their results, that increasing λ promotes the stable growth of tumor cells. In particular, their results for the steady-state probability, as a function of cell number, at different correlation strengths, presented in Figs. 1 and 2 of their paper show different behavior than one would expect from the simple mathematical expression for the steady-state probability. Additionally, their interpretation that at small values of cell number the steady-state probability increases as the correlation parameter is increased is also questionable. Another striking feature in their Figs. 1 and 3 is that, for the same values of the parameters λ and α , their simulation produces two different curves, both qualitatively and quantitatively.
Modeling Concordance Correlation Coefficient for Longitudinal Study Data
Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.
2010-01-01
Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of…
Models and correlations of the DEBRIS Late-Phase Melt Progression Model
International Nuclear Information System (INIS)
Schmidt, R.C.; Gasser, R.D.
1997-09-01
The DEBRIS Late Phase Melt Progression Model is an assembly of models, embodied in a computer code, which is designed to treat late-phase melt progression in dry rubble (or debris) regions that can form as a consequence of a severe core uncover accident in a commercial light water nuclear reactor. The approach is fully two-dimensional, and incorporates a porous medium modeling framework together with conservation and constitutive relationships to simulate the time-dependent evolution of such regions as various physical processes act upon the materials. The objective of the code is to accurately model these processes so that the late-phase melt progression that would occur in different hypothetical severe nuclear reactor accidents can be better understood and characterized. In this report the models and correlations incorporated and used within the current version of DEBRIS are described. These include the global conservation equations solved, heat transfer and fission heating models, melting and refreezing models (including material interactions), liquid and solid relocation models, gas flow and pressure field models, and the temperature and compositionally dependent material properties employed. The specific models described here have been used in the experiment design analysis of the Phebus FPT-4 debris-bed fission-product release experiment. An earlier DEBRIS code version was used to analyze the MP-1 and MP-2 late-phase melt progression experiments conducted at Sandia National Laboratories for the US Nuclear Regulatory Commission
Multivariate Receptor Models for Spatially Correlated Multipollutant Data
Jun, Mikyoung; Park, Eun Sug
2013-01-01
The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air
Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.
2018-05-01
Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed
Parametric level correlations in random-matrix models
International Nuclear Information System (INIS)
Weidenmueller, Hans A
2005-01-01
We show that parametric level correlations in random-matrix theories are closely related to a breaking of the symmetry between the advanced and the retarded Green functions. The form of the parametric level correlation function is the same as for the disordered case considered earlier by Simons and Altshuler and is given by the graded trace of the commutator of the saddle-point solution with the particular matrix that describes the symmetry breaking in the actual case of interest. The strength factor differs from the case of disorder. It is determined solely by the Goldstone mode. It is essentially given by the number of levels that are strongly mixed as the external parameter changes. The factor can easily be estimated in applications
Correlations between resonances in a statistical scattering model
International Nuclear Information System (INIS)
Gorin, T.; Rotter, I.
1997-01-01
The distortion of the regular motion in a quantum system by its coupling to the continuum of decay channels is investigated. The regular motion is described by means of a Poissonian ensemble. We focus on the case of only few channels K 2 K distribution in the GOE case. 2. Due to the coupling to the continuum, correlations are induced not only between the positions of the resonances but also between positions and widths. These correlations remain even in the strong coupling limit. In order to explain these results, an asymptotic expression for the width distribution is derived for the one channel case. It relates the width of a trapped resonance state to the distance between its two neighboring levels. (orig.)
International Nuclear Information System (INIS)
Clifton, P.M.
1984-12-01
The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs
Explaining quantum correlations through evolution of causal models
Harper, Robin; Chapman, Robert J.; Ferrie, Christopher; Granade, Christopher; Kueng, Richard; Naoumenko, Daniel; Flammia, Steven T.; Peruzzo, Alberto
2017-04-01
We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.
On the correlation between process model metrics and errors
Mendling, J.; Neumann, G.; Aalst, van der W.M.P.; Grundy, J.; Hartmann, S.; Laender, S.; Maciaszek, L.; Roddick, J.F.
2007-01-01
Business process models play an important role for the management, design, and improvement of process organizations and process-aware information systems. Despite the extensive application of process modeling in practice there are hardly empirical results available on quality aspects of process
Elucidation of spin echo small angle neutron scattering correlation functions through model studies.
Shew, Chwen-Yang; Chen, Wei-Ren
2012-02-14
Several single-modal Debye correlation functions to approximate part of the overall Debey correlation function of liquids are closely examined for elucidating their behavior in the corresponding spin echo small angle neutron scattering (SESANS) correlation functions. We find that the maximum length scale of a Debye correlation function is identical to that of its SESANS correlation function. For discrete Debye correlation functions, the peak of SESANS correlation function emerges at their first discrete point, whereas for continuous Debye correlation functions with greater width, the peak position shifts to a greater value. In both cases, the intensity and shape of the peak of the SESANS correlation function are determined by the width of the Debye correlation functions. Furthermore, we mimic the intramolecular and intermolecular Debye correlation functions of liquids composed of interacting particles based on a simple model to elucidate their competition in the SESANS correlation function. Our calculations show that the first local minimum of a SESANS correlation function can be negative and positive. By adjusting the spatial distribution of the intermolecular Debye function in the model, the calculated SESANS spectra exhibit the profile consistent with that of hard-sphere and sticky-hard-sphere liquids predicted by more sophisticated liquid state theory and computer simulation. © 2012 American Institute of Physics
Thermodynamically consistent description of criticality in models of correlated electrons
Czech Academy of Sciences Publication Activity Database
Janiš, Václav; Kauch, Anna; Pokorný, Vladislav
2017-01-01
Roč. 95, č. 4 (2017), s. 1-14, č. článku 045108. ISSN 2469-9950 R&D Projects: GA ČR GA15-14259S Institutional support: RVO:68378271 Keywords : conserving approximations * Anderson model * Hubbard model * parquet equations Subject RIV: BM - Solid Matter Physics ; Magnetism OBOR OECD: Condensed matter physics (including formerly solid state physics, supercond.) Impact factor: 3.836, year: 2016
Simulation of a directed random-walk model: the effect of pseudo-random-number correlations
Shchur, L. N.; Heringa, J. R.; Blöte, H. W. J.
1996-01-01
We investigate the mechanism that leads to systematic deviations in cluster Monte Carlo simulations when correlated pseudo-random numbers are used. We present a simple model, which enables an analysis of the effects due to correlations in several types of pseudo-random-number sequences. This model provides qualitative understanding of the bias mechanism in a class of cluster Monte Carlo algorithms.
DEFF Research Database (Denmark)
Lassota, Nathan; Kiilgaard, Jens Folke; Prause, Jan Ulrik
2006-01-01
To analyse the histological changes in the retina and the choroid in a pig model of choroidal neovascularization (CNV) and to correlate these findings with fundus photographic and fluorescein angiographic features.......To analyse the histological changes in the retina and the choroid in a pig model of choroidal neovascularization (CNV) and to correlate these findings with fundus photographic and fluorescein angiographic features....
On cross-currency models with stochastic volatility and correlated interest rates
Grzelak, L.A.; Oosterlee, C.W.
2010-01-01
We construct multi-currency models with stochastic volatility and correlated stochastic interest rates with a full matrix of correlations. We first deal with a foreign exchange (FX) model of Heston-type, in which the domestic and foreign interest rates are generated by the short-rate process of
International Nuclear Information System (INIS)
Zeng Chunhua; Zhou Xiaofeng; Tao Shufen
2009-01-01
The transient properties of a tumor cell growth model with immune surveillance driven by cross-correlated multiplicative and additive noises are investigated. The explicit expression of extinction rate from the state of a stable tumor to the state of extinction is obtained. Based on the numerical computations, we find the following: (i) the intensity of multiplicative noise D and the intensity of additive noise α enhance the extinction rate for the case of λ ≤ 0 (i.e. λ denotes cross-correlation intensity between two noises), but for the case of λ > 0, a critical noise intensity D or α exists at which the extinction rate is the smallest; D and α at first weaken the extinction rate and then enhance it. (ii) The immune rate β and the cross-correlation intensity λ play opposite roles on the extinction rate, i.e. β enhances the extinction rate of the tumor cell, while λ weakens the extinction rate of the tumor cell. Namely, the immune rate can enhance the extinction of the tumor cell and the cross-correlation between two noises can enhance stability of the cancer state.
Multivariate Receptor Models for Spatially Correlated Multipollutant Data
Jun, Mikyoung
2013-08-01
The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.
Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting
Directory of Open Access Journals (Sweden)
Hua-pu Lu
2015-01-01
Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.
Correlation function of four spins in the percolation model
Directory of Open Access Journals (Sweden)
Vladimir S. Dotsenko
2016-10-01
It is known that the four-point functions define the actual fusion rules of a particular model. In this respect, we find that fusion of two spins, of dimension Δσ=596, produce a new channel, in the 4-point function, which is due to the operator with dimension Δ=5/8.
Performances of estimators of linear auto-correlated error model ...
African Journals Online (AJOL)
The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...
Multidimensional Model of Trauma and Correlated Antisocial Personality Disorder
Martens, Willem H. J.
2005-01-01
Many studies have revealed an important relationship between psychosocial trauma and antisocial personality disorder. A multidimensional model is presented which describes the psychopathological route from trauma to antisocial development. A case report is also included that can illustrate the etiological process from trauma to severe antisocial…
Fluctuations and correlations in statistical models of hadron production
International Nuclear Information System (INIS)
Gorenstein, M. I.
2012-01-01
An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution are introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.
Directory of Open Access Journals (Sweden)
Kristijan Posavec
2017-01-01
Full Text Available Modelling responses of groundwater levels in aquifer systems, which occur as a reaction to changes in aquifer system boundary conditions such as river or stream stages, is commonly being studied using statistical methods, namely correlation, cross-correlation and regression methods. Although correlation and regression analysis tools are readily available in Microsoft Excel, a widely applied spreadsheet industry standard, the cross-correlation analysis tool is missing. As a part of research of groundwater pressure propagation into alluvial aquifer systems of the Sava and Drava/Danube River catchments following river stages rise, focused on estimating groundwater pressure travel times in aquifers, an Excel spreadsheet data analysis application for cross-correlation modelling has been designed and used in modelling surface water – groundwater interaction. Examples of fi eld data from the Zagreb aquifer system and the Kopački rit Nature Park aquifer system are used to illustrate the usefulness of the cross-correlation application.
Superconducting, magnetic, and charge correlations in the doped two-chain Hubbard model
International Nuclear Information System (INIS)
Asai, Y.
1995-01-01
We have studied the superconducting, magnetic, and charge correlation functions and the spin excitation spectrum in the doped two-chain Hubbard model by projector Monte Carlo and Lanczos diagonalization methods. The exponent of the interchain singlet superconducting correlation function, γ, is found to be close to 2.0 as long as two distinct noninteracting bands cross the Fermi level. Magnetic and charge correlation functions decay more rapidly than or as fast as the interchain singlet superconducting correlation function along the chains. The superconducting correlation in the doped two-chain Hubbard model is the most long-range correlation studied here. Implications of the results for the possible universality class of the doped two-chain Hubbard model are discussed
Holschneider, M.; Ferrat, K.; Lesur, V.; Stolle, C.
2017-12-01
Ionospheric fields are modelled in terms of random structures taking into account a mean behaviour as well as random fluctuations which are described through two point correlation kernels. These kernels are estimated from long time series of numerical simulations from various models. These correlations are best expressed in SM system of coordinates. For the moment we limit ourselves to spatial correlations only in this coordinate system. We study the influence of various indices as possible predictor parameters for these correlations as well as seasonal effects. The various time series of ionospheric fields are stored in a HDF5 database which is accessible via a web interface. The obtained correlation structures serve as prior information to separate external and internal field components from observatory based measurements. We present a model that predicts the correlations as a function of time and some geomagnetic indices. First results of the inversion from observatory data are presented.
Exact solution of the one-dimensional fermionic model with correlated hopping
International Nuclear Information System (INIS)
Schadschneider, A.; Su Gang; Zittartz, J.
1997-01-01
We extend the Bethe Ansatz solution of a one-dimensional integrable fermionic model with correlated hopping to the parameter regime Δt > 1. It is found that the model is equivalent to one with interaction 2 - Δt, but with twisted boundary conditions. Apart from the ground state energy we investigate the low-lying excitations and the asymptotic behaviour of the correlation functions. As in the case of Δt < 1 we find dominating superconducting correlations for small doping. The behaviour in this regime therefore differs from that of the non-integrable model with symmetric bond-charge interaction (Hirsch model). (orig.)
Correlation functions of heisenberg-mattis model in one dimension
International Nuclear Information System (INIS)
Azeeem, W.
1991-01-01
The technique of real-space renormalization to the dynamics of Heisenberg-Mattis model, which represents a random magnetic system with competing ferromagnetic and antiferromagnetic interactions has been applied. The renormalization technique, which has been in use for calculating density of states, is extended to calculate dynamical response function from momentum energy dependent Green's functions. Our numerical results on density of states and structure function of one-dimensional Heisenberg-Mattis model come out to be in good agreement with computer simulation results. The numerical scheme worked out in this thesis has the advantage that it can also provide a complete map of momentum and energy dependence of the structure function. (author)
Parametric modelling of correlation in a dense plasma
International Nuclear Information System (INIS)
Krikorian V, R.; Daveloza de K, S.
1982-01-01
A two-component-symmetric quantum plasma is analyzed. The collective repulsive effects are considered by means of models for the local structures, in their coordination shell, using partial distribution functions. The generalized expressions for the internal energy and equation of state of the system are presented, which reflect the local structure effects and guarantee the thermodynamic stability of the system. The only limit on the density is that due to the impenetrability of the particles. (L.C.) [pt
Correlation effects of third-order perturbation in the extended Hubbard model
International Nuclear Information System (INIS)
Wei, G.Z.; Nie, H.Q.; Li, L.; Zhang, K.Y.
1989-01-01
Using the local approach, a third-order perturbation calculation has been performed to investigate the effects of intra-atomic electron correlation and electron and spin correlation between nearest neighbour sites in the extended Hubbard model. It was found that significant correction of the third order over the second order results and, in comparison with the results of the third-order perturbation where only the intra-atomic electron correlation is included, the influence of the electron and spin correlation between nearest neighbour sites on the correlation energy is non-negligible. 17 refs., 3 figs
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Directory of Open Access Journals (Sweden)
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-01-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-06-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
Nonlinearity of the forward-backward correlation function in the model with string fusion
Vechernin, Vladimir
2017-12-01
The behavior of the forward-backward correlation functions and the corresponding correlation coefficients between multiplicities and transverse momenta of particles produced in high energy hadronic interactions is analyzed by analytical and MC calculations in the models with and without string fusion. The string fusion is taking into account in simplified form by introducing the lattice in the transverse plane. The results obtained with two alternative definitions of the forward-backward correlation coefficient are compared. It is shown that the nonlinearity of correlation functions increases with the width of observation windows, leading at small string density to a strong dependence of correlation coefficient value on the definition. The results of the modeling enable qualitatively to explain the experimentally observed features in the behavior of the correlation functions between multiplicities and mean transverse momenta at small and large multiplicities.
Models and Correlations of Interfacial and Wall Frictions for the SPACE code
International Nuclear Information System (INIS)
Kim, Soo Hyung; Hwang, Moon Kyu; Chung, Bub Dong
2010-04-01
This report describes models and correlations for the interfacial and wall frictions implemented in the SPACE code which has the capability to predict thermal-hydraulic behavior of nuclear power plants. The interfacial and wall frictions are essential to solve the momentum conservation equations of gas, continuous liquid and droplet. The interfacial and wall frictions are dealt in the Chapter 2 and 3, respectively. In Chapter 4, selection criteria for models and correlations are explained. In Chapter 5, the origins of the selected models and correlations used in this code are examined to check whether they are in confliction with intellectual proprietary rights
Shell model for time-correlated random advection of passive scalars
DEFF Research Database (Denmark)
Andersen, Ken Haste; Muratore-Ginanneschi, P.
1999-01-01
We study a minimal shell model for the advection of a passive scalar by a Gaussian time-correlated velocity field. The anomalous scaling properties of the white noise limit are studied analytically. The effect of the time correlations are investigated using perturbation theory around the white...... noise limit and nonperturbatively by numerical integration. The time correlation of the velocity field is seen to enhance the intermittency of the passive scalar. [S1063-651X(99)07711-9]....
The spherical limit of the n-vector model and correlation inequaljties
International Nuclear Information System (INIS)
Angelescu, N.; Bundaru, M.; Costache, G.
1978-08-01
The asymptotics of the state of the n-vector model with a finite number of spins in the spherical limit is studied. Besides rederiving the limit free energy, corresponding to a generalized spherical model (with ''spherical constraint'' at every site), we obtain also the limit of the correlation functions, which allow a precise definition of the state of the latter model. Correlation inequalities are proved for ferromagnetic interactions in the asymptotic regime. In particular, it is shown that the generalized spherical model fulfills the expected Griffiths' type inequalities, differing in this respect from the spherical model with overall constraint. (author)
Multi-time, multi-scale correlation functions in turbulence and in turbulent models
Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.
1999-01-01
A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is
Correlation inequalities for two-component hypercubic φ4 models. Pt. 2
International Nuclear Information System (INIS)
Soria, J.L.; Instituto Tecnologico de Tijuana
1990-01-01
We continue the program started in the first paper (J. Stat. Phys. 52 (1988) 711-726). We find new and already known correlation inequalities for a family of two-component hypercubic φ 4 models, using techniques of rotated correlation inequalities and random walk representation. (orig.)
Hao, Wenrui; Lu, Zhenzhou; Li, Luyi
2013-05-01
In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.
Pia, Maria Grazia; Bell, Zane W.; Dressendorfer, Paul V.
2010-01-01
A scientometric analysis has been performed on selected physics journals to estimate the presence of simulation and modeling in physics literature in the past fifty years. Correlations between the observed trends and several social and economical factors have been evaluated.
Microscopic universality of complex matrix model correlation functions at weak non-Hermiticity
International Nuclear Information System (INIS)
Akemann, G.
2002-01-01
The microscopic correlation functions of non-chiral random matrix models with complex eigenvalues are analyzed for a wide class of non-Gaussian measures. In the large-N limit of weak non-Hermiticity, where N is the size of the complex matrices, we can prove that all k-point correlation functions including an arbitrary number of Dirac mass terms are universal close to the origin. To this aim we establish the universality of the asymptotics of orthogonal polynomials in the complex plane. The universality of the correlation functions then follows from that of the kernel of orthogonal polynomials and a mapping of massive to massless correlators
Model of geophysical fields representation in problems of complex correlation-extreme navigation
Directory of Open Access Journals (Sweden)
Volodymyr KHARCHENKO
2015-09-01
Full Text Available A model of the optimal representation of spatial data for the task of complex correlation-extreme navigation is developed based on the criterion of minimum deviation of the correlation functions of the original and the resulting fields. Calculations are presented for one-dimensional case using the approximation of the correlation function by Fourier series. It is shown that in the presence of different geophysical map data fields their representation is possible by single template with optimal sampling without distorting the form of the correlation functions.
Modelling asset correlations during the recent financial crisis: A semiparametric approach
DEFF Research Database (Denmark)
Aslanidis, Nektarios; Casas, Isabel
This article proposes alternatives to the Dynamic Conditional Correlation (DCC) model to study assets' correlations during the recent financial crisis. In particular, we adopt a semiparametric and nonparametric approach to estimate the conditional correlations for two interesting portfolios....... The first portfolio consists of equity sectors SPDRs and the S&P 500 composite, while the second one contains major currencies that are actively traded in the foreign exchange market. Methodologically, our contribution is two fold. First, we propose the Local Linear (LL) estimator for the correlations...
A model for the two-point velocity correlation function in turbulent channel flow
International Nuclear Information System (INIS)
Sahay, A.; Sreenivasan, K.R.
1996-01-01
A relatively simple analytical expression is presented to approximate the equal-time, two-point, double-velocity correlation function in turbulent channel flow. To assess the accuracy of the model, we perform the spectral decomposition of the integral operator having the model correlation function as its kernel. Comparisons of the empirical eigenvalues and eigenfunctions with those constructed from direct numerical simulations data show good agreement. copyright 1996 American Institute of Physics
International Nuclear Information System (INIS)
Beck, T.; Bieler, A.; Thomas, N.
2012-01-01
We present structural and thermal model (STM) tests of the BepiColombo laser altimeter (BELA) receiver baffle with emphasis on the correlation of the data with a thermal mathematical model. The test unit is a part of the thermal and optical protection of the BELA instrument being tested under infrared and solar irradiation at University of Bern. An iterative optimization method known as particle swarm optimization has been adapted to adjust the model parameters, mainly the linear conductivity, in such a way that model and test results match. The thermal model reproduces the thermal tests to an accuracy of 4.2 °C ± 3.2 °C in a temperature range of 200 °C after using only 600 iteration steps of the correlation algorithm. The use of this method brings major benefits to the accuracy of the results as well as to the computational time required for the correlation. - Highlights: ► We present model correlations of the BELA receiver baffle to thermal balance tests. ► Adaptive particle swarm optimization has been adapted for the correlation. ► The method improves the accuracy of the correlation and the computational time.
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.
Zheng, Guo; Wang, Jue; Wang, Lin; Zhou, Muchun; Xin, Yu; Song, Minmin
2017-11-15
The general formulae for second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence are derived and validated by the Bessel-Gaussian Schell-model beams and cosine-Gaussian-correlated Schell-model beams. Our finding shows that the second-order moments of partially coherent Schell-model beams are related to the second-order partial derivatives of source spectral degree of coherence at the origin. The formulae we provide are much more convenient to analyze and research propagation problems in turbulence.
Multiparticle correlations and identical particle effects in the independent cluster emission model
International Nuclear Information System (INIS)
Ranft, J.
1977-01-01
In the nucleon approach to phenomenological applications, the model is compared to many different kinds of experimental data. The comparison indicates, that the model is qualitatively consistent with all available data. Analysis indicates, that identical particle effects due to the Bose statistics are present in data on joint rapidity-asimuthal correlations near Δy=ΔPHI=0. A new approach to this problem is the uncorrelated jet model with the Bose statistics. This model confirms the previous results. Furthermore, taking isospin conservation into account, the Bose correlations are predicted in π + π - channels, which should be most easily detectable in the decay of heavy resonances J/PSI
Well test analysis in fractured media
Energy Technology Data Exchange (ETDEWEB)
Karasaki, K.
1986-04-01
In this study the behavior of fracture systems under well test conditions and methods for analyzing well test data from fractured media are investigated. Several analytical models are developed to be used for analyzing well test data from fractured media. Numerical tools that may be used to simulate fluid flow in fractured media are also presented. Three types of composite models for constant flux tests are investigated. Several slug test models with different geometric conditions that may be present in fractured media are also investigated. A finite element model that can simulate transient fluid flow in fracture networks is used to study the behavior of various two-dimensional fracture systems under well test conditions. A mesh generator that can be used to model mass and heat flow in a fractured-porous media is presented. This model develops an explicit solution in the porous matrix as well as in the discrete fractures. Because the model does not require the assumptions of the conventional double porosity approach, it may be used to simulate cases where double porosity models fail.
Mckim, Stephen A.
2016-01-01
This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within plus or minus 3 degrees Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2 to 2.5 C lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
Thermal Testing and Model Correlation for Advanced Topographic Laser Altimeter Instrument (ATLAS)
Patel, Deepak
2016-01-01
The Advanced Topographic Laser Altimeter System (ATLAS) part of the Ice Cloud and Land Elevation Satellite 2 (ICESat-2) is an upcoming Earth Science mission focusing on the effects of climate change. The flight instrument passed all environmental testing at GSFC (Goddard Space Flight Center) and is now ready to be shipped to the spacecraft vendor for integration and testing. This topic covers the analysis leading up to the test setup for ATLAS thermal testing as well as model correlation to flight predictions. Test setup analysis section will include areas where ATLAS could not meet flight like conditions and what were the limitations. Model correlation section will walk through changes that had to be made to the thermal model in order to match test results. The correlated model will then be integrated with spacecraft model for on-orbit predictions.
Chiral correlators in Landau-Ginsburg theories and N=2 superconformal models
International Nuclear Information System (INIS)
Howe, P.S.; West, P.C.
1989-01-01
Chiral correlation functions are computed in N=2 Landau-Ginsburg models using the ε-expansion and the superconformal Ward identities for the Landau-Ginsburg effective action. They are also computed directly using superconformal model techniques. The same results are obtained yielding further confirmation of the identification of superconformal minimal models with Landau-Ginsburg models evaluated at their fixed points. The formulae for the chiral commutators that we compute are extremely simple when expressed in terms of effective actions. (orig.)
DEFF Research Database (Denmark)
Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne
2003-01-01
Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
Well test analysis in fractured media
Energy Technology Data Exchange (ETDEWEB)
Karasaki, K.
1987-04-01
The behavior of fracture systems under well test conditions and methods for analyzing well test data from fractured media are investigated. Several analytical models are developed to be used for analyzing well test data from fractured media. Numerical tools that may be used to simulate fluid flow in fractured media are also presented. Three types of composite models for constant flux tests are investigated. These models are based on the assumption that a fracture system under well test conditions may be represented by two concentric regions, one representing a small number of fractures that dominates flow near the well, and the other representing average conditions farther away from the well. Type curves are presented that can be used to find the flow parameters of these two regions and the extent of the inner concentric region. Several slug test models with different geometric conditions that may be present in fractured media are also investigated. A finite element model that can simulate transient fluid flow in fracture networks is used to study the behavior of various two-dimensional fracture systems under well test conditions. A mesh generator that can be used to model mass and heat flow in a fractured-porous media is presented.
A neural network model and an update correlation for estimation of dead crude oil viscosity
Energy Technology Data Exchange (ETDEWEB)
Naseri, A.; Gharesheikhlou, A.A. [Research Institute of Petroleum Industry (RIPI), Tehran (Iran, Islamic Republic of). PVT Dept.; Yousefi, S.H.; Sanaei, A. [Amirkabir University of Technology, Tehran (Iran, Islamic Republic of). Faculty of Petroleum Engineering], E-mail: alirezasanaei.aut@gmail.com
2012-01-15
Viscosity is one of the most important physical properties in reservoir simulation, formation evaluation, in designing surface facilities and in the calculation of original hydrocarbon in-place. Mostly, oil viscosity is measured in PVT laboratories only at reservoir temperature. Hence, it is of great importance to use an accurate correlation for prediction of oil viscosity at different operating conditions and various temperatures. Although, different correlations have been proposed for various regions, the applicability of the existing correlations for Iranian oil reservoirs is limited due to the nature of the Iranian crude oil. In this study, based on Iranian oil reservoir data, a new correlation for the estimation of dead oil viscosity was provided using non-linear multivariable regression and non-linear optimization methods simultaneously with the optimization of the other existing correlations. This new correlation uses API Gravity and temperature as an input parameter. In addition, a neural-network-based model for prediction of dead oil viscosity is presented. Detailed comparisons show that validity and accuracy of the new correlation and the neural-network model are in good agreement with large data set of Iranian oil reservoir when compared with other correlations. (author)
Directory of Open Access Journals (Sweden)
Yuuki Kanemiyo
2012-01-01
Full Text Available This paper described a spatial correlation and eigenvalue in a multiple-input multiple-output (MIMO channel. A MIMO channel model with a multipath propagation mechanism was proposed and showed the channel matrix. The spatial correlation coefficient formula −,′−′( between MIMO channel matrix elements was derived for the model and was expressed as a directive wave term added to the product of mobile site correlation −′( and base site correlation −′( without LOS path, which are calculated independently of each other. By using −,′−′(, it is possible to create the channel matrix element with a fixed correlation value estimated by −,′−′( for a given multipath condition and a given antenna configuration. Furthermore, the correlation and the channel matrix eigenvalue were simulated, and the simulated and theoretical correlation values agreed well. The simulated eigenvalue showed that the average of the first eigenvalue λ1 hardly depends on the correlation −,′−′(, but the others do depend on −,′−′( and approach 1 as −,′−′( decreases. Moreover, as the path moves into LOS, the 1 state with mobile movement becomes more stable than the 1 of NLOS path.
International Nuclear Information System (INIS)
Aspect, A.
1986-01-01
The author states that ''It is impossible to mimick the quantum mechanical predictions for the EPR correlations, with a reasonable classical-looking model, in the spirit of Einstein's ideas''. The author feels that if he is wrong somebody could make a classical model (i.e. following the laws of classical physics) mimicking all the quantum mechanical predictions for the EPR correlations. He attempts to show that it is not the case for Barut's model for the following reasons: the first version of his model is classical, but doesn't mimick at all an EPR type experiment; and by reinterpretation one can get a model that does mimick the experiment, but this model is no longer ''reasonably classical looking'' since it involves negative probabilities. The claim is put in the form of a challenge. It is shown that the model under discussion can be reinterpreted by adding a chip converting the continuous outputs into two-valved outputs
Correlation Educational Model in Primary Education Curriculum of Mathematics and Computer Science
Macinko Kovac, Maja; Eret, Lidija
2012-01-01
This article gives insight into methodical correlation model of teaching mathematics and computer science. The model shows the way in which the related areas of computer science and mathematics can be supplemented, if it transforms the way of teaching and creates a "joint" lessons. Various didactic materials are designed, in which all…
Anisotropic correlated electron model associated with the Temperley-Lieb algebra
International Nuclear Information System (INIS)
Foerster, Angela; Links, Jon; Roditi, Itzhak
1997-12-01
We present and anisotropic correlated electron model on a periodic lattice, constructed from an R-matrix associated with the Temperley-Lieb algebra. By modification of the coupling of the first and last sites we obtain a model with quantum algebra invariance. (author)
Inference and testing on the boundary in extended constant conditional correlation GARCH models
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard
2017-01-01
We consider inference and testing in extended constant conditional correlation GARCH models in the case where the true parameter vector is a boundary point of the parameter space. This is of particular importance when testing for volatility spillovers in the model. The large-sample properties...
High temperature limit of the order parameter correlation functions in the quantum Ising model
Reyes, S. A.; Tsvelik, A. M.
2006-06-01
In this paper we use the exact results for the anisotropic two-dimensional Ising model obtained by Bugrii and Lisovyy [A.I. Bugrii, O.O. Lisovyy, Theor. Math. Phys. 140 (2004) 987] to derive the expressions for dynamical correlation functions for the quantum Ising model in one dimension at high temperatures.
High temperature limit of the order parameter correlation functions in the quantum Ising model
Energy Technology Data Exchange (ETDEWEB)
Reyes, S.A. [Department of Physics and Astronomy, SUNY at Stony Brook, Stony Brook, NY 11794-3840 (United States); Department of Condensed Matter Physics and Materials Science, Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Tsvelik, A.M. [Department of Physics and Astronomy, SUNY at Stony Brook, Stony Brook, NY 11794-3840 (United States) and Department of Condensed Matter Physics and Materials Science, Brookhaven National Laboratory, Upton, NY 11973-5000 (United States)]. E-mail tsvelik@bnl.gov
2006-06-12
In this paper we use the exact results for the anisotropic two-dimensional Ising model obtained by Bugrii and Lisovyy [A.I. Bugrii, O.O. Lisovyy, Theor. Math. Phys. 140 (2004) 987] to derive the expressions for dynamical correlation functions for the quantum Ising model in one dimension at high temperatures.
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
-run and the short-run dynamic behaviour of the volatilities. The structure of the conditional correlation matrix is assumed to be either time independent or to vary over time. We apply our model to pairs of seven daily stock returns belonging to the S&P 500 composite index and traded at the New York Stock Exchange......In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilities of stock market returns on the conditional correlation structure. To this end we allow the individual unconditional variances in Conditional Correlation GARCH models to change smoothly over time...... by incorporating a nonstationary component in the variance equations. The modelling technique to determine the parametric structure of this time-varying component is based on a sequence of specification Lagrange multiplier-type tests derived in Amado and Teräsvirta (2011). The variance equations combine the long...
Long-range correlations in a simple stochastic model of coupled transport
International Nuclear Information System (INIS)
Larralde, Hernan; Sanders, David P
2009-01-01
We study coupled transport in the nonequilibrium stationary state of a model consisting of independent random walkers, moving along a one-dimensional channel, which carry a conserved energy-like quantity, with density and temperature gradients imposed by reservoirs at the ends of the channel. In our model, walkers interact with other walkers at the same site by sharing energy at each time step, but the amount of energy carried does not affect the motion of the walkers. We find that already in this simple model long-range correlations arise in the nonequilibrium stationary state which are similar to those observed in more realistic models of coupled transport. We derive an analytical expression for the source of these correlations, which we use to obtain semi-analytical results for the correlations themselves assuming a local-equilibrium hypothesis. These are in very good agreement with results from direct numerical simulations.
Event-plane dependent di-hadron correlations with harmonic vn subtraction in a hydrodynamic model
Castilho, Wagner M.; Qian, Wei-Liang; Hama, Yogiro; Kodama, Takeshi
2018-02-01
In this work, a hydrodynamic study of the di-hadron azimuthal correlations for the Au+Au collisions at 200 GeV is carried out. The correlations are evaluated using the ZYAM method for the centrality windows as well as the transverse momentum range in accordance with the existing data. Event-plane dependence of the correlation is obtained after the subtraction of contributions from the most dominant harmonic coefficients. In particular, the contribution from the triangular flow, v3, is removed from the proper correlations following the procedure implemented by the STAR collaboration. The resultant structure observed in the correlations was sometimes attributed to the mini-jet dynamics, but the present calculations show that a pure hydrodynamic model gives a reasonable agreement with the main feature of the published data. A brief discussion on the physical content of the present findings is presented.
Comparing Free-Free and Shaker Table Model Correlation Methods Using Jim Beam
Ristow, James; Smith, Kenneth Wayne, Jr.; Johnson, Nathaniel; Kinney, Jackson
2018-01-01
Finite element model correlation as part of a spacecraft program has always been a challenge. For any NASA mission, the coupled system response of the spacecraft and launch vehicle can be determined analytically through a Coupled Loads Analysis (CLA), as it is not possible to test the spacecraft and launch vehicle coupled system before launch. The value of the CLA is highly dependent on the accuracy of the frequencies and mode shapes extracted from the spacecraft model. NASA standards require the spacecraft model used in the final Verification Loads Cycle to be correlated by either a modal test or by comparison of the model with Frequency Response Functions (FRFs) obtained during the environmental qualification test. Due to budgetary and time constraints, most programs opt to correlate the spacecraft dynamic model during the environmental qualification test, conducted on a large shaker table. For any model correlation effort, the key has always been finding a proper definition of the boundary conditions. This paper is a correlation case study to investigate the difference in responses of a simple structure using a free-free boundary, a fixed boundary on the shaker table, and a base-drive vibration test, all using identical instrumentation. The NAVCON Jim Beam test structure, featured in the IMAC round robin modal test of 2009, was selected as a simple, well recognized and well characterized structure to conduct this investigation. First, a free-free impact modal test of the Jim Beam was done as an experimental control. Second, the Jim Beam was mounted to a large 20,000 lbf shaker, and an impact modal test in this fixed configuration was conducted. Lastly, a vibration test of the Jim Beam was conducted on the shaker table. The free-free impact test, the fixed impact test, and the base-drive test were used to assess the effect of the shaker modes, evaluate the validity of fixed-base modeling assumptions, and compare final model correlation results between these
Model of the Correlation between Lidar Systems and Wind Turbines for Lidar-Assisted Control
DEFF Research Database (Denmark)
Schlipf, David; Cheng, Po Wen; Mann, Jakob
2013-01-01
- or spinner-based lidar system. If on the one hand, the assumed correlation is overestimated, then the uncorrelated frequencies of the preview will cause unnecessary control action, inducing undesired loads. On the other hand, the benefits of the lidar-assisted controller will not be fully exhausted......, if correlated frequencies are filtered out. To avoid these miscalculations, this work presents a method to model the correlation between lidar systems and wind turbines using Kaimal wind spectra. The derived model accounts for different measurement configurations and spatial averaging of the lidar system......Investigations of lidar-assisted control to optimize the energy yield and to reduce loads of wind turbines have increased significantly in recent years. For this kind of control, it is crucial to know the correlation between the rotor effective wind speed and the wind preview provided by a nacelle...
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.
A goodness-of-fit test for occupancy models with correlated within-season revisits
Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.
2016-01-01
Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and
Correlations in simple multi-string models of pp collisions at ISR energies
International Nuclear Information System (INIS)
Lugovoj, V.V.; Chudakov, V.M.
1989-01-01
Simple statistical simulation algorithms are suggested for formation and breaking of a few quark-gluon strings in inelastic pp collisions. Theoretical multiplicity distributions, semi-inclusive quasirapidity spectra, forward-backward correlations of charged secondaries and seagull effect agree well with the experimental data at ISR energies. In the framework of the model, the semi-inclusive two-particle correlations of quasirapidities depend upon the fraction of the spherical chains. The seagull effect is qualitatively interpretated
International Nuclear Information System (INIS)
Bachschmid-Romano, Ludovica; Opper, Manfred
2015-01-01
We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the nontrivial equal time correlations between spins induced by the dynamics for the speed of learning. These correlations become more important as the spin’s stochasticity is decreased. We also analyse the deviation of the estimation error (paper)
Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas
2010-01-01
Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...
New Models for Velocity/Pressure-Gradient Correlations in Turbulent Boundary Layers
Poroseva, Svetlana; Murman, Scott
2014-11-01
To improve the performance of Reynolds-Averaged Navier-Stokes (RANS) turbulence models, one has to improve the accuracy of models for three physical processes: turbulent diffusion, interaction of turbulent pressure and velocity fluctuation fields, and dissipative processes. The accuracy of modeling the turbulent diffusion depends on the order of a statistical closure chosen as a basis for a RANS model. When the Gram-Charlier series expansions for the velocity correlations are used to close the set of RANS equations, no assumption on Gaussian turbulence is invoked and no unknown model coefficients are introduced into the modeled equations. In such a way, this closure procedure reduces the modeling uncertainty of fourth-order RANS (FORANS) closures. Experimental and direct numerical simulation data confirmed the validity of using the Gram-Charlier series expansions in various flows including boundary layers. We will address modeling the velocity/pressure-gradient correlations. New linear models will be introduced for the second- and higher-order correlations applicable to two-dimensional incompressible wall-bounded flows. Results of models' validation with DNS data in a channel flow and in a zero-pressure gradient boundary layer over a flat plate will be demonstrated. A part of the material is based upon work supported by NASA under award NNX12AJ61A.
Importance analysis for models with correlated variables and its sparse grid solution
International Nuclear Information System (INIS)
Li, Luyi; Lu, Zhenzhou
2013-01-01
For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built
Summary of CPAS EDU Testing Analysis Results
Romero, Leah M.; Bledsoe, Kristin J.; Davidson, John.; Engert, Meagan E.; Fraire, Usbaldo, Jr.; Galaviz, Fernando S.; Galvin, Patrick J.; Ray, Eric S.; Varela, Jose
2015-01-01
The Orion program's Capsule Parachute Assembly System (CPAS) project is currently conducting its third generation of testing, the Engineering Development Unit (EDU) series. This series utilizes two test articles, a dart-shaped Parachute Compartment Drop Test Vehicle (PCDTV) and capsule-shaped Parachute Test Vehicle (PTV), both of which include a full size, flight-like parachute system and require a pallet delivery system for aircraft extraction. To date, 15 tests have been completed, including six with PCDTVs and nine with PTVs. Two of the PTV tests included the Forward Bay Cover (FBC) provided by Lockheed Martin. Advancements in modeling techniques applicable to parachute fly-out, vehicle rate of descent, torque, and load train, also occurred during the EDU testing series. An upgrade from a composite to an independent parachute simulation allowed parachute modeling at a higher level of fidelity than during previous generations. The complexity of separating the test vehicles from their pallet delivery systems necessitated the use the Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulator for modeling mated vehicle aircraft extraction and separation. This paper gives an overview of each EDU test and summarizes the development of CPAS analysis tools and techniques during EDU testing.
Fidelity susceptibility and long-range correlation in the Kitaev honeycomb model
Yang, Shuo; Gu, Shi-Jian; Sun, Chang-Pu; Lin, Hai-Qing
2008-07-01
We study exactly both the ground-state fidelity susceptibility and bond-bond correlation function in the Kitaev honeycomb model. Our results show that the fidelity susceptibility can be used to identify the topological phase transition from a gapped A phase with Abelian anyon excitations to a gapless B phase with non-Abelian anyon excitations. We also find that the bond-bond correlation function decays exponentially in the gapped phase, but algebraically in the gapless phase. For the former case, the correlation length is found to be 1/ξ=2sinh-1[2Jz-1/(1-Jz)] , which diverges around the critical point Jz=(1/2)+ .
Accounting of inter-electron correlations in the model of mobile electron shells
International Nuclear Information System (INIS)
Panov, Yu.D.; Moskvin, A.S.
2000-01-01
One studied the basic peculiar features of the model for mobile electron shells for multielectron atom or cluster. One offered a variation technique to take account of the electron correlations where the coordinates of the centre of single-particle atomic orbital served as variation parameters. It enables to interpret dramatically variation of electron density distribution under anisotropic external effect in terms of the limited initial basis. One studied specific correlated states that might make correlation contribution into the orbital current. Paper presents generalization of the typical MO-LCAO pattern with the limited set of single particle functions enabling to take account of additional multipole-multipole interactions in the cluster [ru
Papalexiou, Simon Michael
2018-05-01
Hydroclimatic processes come in all "shapes and sizes". They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific "parent" Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.
Directory of Open Access Journals (Sweden)
Linhong Wang
2013-01-01
Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.
Charge distributions and correlations in fragmentation models for soft hadron collisions
International Nuclear Information System (INIS)
Wolf, E.A. de
1984-01-01
Data on charge distributions and charge correlations in pp and meson-proton interactions at PS and SPS energies are successfully compared with the Lund fragmentation model for low-psub(T) hadron collisions. It is argued that local conservation of quantum numbers and resonance production, as implemented in fragmentation models, are sufficient ingredients to explain most of the available experimental results at these energies. No necessity is found for dual-sheet contributions considered in DTU-based parton models. (orig.)
Scattering of long folded strings and mixed correlators in the two-matrix model
International Nuclear Information System (INIS)
Bourgine, J.-E.; Hosomichi, K.; Kostov, I.; Matsuo, Y.
2008-01-01
We study the interactions of Maldacena's long folded strings in two-dimensional string theory. We find the amplitude for a state containing two long folded strings to come and go back to infinity. We calculate this amplitude both in the worldsheet theory and in the dual matrix model, the matrix quantum mechanics. The matrix model description allows to evaluate the amplitudes involving any number of long strings, which are given by the mixed trace correlators in an effective two-matrix model
Boundary-layer transition prediction using a simplified correlation-based model
Directory of Open Access Journals (Sweden)
Xia Chenchao
2016-02-01
Full Text Available This paper describes a simplified transition model based on the recently developed correlation-based γ-Reθt transition model. The transport equation of transition momentum thickness Reynolds number is eliminated for simplicity, and new transition length function and critical Reynolds number correlation are proposed. The new model is implemented into an in-house computational fluid dynamics (CFD code and validated for low and high-speed flow cases, including the zero pressure flat plate, airfoils, hypersonic flat plate and double wedge. Comparisons between the simulation results and experimental data show that the boundary-layer transition phenomena can be reasonably illustrated by the new model, which gives rise to significant improvements over the fully laminar and fully turbulent results. Moreover, the new model has comparable features of accuracy and applicability when compared with the original γ-Reθt model. In the meantime, the newly proposed model takes only one transport equation of intermittency factor and requires fewer correlations, which simplifies the original model greatly. Further studies, especially on separation-induced transition flows, are required for the improvement of the new model.
A perturbative approach to the redshift space correlation function: beyond the Standard Model
Energy Technology Data Exchange (ETDEWEB)
Bose, Benjamin; Koyama, Kazuya, E-mail: benjamin.bose@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Burnaby Road, Portsmouth, Hampshire, PO1 3FX (United Kingdom)
2017-08-01
We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 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.
A perturbative approach to the redshift space correlation function: beyond the Standard Model
Bose, Benjamin; Koyama, Kazuya
2017-08-01
We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.
Li, Y.; McDougall, T. J.
2016-02-01
Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.
Comparison of co-expression measures: mutual information, correlation, and model based indices.
Song, Lin; Langfelder, Peter; Horvath, Steve
2012-12-09
Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI
Population models and simulation methods: The case of the Spearman rank correlation.
Astivia, Oscar L Olvera; Zumbo, Bruno D
2017-11-01
The purpose of this paper is to highlight the importance of a population model in guiding the design and interpretation of simulation studies used to investigate the Spearman rank correlation. The Spearman rank correlation has been known for over a hundred years to applied researchers and methodologists alike and is one of the most widely used non-parametric statistics. Still, certain misconceptions can be found, either explicitly or implicitly, in the published literature because a population definition for this statistic is rarely discussed within the social and behavioural sciences. By relying on copula distribution theory, a population model is presented for the Spearman rank correlation, and its properties are explored both theoretically and in a simulation study. Through the use of the Iman-Conover algorithm (which allows the user to specify the rank correlation as a population parameter), simulation studies from previously published articles are explored, and it is found that many of the conclusions purported in them regarding the nature of the Spearman correlation would change if the data-generation mechanism better matched the simulation design. More specifically, issues such as small sample bias and lack of power of the t-test and r-to-z Fisher transformation disappear when the rank correlation is calculated from data sampled where the rank correlation is the population parameter. A proof for the consistency of the sample estimate of the rank correlation is shown as well as the flexibility of the copula model to encompass results previously published in the mathematical literature. © 2017 The British Psychological Society.
Amplitudes of solar p modes: Modelling of the eddy time-correlation function
Energy Technology Data Exchange (ETDEWEB)
Belkacem, K [Institut d' Astrophysique et de Geophysique, Universite de Liege, Allee du 6 Aout 17-B 4000 Liege (Belgium); Samadi, R; Goupil, M J, E-mail: Kevin.Belkacem@ulg.ac.BE [LESIA, UMR8109, Universite Pierre et Marie Curie, Universite Denis Diderot, Obs. de Paris, 92195 Meudon Cedex (France)
2011-01-01
Modelling amplitudes of stochastically excited oscillations in stars is a powerful tool for understanding the properties of the convective zones. For instance, it gives us information on the way turbulent eddies are temporally correlated in a very large Reynolds number regime. We discuss the way the time correlation between eddies is modelled and we present recent theoretical developments as well as observational results. Eventually, we discuss the physical underlying meaning of the results by introducing the Ornstein-Uhlenbeck process, which is a sub-class of a Gaussian Markov process.
Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia
2018-07-14
In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.
Hot nuclear matter in the modified quark-meson coupling model with quark-quark correlations
International Nuclear Information System (INIS)
Zakout, I.; Jaqaman, H.R.
2000-01-01
Short-range quark-quark correlations in hot nuclear matter are examined within the modified quark-meson coupling (MQMC) model by adding repulsive scalar and vector quark-quark interactions. Without these correlations, the bag radius increases with the baryon density. However, when the correlations are introduced the bag size shrinks as the bags overlap. Also as the strength of the scalar quark-quark correlation is increased, the decrease of the effective nucleon mass M* N with the baryonic density is slowed down and tends to saturate at high densities. Within this model we study the phase transition from the baryon-meson phase to the quark-gluon plasma (QGP) phase with the latter modelled as an ideal gas of quarks and gluons inside a bag. Two models for the QGP bag parameter are considered. In one case, the bag is taken to be medium-independent and the phase transition from the hadron phase to QGP is found to occur at five to eight times ordinary nuclear matter density for temperatures less than 60 MeV. For lower densities, the transition takes place at a higher temperature, reaching up to 130 MeV at zero density. In the second case, the QGP bag parameter is considered to be medium-dependent as in the MQMC model for the hadronic phase. In this case, it is found that the phase transition occurs at much lower densities. (author)
Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.
Martínez, C A; Khare, K; Rahman, S; Elzo, M A
2017-10-01
Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.
Bulk-boundary correlators in the hermitian matrix model and minimal Liouville gravity
International Nuclear Information System (INIS)
Bourgine, Jean-Emile; Ishiki, Goro; Rim, Chaiho
2012-01-01
We construct the one matrix model (MM) correlators corresponding to the general bulk-boundary correlation numbers of the minimal Liouville gravity (LG) on the disc. To find agreement between both discrete and continuous approach, we investigate the resonance transformation mixing boundary and bulk couplings. It leads to consider two sectors, depending on whether the matter part of the LG correlator is vanishing due to the fusion rules. In the vanishing case, we determine the explicit transformation of the boundary couplings at the first order in bulk couplings. In the non-vanishing case, no bulk-boundary resonance is involved and only the first order of pure boundary resonances have to be considered. Those are encoded in the matrix polynomials determined in our previous paper. We checked the agreement for the bulk-boundary correlators of MM and LG in several non-trivial cases. In this process, we developed an alternative method to derive the boundary resonance encoding polynomials.
Interpretation of correlated neural variability from models of feed-forward and recurrent circuits
2018-01-01
Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures—recurrent connections, shared feed-forward projections, and shared gain fluctuations—on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing. PMID:29408930
Effects of doping on spin correlations in the periodic Anderson model
International Nuclear Information System (INIS)
Bonca, J.; Gubernatis, J.E.
1998-01-01
We studied the effects of hole doping on spin correlations in the two-dimensional periodic Anderson model, mainly at the full and three-quarters-full lower bands cases. In the full lower band case, strong antiferromagnetic correlations develop when the on-site repulsive interaction strength U becomes comparable to the quasiparticle bandwidth. In the three-quarters full case, a kind of spin correlation develops that is consistent with the resonance between a (π,0) and a (0,π) spin-density wave. In this state the spins on different sublattices appear uncorrelated. Hole doping away from the completely full case rapidly destroys the long-range antiferromagnetic correlations, in a manner reminiscent of the destruction of antiferromagnetism in the Hubbard model. In contrast to the Hubbard model, the doping does not shift the peak in the magnetic structure factor from the (π,π) position. At dopings intermediate to the full and three-quarters full cases, only weak spin correlations exist. copyright 1998 The American Physical Society
Interpretation of correlated neural variability from models of feed-forward and recurrent circuits.
Directory of Open Access Journals (Sweden)
Volker Pernice
2018-02-01
Full Text Available Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing.
A two-scale model for correlation between B cell VDJ usage in zebrafish
Pan, Keyao; Deem, Michael
2011-03-01
The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.
Energy Technology Data Exchange (ETDEWEB)
Reimus, Paul W [Los Alamos National Laboratory
2010-12-08
A process-oriented modeling approach is implemented to examine the importance of parameter variances, correlation lengths, and especially cross-correlations in contaminant transport predictions over large scales. It is shown that the most important consideration is the correlation between flow rates and retardation processes (e.g., sorption, matrix diffusion) in the system. lf flow rates are negatively correlated with retardation factors in systems containing multiple flow pathways, then characterizing these negative correlation(s) may have more impact on reactive transport modeling than microscale information. Such negative correlations are expected in porous-media systems where permeability is negatively correlated with clay content and rock alteration (which are usually associated with increased sorption). Likewise, negative correlations are expected in fractured rocks where permeability is positively correlated with fracture apertures, which in turn are negatively correlated with sorption and matrix diffusion. Parameter variances and correlation lengths are also shown to have important effects on reactive transport predictions, but they are less important than parameter cross-correlations. Microscale information pertaining to contaminant transport has become more readily available as characterization methods and spectroscopic instrumentation have achieved lower detection limits, greater resolution, and better precision. Obtaining detailed mechanistic insights into contaminant-rock-water interactions is becoming a routine practice in characterizing reactive transport processes in groundwater systems (almost necessary for high-profile publications). Unfortunately, a quantitative link between microscale information and flow and transport parameter distributions or cross-correlations has not yet been established. One reason for this is that quantitative microscale information is difficult to obtain in complex, heterogeneous systems. So simple systems that lack the
Statistical model of exotic rotational correlations in emergent space-time
Energy Technology Data Exchange (ETDEWEB)
Hogan, Craig; Kwon, Ohkyung; Richardson, Jonathan
2017-06-06
A statistical model is formulated to compute exotic rotational correlations that arise as inertial frames and causal structure emerge on large scales from entangled Planck scale quantum systems. Noncommutative quantum dynamics are represented by random transverse displacements that respect causal symmetry. Entanglement is represented by covariance of these displacements in Planck scale intervals defined by future null cones of events on an observer's world line. Light that propagates in a nonradial direction inherits a projected component of the exotic rotational correlation that accumulates as a random walk in phase. A calculation of the projection and accumulation leads to exact predictions for statistical properties of exotic Planck scale correlations in an interferometer of any configuration. The cross-covariance for two nearly co-located interferometers is shown to depart only slightly from the autocovariance. Specific examples are computed for configurations that approximate realistic experiments, and show that the model can be rigorously tested.
DEFF Research Database (Denmark)
Jepsen, Allan Dam; Hvam, Lars
2010-01-01
In order for companies to make well founded decisions on the product family makeup, an understanding of the correlation between the complexity of the product family and business processes is required, though it is often not available. This paper investigates the potential of using the Product...... Variant Master (PVM) modeling technique and Process Flow Charts in combination, to analyze the correlation between complexity in product families and business processes. The approach is based on a visual modeling of the product assortment and the business processes. It is hypothesized that the combined...... use of the modeling techniques can allow for analysis and communication of the product family and business processes; as well as the connections between the two, with the potential of creating a single combined model. A case from a Danish industrial company is used for the purpose of the investigation...
W-infinity ward identities and correlation functions in the c = 1 matrix model
International Nuclear Information System (INIS)
Das, S.R.; Dhar, A.; Mandal, G.; Wadia, S.R.
1992-01-01
In this paper, the authors explore consequences of W-infinity symmetry in the fermionic field theory of the c = 1 matrix model. The authors derive exact Ward identities relating correlation functions of the bilocal operator. These identities can be expressed as equations satisfied by the effective action of a three-dimensional theory and contain non-perturbative information about the model. The authors use thee identities to calculate the two-point function of the bilocal operator in the double scaling limit. The authors extract the operator whose two-point correlator has a single pole at an (imaginary) integer value of the energy. The authors then rewrite the W-infinity charges in terms of operators in the matrix model and use this to derive constraints satisfied by the partition function of the matrix model with a general time dependent potential
From pair correlations to the quasi-particle-phonon nuclear model
International Nuclear Information System (INIS)
Solov'ev, V.G.
1986-01-01
Modern state of the nucleus theory is discussed. The main attention is paid to pair correlation theory of superconducting type and quasiparticle - phonon nucleus model. Pair correlation account allowed one to describe in detail a series of nucleus properties which did not fall within the framework of earlier known models as, for example, double-quasi-particle states in even-even deformed nuclei. To describe the wave function low-quasi-particle components at low, mean and high excitation energies, the nucleus quasi-particle-phonon model is formulated. The strength function method is used in the model and fragmentation of mono-quasi-particle, mono-phonon states and quasi-particle phonon state by many nuclear levels is calculated
Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.
2016-04-01
Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.
Directory of Open Access Journals (Sweden)
Yuankun Li
2018-02-01
Full Text Available Although correlation filter (CF-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.
DEFF Research Database (Denmark)
Guo, Yifei; Gao, Houlei; Wu, Qiuwei
2017-01-01
and WTGs outage. The wind speed correlation between different WFs is included in the two-dimensional multistate WF model by using an improved k-means clustering method. Then, the entire system with two WFs and a threeterminal VSC-HVDC system is modeled as a multi-state generation unit. The proposed model...... is applied to the Roy Billinton test system (RBTS) for adequacy studies. Both the probability and frequency indices are calculated. The effectiveness and accuracy of the combined model is validated by comparing results with the sequential Monte Carlo simulation (MCS) method. The effects of the outage of VSC-HVDC...... system and wind speed correlation on the system reliability were analyzed. Sensitivity analyses were conducted to investigate the impact of repair time of the offshore VSC-HVDC system on system reliability....
Oblique penetration modeling and correlation with field tests into a soil target
Energy Technology Data Exchange (ETDEWEB)
Longcope, D.B. Jr. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.
1996-09-01
An oblique penetration modeling procedure is evaluated by correlation with onboard acceleration data from a series of six penetration tests into Antelope Dry Lake soil at Tonopah Test Range, Nevada. The modeling represents both the loading which is coupled to the penetrator bending and the penetrator structure including connections between the major subsections. Model results show reasonable agreement with the data which validates the modeling procedure within a modest uncertainty related to accelerometer clipping and rattling of the telemetry package. The experimental and analytical results provide design guidance for the location and lateral restraint of components to reduce their shock environment.
Accounting for correlated observations in an age-based state-space stock assessment model
DEFF Research Database (Denmark)
Berg, Casper Willestofte; Nielsen, Anders
2016-01-01
Fish stock assessment models often relyon size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics base...... the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased....
Ma, Manman; Xu, Zhenli
2014-12-28
Electrostatic correlations and variable permittivity of electrolytes are essential for exploring many chemical and physical properties of interfaces in aqueous solutions. We propose a continuum electrostatic model for the treatment of these effects in the framework of the self-consistent field theory. The model incorporates a space- or field-dependent dielectric permittivity and an excluded ion-size effect for the correlation energy. This results in a self-energy modified Poisson-Nernst-Planck or Poisson-Boltzmann equation together with state equations for the self energy and the dielectric function. We show that the ionic size is of significant importance in predicting a finite self energy for an ion in an inhomogeneous medium. Asymptotic approximation is proposed for the solution of a generalized Debye-Hückel equation, which has been shown to capture the ionic correlation and dielectric self energy. Through simulating ionic distribution surrounding a macroion, the modified self-consistent field model is shown to agree with particle-based Monte Carlo simulations. Numerical results for symmetric and asymmetric electrolytes demonstrate that the model is able to predict the charge inversion at high correlation regime in the presence of multivalent interfacial ions which is beyond the mean-field theory and also show strong effect to double layer structure due to the space- or field-dependent dielectric permittivity.
Self-consistent field model for strong electrostatic correlations and inhomogeneous dielectric media
Energy Technology Data Exchange (ETDEWEB)
Ma, Manman, E-mail: mmm@sjtu.edu.cn; Xu, Zhenli, E-mail: xuzl@sjtu.edu.cn [Department of Mathematics, Institute of Natural Sciences, and MoE Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240 (China)
2014-12-28
Electrostatic correlations and variable permittivity of electrolytes are essential for exploring many chemical and physical properties of interfaces in aqueous solutions. We propose a continuum electrostatic model for the treatment of these effects in the framework of the self-consistent field theory. The model incorporates a space- or field-dependent dielectric permittivity and an excluded ion-size effect for the correlation energy. This results in a self-energy modified Poisson-Nernst-Planck or Poisson-Boltzmann equation together with state equations for the self energy and the dielectric function. We show that the ionic size is of significant importance in predicting a finite self energy for an ion in an inhomogeneous medium. Asymptotic approximation is proposed for the solution of a generalized Debye-Hückel equation, which has been shown to capture the ionic correlation and dielectric self energy. Through simulating ionic distribution surrounding a macroion, the modified self-consistent field model is shown to agree with particle-based Monte Carlo simulations. Numerical results for symmetric and asymmetric electrolytes demonstrate that the model is able to predict the charge inversion at high correlation regime in the presence of multivalent interfacial ions which is beyond the mean-field theory and also show strong effect to double layer structure due to the space- or field-dependent dielectric permittivity.
A Frank mixture copula family for modeling higher-order correlations of neural spike counts
International Nuclear Information System (INIS)
Onken, Arno; Obermayer, Klaus
2009-01-01
In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all pairwise and higher-order correlations. In contrast to the Farlie-Gumbel-Morgenstern copula family that shares this property, the Frank mixture copula can model strong correlations. We apply spike count models based on the Frank mixture copula to data generated by a network of leaky integrate-and-fire neurons and compare the goodness of fit to distributions based on the Farlie-Gumbel-Morgenstern family. Finally, we evaluate the importance of using proper single neuron spike count distributions on the Shannon information. We find notable deviations in the entropy that increase with decreasing firing rates. Moreover, we find that the Frank mixture family increases the log likelihood of the fit significantly compared to the Farlie-Gumbel-Morgenstern family. This shows that the Frank mixture copula is a useful tool to assess the importance of higher-order correlations in spike count codes.
Shell-model calculations with a basis that contains correlated pairs
International Nuclear Information System (INIS)
Boisson, J.P.; Silvestre-Brac, B.A.; Liotta, R.J.
1979-01-01
A method to solve the shell-model equations within a basis that contains correlated pairs of particles is presented. The method is illustrated for the three-identical-particle system. Applications in nuclei around 208 Pb are given and comparisons with both experimental data and other calculations are carried out. (Auth.)
Mean spherical model for hard ions and dipoles: Thermodynamics and correlation functions
International Nuclear Information System (INIS)
Vericat, F.; Blum, L.
1980-01-01
The solution of the mean spherical model of a mixture of equal-size hard ions and dipoles is reinvestigated. Simple expressions for the coefficients of the Laplace transform of the pair correlation function and the other thermodynamic properties are given
Raykov, Tenko
2011-01-01
Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
Some remarks on estimating a covariance structure model from a sample correlation matrix
Maydeu Olivares, Alberto; Hernández Estrada, Adolfo
2000-01-01
A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...
International Nuclear Information System (INIS)
Tourniaire, B. . E-mail bruno.tourniaire@cea.fr
2006-01-01
The prediction of heat transfer between corium pool and concrete basemat is of particular significance in the framework of the study of PWR's severe accident. Heat transfer directly governs the ablation velocity of concrete in case of molten core concrete interaction (MCCI) and, consequently, the time delay when the reactor cavity may fail. From a restricted hydrodynamic point of view, this issue is related to heat transfer between a heated bubbling pool and a porous wall with gas injection. Several experimental studies have been performed with simulant materials and many correlations have been provided to address this issue. The comparisons of the results of these correlations with the measurements and their extrapolation to reactor materials show that strong discrepancies between the results of these models are obtained which probably means that some phenomena are not well taken into account. The main purpose of this paper is to present an alternative heat transfer model which was originally developed for chemical engineering applications (bubble columns) by Deckwer. A part of this work is devoted to the presentation of this model, which is based on a surface renewal assumption. Comparison of the results of this model with available experimental data in different systems are presented and discussed. These comparisons clearly show that this model can be used to deal with the particular problem of MCCI. The analyses also lead to enrich the original model by taking into account the thermal resistance of the wall: a new formulation of the Deckwer's correlation is finally proposed
Entropy correlation and entanglement for mixed states in an algebraic model
International Nuclear Information System (INIS)
Hou Xiwen; Chen Jinghua; Wan Mingfang; Ma Zhongqi
2009-01-01
As an alternative with potential connections to actual experiments, other than the systems more usually used in the field of entanglement, the dynamics of entropy correlation and entanglement between two anharmonic vibrations in a well-established algebraic model, with parameters extracted from fitting to highly excited spectral experimental results for molecules H 2 O and SO 2 , is studied in terms of the linear entropy and two negativities for various initial states that are respectively taken to be the mixed density matrices of thermal states and squeezed states on each mode. For a suitable parameter in initial states the entropies in two stretches can show positive correlation or anti-correlation. And the linear entropy of each mode is positively correlated with the negativities just for the mixed-squeezed states with small parameters in H 2 O while they do not display any correlation in other cases. For the mixed-squeezed states the negativities exhibit dominantly positive correlations with an effective mutual entropy. The differences in the linear entropy and the negativities between H 2 O and SO 2 are discussed as well. Those are useful for molecular quantum computing and quantum information processing
Directory of Open Access Journals (Sweden)
Di Fang
Full Text Available Recent advances in statistical methods enable the study of correlation among outcomes through joint modeling, thereby addressing spillover effects. By joint modeling, we refer to simultaneously analyzing two or more different response variables emanating from the same individual. Using the 2011 Bangladesh Demographic and Health Survey, we jointly address spillover effects between contraceptive use (CUC and knowledge of HIV and other sexually transmitted diseases. Jointly modeling these two outcomes is appropriate because certain types of contraceptive use contribute to the prevention of HIV and STDs and the knowledge and awareness of HIV and STDs typically lead to protection during sexual intercourse. In particular, we compared the differences as they pertained to the interpretive advantage of modeling the spillover effects of joint modeling HIV and CUC as opposed to addressing them separately. We also identified risk factors that determine contraceptive use and knowledge of HIV and STDs among women in Bangladesh. We found that by jointly modeling the correlation between HIV knowledge and contraceptive use, the importance of education decreased. The HIV prevention program had a spillover effect on CUC: what seemed to be impacted by education can be partially contributed to one's exposure to HIV knowledge. The joint model revealed a less significant impact of covariates as opposed to both separate models and standard models. Additionally, we found a spillover effect that would have otherwise been undiscovered if we did not jointly model. These findings further suggested that the simultaneous impact of correlated outcomes can be adequately addressed for the commonality between different responses and deflate, which is otherwise overestimated when examined separately.
Spatio-temporal correlations in the Manna model in one, three and five dimensions
Willis, Gary; Pruessner, Gunnar
2018-02-01
Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five
Operator content of the critical Potts model in d dimensions and logarithmic correlations
International Nuclear Information System (INIS)
Vasseur, Romain; Jacobsen, Jesper Lykke
2014-01-01
Using the symmetric group S Q symmetry of the Q-state Potts model, we classify the (scalar) operator content of its underlying field theory in arbitrary dimension. In addition to the usual identity, energy and magnetization operators, we find fields that generalize the N-cluster operators well-known in two dimensions, together with their subleading counterparts. We give the explicit form of all these operators – up to non-universal constants – both on the lattice and in the continuum limit for the Landau theory. We compute exactly their two- and three-point correlation functions on an arbitrary graph in terms of simple probabilities, and give the general form of these correlation functions in the continuum limit at the critical point. Specializing to integer values of the parameter Q, we argue that the analytic continuation of the S Q symmetry yields logarithmic correlations at the critical point in arbitrary dimension, thus implying a mixing of some scaling fields by the scale transformation generator. All these logarithmic correlation functions are given a clear geometrical meaning, which can be checked in numerical simulations. Several physical examples are discussed, including bond percolation, spanning trees and forests, resistor networks and the Ising model. We also briefly address the generalization of our approach to the O(n) model
Correlation inequalities for two-component hypercubic /varreverse arrowphi/4 models
International Nuclear Information System (INIS)
Soria, J.L.
1988-01-01
A collection of new and already known correlation inequalities is found for a family of two-component hypercubic /varreverse arrowphi/ 4 models, using techniques of duplicated variables, rotated correlation inequalities, and random walk representation. Among the interesting new inequalities are: rotated very special Dunlop-Newman inequality 2 ; /varreverse arrowphi//sub 1z/ 2 + /varreverse arrowphi//sub 2z/ 2 ≥ 0, rotated Griffiths I inequality 2 - /varreverse arrowphi//sub 2z/ 2 > ≥ 0, and anti-Lebowitz inequality u 4 1111 ≥ 0
Rigorous spin-spin correlation function of Ising model on a special kind of Sierpinski Carpets
International Nuclear Information System (INIS)
Yang, Z.R.
1993-10-01
We have exactly calculated the rigorous spin-spin correlation function of Ising model on a special kind of Sierpinski Carpets (SC's) by means of graph expansion and a combinatorial approach and investigated the asymptotic behaviour in the limit of long distance. The result show there is no long range correlation between spins at any finite temperature which indicates no existence of phase transition and thus finally confirms the conclusion produced by the renormalization group method and other physical arguments. (author). 7 refs, 6 figs
Zigzagging causility model of EPR correlations and on the interpretation of quantum mechanics
International Nuclear Information System (INIS)
de Beauregard, O.C.
1988-01-01
Being formalized inside the S-matrix scheme, the zigzagging causility model of EPR correlations has full Lorentz and CPT invariance. EPR correlations, proper or reversed, and Wheeler's smoky dragon metaphor are respectively pictured in a spacetime or in the momentum-energy space, as V-shaped, anti LAMBDA-shaped, or C-shaped ABC zigzags, with a summation at B over virtual states absolute value B> = *. The reversibility = * implies that causality is CPT-invariant, or arrowless, at the microlevel. Arrowed causality is a macroscopic emergence, corollary to wave retardation and probability increase. Factlike irreversibility states repression, not suppression, of blind statistical retrodiction- that is, of final cause
Exact correlations in the Lieb-Liniger model and detailed balance out-of-equilibrium
Directory of Open Access Journals (Sweden)
Jacopo De Nardis, Miłosz Panfil
2016-12-01
Full Text Available We study the density-density correlation function of the 1D Lieb-Liniger model and obtain an exact expression for the small momentum limit of the static correlator in the thermodynamic limit. We achieve this by summing exactly over the relevant form factors of the density operator in the small momentum limit. The result is valid for any eigenstate, including thermal and non-thermal states. We also show that the small momentum limit of the dynamic structure factors obeys a generalized detailed balance relation valid for any equilibrium state.
Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S
2015-09-01
Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.
Zhang, Wei; Wang, Jun
2017-09-01
In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.
DEFF Research Database (Denmark)
Wellendorff, Jess; Lundgård, Keld Troen; Møgelhøj, Andreas
2012-01-01
A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding the overfit......A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding...... the energetics of intramolecular and intermolecular, bulk solid, and surface chemical bonding, and the developed optimization method explicitly handles making the compromise based on the directions in model space favored by different materials properties. The approach is applied to designing the Bayesian error...... sets validates the applicability of BEEF-vdW to studies in chemistry and condensed matter physics. Applications of the approximation and its Bayesian ensemble error estimate to two intricate surface science problems support this....
Security of statistical data bases: invasion of privacy through attribute correlational modeling
Energy Technology Data Exchange (ETDEWEB)
Palley, M.A.
1985-01-01
This study develops, defines, and applies a statistical technique for the compromise of confidential information in a statistical data base. Attribute Correlational Modeling (ACM) recognizes that the information contained in a statistical data base represents real world statistical phenomena. As such, ACM assumes correlational behavior among the database attributes. ACM proceeds to compromise confidential information through creation of a regression model, where the confidential attribute is treated as the dependent variable. The typical statistical data base may preclude the direct application of regression. In this scenario, the research introduces the notion of a synthetic data base, created through legitimate queries of the actual data base, and through proportional random variation of responses to these queries. The synthetic data base is constructed to resemble the actual data base as closely as possible in a statistical sense. ACM then applies regression analysis to the synthetic data base, and utilizes the derived model to estimate confidential information in the actual database.
A multi-scale model for correlation in B cell VDJ usage of zebrafish
International Nuclear Information System (INIS)
Pan, Keyao; Deem, Michael W
2011-01-01
The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment
A multi-scale model for correlation in B cell VDJ usage of zebrafish
Pan, Keyao; Deem, Michael W.
2011-10-01
The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.
Directory of Open Access Journals (Sweden)
Thibaud Rougier
Full Text Available Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa, an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5. We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local
An Introduction to the Use of Linear Models with Correlated Data
Directory of Open Access Journals (Sweden)
Benoît Laplante
2001-12-01
conventional methods for estimating the variances of these estimates may yield biased results. These two problems are different, but they are related. This paper provides an introduction to the problems caused by correlated data and to possible solutions to these problems. First, we present the two problems and try to specify the relations between the two as clearly as possible. Second, we provide a critical presentation of random effects, mixed effects and hierarchical models that would help researchers to see their relevance in other kinds of linear models, particularly the so-called measurement models.
Long-range correlation in synchronization and syncopation tapping: a linear phase correction model.
Directory of Open Access Journals (Sweden)
Didier Delignières
Full Text Available We propose in this paper a model for accounting for the increase in long-range correlations observed in asynchrony series in syncopation tapping, as compared with synchronization tapping. Our model is an extension of the linear phase correction model for synchronization tapping. We suppose that the timekeeper represents a fractal source in the system, and that a process of estimation of the half-period of the metronome, obeying a random-walk dynamics, combines with the linear phase correction process. Comparing experimental and simulated series, we show that our model allows accounting for the experimentally observed pattern of serial dependence. This model complete previous modeling solutions proposed for self-paced and synchronization tapping, for a unifying framework of event-based timing.
International Nuclear Information System (INIS)
Yamanaka, Masanori; Honjo, Shinsuke; Kohmoto, Mahito
1996-01-01
We investigate one-dimensional strongly correlated electron models which have the resonating-valence-bond state as the exact ground state. The correlation functions are evaluated exactly using the transfer matrix method for the geometric representations of the valence-bond states. In this method, we only treat matrices with small dimensions. This enables us to give analytical results. It is shown that the correlation functions decay exponentially with distance. The result suggests that there is a finite excitation gap, and that the ground state is insulating. Since the corresponding noninteracting systems may be insulating or metallic, we can say that the gap originates from strong correlation. The persistent currents of the present models are also investigated and found to be exactly vanishing
Hadron Azimuthal Correlations and Mach-like Structures in a Partonic/Hadronic Transport Model
International Nuclear Information System (INIS)
Ma, G.L.; Zhang, S.; Ma, Y.G.; Cai, X.Z.; Chen, J.H.; He, Z.J.; Huang, H.Z.; Long, J.L.; Shen, W.Q.; Shi, X.H.; Zhong, C.; Zuo, J.X.
2007-01-01
With a multi-phase transport model (AMPT) with both partonic and hadronic interactions, two- and three-particle azimuthal correlations in Au + Au collisions at s NN =200 GeV have been studied by the mixing-event technique. A Mach-like structure has been observed in two- and three-particle correlations in central collisions. It has been found that both partonic and hadronic dynamical mechanisms contribute to the Mach-like structure. However, only hadronic rescattering is unable to reproduce experimental amplitude of Mach-like structure, and parton cascade process is indispensable. The results of three-particle correlation indicate a partonic Mach-like shock wave can be produced by strong parton cascade in central Au+Au collisions
Equilibrium dynamical correlations in the Toda chain and other integrable models
Kundu, Aritra; Dhar, Abhishek
2016-12-01
We investigate the form of equilibrium spatiotemporal correlation functions of conserved quantities in the Toda lattice and in other integrable models. From numerical simulations we find that the correlations satisfy ballistic scaling with a remarkable collapse of data from different times. We examine special limiting choices of parameter values, for which the Toda lattice tends to either the harmonic chain or the equal mass hard-particle gas. In both these limiting cases, one can obtain the correlations exactly and we find excellent agreement with the direct Toda simulation results. We also discuss a transformation to "normal mode" variables, as commonly done in hydrodynamic theory of nonintegrable systems, and find that this is useful, to some extent, even for the integrable system. The striking differences between the Toda chain and a truncated version, expected to be nonintegrable, are pointed out.
About long range pairing correlations in the Hubbard U-t-t' models
International Nuclear Information System (INIS)
Moreo, A.
1991-01-01
Using a quantum Monte Carlo method the authors measured pair correlation functions with different symmetries as a function of the filling, U/t and t'/t for the Hubbard and U-t-t' models. For the first time the Monte Carlo results are presented for U/t larger than the bandwidth 8t, away from half-filling. D-wave and extended S-wave pairing correlations are enhanced. D-wave pairing is stronger at half-filling but this behavior is reversed when the filling decreases. However, none of the eight pairing correlations that were studied increases as a function of lattice size, which makes the existence of long range superconducting order unlikely. (author). 10 refs.; 5 figs
Low-temperature expansions and correlation functions of the Z3-chiral Potts model
International Nuclear Information System (INIS)
Han, N.S.; Honecker, A.
1993-04-01
Using perturbative methods we derive new results for the spectrum and correlation functions of the general Z 3 -chiral Potts quantum chain in the massive low-temperature phase. Explicit calculations of the ground state energy and the first excitations in the zero momentum sector give excellent approximations and confirm the general statement that the spectrum in the low-temperature phase of general Z n -spin quantum chains is identical to one in the high-temperature phase where the role of charge and boundary conditions are interchanged. Using a perturbative expansion of the ground state for the Z 3 model we are able to gain some insight in correlation functions. We argue that they might be oscillating and give estimates for the oscillation length as well as the correlation length. (orig.)
Logarithmic two-point correlation functions from a z=2 Lifshitz model
International Nuclear Information System (INIS)
Zingg, T.
2014-01-01
The Einstein-Proca action is known to have asymptotically locally Lifshitz spacetimes as classical solutions. For dynamical exponent z=2, two-point correlation functions for fluctuations around such a geometry are derived analytically. It is found that the retarded correlators are stable in the sense that all quasinormal modes are situated in the lower half-plane of complex frequencies. Correlators in the longitudinal channel exhibit features that are reminiscent of a structure usually obtained in field theories that are logarithmic, i.e. contain an indecomposable but non-diagonalizable highest weight representation. This provides further evidence for conjecturing the model at hand as a candidate for a gravity dual of a logarithmic field theory with anisotropic scaling symmetry
DEFF Research Database (Denmark)
Silvennoinen, Annestiina; Terasvirta, Timo
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations...
Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data
Zhou, Lan
2010-03-01
Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.
International Nuclear Information System (INIS)
Chung, Hyekyun; Poulsen, Per Rugaard; Keall, Paul J.; Cho, Seungryong; Cho, Byungchul
2016-01-01
Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation of the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior
Energy Technology Data Exchange (ETDEWEB)
Chung, Hyekyun [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea and Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 138-736 (Korea, Republic of); Poulsen, Per Rugaard [Department of Oncology, Aarhus University Hospital, Nørrebrogade 44, 8000 Aarhus C (Denmark); Keall, Paul J. [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Cho, Seungryong [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141 (Korea, Republic of); Cho, Byungchul, E-mail: cho.byungchul@gmail.com, E-mail: bcho@amc.seoul.kr [Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505 (Korea, Republic of)
2016-08-15
Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation of the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior
Directory of Open Access Journals (Sweden)
Cheng-Xiang Wang
2007-02-01
Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.
International Nuclear Information System (INIS)
Li, W.; Zhang, S.; Ma, Y. G.; Cai, X. Z.; Chen, J. H.; Ma, G. L.; Zhong, C.; Huang, H. Z.
2009-01-01
Dihadron azimuthal angle correlations relative to the reaction plane have been investigated in Au+Au collisions at √(s NN )=200 GeV using a multiphase transport model (AMPT). Such reaction plane azimuthal-angle-dependent correlations can shed light on the path-length effect of energy loss of high-transverse-momentum particles propagating through a hot dense medium. The correlations vary with the trigger particle azimuthal angle with respect to the reaction plane direction, φ s =φ T -Ψ EP , which is consistent with the experimental observation by the STAR Collaboration. The dihadron azimuthal angle correlation functions on the away side of the trigger particle present a distinct evolution from a single-peak to a broad, possibly double-peak structure when the trigger particle direction goes from in-plane to out-of-plane with the reaction plane. The away-side angular correlation functions are asymmetric with respect to the back-to-back direction in some regions of φ s , which could provide insight into the testing v 1 method for reconstructing the reaction plane. In addition, both the root-mean-square width (W rms ) of the away-side correlation distribution and the splitting parameter (D) between the away-side double peaks increase slightly with φ s , and the average transverse momentum of away-side-associated hadrons shows a strong φ s dependence. Our results indicate that a strong parton cascade and resultant energy loss could play an important role in the appearance of a double-peak structure in the dihadron azimuthal angular correlation function on the away side of the trigger particle.
Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.
Aprasoff, Jonathan; Donchin, Opher
2012-04-01
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.
Non-local correlation and quantum discord in two atoms in the non-degenerate model
International Nuclear Information System (INIS)
Mohamed, A.-B.A.
2012-01-01
By using geometric quantum discord (GQD) and measurement-induced nonlocality (MIN), quantum correlation is investigated for two atoms in the non-degenerate two-photon Tavis–Cummings model. It is shown that there is no asymptotic decay for MIN while asymptotic decay exists for GQD. Quantum correlations can be strengthened by introducing the dipole–dipole interaction. The evolvement period of quantum correlation gets shorter with the increase in the dipole–dipole parameter. It is found that there exists not only quantum nonlocality without entanglement but also quantum nonlocality without quantum discord. Also, the MIN and GQD are raised rather than entanglement, and also with weak initial entanglement, there are MIN and entanglement in a interval of death quantum discord. - Highlights: ► Geometric quantum discord (GQD) and measurement induced nonlocality (MIN) are used to investigate the correlations of two two-level atoms. ► There is no asymptotic decay for MIN while asymptotic decay exists for GQD. ► Quantum correlations can be strengthened by introducing the dipole–dipole interaction. ► There exists not only quantum nonlocality without entanglement but also without discord. ► Weak initial entanglement leads to MIN and entanglement in intervals of death discord.
Centrality and transverse momentum dependence of dihadron correlations in a hydrodynamic model
Castilho, Wagner M.; Qian, Wei-Liang
2018-06-01
In this work, we study the centrality as well as transverse momentum dependence of the dihadron correlation for Au+Au collisions at 200A GeV. The numerical simulations are carried out by using a hydrodynamical code NeXSPheRIO, where the initial conditions are obtained from a Regge-Gribov based microscopic model, NeXuS. In our calculations, the centrality windows are evaluated regarding multiplicity. The final correlations are obtained by the background subtraction via ZYAM methods, where higher harmonics are considered explicitly. The correlations are evaluated for the 0-20%, 20%-40% and 60%-92% centrality windows. Also, the transverse momentum dependence of the dihadron correlations is investigated. The obtained results are compared with experimental data. It is observed that the centrality dependence of the "ridge" and "double shoulder" structures is in consistency with the data. Based on specific set of parameters employed in the present study, it is found that different ZYAM subtraction schemes might lead to different features in the resultant correlations.
International Nuclear Information System (INIS)
Dupuis, M.; Karataglidis, S.; Bauge, E.; Delaroche, J.P.; Gogny, D.
2006-01-01
The random phase approximation (RPA) long-range correlations are known to play a significant role in understanding the depletion of single particle-hole states observed in (e,e ' ) and (e,e ' p) measurements. Here the RPA theory, implemented using the D1S force is considered for the specific purpose of building correlated ground states and related one-body density matrix elements. These may be implemented and tested in a fully microscopic optical model for NA scattering off doubly closed-shell nuclei. A method is presented to correct for the correlations overcounting inherent to the RPA formalism. One-body density matrix elements in the uncorrelated (i.e., Hartree-Fock) and correlated (i.e., RPA) ground states are then challenged in proton scattering studies based on the Melbourne microscopic optical model to highlight the role played by the RPA correlations. Agreement between the parameter free scattering predictions and measurements is good for incident proton energies ranging from 200 MeV down to approximately 60 MeV and becomes gradually worse in the lower energy range. Those features point unambiguously to the relevance of the g-matrix method to build microscopic optical model potentials at medium energies, and emphasize the need to include nucleon-phonon coupling, that is, a second-order component of the Feshbach type in the potential at lower energies. Illustrations are given for proton scattering observables measured up to 201 MeV for the 16 O, 40 Ca, 48 Ca, and 208 Pb target nuclei
Angle-correlated cross sections in the framework of the continuum shell model
International Nuclear Information System (INIS)
Moerschel, K.P.
1984-01-01
In the present thesis in the framework of the continuum shell modell a concept for the treatment of angle-correlated cross sections was developed by which coincidence experiments on electron scattering on nuclei are described. For this the existing Darmstadt continuum-shell-model code had to be extended to the calculation of the correlation coefficients in which nuclear dynamics enter and which determine completely the angle-correlated cross sections. Under inclusion of the kinematics a method for the integration over the scattered electron was presented and used for the comparison with corresponding experiments. As application correlation coefficients for the proton channel in 12 C with 1 - and 2 + excitations were studied. By means of these coefficients finally cross sections for the reaction 12 C (e,p) 11 B could be calculated and compared with the experiment whereby the developed methods were proved as suitable to predict correctly both the slope and the quantity of the experimental cross sections. (orig.) [de
Genotype-phenotype correlations in neurogenetics: Lesch-Nyhan disease as a model disorder.
Fu, Rong; Ceballos-Picot, Irene; Torres, Rosa J; Larovere, Laura E; Yamada, Yasukazu; Nguyen, Khue V; Hegde, Madhuri; Visser, Jasper E; Schretlen, David J; Nyhan, William L; Puig, Juan G; O'Neill, Patrick J; Jinnah, H A
2014-05-01
Establishing meaningful relationships between genetic variations and clinical disease is a fundamental goal for all human genetic disorders. However, these genotype-phenotype correlations remain incompletely characterized and sometimes conflicting for many diseases. Lesch-Nyhan disease is an X-linked recessive disorder that is caused by a wide variety of mutations in the HPRT1 gene. The gene encodes hypoxanthine-guanine phosphoribosyl transferase, an enzyme involved in purine metabolism. The fine structure of enzyme has been established by crystallography studies, and its function can be measured with very precise biochemical assays. This rich knowledge of genetic alterations in the gene and their functional effect on its protein product provides a powerful model for exploring factors that influence genotype-phenotype correlations. The present study summarizes 615 known genetic mutations, their influence on the gene product, and their relationship to the clinical phenotype. In general, the results are compatible with the concept that the overall severity of the disease depends on how mutations ultimately influence enzyme activity. However, careful evaluation of exceptions to this concept point to several additional genetic and non-genetic factors that influence genotype-phenotype correlations. These factors are not unique to Lesch-Nyhan disease, and are relevant to most other genetic diseases. The disease therefore serves as a valuable model for understanding the challenges associated with establishing genotype-phenotype correlations for other disorders.
Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei
2018-07-01
A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.
Killiches, Matthias; Czado, Claudia
2018-03-22
We propose a model for unbalanced longitudinal data, where the univariate margins can be selected arbitrarily and the dependence structure is described with the help of a D-vine copula. We show that our approach is an extremely flexible extension of the widely used linear mixed model if the correlation is homogeneous over the considered individuals. As an alternative to joint maximum-likelihood a sequential estimation approach for the D-vine copula is provided and validated in a simulation study. The model can handle missing values without being forced to discard data. Since conditional distributions are known analytically, we easily make predictions for future events. For model selection, we adjust the Bayesian information criterion to our situation. In an application to heart surgery data our model performs clearly better than competing linear mixed models. © 2018, The International Biometric Society.
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.
Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano
2016-11-15
Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.
McKim, Stephen A.
2016-01-01
This thesis describes the development and test data validation of the thermal model that is the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented to validate the model are presented. The thermal model was correlated to within plus or minus 3 degrees Centigrade of the thermal vacuum test data, and was found to be relatively insensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed, however, to refine the thermal model to further improve temperature predictions in the upper hemisphere of the propellant tank. Temperatures predictions in this portion were found to be 2-2.5 degrees Centigrade lower than the test data. A road map to apply the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
International Nuclear Information System (INIS)
Fyodorov, Yan V; Bouchaud, Jean-Philippe
2008-01-01
We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)
Energy Technology Data Exchange (ETDEWEB)
Fyodorov, Yan V [School of Mathematical Sciences, University of Nottingham, Nottingham NG72RD (United Kingdom); Bouchaud, Jean-Philippe [Science and Finance, Capital Fund Management 6-8 Bd Haussmann, 75009 Paris (France)
2008-09-19
We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)
Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models
DEFF Research Database (Denmark)
Yang, Bin; Guo, Chenjuan; Jensen, Christian S.
2013-01-01
of such time series offers insight into the underlying system and enables prediction of system behavior. While the techniques presented in the paper apply more generally, we consider the case of transportation systems and aim to predict travel cost from GPS tracking data from probe vehicles. Specifically, each...... road segment has an associated travel-cost time series, which is derived from GPS data. We use spatio-temporal hidden Markov models (STHMM) to model correlations among different traffic time series. We provide algorithms that are able to learn the parameters of an STHMM while contending...... with the sparsity, spatio-temporal correlation, and heterogeneity of the time series. Using the resulting STHMM, near future travel costs in the transportation network, e.g., travel time or greenhouse gas emissions, can be inferred, enabling a variety of routing services, e.g., eco-routing. Empirical studies...
Hadronic J/psi and charmed particle production and correlating quark rearrangement model
International Nuclear Information System (INIS)
Nishitani, Tadashi
1979-01-01
On the basis of the correlating quark rearrangement model, the exclusive and inclusive production cross sections of J/psi and charmed particles in hadron collisions are calculated. It is shown that the inclusive production cross section of charmed particles is several tens of μb at p sub( l) -- 100 GeV/c in hadron collisions. The OZI rule is discussed in connection with the production mechanism of J/psi particles. (author)
International Nuclear Information System (INIS)
Altsybeev, Igor
2016-01-01
In the present work, Monte-Carlo toy model with repulsing quark-gluon strings in hadron-hadron collisions is described. String repulsion creates transverse boosts for the string decay products, giving modifications of observables. As an example, long-range correlations between mean transverse momenta of particles in two observation windows are studied in MC toy simulation of the heavy-ion collisions
Effect of correlation on covariate selection in linear and nonlinear mixed effect models.
Bonate, Peter L
2017-01-01
The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Two site spin correlation function in Bethe-Peierls approximation for Ising model
Energy Technology Data Exchange (ETDEWEB)
Kumar, D [Roorkee Univ. (India). Dept. of Physics
1976-07-01
Two site spin correlation function for an Ising model above Curie temperature has been calculated by generalising Bethe-Peierls approximation. The results derived by a graphical method due to Englert are essentially the same as those obtained earlier by Elliott and Marshall, and Oguchi and Ono. The earlier results were obtained by a direct generalisation of the cluster method of Bethe, while these results are derived by retaining that class of diagrams , which is exact on Bethe lattice.
Thermal Testing and Model Correlation of the Magnetospheric Multiscale (MMS) Observatories
Kim, Jong S.; Teti, Nicholas M.
2015-01-01
The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth's magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. This paper presents the complete thermal balance (TB) test performed on the first of four observatories to go through thermal vacuum (TV) and the minibalance testing that was performed on the subsequent observatories to provide a comparison of all four. The TV and TB tests were conducted in a thermal vacuum chamber at the Naval Research Laboratory (NRL) in Washington, D.C. with the vacuum level higher than 1.3 x 10 (sup -4) pascals (10 (sup -6) torr) and the surrounding temperature achieving -180 degrees Centigrade. Three TB test cases were performed that included hot operational science, cold operational science and a cold survival case. In addition to the three balance cases a two hour eclipse and a four hour eclipse simulation was performed during the TV test to provide additional transient data points that represent the orbit in eclipse (or Earth's shadow) The goal was to perform testing such that the flight orbital environments could be simulated as closely as possible. A thermal model correlation between the thermal analysis and the test results was completed. Over 400 1-Wire temperature sensors, 200 thermocouples and 125 flight thermistor temperature sensors recorded data during TV and TB testing. These temperature versus time profiles and their agreements with the analytical results obtained using Thermal Desktop and SINDA/FLUINT are discussed. The model correlation for the thermal mathematical model (TMM) is conducted based on the numerical analysis results and the test data. The philosophy of model correlation was to correlate the model to within 3 degrees Centigrade of the test data using the standard deviation and mean deviation error
Directory of Open Access Journals (Sweden)
Yiming Hu
2017-06-01
Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.
A Hidden Markov Model Representing the Spatial and Temporal Correlation of Multiple Wind Farms
DEFF Research Database (Denmark)
Fang, Jiakun; Su, Chi; Hu, Weihao
2015-01-01
To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps is ado....... The proposed statistical modeling framework is compatible with the sequential power system reliability analysis. A case study on optimal sizing and location of fast-response regulation sources is presented.......To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps...... is adopted to categorize the similar output patterns of several wind farms into joint states. Then the hidden Markov model (HMM) is then designed to describe the temporal correlations among these joint states. Unlike the conventional Markov chain model, the accumulated wind power is taken into consideration...
Assessment of correlations and models for the prediction of CHF in water subcooled flow boiling
Celata, G. P.; Cumo, M.; Mariani, A.
1994-01-01
The present paper provides an analysis of available correlations and models for the prediction of Critical Heat Flux (CHF) in subcooled flow boiling in the range of interest of fusion reactors thermal-hydraulic conditions, i.e. high inlet liquid subcooling and velocity and small channel diameter and length. The aim of the study was to establish the limits of validity of present predictive tools (most of them were proposed with reference to light water reactors (LWR) thermal-hydraulic studies) in the above conditions. The reference dataset represents almost all available data (1865 data points) covering wide ranges of operating conditions in the frame of present interest (0.1 less than p less than 8.4 MPa; 0.3 less than D less than 25.4 mm; 0.1 less than L less than 0.61 m; 2 less than G less than 90.0 Mg/sq m/s; 90 less than delta T(sub sub,in) less than 230 K). Among the tens of predictive tools available in literature four correlations (Levy, Westinghouse, modified-Tong and Tong-75) and three models (Weisman and Ileslamlou, Lee and Mudawar and Katto) were selected. The modified-Tong correlation and the Katto model seem to be reliable predictive tools for the calculation of the CHF in subcooled flow boiling.
Assessment of correlations and models for prediction of CHF in subcooled flow boiling
International Nuclear Information System (INIS)
Celata, G.P.; Mariani, A.; Cumo, M.
1992-01-01
This paper provides an analysis of available correlations and models for the prediction of Critical Heat Flux (CHF) in subcooled flow boiling in the ranges of interest of fusion reactor thermal-hydraulic conditions, i.e., high inlet liquid subcooling and velocity and small channel diameter and length. The aim of the study was to establish the limits of validity of present predictive tools (most of them were proposed with reference to LWR thermal-hydraulic studies) in the above conditions. The reference data-set represents most of available data covering wide ranges of operating conditions in the framework of present interest (0.1 s ub, in < 230 K). Among the tens of predictive tools available in literature, four correlations (Levy, Westinghouse, modified-Tong and Tong-75) and three models (Weisman and Ileslamlou Lee and Mudawar and Katto) were selected. The modified-Tong correlation and the Katto model seem to be reliable predictive tools for the calculation of the CHF in subcooled flow boiling
International Nuclear Information System (INIS)
Schuetz, G.; Sandow, S.
1993-05-01
We consider systems of particles hopping stochastically on d-dimensional lattices with space-dependent probabilities. We map the master equation in a Fock space where the dynamics are given by a quantum Hamiltonian (continuous time) or a transfer matrix resp. (discrete time). We show that under certain conditions the time-dependent two-point density correlation function in N-particle steady state can be computed from the probability distribution of a single particle moving in the same environment. Focussing on exclusion models where the lattice site can be occupied by at most one particle we discuss as an example for such a stochastic process a generalized Heisenberg antiferromagnet where the strength of the spin-spin coupling in space-dependent. In discrete time one obtains for one dimensional systems the diagonal-to-diagonal transfer matrix of the two dimensional six vertex model with space dependent vertex weights. For a random distribution of the vertex weights one obtains a version of the random barrier model describing diffusion of particles in disordered media. We derive exact expressions for the average two-point density correlation function in the presence of weak, correlated disorder. (authors)
Higher genus correlators for the hermitian matrix model with multiple cuts
International Nuclear Information System (INIS)
Akemann, G.
1996-01-01
An iterative scheme is set up for solving the loop equation of the hermitian one-matrix model with a multi-cut structure. Explicit results are presented for genus one for an arbitrary but finite number of cuts. Due to the complicated form of the boundary conditions, the loop correlators now contain elliptic integrals. This demonstrates the existence of new universality classes for the hermitian matrix model. The two-cut solution is investigated in more detail, including the double scaling limit. It is shown that in special cases it differs from the known continuum solution with one cut. (orig.)
Fitting the CDO correlation skew: a tractable structural jump-diffusion model
DEFF Research Database (Denmark)
Willemann, Søren
2007-01-01
We extend a well-known structural jump-diffusion model for credit risk to handle both correlations through diffusion of asset values and common jumps in asset value. Through a simplifying assumption on the default timing and efficient numerical techniques, we develop a semi-analytic framework...... allowing for instantaneous calibration to heterogeneous CDS curves and fast computation of CDO tranche spreads. We calibrate the model to CDX and iTraxx data from February 2007 and achieve a satisfactory fit. To price the senior tranches for both indices, we require a risk-neutral probability of a market...
Differential models of twin correlations in skew for body-mass index (BMI).
Tsang, Siny; Duncan, Glen E; Dinescu, Diana; Turkheimer, Eric
2018-01-01
Body Mass Index (BMI), like most human phenotypes, is substantially heritable. However, BMI is not normally distributed; the skew appears to be structural, and increases as a function of age. Moreover, twin correlations for BMI commonly violate the assumptions of the most common variety of the classical twin model, with the MZ twin correlation greater than twice the DZ correlation. This study aimed to decompose twin correlations for BMI using more general skew-t distributions. Same sex MZ and DZ twin pairs (N = 7,086) from the community-based Washington State Twin Registry were included. We used latent profile analysis (LPA) to decompose twin correlations for BMI into multiple mixture distributions. LPA was performed using the default normal mixture distribution and the skew-t mixture distribution. Similar analyses were performed for height as a comparison. Our analyses are then replicated in an independent dataset. A two-class solution under the skew-t mixture distribution fits the BMI distribution for both genders. The first class consists of a relatively normally distributed, highly heritable BMI with a mean in the normal range. The second class is a positively skewed BMI in the overweight and obese range, with lower twin correlations. In contrast, height is normally distributed, highly heritable, and is well-fit by a single latent class. Results in the replication dataset were highly similar. Our findings suggest that two distinct processes underlie the skew of the BMI distribution. The contrast between height and weight is in accord with subjective psychological experience: both are under obvious genetic influence, but BMI is also subject to behavioral control, whereas height is not.
Lee, Dong Yeon; Seo, Sang Gyo; Kim, Eo Jin; Kim, Sung Ju; Lee, Kyoung Min; Farber, Daniel C; Chung, Chin Youb; Choi, In Ho
2015-01-01
Radiographic examination is a widely used evaluation method in the orthopedic clinic. However, conventional radiography alone does not reflect the dynamic changes between foot and ankle segments during gait. Multiple 3-dimensional multisegment foot models (3D MFMs) have been introduced to evaluate intersegmental motion of the foot. In this study, we evaluated the correlation between static radiographic indices and intersegmental foot motion indices. One hundred twenty-five females were tested. Static radiographs of full-leg and anteroposterior (AP) and lateral foot views were performed. For hindfoot evaluation, we measured the AP tibiotalar angle (TiTA), talar tilt (TT), calcaneal pitch, lateral tibiocalcaneal angle, and lateral talcocalcaneal angle. For the midfoot segment, naviculocuboid overlap and talonavicular coverage angle were calculated. AP and lateral talo-first metatarsal angles and metatarsal stacking angle (MSA) were measured to assess the forefoot. Hallux valgus angle (HVA) and hallux interphalangeal angle were measured. In gait analysis by 3D MFM, intersegmental angle (ISA) measurements of each segment (hallux, forefoot, hindfoot, arch) were recorded. ISAs at midstance phase were most highly correlated with radiography. Significant correlations were observed between ISA measurements using MFM and static radiographic measurements in the same segment. In the hindfoot, coronal plane ISA was correlated with AP TiTA (P foot motion indices at midstance phase during gait measured by 3D MFM gait analysis were correlated with the conventional radiographic indices. The observed correlation between MFM measurements at midstance phase during gait and static radiographic measurements supports the fundamental basis for the use of MFM in analysis of dynamic motion of foot segment during gait. © The Author(s) 2014.
Correlation among extinction efficiency and other parameters in an aggregate dust model
Dhar, Tanuj Kumar; Sekhar Das, Himadri
2017-10-01
We study the extinction properties of highly porous Ballistic Cluster-Cluster Aggregate dust aggregates in a wide range of complex refractive indices (1.4≤ n≤ 2.0, 0.001≤ k≤ 1.0) and wavelengths (0.11 {{μ }}{{m}}≤ {{λ }}≤ 3.4 {{μ }} m). An attempt has been made for the first time to investigate the correlation among extinction efficiency ({Q}{ext}), composition of dust aggregates (n,k), wavelength of radiation (λ) and size parameter of the monomers (x). If k is fixed at any value between 0.001 and 1.0, {Q}{ext} increases with increase of n from 1.4 to 2.0. {Q}{ext} and n are correlated via linear regression when the cluster size is small, whereas the correlation is quadratic at moderate and higher sizes of the cluster. This feature is observed at all wavelengths (ultraviolet to optical to infrared). We also find that the variation of {Q}{ext} with n is very small when λ is high. When n is fixed at any value between 1.4 and 2.0, it is observed that {Q}{ext} and k are correlated via a polynomial regression equation (of degree 1, 2, 3 or 4), where the degree of the equation depends on the cluster size, n and λ. The correlation is linear for small size and quadratic/cubic/quartic for moderate and higher sizes. We have also found that {Q}{ext} and x are correlated via a polynomial regression (of degree 3, 4 or 5) for all values of n. The degree of regression is found to be n and k-dependent. The set of relations obtained from our work can be used to model interstellar extinction for dust aggregates in a wide range of wavelengths and complex refractive indices.
Correlations in multiple production on nuclei and Glauber model of multiple scattering
International Nuclear Information System (INIS)
Zoller, V.R.; Nikolaev, N.N.
1982-01-01
Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei
Langevin Dynamics with Spatial Correlations as a Model for Electron-Phonon Coupling
Tamm, A.; Caro, M.; Caro, A.; Samolyuk, G.; Klintenberg, M.; Correa, A. A.
2018-05-01
Stochastic Langevin dynamics has been traditionally used as a tool to describe nonequilibrium processes. When utilized in systems with collective modes, traditional Langevin dynamics relaxes all modes indiscriminately, regardless of their wavelength. We propose a generalization of Langevin dynamics that can capture a differential coupling between collective modes and the bath, by introducing spatial correlations in the random forces. This allows modeling the electronic subsystem in a metal as a generalized Langevin bath endowed with a concept of locality, greatly improving the capabilities of the two-temperature model. The specific form proposed here for the spatial correlations produces a physical wave-vector and polarization dependency of the relaxation produced by the electron-phonon coupling in a solid. We show that the resulting model can be used for describing the path to equilibration of ions and electrons and also as a thermostat to sample the equilibrium canonical ensemble. By extension, the family of models presented here can be applied in general to any dense system, solids, alloys, and dense plasmas. As an example, we apply the model to study the nonequilibrium dynamics of an electron-ion two-temperature Ni crystal.
Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S
2017-08-01
Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.
Taguchi, Katsuyuki; Polster, Christoph; Lee, Okkyun; Stierstorfer, Karl; Kappler, Steffen
2016-12-01
An x-ray photon interacts with photon counting detectors (PCDs) and generates an electron charge cloud or multiple clouds. The clouds (thus, the photon energy) may be split between two adjacent PCD pixels when the interaction occurs near pixel boundaries, producing a count at both of the pixels. This is called double-counting with charge sharing. (A photoelectric effect with K-shell fluorescence x-ray emission would result in double-counting as well). As a result, PCD data are spatially and energetically correlated, although the output of individual PCD pixels is Poisson distributed. Major problems include the lack of a detector noise model for the spatio-energetic cross talk and lack of a computationally efficient simulation tool for generating correlated Poisson data. A Monte Carlo (MC) simulation can accurately simulate these phenomena and produce noisy data; however, it is not computationally efficient. In this study, the authors developed a new detector model and implemented it in an efficient software simulator that uses a Poisson random number generator to produce correlated noisy integer counts. The detector model takes the following effects into account: (1) detection efficiency; (2) incomplete charge collection and ballistic effect; (3) interaction with PCDs via photoelectric effect (with or without K-shell fluorescence x-ray emission, which may escape from the PCDs or be reabsorbed); and (4) electronic noise. The correlation was modeled by using these two simplifying assumptions: energy conservation and mutual exclusiveness. The mutual exclusiveness is that no more than two pixels measure energy from one photon. The effect of model parameters has been studied and results were compared with MC simulations. The agreement, with respect to the spectrum, was evaluated using the reduced χ 2 statistics or a weighted sum of squared errors, χ red 2 (≥1), where χ red 2 =1 indicates a perfect fit. The model produced spectra with flat field irradiation that
Reliability Assessment of IGBT Modules Modeled as Systems with Correlated Components
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2013-01-01
configuration. The estimated system reliability by the proposed method is a conservative estimate. Application of the suggested method could be extended for reliability estimation of systems composing of welding joints, bolts, bearings, etc. The reliability model incorporates the correlation between...... was applied for the systems failure functions estimation. It is desired to compare the results with the true system failure function, which is possible to estimate using simulation techniques. Theoretical model development should be applied for the further research. One of the directions for it might...... be modeling the system based on the Sequential Order Statistics, by considering the failure of the minimum (weakest component) at each loading level. The proposed idea to represent the system by the independent components could also be used for modeling reliability by Sequential Order Statistics....
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.
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.
Implementing the correlated fermi gas nuclear model for quasielastic neutrino-nucleus scattering
Tockstein, Jameson
2017-09-01
When studying neutrino oscillations an understanding of charged current quasielastic (CCQE) neutrino-nucleus scattering is imperative. This interaction depends on a nuclear model as well as knowledge of form factors. Neutrino experiments, such as MiniBooNE, often use the Relativistic Fermi Gas (RFG) nuclear model. Recently, the Correlated Fermi Gas (CFG) nuclear model was suggested in, based on inclusive and exclusive scattering experiments at JLab. We implement the CFG model for CCQE scattering. In particular, we provide analytic expressions for this implementation that can be used to analyze current and future neutrino CCQE data. This project was supported through the Wayne State University REU program under NSF Grant PHY-1460853 and by the DOE Grant DE-SC0007983.
Camporese, Matteo; Botto, Anna
2017-04-01
Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows us to integrate multisource observation data in modeling predictions and, in doing so, to reduce uncertainty. For this reason, data assimilation has been recently the focus of much attention also for physically-based integrated hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). One of the typical assumptions in these studies is that the measurement errors are uncorrelated, whereas in certain situations it is reasonable to believe that some degree of correlation occurs, due for example to the fact that a pair of sensors share the same soil type. The goal of this study is to show if and how the measurement error correlations between different observation data play a significant role on assimilation results in a real-world application of an integrated hydrological model. The model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope. The physical model, located in the Department of Civil, Environmental and Architectural Engineering of the University of Padova (Italy), consists of a reinforced concrete box containing a soil prism with maximum height of 3.5 m, length of 6 m, and width of 2 m. The hillslope is equipped with sensors to monitor the pressure head and soil moisture responses to a series of generated rainfall events applied onto a 60 cm thick sand layer overlying a sandy clay soil. The measurement network is completed by two tipping bucket flow gages to measure the two components (subsurface and surface) of the outflow. By collecting
Energy Technology Data Exchange (ETDEWEB)
Leng, Shuai; Yu, Lifeng; Zhang, Yi; McCollough, Cynthia H. [Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Carter, Rickey [Department of Biostatistics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Toledano, Alicia Y. [Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, Maryland 20895 (United States)
2013-08-15
Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with −15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC
Improving stability of prediction models based on correlated omics data by using network approaches.
Directory of Open Access Journals (Sweden)
Renaud Tissier
Full Text Available Building prediction models based on complex omics datasets such as transcriptomics, proteomics, metabolomics remains a challenge in bioinformatics and biostatistics. Regularized regression techniques are typically used to deal with the high dimensionality of these datasets. However, due to the presence of correlation in the datasets, it is difficult to select the best model and application of these methods yields unstable results. We propose a novel strategy for model selection where the obtained models also perform well in terms of overall predictability. Several three step approaches are considered, where the steps are 1 network construction, 2 clustering to empirically derive modules or pathways, and 3 building a prediction model incorporating the information on the modules. For the first step, we use weighted correlation networks and Gaussian graphical modelling. Identification of groups of features is performed by hierarchical clustering. The grouping information is included in the prediction model by using group-based variable selection or group-specific penalization. We compare the performance of our new approaches with standard regularized regression via simulations. Based on these results we provide recommendations for selecting a strategy for building a prediction model given the specific goal of the analysis and the sizes of the datasets. Finally we illustrate the advantages of our approach by application of the methodology to two problems, namely prediction of body mass index in the DIetary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome study (DILGOM and prediction of response of each breast cancer cell line to treatment with specific drugs using a breast cancer cell lines pharmacogenomics dataset.
Post-test analysis of PANDA test P4
International Nuclear Information System (INIS)
Hart, J.; Woudstra, A.; Koning, H.
1999-01-01
The results of a post-test analysis of the integral system test P4, which has been executed in the PANDA facility at PSI in Switzerland within the framework of Work Package 2 of the TEPSS project are presented. The post-test analysis comprises an evaluation of the PANDA test P4 and a comparison of the test results with the results of simulations using the RELAPS/MOD3.2, TRAC-BF1, and MELCOR 1.8.4 codes. The PANDA test P4 has provided data about how trapped air released from the drywell later in the transient affects PCCS performance in an adequate manner. The well-defined measurements can serve as an important database for the assessment of thermal hydraulic system analysis codes, especially for conditions that could be met in passively operated advanced reactors, i.e. low pressure and small driving forces. Based on the analysis of the test data, the test acceptance criteria have been met. The test P4 has been successfully completed and the instrument readings were with the permitted ranges. The PCCs showed a favorable and robust performance and a wide margin for decay heat removal from the containment. The PANDA P4 test demonstrated that trapped air, released from the drywell later in the transient, only temporarily and only slightly affected the performance of the passive containment cooling system. The analysis of the results of the RELAPS code showed that the overall behaviour of the test has been calculated quite well with regards to pressure, mass flow rates, and pool boil-down. This accounts both for the pre-test and the post-test simulations. However, due to the one-dimensional, stacked-volume modeling of the PANDA DW, WW, and GDCS vessels, 3D-effects such as in-vessel mixing and recirculation could not be calculated. The post-test MELCOR simulation showed an overall behaviour that is comparable to RELAPS. However, MELCOR calculated almost no air trapping in the PCC tubes that could hinder the steam condensation rate. This resulted in lower calculated
Directory of Open Access Journals (Sweden)
Susila Sumartiningsih
2015-06-01
Full Text Available ABSTRACT The learning model is one of the enabling factors that influence the achievement of students. That students have a good learning outcomes the lecturer must choose appropriate learning models. But in fact not all lecturers choose the most appropriate learning model with the demands of learning outcomes and student characteristics.The study design was descriptive quantitative correlation. Total population of 785 the number of samples are 202 were taken by purposive sampling. Techniques of data collection is done by cross-sectional and then processed through the Spearman test. The results showed no significant relationship between classroom lecture method in the context of blended learning models to study the effectiveness perspective the p value of 0.001. There is a significant relationship between e-learning methods in the context of blended learning models with perspective of activities study of nursing students the p value of 0.028. There is a significant relationship between learning model of blended learning with the perspective of nursing students learning effectiveness p value 0.167. Researchers recommend to future researchers conduct more research on the comparison between the effectiveness of the learning model based on student learning centers with the e-learning models and its impact on student achievement of learning competencies as well as to the implications for other dimensions of learning outcomes and others.
One-loop correlation functions in the model of noncritical fermionic strings
International Nuclear Information System (INIS)
Belokurov, V.V.; Iofa, M.Z.
1996-01-01
In the model of noncritical fermionic strings, the David-Distler-Kawai ansatz is used to study one-loop n-point (n≤4) correlation functions for the vertex operators of massless bosonic states. The action functional of the model is the sum of super-Liouville action functional for the conformal mode and the action functional of d scalar supermultiplets. It is assumed that the total cosmological term is equal to zero. The amplitudes are calculated as the residues at the pole of the correlation function that corresponds to the conservation of Liouville momentum in the form Σβi=Q(1-h), where Q=√(9-d)/2 and h is the genus of the work sheet. In the one-loop approximation, the amplitudes can be obtained in the modular-invariant form, provided that the coefficients appearing in the sum over spin structures depend on moduli. In this case, the modular measure is defined up to a modular-invariant factor. This arbitrariness can be used to represent one-point correlation functions in the same functional form as for strings of critical dimension
A review of gene-environment correlations and their implications for autism: a conceptual model.
Meek, Shantel E; Lemery-Chalfant, Kathryn; Jahromi, Laudan B; Valiente, Carlos
2013-07-01
A conceptual model is proposed that explains how gene-environment correlations and the multiplier effect function in the context of social development in individuals with autism. The review discusses the current state of autism genetic research, including its challenges, such as the genetic and phenotypic heterogeneity of the disorder, and its limitations, such as the lack of interdisciplinary work between geneticists and social scientists. We discuss literature on gene-environment correlations in the context of social development and draw implications for individuals with autism. The review expands upon genes, behaviors, types of environmental exposure, and exogenous variables relevant to social development in individuals on the autism spectrum, and explains these factors in the context of the conceptual model to provide a more in-depth understanding of how the effects of certain genetic variants can be multiplied by the environment to cause largely phenotypic individual differences. Using the knowledge gathered from gene-environment correlations and the multiplier effect, we outline novel intervention directions and implications. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Deformed model Sp(4) model for studying pairing correlations in atomic nuclei
Georgieva, A I; Sviratcheva, K
2002-01-01
A fermion representation of the compact symplectic sp(4) algebra introduces a theoretical framework for describing pairing correlations in atomic nuclei. The important non-deformed and deformed subalgebras of sp sub ( sub q sub ) (4) and the corresponding reduction chains are explored for the multiple orbit problem. One realization of the u sub ( sub q sub ) (2) subalgebra is associated with the valence isospin, other reductions describe coupling between identical nucleons or proton-neutron pairs. Microscopic non-deformed and deformed Hamiltonians are expressed in terms of the generators of the sp(4) and sp sub q (4) algebras. In both cases eigenvalues of the isospin breaking Hamiltonian are fit to experimental ground state energies. The theory can be used to investigate the origin of the deformation and predict binding energies of nuclei in proton-rich regions. The q-deformation parameter changes the pairing strength and in so doing introduces a non-linear coupling into the collective degree of freedom
Directory of Open Access Journals (Sweden)
J. Florian Wellmann
2013-04-01
Full Text Available The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random variables. In the work presented here, joint entropy, conditional entropy, and mutual information are applied for a detailed analysis of spatial uncertainty correlations. The aim is to determine (i which areas in a spatial analysis share information, and (ii where, and by how much, additional information would reduce uncertainties. As an illustration, a typical geological example is evaluated: the case of a subsurface layer with uncertain depth, shape and thickness. Mutual information and multivariate conditional entropies are determined based on multiple simulated model realisations. Even for this simple case, the measures not only provide a clear picture of uncertainties and their correlations but also give detailed insights into the potential reduction of uncertainties at each position, given additional information at a different location. The methods are directly applicable to other types of spatial uncertainty evaluations, especially where multiple realisations of a model simulation are analysed. In summary, the application of information theoretic measures opens up the path to a better understanding of spatial uncertainties, and their relationship to information and prior knowledge, for cases where uncertain property distributions are spatially analysed and visualised in maps and models.
Impact of Forecast and Model Error Correlations In 4dvar Data Assimilation
Zupanski, M.; Zupanski, D.; Vukicevic, T.; Greenwald, T.; Eis, K.; Vonder Haar, T.
A weak-constraint 4DVAR data assimilation system has been developed at Cooper- ative Institute for Research in the Atmosphere (CIRA), Colorado State University. It is based on the NCEP's ETA 4DVAR system, and it is fully parallel (MPI coding). The CIRA's 4DVAR system is aimed for satellite data assimilation research, with cur- rent focus on assimilation of cloudy radiances and microwave satellite measurements. Most important improvement over the previous 4DVAR system is a degree of gener- ality introduced into the new algorithm, namely for applications with different NWP models (e.g., RAMS, WRF, ETA, etc.), and for the choice of control variable. In cur- rent applications, the non-hydrostatic RAMS model and its adjoint are used, including all microphysical processess. The control variable includes potential temperature, ve- locity potential and stream function, vertical velocity, and seven mixing ratios with respect to all water phases. Since the statistics of the microphysical components of the control variable is not well known, a special attention will be paid to the impact of the forecast and model (prior) error correlations on the 4DVAR analysis. In particular, the sensitivity of the analysis with respect to decorrelation length will be examined. The prior error covariances are modelled using the compactly-supported, space-limited correlations developed at NASA DAO.
The responses of a forest model to serial correlations of global warming
International Nuclear Information System (INIS)
Cohen, Y.; Pastor, J.
1991-01-01
Predictions of CO 2 -inducing changes to climate have focused on equilibrial responses of the global climate system to different levels of trace-gas forcings. The authors forced a forest ecosystem model with linear changes in temperature and precipitation and varied the degree of serial correlation around mean values. The ecosystem model considers the establishment and growth of individual trees in a 1/12 haplot and their responses to degree days, soil water deficits, soil nitrogen availability, and light. A recent formal analysis indicates that the model output is more sensitive to changes in means and variances of temperature, as opposed to precipitation. Of particular interest to the current paper is the assumption that the probability of mortality increases from about 10% to 30% upon two consecutive years of slow growth due to stress. Thus, year-to-year serial correlations could potentially increase mortality compared with random variation between years. Using this model, Pastor and Post (1988) showed that the forests of the boreal-northern hardwood transition zone in the Lake Superior region are particularly sensitive to climate warming
EEG correlates of cognitive time scales in the Necker-Zeno model for bistable perception.
Kornmeier, J; Friedel, E; Wittmann, M; Atmanspacher, H
2017-08-01
The Necker-Zeno model of bistable perception provides a formal relation between the average duration of meta-stable percepts (dwell times T) of ambiguous figures and two other basic time scales (t 0 , ΔT) underlying cognitive processing. The model predicts that dwell times T covary with t 0 , ΔT or both. We tested this prediction by exploiting that observers, in particular experienced meditators, can volitionally control dwell times T. Meditators and non-meditators observed bistable Necker cubes either passively or tried to hold their current percept. The latencies of a centro-parietal event-related potential (CPP) were recorded as a physiological correlate of t 0 . Dwell times T and the CPP latencies, correlated with t 0 , differed between conditions and observer groups, while ΔT remained constant in the range predicted by the model. The covariation of CPP latencies and dwell times, as well as their quadratic functional dependence extends previous psychophysical confirmation of the Necker-Zeno model to psychophysiological measures. Copyright © 2017. Published by Elsevier Inc.
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.
A network model of correlated growth of tissue stiffening in pulmonary fibrosis
Oliveira, Cláudio L. N.; Bates, Jason H. T.; Suki, Béla
2014-06-01
During the progression of pulmonary fibrosis, initially isolated regions of high stiffness form and grow in the lung tissue due to collagen deposition by fibroblast cells. We have previously shown that ongoing collagen deposition may not lead to significant increases in the bulk modulus of the lung until these local remodeled regions have become sufficiently numerous and extensive to percolate in a continuous path across the entire tissue (Bates et al 2007 Am. J. Respir. Crit. Care Med. 176 617). This model, however, did not include the possibility of spatially correlated deposition of collagen. In the present study, we investigate whether spatial correlations influence the bulk modulus in a two-dimensional elastic network model of lung tissue. Random collagen deposition at a single site is modeled by increasing the elastic constant of the spring at that site by a factor of 100. By contrast, correlated collagen deposition is represented by stiffening the springs encountered along a random walk starting from some initial spring, the rationale being that excess collagen deposition is more likely in the vicinity of an already stiff region. A combination of random and correlated deposition is modeled by performing random walks of length N from randomly selected initial sites, the balance between the two processes being determined by N. We found that the dependence of bulk modulus, B(N,c), on both N and the fraction of stiff springs, c, can be described by a strikingly simple set of empirical equations. For c0.8, B(N,c) is linear in c and independent of N, such that B(N,c)=100\\;{{B}_{0}}-100{{a}_{III}}(1-c){{B}_{0}}, where {{a}_{III}}=2.857. For small concentrations, the physiologically most relevant regime, the forces in the network springs are distributed according to a power law. When c = 0.3, the exponent of this power law increases from -4.5, when N = 1, and saturates to about -2, as N increases above 40. These results suggest that the spatial correlation of
Global unitary fixing and matrix-valued correlations in matrix models
International Nuclear Information System (INIS)
Adler, Stephen L.; Horwitz, Lawrence P.
2003-01-01
We consider the partition function for a matrix model with a global unitary invariant energy function. We show that the averages over the partition function of global unitary invariant trace polynomials of the matrix variables are the same when calculated with any choice of a global unitary fixing, while averages of such polynomials without a trace define matrix-valued correlation functions, that depend on the choice of unitary fixing. The unitary fixing is formulated within the standard Faddeev-Popov framework, in which the squared Vandermonde determinant emerges as a factor of the complete Faddeev-Popov determinant. We give the ghost representation for the FP determinant, and the corresponding BRST invariance of the unitary-fixed partition function. The formalism is relevant for deriving Ward identities obeyed by matrix-valued correlation functions
Transverse spin correlations of the random transverse-field Ising model
Iglói, Ferenc; Kovács, István A.
2018-03-01
The critical behavior of the random transverse-field Ising model in finite-dimensional lattices is governed by infinite disorder fixed points, several properties of which have already been calculated by the use of the strong disorder renormalization-group (SDRG) method. Here we extend these studies and calculate the connected transverse-spin correlation function by a numerical implementation of the SDRG method in d =1 ,2 , and 3 dimensions. At the critical point an algebraic decay of the form ˜r-ηt is found, with a decay exponent being approximately ηt≈2 +2 d . In d =1 the results are related to dimer-dimer correlations in the random antiferromagnetic X X chain and have been tested by numerical calculations using free-fermionic techniques.
Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu
2014-01-01
This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.
Cluster-cluster correlations in the two-dimensional stationary Ising-model
International Nuclear Information System (INIS)
Klassmann, A.
1997-01-01
In numerical integration of the Cahn-Hillard equation, which describes Oswald rising in a two-phase matrix, N. Masbaum showed that spatial correlations between clusters scale with respect to the mean cluster size (itself a function of time). T. B. Liverpool showed by Monte Carlo simulations for the Ising model that the analogous correlations have a similar form. Both demonstrated that immediately around each cluster there is some depletion area followed by something like a ring of clusters of the same size as the original one. More precisely, it has been shown that the distribution of clusters around a given cluster looks like a sinus-curve decaying exponentially with respect to the distance to a constant value
Model of components in a process of acoustic diagnosis correlated with learning
International Nuclear Information System (INIS)
Seballos, S.; Costabal, H.; Matamala, P.
1992-06-01
Using Linden's functional scheme as a theoretical reference framework, we define a matrix of component for clinical and field applications in the acoustic diagnostic process and correlations with audiologic, learning and behavioral problems. It is expected that the model effectively contributes to classify and provide a greater knowledge about this multidisciplinary problem. Although the exact nature of this component is at present a matter to be defined, its correlation can be hypothetically established. Applying this descriptive and integral approach in the diagnostic process it is possible if not to avoid, at least to decrease, the uncertainties and assure the proper solutions becoming a powerful tool applicable to environmental studies and/or social claims. (author). 8 refs, 2 figs
Mass effects in three-point chronological current correlators in n-dimensional multifermion models
International Nuclear Information System (INIS)
Kucheryavyj, V.I.
1991-01-01
Three-types of quantities associated with three-point chronological fermion-current correlators having arbitrary Lorentz and internal structure are calculated in the n-dimensional multifermion models with different masses. The analysis of vector and axial-vector Ward identities for regular (finite) and dimensionally regularized values of these quantities is carried out. Quantum corrections to the canonical Ward identities are obtained. These corrections are generally homogenious functions of zeroth order in masses and under some definite conditions they are reduced to known axial-vector anomalies. The structure and properties of quantum corrections to AVV and AAA correlators in the four-dimension space-time are investigated in detail
Modeling fractal structure of city-size distributions using correlation functions.
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.
De Haas, Y; Janss, L L G; Kadarmideen, H N
2007-10-01
Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.
Malpetti, Daniele; Roscilde, Tommaso
2017-02-01
The mean-field approximation is at the heart of our understanding of complex systems, despite its fundamental limitation of completely neglecting correlations between the elementary constituents. In a recent work [Phys. Rev. Lett. 117, 130401 (2016), 10.1103/PhysRevLett.117.130401], we have shown that in quantum many-body systems at finite temperature, two-point correlations can be formally separated into a thermal part and a quantum part and that quantum correlations are generically found to decay exponentially at finite temperature, with a characteristic, temperature-dependent quantum coherence length. The existence of these two different forms of correlation in quantum many-body systems suggests the possibility of formulating an approximation, which affects quantum correlations only, without preventing the correct description of classical fluctuations at all length scales. Focusing on lattice boson and quantum Ising models, we make use of the path-integral formulation of quantum statistical mechanics to introduce such an approximation, which we dub quantum mean-field (QMF) approach, and which can be readily generalized to a cluster form (cluster QMF or cQMF). The cQMF approximation reduces to cluster mean-field theory at T =0 , while at any finite temperature it produces a family of systematically improved, semi-classical approximations to the quantum statistical mechanics of the lattice theory at hand. Contrary to standard MF approximations, the correct nature of thermal critical phenomena is captured by any cluster size. In the two exemplary cases of the two-dimensional quantum Ising model and of two-dimensional quantum rotors, we study systematically the convergence of the cQMF approximation towards the exact result, and show that the convergence is typically linear or sublinear in the boundary-to-bulk ratio of the clusters as T →0 , while it becomes faster than linear as T grows. These results pave the way towards the development of semiclassical numerical
Zebrafish as a correlative and predictive model for assessing biomaterial nanotoxicity.
Fako, Valerie E; Furgeson, Darin Y
2009-06-21
The lack of correlative and predictive models to assess acute and chronic toxicities limits the rapid pre-clinical development of new therapeutics. This barrier is due in part to the exponential growth of nanotechnology and nanotherapeutics, coupled with the lack of rigorous and robust screening assays and putative standards. It is a fairly simple and cost-effective process to initially screen the toxicity of a nanomaterial by using invitro cell cultures; unfortunately it is nearly impossible to imitate a complimentary invivo system. Small mammalian models are the most common method used to assess possible toxicities and biodistribution of nanomaterials in humans. Alternatively, Daniorerio, commonly known as zebrafish, are proving to be a quick, cheap, and facile model to conservatively assess toxicity of nanomaterials.
Chen, Baojiang; Zhou, Xiao-Hua
2013-05-01
Life history data arising in clusters with prespecified assessment time points for patients often feature incomplete data since patients may choose to visit the clinic based on their needs. Markov process models provide a useful tool describing disease progression for life history data. The literature mainly focuses on time homogeneous process. In this paper we develop methods to deal with non-homogeneous Markov process with incomplete clustered life history data. A correlated random effects model is developed to deal with the nonignorable missingness, and a time transformation is employed to address the non-homogeneity in the transition model. Maximum likelihood estimate based on the Monte-Carlo EM algorithm is advocated for parameter estimation. Simulation studies demonstrate that the proposed method works well in many situations. We also apply this method to an Alzheimer's disease study.
Directory of Open Access Journals (Sweden)
James G. McLarnon
2014-01-01
Full Text Available Animal models of Alzheimer’s disease (AD which emphasize activation of microglia may have particular utility in correlating proinflammatory activity with neurodegeneration. This paper reviews injection of amyloid-β (Aβ into rat brain as an alternative AD animal model to the use of transgenic animals. In particular, intrahippocampal injection of Aβ1-42 peptide demonstrates prominent microglial mobilization and activation accompanied by a significant loss of granule cell neurons. Furthermore, pharmacological inhibition of inflammatory reactivity is demonstrated by a broad spectrum of drugs with a common endpoint in conferring neuroprotection in peptide-injected animals. Peptide-injection models provide a focus on glial cell responses to direct peptide injection in rat brain and offer advantages in the study of the mechanisms underlying neuroinflammation in AD brain.
Green Grown- Bases of Bioeconomy Models in Correlation with Danubian Projects
Directory of Open Access Journals (Sweden)
Iudith Ipate
2015-08-01
Full Text Available The objective of the our study is to provide defined measureable indicators at the Romanian region level that to possibility over time transition to low carbon-economic and developed the bio-economic models in correlation with economic development in this areas. For implementing the global bio-economy models is important to develop the innovative research in cooperation with regional entrepreneur. In this context must to implementing the projects in cooperation with local authority, promoting common action to overcome the physical and socio-cultural barriers, and to better exploit the opportunities offered by the development of the cross-border area for a mid-longterm sustainable growth. In our research we developed one model using the series from water exploitation index (WEI, GDP per capita, CO2 emissions per capita (2emision and population growth – POP.
A correlated-k model of radiative transfer in the near-infrared windows of Venus
International Nuclear Information System (INIS)
Tsang, C.C.C.; Irwin, P.G.J.; Taylor, F.W.; Wilson, C.F.
2008-01-01
We present a correlated-k-based model for generating synthetic spectra in the near-infrared window regions, from 1.0 to 2.5 μm, emitted from the deep atmosphere of Venus on the nightside. This approach is applicable for use with any near-infrared instrument, ground-based and space-borne, for analysis of the thermal emissions in this spectral range. We also approach this work with the view of using the model, in conjunction with a retrieval algorithm, to retrieve minor species from the Venus Express/VIRTIS instrument. An existing radiative-transfer model was adapted for Venusian conditions to deal with the prevailing high pressures and temperatures and other conditions. A comprehensive four-modal cloud structure model based on Pollack et al. [Near-infrared light from venus' nightside: a spectroscopic analysis. Icarus 1993;103:1-42], using refractive indices for a 75% H 2 SO 4 25% H 2 O mixture from Palmer and Williams [Optical constants of sulfuric acid; application to the clouds of Venus? Appl Opt 1975;14(1):208-19], was also implemented. We then utilized a Mie scattering algorithm to account for the multiple scattering effect between cloud and haze layers that occur in the Venusian atmosphere. The correlated-k model is shown to produce good agreement with ground-based spectra of Venus in the near infrared, and to match the output from a line-by-line radiative-transfer model to better than 10%
A Correlated Model for Evaluating Performance and Energy of Cloud System Given System Reliability
Directory of Open Access Journals (Sweden)
Hongli Zhang
2015-01-01
Full Text Available The serious issue of energy consumption for high performance computing systems has attracted much attention. Performance and energy-saving have become important measures of a computing system. In the cloud computing environment, the systems usually allocate various resources (such as CPU, Memory, Storage, etc. on multiple virtual machines (VMs for executing tasks. Therefore, the problem of resource allocation for running VMs should have significant influence on both system performance and energy consumption. For different processor utilizations assigned to the VM, there exists the tradeoff between energy consumption and task completion time when a given task is executed by the VMs. Moreover, the hardware failure, software failure and restoration characteristics also have obvious influences on overall performance and energy. In this paper, a correlated model is built to analyze both performance and energy in the VM execution environment given the reliability restriction, and an optimization model is presented to derive the most effective solution of processor utilization for the VM. Then, the tradeoff between energy-saving and task completion time is studied and balanced when the VMs execute given tasks. Numerical examples are illustrated to build the performance-energy correlated model and evaluate the expected values of task completion time and consumed energy.
Zhang, Lei; Huang, Chunping; Lan, Yajia; Wang, Mianzhen
2015-12-01
To analyze the correlation between population characteristics and work ability of employees with a multilevel model, to investigate the important influencing factors for work ability, and to provide a basis for improvement in work ability. Work ability index (WAI)was applied to measure the work ability of 1686 subjects from different companies (n=6). MLwi N2.0 software was applied for two-level variance component model fitting. The WAI of employees showed differences between various companies (χ2=3.378 6, P=0.0660); working years was negatively correlated with WAI (χ2=38.229 2, P=0.0001), and the WAI of the employees with 20 or more working years was 1.63 lower than that of the employees with less than 20 working years; the work ability of manual workers was lower than that of mental-manual workers (χ2=8.2726, P=0.0040), and the work ability showed no significant difference between mental workers and mental-manual workers (χ2=2.086 0, P=0.148 7). From the perspective of probability, the multilevel model analysis reveals the differences in work ability of employees between different companies, and suggests that company, work type, and working years are the important influencing factors for work ability of employees. These factors should be improved and adjusted to protect or enhance the work ability of employees.
A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.
Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P
2013-01-01
We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.
Directory of Open Access Journals (Sweden)
Youn Shik Park
2016-08-01
Full Text Available Water quality samples are typically collected less frequently than flow since water quality sampling is costly. Load Estimator (LOADEST, provided by the United States Geological Survey, is used to predict water quality concentration (or load on days when flow data are measured so that the water quality data are sufficient for annual pollutant load estimation. However, there is a need to identify water quality data requirements for accurate pollutant load estimation. Measured daily sediment data were collected from 211 streams. Estimated annual sediment loads from LOADEST and subsampled data were compared to the measured annual sediment loads (true load. The means of flow for calibration data were correlated to model behavior. A regression equation was developed to compute the required mean of flow in calibration data to best calibrate the LOADEST regression model coefficients. LOADEST runs were performed to investigate the correlation between the mean flow in calibration data and model behaviors as daily water quality data were subsampled. LOADEST calibration data used sediment concentration data for flows suggested by the regression equation. Using the mean flow calibrated by the regression equation reduced errors in annual sediment load estimation from −39.7% to −10.8% compared to using all available data.
On the Entropy Based Associative Memory Model with Higher-Order Correlations
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Masahiro Nakagawa
2010-01-01
Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.
Directory of Open Access Journals (Sweden)
Vladimir Dmitrievich Bogdanov
2016-03-01
Full Text Available The most common international standards for the non-financial reporting are reviewed. The Global Reporting Initiative (GRI is determined as an optimal standard of sustainability reporting for the use in the Russian conditions. The environmental component of guidance on the compilation of G4 non-financial reporting of GRI standard is analyzed, the contribution of each aspect in terms of the overall picture of sustainability is determined. The progress of economic science has outlined the importance of incorporating natural components. Moreover, the value of biological resources would be increased through time, and therefore, the economic development of the company cannot be in isolation. To determine the degree of harmony between the economic development and ecological condition of the territory where the company carries out the economic activities, the application of new approaches and methods is necessary. Based on the statistical methods, a correlation model between economic development and environmental performance is developed to identify their relationship on the basis of non-financial reporting. The developed model of correlation can be used by a wide range of oil and gas companies and its general principles by the companies of different industries. The results may be of interest to stakeholders, also, it can be used for administrative purposes, to serve as a platform for forecasting and adoption of administrative decisions to achieve harmony between economic development and environmental performance. The model of correlation has been tested for the data of non-financial reporting of the Russian largest oil and gas company JSC “Surgutneftegas”. The testing has shown a positive relationship between the two systems of the company’s sustainable development: economy and ecology. This obtained result demonstrates a high level of social responsibility of the company in terms of environmental protection. A further study in this field can
Directory of Open Access Journals (Sweden)
Rajesh Karki
2013-02-01
Full Text Available Adverse environmental impacts of carbon emissions are causing increasing concerns to the general public throughout the world. Electric energy generation from conventional energy sources is considered to be a major contributor to these harmful emissions. High emphasis is therefore being given to green alternatives of energy, such as wind and solar. Wind energy is being perceived as a promising alternative. This source of energy technology and its applications have undergone significant research and development over the past decade. As a result, many modern power systems include a significant portion of power generation from wind energy sources. The impact of wind generation on the overall system performance increases substantially as wind penetration in power systems continues to increase to relatively high levels. It becomes increasingly important to accurately model the wind behavior, the interaction with other wind sources and conventional sources, and incorporate the characteristics of the energy demand in order to carry out a realistic evaluation of system reliability. Power systems with high wind penetrations are often connected to multiple wind farms at different geographic locations. Wind speed correlations between the different wind farms largely affect the total wind power generation characteristics of such systems, and therefore should be an important parameter in the wind modeling process. This paper evaluates the effect of the correlation between multiple wind farms on the adequacy indices of wind-integrated systems. The paper also proposes a simple and appropriate probabilistic analytical model that incorporates wind correlations, and can be used for adequacy evaluation of multiple wind-integrated systems.
Characteristic Value Method of Well Test Analysis for Horizontal Gas Well
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Xiao-Ping Li
2014-01-01
Full Text Available This paper presents a study of characteristic value method of well test analysis for horizontal gas well. Owing to the complicated seepage flow mechanism in horizontal gas well and the difficulty in the analysis of transient pressure test data, this paper establishes the mathematical models of well test analysis for horizontal gas well with different inner and outer boundary conditions. On the basis of obtaining the solutions of the mathematical models, several type curves are plotted with Stehfest inversion algorithm. For gas reservoir with closed outer boundary in vertical direction and infinite outer boundary in horizontal direction, while considering the effect of wellbore storage and skin effect, the pseudopressure behavior of the horizontal gas well can manifest four characteristic periods: pure wellbore storage period, early vertical radial flow period, early linear flow period, and late horizontal pseudoradial flow period. For gas reservoir with closed outer boundary both in vertical and horizontal directions, the pseudopressure behavior of the horizontal gas well adds the pseudosteady state flow period which appears after the boundary response. For gas reservoir with closed outer boundary in vertical direction and constant pressure outer boundary in horizontal direction, the pseudopressure behavior of the horizontal gas well adds the steady state flow period which appears after the boundary response. According to the characteristic lines which are manifested by pseudopressure derivative curve of each flow period, formulas are developed to obtain horizontal permeability, vertical permeability, skin factor, reservoir pressure, and pore volume of the gas reservoir, and thus the characteristic value method of well test analysis for horizontal gas well is established. Finally, the example study verifies that the new method is reliable. Characteristic value method of well test analysis for horizontal gas well makes the well test analysis
3D CFD computations of trasitional flows using DES and a correlation based transition model
DEFF Research Database (Denmark)
Sørensen, Niels N.; Bechmann, Andreas; Zahle, Frederik
2011-01-01
a circular cylinder from Re = 10 to 1 × 106 reproducing the cylinder drag crisis. The computations show good quantitative and qualitative agreement with the behaviour seen in experiments. This case shows that the methodology performs smoothly from the laminar cases at low Re to the turbulent cases at high Re......The present article describes the application of the correlation based transition model of Menter et al. in combination with the Detached Eddy Simulation (DES) methodology to two cases with large degree of flow separation typically considered difficult to compute. Firstly, the flow is computed over...
Superconducting correlations in the one- and two-band Hubbard models
International Nuclear Information System (INIS)
Jain, K.P.; Ramakumar, R.; Chancey, C.C.
1989-01-01
An approximate expression is derived for the generalized energy gap function Δ kμ for a system of interacting electrons in a narrow s-band. This function has the virtue that it interpolates between the weak interaction limit (BCS) and the intermediate coupling regime. Starting from the Cooper pairing state, the authors investigate the build-up of pairing correlations and study the properties of the generalized gap in these two regimes as a function of the band filling. The coupled equations for the gap and the band filling define the self-consistency conditions. A recent extension of this analysis to the two-band model is also discussed
Directory of Open Access Journals (Sweden)
Hussain Alkharusi
2013-01-01
Full Text Available The present study aims at deriving correlational models of students' perceptions of assessment tasks, motivational orientations, and learning strategies using canonical analyses. Data were collected from 198 Omani tenth grade students. Results showed that high degrees of authenticity and transparency in assessment were associated with positive students' self-efficacy and task value. Also, high degrees of authenticity, transparency, and diversity in assessment were associated with a strong reliance on deep learning strategies; whereas a high degree of congruence with planned learning and a low degree of authenticity were associated with more reliance on surface learning strategies. Implications for classroom assessment practice and research were discussed.
Tango, Fabio; Minin, Luca; Tesauri, Francesco; Montanari, Roberto
2010-03-01
This paper describes the field tests on a driving simulator carried out to validate the algorithms and the correlations of dynamic parameters, specifically driving task demand and drivers' distraction, able to predict drivers' intentions. These parameters belong to the driver's model developed by AIDE (Adaptive Integrated Driver-vehicle InterfacE) European Integrated Project. Drivers' behavioural data have been collected from the simulator tests to model and validate these parameters using machine learning techniques, specifically the adaptive neuro fuzzy inference systems (ANFIS) and the artificial neural network (ANN). Two models of task demand and distraction have been developed, one for each adopted technique. The paper provides an overview of the driver's model, the description of the task demand and distraction modelling and the tests conducted for the validation of these parameters. A test comparing predicted and expected outcomes of the modelled parameters for each machine learning technique has been carried out: for distraction, in particular, promising results (low prediction errors) have been obtained by adopting an artificial neural network.
RELAP5/MOD3 code manual. Volume 4, Models and correlations
International Nuclear Information System (INIS)
1995-08-01
The RELAP5 code has been developed for best-estimate transient simulation of light water reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents and operational transients such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems. Control system and secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems. RELAP5/MOD3 code documentation is divided into seven volumes: Volume I presents modeling theory and associated numerical schemes; Volume II details instructions for code application and input data preparation; Volume III presents the results of developmental assessment cases that demonstrate and verify the models used in the code; Volume IV discusses in detail RELAP5 models and correlations; Volume V presents guidelines that have evolved over the past several years through the use of the RELAP5 code; Volume VI discusses the numerical scheme used in RELAP5; and Volume VII presents a collection of independent assessment calculations
Forecasting model for energy consumption in South Africa correlated with the income
Energy Technology Data Exchange (ETDEWEB)
Siti, M.W.; Nicolae, D.V.; Jimoh, A.A. [Tshwane Univ. of Technology, Pretoria (South Africa). Dept. of Electrical Engineers
2008-07-01
Demand-side-management (DSM) programs are used to influence customer electricity usage and reduce capital and operating costs for electric utilities. Escalating fuel costs and regulatory pressure are now causing some municipalities to consider demand-side options as alternatives to traditional resource planning. A mathematical model for forecasting energy consumption in South Africa was presented in this paper. The model used data from an energy consumption audit conducted in South Africa, and was correlated to the income of consumers. The model was used to study the impact of society, personality, and fixed contribution indexes on electricity consumption. Results of the modelling study showed that a higher fixed contribution factor indicates a more developed economic infrastructure and higher electrical expenditure. The personality index influences dynamic expenditures that are likely to be improved by electricity awareness programs. The study also showed that small changes in the society index can have a significant impact on electricity consumption. The model can be extrapolated to predict load profiles for particular localities or communities based on household income data. The model can also be used to validate load shaping, profiling, and prediction approaches. 6 refs., 4 tabs., 6 figs.
International Nuclear Information System (INIS)
Li, Ke; Garrett, John; Chen, Guang-Hong
2013-01-01
Purpose: With the recently expanding interest and developments in x-ray differential phase contrast CT (DPC-CT), the evaluation of its task-specific detection performance and comparison with the corresponding absorption CT under a given radiation dose constraint become increasingly important. Mathematical model observers are often used to quantify the performance of imaging systems, but their correlations with actual human observers need to be confirmed for each new imaging method. This work is an investigation of the effects of stochastic DPC-CT noise on the correlation of detection performance between model and human observers with signal-known-exactly (SKE) detection tasks.Methods: The detectabilities of different objects (five disks with different diameters and two breast lesion masses) embedded in an experimental DPC-CT noise background were assessed using both model and human observers. The detectability of the disk and lesion signals was then measured using five types of model observers including the prewhitening ideal observer, the nonprewhitening (NPW) observer, the nonprewhitening observer with eye filter and internal noise (NPWEi), the prewhitening observer with eye filter and internal noise (PWEi), and the channelized Hotelling observer (CHO). The same objects were also evaluated by four human observers using the two-alternative forced choice method. The results from the model observer experiment were quantitatively compared to the human observer results to assess the correlation between the two techniques.Results: The contrast-to-detail (CD) curve generated by the human observers for the disk-detection experiments shows that the required contrast to detect a disk is inversely proportional to the square root of the disk size. Based on the CD curves, the ideal and NPW observers tend to systematically overestimate the performance of the human observers. The NPWEi and PWEi observers did not predict human performance well either, as the slopes of their CD
Identification of AR(I)MA processes for modelling temporal correlations of GPS observations
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
International Nuclear Information System (INIS)
Sadeghi, Rahmat
2005-01-01
The polymer Wilson model and the polymer NRTL model have been extended for the representation of the excess enthalpy of multicomponent polymer solutions. Applicability of obtained equations in the correlation of the excess enthalpies of polymer solutions has been examined. It is found that the both models are suitable models in representing the published excess enthalpy data for the tested polymer solutions
Weirich, S D; Cotler, H B; Narayana, P A; Hazle, J D; Jackson, E F; Coupe, K J; McDonald, C L; Langford, L A; Harris, J H
1990-07-01
Magnetic resonance imaging (MRI) provides a noninvasive method of monitoring the pathologic response to spinal cord injury. Specific MR signal intensity patterns appear to correlate with degrees of improvement in the neurologic status in spinal cord injury patients. Histologic correlation of two types of MR signal intensity patterns are confirmed in the current study using a rat animal model. Adult male Sprague-Dawley rats underwent spinal cord trauma at the midthoracic level using a weight-dropping technique. After laminectomy, 5- and 10-gm brass weights were dropped from designated heights onto a 0.1-gm impounder placed on the exposed dura. Animals allowed to regain consciousness demonstrated variable recovery of hind limb paraplegia. Magnetic resonance images were obtained from 2 hours to 1 week after injury using a 2-tesla MRI/spectrometer. Sacrifice under anesthesia was performed by perfusive fixation; spinal columns were excised en bloc, embedded, sectioned, and observed with the compound light microscope. Magnetic resonance axial images obtained during the time sequence after injury demonstrate a distinct correlation between MR signal intensity patterns and the histologic appearance of the spinal cord. Magnetic resonance imaging delineates the pathologic processes resulting from acute spinal cord injury and can be used to differentiate the type of injury and prognosis.
Development of the critical thickness correlation for an improvement of MARS code dryout model
International Nuclear Information System (INIS)
Jeon, J. H.; Lee, W. J.; Lee, E. C.
2002-01-01
The mechanical film dryout analysis defines that the critical heat flux arises when liquid film calculation from evaporation, droplet entrainment and deposition gets dryout. The dryout of film is generally assumed when film thickness becomes zero. However, it was proven that the complete dryout assumption can estimate CHF well for uniform heating case but can not simulate accurately for non-uniform heating case. The critical thickness concept is an appropriate approach physically because there is a possibility of instantaneous disappearance of liquid film when it gets very thin. Therefore, the dryout phenomenon was modeled introducing critical thickness concept and development of proper critical thickness correlation. In this study, MARS code and some steady state dryout experimental data were used to develop a critical thickness correlation. The version including new critical thickness correlation was assessed using the several dryout CHF tests of various test conditions including non uniform heating case and flow reduction transient test and the results showed enhanced agreement with the experimental data
Directory of Open Access Journals (Sweden)
Lazarus K. Mramba
2018-03-01
Full Text Available The aim of this study was to generate and evaluate the efficiency of improved field experiments while simultaneously accounting for spatial correlations and different levels of genetic relatedness using a mixed models framework for orthogonal and non-orthogonal designs. Optimality criteria and a search algorithm were implemented to generate randomized complete block (RCB, incomplete block (IB, augmented block (AB and unequally replicated (UR designs. Several conditions were evaluated including size of the experiment, levels of heritability, and optimality criteria. For RCB designs with half-sib or full-sib families, the optimization procedure yielded important improvements under the presence of mild to strong spatial correlation levels and relatively low heritability values. Also, for these designs, improvements in terms of overall design efficiency (ODE% reached values of up to 8.7%, but these gains varied depending on the evaluated conditions. In general, for all evaluated designs, higher ODE% values were achieved from genetically unrelated individuals compared to experiments with half-sib and full-sib families. As expected, accuracy of prediction of genetic values improved as levels of heritability and spatial correlations increased. This study has demonstrated that important improvements in design efficiency and prediction accuracies can be achieved by optimizing how the levels of a treatment are assigned to the experimental units.
International Nuclear Information System (INIS)
Cavan, A.E.; Wilson, P.L.; Meyer, J.; Berbeco, R.I.
2010-01-01
Full text: Accuracy of radiotherapy treatment of lung cancer is limited by respiratory induced tumour motion. Compensation for this motion is required to increase treatment efficacy. The lung tumour motion is related to motion of an external abdominal marker, but a reliable model of this correlation is essential. Three viscoelastic systems were developed, in order to determine the best model and analyse its effectiveness on clinical data. Three 1D viscoelastic systems (a spring and dash pot in parallel, series and a combination) were developed and compared using a simulated breathing pattern. The most effective model was applied to 60 clinical data sets (consisting of co-ordinates of tumour and abdominal motion) from multiple treatment fractions of ten patients. The model was optimised for each data set, and efficacy determined by calculating the root mean square (RMS) error between the mo elled position and the actual tumour motion. Upon application to clinical data the parallel configuration achieved an average RMS error of 0.95 mm (superior-inferior direction). The model had patient specific parameters, and displayed good consistency over extended treatment periods. The model ha dled amplitude, frequency and baseline variations of the input signal, and phase shifts between tumour and abdominal motions. This study has shown that a viscoelastic model can be used to cor relate internal lung tumour motion with an external abdominal signal. The ability to handle breathing pattern in'egularities is comparable or better than previous models. Extending the model to a full 3D, pr dictive system could allow clinical implementation for radiotherapy.
Crack phantoms: localized damage correlations and failure in network models of disordered materials
International Nuclear Information System (INIS)
Zaiser, M; Moretti, P; Lennartz-Sassinek, S
2015-01-01
We study the initiation of failure in network models of disordered materials such as random fuse and spring models, which serve as idealized representations of fracture processes in quasi-two-dimensional, disordered material systems. We consider two different geometries, namely rupture of thin sheets and delamination of thin films, and demonstrate that irrespective of geometry and implementation of the disorder (random failure thresholds versus dilution disorder) failure initiation is associated with the emergence of typical localized correlation structures in the damage patterns. These structures (‘crack phantoms’) exhibit well-defined characteristic lengths, which relate to the failure stress by scaling relations that are typical for critical crack nuclei in disorder-free materials. We discuss our findings in view of the fundamental nature of failure processes in materials with random microstructural heterogeneity. (paper)
Vector and Axial-Vector Correlators in AN Instanton-Like Quark Model
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.
Variational Wavefunction for the Periodic Anderson Model with Onsite Correlation Factors
Kubo, Katsunori; Onishi, Hiroaki
2017-01-01
We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model.
Variance-based sensitivity indices for stochastic models with correlated inputs
Energy Technology Data Exchange (ETDEWEB)
Kala, Zdeněk [Brno University of Technology, Faculty of Civil Engineering, Department of Structural Mechanics Veveří St. 95, ZIP 602 00, Brno (Czech Republic)
2015-03-10
The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.
Variance-based sensitivity indices for stochastic models with correlated inputs
International Nuclear Information System (INIS)
Kala, Zdeněk
2015-01-01
The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics
Variational wavefunction for the periodic anderson model with onsite correlation factors
International Nuclear Information System (INIS)
Kubo, Katsunori; Onishi, Hiroaki
2017-01-01
We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model. (author)
Mutual information as a two-point correlation function in stochastic lattice models
International Nuclear Information System (INIS)
Müller, Ulrich; Hinrichsen, Haye
2013-01-01
In statistical physics entropy is usually introduced as a global quantity which expresses the amount of information that would be needed to specify the microscopic configuration of a system. However, for lattice models with infinitely many possible configurations per lattice site it is also meaningful to introduce entropy as a local observable that describes the information content of a single lattice site. Likewise, the mutual information between two sites can be interpreted as a two-point correlation function which quantifies how much information a lattice site has about the state of another one and vice versa. Studying a particular growth model we demonstrate that the mutual information exhibits scaling properties that are consistent with the established phenomenological scaling picture. (paper)
A simple method for identifying parameter correlations in partially observed linear dynamic models.
Li, Pu; Vu, Quoc Dong
2015-12-14
Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a
Mulder, Willem H; Crawford, Forrest W
2015-01-07
Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Nazelie Kassabian
2014-06-01
Full Text Available Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs. This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold.
Pre-analysis techniques applied to area-based correlation aiming Digital Terrain Model generation
Directory of Open Access Journals (Sweden)
Maurício Galo
2005-12-01
Full Text Available Area-based matching is an useful procedure in some photogrammetric processes and its results are of crucial importance in applications such as relative orientation, phototriangulation and Digital Terrain Model generation. The successful determination of correspondence depends on radiometric and geometric factors. Considering these aspects, the use of procedures that previously estimate the quality of the parameters to be computed is a relevant issue. This paper describes these procedures and it is shown that the quality prediction can be computed before performing matching by correlation, trough the analysis of the reference window. This procedure can be incorporated in the correspondence process for Digital Terrain Model generation and Phototriangulation. The proposed approach comprises the estimation of the variance matrix of the translations from the gray levels in the reference window and the reduction of the search space using the knowledge of the epipolar geometry. As a consequence, the correlation process becomes more reliable, avoiding the application of matching procedures in doubtful areas. Some experiments with simulated and real data are presented, evidencing the efficiency of the studied strategy.
International Nuclear Information System (INIS)
Žukovič, Milan; Hristopulos, Dionissios T
2009-01-01
A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the N c -state Potts model, each point is assigned to one of N c classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of
Žukovič, Milan; Hristopulos, Dionissios T.
2009-02-01
A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of
Study of the tensor correlation in oxygen isotopes using mean-field-type and shell model methods
International Nuclear Information System (INIS)
Sugimoto, Satoru
2007-01-01
The tensor force plays important roles in nuclear structure. Recently, we have developed a mean-field-type model which can treat the two-particle-two-hole correlation induced by the tensor force. We applied the model to sub-closed-shell oxygen isotopes and found that an sizable attractive energy comes from the tensor force. We also studied the tensor correlation in 16O using a shell model including two-particle-two-hole configurations. In this case, quite a large attractive energy is obtained for the correlation energy from the tensor force
Pair correlation function decay in models of simple fluids that contain dispersion interactions.
Evans, R; Henderson, J R
2009-11-25
We investigate the intermediate-and longest-range decay of the total pair correlation function h(r) in model fluids where the inter-particle potential decays as -r(-6), as is appropriate to real fluids in which dispersion forces govern the attraction between particles. It is well-known that such interactions give rise to a term in q(3) in the expansion of [Formula: see text], the Fourier transform of the direct correlation function. Here we show that the presence of the r(-6) tail changes significantly the analytic structure of [Formula: see text] from that found in models where the inter-particle potential is short ranged. In particular the pure imaginary pole at q = iα(0), which generates monotonic-exponential decay of rh(r) in the short-ranged case, is replaced by a complex (pseudo-exponential) pole at q = iα(0)+α(1) whose real part α(1) is negative and generally very small in magnitude. Near the critical point α(1)∼-α(0)(2) and we show how classical Ornstein-Zernike behaviour of the pair correlation function is recovered on approaching the mean-field critical point. Explicit calculations, based on the random phase approximation, enable us to demonstrate the accuracy of asymptotic formulae for h(r) in all regions of the phase diagram and to determine a pseudo-Fisher-Widom (pFW) line. On the high density side of this line, intermediate-range decay of rh(r) is exponentially damped-oscillatory and the ultimate long-range decay is power-law, proportional to r(-6), whereas on the low density side this damped-oscillatory decay is sub-dominant to both monotonic-exponential and power-law decay. Earlier analyses did not identify the pseudo-exponential pole and therefore the existence of the pFW line. Our results enable us to write down the generic wetting potential for a 'real' fluid exhibiting both short-ranged and dispersion interactions. The monotonic-exponential decay of correlations associated with the pseudo-exponential pole introduces additional terms into
A network model of correlated growth of tissue stiffening in pulmonary fibrosis
International Nuclear Information System (INIS)
Oliveira, Cláudio L N; Suki, Béla; Bates, Jason H T
2014-01-01
During the progression of pulmonary fibrosis, initially isolated regions of high stiffness form and grow in the lung tissue due to collagen deposition by fibroblast cells. We have previously shown that ongoing collagen deposition may not lead to significant increases in the bulk modulus of the lung until these local remodeled regions have become sufficiently numerous and extensive to percolate in a continuous path across the entire tissue (Bates et al 2007 Am. J. Respir. Crit. Care Med. 176 617). This model, however, did not include the possibility of spatially correlated deposition of collagen. In the present study, we investigate whether spatial correlations influence the bulk modulus in a two-dimensional elastic network model of lung tissue. Random collagen deposition at a single site is modeled by increasing the elastic constant of the spring at that site by a factor of 100. By contrast, correlated collagen deposition is represented by stiffening the springs encountered along a random walk starting from some initial spring, the rationale being that excess collagen deposition is more likely in the vicinity of an already stiff region. A combination of random and correlated deposition is modeled by performing random walks of length N from randomly selected initial sites, the balance between the two processes being determined by N. We found that the dependence of bulk modulus, B(N,c), on both N and the fraction of stiff springs, c, can be described by a strikingly simple set of empirical equations. For c<0.3, B(N,c) exhibits exponential growth from its initial value according to B(N,c)≈B 0 exp(2c)[1+c β ln(N a I )], where β=0.994± 0.024 and a I =0.54±0.026. For intermediate concentrations of stiffening, 0.3⩽c⩽0.8, another exponential rule describes the bulk modulus as B(N,c)=4B 0 exp[a II (c−c c )], where a II and c c are parameters that depend on N. For c>0.8, B(N,c) is linear in c and independent of N, such that B(N,c)=100 B 0 −100a III (1−c)B 0
Physics of the Kitaev Model: Fractionalization, Dynamic Correlations, and Material Connections
Hermanns, M.; Kimchi, I.; Knolle, J.
2018-03-01
Quantum spin liquids have fascinated condensed matter physicists for decades because of their unusual properties such as spin fractionalization and long-range entanglement. Unlike conventional symmetry breaking, the topological order underlying quantum spin liquids is hard to detect experimentally. Even theoretical models are scarce for which the ground state is established to be a quantum spin liquid. The Kitaev honeycomb model and its generalizations to other tricoordinated lattices are chief counterexamples - they are exactly solvable, harbor a variety of quantum spin liquid phases, and are also relevant for certain transition metal compounds including the polymorphs of (Na,Li)2IrO3 iridates and RuCl3. In this review, we give an overview of the rich physics of the Kitaev model, including two-dimensional and three-dimensional fractionalization as well as dynamic correlations and behavior at finite temperatures. We discuss the different materials and argue how the Kitaev model physics can be relevant even though most materials show magnetic ordering at low temperatures.
International Nuclear Information System (INIS)
Suluksna, Keerati; Dechaumphai, Pramote; Juntasaro, Ekachai
2009-01-01
This paper presents mathematical expressions for two significant parameters which control the onset location and length of transition in the γ-Re θ transition model of Menter et al. [Menter, F.R., Langtry, R.B., Volker, S., Huang, P.G., 2005. Transition modelling for general purpose CFD codes. In: ERCOFTAC International Symposium on Engineering Turbulence Modelling and Measurements]. The expressions are formulated and calibrated by means of numerical experiments for predicting transitional boundary layers under the influences of freestream turbulence and pressure gradient. It was also found that the correlation for transition momentum thickness Reynolds number needs only to be expressed in terms of local turbulence intensity, so that the more complex form that includes pressure gradient effects is unnecessary. Transitional boundary layers on a flat plate both with and without pressure gradients are employed to assess the performance of these two expressions for predicting the transition. The results show that the proposed expressions can work well with the model of Menter et al. (2005)
A Spalart-Allmaras local correlation-based transition model for Thermo-fuid dynamics
D'Alessandro, V.; Garbuglia, F.; Montelpare, S.; Zoppi, A.
2017-11-01
The study of innovative energy systems often involves complex fluid flows problems and the Computational Fluid-Dynamics (CFD) is one of the main tools of analysis. It is important to put in evidence that in several energy systems the flow field experiences the laminar-to-turbulent transition. Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) are able to predict the flow transition but they are still inapplicable to the study of real problems due to the significant computational resources requirements. Differently standard Reynolds Averaged Navier Stokes (RANS) approaches are not always reliable since they assume a fully turbulent regime. In order to overcome this drawback in the recent years some locally formulated transition RANS models have been developed. In this work, we present a local correlation-based transition approach adding two equations that control the laminar-toturbulent transition process -γ and \\[\\overset{}{\\mathop{{{\\operatorname{Re}}θ, \\text{t}}}} \\] - to the well-known Spalart-Allmaras (SA) turbulence model. The new model was implemented within OpenFOAM code. The energy equation is also implemented in order to evaluate the model performance in thermal-fluid dynamics applications. In all the considered cases a very good agreement between numerical and experimental data was observed.
Navigational efficiency in a biased and correlated random walk model of individual animal movement.
Bailey, Joseph D; Wallis, Jamie; Codling, Edward A
2018-01-01
Understanding how an individual animal is able to navigate through its environment is a key question in movement ecology that can give insight into observed movement patterns and the mechanisms behind them. Efficiency of navigation is important for behavioral processes at a range of different spatio-temporal scales, including foraging and migration. Random walk models provide a standard framework for modeling individual animal movement and navigation. Here we consider a vector-weighted biased and correlated random walk (BCRW) model for directed movement (taxis), where external navigation cues are balanced with forward persistence. We derive a mathematical approximation of the expected navigational efficiency for any BCRW of this form and confirm the model predictions using simulations. We demonstrate how the navigational efficiency is related to the weighting given to forward persistence and external navigation cues, and highlight the counter-intuitive result that for low (but realistic) levels of error on forward persistence, a higher navigational efficiency is achieved by giving more weighting to this indirect navigation cue rather than direct navigational cues. We discuss and interpret the relevance of these results for understanding animal movement and navigation strategies. © 2017 by the Ecological Society of America.
International Nuclear Information System (INIS)
Backes, Steffen
2017-04-01
-local fluctuations. It has been successfully used to study the whole range of weakly to strongly correlated lattice models, including the metal-insulator transition, since even in the relevant dimensions of d = 2 and d = 3 spatial fluctuations are often small. The extension of DMFT towards realistic system by the use of DFT has been termed LDA+DMFT and has since then allowed for a significant improvement of the understanding of strongly correlated materials. We dedicate this thesis to the LDA+DMFT method and the study of the recently discovered ironpnictide superconductors, which are known to show effects of strong electronic correlations. Thus, in many cases these materials cannot be adequately described by a pure DFT approach alone and provide and ideal case for an investigation of their electronic properties within LDA+DMFT. We will first review the DFT method and point out what kind of approximations have to be made in practical calculations and what deficits they entail. Then we will give an introduction into the Green's function formalism in the real and imaginary time representation and discuss the resulting consequences like analytic continuation to pave the way for the derivation of the DMFT equations. After that, we will discuss the combination of DFT and DMFT into the LDA+DMFT method and how to set up the effective lattice models for practical calculations. Then we will apply the LDA+DMFT method to the hole-doped iron-pnictide superconductor KFe 2 As 2 , which we find to be a rather strongly correlated material that can only be reasonably described when electronic correlations are treated on a proper level beyond the the standard DFT approach. Our results show that the LDA+DMFT method is able to significantly improve the agreement of the theoretical calculation with experimental observations. Then we expand our study towards the isovalent series of KFe 2 As 2 , RbFe 2 As 2 and CsFe 2 As 2 , which we propose to show even stronger effects of electronic correlations due
Energy Technology Data Exchange (ETDEWEB)
Backes, Steffen
2017-04-15
-local fluctuations. It has been successfully used to study the whole range of weakly to strongly correlated lattice models, including the metal-insulator transition, since even in the relevant dimensions of d = 2 and d = 3 spatial fluctuations are often small. The extension of DMFT towards realistic system by the use of DFT has been termed LDA+DMFT and has since then allowed for a significant improvement of the understanding of strongly correlated materials. We dedicate this thesis to the LDA+DMFT method and the study of the recently discovered ironpnictide superconductors, which are known to show effects of strong electronic correlations. Thus, in many cases these materials cannot be adequately described by a pure DFT approach alone and provide and ideal case for an investigation of their electronic properties within LDA+DMFT. We will first review the DFT method and point out what kind of approximations have to be made in practical calculations and what deficits they entail. Then we will give an introduction into the Green's function formalism in the real and imaginary time representation and discuss the resulting consequences like analytic continuation to pave the way for the derivation of the DMFT equations. After that, we will discuss the combination of DFT and DMFT into the LDA+DMFT method and how to set up the effective lattice models for practical calculations. Then we will apply the LDA+DMFT method to the hole-doped iron-pnictide superconductor KFe{sub 2}As{sub 2}, which we find to be a rather strongly correlated material that can only be reasonably described when electronic correlations are treated on a proper level beyond the the standard DFT approach. Our results show that the LDA+DMFT method is able to significantly improve the agreement of the theoretical calculation with experimental observations. Then we expand our study towards the isovalent series of KFe{sub 2}As{sub 2}, RbFe{sub 2}As{sub 2} and CsFe{sub 2}As{sub 2}, which we propose to show even stronger
Quantum Correlation Properties in Two Qubits One-axis Spin Squeezing Model
Guo-Hui, Yang
2017-02-01
Using the concurrence (C) and quantum discord (QD) criterions, the quantum correlation properties in two qubits one-axis spin squeezing model with an external magnetic field are investigated. It is found that one obvious difference in the limit case T → 0 (ground state) is the sudden disappearance phenomenon (SDP) occured in the behavior of C, while not in QD. In order to further explain the SDP, we obtain the analytic expressions of ground state C and QD which reveal that the SDP is not really "entanglement sudden disappeared", it is decayed to zero very quickly. Proper tuning the parameters μ(the spin squeezing interaction in x direction) and Ω(the external magnetic field in z direction) not only can obviously broaden the scope of ground state C exists but also can enhance the value of ground state QD. For the finite temperature case, one evident difference is that the sudden birth phenomenon (SBP) is appeared in the evolution of C, while not in QD, and decreasing the coupling parameters μ or Ω can obviously prolong the time interval before entanglement sudden birth. The value of C and QD are both enhanced by increasing the parameters μ or Ω in finite temperature case. In addition, through investigating the effects of temperature T on the quantum correlation properties with the variation of Ω and μ, one can find that the temperature scope of C and QD exists are broadened with increasing the parameters μ or Ω, and one can obtain the quantum correlation at higher temperature through changing these parameters.
International Nuclear Information System (INIS)
Plakida, N. M.; Anton, L.; Adam, S. . Department of Theoretical Physics, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-76900 Bucharest - Magurele; RO); Adam, Gh. . Department of Theoretical Physics, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-76900 Bucharest - Magurele; RO)
2001-01-01
A microscopical theory of superconductivity in the two-band singlet-hole Hubbard model, in the strong coupling limit in a paramagnetic state, is developed. The model Hamiltonian is obtained by projecting the p-d model to an asymmetric Hubbard model with the lower Hubbard subband occupied by one-hole Cu d-like states and the upper Hubbard subband occupied by two-hole p-d singlet states. The model requires two microscopical parameters only, the p-d hybridization parameter t and the charge-transfer gap Δ. It was previously shown to secure an appropriate description of the normal state properties of the high -T c cuprates. To treat rigorously the strong correlations, the Hubbard operator technique within the projection method for the Green function is used. The Dyson equation is derived. In the molecular field approximation, d-wave superconducting pairing of conventional hole (electron) pairs in one Hubbard subband is found, which is mediated by the exchange interaction given by the interband hopping, J ij = 4 (t ij ) 2 / Δ. The normal and anomalous components of the self-energy matrix are calculated in the self-consistent Born approximation for the electron-spin-fluctuation scattering mediated by kinematic interaction of the second order of the intraband hopping. The derived numerical and analytical solutions predict the occurrence of singlet d x 2 -y 2 -wave pairing both in the d-hole and singlet Hubbard subbands. The gap functions and T c are calculated for different hole concentrations. The exchange interaction is shown to be the most important pairing interaction in the Hubbard model in the strong correlation limit, while the spin-fluctuation coupling results only in a moderate enhancement of T c . The smaller weight of the latter comes from two specific features: its vanishing inside the Brillouin zone (BZ) along the lines, |k x | + |k y |=π pointing towards the hot spots and the existence of a small energy shell within which the pairing is effective. By
Early warning model based on correlated networks in global crude oil markets
Yu, Jia-Wei; Xie, Wen-Jie; Jiang, Zhi-Qiang
2018-01-01
Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets.
Quantum correlated cluster mean-field theory applied to the transverse Ising model.
Zimmer, F M; Schmidt, M; Maziero, Jonas
2016-06-01
Mean-field theory (MFT) is one of the main available tools for analytical calculations entailed in investigations regarding many-body systems. Recently, there has been a surge of interest in ameliorating this kind of method, mainly with the aim of incorporating geometric and correlation properties of these systems. The correlated cluster MFT (CCMFT) is an improvement that succeeded quite well in doing that for classical spin systems. Nevertheless, even the CCMFT presents some deficiencies when applied to quantum systems. In this article, we address this issue by proposing the quantum CCMFT (QCCMFT), which, in contrast to its former approach, uses general quantum states in its self-consistent mean-field equations. We apply the introduced QCCMFT to the transverse Ising model in honeycomb, square, and simple cubic lattices and obtain fairly good results both for the Curie temperature of thermal phase transition and for the critical field of quantum phase transition. Actually, our results match those obtained via exact solutions, series expansions or Monte Carlo simulations.
On the zigzagging causility model of EPR correlations and on the interpretation of quantum mechanics
de Beauregard, O. Costa
1988-09-01
Being formalized inside the S-matrix scheme, the zigzagging causility model of EPR correlations has full Lorentz and CPT invariance. EPR correlations, proper or reversed, and Wheeler's smoky dragon metaphor are respectively pictured in spacetime or in the momentum-energy space, as V-shaped, A-shaped, or C-shaped ABC zigzags, with a summation at B over virtual states |B> = *. The formal parrallelism breaks down at the level of interpretation because (A|C) = ||2. CPT invariance implies the Fock and Watanabe principle that, in quantum mechanics, retarded (advanced) waves are used for prediction (retrodiction), an expression of which is = = , with |Φ> denoting a preparation, |Ψ> a measurement, and U the evolution operator. The transformation |Ψ> = |UΦ> or |Φ> = |U-1Ψ> exchanges the “preparation representation” and the “measurement representation” of a system and is ancillary in the formalization of the quantum chance game by the “wavelike algebra” of conditional amplitude. In 1935 EPR overlooked that a conditional amplitude = Σ between the two distant measurements is at stake, and that only measurements actually performed do make sense. The reversibility = * implies that causality is CPT-invariant, or arrowless, at the microlevel. Arrowed causality is a macroscopic emergence, corollary to wave retardation and probability increase. Factlike irreversibility states repression, not suppression, of “blind statistical retrodiction”—that is, of “final cause.”
Gozem, Samer; Huntress, Mark; Schapiro, Igor; Lindh, Roland; Granovsky, Alexander A; Angeli, Celestino; Olivucci, Massimo
2012-11-13
The ground state potential energy surface of the retinal chromophore of visual pigments (e.g., bovine rhodopsin) features a low-lying conical intersection surrounded by regions with variable charge-transfer and diradical electronic structures. This implies that dynamic electron correlation may have a large effect on the shape of the force fields driving its reactivity. To investigate this effect, we focus on mapping the potential energy for three paths located along the ground state CASSCF potential energy surface of the penta-2,4-dieniminium cation taken as a minimal model of the retinal chromophore. The first path spans the bond length alternation coordinate and intercepts a conical intersection point. The other two are minimum energy paths along two distinct but kinetically competitive thermal isomerization coordinates. We show that the effect of introducing the missing dynamic electron correlation variationally (with MRCISD) and perturbatively (with the CASPT2, NEVPT2, and XMCQDPT2 methods) leads, invariably, to a stabilization of the regions with charge transfer character and to a significant reshaping of the reference CASSCF potential energy surface and suggesting a change in the dominating isomerization mechanism. The possible impact of such a correction on the photoisomerization of the retinal chromophore is discussed.
Effects of correlated hybridization in the single-impurity Anderson model
Líbero, Valter; Veiga, Rodrigo
2013-03-01
The development of new materials often dependents on the theoretical foundations which study the microscopic matter, i.e., the way atoms interact and create distinct configurations. Among the interesting materials, those with partially filled d or f orbitals immersed in nonmagnetic metals have been described by the Anderson model, which takes into account Coulomb correlation (U) when a local level (energy Ed) is doubled occupied, and an electronic hybridization between local levels and conduction band states. In addition, here we include a correlated hybridization term, which depends on the local-level occupation number involved. This term breaks particle-hole symmetry (even when U + 2Ed = 0), enhances charge fluctuations on local levels and as a consequence strongly modifies the crossover between the Hamiltonian fixed-points, even suppressing one or other. We exemplify these behaviors showing data obtained from the Numerical Renormalization Group (NRG) computation for the impurity temperature-dependent specific heat, entropy and magnetic susceptibility. The interleaving procedure is used to recover the continuum spectrum after the NRG-logarithmic discretization of the conduction band. Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP.
Cox, Christopher; Plesniak, Michael W.
2017-11-01
One of the most physiologically relevant factors within the cardiovascular system is the wall shear stress. The wall shear stress affects endothelial cells via mechanotransduction and atherosclerotic regions are strongly correlated with curvature and branching in the human vasculature, where the shear stress is both oscillatory and multidirectional. Also, the combined effect of curvature and pulsatility in cardiovascular flows produces unsteady vortices. In this work, our goal is to assess the correlation between multiple vortex pairs and wall shear stress. To accomplish this, we use an in-house high-order flux reconstruction Navier-Stokes solver to simulate pulsatile flow of a Newtonian blood-analog fluid through a rigid 180° curved artery model. We use a physiologically relevant flow rate and generate results using both fully developed and uniform entrance conditions, the latter motivated by the fact that flow upstream to a curved artery may not be fully developed. Under these two inflow conditions, we characterize the evolution of various vortex pairs and their subsequent effect on several wall shear stress metrics. Supported by GW Center for Biomimetics and Bioinspired Engineering.
A Subpath-based Logit Model to Capture the Correlation of Routes
Directory of Open Access Journals (Sweden)
Xinjun Lai
2016-06-01
Full Text Available A subpath-based methodology is proposed to capture the travellers’ route choice behaviours and their perceptual correlation of routes, because the original link-based style may not be suitable in application: (1 travellers do not process road network information and construct the chosen route by a link-by-link style; (2 observations from questionnaires and GPS data, however, are not always link-specific. Subpaths are defined as important portions of the route, such as major roads and landmarks. The cross-nested Logit (CNL structure is used for its tractable closed-form and its capability to explicitly capture the routes correlation. Nests represent subpaths other than links so that the number of nests is significantly reduced. Moreover, the proposed method simplifies the original link-based CNL model; therefore, it alleviates the estimation and computation difficulties. The estimation and forecast validation with real data are presented, and the results suggest that the new method is practical.
MODELLING THE INTERACTION IN GAME SPORTS - RELATIVE PHASE AND MOVING CORRELATIONS
Directory of Open Access Journals (Sweden)
Martin Lames
2006-12-01
Full Text Available Model building in game sports should maintain the constitutive feature of this group of sports, the dynamic interaction process between the two parties. For single net/wall games relative phase is suggested to describe the positional interaction between the two players. 30 baseline rallies in tennis were examined and relative phase was calculated by Hilbert transform from the two time-series of lateral displacement and trajectory in the court respectively. Results showed that relative phase indicates some aspects of the tactical interaction in tennis. At a more abstract level the interaction between two teams in handball was studied by examining the relationship of the two scoring processes. Each process can be conceived as a random walk. Moving averages of the scoring probabilities indicate something like a momentary strength. A moving correlation (length = 20 ball possessions describes the momentary relationship between the teams' strength. Evidence was found that this correlation is heavily time-dependent, in almost every single game among the 40 examined ones we found phases with a significant positive as well as significant negative relationship. This underlines the importance of a dynamic view on the interaction in these games.
Miller, Joshua D; Mackillop, James; Fortune, Erica E; Maples, Jessica; Lance, Charles E; Keith Campbell, W; Goodie, Adam S
2013-03-30
Personality traits have proved to be consistent and important factors in a variety of externalizing behaviors including addiction, aggression, and antisocial behavior. Given the comorbidity of these behaviors with pathological gambling (PG), it is important to test the degree to which PG shares these trait correlates. In a large community sample of regular gamblers (N=354; 111 with diagnoses of pathological gambling), the relations between measures of two major models of personality - Big Three and Big Five - were examined in relation to PG symptoms derived from a semi-structured diagnostic interview. Across measures, traits related to the experience of strong negative emotions were the most consistent correlates of PG, regardless of whether they were analyzed using bivariate or multivariate analyses. In several instances, however, the relations between personality and PG were moderated by demographic variable such as gender, race, and age. It will be important for future empirical work of this nature to pay closer attention to potentially important moderators of these relations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Gray correlation analysis and prediction models of living refuse generation in Shanghai city.
Liu, Gousheng; Yu, Jianguo
2007-01-01
A better understanding of the factors that affect the generation of municipal living refuse (MLF) and the accurate prediction of its generation are crucial for municipal planning projects and city management. Up to now, most of the design efforts have been based on a rough prediction of MLF without any actual support. In this paper, based on published data of socioeconomic variables and MLF generation from 1990 to 2003 in the city of Shanghai, the main factors that affect MLF generation have been quantitatively studied using the method of gray correlation coefficient. Several gray models, such as GM(1,1), GIM(1), GPPM(1) and GLPM(1), have been studied, and predicted results are verified with subsequent residual test. Results show that, among the selected seven factors, consumption of gas, water and electricity are the largest three factors affecting MLF generation, and GLPM(1) is the optimized model to predict MLF generation. Through this model, the predicted MLF generation in 2010 in Shanghai will be 7.65 million tons. The methods and results developed in this paper can provide valuable information for MLF management and related municipal planning projects.
Vitu, L.; Laforge, N.; Malécot, P.; Boudeau, N.; Manov, S.; Milesi, M.
2018-05-01
Zinc alloys are used in a wide range of application such as electronics, automotive and building construction. Their various shapes are generally obtained by metal forming operation such as stamping. Therefore, it is important to characterize the material with adequate characterization tests. Sheet Bulging Test (SBT) is well recognized in the metal forming community. Different theoretical models of the literature for the evaluation of thickness and radius of the deformed sheet in SBT have been studied in order to get the hardening curve of different materials. These theoretical models present the advantage that the experimental procedure is very simple. But Koç et al. showed their limitation, since the combination of thickness and radius evaluations depend on the material. As Zinc alloys are strongly anisotropic with a special crystalline structure, a procedure is adopted for characterizing the hardening curve of a Zinc alloy. The anisotropy is first studied with tensile test, and SBT with elliptical dies is also investigated. Parallel to this, Digital Image Correlation (DIC) measures are carried out. The results obtained from theoretical models and DIC measures are compared. Measures done on post-mortem specimens complete the comparisons. Finally, DIC measures give better results and the resulting hardening curve of the studied zinc alloy is provided.
Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models
Directory of Open Access Journals (Sweden)
B. M. Brentan
2017-01-01
Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.
Directory of Open Access Journals (Sweden)
Jelmer P Borst
Full Text Available BACKGROUND: It has been shown that people can only maintain one problem state, or intermediate mental representation, at a time. When more than one problem state is required, for example in multitasking, performance decreases considerably. This effect has been explained in terms of a problem state bottleneck. METHODOLOGY: In the current study we use the complimentary methodologies of computational cognitive modeling and neuroimaging to investigate the neural correlates of this problem state bottleneck. In particular, an existing computational cognitive model was used to generate a priori fMRI predictions for a multitasking experiment in which the problem state bottleneck plays a major role. Hemodynamic responses were predicted for five brain regions, corresponding to five cognitive resources in the model. Most importantly, we predicted the intraparietal sulcus to show a strong effect of the problem state manipulations. CONCLUSIONS: Some of the predictions were confirmed by a subsequent fMRI experiment, while others were not matched by the data. The experiment supported the hypothesis that the problem state bottleneck is a plausible cause of the interference in the experiment and that it could be located in the intraparietal sulcus.
Bruno, Luigi; Decuzzi, Paolo; Gentile, Francesco
2016-01-01
The promise of nanotechnology lies in the possibility of engineering matter on the nanoscale and creating technological interfaces that, because of their small scales, may directly interact with biological objects, creating new strategies for the treatment of pathologies that are otherwise beyond the reach of conventional medicine. Nanotechnology is inherently a multiscale, multiphenomena challenge. Fundamental understanding and highly accurate predictive methods are critical to successful manufacturing of nanostructured materials, bio/mechanical devices and systems. In biomedical engineering, and in the mechanical analysis of biological tissues, classical continuum approaches are routinely utilized, even if these disregard the discrete nature of tissues, that are an interpenetrating network of a matrix (the extra cellular matrix, ECM) and a generally large but finite number of cells with a size falling in the micrometer range. Here, we introduce a nano-mechanical theory that accounts for the-non continuum nature of bio systems and other discrete systems. This discrete field theory, doublet mechanics (DM), is a technique to model the mechanical behavior of materials over multiple scales, ranging from some millimeters down to few nanometers. In the paper, we use this theory to predict the response of a granular material to an external applied load. Such a representation is extremely attractive in modeling biological tissues which may be considered as a spatial set of a large number of particulate (cells) dispersed in an extracellular matrix. Possibly more important of this, using digital image correlation (DIC) optical methods, we provide an experimental verification of the model.
Dynamical correlation functions of the quadratic coupling spin-Boson model
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 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).
The three-point correlation function of the cosmic microwave background in inflationary models
Gangui, Alejandro; Matarrese, Sabino; Mollerach, Silvia
1994-01-01
We analyze the temperature three-point correlation function and the skewness of the Cosmic Microwave Background (CMB), providing general relations in terms of multipole coefficients. We then focus on applications to large angular scale anisotropies, such as those measured by the {\\em COBE} DMR, calculating the contribution to these quantities from primordial, inflation generated, scalar perturbations, via the Sachs--Wolfe effect. Using the techniques of stochastic inflation we are able to provide a {\\it universal} expression for the ensemble averaged three-point function and for the corresponding skewness, which accounts for all primordial second-order effects. These general expressions would moreover apply to any situation where the bispectrum of the primordial gravitational potential has a {\\em hierarchical} form. Our results are then specialized to a number of relevant models: power-law inflation driven by an exponential potential, chaotic inflation with a quartic and quadratic potential and a particular c...
International Nuclear Information System (INIS)
Takasugi, E.; Tata, X.
1982-01-01
The recombination model associated with modified Kuti-Weisskopf multiquark structure functions is used to analyze particle production by hadronic collisions. The justification of the use of the impulse approximation in these processes and the universal nature of the recombination process are discussed. Single-meson inclusive production in the fragmentation domains of the proton, the pion, and the kaon is used as an input to determine the primitive structure functions. Our parameter-free predictions for low-p/sub T/ multimeson and associated meson-baryon inclusive production are found to be in good agreement with a large amount of recently obtained correlation data. It is pointed out, however, that reactions involving multivalence recombination fall outside the scope of present considerations
Streamwise evolution of statistical events and the triple correlation in a model wind turbine array
Viestenz, Kyle; Cal, Raúl Bayoán
2013-11-01
Hot-wire anemometry data, obtained from a wind tunnel experiment containing a 3 × 3 wind turbine array, are used to conditionally average the Reynolds stresses. Nine profiles at the centerline behind the array are analyzed to characterize the turbulent velocity statistics of the wake flow. Quadrant analysis yields statistical events occurring in the wake of the wind farm, where quadrants 2 and 4 produce ejections and sweeps, respectively. A balance between these quadrants is expressed via the ΔSo parameter, which attains a maximum value at the bottom tip and changes sign near the top tip of the rotor. These are then associated to the triple correlation term present in the turbulent kinetic energy equation of the fluctuations. The development of these various quantities is assessed in light of wake remediation, energy transport and possess significance in closure models. National Science Foundation: ECCS-1032647.
The integrated model of sport confidence: a canonical correlation and mediational analysis.
Koehn, Stefan; Pearce, Alan J; Morris, Tony
2013-12-01
The main purpose of the study was to examine crucial parts of Vealey's (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes' affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge-skills balance, clear goals, and concentration on the task at hand.
Correlation mediated superconductivity in a Spin Peierls Phase of the Hubbard Model
International Nuclear Information System (INIS)
Long, M.W.
1987-08-01
The author explores the consequences of a mapping of the Hubbard Hamiltonian with a view to finding possible superconducting phases. The transformation pairs up all the sites and is therefore a much more natural starting point for describing a 'Spin Peierls' transition, generating enhanced singlet correlations for this pairing, than it is for describing the 'Resonating Valence Bond' state. It is shown that in the less than half filling case, an effective non-linear hopping Hamiltonian is quite useful in describing half of the electrons. This effective Hamiltonian can show a form of superconducting instability when nearest neighbour hopping is introduced to stabilise it. This superconducting phase seems to be a very unlikely possibility for the standard Hubbard model. (author)
Exact ground-state correlation functions of an atomic-molecular Bose–Einstein condensate model
Links, Jon; Shen, Yibing
2018-05-01
We study the ground-state properties of an atomic-molecular Bose–Einstein condensate model through an exact Bethe Ansatz solution. For a certain range of parameter choices, we prove that the ground-state Bethe roots lie on the positive real-axis. We then use a continuum limit approach to obtain a singular integral equation characterising the distribution of these Bethe roots. Solving this equation leads to an analytic expression for the ground-state energy. The form of the expression is consistent with the existence of a line of quantum phase transitions, which has been identified in earlier studies. This line demarcates a molecular phase from a mixed phase. Certain correlation functions, which characterise these phases, are then obtained through the Hellmann–Feynman theorem.
Pore Network Modeling: Alternative Methods to Account for Trapping and Spatial Correlation
De La Garza Martinez, Pablo
2016-05-01
Pore network models have served as a predictive tool for soil and rock properties with a broad range of applications, particularly in oil recovery, geothermal energy from underground reservoirs, and pollutant transport in soils and aquifers [39]. They rely on the representation of the void space within porous materials as a network of interconnected pores with idealised geometries. Typically, a two-phase flow simulation of a drainage (or imbibition) process is employed, and by averaging the physical properties at the pore scale, macroscopic parameters such as capillary pressure and relative permeability can be estimated. One of the most demanding tasks in these models is to include the possibility of fluids to remain trapped inside the pore space. In this work I proposed a trapping rule which uses the information of neighboring pores instead of a search algorithm. This approximation reduces the simulation time significantly and does not perturb the accuracy of results. Additionally, I included spatial correlation to generate the pore sizes using a matrix decomposition method. Results show higher relative permeabilities and smaller values for irreducible saturation, which emphasizes the effects of ignoring the intrinsic correlation seen in pore sizes from actual porous media. Finally, I implemented the algorithm from Raoof et al. (2010) [38] to generate the topology of a Fontainebleau sandstone by solving an optimization problem using the steepest descent algorithm with a stochastic approximation for the gradient. A drainage simulation is performed on this representative network and relative permeability is compared with published results. The limitations of this algorithm are discussed and other methods are suggested to create a more faithful representation of the pore space.
Pore Network Modeling: Alternative Methods to Account for Trapping and Spatial Correlation
De La Garza Martinez, Pablo
2016-01-01
Pore network models have served as a predictive tool for soil and rock properties with a broad range of applications, particularly in oil recovery, geothermal energy from underground reservoirs, and pollutant transport in soils and aquifers [39]. They rely on the representation of the void space within porous materials as a network of interconnected pores with idealised geometries. Typically, a two-phase flow simulation of a drainage (or imbibition) process is employed, and by averaging the physical properties at the pore scale, macroscopic parameters such as capillary pressure and relative permeability can be estimated. One of the most demanding tasks in these models is to include the possibility of fluids to remain trapped inside the pore space. In this work I proposed a trapping rule which uses the information of neighboring pores instead of a search algorithm. This approximation reduces the simulation time significantly and does not perturb the accuracy of results. Additionally, I included spatial correlation to generate the pore sizes using a matrix decomposition method. Results show higher relative permeabilities and smaller values for irreducible saturation, which emphasizes the effects of ignoring the intrinsic correlation seen in pore sizes from actual porous media. Finally, I implemented the algorithm from Raoof et al. (2010) [38] to generate the topology of a Fontainebleau sandstone by solving an optimization problem using the steepest descent algorithm with a stochastic approximation for the gradient. A drainage simulation is performed on this representative network and relative permeability is compared with published results. The limitations of this algorithm are discussed and other methods are suggested to create a more faithful representation of the pore space.
International Nuclear Information System (INIS)
Popov, N.K.; Rohatgi, U.S.
1987-01-01
The bypass/refill process in the PWR reactor downcomer, following a large rupture of a cold leg coolant supply pipe, is a complicated thermo-hydraulic two-phase flow phenomenon. Mathematical modeling of such phenomena is always accompanied with a difficult task of selection of suitable constitutive correlations. In a typically hydrodynamic phenomenon, like ECC refill process of the reactor lower plenum is considered, the phasic interfacial friction is the most influential constitutive correlation. Therefore, assessment of the well-known widely-used interfacial friction constitutive correlations in the model of ECC bypass/refill process, is the subject of this paper
International Nuclear Information System (INIS)
Gerweck, Leo E.; Dubois, Willum; Baumann, Michael; Suit, Herman D.
1995-01-01
, the rank-order correlation coefficient between the single dose hypoxic versus fractionated dose TCD50s under hypoxic or aerobic conditions was 1.0. For all 5 tumors examined, a trend for rank correlation was observed between the single dose and the fractionated dose TCD50s performed under normal or clamp hypoxic conditions (r=0.7, p=0.16 in both cases). The linear correlation coefficients were 0.83, p=0.08 and 0.72, p=0.17, respectively. Failure to attain a rank correlation of 1.0 was due to one tumor exhibiting an insignificant fractionation effect. The rank correlation between the TCD50s for fractionated treatments under normal versus the extrapolated TCD50s under clamp hypoxic conditions was 1.00; the linear correlation coefficient was 0.97 (p=0.01). Conclusions: In the tumor models examined, factors controlling the single fraction tumor control dose, also impact the response to fractionated treatments. These results suggest that laboratory estimates of intrinsic radiosensitivity and tumor clonogen number at the onset of treatment, will be of use in predicting radiocurability for fractionated treatments, as has been observed for single dose treatments
A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.
Gompert, Zachariah
2016-01-01
Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur
A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.
Directory of Open Access Journals (Sweden)
Zachariah Gompert
Full Text Available Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20 SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure, particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among
Velocity-mass correlation of the O-type stars: model results
International Nuclear Information System (INIS)
Stone, R.C.
1982-01-01
This paper presents new model results describing the evolution of massive close binaries from their initial ZAMS to post-supernova stages. Unlike the previous conservative study by Stone [Astrophys. J. 232, 520 (1979) (Paper II)], these results allow explicitly for mass loss from the binary system occurring during the core hydrogen- and helium-burning stages of the primary binary star as well as during the Roche lobe overflow. Because of uncertainties in these rates, model results are given for several reasonable choices for these rates. All of the models consistently predict an increasing relation between the peculiar space velocities and masses for runaway OB stars which agrees well with the observed correlations discussed in Stone [Astron. J. 86, 544 (1981) (Paper III)] and also predict a lower limit at Mroughly-equal11M/sub sun/ for the masses of runaway stars, in agreement with the observational limit found by A. Blaauw (Bull. Astron. Inst. Neth. 15, 265, 1961), both of which support the binary-supernova scenario described by van den Heuvel and Heise for the origin of runaway stars. These models also predict that the more massive O stars will produce correspondingly more massive compact remnants, and that most binaries experiencing supernova-induced kick velocities of magnitude V/sub k/> or approx. =300 km s -1 will disrupt following the explosions. The best estimate for this velocity as established from pulsar observations is V/sub k/roughly-equal150 km s -1 , in which case probably only 15% if these binaries will be disrupted by the supernova explosions, and therefore, almost all runaway stars should have either neutron star or black hole companions
DEFF Research Database (Denmark)
Ottesen, Johnny T.; Mehlsen, Jesper; Olufsen, Mette
2014-01-01
We consider the inverse and patient specific problem of short term (seconds to minutes) heart rate regulation specified by a system of nonlinear ODEs and corresponding data. We show how a recent method termed the structural correlation method (SCM) can be used for model reduction and for obtaining...... a set of practically identifiable parameters. The structural correlation method includes two steps: sensitivity and correlation analysis. When combined with an optimization step, it is possible to estimate model parameters, enabling the model to fit dynamics observed in data. This method is illustrated...... in detail on a model predicting baroreflex regulation of heart rate and applied to analysis of data from a rat and healthy humans. Numerous mathematical models have been proposed for prediction of baroreflex regulation of heart rate, yet most of these have been designed to provide qualitative predictions...
Made Tirta, I.; Anggraeni, Dian
2018-04-01
Statistical models have been developed rapidly into various directions to accommodate various types of data. Data collected from longitudinal, repeated measured, clustered data (either continuous, binary, count, or ordinal), are more likely to be correlated. Therefore statistical model for independent responses, such as Generalized Linear Model (GLM), Generalized Additive Model (GAM) are not appropriate. There are several models available to apply for correlated responses including GEEs (Generalized Estimating Equations), for marginal model and various mixed effect model such as GLMM (Generalized Linear Mixed Models) and HGLM (Hierarchical Generalized Linear Models) for subject spesific models. These models are available on free open source software R, but they can only be accessed through command line interface (using scrit). On the othe hand, most practical researchers very much rely on menu based or Graphical User Interface (GUI). We develop, using Shiny framework, standard pull down menu Web-GUI that unifies most models for correlated responses. The Web-GUI has accomodated almost all needed features. It enables users to do and compare various modeling for repeated measure data (GEE, GLMM, HGLM, GEE for nominal responses) much more easily trough online menus. This paper discusses the features of the Web-GUI and illustrates the use of them. In General we find that GEE, GLMM, HGLM gave very closed results.
Damping at positive frequencies in the limit J⊥-->0 in the strongly correlated Hubbard model
Mohan, Minette M.
1992-08-01
I show damping in the two-dimensional strongly correlated Hubbard model within the retraceable-path approximation, using an expansion around dominant poles for the self-energy. The damping half-width ~J2/3z occurs only at positive frequencies ω>5/2Jz, the excitation energy of a pure ``string'' state of length one, where Jz is the Ising part of the superexchange interaction, and occurs even in the absence of spin-flip terms ~J⊥ in contrast to other theoretical treatments. The dispersion relation for both damped and undamped peaks near the upper band edge is found and is shown to have lost the simple J2/3z dependence characteristic of the peaks near the lower band edge. The position of the first three peaks near the upper band edge agrees well with numerical simulations on the t-J model. The weight of the undamped peaks near the upper band edge is ~J4/3z, contrasting with Jz for the weight near the lower band edge.
Correlations between chaos in a perturbed sine-Gordon equation and a truncated model system
International Nuclear Information System (INIS)
Bishop, A.R.; Flesch, R.; Forests, M.G.; Overman, E.A.
1990-01-01
The purpose of this paper is to present a first step toward providing coordinates and associated dynamics for low-dimensional attractors in nearly integrable partial differential equations (pdes), in particular, where the truncated system reflects salient geometric properties of the pde. This is achieved by correlating: (1) numerical results on the bifurcations to temporal chaos with spatial coherence of the damped, periodically forced sine-Gordon equation with periodic boundary conditions; (2) an interpretation of the spatial and temporal bifurcation structures of this perturbed integrable system with regard to the exact structure of the sine-Gordon phase space; (3) a model dynamical systems problem, which is itself a perturbed integrable Hamiltonian system, derived from the perturbed sine-Gordon equation by a finite mode Fourier truncation in the nonlinear Schroedinger limit; and (4) the bifurcations to chaos in the truncated phase space. In particular, a potential source of chaos in both the pde and the model ordinary differential equation systems is focused on: the existence of homoclinic orbits in the unperturbed integrable phase space and their continuation in the perturbed problem. The evidence presented here supports the thesis that the chaotic attractors of the weakly perturbed periodic sine-Gordon system consists of low-dimensional metastable attacking states together with intermediate states that are O(1) unstable and correspond to homoclinic states in the integrable phase space. It is surmised that the chaotic dynamics on these attractors is due to the perturbation of these homocline integrable configurations
Bernaola-Galván, Pedro A.; Gómez-Extremera, Manuel; Romance, A. Ramón; Carpena, Pedro
2017-09-01
The correlation properties of the magnitude of a time series are associated with nonlinear and multifractal properties and have been applied in a great variety of fields. Here we have obtained the analytical expression of the autocorrelation of the magnitude series (C|x |) of a linear Gaussian noise as a function of its autocorrelation (Cx). For both, models and natural signals, the deviation of C|x | from its expectation in linear Gaussian noises can be used as an index of nonlinearity that can be applied to relatively short records and does not require the presence of scaling in the time series under study. In a model of artificial Gaussian multifractal signal we use this approach to analyze the relation between nonlinearity and multifractallity and show that the former implies the latter but the reverse is not true. We also apply this approach to analyze experimental data: heart-beat records during rest and moderate exercise. For each individual subject, we observe higher nonlinearities during rest. This behavior is also achieved on average for the analyzed set of 10 semiprofessional soccer players. This result agrees with the fact that other measures of complexity are dramatically reduced during exercise and can shed light on its relationship with the withdrawal of parasympathetic tone and/or the activation of sympathetic activity during physical activity.
The Bass diffusion model on networks with correlations and inhomogeneous advertising
Bertotti, M. L.; Brunner, J.; Modanese, G.
2016-09-01
The Bass model, which is an effective forecasting tool for innovation diffusion based on large collections of empirical data, assumes an homogeneous diffusion process. We introduce a network structure into this model and we investigate numerically the dynamics in the case of networks with link density $P(k)=c/k^\\gamma$, where $k=1, \\ldots , N$. The resulting curve of the total adoptions in time is qualitatively similar to the homogeneous Bass curve corresponding to a case with the same average number of connections. The peak of the adoptions, however, tends to occur earlier, particularly when $\\gamma$ and $N$ are large (i.e., when there are few hubs with a large maximum number of connections). Most interestingly, the adoption curve of the hubs anticipates the total adoption curve in a predictable way, with peak times which can be, for instance when $N=100$, between 10% and 60% of the total adoptions peak. This may allow to monitor the hubs for forecasting purposes. We also consider the case of networks with assortative and disassortative correlations and a case of inhomogeneous advertising where the publicity terms are "targeted" on the hubs while maintaining their total cost constant.
International Nuclear Information System (INIS)
Rodriguez Diana Marcela; Hernandez Orlando; Kammer Andreas
2009-01-01
The aim of this research is to apply spectral correlation, local favorability indexes and Poisson's theorem as numerical methods for data processing and interpretation of potential field data associated with structural features; these techniques are applied to theoretical and real gravity and magnetic data of the Soapaga fault, located in the Boyaca Department, in the eastern Andean Mountains. Theoretical data of the Soapaga fault was obtained by forward modeling of geological and structural sections. Real data of the Soapaga fault included compiled gravity data and acquired magnetic data along four profiles oriented perpendicular to the fault. As a result, the geometry of the fault and its structural characteristics were obtained by interactive forward and inverse modeling. This methodology allows highlighting anomaly trends associated with density and magnetic susceptibility contrast that occur along the Soapaga fault zone. Additionally, this work provides a quantitative approach to establish the relationship between gravity and magnetic anomalies, supported by a rigorous mathematical methodology rather than isolated data interpretation to better understand the gravity and magnetic signatures of outcropping and hidden structural features.
Magnetic moment of inertia within the torque-torque correlation model.
Thonig, Danny; Eriksson, Olle; Pereiro, Manuel
2017-04-19
An essential property of magnetic devices is the relaxation rate in magnetic switching which strongly depends on the energy dissipation. This is described by the Landau-Lifshitz-Gilbert equation and the well known damping parameter, which has been shown to be reproduced from quantum mechanical calculations. Recently the importance of inertia phenomena have been discussed for magnetisation dynamics. This magnetic counterpart to the well-known inertia of Newtonian mechanics, represents a research field that so far has received only limited attention. We present and elaborate here on a theoretical model for calculating the magnetic moment of inertia based on the torque-torque correlation model. Particularly, the method has been applied to bulk itinerant magnets and we show that numerical values are comparable with recent experimental measurements. The theoretical analysis shows that even though the moment of inertia and damping are produced by the spin-orbit coupling, and the expression for them have common features, they are caused by very different electronic structure mechanisms. We propose ways to utilise this in order to tune the inertia experimentally, and to find materials with significant inertia dynamics.
Assessment of motor recovery and MRI correlates in a porcine spinal cord injury model
Directory of Open Access Journals (Sweden)
Igor Šulla
2014-01-01
Full Text Available The study concentrated on behavioral and magnetic resonance imaging (MRI characteristics in a porcine spinal cord injury model. Six adult minipigs weighing 32–35 kg were narcotized by thiopental, intubated, and placed on a volume-cycled ventilator. Anaesthesia was maintained by 1.5% sevoflurane with oxygen. Following location of the 1st lumbar vertebra animals were fastened in an immobilization frame. The spinal cord, exposed through a laminectomy, was compressed by a 5 mm thick circular rod with a peak force of 0.8 kg at a velocity of 3 cm·s-1. The next day the minipigs were paraplegic but improved rapidly to paraparesis. On the 12th postoperative day they were euthanasied. Neural tissue changes were evaluated by post mortem MRI, which showed damage to the spinal cord white and/or gray matter in the epicentre of compression with longitudinal spreading over one segment cranially and caudally. Statistical analyses performed by Spearman’s rho test revealed positive correlations between damaged areas and the whole area of the spinal cord white/gray matter (P = 0.047; rs = 0.742 and (P = 0.002; rs = 0.943, respectively. The study confirmed the reliability and reproducibility of the utilised model of spinal cord trauma. The structural changes in the epicentre of injury did not impede the rapid but incomplete recovery of motor functions.
Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi
2018-04-01
Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.
Considering built environment and spatial correlation in modeling pedestrian injury severity.
Prato, Carlo G; Kaplan, Sigal; Patrier, Alexandre; Rasmussen, Thomas K
2018-01-02
This study looks at mitigating and aggravating factors that are associated with the injury severity of pedestrians when they have crashes with another road user and overcomes existing limitations in the literature by focusing attention on the built environment and considering spatial correlation across crashes. Reports for 6,539 pedestrian crashes occurred in Denmark between 2006 and 2015 were merged with geographic information system resources containing detailed information about the built environment and exposure at the crash locations. A linearized spatial logit model estimated the probability of pedestrians sustaining a severe or fatal injury conditional on the occurrence of a crash with another road user. This study confirms previous findings about older pedestrians and intoxicated pedestrians being the most vulnerable road users and crashes with heavy vehicles and in roads with higher speed limits being related to the most severe outcomes. This study provides novel perspectives by showing positive spatial correlations of crashes with the same severity outcomes and emphasizing the role of the built environment in the proximity of the crash. This study emphasizes the need for thinking about traffic calming measures, illumination solutions, road maintenance programs, and speed limit reductions. Moreover, this study emphasizes the role of the built environment, because shopping areas, residential areas, and walking traffic density are positively related to a reduction in pedestrian injury severity. Often, these areas have in common a larger pedestrian mass that is more likely to make other road users more aware and attentive, whereas the same does not seem to apply to areas with lower pedestrian density.
International Nuclear Information System (INIS)
Giraud, B.G.; Heumann, J.M.; Lapedes, A.S.
1999-01-01
The fact that correlation does not imply causation is well known. Correlation between variables at two sites does not imply that the two sites directly interact, because, e.g., correlation between distant sites may be induced by chaining of correlation between a set of intervening, directly interacting sites. Such 'noncausal correlation' is well understood in statistical physics: an example is long-range order in spin systems, where spins which have only short-range direct interactions, e.g., the Ising model, display correlation at a distance. It is less well recognized that such long-range 'noncausal' correlations can in fact be stronger than the magnitude of any causal correlation induced by direct interactions. We call this phenomenon superadditive correlation (SAC). We demonstrate this counterintuitive phenomenon by explicit examples in (i) a model spin system and (ii) a model continuous variable system, where both models are such that two variables have multiple intervening pathways of indirect interaction. We apply the technique known as decimation to explain SAC as an additive, constructive interference phenomenon between the multiple pathways of indirect interaction. We also explain the effect using a definition of the collective mode describing the intervening spin variables. Finally, we show that the SAC effect is mirrored in information theory, and is true for mutual information measures in addition to correlation measures. Generic complex systems typically exhibit multiple pathways of indirect interaction, making SAC a potentially widespread phenomenon. This affects, e.g., attempts to deduce interactions by examination of correlations, as well as, e.g., hierarchical approximation methods for multivariate probability distributions, which introduce parameters based on successive orders of correlation. copyright 1999 The American Physical Society
The role of spurious correlation in the development of a komatiite alteration model
Butler, John C.
1986-11-01
Procedures for detecting alterations in komatiites are described. The research of Pearson (1897) on spurious correlation and of Chayes (1949, 1971) on ratio correlation is reviewed. The equations for the ratio correlation procedure are provided. The ratio correlation procedure is applied to the komatiites from Gorgona Island and the Barberton suite. Plots of the molecular proportion ratios of (FeO + MgO)/TiO2 versus SiO2/TiO2, and correlation coefficients for the komatiites are presented and analyzed.
Correlation of Amine Swingbed On-Orbit CO2 Performance with a Hardware Independent Predictive Model
Papale, William; Sweterlitsch, Jeffery
2015-01-01
The Amine Swingbed Payload is an experimental system deployed on the International Space Station (ISS) that includes a two-bed, vacuum regenerated, amine-based carbon dioxide (CO2) removal subsystem as the principal item under investigation. The aminebased subsystem, also described previously in various publications as CAMRAS 3, was originally designed, fabricated and tested by Hamilton Sundstrand Space Systems International, Inc. (HSSSI) and delivered to NASA in November 2008. The CAMRAS 3 unit was subsequently designed into a flight payload experiment in 2010 and 2011, with flight test integration activities accomplished on-orbit between January 2012 and March 2013. Payload activation was accomplished in May 2013 followed by a 1000 hour experimental period. The experimental nature of the Payload and the interaction with the dynamic ISS environment present unique scientific and engineering challenges, in particular to the verification and validation of the expected Payload CO2 removal performance. A modeling and simulation approach that incorporates principles of chemical reaction engineering has been developed for the amine-based system to predict the dynamic cabin CO2 partial pressure with given inputs of sorbent bed size, process air flow, operating temperature, half-cycle time, CO2 generation rate, cabin volume and the magnitude of vacuum available. Simulation runs using the model to predict ambient CO2 concentrations show good correlation to on-orbit performance measurements and ISS dynamic concentrations for the assumed operating conditions. The dynamic predictive modelling could benefit operational planning to help ensure ISS CO2 concentrations are maintained below prescribed limits and for the Orion vehicle to simulate various operating conditions, scenarios and transients.
Directory of Open Access Journals (Sweden)
Florian Schmitz
2016-10-01
Full Text Available Previous research has shown an inverse relation between response times in elementary cognitive tasks and intelligence, but findings are inconsistent as to which is the most informative score. We conducted a study (N = 200 using a battery of elementary cognitive tasks, working memory capacity (WMC paradigms, and a test of fluid intelligence (gf. Frequently used candidate scores and model parameters derived from the response time (RT distribution were tested. Results confirmed a clear correlation of mean RT with WMC and to a lesser degree with gf. Highly comparable correlations were obtained for alternative location measures with or without extreme value treatment. Moderate correlations were found as well for scores of RT variability, but they were not as strong as for mean RT. Additionally, there was a trend towards higher correlations for slow RT bands, as compared to faster RT bands. Clearer evidence was obtained in an ex-Gaussian decomposition of the response times: the exponential component was selectively related to WMC and gf in easy tasks, while mean response time was additionally predictive in the most complex tasks. The diffusion model parsimoniously accounted for these effects in terms of individual differences in drift rate. Finally, correlations of model parameters as trait-like dispositions were investigated across different tasks, by correlating parameters of the diffusion and the ex-Gaussian model with conventional RT and accuracy scores.
Study on the petroleum recovery technology: well testing analysis
Energy Technology Data Exchange (ETDEWEB)
Huh, Dae Gee; Kim, Se Joon; Kim, Hyun Tae [Korea Inst. of Geology Mining and Materials, Taejon (Korea, Republic of)
1995-12-01
Well testing is one of the most widely used tools to characterize reservoirs throughout the entire life of petroleum exploration and production. In this study, we first try to set up a procedure of computer aided well test analysis and then attempt to characterize potential reservoirs by performing well test analysis for some of the exploratory wells in the Korean continental shelf. A couple of gas well testing data already published in the literature were also analyzed and compared. First task was to analyze the drill stem test(DST) in KCS-1 gas well. The second analysis was also DST data on multi-rate gas wells. The third case is a Devonian shale reservoir. The final problem is a multi-rate drawdown test without early time pressure data. It is now possible to analyze insufficient well test data with less accuracy. One remark should be pointed out on multi-rate gas well testing. It is recommended to have variable skins rather than a constant skin because rate dependent skins due to turbulence of gas flow must be considered in addition to the mechanical skin. (author). 14 refs.
Czech Academy of Sciences Publication Activity Database
Pekár, S.; Brabec, Marek
2018-01-01
Roč. 124, č. 2 (2018), s. 86-93 ISSN 0179-1613 Institutional support: RVO:67985807 Keywords : correlated data * generalized estimating equations * marginal model * regression models * statistical analysis Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.398, year: 2016
Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin
2011-05-01
The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is
Mikhaylov, Rebecca; Dawson, Douglas; Kwack, Eug
2014-01-01
NASA's Earth observing Soil Moisture Active & Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 km near-polar, sun synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its 3 year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 rpm, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within 3 days. In order to make the necessary precise surface emission measurements from space, a temperature knowledge of 60 deg C for the mesh reflector is required. In order to show compliance, a thermal vacuum test was conducted using a portable solar simulator to illuminate a non flight, but flight-like test article through the quartz window of the vacuum chamber. The molybdenum wire of the antenna mesh is too fine to accommodate thermal sensors for direct temperature measurements. Instead, the mesh temperature was inferred from resistance measurements made during the test. The test article was rotated to five separate angles between 10 deg and 90 deg via chamber breaks to simulate the maximum expected on-orbit solar loading during the mission. The resistance measurements were converted to temperature via a resistance versus temperature calibration plot that was constructed from data collected in a separate calibration test. A simple thermal model of two different representations of the mesh (plate and torus) was created to correlate the mesh temperature predictions to within 60 deg C. The on-orbit mesh
Energy Technology Data Exchange (ETDEWEB)
Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)
2017-01-15
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.
International Nuclear Information System (INIS)
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.
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 Â© 2016 Elsevier Ltd. All rights reserved.
Safe affordable fission engine (SAFE 30) module conductivity test thermal model correlation
International Nuclear Information System (INIS)
Roman, Jose
2001-01-01
The SAFE 30 is a simple, robust space fission power system that is comprised of several independent modules. Each module contains 4 fuel tubes bonded to a central heatpipe. Fission energy is conducted from the fuel tubes to the heatpipe, which in turn transfers the energy to a power conversion system. This paper benchmarks a thermal model of the SAFE 30 with actual test data from simulated SAFE 30 module tests. Two 'dummy' SAFE 30 modules were fabricated - each consisted of 4 1-inch dia. tubes (simulating the fuel tubes) bonded to a central '1' dia. tube (simulating the heatpipe). In the first module the fuel tubes were simply brazed to the heatpipe along the line of contact (leaving void space in the interstices), and in the second module the tubes and heatpipe were brazed via tri-cusps that completely fill the interstices between the tubes. In these tests, fission energy is simulated by placing resistance heaters within each of the 4 fuel tubes. The tests were conducted in a vacuum chamber in 4 configurations: tri-cusps filled with and without an outer insulation wrap, and no tri-cusps with and without an outer insulation wrap. The baseline SAFE 30 configuration uses the brazed tri-cusps. During the tests, the power applied to the heaters was varied in a stepwise fashion, until a steady-state temperature profile was reached. These temperature levels varied between 773 K and 1073 K. To benchmark the thermal model, the input energy and chamber surface temperature were used as boundary conditions for the model. The analytical results from the nodes at the same location as the test thermocouples were plotted again test data to determinate the accuracy of the analysis. The unknown variables on the analysis are the radiation emissivity of the pipe and chamber and the radiation view factor between the module and the chamber. A correlation was determined using a parametric analysis by varying the surface emissivity and view factor until a good match was reached. This
Oliveira, Luiz Gustavo de; Cunha, André Luiz da; Duarte, Amaury Caiafa; Castañon, Maria Christina Marques Nogueira; Chebli, Júlio Maria Fonseca; Aguiar, Jair Adriano Kopke de
2014-01-01
Inflammatory bowel disease, including ulcerative colitis and Crohn's disease, comprising a broad spectrum of diseases those have in common chronic inflammation of the gastrointestinal tract, histological alterations and an increased activity levels of certain enzymes, such as, metalloproteinases. Evaluate a possible correlation of disease activity index with the severity of colonic mucosal damage and increased activity of metalloproteinases in a model of ulcerative colitis induced by dextran sulfate sodium. Colitis was induced by oral administration of 5% dextran sulfate sodium for seven days in this group (n=10), whereas control group (n=16) received water. Effects were analyzed daily by disease activity index. In the seventh day, animals were euthanized and hematological measurements, histological changes (hematoxylin and eosin and Alcian Blue staining), myeloperoxidase and metalloproteinase activities (MMP-2 and MMP-9) were determined. Dextran sulfate sodium group showed elevated disease activity index and reduced hematological parameters. Induction of colitis caused tissue injury with loss of mucin and increased myeloperoxidase (Pcorrelation with the degree of histopathological changes after induction of colitis, and this result may be related mainly to the increased activity of MMP-9 and mieloperoxidase.
Krafft, Paul R; McBride, Devin W; Lekic, Tim; Rolland, William B; Mansell, Charles E; Ma, Qingyi; Tang, Jiping; Zhang, John H
2014-05-01
Formation of brain edema after intracerebral hemorrhage (ICH) is highly associated with its poor outcome. However, the relationship between cerebral edema and behavioral deficits has not been thoroughly examined in the preclinical setting. Hence, this study aimed to evaluate the ability of common sensorimotor tests to predict the extent of brain edema in two mouse models of ICH. One hundred male CD-1 mice were subjected to sham surgery or ICH induction via intrastriatal injection of either autologous blood (30 μL) or bacterial collagenase (0.0375U or 0.075U). At 24 and 72 h after surgery, animals underwent a battery of behavioral tests, including the modified Garcia neuroscore (Neuroscore), corner turn test (CTT), forelimb placing test (FPT), wire hang task (WHT) and beam walking (BW). Brain edema was evaluated via the wet weight/dry weight method. Intrastriatal injection of autologous blood or bacterial collagenase resulted in a significant increase in brain water content and associated sensorimotor deficits (p<0.05). A significant correlation between brain edema and sensorimotor deficits was observed for all behavioral tests except for WHT and BW. Based on these findings, we recommend implementing the Neuroscore, CTT and/or FPT in preclinical studies of unilateral ICH in mice. Copyright © 2014 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Sartoris, D.J.; Resnick, D.; Holmes, R.E.; Tencer, A.F.; Texas Univ., Dallas; Mooney, V.
1986-01-01
Radiographic and biomechanical assessment of a new type of bone graft substitute derived from reef-building sea coral was performed in a canine metaphyseal defect model. Blocks of this material and autogenous iliac crest graft were implanted, respectively, into the right and left proximal tibial metaphyses of eight dogs. Qualitative and quantitative radiographic evaluation was performed in the immediate postoperative period and at 6 months after surgery. Biomechanical testing was carried out on all grafts following harvest at 6 months, as well as on nonimplanted coralline hydroxyapatite and autogenous iliac cancellous bone. In contrast to autografts, incorporation of coralline implants was characterized by predictable osseous growth and apposition with preservation of intrinsic architecture. Greater percent increase in radiography density, higher ultimate compressive strength, and lower stiffness with incorporation were documented advantages of coralline hydroxyapatite over autogenous graft. Densitometric measurements correlated moderately with strength for both types of graft material (r=0.65). These promising results have important implications to the clinical application of coralline hydroxyapatite bone graft substitutes as an alternative to autogenous grafting. (orig.)
Directory of Open Access Journals (Sweden)
Martha Elba Gonzalez-Mejia
2014-04-01
Full Text Available Chagas disease, caused by Trypanosoma cruzi, represents an endemic among Latin America countries. The participation of free radicals, especially nitric oxide (NO, has been demonstrated in the pathophysiology of seropositive individuals with T. cruzi. In Chagas disease, increased NO contributes to the development of cardiomyopathy and megacolon. Metallothioneins (MTs are efficient free radicals scavengers of NO in vitro and in vivo. Here, we developed a murine model of the chronic phase of Chagas disease using endemic T. cruzi RyCH1 in BALB/c mice, which were divided into four groups: infected non-treated (Inf, infected N-monomethyl-L-arginine treated (Inf L-NAME, non-infected L-NAME treated and non-infected vehicle-treated. We determined blood parasitaemia and NO levels, the extent of parasite nests in tissues and liver MT-I expression levels. It was observed that NO levels were increasing in Inf mice in a time-dependent manner. Inf L-NAME mice had fewer T. cruzi nests in cardiac and skeletal muscle with decreased blood NO levels at day 135 post infection. This affect was negatively correlated with an increase of MT-I expression (r = -0.8462, p < 0.0001. In conclusion, we determined that in Chagas disease, an unknown inhibitory mechanism reduces MT-I expression, allowing augmented NO levels.
Telling, Neil D; Everett, James; Collingwood, Joanna F; Dobson, Jon; van der Laan, Gerrit; Gallagher, Joseph J; Wang, Jian; Hitchcock, Adam P
2017-10-19
A signature characteristic of Alzheimer's disease (AD) is aggregation of amyloid-beta (Aβ) fibrils in the brain. Nevertheless, the links between Aβ and AD pathology remain incompletely understood. It has been proposed that neurotoxicity arising from aggregation of the Aβ 1-42 peptide can in part be explained by metal ion binding interactions. Using advanced X-ray microscopy techniques at sub-micron resolution, we investigated relationships between iron biochemistry and AD pathology in intact cortex from an established mouse model over-producing Aβ. We found a direct correlation of amyloid plaque morphology with iron, and evidence for the formation of an iron-amyloid complex. We also show that iron biomineral deposits in the cortical tissue contain the mineral magnetite, and provide evidence that Aβ-induced chemical reduction of iron could occur in vivo. Our observations point to the specific role of iron in amyloid deposition and AD pathology, and may impact development of iron-modifying therapeutics for AD. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Recurrent network models for perfect temporal integration of fluctuating correlated inputs.
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Hiroshi Okamoto
2009-06-01
Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.
Energy Technology Data Exchange (ETDEWEB)
Pasechnik, M V
1978-01-01
Major results of investigations into the shell structure of deformed nuclei with the number of neutrons of approximately 100, as well as new isotopic effects in the inelastic scattering of fast neutrons with nuclei are reported. The experiments conducted at the WWR-M research reactor have shown a substantial dependence of the nuclear excited energy-level density on the mass number and the number of neutrons. The fact resulted in a conclusion that the deformed nuclei possess filled shells, that was an incentive to revise the whole nuclear shell concept. In particular it was established that the property of magicity rests not only on the sphericity of nuclei but it may be also observed in strongly deformed nuclei. The isotope-spin dependence of the nuclear potential was studied at the AG-5 pulse electrostatic generator. The parameters of the potential were determined by comparing the experimental data on inelastic scattering and polarization of fast neutrons by nuclei from /sup 48/Ti to /sup 209/Bi with the calculations in terms of the optical model. Simple correlations were established between the optical potential and the nucleus asymmetry parameter ..cap alpha..=N-Z/A in wide ranges of mass numbers and neutron energy.
Expression of Caytaxin protein in Cayman Ataxia mouse models correlates with phenotype severity.
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Kristine M Sikora
Full Text Available Caytaxin is a highly-conserved protein, which is encoded by the Atcay/ATCAY gene. Mutations in Atcay/ATCAY have been identified as causative of cerebellar disorders such as the rare hereditary disease Cayman ataxia in humans, generalized dystonia in the dystonic (dt rat, and marked motor defects in three ataxic mouse lines. While several lines of evidence suggest that Caytaxin plays a critical role in maintaining nervous system processes, the physiological function of Caytaxin has not been fully characterized. In the study presented here, we generated novel specific monoclonal antibodies against full-length Caytaxin to examine endogenous Caytaxin expression in wild type and Atcay mutant mouse lines. Caytaxin protein is absent from brain tissues in the two severely ataxic Atcay(jit (jittery and Atcay(swd (sidewinder mutant lines, and markedly decreased in the mildly ataxic/dystonic Atcay(ji-hes (hesitant line, indicating a correlation between Caytaxin expression and disease severity. As the expression of wild type human Caytaxin in mutant sidewinder and jittery mice rescues the ataxic phenotype, Caytaxin's physiological function appears to be conserved between the human and mouse orthologs. Across multiple species and in several neuronal cell lines Caytaxin is expressed as several protein isoforms, the two largest of which are caused by the usage of conserved methionine translation start sites. The work described in this manuscript presents an initial characterization of the Caytaxin protein and its expression in wild type and several mutant mouse models. Utilizing these animal models of human Cayman Ataxia will now allow an in-depth analysis to elucidate Caytaxin's role in maintaining normal neuronal function.
Plasma metabolite score correlates with Hypoxia time in a newly born piglet model for asphyxia
Directory of Open Access Journals (Sweden)
Julia Kuligowski
2017-08-01
Full Text Available Hypoxic-ischemic encephalopathy (HIE secondary to perinatal asphyxia is a leading cause of mortality and acquired long-term neurologic co-morbidities in the neonate. The most successful intervention for the treatment of moderate to severe HIE is moderate whole body hypothermia initiated within 6 h from birth. The objective and prompt identification of infants who are at risk of developing moderate to severe HIE in the critical first hours still remains a challenge. This work proposes a metabolite score calculated based on the relative intensities of three metabolites (choline, 6,8-dihydroxypurine and hypoxanthine that showed maximum correlation with hypoxia time in a consolidated piglet model for neonatal hypoxia-ischemia. The metabolite score's performance as a biomarker for perinatal hypoxia and its usefulness for clinical grading and decision making have been assessed and compared to the performance of lactate which is currently considered the gold standard. For plasma samples withdrawn before and directly after a hypoxic insult, the metabolite score performed similar to lactate. However, it provided an enhanced predictive capacity at 2 h after resuscitation. The present study evidences the usefulness of the metabolite score for improving the early assessment of the severity of the hypoxic insult based on serial determinations in a minimally invasive biofluid. The applicability of the metabolite score for clinical diagnosis and patient stratification for hypothermia treatment has to be confirmed in multicenter trials involving newborns suffering from HIE. Keywords: Hypoxia, Perinatal asphyxia, Newborn, Metabolic biomarker, Neonatal piglet model, Liquid Chromatography – Time-of-Flight Mass Spectrometry (LC-TOF-MS
International Nuclear Information System (INIS)
Wang, Hsiu-Che; Mamishev, Alexander V.
2012-01-01
Development of future electronics for high speed computing requires a silent thermal management method capable of dissipating a broad range of heat generated from application-specific integrated circuits, while keeping the skin temperature below 45 °C. Electrospray evaporative cooling (ESEC) chambers show promise because of their ability to dissipate a broad range of heat within a relatively small size. However, the development and the optimization of ESEC chambers are currently restricted, in part due to the lack of sufficient empirical heat transfer correlations. This paper investigates empirical heat transfer correlations for ESEC chambers with three different geometry types. Since the unstable multi-jet behavior of an ESEC chamber is similar to that of a free-surface traditional impinging liquid jet, these correlations are based on the traditional impinging liquid jet’s empirical correlations, yet are modified to factor in the electric field effect. The results show that the heat transfer enhancement ratio correlations and the Nusselt number correlations for different ESEC chambers cover more than 83% of the experimental data, within ±10% deviation. The sensitivity analysis results and experimental data prove that the variation in the enhancement ratio is sensitive to that of the potential and the flow rate. It is not sensitive to the geometric factor of the same ESEC type. This paper presents a natural convection correlation for chip-scale, heated, flat surfaces when the Rayleigh number is below 3000. Further investigation is necessary to extend these heat transfer correlations to cover additional parameters for different thermal management applications. - Highlights: ► We develop empirical heat transfer correlations for electrospray evaporative cooling chambers. ► The developed heat transfer enhancement correlations fit more than 83% experimental data. ► The developed Nusselt number correlations fit more than 89% experimental data. ► We present a
Directory of Open Access Journals (Sweden)
Xiuli Sang
2012-01-01
Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.
Fisher, Karl B.
1995-08-01
The relation between the galaxy correlation functions in real-space and redshift-space is derived in the linear regime by an appropriate averaging of the joint probability distribution of density and velocity. The derivation recovers the familiar linear theory result on large scales but has the advantage of clearly revealing the dependence of the redshift distortions on the underlying peculiar velocity field; streaming motions give rise to distortions of θ(Ω0.6/b) while variations in the anisotropic velocity dispersion yield terms of order θ(Ω1.2/b2). This probabilistic derivation of the redshift-space correlation function is similar in spirit to the derivation of the commonly used "streaming" model, in which the distortions are given by a convolution of the real-space correlation function with a velocity distribution function. The streaming model is often used to model the redshift-space correlation function on small, highly nonlinear, scales. There have been claims in the literature, however, that the streaming model is not valid in the linear regime. Our analysis confirms this claim, but we show that the streaming model can be made consistent with linear theory provided that the model for the streaming has the functional form predicted by linear theory and that the velocity distribution is chosen to be a Gaussian with the correct linear theory dispersion.
Ran, Shi-Ju
2016-05-01
In this work, a simple and fundamental numeric scheme dubbed as ab initio optimization principle (AOP) is proposed for the ground states of translational invariant strongly correlated quantum lattice models. The idea is to transform a nondeterministic-polynomial-hard ground-state simulation with infinite degrees of freedom into a single optimization problem of a local function with finite number of physical and ancillary degrees of freedom. This work contributes mainly in the following aspects: (1) AOP provides a simple and efficient scheme to simulate the ground state by solving a local optimization problem. Its solution contains two kinds of boundary states, one of which play the role of the entanglement bath that mimics the interactions between a supercell and the infinite environment, and the other gives the ground state in a tensor network (TN) form. (2) In the sense of TN, a novel decomposition named as tensor ring decomposition (TRD) is proposed to implement AOP. Instead of following the contraction-truncation scheme used by many existing TN-based algorithms, TRD solves the contraction of a uniform TN in an opposite way by encoding the contraction in a set of self-consistent equations that automatically reconstruct the whole TN, making the simulation simple and unified; (3) AOP inherits and develops the ideas of different well-established methods, including the density matrix renormalization group (DMRG), infinite time-evolving block decimation (iTEBD), network contractor dynamics, density matrix embedding theory, etc., providing a unified perspective that is previously missing in this fields. (4) AOP as well as TRD give novel implications to existing TN-based algorithms: A modified iTEBD is suggested and the two-dimensional (2D) AOP is argued to be an intrinsic 2D extension of DMRG that is based on infinite projected entangled pair state. This paper is focused on one-dimensional quantum models to present AOP. The benchmark is given on a transverse Ising
Correlation models between environmental factors and bacterial resistance to antimony and copper.
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Zunji Shi
Full Text Available Antimony (Sb and copper (Cu are toxic heavy metals that are associated with a wide variety of minerals. Sb(III-oxidizing bacteria that convert the toxic Sb(III to the less toxic Sb(V are potentially useful for environmental Sb bioremediation. A total of 125 culturable Sb(III/Cu(II-resistant bacteria from 11 different types of mining soils were isolated. Four strains identified as Arthrobacter, Acinetobacter and Janibacter exhibited notably high minimum inhibitory concentrations (MICs for Sb(III (>10 mM,making them the most highly Sb(III-resistant bacteria to date. Thirty-six strains were able to oxidize Sb(III, including Pseudomonas-, Comamonas-, Acinetobacter-, Sphingopyxis-, Paracoccus- Aminobacter-, Arthrobacter-, Bacillus-, Janibacter- and Variovorax-like isolates. Canonical correspondence analysis (CCA revealed that the soil concentrations of Sb and Cu were the most obvious environmental factors affecting the culturable bacterial population structures. Stepwise linear regression was used to create two predictive models for the correlation between soil characteristics and the bacterial Sb(III or Cu(II resistance. The concentrations of Sb and Cu in the soil was the significant factors affecting the bacterial Sb(III resistance, whereas the concentrations of S and P in the soil greatly affected the bacterial Cu(II resistance. The two stepwise linear regression models that we derived are as follows: MIC(Sb(III=606.605+0.14533 x C(Sb+0.4128 x C(Cu and MIC((Cu(II=58.3844+0.02119 x C(S+0.00199 x CP [where the MIC(Sb(III and MIC(Cu(II represent the average bacterial MIC for the metal of each soil (μM, and the C(Sb, C(Cu, C(S and C(P represent concentrations for Sb, Cu, S and P (mg/kg in soil, respectively, p<0.01]. The stepwise linear regression models we developed suggest that metals as well as other soil physicochemical parameters can contribute to bacterial resistance to metals.
Directory of Open Access Journals (Sweden)
Marc Ebner
2011-01-01
synchrony, within which the contents of perception are represented and contained. This mobile zone can be viewed as a model of the neural correlate of consciousness in the brain.
Modelling the correlation between the activities of adjacent genes in drosophila
Thygesen, Helene H.; Zwinderman, Aeilko H.
2005-01-01
Background: Correlation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila and humans. Since such a correlation could be explained by several biochemical, evolutionary, genetic and technological
Correlation between centrality metrics and their application to the opinion model
Li, C.; Li, Q.; Van Mieghem, P.F.A.; Stanley, H.E.; Wang, H.
2015-01-01
In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated
International Nuclear Information System (INIS)
Kim, Hyun-Chul.
1993-05-01
A microscopic model for the N anti N→ππ amplitude has been constructed based on nucleon and delta-isobar exchange, which in the pseudophysical region (4 m π 2 ≤t≤50 m π 2 ) roughly agrees with information obtained by analytic continuation of empirical πN and ππ data. Starting from these amplitudes, the correlated 2 π exchange contribution to the NN interaction has been derived using dispersion theoretic methods. It turns out that, in high partial waves, this contribution is considerably larger (by about 20%) compared to the effective σ'- and ρ-exchange used in the full Bonn potential. As a consequence, it turned out that a quantitative description of high NN partial wave phase shifts definitely favors a somewhat smaller πNN coupling constant, in agreement with recent findings in an empirical analysis by the Nijmegen group. The prediction of low NN partial wave phase shifts has been presented, being compared with empirical NN data. In addition to free NN scattering, medium modifications of the σ channel in the NN potential have been studied. These modifications arise from a change in the ππ rescattering through the in-matter pion dispersion relation. We also have considered the possibility of dropping meson masses as suggested by QCD sum rules. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Soerensen, Niels N.
2009-07-15
The report describes the application of the correlation based transition model of Menter et. al. [1, 2] to the cylinder drag crisis and the stalled flow over an DU-96-W-351 airfoil using the DES methodology. When predicting the flow over airfoils and rotors, the laminar-turbulent transition process can be important for the aerodynamic performance. Today, the most widespread approach is to use fully turbulent computations, where the transitional process is ignored and the entire boundary layer on the wings or airfoils is handled by the turbulence model. The correlation based transition model has lately shown promising results, and the present paper describes the application of the model to predict the drag and shedding frequency for flow around a cylinder from sub to super-critical Reynolds numbers. Additionally, the model is applied to the flow around the DU-96 airfoil, at high angles of attack. (au)
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.
Directory of Open Access Journals (Sweden)
R. Vlijm, I. S. Eliëns, J. -S. Caux
2016-10-01
Full Text Available Pumping a finite energy density into a quantum system typically leads to `melted' states characterized by exponentially-decaying correlations, as is the case for finite-temperature equilibrium situations. An important exception to this rule are states which, while being at high energy, maintain a low entropy. Such states can interestingly still display features of quantum criticality, especially in one dimension. Here, we consider high-energy states in anisotropic Heisenberg quantum spin chains obtained by splitting the ground state's magnon Fermi sea into separate pieces. Using methods based on integrability, we provide a detailed study of static and dynamical spin-spin correlations. These carry distinctive signatures of the Fermi sea splittings, which would be observable in eventual experimental realizations. Going further, we employ a multi-component Tomonaga-Luttinger model in order to predict the asymptotics of static correlations. For this effective field theory, we fix all universal exponents from energetics, and all non-universal correlation prefactors using finite-size scaling of matrix elements. The correlations obtained directly from integrability and those emerging from the Luttinger field theory description are shown to be in extremely good correspondence, as expected, for the large distance asymptotics, but surprisingly also for the short distance behavior. Finally, we discuss the description of dynamical correlations from a mobile impurity model, and clarify the relation of the effective field theory parameters to the Bethe Ansatz solution.
Hölsken, Annett; Schwarz, Marc; Gillmann, Clarissa; Pfister, Christina; Uder, Michael; Doerfler, Arnd; Buchfelder, Michael; Schlaffer, Sven; Fahlbusch, Rudolf; Buslei, Rolf; Bäuerle, Tobias
2018-01-01
Adamantinomatous craniopharyngiomas (ACP) as benign sellar brain tumors are challenging to treat. In order to develop robust in vivo drug testing methodology, the murine orthotopic craniopharyngioma model (PDX) was characterized by magnetic resonance imaging (MRI) and histology in xenografts from three patients (ACP1-3). In ACP PDX, multiparametric MRI was conducted to assess morphologic characteristics such as contrast-enhancing tumor volume (CETV) as well as functional parameters from dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) including area-under-the-curve (AUC), peak enhancement (PE), time-to-peak (TTP) and apparent diffusion coefficient (ADC). These MRI parameters evaluated in 27 ACP PDX were correlated to histological features and percentage of vital tumor cell content. Qualitative analysis of MRI and histology from PDX revealed a similar phenotype as seen in patients, although the MRI appearance in mice resulted in a more solid tumor growth than in humans. CETV were significantly higher in ACP2 xenografts relative to ACP1 and ACP3 which correspond to respective average vitality of 41%, <10% and 26% determined histologically. Importantly, CETV prove tumor growth of ACP2 PDX as it significantly increases in longitudinal follow-up of 110 days. Furthermore, xenografts from ACP2 revealed a significantly higher AUC, PE and TTP in comparison to ACP3, and significantly increased ADC relative to ACP1 and ACP3 respectively. Overall, DCE-MRI and DWI can be used to distinguish vital from non-vital grafts, when using a cut off value of 15% for vital tumor cell content. MRI enables the assessment of craniopharyngioma PDX vitality in vivo as validated histologically.
Bayesian model comparison for one-dimensional azimuthal correlations in 200GeV AuAu collisions
Directory of Open Access Journals (Sweden)
Eggers Hans C.
2016-01-01
Full Text Available In the context of data modeling and comparisons between different fit models, Bayesian analysis calls that model best which has the largest evidence, the prior-weighted integral over model parameters of the likelihood function. Evidence calculations automatically take into account both the usual chi-squared measure and an Occam factor which quantifies the price for adding extra parameters. Applying Bayesian analysis to projections onto azimuth of 2D angular correlations from 200 GeV AuAu collisions, we consider typical model choices including Fourier series and a Gaussian plus combinations of individual cosine components. We find that models including a Gaussian component are consistently preferred over pure Fourier-series parametrizations, sometimes strongly so. For 0–5% central collisions the Gaussian-plus-dipole model performs better than Fourier Series models or any other combination of Gaussian-plus-multipoles.
On two-point boundary correlations in the six-vertex model with domain wall boundary conditions
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.
International Nuclear Information System (INIS)
Mac Low, Mordecai-Mark; Glover, Simon C. O.
2012-01-01
Observations of spiral galaxies show a strong linear correlation between the ratio of molecular to atomic hydrogen surface density R mol and midplane pressure. To explain this, we simulate three-dimensional, magnetized turbulence, including simplified treatments of non-equilibrium chemistry and the propagation of dissociating radiation, to follow the formation of H 2 from cold atomic gas. The formation timescale for H 2 is sufficiently long that equilibrium is not reached within the 20-30 Myr lifetimes of molecular clouds. The equilibrium balance between radiative dissociation and H 2 formation on dust grains fails to predict the time-dependent molecular fractions we find. A simple, time-dependent model of H 2 formation can reproduce the gross behavior, although turbulent density perturbations increase molecular fractions by a factor of few above it. In contradiction to equilibrium models, radiative dissociation of molecules plays little role in our model for diffuse radiation fields with strengths less than 10 times that of the solar neighborhood, because of the effective self-shielding of H 2 . The observed correlation of R mol with pressure corresponds to a correlation with local gas density if the effective temperature in the cold neutral medium of galactic disks is roughly constant. We indeed find such a correlation of R mol with density. If we examine the value of R mol in our local models after a free-fall time at their average density, as expected for models of molecular cloud formation by large-scale gravitational instability, our models reproduce the observed correlation over more than an order-of-magnitude range in density.
Mac Low, Mordecai-Mark; Glover, Simon C. O.
2012-02-01
Observations of spiral galaxies show a strong linear correlation between the ratio of molecular to atomic hydrogen surface density R mol and midplane pressure. To explain this, we simulate three-dimensional, magnetized turbulence, including simplified treatments of non-equilibrium chemistry and the propagation of dissociating radiation, to follow the formation of H2 from cold atomic gas. The formation timescale for H2 is sufficiently long that equilibrium is not reached within the 20-30 Myr lifetimes of molecular clouds. The equilibrium balance between radiative dissociation and H2 formation on dust grains fails to predict the time-dependent molecular fractions we find. A simple, time-dependent model of H2 formation can reproduce the gross behavior, although turbulent density perturbations increase molecular fractions by a factor of few above it. In contradiction to equilibrium models, radiative dissociation of molecules plays little role in our model for diffuse radiation fields with strengths less than 10 times that of the solar neighborhood, because of the effective self-shielding of H2. The observed correlation of R mol with pressure corresponds to a correlation with local gas density if the effective temperature in the cold neutral medium of galactic disks is roughly constant. We indeed find such a correlation of R mol with density. If we examine the value of R mol in our local models after a free-fall time at their average density, as expected for models of molecular cloud formation by large-scale gravitational instability, our models reproduce the observed correlation over more than an order-of-magnitude range in density.
DEFF Research Database (Denmark)
Kinnebrock, Silja; Podolskij, Mark
This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....
International Nuclear Information System (INIS)
Fujiwara, Shigeyasu; Sakata, Fumihiko
2003-01-01
The quantum level fluctuation in various systems has been shown to be characterized by the random matrix theory, and to be related to a regular-to-chaos transition in classical system. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of quantum level density is inversely proportional to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)
Final Test Analysis of Post Graduate Medical Residents
Directory of Open Access Journals (Sweden)
Maliheh Arab
2009-04-01
Full Text Available Background and purpose: Multiple choice questions are the most frequent test for medical students. It is important to analysis the overall response to individual questions in the test.The aim of this study is to analyse questions of post graduate medical residency tests.Methods: Final annual local (Ramadan medical school and national tests given to three Residency groups including 17 Obstetrics and gynecology testees, 7 pediatrics and 12 internal medicine in 2004 were studied. In local tests residents answered to 148, 150 and 144 and in national tests to ISO MCQS. Questions were evaluated regarding cognitive domain level, Difficultly index and Discriminative index and finally to evaluate the optimal, proper, acceptable and ''must omitted" questions.Results: Questions of local Obstetrics and gynecology, pediatrics and internal medicine tests evaluated the "recall" level in 72%, 72% and 51% and in national tests 71%, 35% and 19%, respectively. Questions with Discriminative indices of 0.7 or more (proper were 3 and 5% in Obstetrics and gynecology, 3.5% and 1% in pediatrics and 1% in local and national tests. Proper difficulty indices (30-70 were shown in 53% and 54% in Obstetrics and gynecology, 34% and 43% in pediatrics and 40% and 42% in internal medicine. Generally evaluating, "must omitted" questions in local and national tests were 76% in Obstetrics and gynecology, 81% and 79% in pediatrics and 91% and 85% in internal medicine. The most common causes making the questions to be considered "must omitted" in studied tests were negative, zero or less than 0.2 Discriminative indices.Conclusion: Test analysis of final annual local (Ramadan medical school and national tests of Obstetrics and gynecology, Pediatrics and internal medicine residency programs in 2004 revealed that most of the questions are planned in "recall" level, harbor improper
International Nuclear Information System (INIS)
Ahmadi, B.; Chazal, H.; Waeckerle, T.; Roudet, J.
2008-01-01
Multilayer cores are suitable for integrated planar magnetic components. We proposed here to investigate the frequency behavior of multilayer nanocrystalline cores in the frame of a one-dimensional (1-D) electromagnetic propagation model. Electromagnetic wave equations are considered to explain the phenomena from the macroscopic point of view. A domain wall description is considered to take into account non-homogeneity of magnetic media. This mesoscopic model is correlated to macroscopic model through complex permeability. The scope of validity of the model is determined by means of indirect permeability measurement. Finally, the behavior of the multilayer core is predicted by using an equivalent electrical circuit and will interest component designers
Krumpe, Mirko; Miyaji, Takamitsu; Coil, Alison L.; Aceves, Hector
2018-02-01
We present the clustering properties and halo occupation distribution (HOD) modelling of very low redshift, hard X-ray-detected active galactic nuclei (AGN) using cross-correlation function measurements with Two-Micron All Sky Survey galaxies. Spanning a redshift range of 0.007 2MASS galaxies.
Kim, Song-Ju; Aono, Masashi; Hara, Masahiko
2010-07-01
We propose a model - the "tug-of-war (TOW) model" - to conduct unique parallel searches using many nonlocally-correlated search agents. The model is based on the property of a single-celled amoeba, the true slime mold Physarum, which maintains a constant intracellular resource volume while collecting environmental information by concurrently expanding and shrinking its branches. The conservation law entails a "nonlocal correlation" among the branches, i.e., volume increment in one branch is immediately compensated by volume decrement(s) in the other branch(es). This nonlocal correlation was shown to be useful for decision making in the case of a dilemma. The multi-armed bandit problem is to determine the optimal strategy for maximizing the total reward sum with incompatible demands, by either exploiting the rewards obtained using the already collected information or exploring new information for acquiring higher payoffs involving risks. Our model can efficiently manage the "exploration-exploitation dilemma" and exhibits good performances. The average accuracy rate of our model is higher than those of well-known algorithms such as the modified -greedy algorithm and modified softmax algorithm, especially, for solving relatively difficult problems. Moreover, our model flexibly adapts to changing environments, a property essential for living organisms surviving in uncertain environments.
Molla, Yordanos B; Wardrop, Nicola A; Le Blond, Jennifer S; Baxter, Peter; Newport, Melanie J; Atkinson, Peter M; Davey, Gail
2014-06-20
The precise trigger of podoconiosis - endemic non-filarial elephantiasis of the lower legs - is unknown. Epidemiological and ecological studies have linked the disease with barefoot exposure to red clay soils of volcanic origin. Histopathology investigations have demonstrated that silicon, aluminium, magnesium and iron are present in the lower limb lymph node macrophages of both patients and non-patients living barefoot on these clays. We studied the spatial variation (variations across an area) in podoconiosis prevalence and the associated environmental factors with a goal to better understanding the pathogenesis of podoconiosis. Fieldwork was conducted from June 2011 to February 2013 in 12 kebeles (administrative units) in northern Ethiopia. Geo-located prevalence data and soil samples were collected and analysed along with secondary geological, topographic, meteorological and elevation data. Soil data were analysed for chemical composition, mineralogy and particle size, and were interpolated to provide spatially continuous information. Exploratory, spatial, univariate and multivariate regression analyses of podoconiosis prevalence were conducted in relation to primary (soil) and secondary (elevation, precipitation, and geology) covariates. Podoconiosis distribution showed spatial correlation with variation in elevation and precipitation. Exploratory analysis identified that phyllosilicate minerals, particularly clay (smectite and kaolinite) and mica groups, quartz (crystalline silica), iron oxide, and zirconium were associated with podoconiosis prevalence. The final multivariate model showed that the quantities of smectite (RR = 2.76, 95% CI: 1.35, 5.73; p = 0.007), quartz (RR = 1.16, 95% CI: 1.06, 1.26; p = 0.001) and mica (RR = 1.09, 95% CI: 1.05, 1.13; p < 0.001) in the soil had positive associations with podoconiosis prevalence. More quantities of smectite, mica and quartz within the soil were associated with podoconiosis prevalence. Together with previous
International Nuclear Information System (INIS)
Mayzelis, Z.A.; Apostolov, S.S.; Melnyk, S.S.; Usatenko, O.V.; Yampol'skii, V.A.
2007-01-01
A theory of symbolic dynamic systems with long-range correlations based on the consideration of the binary N-step Markov chains developed earlier in Phys Rev Lett 2003;90:110601 is generalized to the biased case (non-equal numbers of zeros and unities in the chain). In the model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities (zeros) among the preceding N symbols. The correlation and distribution functions as well as the variance of number of symbols in the words of arbitrary length L are obtained analytically and verified by numerical simulations. A self-similarity of the studied stochastic process is revealed and the similarity group transformation of the chain parameters is presented. The diffusion Fokker-Planck equation governing the distribution function of the L-words is explored. If the persistent correlations are not extremely strong, the distribution function is shown to be the Gaussian with the variance being nonlinearly dependent on L. An equation connecting the memory and correlation function of the additive Markov chain is presented. This equation allows reconstructing a memory function using a correlation function of the system. Effectiveness and robustness of the proposed method is demonstrated by simple model examples. Memory functions of concrete coarse-grained literary texts are found and their universal power-law behavior at long distances is revealed
Energy Technology Data Exchange (ETDEWEB)
Mayzelis, Z.A. [Department of Physics, Kharkov National University, 4 Svoboda Sq., Kharkov 61077 (Ukraine); Apostolov, S.S. [Department of Physics, Kharkov National University, 4 Svoboda Sq., Kharkov 61077 (Ukraine); Melnyk, S.S. [A. Ya. Usikov Institute for Radiophysics and Electronics, Ukrainian Academy of Science, 12 Proskura Street, 61085 Kharkov (Ukraine); Usatenko, O.V. [A. Ya. Usikov Institute for Radiophysics and Electronics, Ukrainian Academy of Science, 12 Proskura Street, 61085 Kharkov (Ukraine)]. E-mail: usatenko@ire.kharkov.ua; Yampol' skii, V.A. [A. Ya. Usikov Institute for Radiophysics and Electronics, Ukrainian Academy of Science, 12 Proskura Street, 61085 Kharkov (Ukraine)
2007-10-15
A theory of symbolic dynamic systems with long-range correlations based on the consideration of the binary N-step Markov chains developed earlier in Phys Rev Lett 2003;90:110601 is generalized to the biased case (non-equal numbers of zeros and unities in the chain). In the model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities (zeros) among the preceding N symbols. The correlation and distribution functions as well as the variance of number of symbols in the words of arbitrary length L are obtained analytically and verified by numerical simulations. A self-similarity of the studied stochastic process is revealed and the similarity group transformation of the chain parameters is presented. The diffusion Fokker-Planck equation governing the distribution function of the L-words is explored. If the persistent correlations are not extremely strong, the distribution function is shown to be the Gaussian with the variance being nonlinearly dependent on L. An equation connecting the memory and correlation function of the additive Markov chain is presented. This equation allows reconstructing a memory function using a correlation function of the system. Effectiveness and robustness of the proposed method is demonstrated by simple model examples. Memory functions of concrete coarse-grained literary texts are found and their universal power-law behavior at long distances is revealed.
Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin
2015-06-01
We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.
Correlations in state space can cause sub-optimal adaptation of optimal feedback control models
Aprasoff, Jonathan; Donchin, Opher
2011-01-01
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedb...
Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene
2011-04-01
We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene
2011-04-01
We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Change in genetic correlation due to selection using animal model evaluation.
Strandén, I; Mäntysaari, E A; Mäki-Tanila, A
1993-01-12
Monte Carlo simulation and analytical calculations were used to study the effect of selection on genetic correlation between two traits. The simulated breeding program was based on a closed adult multiple ovulation and embryo transfer nucleus breeding scheme. Selection was on an index calculated using multi-trait animal model (AM). Analytical formulae applicable to any evaluation method were derived to predict change in genetic (co)variance due to selection under multi-trait selection using different evaluation methods. Two formulae were investigated, one assuming phenotypic selection and the other based on a recursive two-generation AM selection index. The recursive AM method approximated information due to relatives by a relationship matrix of two generations. Genetic correlation after selection was compared under different levels of initial genetic and environmental correlations with two different selection criteria. Changes in genetic correlation were similar in simulation and analytical predictions. After one round of selection the recursive AM method and the simulation gave similar predictions while the phenotypic selection predicted usually more change in genetic correlation. After several rounds of selection both analytical formulae predicted more change in genetic correlation than the simulation. ZUSAMMENFASSUNG: Änderung der genetischen Korrelation bei Selektion mit einem Tiermodell Der Selektionseffekt auf die genetische Korrelation zwischen zwei Merkmalen wurde mit Hilfe von Monte Carlo-Simulation und analytischen Berechnungen untersucht. Ein geschlossener Adulter - MOET (Multiple Ovulation and Embryo Transfer) Zuchtplan wurde simuliert. Die Selektion gründete sich auf einen Index, der die Zuchtwertschätzung des Mehrmerkmals-Tiermodells benutzte. Analytische Formeln für die Voraussage der Änderung der genetischen (Ko)varianz unter multivariate Selektion für verschiedene Zuchtwertschätzungsmethode wurden deduziert. Zwei Formeln wurden studiert
Swanson, David L; Thomas, Nathan E; Liknes, Eric T; Cooper, Sheldon J
2012-01-01
The underlying assumption of the aerobic capacity model for the evolution of endothermy is that basal (BMR) and maximal aerobic metabolic rates are phenotypically linked. However, because BMR is largely a function of central organs whereas maximal metabolic output is largely a function of skeletal muscles, the mechanistic underpinnings for their linkage are not obvious. Interspecific studies in birds generally support a phenotypic correlation between BMR and maximal metabolic output. If the aerobic capacity model is valid, these phenotypic correlations should also extend to intraspecific comparisons. We measured BMR, M(sum) (maximum thermoregulatory metabolic rate) and MMR (maximum exercise metabolic rate in a hop-flutter chamber) in winter for dark-eyed juncos (Junco hyemalis), American goldfinches (Carduelis tristis; M(sum) and MMR only), and black-capped chickadees (Poecile atricapillus; BMR and M(sum) only) and examined correlations among these variables. We also measured BMR and M(sum) in individual house sparrows (Passer domesticus) in both summer, winter and spring. For both raw metabolic rates and residuals from allometric regressions, BMR was not significantly correlated with either M(sum) or MMR in juncos. Moreover, no significant correlation between M(sum) and MMR or their mass-independent residuals occurred for juncos or goldfinches. Raw BMR and M(sum) were significantly positively correlated for black-capped chickadees and house sparrows, but mass-independent residuals of BMR and M(sum) were not. These data suggest that central organ and exercise organ metabolic levels are not inextricably linked and that muscular capacities for exercise and shivering do not necessarily vary in tandem in individual birds. Why intraspecific and interspecific avian studies show differing results and the significance of these differences to the aerobic capacity model are unknown, and resolution of these questions will require additional studies of potential mechanistic
Directory of Open Access Journals (Sweden)
David L Swanson
Full Text Available The underlying assumption of the aerobic capacity model for the evolution of endothermy is that basal (BMR and maximal aerobic metabolic rates are phenotypically linked. However, because BMR is largely a function of central organs whereas maximal metabolic output is largely a function of skeletal muscles, the mechanistic underpinnings for their linkage are not obvious. Interspecific studies in birds generally support a phenotypic correlation between BMR and maximal metabolic output. If the aerobic capacity model is valid, these phenotypic correlations should also extend to intraspecific comparisons. We measured BMR, M(sum (maximum thermoregulatory metabolic rate and MMR (maximum exercise metabolic rate in a hop-flutter chamber in winter for dark-eyed juncos (Junco hyemalis, American goldfinches (Carduelis tristis; M(sum and MMR only, and black-capped chickadees (Poecile atricapillus; BMR and M(sum only and examined correlations among these variables. We also measured BMR and M(sum in individual house sparrows (Passer domesticus in both summer, winter and spring. For both raw metabolic rates and residuals from allometric regressions, BMR was not significantly correlated with either M(sum or MMR in juncos. Moreover, no significant correlation between M(sum and MMR or their mass-independent residuals occurred for juncos or goldfinches. Raw BMR and M(sum were significantly positively correlated for black-capped chickadees and house sparrows, but mass-independent residuals of BMR and M(sum were not. These data suggest that central organ and exercise organ metabolic levels are not inextricably linked and that muscular capacities for exercise and shivering do not necessarily vary in tandem in individual birds. Why intraspecific and interspecific avian studies show differing results and the significance of these differences to the aerobic capacity model are unknown, and resolution of these questions will require additional studies of potential
The development of a tensile-shear punch correlation for yield properties of model austenitic alloys
Energy Technology Data Exchange (ETDEWEB)
Hankin, G.L.; Faulkner, R.G. [Loughborough Univ. (United Kingdom); Hamilton, M.L.; Garner, F.A. [Pacific Northwest National Lab., Richland, WA (United States)
1997-08-01
The effective shear yield and maximum strengths of a set of neutron-irradiated, isotopically tailored austentic alloys were evaluated using the shear punch test. The dependence on composition and neutron dose showed the same trends as were observed in the corresponding miniature tensile specimen study conducted earlier. A single tensile-shear punch correlation was developed for the three alloys in which the maximum shear stress or Tresca criterion was successfully applied to predict the slope. The correlation will predict the tensile yield strength of the three different austenitic alloys tested to within {+-}53 MPa. The accuracy of the correlation improves with increasing material strength, to within {+-} MPa for predicting tensile yield strengths in the range of 400-800 MPa.
The development of a tensile-shear punch correlation for yield properties of model austenitic alloys
International Nuclear Information System (INIS)
Hankin, G.L.; Faulkner, R.G.; Hamilton, M.L.; Garner, F.A.
1997-01-01
The effective shear yield and maximum strengths of a set of neutron-irradiated, isotopically tailored austentic alloys were evaluated using the shear punch test. The dependence on composition and neutron dose showed the same trends as were observed in the corresponding miniature tensile specimen study conducted earlier. A single tensile-shear punch correlation was developed for the three alloys in which the maximum shear stress or Tresca criterion was successfully applied to predict the slope. The correlation will predict the tensile yield strength of the three different austenitic alloys tested to within ±53 MPa. The accuracy of the correlation improves with increasing material strength, to within ± MPa for predicting tensile yield strengths in the range of 400-800 MPa
International Nuclear Information System (INIS)
Boucher, T.J.
1987-01-01
To provide data for assessment and development of thermal-hydraulic computer codes, bottom main feedwater-line-break transient simulations were performed in a scale model (Semiscale Mod-2C) of a pressurized water reactor (PWR) with conditions typical of a PWR (15.0 MPa primary pressure, 600 K steam generator inlet plenum fluid temperatures, 6.2 MPa secondary pressure). The state-of-the-art measurements in the scale model (Type III) steam generator allow for the determination of U-tube steam generator allow for the determination of U-tube steam generator secondary component interactions, tube bundle local radial heat transfer, and tube bundle and riser vapor void fractions for steady state and transient operations. To enhance the understanding of the observed phenomena, the component interactions, local heat fluxes, local secondary convective heat transfer coefficients and local vapor void fractions are discussed for steady state, full-power and transient operations. Comparisons between the measurement-derived secondary convective heat transfer coefficients and those predicted by a number of correlations, including the Chen correlation currently used in thermal-hydraulic computer codes, show that none of the correlations adequately predict the data and points out the need for the formulation of a new correlation based on this experimental data. The unique information presented herein should be of the interest to anyone involved in modeling inverted U-tube steam generator thermal-hydraulics for forced convection boiling/vaporization heat transfer. 5 refs., 13 figs., 1 tab
Watkins, N. W.
2013-01-01
I review the hierarchy of approaches to complex systems, focusing particularly on stochastic equations. I discuss how the main models advocated by the late Benoit Mandelbrot fit into this classification, and how they continue to contribute to cross-disciplinary approaches to the increasingly important problems of correlated extreme events and unresolved scales. The ideas have broad importance, with applications ranging across science areas as diverse as the heavy tailed distributions of intense rainfall in hydrology, after which Mandelbrot named the "Noah effect"; the problem of correlated runs of dry summers in climate, after which the "Joseph effect" was named; and the intermittent, bursty, volatility seen in finance and fluid turbulence.
Markelov, Oleg; Nguyen Duc, Viet; Bogachev, Mikhail
2017-11-01
Recently we have suggested a universal superstatistical model of user access patterns and aggregated network traffic. The model takes into account the irregular character of end user access patterns on the web via the non-exponential distributions of the local access rates, but neglects the long-term correlations between these rates. While the model is accurate for quasi-stationary traffic records, its performance under highly variable and especially non-stationary access dynamics remains questionable. In this paper, using an example of the traffic patterns from a highly loaded network cluster hosting the website of the 1998 FIFA World Cup, we suggest a generalization of the previously suggested superstatistical model by introducing long-term correlations between access rates. Using queueing system simulations, we show explicitly that this generalization is essential for modeling network nodes with highly non-stationary access patterns, where neglecting long-term correlations leads to the underestimation of the empirical average sojourn time by several decades under high throughput utilization.
Slade, Gordon; Tomberg, Alexandre
2016-03-01
We extend and apply a rigorous renormalisation group method to study critical correlation functions, on the 4-dimensional lattice Z4, for the weakly coupled n-component {|\\varphi|4} spin model for all {n ≥ 1}, and for the continuous-time weakly self-avoiding walk. For the {|\\varphi|4} model, we prove that the critical two-point function has | x|-2 (Gaussian) decay asymptotically, for {n ≥ 1}. We also determine the asymptotic decay of the critical correlations of the squares of components of {\\varphi}, including the logarithmic corrections to Gaussian scaling, for {n ≥ 1}. The above extends previously known results for n = 1 to all {n ≥ 1}, and also observes new phenomena for n > 1, all with a new method of proof. For the continuous-time weakly self-avoiding walk, we determine the decay of the critical generating function for the "watermelon" network consisting of p weakly mutually- and self-avoiding walks, for all {p ≥ 1}, including the logarithmic corrections. This extends a previously known result for p = 1, for which there is no logarithmic correction, to a much more general setting. In addition, for both models, we study the approach to the critical point and prove the existence of logarithmic corrections to scaling for certain correlation functions. Our method gives a rigorous analysis of the weakly self-avoiding walk as the n = 0 case of the {|\\varphi|4} model, and provides a unified treatment of both models, and of all the above results.
Chenghua, Ou; Chaochun, Li; Siyuan, Huang; Sheng, James J.; Yuan, Xu
2017-12-01
As the platform-based horizontal well production mode has been widely applied in petroleum industry, building a reliable fine reservoir structure model by using horizontal well stratigraphic correlation has become very important. Horizontal wells usually extend between the upper and bottom boundaries of the target formation, with limited penetration points. Using these limited penetration points to conduct well deviation correction means the formation depth information obtained is not accurate, which makes it hard to build a fine structure model. In order to solve this problem, a method of fine reservoir structure modeling, based on 3D visualized stratigraphic correlation among horizontal wells, is proposed. This method can increase the accuracy when estimating the depth of the penetration points, and can also effectively predict the top and bottom interfaces in the horizontal penetrating section. Moreover, this method will greatly increase not only the number of points of depth data available, but also the accuracy of these data, which achieves the goal of building a reliable fine reservoir structure model by using the stratigraphic correlation among horizontal wells. Using this method, four 3D fine structure layer models have been successfully built of a specimen shale gas field with platform-based horizontal well production mode. The shale gas field is located to the east of Sichuan Basin, China; the successful application of the method has proven its feasibility and reliability.
International Nuclear Information System (INIS)
Fujiwara, Shigeyasu; Sakata, Fumihiko
2003-01-01
In many quantum systems, random matrix theory has been used to characterize quantum level fluctuations, which is known to be a quantum correspondent to a regular-to-chaos transition in classical systems. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of the quantum level density is roughly inversely proportional relation to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)
Noise sensitivity of portfolio selection in constant conditional correlation GARCH models
Varga-Haszonits, I.; Kondor, I.
2007-11-01
This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.
Van Dyke, Michael B.
2013-01-01
Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.
Brown, Andrew M.; DeLessio, Jennifer L.; Jacobs, Preston W.
2018-01-01
Many structures in the launch vehicle industry operate in liquid hydrogen (LH2), from the hydrogen fuel tanks through the ducts and valves and into the pump sides of the turbopumps. Calculating the structural dynamic response of these structures is critical for successful qualification of this hardware, but accurate knowledge of the natural frequencies is based entirely on numerical or analytical predictions of frequency reduction due to the added-fluid-mass effect because testing in LH2 has always been considered too difficult and dangerous. This fluid effect is predicted to be approximately 4-5% using analytical formulations for simple cantilever beams. As part of a comprehensive test/analysis program to more accurately assess pump inducers operating in LH2, a series of frequency tests in LH2 were performed at NASA/Marshall Space Flight Center's unique cryogenic test facility. These frequency tests are coupled with modal tests in air and water to provide critical information not only on the mass effect of LH2, but also the cryogenic temperature effect on Young's Modulus for which the data is not extensive. The authors are unaware of any other reported natural frequency testing in this media. In addition to the inducer, a simple cantilever beam was also tested in the tank to provide a more easily modeled geometry as well as one that has an analytical solution for the mass effect. This data will prove critical for accurate structural dynamic analysis of these structures, which operate in a highly-dynamic environment.
Energy Technology Data Exchange (ETDEWEB)
Yamini, Yadollah, E-mail: yyamini@modares.ac.ir [Department of Chemistry, Faculty of Sciences, Tarbiat Modares University, P.O. Box 14115-175, Tehran (Iran, Islamic Republic of); Moradi, Morteza [Department of Chemistry, Faculty of Sciences, Tarbiat Modares University, P.O. Box 14115-175, Tehran (Iran, Islamic Republic of)
2011-07-15
Highlights: > Ketoconazole (KZ) and clotrimazole (CZ) are two antifungal drugs. > The solubilities of KZ and CZ were measured in supercritical CO{sub 2}. > The experimental results were correlated using five density based models. > The heats' of drug-CO{sub 2} solvation and drug vaporization were estimated. - Abstract: In the present study the solubilities of two antifungal drugs of ketoconazole and clotrimazole in supercritical carbon dioxide were measured using a simple static method. The experimental data were measured at (308 to 348) K, over the pressure range of (12.2 to 35.5) MPa. The mole fraction solubilities ranged from 0.2 . 10{sup -6} to 17.45 . 10{sup -5}. In this study five density based models were used to calculate the solubility of drugs in supercritical carbon dioxide. The density based models are Chrastil, modified Chrastil, Bartle, modified Bartle and Mendez-Santiago and Teja (M-T). Interaction parameters for the studied models were obtained and the percentage of average absolute relative deviation (AARD%) in each calculation was displayed. The correlation results showed good agreement with the experimental data. A comparison among the five models revealed that the Bartle and its modified models gave much better correlations of the solubility data with an average absolute relative deviation (AARD%) ranging from 4.8% to 6.2% and from 4.5% to 6.3% for ketoconazole and clotrimazole, respectively. Using the correlation results, the heat of drug-CO{sub 2} solvation and that of drug vaporization was separately approximated in the range of (-22.1 to -26.4 and 88.3 to 125.9) kJ . mol{sup -1}.
International Nuclear Information System (INIS)
Boschi, C Degli Esposti; Di Dio, M; Morandi, G; Roncaglia, M
2009-01-01
We derive the dominant contribution to the large-distance decay laws of correlation functions towards their asymptotic limits for a spin chain model that exhibits both Haldane and Neel phases in its ground-state phase diagram. The analytic results are obtained by means of an approximate mapping between a spin-1 anisotropic Hamiltonian onto a fermionic model of noninteracting Bogoliubov quasiparticles related in turn (via Jordan-Wigner transformation) to the XY spin-1/2 chain in a transverse field. This approach allows us to express the spin-1 string operators in terms of fermionic operators so that the dominant contribution to the string correlators at large distances can be computed using the technique of Toeplitz determinants. As expected, we find long-range string order both in the longitudinal and in the transverse channel in the Haldane phase, while in the Neel phase only the longitudinal order survives. In this way, the long-range string order can be explicitly related to the components of the magnetization of the XY model. Moreover, apart from the critical line, where the decay is algebraic, we find that in the gapped phases the decay is governed by an exponential tail multiplied by power-law factors. As regards the usual two points correlation functions, we show that the longitudinal one behaves in a 'dual' fashion with respect to the transverse string correlator, namely both the asymptotic values and the decay laws exchange when the transition line is crossed. For the transverse spin-spin correlator, we always find a finite characteristic length which is an unexpected feature at the critical point. The results of this analysis prove some conjectures put forward in the past. We also comment briefly on the entanglement features of the original system versus those of the effective model. The goodness of the approximation and the analytical predictions are checked versus density-matrix renormalization group calculations
International Nuclear Information System (INIS)
Krommes, J.A.
1999-01-01
Highly simplified models of random flows interacting with background microturbulence are analyzed. In the limit of very rapid velocity fluctuations, it is shown rigorously that the fluctuation level of a passively advected scalar is not controlled by the rms shear. In a model with random velocities dependent only on time, the level of cross-correlations between the flows and the background turbulence regulates the saturation level. This effect is illustrated by considering a simple stochastic-oscillator model, both exactly and with analysis and numerical solutions of the direct-interaction approximation. Implications for the understanding of self-consistent turbulence are discussed briefly
Multi-loop correlators for rational theories of 2D gravity from the generalized Kontsevich models
DEFF Research Database (Denmark)
Kristjansen, C.
1994-01-01
functions of the susceptibilities and the eigenvalues of the external field. We furthermore use the moment technique to derive a closed expression for the genus zero multi-loop correlators for $(3,3m-1)$ and $(3,3m-2)$ rational matter fields coupled to gravity. We comment on the relation between the two-matrix...
A correlated-cluster model and the ridge phenomenon in hadron–hadron collisions
Energy Technology Data Exchange (ETDEWEB)
Sanchis-Lozano, Miguel-Angel, E-mail: Miguel.Angel.Sanchis@ific.uv.es [Instituto de Física Corpuscular (IFIC) and Departamento de Física Teórica, Centro Mixto Universitat de València-CSIC, Dr. Moliner 50, E-46100 Burjassot, Valencia (Spain); Sarkisyan-Grinbaum, Edward, E-mail: sedward@cern.ch [Experimental Physics Department, CERN, 1211 Geneva 23 (Switzerland); Department of Physics, The University of Texas at Arlington, Arlington, TX 76019 (United States)
2017-03-10
A study of the near-side ridge phenomenon in hadron–hadron collisions based on a cluster picture of multiparticle production is presented. The near-side ridge effect is shown to have a natural explanation in this context provided that clusters are produced in a correlated manner in the collision transverse plane.
Carbon dioxide exchange over agricultural landscape using eddy correlation and footprint modelling
DEFF Research Database (Denmark)
Søgaard, H.; Jensen, N.O.; Bøgh, E.
2003-01-01
Within an agricultural landscape of western Denmark, the carbon dioxide exchange was studied throughout a year (April 1998-March 1999). During the growing season, five eddy correlation systems were operated in parallel over some of the more important crops (winter wheat, winter barley, spring...
Modelling the distribution of fish accounting for spatial correlation and overdispersion
DEFF Research Database (Denmark)
Lewy, Peter; Kristensen, Kasper
2009-01-01
correlation between observations. It is therefore possible to predict and interpolate unobserved densities at any location in the area. This is important for obtaining unbiased estimates of stock concentration and other measures depending on the distribution in the entire area. Results show that the spatial...
A correlated-cluster model and the ridge phenomenon in hadron-hadron collisions
Sanchis-Lozano, Miguel-Angel
2017-03-10
A study of the near-side ridge phenomenon in hadron-hadron collisions based on a cluster picture of multiparticle production is presented. The near-side ridge effect is shown to have a natural explanation in this context provided that clusters are produced in a correlated manner in the collision transverse plane.
Correlation between observable of four nucleon system in two-body model
International Nuclear Information System (INIS)
Barlette, V.E.
1988-01-01
The four nucleon system with effective nucleon-trinucleon interaction for s waves in states of spin Y = 0 and isospin Y = 0, is studied. The correlations between four nucleon systemn and scattering wavelength, binding energies and, coulomb energy of four nucleons are investigated by N/D method considering only the excited state. (M.C.K.)
Institute of Scientific and Technical Information of China (English)
HAN Li-Bo; GONG Xiao-Long; CAO Li; WU Da-Jin
2007-01-01
An approximate Fokker-P1anck equation for the logistic growth model which is driven by coloured correlated noises is derived by applying the Novikov theorem and the Fox approximation. The steady-state probability distribution (SPD) and the mean of the tumour cell number are analysed. It is found that the SPD is the single extremum configuration when the degree of correlation between the multiplicative and additive noises, λ, is in -1＜λ ≤ 0 and can be the double extrema in 0＜λ＜1. A configuration transition occurs because of the variation of noise parameters. A minimum appears in the curve of the mean of the steady-state tumour cell number, 〈x〉, versus λ. The position and the value of the minimum are controlled by the noise-correlated times.
International Nuclear Information System (INIS)
Krutitsky, Konstantin V.; Navez, Patrick; Schuetzhold, Ralf; Queisser, Friedemann
2014-01-01
We study a quantum quench in the Bose-Hubbard model where the tunneling rate J is suddenly switched from zero to a finite value in the Mott regime. In order to solve the many-body quantum dynamics far from equilibrium, we consider the reduced density matrices for a finite number of lattice sites and split them up into on-site density operators, i.e., the mean field, plus two-point and three-point correlations etc. Neglecting three-point and higher correlations, we are able to numerically simulate the time-evolution of the on-site density matrices and the two-point quantum correlations (e.g., their effective light-cone structure) for a comparably large number of lattice sites. (orig.)
Correlation studies for B-spline modeled F2 Chapman parameters obtained from FORMOSAT-3/COSMIC data
Directory of Open Access Journals (Sweden)
M. Limberger
2014-12-01
Full Text Available The determination of ionospheric key quantities such as the maximum electron density of the F2 layer NmF2, the corresponding F2 peak height hmF2 and the F2 scale height HF2 are of high relevance in 4-D ionosphere modeling to provide information on the vertical structure of the electron density (Ne. The Ne distribution with respect to height can, for instance, be modeled by the commonly accepted F2 Chapman layer. An adequate and observation driven description of the vertical Ne variation can be obtained from electron density profiles (EDPs derived by ionospheric radio occultation measurements between GPS and low Earth orbiter (LEO satellites. For these purposes, the six FORMOSAT-3/COSMIC (F3/C satellites provide an excellent opportunity to collect EDPs that cover most of the ionospheric region, in particular the F2 layer. For the contents of this paper, F3/C EDPs have been exploited to determine NmF2, hmF2 and HF2 within a regional modeling approach. As mathematical base functions, endpoint-interpolating polynomial B-splines are considered to model the key parameters with respect to longitude, latitude and time. The description of deterministic processes and the verification of this modeling approach have been published previously in Limberger et al. (2013, whereas this paper should be considered as an extension dealing with related correlation studies, a topic to which less attention has been paid in the literature. Relations between the B-spline series coefficients regarding specific key parameters as well as dependencies between the three F2 Chapman key parameters are in the main focus. Dependencies are interpreted from the post-derived correlation matrices as a result of (1 a simulated scenario without data gaps by taking dense, homogenously distributed profiles into account and (2 two real data scenarios on 1 July 2008 and 1 July 2012 including sparsely, inhomogeneously distributed F3/C EDPs. Moderate correlations between hmF2 and HF2 as
Energy Technology Data Exchange (ETDEWEB)
Abd El-Moneim, Amin, E-mail: aminabdelmoneim@hotmail.com
2016-04-15
Correlation between room temperature ultrasonic attenuation coefficient and the most significant structural parameters has been studied in the bioactive silica based glasses, for the first time. The correlation has been carried out in the quaternary SiO{sub 2}–Na{sub 2}O–CaO–P{sub 2}O{sub 5} glass system using the two semi-empirical formulas, which have been presented recently by the author. Changes in the elastic properties, related to the substitution of SiO{sub 2} by alkali Na{sub 2}O and alkaline earth CaO oxides, have also been deduced by evaluating the mean atomic volume, packing density, fractal bond connectivity and density of the analogous crystalline structure. Furthermore, values of the theoretical elastic moduli have been calculated on the basis of Makishima-Mackenzie theory and compared with the corresponding observed values. Results show that the correlation between ultrasonic attenuation coefficient and the oxygen density, average atomic ring size, first-order stretching force constant and experimental bulk modulus was achieved at 5 MHz frequency. Values of the theoretically calculated shear modulus are in excellent correlation (C. R. ≻95%) with the corresponding experimental ones. The divergence between the theoretical and experimental values of bulk modulus has been discussed. - Highlights: • Abd El-Moneim model was extended for bioactive glasses. • Ultrasonic attenuation was correlated with structural parameters. • Correlation was carried out in Si–Na–Ca–P glasses. • The model is valid for all investigated glass samples. • Agreement between theoretical and experimental elastic moduli was studied.