Relationship between the Wigner function and the probability density function in quantum phase space representation

International Nuclear Information System (INIS)

Li Qianshu; Lue Liqiang; Wei Gongmin

2004-01-01

This paper discusses the relationship between the Wigner function, along with other related quasiprobability distribution functions, and the probability density distribution function constructed from the wave function of the Schroedinger equation in quantum phase space, as formulated by Torres-Vega and Frederick (TF). At the same time, a general approach in solving the wave function of the Schroedinger equation of TF quantum phase space theory is proposed. The relationship of the wave functions between the TF quantum phase space representation and the coordinate or momentum representation is thus revealed

Noise-level determination for discrete spectra with Gaussian or Lorentzian probability density functions

International Nuclear Information System (INIS)

Moriya, Netzer

2010-01-01

A method, based on binomial filtering, to estimate the noise level of an arbitrary, smoothed pure signal, contaminated with an additive, uncorrelated noise component is presented. If the noise characteristics of the experimental spectrum are known, as for instance the type of the corresponding probability density function (e.g., Gaussian), the noise properties can be extracted. In such cases, both the noise level, as may arbitrarily be defined, and a simulated white noise component can be generated, such that the simulated noise component is statistically indistinguishable from the true noise component present in the original signal. In this paper we present a detailed analysis of the noise level extraction when the additive noise is Gaussian or Lorentzian. We show that the statistical parameters in these cases (mainly the variance and the half width at half maximum, respectively) can directly be obtained from the experimental spectrum even when the pure signal is erratic. Further discussion is given for cases where the noise probability density function is initially unknown.

Probability densities and the radon variable transformation theorem

International Nuclear Information System (INIS)

Ramshaw, J.D.

1985-01-01

D. T. Gillespie recently derived a random variable transformation theorem relating to the joint probability densities of functionally dependent sets of random variables. The present author points out that the theorem can be derived as an immediate corollary of a simpler and more fundamental relation. In this relation the probability density is represented as a delta function averaged over an unspecified distribution of unspecified internal random variables. The random variable transformation is derived from this relation

Continuation of probability density functions using a generalized Lyapunov approach

Energy Technology Data Exchange (ETDEWEB)

Baars, S., E-mail: s.baars@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Viebahn, J.P., E-mail: viebahn@cwi.nl [Centrum Wiskunde & Informatica (CWI), P.O. Box 94079, 1090 GB, Amsterdam (Netherlands); Mulder, T.E., E-mail: t.e.mulder@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); Kuehn, C., E-mail: ckuehn@ma.tum.de [Technical University of Munich, Faculty of Mathematics, Boltzmannstr. 3, 85748 Garching bei München (Germany); Wubs, F.W., E-mail: f.w.wubs@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Dijkstra, H.A., E-mail: h.a.dijkstra@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY (United States)

2017-05-01

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is the efficient solution of a generalized Lyapunov equation using an iterative method involving low-rank approximations. We apply and illustrate the capabilities of the method using a problem in physical oceanography, i.e. the occurrence of multiple steady states of the Atlantic Ocean circulation.

Probability density function method for variable-density pressure-gradient-driven turbulence and mixing

International Nuclear Information System (INIS)

Bakosi, Jozsef; Ristorcelli, Raymond J.

2010-01-01

Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.

Interactive design of probability density functions for shape grammars

KAUST Repository

Dang, Minh

2015-11-02

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (pdf) over such a shape space and to sample models according to the designed pdf. First, we propose a user interface that enables a user to quickly provide preference scores for selected shapes and suggest sampling strategies to decide which models to present to the user to evaluate. Second, we propose a novel kernel function to encode the similarity between two procedural models. Third, we propose a framework to interpolate user preference scores by combining multiple techniques: function factorization, Gaussian process regression, autorelevance detection, and l1 regularization. Fourth, we modify the original grammars to generate models with a pdf proportional to the user preference scores. Finally, we provide evaluations of our user interface and framework parameters and a comparison to other exploratory modeling techniques using modeling tasks in five example shape spaces: furniture, low-rise buildings, skyscrapers, airplanes, and vegetation.

Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

Science.gov (United States)

Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

2014-01-01

Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

Probability density functions for CP-violating rephasing invariants

Science.gov (United States)

Fortin, Jean-François; Giasson, Nicolas; Marleau, Luc

2018-05-01

The implications of the anarchy principle on CP violation in the lepton sector are investigated. A systematic method is introduced to compute the probability density functions for the CP-violating rephasing invariants of the PMNS matrix from the Haar measure relevant to the anarchy principle. Contrary to the CKM matrix which is hierarchical, it is shown that the Haar measure, and hence the anarchy principle, are very likely to lead to the observed PMNS matrix. Predictions on the CP-violating Dirac rephasing invariant |jD | and Majorana rephasing invariant |j1 | are also obtained. They correspond to 〈 |jD | 〉 Haar = π / 105 ≈ 0.030 and 〈 |j1 | 〉 Haar = 1 / (6 π) ≈ 0.053 respectively, in agreement with the experimental hint from T2K of | jDexp | ≈ 0.032 ± 0.005 (or ≈ 0.033 ± 0.003) for the normal (or inverted) hierarchy.

Stochastic chaos induced by diffusion processes with identical spectral density but different probability density functions.

Science.gov (United States)

Lei, Youming; Zheng, Fan

2016-12-01

Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.

Exact joint density-current probability function for the asymmetric exclusion process.

Science.gov (United States)

Depken, Martin; Stinchcombe, Robin

2004-07-23

We study the asymmetric simple exclusion process with open boundaries and derive the exact form of the joint probability function for the occupation number and the current through the system. We further consider the thermodynamic limit, showing that the resulting distribution is non-Gaussian and that the density fluctuations have a discontinuity at the continuous phase transition, while the current fluctuations are continuous. The derivations are performed by using the standard operator algebraic approach and by the introduction of new operators satisfying a modified version of the original algebra. Copyright 2004 The American Physical Society

Spatial correlations and probability density function of the phase difference in a developed speckle-field: numerical and natural experiments

International Nuclear Information System (INIS)

Mysina, N Yu; Maksimova, L A; Ryabukho, V P; Gorbatenko, B B

2015-01-01

Investigated are statistical properties of the phase difference of oscillations in speckle-fields at two points in the far-field diffraction region, with different shapes of the scatterer aperture. Statistical and spatial nonuniformity of the probability density function of the field phase difference is established. Numerical experiments show that, for the speckle-fields with an oscillating alternating-sign transverse correlation function, a significant nonuniformity of the probability density function of the phase difference in the correlation region of the field complex amplitude, with the most probable values 0 and p, is observed. A natural statistical interference experiment using Young diagrams has confirmed the results of numerical experiments. (laser applications and other topics in quantum electronics)

Interactive design of probability density functions for shape grammars

KAUST Repository

Dang, Minh; Lienhard, Stefan; Ceylan, Duygu; Neubert, Boris; Wonka, Peter; Pauly, Mark

2015-01-01

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density

Dictionary-Based Stochastic Expectation–Maximization for SAR Amplitude Probability Density Function Estimation

OpenAIRE

Moser , Gabriele; Zerubia , Josiane; Serpico , Sebastiano B.

2006-01-01

International audience; In remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of the pixel intensities. This paper deals with the problem of probability density function (pdf) estimation in the context of synthetic aperture radar (SAR) amplitude data analysis. Several theoretical and heuristic models for the pdfs of SAR data have been proposed in the literature, which have been proved to be effective for different land-cov...

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

A new formulation of the probability density function in random walk models for atmospheric dispersion

DEFF Research Database (Denmark)

Falk, Anne Katrine Vinther; Gryning, Sven-Erik

1997-01-01

In this model for atmospheric dispersion particles are simulated by the Langevin Equation, which is a stochastic differential equation. It uses the probability density function (PDF) of the vertical velocity fluctuations as input. The PDF is constructed as an expansion after Hermite polynomials...

Probability density function evolution of power systems subject to stochastic variation of renewable energy

Science.gov (United States)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Generalized Probability Functions

Directory of Open Access Journals (Sweden)

Alexandre Souto Martinez

2009-01-01

Full Text Available From the integration of nonsymmetrical hyperboles, a one-parameter generalization of the logarithmic function is obtained. Inverting this function, one obtains the generalized exponential function. Motivated by the mathematical curiosity, we show that these generalized functions are suitable to generalize some probability density functions (pdfs. A very reliable rank distribution can be conveniently described by the generalized exponential function. Finally, we turn the attention to the generalization of one- and two-tail stretched exponential functions. We obtain, as particular cases, the generalized error function, the Zipf-Mandelbrot pdf, the generalized Gaussian and Laplace pdf. Their cumulative functions and moments were also obtained analytically.

TRACING OUTFLOWS AND ACCRETION: A BIMODAL AZIMUTHAL DEPENDENCE OF Mg II ABSORPTION

International Nuclear Information System (INIS)

Kacprzak, Glenn G.; Churchill, Christopher W.; Nielsen, Nikole M.

2012-01-01

We report a bimodality in the azimuthal angle distribution of gas around galaxies as traced by Mg II absorption: halo gas prefers to exist near the projected galaxy major and minor axes. The bimodality is demonstrated by computing the mean azimuthal angle probability distribution function using 88 spectroscopically confirmed Mg II-absorption-selected galaxies [W r (2796) ≥ 0.1 Å] and 35 spectroscopically confirmed non-absorbing galaxies [W r (2796) r (2796) r (2796) distribution for gas along the major axis is likely skewed toward weaker Mg II absorption than for gas along the projected minor axis. These combined results are highly suggestive that the bimodality is driven by gas accreted along the galaxy major axis and outflowing along the galaxy minor axis. Adopting these assumptions, we find that the opening angle of outflows and inflows to be 100° and 40°, respectively. We find that the probability of detecting outflows is ∼60%, implying that winds are more commonly observed.

Charged-particle thermonuclear reaction rates: II. Tables and graphs of reaction rates and probability density functions

International Nuclear Information System (INIS)

Iliadis, C.; Longland, R.; Champagne, A.E.; Coc, A.; Fitzgerald, R.

2010-01-01

Numerical values of charged-particle thermonuclear reaction rates for nuclei in the A=14 to 40 region are tabulated. The results are obtained using a method, based on Monte Carlo techniques, that has been described in the preceding paper of this issue (Paper I). We present a low rate, median rate and high rate which correspond to the 0.16, 0.50 and 0.84 quantiles, respectively, of the cumulative reaction rate distribution. The meaning of these quantities is in general different from the commonly reported, but statistically meaningless expressions, 'lower limit', 'nominal value' and 'upper limit' of the total reaction rate. In addition, we approximate the Monte Carlo probability density function of the total reaction rate by a lognormal distribution and tabulate the lognormal parameters μ and σ at each temperature. We also provide a quantitative measure (Anderson-Darling test statistic) for the reliability of the lognormal approximation. The user can implement the approximate lognormal reaction rate probability density functions directly in a stellar model code for studies of stellar energy generation and nucleosynthesis. For each reaction, the Monte Carlo reaction rate probability density functions, together with their lognormal approximations, are displayed graphically for selected temperatures in order to provide a visual impression. Our new reaction rates are appropriate for bare nuclei in the laboratory. The nuclear physics input used to derive our reaction rates is presented in the subsequent paper of this issue (Paper III). In the fourth paper of this issue (Paper IV) we compare our new reaction rates to previous results.

Estimating the population size and colony boundary of subterranean termites by using the density functions of directionally averaged capture probability.

Science.gov (United States)

Su, Nan-Yao; Lee, Sang-Hee

2008-04-01

Marked termites were released in a linear-connected foraging arena, and the spatial heterogeneity of their capture probabilities was averaged for both directions at distance r from release point to obtain a symmetrical distribution, from which the density function of directionally averaged capture probability P(x) was derived. We hypothesized that as marked termites move into the population and given sufficient time, the directionally averaged capture probability may reach an equilibrium P(e) over the distance r and thus satisfy the equal mixing assumption of the mark-recapture protocol. The equilibrium capture probability P(e) was used to estimate the population size N. The hypothesis was tested in a 50-m extended foraging arena to simulate the distance factor of field colonies of subterranean termites. Over the 42-d test period, the density functions of directionally averaged capture probability P(x) exhibited four phases: exponential decline phase, linear decline phase, equilibrium phase, and postequilibrium phase. The equilibrium capture probability P(e), derived as the intercept of the linear regression during the equilibrium phase, correctly projected N estimates that were not significantly different from the known number of workers in the arena. Because the area beneath the probability density function is a constant (50% in this study), preequilibrium regression parameters and P(e) were used to estimate the population boundary distance 1, which is the distance between the release point and the boundary beyond which the population is absent.

Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures

Science.gov (United States)

Liu, Zhangjun; Liu, Zenghui

2018-06-01

This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.

Estimating reliability of degraded system based on the probability density evolution with multi-parameter

Directory of Open Access Journals (Sweden)

Jiang Ge

2017-01-01

Full Text Available System degradation was usually caused by multiple-parameter degradation. The assessment result of system reliability by universal generating function was low accurate when compared with the Monte Carlo simulation. And the probability density function of the system output performance cannot be got. So the reliability assessment method based on the probability density evolution with multi-parameter was presented for complexly degraded system. Firstly, the system output function was founded according to the transitive relation between component parameters and the system output performance. Then, the probability density evolution equation based on the probability conservation principle and the system output function was established. Furthermore, probability distribution characteristics of the system output performance was obtained by solving differential equation. Finally, the reliability of the degraded system was estimated. This method did not need to discrete the performance parameters and can establish continuous probability density function of the system output performance with high calculation efficiency and low cost. Numerical example shows that this method is applicable to evaluate the reliability of multi-parameter degraded system.

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

OpenAIRE

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2010-01-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth & Pope with Durbin's method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous ...

Using Prediction Markets to Generate Probability Density Functions for Climate Change Risk Assessment

Science.gov (United States)

Boslough, M.

2011-12-01

Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based

Exact probability function for bulk density and current in the asymmetric exclusion process

Science.gov (United States)

Depken, Martin; Stinchcombe, Robin

2005-03-01

We examine the asymmetric simple exclusion process with open boundaries, a paradigm of driven diffusive systems, having a nonequilibrium steady-state transition. We provide a full derivation and expanded discussion and digression on results previously reported briefly in M. Depken and R. Stinchcombe, Phys. Rev. Lett. 93, 040602 (2004). In particular we derive an exact form for the joint probability function for the bulk density and current, both for finite systems, and also in the thermodynamic limit. The resulting distribution is non-Gaussian, and while the fluctuations in the current are continuous at the continuous phase transitions, the density fluctuations are discontinuous. The derivations are done by using the standard operator algebraic techniques and by introducing a modified version of the original operator algebra. As a by-product of these considerations we also arrive at a very simple way of calculating the normalization constant appearing in the standard treatment with the operator algebra. Like the partition function in equilibrium systems, this normalization constant is shown to completely characterize the fluctuations, albeit in a very different manner.

Continuous time random walk model with asymptotical probability density of waiting times via inverse Mittag-Leffler function

Science.gov (United States)

Liang, Yingjie; Chen, Wen

2018-04-01

The mean squared displacement (MSD) of the traditional ultraslow diffusion is a logarithmic function of time. Recently, the continuous time random walk model is employed to characterize this ultraslow diffusion dynamics by connecting the heavy-tailed logarithmic function and its variation as the asymptotical waiting time density. In this study we investigate the limiting waiting time density of a general ultraslow diffusion model via the inverse Mittag-Leffler function, whose special case includes the traditional logarithmic ultraslow diffusion model. The MSD of the general ultraslow diffusion model is analytically derived as an inverse Mittag-Leffler function, and is observed to increase even more slowly than that of the logarithmic function model. The occurrence of very long waiting time in the case of the inverse Mittag-Leffler function has the largest probability compared with the power law model and the logarithmic function model. The Monte Carlo simulations of one dimensional sample path of a single particle are also performed. The results show that the inverse Mittag-Leffler waiting time density is effective in depicting the general ultraslow random motion.

Probability Density Function Method for Observing Reconstructed Attractor Structure

Institute of Scientific and Technical Information of China (English)

陆宏伟; 陈亚珠; 卫青

2004-01-01

Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men. PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor. To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure. Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6 - 6.5 dimensional complex dynamical systems. It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough. A cluster effect mechanism is presented to explain this phenomenon. By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated. Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.

Quantum probability measures and tomographic probability densities

NARCIS (Netherlands)

Amosov, GG; Man'ko, [No Value

2004-01-01

Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

Science.gov (United States)

Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

2005-01-01

The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

Probability function of breaking-limited surface elevation. [wind generated waves of ocean

Science.gov (United States)

Tung, C. C.; Huang, N. E.; Yuan, Y.; Long, S. R.

1989-01-01

The effect of wave breaking on the probability function of surface elevation is examined. The surface elevation limited by wave breaking zeta sub b(t) is first related to the original wave elevation zeta(t) and its second derivative. An approximate, second-order, nonlinear, non-Gaussian model for zeta(t) of arbitrary but moderate bandwidth is presented, and an expression for the probability density function zeta sub b(t) is derived. The results show clearly that the effect of wave breaking on the probability density function of surface elevation is to introduce a secondary hump on the positive side of the probability density function, a phenomenon also observed in wind wave tank experiments.

Probability density functions of photochemicals over a coastal area of Northern Italy

International Nuclear Information System (INIS)

Georgiadis, T.; Fortezza, F.; Alberti, L.; Strocchi, V.; Marani, A.; Dal Bo', G.

1998-01-01

The present paper surveys the findings of experimental studies and analyses of statistical probability density functions (PDFs) applied to air pollutant concentrations to provide an interpretation of the ground-level distributions of photochemical oxidants in the coastal area of Ravenna (Italy). The atmospheric-pollution data set was collected from the local environmental monitoring network for the period 1978-1989. Results suggest that the statistical distribution of surface ozone, once normalised over the solar radiation PDF for the whole measurement period, follows a log-normal law as found for other pollutants. Although the Weibull distribution also offers a good fit of the experimental data, the area's meteorological features seem to favour the former distribution once the statistical index estimates have been analysed. Local transport phenomena are discussed to explain the data tail trends

Fusing probability density function into Dempster-Shafer theory of evidence for the evaluation of water treatment plant.

Science.gov (United States)

Chowdhury, Shakhawat

2013-05-01

The evaluation of the status of a municipal drinking water treatment plant (WTP) is important. The evaluation depends on several factors, including, human health risks from disinfection by-products (R), disinfection performance (D), and cost (C) of water production and distribution. The Dempster-Shafer theory (DST) of evidence can combine the individual status with respect to R, D, and C to generate a new indicator, from which the overall status of a WTP can be evaluated. In the DST, the ranges of different factors affecting the overall status are divided into several segments. The basic probability assignments (BPA) for each segment of these factors are provided by multiple experts, which are then combined to obtain the overall status. In assigning the BPA, the experts use their individual judgments, which can impart subjective biases in the overall evaluation. In this research, an approach has been introduced to avoid the assignment of subjective BPA. The factors contributing to the overall status were characterized using the probability density functions (PDF). The cumulative probabilities for different segments of these factors were determined from the cumulative density function, which were then assigned as the BPA for these factors. A case study is presented to demonstrate the application of PDF in DST to evaluate a WTP, leading to the selection of the required level of upgradation for the WTP.

The non-Gaussian joint probability density function of slope and elevation for a nonlinear gravity wave field. [in ocean surface

Science.gov (United States)

Huang, N. E.; Long, S. R.; Bliven, L. F.; Tung, C.-C.

1984-01-01

On the basis of the mapping method developed by Huang et al. (1983), an analytic expression for the non-Gaussian joint probability density function of slope and elevation for nonlinear gravity waves is derived. Various conditional and marginal density functions are also obtained through the joint density function. The analytic results are compared with a series of carefully controlled laboratory observations, and good agreement is noted. Furthermore, the laboratory wind wave field observations indicate that the capillary or capillary-gravity waves may not be the dominant components in determining the total roughness of the wave field. Thus, the analytic results, though derived specifically for the gravity waves, may have more general applications.

Statistical tests for whether a given set of independent, identically distributed draws comes from a specified probability density.

Science.gov (United States)

Tygert, Mark

2010-09-21

We discuss several tests for determining whether a given set of independent and identically distributed (i.i.d.) draws does not come from a specified probability density function. The most commonly used are Kolmogorov-Smirnov tests, particularly Kuiper's variant, which focus on discrepancies between the cumulative distribution function for the specified probability density and the empirical cumulative distribution function for the given set of i.i.d. draws. Unfortunately, variations in the probability density function often get smoothed over in the cumulative distribution function, making it difficult to detect discrepancies in regions where the probability density is small in comparison with its values in surrounding regions. We discuss tests without this deficiency, complementing the classical methods. The tests of the present paper are based on the plain fact that it is unlikely to draw a random number whose probability is small, provided that the draw is taken from the same distribution used in calculating the probability (thus, if we draw a random number whose probability is small, then we can be confident that we did not draw the number from the same distribution used in calculating the probability).

Assumed Probability Density Functions for Shallow and Deep Convection

Directory of Open Access Journals (Sweden)

Steven K Krueger

2010-10-01

Full Text Available The assumed joint probability density function (PDF between vertical velocity and conserved temperature and total water scalars has been suggested to be a relatively computationally inexpensive and unified subgrid-scale (SGS parameterization for boundary layer clouds and turbulent moments. This paper analyzes the performance of five families of PDFs using large-eddy simulations of deep convection, shallow convection, and a transition from stratocumulus to trade wind cumulus. Three of the PDF families are based on the double Gaussian form and the remaining two are the single Gaussian and a Double Delta Function (analogous to a mass flux model. The assumed PDF method is tested for grid sizes as small as 0.4 km to as large as 204.8 km. In addition, studies are performed for PDF sensitivity to errors in the input moments and for how well the PDFs diagnose some higher-order moments. In general, the double Gaussian PDFs more accurately represent SGS cloud structure and turbulence moments in the boundary layer compared to the single Gaussian and Double Delta Function PDFs for the range of grid sizes tested. This is especially true for small SGS cloud fractions. While the most complex PDF, Lewellen-Yoh, better represents shallow convective cloud properties (cloud fraction and liquid water mixing ratio compared to the less complex Analytic Double Gaussian 1 PDF, there appears to be no advantage in implementing Lewellen-Yoh for deep convection. However, the Analytic Double Gaussian 1 PDF better represents the liquid water flux, is less sensitive to errors in the input moments, and diagnoses higher order moments more accurately. Between the Lewellen-Yoh and Analytic Double Gaussian 1 PDFs, it appears that neither family is distinctly better at representing cloudy layers. However, due to the reduced computational cost and fairly robust results, it appears that the Analytic Double Gaussian 1 PDF could be an ideal family for SGS cloud and turbulence

Protein single-model quality assessment by feature-based probability density functions.

Science.gov (United States)

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Calculation of probability density functions for temperature and precipitation change under global warming

International Nuclear Information System (INIS)

Watterson, Ian G.

2007-01-01

Full text: he IPCC Fourth Assessment Report (Meehl ef al. 2007) presents multi-model means of the CMIP3 simulations as projections of the global climate change over the 21st century under several SRES emission scenarios. To assess the possible range of change for Australia based on the CMIP3 ensemble, we can follow Whetton etal. (2005) and use the 'pattern scaling' approach, which separates the uncertainty in the global mean warming from that in the local change per degree of warming. This study presents several ways of representing these two factors as probability density functions (PDFs). The beta distribution, a smooth, bounded, function allowing skewness, is found to provide a useful representation of the range of CMIP3 results. A weighting of models based on their skill in simulating seasonal means in the present climate over Australia is included. Dessai ef al. (2005) and others have used Monte-Carlo sampling to recombine such global warming and scaled change factors into values of net change. Here, we use a direct integration of the product across the joint probability space defined by the two PDFs. The result is a cumulative distribution function (CDF) for change, for each variable, location, and season. The median of this distribution provides a best estimate of change, while the 10th and 90th percentiles represent a likely range. The probability of exceeding a specified threshold can also be extracted from the CDF. The presentation focuses on changes in Australian temperature and precipitation at 2070 under the A1B scenario. However, the assumption of linearity behind pattern scaling allows results for different scenarios and times to be simply obtained. In the case of precipitation, which must remain non-negative, a simple modification of the calculations (based on decreases being exponential with warming) is used to avoid unrealistic results. These approaches are currently being used for the new CSIRO/ Bureau of Meteorology climate projections

Probability Density Estimation Using Neural Networks in Monte Carlo Calculations

International Nuclear Information System (INIS)

Shim, Hyung Jin; Cho, Jin Young; Song, Jae Seung; Kim, Chang Hyo

2008-01-01

The Monte Carlo neutronics analysis requires the capability for a tally distribution estimation like an axial power distribution or a flux gradient in a fuel rod, etc. This problem can be regarded as a probability density function estimation from an observation set. We apply the neural network based density estimation method to an observation and sampling weight set produced by the Monte Carlo calculations. The neural network method is compared with the histogram and the functional expansion tally method for estimating a non-smooth density, a fission source distribution, and an absorption rate's gradient in a burnable absorber rod. The application results shows that the neural network method can approximate a tally distribution quite well. (authors)

Functionalized bimodal mesoporous silicas as carriers for controlled aspirin delivery

Science.gov (United States)

Gao, Lin; Sun, Jihong; Li, Yuzhen

2011-08-01

The bimodal mesoporous silica modified with 3-aminopropyltriethoxysilane was performed as the aspirin carrier. The samples' structure, drug loading and release profiles were characterized with X-ray diffraction, scanning electron microscopy, N 2 adsorption and desorption, Fourier transform infrared spectroscopy, TG analysis, elemental analysis and UV-spectrophotometer. For further exploring the effects of the bimodal mesopores on the drug delivery behavior, the unimodal mesoporous material MCM-41 was also modified as the aspirin carrier. Meantime, Korsmeyer-Peppas equation ft= ktn was employed to analyze the dissolution data in details. It is indicated that the bimodal mesopores are beneficial for unrestricted drug molecules diffusing and therefore lead to a higher loading and faster releasing than that of MCM-41. The results show that the aspirin delivery properties are influenced considerably by the mesoporous matrix, whereas the large pore of bimodal mesoporous silica is the key point for the improved controlled-release properties.

Multiple model cardinalized probability hypothesis density filter

Science.gov (United States)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Functionalized bimodal mesoporous silicas as carriers for controlled aspirin delivery

International Nuclear Information System (INIS)

Gao Lin; Sun Jihong; Li Yuzhen

2011-01-01

The bimodal mesoporous silica modified with 3-aminopropyltriethoxysilane was performed as the aspirin carrier. The samples' structure, drug loading and release profiles were characterized with X-ray diffraction, scanning electron microscopy, N 2 adsorption and desorption, Fourier transform infrared spectroscopy, TG analysis, elemental analysis and UV-spectrophotometer. For further exploring the effects of the bimodal mesopores on the drug delivery behavior, the unimodal mesoporous material MCM-41 was also modified as the aspirin carrier. Meantime, Korsmeyer-Peppas equation f t =kt n was employed to analyze the dissolution data in details. It is indicated that the bimodal mesopores are beneficial for unrestricted drug molecules diffusing and therefore lead to a higher loading and faster releasing than that of MCM-41. The results show that the aspirin delivery properties are influenced considerably by the mesoporous matrix, whereas the large pore of bimodal mesoporous silica is the key point for the improved controlled-release properties. - Graphical abstract: Loading (A) and release profiles (B) of aspirin in N-BMMs and N-MCM-41 indicated that BMMs have more drug loading capacity and faster release rate than that MCM-41. Highlights: → Bimodal mesoporous silicas (BMMs) and MCM-41 modified with amino group via post-treatment procedure. → Loading and release profiles of aspirin in modified BMMs and MCM-41. → Modified BMMs have more drug loading capacity and faster release rate than that modified MCM-41.

Development and evaluation of probability density functions for a set of human exposure factors

Energy Technology Data Exchange (ETDEWEB)

Maddalena, R.L.; McKone, T.E.; Bodnar, A.; Jacobson, J.

1999-06-01

The purpose of this report is to describe efforts carried out during 1998 and 1999 at the Lawrence Berkeley National Laboratory to assist the U.S. EPA in developing and ranking the robustness of a set of default probability distributions for exposure assessment factors. Among the current needs of the exposure-assessment community is the need to provide data for linking exposure, dose, and health information in ways that improve environmental surveillance, improve predictive models, and enhance risk assessment and risk management (NAS, 1994). The U.S. Environmental Protection Agency (EPA) Office of Emergency and Remedial Response (OERR) plays a lead role in developing national guidance and planning future activities that support the EPA Superfund Program. OERR is in the process of updating its 1989 Risk Assessment Guidance for Superfund (RAGS) as part of the EPA Superfund reform activities. Volume III of RAGS, when completed in 1999 will provide guidance for conducting probabilistic risk assessments. This revised document will contain technical information including probability density functions (PDFs) and methods used to develop and evaluate these PDFs. The PDFs provided in this EPA document are limited to those relating to exposure factors.

Development and evaluation of probability density functions for a set of human exposure factors

International Nuclear Information System (INIS)

Maddalena, R.L.; McKone, T.E.; Bodnar, A.; Jacobson, J.

1999-01-01

The purpose of this report is to describe efforts carried out during 1998 and 1999 at the Lawrence Berkeley National Laboratory to assist the U.S. EPA in developing and ranking the robustness of a set of default probability distributions for exposure assessment factors. Among the current needs of the exposure-assessment community is the need to provide data for linking exposure, dose, and health information in ways that improve environmental surveillance, improve predictive models, and enhance risk assessment and risk management (NAS, 1994). The U.S. Environmental Protection Agency (EPA) Office of Emergency and Remedial Response (OERR) plays a lead role in developing national guidance and planning future activities that support the EPA Superfund Program. OERR is in the process of updating its 1989 Risk Assessment Guidance for Superfund (RAGS) as part of the EPA Superfund reform activities. Volume III of RAGS, when completed in 1999 will provide guidance for conducting probabilistic risk assessments. This revised document will contain technical information including probability density functions (PDFs) and methods used to develop and evaluate these PDFs. The PDFs provided in this EPA document are limited to those relating to exposure factors

Superthermal photon bunching in terms of simple probability distributions

Science.gov (United States)

Lettau, T.; Leymann, H. A. M.; Melcher, B.; Wiersig, J.

2018-05-01

We analyze the second-order photon autocorrelation function g(2 ) with respect to the photon probability distribution and discuss the generic features of a distribution that results in superthermal photon bunching [g(2 )(0 ) >2 ]. Superthermal photon bunching has been reported for a number of optical microcavity systems that exhibit processes such as superradiance or mode competition. We show that a superthermal photon number distribution cannot be constructed from the principle of maximum entropy if only the intensity and the second-order autocorrelation are given. However, for bimodal systems, an unbiased superthermal distribution can be constructed from second-order correlations and the intensities alone. Our findings suggest modeling superthermal single-mode distributions by a mixture of a thermal and a lasinglike state and thus reveal a generic mechanism in the photon probability distribution responsible for creating superthermal photon bunching. We relate our general considerations to a physical system, i.e., a (single-emitter) bimodal laser, and show that its statistics can be approximated and understood within our proposed model. Furthermore, the excellent agreement of the statistics of the bimodal laser and our model reveals that the bimodal laser is an ideal source of bunched photons, in the sense that it can generate statistics that contain no other features but the superthermal bunching.

TRACING OUTFLOWS AND ACCRETION: A BIMODAL AZIMUTHAL DEPENDENCE OF Mg II ABSORPTION

Energy Technology Data Exchange (ETDEWEB)

Kacprzak, Glenn G. [Swinburne University of Technology, Victoria 3122 (Australia); Churchill, Christopher W.; Nielsen, Nikole M., E-mail: gkacprzak@astro.swin.edu.au [New Mexico State University, Las Cruces, NM 88003 (United States)

2012-11-20

We report a bimodality in the azimuthal angle distribution of gas around galaxies as traced by Mg II absorption: halo gas prefers to exist near the projected galaxy major and minor axes. The bimodality is demonstrated by computing the mean azimuthal angle probability distribution function using 88 spectroscopically confirmed Mg II-absorption-selected galaxies [W{sub r} (2796) {>=} 0.1 A] and 35 spectroscopically confirmed non-absorbing galaxies [W{sub r} (2796) < 0.1 A] imaged with Hubble Space Telescope and Sloan Digital Sky Survey. The azimuthal angle distribution for non-absorbers is flat, indicating no azimuthal preference for gas characterized by W{sub r} (2796) < 0.1 A. We find that blue star-forming galaxies clearly drive the bimodality while red passive galaxies may exhibit an excess along their major axis. These results are consistent with galaxy evolution scenarios where star-forming galaxies accrete new gas, forming new stars and producing winds, while red galaxies exist passively due to reduced gas reservoirs. We further compute an azimuthal angle dependent Mg II absorption covering fraction, which is enhanced by as much as 20%-30% along the major and minor axes. The W{sub r} (2796) distribution for gas along the major axis is likely skewed toward weaker Mg II absorption than for gas along the projected minor axis. These combined results are highly suggestive that the bimodality is driven by gas accreted along the galaxy major axis and outflowing along the galaxy minor axis. Adopting these assumptions, we find that the opening angle of outflows and inflows to be 100 Degree-Sign and 40 Degree-Sign , respectively. We find that the probability of detecting outflows is {approx}60%, implying that winds are more commonly observed.

Tribological properties and morphology of bimodal elastomeric nitrile butadiene rubber networks

International Nuclear Information System (INIS)

Guo, Yin; Wang, Jiaxu; Li, Kang; Ding, Xingwu

2013-01-01

Highlights: • Bimodal elastomeric NBR as a new material was developed. • The structure of bimodal elastomeric NBR networks was determined. • The relationship between structure and mechanical properties was investigated. • The tribological properties and mechanisms of bimodal NBR were analyzed. • The benefits of bimodal NBR in the field of tribology were discussed. - Abstract: Bimodal nitrile butadiene rubber (NBR) was examined in this study. The molecular structure was determined by dynamic mechanical analysis and transmission electron microscopy. The relationship between the structure and the mechanical properties related to elastomeric tribological properties was investigated. The properties and the mechanisms of friction and wear of bimodal elastomeric NBR networks were also analyzed. The lubricating characteristics of bimodal NBR networks were revealed based on the mechanisms of friction and wear. Results show that bimodal NBR networks are similar to bimodal polydimethylsiloxane networks. The form and density of the network structure can be controlled from elastomeric networks to thermosetting resin networks. The mechanical properties of bimodal NBR networks, such as elasticity, elongation at break, fatigue characteristic, tensile strength, elastic modulus, and thermal stability can be precisely controlled following the variation in network structure. The friction, wear, and lubrication of bimodal NBR networks can be clearly described according to the principles of tribology. Common elastomers cannot simultaneously reduce friction and wear because of the different mechanisms of friction and wear; however, bimodal elastomer networks can efficiently address this problem

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo [Div. of Mechanical Engineering, Ajou University, Suwon (Korea, Republic of)

2016-10-15

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

International Nuclear Information System (INIS)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo

2016-01-01

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage

Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Jong Kyeom Lee

2016-10-01

Full Text Available This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Time-averaged probability density functions of soot nanoparticles along the centerline of a piloted turbulent diffusion flame using a scanning mobility particle sizer

KAUST Repository

Chowdhury, Snehaunshu; Boyette, Wesley; Roberts, William L.

2017-01-01

In this study, we demonstrate the use of a scanning mobility particle sizer (SMPS) as an effective tool to measure the probability density functions (PDFs) of soot nanoparticles in turbulent flames. Time-averaged soot PDFs necessary for validating

Computing rates of Markov models of voltage-gated ion channels by inverting partial differential equations governing the probability density functions of the conducting and non-conducting states.

Science.gov (United States)

Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew

2016-07-01

Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Postfragmentation density function for bacterial aggregates in laminar flow.

Science.gov (United States)

Byrne, Erin; Dzul, Steve; Solomon, Michael; Younger, John; Bortz, David M

2011-04-01

The postfragmentation probability density of daughter flocs is one of the least well-understood aspects of modeling flocculation. We use three-dimensional positional data of Klebsiella pneumoniae bacterial flocs in suspension and the knowledge of hydrodynamic properties of a laminar flow field to construct a probability density function of floc volumes after a fragmentation event. We provide computational results which predict that the primary fragmentation mechanism for large flocs is erosion. The postfragmentation probability density function has a strong dependence on the size of the original floc and indicates that most fragmentation events result in clumps of one to three bacteria eroding from the original floc. We also provide numerical evidence that exhaustive fragmentation yields a limiting density inconsistent with the log-normal density predicted in the literature, most likely due to the heterogeneous nature of K. pneumoniae flocs. To support our conclusions, artificial flocs were generated and display similar postfragmentation density and exhaustive fragmentation. ©2011 American Physical Society

Evaluation of Presumed Probability-Density-Function Models in Non-Premixed Flames by using Large Eddy Simulation

International Nuclear Information System (INIS)

Cao Hong-Jun; Zhang Hui-Qiang; Lin Wen-Yi

2012-01-01

Four kinds of presumed probability-density-function (PDF) models for non-premixed turbulent combustion are evaluated in flames with various stoichiometric mixture fractions by using large eddy simulation (LES). The LES code is validated by the experimental data of a classical turbulent jet flame (Sandia flame D). The mean and rms temperatures obtained by the presumed PDF models are compared with the LES results. The β-function model achieves a good prediction for different flames. The predicted rms temperature by using the double-δ function model is very small and unphysical in the vicinity of the maximum mean temperature. The clip-Gaussian model and the multi-δ function model make a worse prediction of the extremely fuel-rich or fuel-lean side due to the clip at the boundary of the mixture fraction space. The results also show that the overall prediction performance of presumed PDF models is better at mediate stoichiometric mixture fractions than that at very small or very large ones. (fundamental areas of phenomenology(including applications))

Far-from-Equilibrium Route to Superthermal Light in Bimodal Nanolasers

Directory of Open Access Journals (Sweden)

Mathias Marconi

2018-01-01

Full Text Available Microscale and nanoscale lasers inherently exhibit rich photon statistics due to complex light-matter interaction in a strong spontaneous emission noise background. It is well known that they may display superthermal fluctuations—photon superbunching—in specific situations due to either gain competition, leading to mode-switching instabilities, or carrier-carrier coupling in superradiant microcavities. Here we show a generic route to superbunching in bimodal nanolasers by preparing the system far from equilibrium through a parameter quench. We demonstrate, both theoretically and experimentally, that transient dynamics after a short-pump-pulse-induced quench leads to heavy-tailed superthermal statistics when projected onto the weak mode. We implement a simple experimental technique to access the probability density functions that further enables quantifying the distance from thermal equilibrium via the thermodynamic entropy. The universality of this mechanism relies on the far-from-equilibrium dynamical scenario, which can be mapped to a fast cooling process of a suspension of Brownian particles in a liquid. Our results open up new avenues to mold photon statistics in multimode optical systems and may constitute a test bed to investigate out-of-equilibrium thermodynamics using micro or nanocavity arrays.

Far-from-Equilibrium Route to Superthermal Light in Bimodal Nanolasers

Science.gov (United States)

Marconi, Mathias; Javaloyes, Julien; Hamel, Philippe; Raineri, Fabrice; Levenson, Ariel; Yacomotti, Alejandro M.

2018-02-01

Microscale and nanoscale lasers inherently exhibit rich photon statistics due to complex light-matter interaction in a strong spontaneous emission noise background. It is well known that they may display superthermal fluctuations—photon superbunching—in specific situations due to either gain competition, leading to mode-switching instabilities, or carrier-carrier coupling in superradiant microcavities. Here we show a generic route to superbunching in bimodal nanolasers by preparing the system far from equilibrium through a parameter quench. We demonstrate, both theoretically and experimentally, that transient dynamics after a short-pump-pulse-induced quench leads to heavy-tailed superthermal statistics when projected onto the weak mode. We implement a simple experimental technique to access the probability density functions that further enables quantifying the distance from thermal equilibrium via the thermodynamic entropy. The universality of this mechanism relies on the far-from-equilibrium dynamical scenario, which can be mapped to a fast cooling process of a suspension of Brownian particles in a liquid. Our results open up new avenues to mold photon statistics in multimode optical systems and may constitute a test bed to investigate out-of-equilibrium thermodynamics using micro or nanocavity arrays.

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

International Nuclear Information System (INIS)

Carta, Jose A.; Ramirez, Penelope; Velazquez, Sergio

2008-01-01

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error ε made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R 2 statistic (R a 2 ). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R a 2 statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R a 2 increases

A Balanced Approach to Adaptive Probability Density Estimation

Directory of Open Access Journals (Sweden)

Julio A. Kovacs

2017-04-01

Full Text Available Our development of a Fast (Mutual Information Matching (FIM of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a random variable, especially in cases of very uneven samples. Here, we propose a novel Balanced Adaptive Density Estimation (BADE method that effectively optimizes the amount of smoothing at each point. To do this, BADE relies on an efficient nearest-neighbor search which results in good scaling for large data sizes. Our tests on simulated data show that BADE exhibits equal or better accuracy than existing methods, and visual tests on univariate and bivariate experimental data show that the results are also aesthetically pleasing. This is due in part to the use of a visual criterion for setting the smoothing level of the density estimate. Our results suggest that BADE offers an attractive new take on the fundamental density estimation problem in statistics. We have applied it on molecular dynamics simulations of membrane pore formation. We also expect BADE to be generally useful for low-dimensional applications in other statistical application domains such as bioinformatics, signal processing and econometrics.

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Science.gov (United States)

Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell

2012-01-01

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Solar wind structure suggested by bimodal correlations of solar wind speed and density between the spacecraft SOHO and Wind

Science.gov (United States)

Ogilvie, K. W.; Coplan, M. A.; Roberts, D. A.; Ipavich, F.

2007-08-01

We calculate the cross-spacecraft maximum lagged-cross-correlation coefficients for 2-hour intervals of solar wind speed and density measurements made by the plasma instruments on the Solar and Heliospheric Observatory (SOHO) and Wind spacecraft over the period from 1996, the minimum of solar cycle 23, through the end of 2005. During this period, SOHO was located at L1, about 200 R E upstream from the Earth, while Wind spent most of the time in the interplanetary medium at distances of more than 100 R E from the Earth. Yearly histograms of the maximum, time-lagged correlation coefficients for both the speed and density are bimodal in shape, suggesting the existence of two distinct solar wind regimes. The larger correlation coefficients we suggest are due to structured solar wind, including discontinuities and shocks, while the smaller are likely due to Alfvénic turbulence. While further work will be required to firmly establish the physical nature of the two populations, the results of the analysis are consistent with a solar wind that consists of turbulence from quiet regions of the Sun interspersed with highly filamentary structures largely convected from regions in the inner solar corona. The bimodal appearance of the distributions is less evident in the solar wind speed than in the density correlations, consistent with the observation that the filamentary structures are convected with nearly constant speed by the time they reach 1 AU. We also find that at solar minimum the fits for the density correlations have smaller high-correlation components than at solar maximum. We interpret this as due to the presence of more relatively uniform Alfvénic regions at solar minimum than at solar maximum.

Power probability density function control and performance assessment of a nuclear research reactor

International Nuclear Information System (INIS)

Abharian, Amir Esmaeili; Fadaei, Amir Hosein

2014-01-01

Highlights: • In this paper, the performance assessment of static PDF control system is discussed. • The reactor PDF model is set up based on the B-spline functions. • Acquaints of Nu, and Th-h. equations solve concurrently by reformed Hansen’s method. • A principle of performance assessment is put forward for the PDF of the NR control. - Abstract: One of the main issues in controlling a system is to keep track of the conditions of the system function. The performance condition of the system should be inspected continuously, to keep the system in reliable working condition. In this study, the nuclear reactor is considered as a complicated system and a principle of performance assessment is used for analyzing the performance of the power probability density function (PDF) of the nuclear research reactor control. First, the model of the power PDF is set up, then the controller is designed to make the power PDF for tracing the given shape, that make the reactor to be a closed-loop system. The operating data of the closed-loop reactor are used to assess the control performance with the performance assessment criteria. The modeling, controller design and the performance assessment of the power PDF are all applied to the control of Tehran Research Reactor (TRR) power in a nuclear process. In this paper, the performance assessment of the static PDF control system is discussed, the efficacy and efficiency of the proposed method are investigated, and finally its reliability is proven

Psychophysics of the probability weighting function

Science.gov (United States)

Takahashi, Taiki

2011-03-01

A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(-() (01e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec's probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.

Polyethyleneimine-loaded bimodal porous silica as low-cost and high-capacity sorbent for CO{sub 2} capture

Energy Technology Data Exchange (ETDEWEB)

Witoon, Thongthai, E-mail: fengttwi@ku.ac.th [National Center of Excellence for Petroleum, Petrochemicals and Advance Material, Department of Chemical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900 (Thailand); Center for Advanced Studies in Nanotechnology and Its Applications in Chemical Food and Agricultural Industries, Kasetsart University, Bangkok 10900 (Thailand)

2012-11-15

In this work, bimodal (meso-macro) porous silicas with different mesopore diameters synthesized by using rice husk ash as a low-cost silica source and chitosan as a natural template were used as a polyethyleneimine (PEI) support for CO{sub 2} capture. Unimodal porous silica supports with equivalent mesopore diameters to bimodal porous silica supports have been prepared for purpose of comparison. Effects of different PEI contents (10, 20, 30, 40 and 50 wt%) on CO{sub 2} sorption capacity have been systematically investigated. The porous silica supports and the PEI-loaded porous silica supports were characterized by N{sub 2}-sorption analysis, scanning electron microscopy, Fourier transform infrared spectroscopy and thermal gravimetric analysis. CO{sub 2} sorption measurements of all PEI-loaded porous silica supports were performed at different adsorption temperatures (60, 75, 85, 90, 95 and 105 Degree-Sign C). At low PEI contents (10-20 wt%), the CO{sub 2} sorption of all adsorbents was found to decrease as a function of adsorption temperature, which was a characteristic of a thermodynamically-controlled regime. A transition from the thermodynamically-controlled regime to a kinetically-controlled regime was found when the PEI content was increased up to 30 wt% for PEI-loaded unimodal porous silicas and 40 wt% for PEI-loaded bimodal porous silicas. At high PEI contents (40-50 wt%), the CO{sub 2} capturing efficiency of the PEI-loaded bimodal porous silicas was found to be considerably greater than that of the PEI-loaded unimodal porous silicas, indicating that most of the amine groups of PEI molecules loaded on the unimodal porous silica supports was useless, and thus the appeared macroporosity of the bimodal porous silica supports could provide a higher effective amine density to adsorb CO{sub 2}. Highlights: Black-Right-Pointing-Pointer PEI-impregnated bimodal porous silica as low-cost sorbent for CO{sub 2} capture. Black-Right-Pointing-Pointer Macropores enhances

Probability of Failure in Random Vibration

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

1988-01-01

Close approximations to the first-passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first-passage probability density function and the distribution function for the time interval spent below a barrier before out......-crossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval and thus for the first-passage probability...

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Ramirez, Penelope; Velazquez, Sergio [Department of Renewable Energies, Technological Institute of the Canary Islands, Pozo Izquierdo Beach s/n, 35119 Santa Lucia, Gran Canaria, Canary Islands (Spain)

2008-10-15

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error {epsilon} made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R{sup 2} statistic (R{sub a}{sup 2}). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R{sub a}{sup 2} statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R{sub a}{sup 2} increases. (author)

On the method of logarithmic cumulants for parametric probability density function estimation.

Science.gov (United States)

Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane

2013-10-01

Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.

Probabilistic analysis and fatigue damage assessment of offshore mooring system due to non-Gaussian bimodal tension processes

Science.gov (United States)

Chang, Anteng; Li, Huajun; Wang, Shuqing; Du, Junfeng

2017-08-01

Both wave-frequency (WF) and low-frequency (LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system. This paper conducts a comprehensive investigation of applicable probability density functions (PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. Short-term statistical characteristics of mooring-line tension responses are firstly investigated, in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients. Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes. Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components. A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses. Using time domain simulation as a benchmark, its accuracy is further validated using a numerical case study of a moored semi-submersible platform.

Visualizing classical and quantum probability densities for momentum using variations on familiar one-dimensional potentials

International Nuclear Information System (INIS)

Robinett, R.W.

2002-01-01

After briefly reviewing the definitions of classical probability densities for position, P C L(x), and for momentum, P C L(p), we present several examples of classical mechanical potential systems, mostly variations on such familiar cases as the infinite well and the uniformly accelerated particle for which the classical distributions can be easily derived and visualized. We focus especially on a simple potential which interpolates between the symmetric linear potential, V(x)=F vertical bar x vertical bar, and the infinite well, which can illustrate, in a mathematically straightforward way, how the divergent δ-function classical probability density for momentum for the infinite well can be seen to arise. Such examples can help students understand the quantum mechanical momentum-space wavefunction (and its corresponding probability density) in much the same way that other semiclassical techniques, such as the WKB approximation, can be used to visualize position-space wavefunctions. (author)

Measuring oxygen uptake in fishes with bimodal respiration.

Science.gov (United States)

Lefevre, S; Bayley, M; McKenzie, D J

2016-01-01

Respirometry is a robust method for measurement of oxygen uptake as a proxy for metabolic rate in fishes, and how species with bimodal respiration might meet their demands from water v. air has interested researchers for over a century. The challenges of measuring oxygen uptake from both water and air, preferably simultaneously, have been addressed in a variety of ways, which are briefly reviewed. These methods are not well-suited for the long-term measurements necessary to be certain of obtaining undisturbed patterns of respiratory partitioning, for example, to estimate traits such as standard metabolic rate. Such measurements require automated intermittent-closed respirometry that, for bimodal fishes, has only recently been developed. This paper describes two approaches in enough detail to be replicated by the interested researcher. These methods are for static respirometry. Measuring oxygen uptake by bimodal fishes during exercise poses specific challenges, which are described to aid the reader in designing experiments. The respiratory physiology and behaviour of air-breathing fishes is very complex and can easily be influenced by experimental conditions, and some general considerations are listed to facilitate the design of experiments. Air breathing is believed to have evolved in response to aquatic hypoxia and, probably, associated hypercapnia. The review ends by considering what realistic hypercapnia is, how hypercapnic tropical waters can become and how this might influence bimodal animals' gas exchange. © 2015 The Fisheries Society of the British Isles.

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

Science.gov (United States)

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2007-11-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbin's [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. Single-point velocity and concentration statistics are compared to direct numerical simulation and experimental data at Reτ=1080 based on the friction velocity and the channel half width. The joint model accurately reproduces a wide variety of conditional and unconditional statistics in both physical and composition space.

Bilingualism alters brain functional connectivity between "control" regions and "language" regions: Evidence from bimodal bilinguals.

Science.gov (United States)

Li, Le; Abutalebi, Jubin; Zou, Lijuan; Yan, Xin; Liu, Lanfang; Feng, Xiaoxia; Wang, Ruiming; Guo, Taomei; Ding, Guosheng

2015-05-01

Previous neuroimaging studies have revealed that bilingualism induces both structural and functional neuroplasticity in the dorsal anterior cingulate cortex (dACC) and the left caudate nucleus (LCN), both of which are associated with cognitive control. Since these "control" regions should work together with other language regions during language processing, we hypothesized that bilingualism may also alter the functional interaction between the dACC/LCN and language regions. Here we tested this hypothesis by exploring the functional connectivity (FC) in bimodal bilinguals and monolinguals using functional MRI when they either performed a picture naming task with spoken language or were in resting state. We found that for bimodal bilinguals who use spoken and sign languages, the FC of the dACC with regions involved in spoken language (e.g. the left superior temporal gyrus) was stronger in performing the task, but weaker in the resting state as compared to monolinguals. For the LCN, its intrinsic FC with sign language regions including the left inferior temporo-occipital part and right inferior and superior parietal lobules was increased in the bilinguals. These results demonstrate that bilingual experience may alter the brain functional interaction between "control" regions and "language" regions. For different control regions, the FC alters in different ways. The findings also deepen our understanding of the functional roles of the dACC and LCN in language processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Investigation of heterogeneous asymmetric dihydroxylation over OsO{sub 4}-(QN){sub 2}PHAL catalysts of functionalized bimodal mesoporous silica with ionic liquid

Energy Technology Data Exchange (ETDEWEB)

Qiu, Shenjie [College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124 (China); Sun, Jihong, E-mail: jhsun@bjut.edu.cn [College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124 (China); Li, Yuzhen; Gao, Lin [College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124 (China)

2011-08-15

Highlights: {yields} Functionalized bimodal mesoporous silica with MTMSPIm{sup +}Cl{sup -}. {yields} Mesoporous catalyst immobilized with OsO{sub 4}-(QN){sub 2}PHAL. {yields} Catalysts for asymmetric dihydroxylation reaction with high yield and enatioselectivity. {yields} Recyclable catalysts. -- Abstract: A novel synthesis of the functionalized bimodal mesoporous silica with ionic liquid (FBMMs) was performed. After grafting 1-methyl-3-(trimethoxysilyl)propylimidazolium chloride onto the surface of bimodal mesoporous silicas, 1,4-bis(9-O-quininyl)phthalazine ((QN){sub 2}-PHAL) and K{sub 2}Os(OH){sub 4}.2H{sub 2}O were immobilized onto the modified FBMMs by adsorption or ionic exchange methods, and then, the asymmetric dihydroxylation reaction was carried out by using solid catalysts. Techniques such as X-ray diffraction, Fourier Transform Infrared spectroscopy, N{sub 2} adsorption and desorption were employed to characterize their structure and properties. The results showed that the mesoporous ordering degree of bimodal mesoporous silica decreased after functionalization and immobilization of OsO{sub 4}-(QN){sub 2}PHAL. Being very effective in asymmetric dihydroxylation with high yield and enantioselectivity, the prepared heterogeneous solid catalyst could be recycled for five times with little loss of enantioselectivity, with comparison of those results obtained in homophase system. Moreover, the effect of Osmium catalyst on asymmetric dihydroxylation was investigated.

Invariant probabilities of transition functions

CERN Document Server

Zaharopol, Radu

2014-01-01

The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transition functions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated using transition functions defined by flows, semiflows, and one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 are extended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structure of the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of t...

Aggressive Bimodal Communication in Domestic Dogs, Canis familiaris.

Science.gov (United States)

Déaux, Éloïse C; Clarke, Jennifer A; Charrier, Isabelle

2015-01-01

Evidence of animal multimodal signalling is widespread and compelling. Dogs' aggressive vocalisations (growls and barks) have been extensively studied, but without any consideration of the simultaneously produced visual displays. In this study we aimed to categorize dogs' bimodal aggressive signals according to the redundant/non-redundant classification framework. We presented dogs with unimodal (audio or visual) or bimodal (audio-visual) stimuli and measured their gazing and motor behaviours. Responses did not qualitatively differ between the bimodal and two unimodal contexts, indicating that acoustic and visual signals provide redundant information. We could not further classify the signal as 'equivalent' or 'enhancing' as we found evidence for both subcategories. We discuss our findings in relation to the complex signal framework, and propose several hypotheses for this signal's function.

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2010-01-01

This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties is consistent with a RUM. The choice...... probabilities from the RUM are obtained from the gradient of the CPGF. Mixtures of RUM are characterized by logarithmic mixtures of their associated CPGF. The paper relates CPGF to multivariate extreme value distributions, and reviews and extends methods for constructing generating functions for applications....... The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended to competing risk survival models....

Probability density function of a puff dispersing from the wall of a turbulent channel

Science.gov (United States)

Nguyen, Quoc; Papavassiliou, Dimitrios

2015-11-01

Study of dispersion of passive contaminants in turbulence has proved to be helpful in understanding fundamental heat and mass transfer phenomena. Many simulation and experimental works have been carried out to locate and track motions of scalar markers in a flow. One method is to combine Direct Numerical Simulation (DNS) and Lagrangian Scalar Tracking (LST) to record locations of markers. While this has proved to be useful, high computational cost remains a concern. In this study, we develop a model that could reproduce results obtained by DNS and LST for turbulent flow. Puffs of markers with different Schmidt numbers were released into a flow field at a frictional Reynolds number of 150. The point of release was at the channel wall, so that both diffusion and convection contribute to the puff dispersion pattern, defining different stages of dispersion. Based on outputs from DNS and LST, we seek the most suitable and feasible probability density function (PDF) that represents distribution of markers in the flow field. The PDF would play a significant role in predicting heat and mass transfer in wall turbulence, and would prove to be helpful where DNS and LST are not always available.

Probability density cloud as a geometrical tool to describe statistics of scattered light.

Science.gov (United States)

Yaitskova, Natalia

2017-04-01

First-order statistics of scattered light is described using the representation of the probability density cloud, which visualizes a two-dimensional distribution for complex amplitude. The geometric parameters of the cloud are studied in detail and are connected to the statistical properties of phase. The moment-generating function for intensity is obtained in a closed form through these parameters. An example of exponentially modified normal distribution is provided to illustrate the functioning of this geometrical approach.

Aggressive Bimodal Communication in Domestic Dogs, Canis familiaris.

Directory of Open Access Journals (Sweden)

Éloïse C Déaux

Full Text Available Evidence of animal multimodal signalling is widespread and compelling. Dogs' aggressive vocalisations (growls and barks have been extensively studied, but without any consideration of the simultaneously produced visual displays. In this study we aimed to categorize dogs' bimodal aggressive signals according to the redundant/non-redundant classification framework. We presented dogs with unimodal (audio or visual or bimodal (audio-visual stimuli and measured their gazing and motor behaviours. Responses did not qualitatively differ between the bimodal and two unimodal contexts, indicating that acoustic and visual signals provide redundant information. We could not further classify the signal as 'equivalent' or 'enhancing' as we found evidence for both subcategories. We discuss our findings in relation to the complex signal framework, and propose several hypotheses for this signal's function.

Probability density functions for radial anisotropy: implications for the upper 1200 km of the mantle

Science.gov (United States)

Beghein, Caroline; Trampert, Jeannot

2004-01-01

The presence of radial anisotropy in the upper mantle, transition zone and top of the lower mantle is investigated by applying a model space search technique to Rayleigh and Love wave phase velocity models. Probability density functions are obtained independently for S-wave anisotropy, P-wave anisotropy, intermediate parameter η, Vp, Vs and density anomalies. The likelihoods for P-wave and S-wave anisotropy beneath continents cannot be explained by a dry olivine-rich upper mantle at depths larger than 220 km. Indeed, while shear-wave anisotropy tends to disappear below 220 km depth in continental areas, P-wave anisotropy is still present but its sign changes compared to the uppermost mantle. This could be due to an increase with depth of the amount of pyroxene relative to olivine in these regions, although the presence of water, partial melt or a change in the deformation mechanism cannot be ruled out as yet. A similar observation is made for old oceans, but not for young ones where VSH> VSV appears likely down to 670 km depth and VPH> VPV down to 400 km depth. The change of sign in P-wave anisotropy seems to be qualitatively correlated with the presence of the Lehmann discontinuity, generally observed beneath continents and some oceans but not beneath ridges. Parameter η shows a similar age-related depth pattern as shear-wave anisotropy in the uppermost mantle and it undergoes the same change of sign as P-wave anisotropy at 220 km depth. The ratio between dln Vs and dln Vp suggests that a chemical component is needed to explain the anomalies in most places at depths greater than 220 km. More tests are needed to infer the robustness of the results for density, but they do not affect the results for anisotropy.

COVAL, Compound Probability Distribution for Function of Probability Distribution

International Nuclear Information System (INIS)

Astolfi, M.; Elbaz, J.

1979-01-01

1 - Nature of the physical problem solved: Computation of the probability distribution of a function of variables, given the probability distribution of the variables themselves. 'COVAL' has been applied to reliability analysis of a structure subject to random loads. 2 - Method of solution: Numerical transformation of probability distributions

Box-particle probability hypothesis density filtering

OpenAIRE

Schikora, M.; Gning, A.; Mihaylova, L.; Cremers, D.; Koch, W.

2014-01-01

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small number of box-p...

On the shapes of the presumed probability density function for the modeling of turbulence-radiation interactions

International Nuclear Information System (INIS)

Liu, L.H.; Xu, X.; Chen, Y.L.

2004-01-01

The laminar flamelet equations in combination with the joint probability density function (PDF) transport equation of mixture fraction and turbulence frequency have been used to simulate turbulent jet diffusion flames. To check the suitability of the presumed shapes of the PDF for the modeling of turbulence-radiation interactions (TRI), two types of presumed joint PDFs are constructed by using the second-order moments of temperature and the species concentrations, which are derived by the laminar flamelet model. The time-averaged radiative source terms and the time-averaged absorption coefficients are calculated by the presumed joint PDF approaches, and compared with those obtained by the laminar flamelet model. By comparison, it is shown that there are obvious differences between the results of the independent PDF approach and the laminar flamelet model. Generally, the results of the dependent PDF approach agree better with those of the flamelet model. For the modeling of TRI, the dependent PDF approach is superior to the independent PDF approach

Divergence from, and Convergence to, Uniformity of Probability Density Quantiles

Directory of Open Access Journals (Sweden)

Robert G. Staudte

2018-04-01

Full Text Available We demonstrate that questions of convergence and divergence regarding shapes of distributions can be carried out in a location- and scale-free environment. This environment is the class of probability density quantiles (pdQs, obtained by normalizing the composition of the density with the associated quantile function. It has earlier been shown that the pdQ is representative of a location-scale family and carries essential information regarding shape and tail behavior of the family. The class of pdQs are densities of continuous distributions with common domain, the unit interval, facilitating metric and semi-metric comparisons. The Kullback–Leibler divergences from uniformity of these pdQs are mapped to illustrate their relative positions with respect to uniformity. To gain more insight into the information that is conserved under the pdQ mapping, we repeatedly apply the pdQ mapping and find that further applications of it are quite generally entropy increasing so convergence to the uniform distribution is investigated. New fixed point theorems are established with elementary probabilistic arguments and illustrated by examples.

Choice Probability Generating Functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel L; Bierlaire, Michel

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications....

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2013-01-01

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications. The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended...

Bimodal emotion congruency is critical to preverbal infants' abstract rule learning.

Science.gov (United States)

Tsui, Angeline Sin Mei; Ma, Yuen Ki; Ho, Anna; Chow, Hiu Mei; Tseng, Chia-huei

2016-05-01

Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar-like rules (e.g. ABA) enhanced 5-month-olds' capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of the shapes alone (circle-triangle-circle) or auditory presentation of the syllables (la-ba-la) alone. However, the mechanisms and constraints for this bimodal learning facilitation are still unknown. In this study, we used audio-visual relation congruency between bimodal stimulation to disentangle possible facilitation sources. We exposed 8- to 10-month-old infants to an AAB sequence consisting of visual faces with affective expressions and/or auditory voices conveying emotions. Our results showed that infants were able to distinguish the learned AAB rule from other novel rules under bimodal stimulation when the affects in audio and visual stimuli were congruently paired (Experiments 1A and 2A). Infants failed to acquire the same rule when audio-visual stimuli were incongruently matched (Experiment 2B) and when only the visual (Experiment 1B) or the audio (Experiment 1C) stimuli were presented. Our results highlight that bimodal facilitation in infant rule learning is not only dependent on better statistical probability and redundant sensory information, but also the relational congruency of audio-visual information. A video abstract of this article can be viewed at https://m.youtube.com/watch?v=KYTyjH1k9RQ. © 2015 John Wiley & Sons Ltd.

Using probability density function in the procedure for recognition of the type of physical exercise

Directory of Open Access Journals (Sweden)

Cakić Nikola

2017-01-01

Full Text Available This paper presents a method for recognition of physical exercises, using only a triaxial accelerometer of a smartphone. The smartphone itself is free to move inside subject's pocket. Exercises for leg muscle strengthening from subject's standing position squat, right knee rise and lunge with right leg were analyzed. All exercises were performed with the accelerometric sensor of a smartphone placed in the pocket next to the leg used for exercises. In order to test the proposed recognition method, the knee rise exercise of the opposite leg with the same position of the sensor was randomly selected. Filtering of the raw accelerometric signals was carried out using Butterworth tenth-order low-pass filter. The filtered signals from each of the three axes were described using three signal descriptors. After the descriptors were calculated, a probability density function was constructed for each of the descriptors. The program that implemented the proposed recognition method was executed online within an Android application of the smartphone. Signals from two male and two female subjects were considered as a reference for exercise recognition. The exercise recognition accuracy was 94.22% for three performed exercises, and 85.33% for all four considered exercises.

An empirical probability model of detecting species at low densities.

Science.gov (United States)

Delaney, David G; Leung, Brian

2010-06-01

False negatives, not detecting things that are actually present, are an important but understudied problem. False negatives are the result of our inability to perfectly detect species, especially those at low density such as endangered species or newly arriving introduced species. They reduce our ability to interpret presence-absence survey data and make sound management decisions (e.g., rapid response). To reduce the probability of false negatives, we need to compare the efficacy and sensitivity of different sampling approaches and quantify an unbiased estimate of the probability of detection. We conducted field experiments in the intertidal zone of New England and New York to test the sensitivity of two sampling approaches (quadrat vs. total area search, TAS), given different target characteristics (mobile vs. sessile). Using logistic regression we built detection curves for each sampling approach that related the sampling intensity and the density of targets to the probability of detection. The TAS approach reduced the probability of false negatives and detected targets faster than the quadrat approach. Mobility of targets increased the time to detection but did not affect detection success. Finally, we interpreted two years of presence-absence data on the distribution of the Asian shore crab (Hemigrapsus sanguineus) in New England and New York, using our probability model for false negatives. The type of experimental approach in this paper can help to reduce false negatives and increase our ability to detect species at low densities by refining sampling approaches, which can guide conservation strategies and management decisions in various areas of ecology such as conservation biology and invasion ecology.

Bimodality emerges from transport model calculations of heavy ion collisions at intermediate energy

Science.gov (United States)

Mallik, S.; Das Gupta, S.; Chaudhuri, G.

2016-04-01

This work is a continuation of our effort [S. Mallik, S. Das Gupta, and G. Chaudhuri, Phys. Rev. C 91, 034616 (2015)], 10.1103/PhysRevC.91.034616 to examine if signatures of a phase transition can be extracted from transport model calculations of heavy ion collisions at intermediate energy. A signature of first-order phase transition is the appearance of a bimodal distribution in Pm(k ) in finite systems. Here Pm(k ) is the probability that the maximum of the multiplicity distribution occurs at mass number k . Using a well-known model for event generation [Botzmann-Uehling-Uhlenbeck (BUU) plus fluctuation], we study two cases of central collision: mass 40 on mass 40 and mass 120 on mass 120. Bimodality is seen in both the cases. The results are quite similar to those obtained in statistical model calculations. An intriguing feature is seen. We observe that at the energy where bimodality occurs, other phase-transition-like signatures appear. There are breaks in certain first-order derivatives. We then examine if such breaks appear in standard BUU calculations without fluctuations. They do. The implication is interesting. If first-order phase transition occurs, it may be possible to recognize that from ordinary BUU calculations. Probably the reason this has not been seen already is because this aspect was not investigated before.

On the discretization of probability density functions and the ...

Indian Academy of Sciences (India)

important for most applications or theoretical problems of interest. In statistics ... In probability theory, statistics, statistical mechanics, communication theory, and other .... (1) by taking advantage of SMVT as a general mathematical approach.

Computation of the Complex Probability Function

Energy Technology Data Exchange (ETDEWEB)

Trainer, Amelia Jo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ledwith, Patrick John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-08-22

The complex probability function is important in many areas of physics and many techniques have been developed in an attempt to compute it for some z quickly and e ciently. Most prominent are the methods that use Gauss-Hermite quadrature, which uses the roots of the n^th degree Hermite polynomial and corresponding weights to approximate the complex probability function. This document serves as an overview and discussion of the use, shortcomings, and potential improvements on the Gauss-Hermite quadrature for the complex probability function.

Improving experimental phases for strong reflections prior to density modification

International Nuclear Information System (INIS)

Uervirojnangkoorn, Monarin; Hilgenfeld, Rolf; Terwilliger, Thomas C.; Read, Randy J.

2013-01-01

A genetic algorithm has been developed to optimize the phases of the strongest reflections in SIR/SAD data. This is shown to facilitate density modification and model building in several test cases. Experimental phasing of diffraction data from macromolecular crystals involves deriving phase probability distributions. These distributions are often bimodal, making their weighted average, the centroid phase, improbable, so that electron-density maps computed using centroid phases are often non-interpretable. Density modification brings in information about the characteristics of electron density in protein crystals. In successful cases, this allows a choice between the modes in the phase probability distributions, and the maps can cross the borderline between non-interpretable and interpretable. Based on the suggestions by Vekhter [Vekhter (2005 ▶), Acta Cryst. D61, 899–902], the impact of identifying optimized phases for a small number of strong reflections prior to the density-modification process was investigated while using the centroid phase as a starting point for the remaining reflections. A genetic algorithm was developed that optimizes the quality of such phases using the skewness of the density map as a target function. Phases optimized in this way are then used in density modification. In most of the tests, the resulting maps were of higher quality than maps generated from the original centroid phases. In one of the test cases, the new method sufficiently improved a marginal set of experimental SAD phases to enable successful map interpretation. A computer program, SISA, has been developed to apply this method for phase improvement in macromolecular crystallography

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

Science.gov (United States)

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.

Science.gov (United States)

Yura, Harold T; Hanson, Steen G

2012-04-01

Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.

Nano-scale simulation based study of creep behavior of bimodal nanocrystalline face centered cubic metal.

Science.gov (United States)

Meraj, Md; Pal, Snehanshu

2017-10-11

In this paper, the creep behavior of nanocrystalline Ni having bimodal grain structure is investigated using molecular dynamics simulation. Analysis of structural evolution during the creep process has also been performed. It is observed that an increase in size of coarse grain causes improvement in creep properties of bimodal nanocrystalline Ni. Influence of bimodality (i.e., size difference between coarse and fine grains) on creep properties are found to be reduced with increasing creep temperature. The dislocation density is observed to decrease exponentially with progress of creep deformation. Grain boundary diffusion controlled creep mechanism is found to be dominant at the primary creep region and the initial part of the secondary creep region. After that shear diffusion transformation mechanism is found to be significantly responsible for deformation as bimodal nanocrystalline Ni transforms to amorphous structure with further progress of the creep process. The presence of , , and  distorted icosahedra has a significant influence on creep rate in the tertiary creep regime according to Voronoi cluster analysis.

Acid-base and ion balance in fishes with bimodal respiration.

Science.gov (United States)

Shartau, R B; Brauner, C J

2014-03-01

The evolution of air breathing during the Devonian provided early fishes with bimodal respiration with a stable O2 supply from air. This was, however, probably associated with challenges and trade-offs in terms of acid-base balance and ionoregulation due to reduced gill:water interaction and changes in gill morphology associated with air breathing. While many aspects of acid-base and ionoregulation in air-breathing fishes are similar to water breathers, the specific cellular and molecular mechanisms involved remain largely unstudied. In general, reduced ionic permeability appears to be an important adaptation in the few bimodal fishes investigated but it is not known if this is a general characteristic. The kidney appears to play an important role in minimizing ion loss to the freshwater environment in the few species investigated, and while ion uptake across the gut is probably important, it has been largely unexplored. In general, air breathing in facultative air-breathing fishes is associated with an acid-base disturbance, resulting in an increased partial pressure of arterial CO2 and a reduction in extracellular pH (pHE ); however, several fishes appear to be capable of tightly regulating tissue intracellular pH (pHI ), despite a large sustained reduction in pHE , a trait termed preferential pHI regulation. Further studies are needed to determine whether preferential pHI regulation is a general trait among bimodal fishes and if this confers reduced sensitivity to acid-base disturbances, including those induced by hypercarbia, exhaustive exercise and hypoxia or anoxia. Additionally, elucidating the cellular and molecular mechanisms may yield insight into whether preferential pHI regulation is a trait ultimately associated with the early evolution of air breathing in vertebrates. © 2014 The Fisheries Society of the British Isles.

Disentangling the climate-driven bimodal growth pattern in coastal and continental Mediterranean pine stands.

Science.gov (United States)

Pacheco, Arturo; Camarero, J Julio; Ribas, Montse; Gazol, Antonio; Gutierrez, E; Carrer, Marco

2018-02-15

Mediterranean climate promotes two distinct growth peaks separated by summer quiescence in trees. This bimodal pattern has been associated to favourable growing conditions during spring and autumn when mild temperatures and soil-water availability enhance cambial activity. Climatic models predict progressive warming and drying for the Mediterranean Basin, which could shorten or shift the spring and autumn growing seasons. We explored this idea by comparing two sites with different Mediterranean climate types (continental/dry and coastal/wet) and studied how climate drives the bimodal growth pattern in Aleppo pine (Pinus halepensis). Specifically we investigated the intra-annual changes in wood anatomy and the corresponding formation of density fluctuations (IADF). Trees on both sites were analyzed by dendrometer monitoring and by developing chronologies of wood anatomical traits. Radial-increment dynamics followed a similar bimodal pattern in both sites but coastal trees showed higher increments during the spring and autumn growth peaks, especially in autumn. The summer rest of cambium activity occurs almost one month earlier in the coastal than in the inland site. Lumen area and cell-wall thickness were significantly smaller in the continental site, while the increment rate of cell-wall thickness during an IADF event was much higher in the coastal pines. The accumulated soil moisture deficit was the main climatic constraint of tracheid enlargement in continental pines. Intra-annual density fluctuations were more frequent in the coastal trees where wood anatomy features recover to average values after such events, meanwhile inland trees presented a much lower recovery rate. Growth bimodality and the formation of density fluctuations were linked, but mild climate of the coastal site allows a longer growing season, which explains why trees in this area showed higher and more variable growth rates. Copyright © 2017 Elsevier B.V. All rights reserved.

The dynamics of variable-density turbulence

International Nuclear Information System (INIS)

Sandoval, D.L.

1995-11-01

The dynamics of variable-density turbulent fluids are studied by direct numerical simulation. The flow is incompressible so that acoustic waves are decoupled from the problem, and implying that density is not a thermodynamic variable. Changes in density occur due to molecular mixing. The velocity field, is in general, divergent. A pseudo-spectral numerical technique is used to solve the equations of motion. Three-dimensional simulations are performed using a grid size of 128 3 grid points. Two types of problems are studied: (1) the decay of isotropic, variable-density turbulence, and (2) buoyancy-generated turbulence in a fluid with large density fluctuations. In the case of isotropic, variable-density turbulence, the overall statistical decay behavior, for the cases studied, is relatively unaffected by the presence of density variations when the initial density and velocity fields are statistically independent. The results for this case are in quantitative agreement with previous numerical and laboratory results. In this case, the initial density field has a bimodal probability density function (pdf) which evolves in time towards a Gaussian distribution. The pdf of the density field is symmetric about its mean value throughout its evolution. If the initial velocity and density fields are statistically dependent, however, the decay process is significantly affected by the density fluctuations. For the case of buoyancy-generated turbulence, variable-density departures from the Boussinesq approximation are studied. The results of the buoyancy-generated turbulence are compared with variable-density model predictions. Both a one-point (engineering) model and a two-point (spectral) model are tested against the numerical data. Some deficiencies in these variable-density models are discussed and modifications are suggested

The effect of incremental changes in phonotactic probability and neighborhood density on word learning by preschool children

Science.gov (United States)

Storkel, Holly L.; Bontempo, Daniel E.; Aschenbrenner, Andrew J.; Maekawa, Junko; Lee, Su-Yeon

2013-01-01

Purpose Phonotactic probability or neighborhood density have predominately been defined using gross distinctions (i.e., low vs. high). The current studies examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method The full range of probability or density was examined by sampling five nonwords from each of four quartiles. Three- and 5-year-old children received training on nonword-nonobject pairs. Learning was measured in a picture-naming task immediately following training and 1-week after training. Results were analyzed using multi-level modeling. Results A linear spline model best captured nonlinearities in phonotactic probability. Specifically word learning improved as probability increased in the lowest quartile, worsened as probability increased in the midlow quartile, and then remained stable and poor in the two highest quartiles. An ordinary linear model sufficiently described neighborhood density. Here, word learning improved as density increased across all quartiles. Conclusion Given these different patterns, phonotactic probability and neighborhood density appear to influence different word learning processes. Specifically, phonotactic probability may affect recognition that a sound sequence is an acceptable word in the language and is a novel word for the child, whereas neighborhood density may influence creation of a new representation in long-term memory. PMID:23882005

Spin theory of the density functional: reduced matrices and density functions

International Nuclear Information System (INIS)

Pavlov, R.; Delchev, Y.; Pavlova, K.; Maruani, J.

1993-01-01

Expressions for the reduced matrices and density functions of N-fermion systems of arbitrary order s (1<=s<=N) are derived within the frame of rigorous spin approach to the density functional theory (DFT). Using the local-scale transformation method and taking into account the particle spin it is shown that the reduced matrices and density functions are functionals of the total one-fermion density. Similar dependence is found for the distribution density of s-particle aggregates. Generalization and applicability of DFT to the case of s-particle ensembles and aggregates is discussed. 14 refs

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

International Nuclear Information System (INIS)

Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

2012-01-01

In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

Flexible transparent conducting films with embedded silver networks composed of bimodal-sized nanoparticles for heater application

Science.gov (United States)

Park, Ji Sun; Song, Yookyung; Park, Daseul; Kim, Yeon-Won; Kim, Yoon Jin

2018-06-01

A facile one-pot synthetic method for preparing the Ag nanoparticle inks with a bimodal size distribution was newly devised and they were successfully employed as a conducting filler to form the metal-mesh type transparent conducting electrodes on the flexible substrate. Bimodal-sized Ag nanoparticles were synthesized through the polyol process, and their size variation was occurred via finely tuned composition ratio between Ag+ ions and polymeric capping agents. The prepared bimodal-sized Ag nanoparticles exhibited the form of well-dispersed Ag nanoparticle inks without adding any dispersants and dispersion process. By filling the patterned micro-channels engraved on the flexible polymer substrate using a bimodal-sized Ag nanoparticle ink, a metal-mesh type transparent electrode (transmittance: 90% at 550 nm, haze: 1.5, area: 8 × 8 cm2) was fabricated. By applying DC voltage to the mesh type electrode, a flexible transparent joule heater was successfully achieved with a performance of 4.5 °C s‑1 heat-up rate at a low input power density.

Reactive Sintering of Bimodal WC-Co Hardmetals

Directory of Open Access Journals (Sweden)

Marek Tarraste

2015-09-01

Full Text Available Bimodal WC-Co hardmetals were produced using novel technology - reactive sintering. Milled and activated tungsten and graphite powders were mixed with commercial coarse grained WC-Co powder and then sintered. The microstructure of produced materials was free of defects and consisted of evenly distributed coarse and fine tungsten carbide grains in cobalt binder. The microstructure, hardness and fracture toughness of reactive sintered bimodal WC-Co hardmetals is exhibited. Developed bimodal hardmetal has perspective for demanding wear applications for its increased combined hardness and toughness. Compared to coarse material there is only slight decrease in fracture toughness (K1c is 14.7 for coarse grained and 14.4 for bimodal, hardness is increased from 1290 to 1350 HV units.DOI: http://dx.doi.org/10.5755/j01.ms.21.3.7511

Determination of probability density functions for parameters in the Munson-Dawson model for creep behavior of salt

International Nuclear Information System (INIS)

Pfeifle, T.W.; Mellegard, K.D.; Munson, D.E.

1992-10-01

The modified Munson-Dawson (M-D) constitutive model that describes the creep behavior of salt will be used in performance assessment calculations to assess compliance of the Waste Isolation Pilot Plant (WIPP) facility with requirements governing the disposal of nuclear waste. One of these standards requires that the uncertainty of future states of the system, material model parameters, and data be addressed in the performance assessment models. This paper presents a method in which measurement uncertainty and the inherent variability of the material are characterized by treating the M-D model parameters as random variables. The random variables can be described by appropriate probability distribution functions which then can be used in Monte Carlo or structural reliability analyses. Estimates of three random variables in the M-D model were obtained by fitting a scalar form of the model to triaxial compression creep data generated from tests of WIPP salt. Candidate probability distribution functions for each of the variables were then fitted to the estimates and their relative goodness-of-fit tested using the Kolmogorov-Smirnov statistic. A sophisticated statistical software package obtained from BMDP Statistical Software, Inc. was used in the M-D model fitting. A separate software package, STATGRAPHICS, was used in fitting the candidate probability distribution functions to estimates of the variables. Skewed distributions, i.e., lognormal and Weibull, were found to be appropriate for the random variables analyzed

Language choice in bimodal bilingual development

Directory of Open Access Journals (Sweden)

Diane eLillo-Martin

2014-10-01

Full Text Available Bilingual children develop sensitivity to the language used by their interlocutors at an early age, reflected in differential use of each language by the child depending on their interlocutor. Factors such as discourse context and relative language dominance in the community may mediate the degree of language differentiation in preschool age children.Bimodal bilingual children, acquiring both a sign language and a spoken language, have an even more complex situation. Their Deaf parents vary considerably in access to the spoken language. Furthermore, in addition to code-mixing and code-switching, they use code-blending – expressions in both speech and sign simultaneously – an option uniquely available to bimodal bilinguals. Code-blending is analogous to code-switching sociolinguistically, but is also a way to communicate without suppressing one language. For adult bimodal bilinguals, complete suppression of the non-selected language is cognitively demanding. We expect that bimodal bilingual children also find suppression difficult, and use blending rather than suppression in some contexts. We also expect relative community language dominance to be a factor in children’s language choices.This study analyzes longitudinal spontaneous production data from four bimodal bilingual children and their Deaf and hearing interlocutors. Even at the earliest observations, the children produced more signed utterances with Deaf interlocutors and more speech with hearing interlocutors. However, while three of the four children produced >75% speech alone in speech target sessions, they produced <25% sign alone in sign target sessions. All four produced bimodal utterances in both, but more frequently in the sign sessions, potentially because they find suppression of the dominant language more difficult.Our results indicate that these children are sensitive to the language used by their interlocutors, while showing considerable influence from the dominant

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

CERN Document Server

Dannheim, Dominik; Voigt, Alexander; Grahn, Karl-Johan; Speckmayer, Peter

2009-01-01

Probability-Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. To efficiently use large event samples to estimate the probability density, a binary search tree (range searching) is used in the PDE-RS implementation. It is a generalisation of standard likelihood methods and a powerful classification tool for problems with highly non-linearly correlated observables. In this paper, we present an innovative improvement of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multidimensional phase space, minimizing the variance of the signal and background densities inside the cells. The binned density information is stored in binary trees, allowing for a very ...

Bimodal Programming: A Survey of Current Clinical Practice.

Science.gov (United States)

Siburt, Hannah W; Holmes, Alice E

2015-06-01

The purpose of this study was to determine the current clinical practice in approaches to bimodal programming in the United States. To be specific, if clinicians are recommending bimodal stimulation, who programs the hearing aid in the bimodal condition, and what method is used for programming the hearing aid? An 11-question online survey was created and sent via email to a comprehensive list of cochlear implant programming centers in the United States. The survey was sent to 360 recipients. Respondents in this study represented a diverse group of clinical settings (response rate: 26%). Results indicate little agreement about who programs the hearing aids, when they are programmed, and how they are programmed in the bimodal condition. Analysis of small versus large implant centers indicated small centers are less likely to add a device to the contralateral ear. Although a growing number of cochlear implant recipients choose to wear a hearing aid on the contralateral ear, there is inconsistency in the current clinical approach to bimodal programming. These survey results provide evidence of large variability in the current bimodal programming practices and indicate a need for more structured clinical recommendations and programming approaches.

Bimodal Nuclear Thermal Rocket Analysis Developments

Science.gov (United States)

Belair, Michael; Lavelle, Thomas; Saimento, Charles; Juhasz, Albert; Stewart, Mark

2014-01-01

Nuclear thermal propulsion has long been considered an enabling technology for human missions to Mars and beyond. One concept of operations for these missions utilizes the nuclear reactor to generate electrical power during coast phases, known as bimodal operation. This presentation focuses on the systems modeling and analysis efforts for a NERVA derived concept. The NERVA bimodal operation derives the thermal energy from the core tie tube elements. Recent analysis has shown potential temperature distributions in the tie tube elements that may limit the thermodynamic efficiency of the closed Brayton cycle used to generate electricity with the current design. The results of this analysis are discussed as well as the potential implications to a bimodal NERVA type reactor.

Kinetic and dynamic probability-density-function descriptions of disperse turbulent two-phase flows

Science.gov (United States)

Minier, Jean-Pierre; Profeta, Christophe

2015-11-01

This article analyzes the status of two classical one-particle probability density function (PDF) descriptions of the dynamics of discrete particles dispersed in turbulent flows. The first PDF formulation considers only the process made up by particle position and velocity Zp=(xp,Up) and is represented by its PDF p (t ;yp,Vp) which is the solution of a kinetic PDF equation obtained through a flux closure based on the Furutsu-Novikov theorem. The second PDF formulation includes fluid variables into the particle state vector, for example, the fluid velocity seen by particles Zp=(xp,Up,Us) , and, consequently, handles an extended PDF p (t ;yp,Vp,Vs) which is the solution of a dynamic PDF equation. For high-Reynolds-number fluid flows, a typical formulation of the latter category relies on a Langevin model for the trajectories of the fluid seen or, conversely, on a Fokker-Planck equation for the extended PDF. In the present work, a new derivation of the kinetic PDF equation is worked out and new physical expressions of the dispersion tensors entering the kinetic PDF equation are obtained by starting from the extended PDF and integrating over the fluid seen. This demonstrates that, under the same assumption of a Gaussian colored noise and irrespective of the specific stochastic model chosen for the fluid seen, the kinetic PDF description is the marginal of a dynamic PDF one. However, a detailed analysis reveals that kinetic PDF models of particle dynamics in turbulent flows described by statistical correlations constitute incomplete stand-alone PDF descriptions and, moreover, that present kinetic-PDF equations are mathematically ill posed. This is shown to be the consequence of the non-Markovian characteristic of the stochastic process retained to describe the system and the use of an external colored noise. Furthermore, developments bring out that well-posed PDF descriptions are essentially due to a proper choice of the variables selected to describe physical systems

Intrinsic-density functionals

International Nuclear Information System (INIS)

Engel, J.

2007-01-01

The Hohenberg-Kohn theorem and Kohn-Sham procedure are extended to functionals of the localized intrinsic density of a self-bound system such as a nucleus. After defining the intrinsic-density functional, we modify the usual Kohn-Sham procedure slightly to evaluate the mean-field approximation to the functional, and carefully describe the construction of the leading corrections for a system of fermions in one dimension with a spin-degeneracy equal to the number of particles N. Despite the fact that the corrections are complicated and nonlocal, we are able to construct a local Skyrme-like intrinsic-density functional that, while different from the exact functional, shares with it a minimum value equal to the exact ground-state energy at the exact ground-state intrinsic density, to next-to-leading order in 1/N. We briefly discuss implications for real Skyrme functionals

New evolution equations for the joint response-excitation probability density function of stochastic solutions to first-order nonlinear PDEs

Science.gov (United States)

Venturi, D.; Karniadakis, G. E.

2012-08-01

By using functional integral methods we determine new evolution equations satisfied by the joint response-excitation probability density function (PDF) associated with the stochastic solution to first-order nonlinear partial differential equations (PDEs). The theory is presented for both fully nonlinear and for quasilinear scalar PDEs subject to random boundary conditions, random initial conditions or random forcing terms. Particular applications are discussed for the classical linear and nonlinear advection equations and for the advection-reaction equation. By using a Fourier-Galerkin spectral method we obtain numerical solutions of the proposed response-excitation PDF equations. These numerical solutions are compared against those obtained by using more conventional statistical approaches such as probabilistic collocation and multi-element probabilistic collocation methods. It is found that the response-excitation approach yields accurate predictions of the statistical properties of the system. In addition, it allows to directly ascertain the tails of probabilistic distributions, thus facilitating the assessment of rare events and associated risks. The computational cost of the response-excitation method is order magnitudes smaller than the one of more conventional statistical approaches if the PDE is subject to high-dimensional random boundary or initial conditions. The question of high-dimensionality for evolution equations involving multidimensional joint response-excitation PDFs is also addressed.

Unification of field theory and maximum entropy methods for learning probability densities

Science.gov (United States)

Kinney, Justin B.

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Unification of field theory and maximum entropy methods for learning probability densities.

Science.gov (United States)

Kinney, Justin B

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Energy density functional analysis of shape coexistence in 44S

International Nuclear Information System (INIS)

Li, Z. P.; Yao, J. M.; Vretenar, D.; Nikšić, T.; Meng, J.

2012-01-01

The structure of low-energy collective states in the neutron-rich nucleus 44 S is analyzed using a microscopic collective Hamiltonian model based on energy density functionals (EDFs). The calculated triaxial energy map, low-energy spectrum and corresponding probability distributions indicate a coexistence of prolate and oblate shapes in this nucleus.

Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.

Science.gov (United States)

Sabahi, Farnaz

2018-04-04

Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors. Copyright © 2018 Elsevier Inc. All

Alert-derivative bimodal space power and propulsion systems

International Nuclear Information System (INIS)

Houts, M.G.; Ranken, W.A.; Buksa, J.J.

1994-01-01

Safe, reliable, low-mass bimodal space power and propulsion systems could have numerous civilian and military applications. This paper discusses potential bimodal systems that could be derived from the ALERT space fission power supply concept. These bimodal concepts have the potential for providing 5 to 10 kW of electrical power and a total impulse of 100 MN-s at an average specific impulse of 770 s. System mass is on the order of 1000 kg

Beta-binomial regression and bimodal utilization.

Science.gov (United States)

Liu, Chuan-Fen; Burgess, James F; Manning, Willard G; Maciejewski, Matthew L

2013-10-01

To illustrate how the analysis of bimodal U-shaped distributed utilization can be modeled with beta-binomial regression, which is rarely used in health services research. Veterans Affairs (VA) administrative data and Medicare claims in 2001-2004 for 11,123 Medicare-eligible VA primary care users in 2000. We compared means and distributions of VA reliance (the proportion of all VA/Medicare primary care visits occurring in VA) predicted from beta-binomial, binomial, and ordinary least-squares (OLS) models. Beta-binomial model fits the bimodal distribution of VA reliance better than binomial and OLS models due to the nondependence on normality and the greater flexibility in shape parameters. Increased awareness of beta-binomial regression may help analysts apply appropriate methods to outcomes with bimodal or U-shaped distributions. © Health Research and Educational Trust.

Bimodality in heavy ions collisions: systematic and comparisons

International Nuclear Information System (INIS)

Mercier, D.

2008-11-01

During the last few years, bi-modality in heavy ions collisions has been observed for different systems, on large energy scale (from 35 MeV/u up to 1 GeV/u). In this thesis, the bimodal behaviour of the largest fragment distribution (Zmax) is studied for different INDRA data sets. For peripheral collisions (Au+Au from 60 to 150 MeV/u, Xe+Sn 80-100 MeV/u), the influence of sorting and selections on bi-modality is tested. Then, two different approaches based on models are considered. In the first one (ELIE), bi-modality would reflect mainly the collision geometry and the Fermi motion of the nucleon. In the second one (SMM), bi-modality would reflect a phase transition of nuclear matter. The data are in favour of the second model. Zmax can then be considered as an order parameter of the transition. A re-weighting procedure producing a flat excitation energy distribution is used to achieve comparisons between various bombarding energies and theoretical predictions based on a canonical approach. A latent heat of the transition is extracted. For central collisions (Ni+Ni from 32 to 74 MeV/u and Xe+Sn from 25 to 50 MeV/u) single source events are isolated by a Discriminant Factor Analysis. Bi-modality is then looked for, in cumulating the different incident energies and in applying the re-weighting procedure of the corresponding excitation energy as done for peripheral collisions. The bi-modality behaviour is less manifest for central collisions than for peripheral ones. The possible reasons of this difference are discussed. (author)

The problem of the universal density functional and the density matrix functional theory

International Nuclear Information System (INIS)

Bobrov, V. B.; Trigger, S. A.

2013-01-01

The analysis in this paper shows that the Hohenberg-Kohn theorem is the constellation of two statements: (i) the mathematically rigorous Hohenberg-Kohn lemma, which demonstrates that the same ground-state density cannot correspond to two different potentials of an external field, and (ii) the hypothesis of the existence of the universal density functional. Based on the obtained explicit expression for the nonrel-ativistic particle energy in a local external field, we prove that the energy of the system of more than two non-interacting electrons cannot be a functional of the inhomogeneous density. This result is generalized to the system of interacting electrons. It means that the Hohenberg-Kohn lemma cannot provide justification of the universal density functional for fermions. At the same time, statements of the density functional theory remain valid when considering any number of noninteracting ground-state bosons due to the Bose condensation effect. In the framework of the density matrix functional theory, the hypothesis of the existence of the universal density matrix functional corresponds to the cases of noninteracting particles and to interaction in the Hartree-Fock approximation.

Synergy between pair coupled cluster doubles and pair density functional theory

Energy Technology Data Exchange (ETDEWEB)

Garza, Alejandro J.; Bulik, Ireneusz W. [Department of Chemistry, Rice University, Houston, Texas 77251-1892 (United States); Henderson, Thomas M. [Department of Chemistry and Department of Physics and Astronomy, Rice University, Houston, Texas 77251-1892 (United States); Scuseria, Gustavo E. [Department of Chemistry and Department of Physics and Astronomy, Rice University, Houston, Texas 77251-1892 (United States); Chemistry Department, Faculty of Science, King Abdulaziz University, Jeddah 21589 (Saudi Arabia)

2015-01-28

Pair coupled cluster doubles (pCCD) has been recently studied as a method capable of accounting for static correlation with low polynomial cost. We present three combinations of pCCD with Kohn–Sham functionals of the density and on-top pair density (the probability of finding two electrons on top of each other) to add dynamic correlation to pCCD without double counting. With a negligible increase in computational cost, these pCCD+DFT blends greatly improve upon pCCD in the description of typical problems where static and dynamic correlations are both important. We argue that—as a black-box method with low scaling, size-extensivity, size-consistency, and a simple quasidiagonal two-particle density matrix—pCCD is an excellent match for pair density functionals in this type of fusion of multireference wavefunctions with DFT.

Estimation of Extreme Response and Failure Probability of Wind Turbines under Normal Operation using Probability Density Evolution Method

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Liu, W. F.

2013-01-01

Estimation of extreme response and failure probability of structures subjected to ultimate design loads is essential for structural design of wind turbines according to the new standard IEC61400-1. This task is focused on in the present paper in virtue of probability density evolution method (PDEM......), which underlies the schemes of random vibration analysis and structural reliability assessment. The short-term rare failure probability of 5-mega-watt wind turbines, for illustrative purposes, in case of given mean wind speeds and turbulence levels is investigated through the scheme of extreme value...... distribution instead of any other approximate schemes of fitted distribution currently used in statistical extrapolation techniques. Besides, the comparative studies against the classical fitted distributions and the standard Monte Carlo techniques are carried out. Numerical results indicate that PDEM exhibits...

A bimodal flexible distribution for lifetime data

OpenAIRE

Ramires, Thiago G.; Ortega, Edwin M. M.; Cordeiro, Gauss M.; Hens, Niel

2016-01-01

A four-parameter extended bimodal lifetime model called the exponentiated log-sinh Cauchy distribution is proposed. It extends the log-sinh Cauchy and folded Cauchy distributions. We derive some of its mathematical properties including explicit expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood is used to estimate the model parameters. We implement the fit of the model in the GAMLSS package and provide the codes. The flexibility of the...

Density Functional Simulation of a Breaking Nanowire

DEFF Research Database (Denmark)

Nakamura, A.; Brandbyge, Mads; Hansen, Lars Bruno

1999-01-01

to a specific number of eigenchannels. The transitions between plateaus can be abrupt in connection with structural rearrangements or extend over a few a of elongation. The interplay between conductance modes and structural deformation is discussed by means of the eigenchannel transmission probabilities.......We study the deformation and breaking of an atomic-sized sodium wire using density functional simulations. The wire deforms through sudden atomic rearrangements and smoother atomic displacements. The conductance of the wire exhibits plateaus at integer values in units of 2e(2)/h corresponding...

Path probability of stochastic motion: A functional approach

Science.gov (United States)

Hattori, Masayuki; Abe, Sumiyoshi

2016-06-01

The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a tube/band, the center of which is stipulated by a given path, is analytically evaluated in a way analogous to continuous measurements in quantum mechanics. Then, the formalism developed here is applied to the stochastic dynamics of stock price in finance.

A note on iterated function systems with discontinuous probabilities

International Nuclear Information System (INIS)

Jaroszewska, Joanna

2013-01-01

Highlights: ► Certain iterated function system with discontinuous probabilities is discussed. ► Existence of an invariant measure via the Schauder–Tychonov theorem is established. ► Asymptotic stability of the system under examination is proved. -- Abstract: We consider an example of an iterated function system with discontinuous probabilities. We prove that it posses an invariant probability measure. We also prove that it is asymptotically stable provided probabilities are positive

Computational complexity of time-dependent density functional theory

International Nuclear Information System (INIS)

Whitfield, J D; Yung, M-H; Tempel, D G; Aspuru-Guzik, A; Boixo, S

2014-01-01

Time-dependent density functional theory (TDDFT) is rapidly emerging as a premier method for solving dynamical many-body problems in physics and chemistry. The mathematical foundations of TDDFT are established through the formal existence of a fictitious non-interacting system (known as the Kohn–Sham system), which can reproduce the one-electron reduced probability density of the actual system. We build upon these works and show that on the interior of the domain of existence, the Kohn–Sham system can be efficiently obtained given the time-dependent density. We introduce a V-representability parameter which diverges at the boundary of the existence domain and serves to quantify the numerical difficulty of constructing the Kohn-Sham potential. For bounded values of V-representability, we present a polynomial time quantum algorithm to generate the time-dependent Kohn–Sham potential with controllable error bounds. (paper)

Gaze-independent ERP-BCIs: augmenting performance through location-congruent bimodal stimuli

Science.gov (United States)

Thurlings, Marieke E.; Brouwer, Anne-Marie; Van Erp, Jan B. F.; Werkhoven, Peter

2014-01-01

Gaze-independent event-related potential (ERP) based brain-computer interfaces (BCIs) yield relatively low BCI performance and traditionally employ unimodal stimuli. Bimodal ERP-BCIs may increase BCI performance due to multisensory integration or summation in the brain. An additional advantage of bimodal BCIs may be that the user can choose which modality or modalities to attend to. We studied bimodal, visual-tactile, gaze-independent BCIs and investigated whether or not ERP components’ tAUCs and subsequent classification accuracies are increased for (1) bimodal vs. unimodal stimuli; (2) location-congruent vs. location-incongruent bimodal stimuli; and (3) attending to both modalities vs. to either one modality. We observed an enhanced bimodal (compared to unimodal) P300 tAUC, which appeared to be positively affected by location-congruency (p = 0.056) and resulted in higher classification accuracies. Attending either to one or to both modalities of the bimodal location-congruent stimuli resulted in differences between ERP components, but not in classification performance. We conclude that location-congruent bimodal stimuli improve ERP-BCIs, and offer the user the possibility to switch the attended modality without losing performance. PMID:25249947

Unification of field theory and maximum entropy methods for learning probability densities

OpenAIRE

Kinney, Justin B.

2014-01-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy de...

Universal Probability Distribution Function for Bursty Transport in Plasma Turbulence

International Nuclear Information System (INIS)

Sandberg, I.; Benkadda, S.; Garbet, X.; Ropokis, G.; Hizanidis, K.; Castillo-Negrete, D. del

2009-01-01

Bursty transport phenomena associated with convective motion present universal statistical characteristics among different physical systems. In this Letter, a stochastic univariate model and the associated probability distribution function for the description of bursty transport in plasma turbulence is presented. The proposed stochastic process recovers the universal distribution of density fluctuations observed in plasma edge of several magnetic confinement devices and the remarkable scaling between their skewness S and kurtosis K. Similar statistical characteristics of variabilities have been also observed in other physical systems that are characterized by convection such as the x-ray fluctuations emitted by the Cygnus X-1 accretion disc plasmas and the sea surface temperature fluctuations.

Disentangling internal and external factors in bimodal acquisition

NARCIS (Netherlands)

Hulk, A.; Van den Bogaerde, B.

2016-01-01

In this commentary we address some of the internal and external factors which are generally found to interact with purely linguistic factors in the languages of bimodal children, and which we think should be taken into account while analysing the bimodal data.

Spin-Density Functionals from Current-Density Functional Theory and Vice Versa: A Road towards New Approximations

International Nuclear Information System (INIS)

Capelle, K.; Gross, E.

1997-01-01

It is shown that the exchange-correlation functional of spin-density functional theory is identical, on a certain set of densities, with the exchange-correlation functional of current-density functional theory. This rigorous connection is used to construct new approximations of the exchange-correlation functionals. These include a conceptually new generalized-gradient spin-density functional and a nonlocal current-density functional. copyright 1997 The American Physical Society

On the shake-off probability for atomic systems

Energy Technology Data Exchange (ETDEWEB)

Santos, A.C.F., E-mail: toniufrj@gmail.com [Instituto de Física, Universidade Federal do Rio de Janeiro, P.O. Box 68528, 21941-972 Rio de Janeiro, RJ (Brazil); Almeida, D.P. [Departamento de Física, Universidade Federal de Santa Catarina, 88040-900 Florianópolis (Brazil)

2016-07-15

Highlights: • The scope is to find the relationship among SO probabilities, Z and electron density. • A scaling law is suggested, allowing us to find the SO probabilities for atoms. • SO probabilities have been scaled as a function of target Z and polarizability. - Abstract: The main scope in this work has been upon the relationship between shake-off probabilities, target atomic number and electron density. By comparing the saturation values of measured double-to-single photoionization ratios from the literature, a simple scaling law has been found, which allows us to predict the shake-off probabilities for several elements up to Z = 54 within a factor 2. The electron shake-off probabilities accompanying valence shell photoionization have been scaled as a function of the target atomic number, Z, and polarizability, α. This behavior is in qualitative agreement with the experimental results.

Laboratory Density Functionals

OpenAIRE

Giraud, B. G.

2007-01-01

We compare several definitions of the density of a self-bound system, such as a nucleus, in relation with its center-of-mass zero-point motion. A trivial deconvolution relates the internal density to the density defined in the laboratory frame. This result is useful for the practical definition of density functionals.

Non-stationary random vibration analysis of a 3D train-bridge system using the probability density evolution method

Science.gov (United States)

Yu, Zhi-wu; Mao, Jian-feng; Guo, Feng-qi; Guo, Wei

2016-03-01

Rail irregularity is one of the main sources causing train-bridge random vibration. A new random vibration theory for the coupled train-bridge systems is proposed in this paper. First, number theory method (NTM) with 2N-dimensional vectors for the stochastic harmonic function (SHF) of rail irregularity power spectrum density was adopted to determine the representative points of spatial frequencies and phases to generate the random rail irregularity samples, and the non-stationary rail irregularity samples were modulated with the slowly varying function. Second, the probability density evolution method (PDEM) was employed to calculate the random dynamic vibration of the three-dimensional (3D) train-bridge system by a program compiled on the MATLAB® software platform. Eventually, the Newmark-β integration method and double edge difference method of total variation diminishing (TVD) format were adopted to obtain the mean value curve, the standard deviation curve and the time-history probability density information of responses. A case study was presented in which the ICE-3 train travels on a three-span simply-supported high-speed railway bridge with excitation of random rail irregularity. The results showed that compared to the Monte Carlo simulation, the PDEM has higher computational efficiency for the same accuracy, i.e., an improvement by 1-2 orders of magnitude. Additionally, the influences of rail irregularity and train speed on the random vibration of the coupled train-bridge system were discussed.

Proposal for Modified Damage Probability Distribution Functions

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup; Hansen, Peter Friis

1996-01-01

Immidiately following the Estonia disaster, the Nordic countries establishe a project entitled "Safety of Passenger/RoRo Vessels" As part of this project the present proposal for modified damage stability probability distribution functions has been developed. and submitted to "Sub-committee on st......Immidiately following the Estonia disaster, the Nordic countries establishe a project entitled "Safety of Passenger/RoRo Vessels" As part of this project the present proposal for modified damage stability probability distribution functions has been developed. and submitted to "Sub...

Probability and Cumulative Density Function Methods for the Stochastic Advection-Reaction Equation

Energy Technology Data Exchange (ETDEWEB)

Barajas-Solano, David A.; Tartakovsky, Alexandre M.

2018-01-01

We present a cumulative density function (CDF) method for the probabilistic analysis of $d$-dimensional advection-dominated reactive transport in heterogeneous media. We employ a probabilistic approach in which epistemic uncertainty on the spatial heterogeneity of Darcy-scale transport coefficients is modeled in terms of random fields with given correlation structures. Our proposed CDF method employs a modified Large-Eddy-Diffusivity (LED) approach to close and localize the nonlocal equations governing the one-point PDF and CDF of the concentration field, resulting in a $(d + 1)$ dimensional PDE. Compared to the classsical LED localization, the proposed modified LED localization explicitly accounts for the mean-field advective dynamics over the phase space of the PDF and CDF. To illustrate the accuracy of the proposed closure, we apply our CDF method to one-dimensional single-species reactive transport with uncertain, heterogeneous advection velocities and reaction rates modeled as random fields.

The Effect of Incremental Changes in Phonotactic Probability and Neighborhood Density on Word Learning by Preschool Children

Science.gov (United States)

Storkel, Holly L.; Bontempo, Daniel E.; Aschenbrenner, Andrew J.; Maekawa, Junko; Lee, Su-Yeon

2013-01-01

Purpose: Phonotactic probability or neighborhood density has predominately been defined through the use of gross distinctions (i.e., low vs. high). In the current studies, the authors examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method: The authors examined the full range of…

On the probability density interpretation of smoothed Wigner functions

International Nuclear Information System (INIS)

De Aguiar, M.A.M.; Ozorio de Almeida, A.M.

1990-01-01

It has been conjectured that the averages of the Wigner function over phase space volumes, larger than those of minimum uncertainty, are always positive. This is true for Gaussian averaging, so that the Husimi distribution is positive. However, we provide a specific counterexample for the averaging with a discontinuous hat function. The analysis of the specific system of a one-dimensional particle in a box also elucidates the respective advantages of the Wigner and the Husimi functions for the study of the semiclassical limit. The falsification of the averaging conjecture is shown not to depend on the discontinuities of the hat function, by considering the latter as the limit of a sequence of analytic functions. (author)

External field as the functional of inhomogeneous density and the density matrix functional approach

NARCIS (Netherlands)

Bobrov, V.B.; Trigger, S.A.; Vlasov, Y.P.

2012-01-01

Based on the Hohenberg-Kohn lemma and the hypotheses of the density functional existence for the external-field potential, it is shown that the strict result of the density functional theory is the equation of the external-field potential as the density functional. This result leads to the

Orbital functionals in density-matrix- and current-density-functional theory

Energy Technology Data Exchange (ETDEWEB)

Helbig, N

2006-05-15

Density-Functional Theory (DFT), although widely used and very successful in the calculation of several observables, fails to correctly describe strongly correlated materials. In the first part of this work we, therefore, introduce reduced-densitymatrix- functional theory (RDMFT) which is one possible way to treat electron correlation beyond DFT. Within this theory the one-body reduced density matrix (1- RDM) is used as the basic variable. Our main interest is the calculation of the fundamental gap which proves very problematic within DFT. In order to calculate the fundamental gap we generalize RDMFT to fractional particle numbers M by describing the system as an ensemble of an N and an N+1 particle system (with N{<=}M{<=}N+1). For each fixed particle number, M, the total energy is minimized with respect to the natural orbitals and their occupation numbers. This leads to the total energy as a function of M. The derivative of this function with respect to the particle number has a discontinuity at integer particle number which is identical to the gap. In addition, we investigate the necessary and sufficient conditions for the 1- RDM of a system with fractional particle number to be N-representable. Numerical results are presented for alkali atoms, small molecules, and periodic systems. Another problem within DFT is the description of non-relativistic many-electron systems in the presence of magnetic fields. It requires the paramagnetic current density and the spin magnetization to be used as basic variables besides the electron density. However, electron-gas-based functionals of current-spin-density-functional Theory (CSDFT) exhibit derivative discontinuities as a function of the magnetic field whenever a new Landau level is occupied, which makes them difficult to use in practice. Since the appearance of Landau levels is, intrinsically, an orbital effect it is appealing to use orbital-dependent functionals. We have developed a CSDFT version of the optimized

Probability density fittings of corrosion test-data: Implications on ...

Indian Academy of Sciences (India)

Steel-reinforced concrete; probability distribution functions; corrosion ... to be present in the corrosive system at a suitable concentration (Holoway et al 2004; Söylev & ..... voltage, equivalent to voltage drop, across a resistor divided by the ...

Pluto/Charon exploration utilizing a bi-modal PBR nuclear propulsion/power system

Science.gov (United States)

Venetoklis, Peter S.

1995-01-01

The paper describes a Pluto/Charon orbiter utilizing a bi-modal nuclear propulsion and power system based on the Particle Bed Reactor. The orbiter is sized for launch to Nuclear-Safe orbit atop a Titan IV or equivalent launch veicle. The bi-modal system provides thermal propulsion for Earth orbital departure and Pluto orbital capture, and 10 kWe of electric power for payload functions and for in-system maneuvering with ion thrusters. Ion thrusters are used to perform inclination changes about Pluto, a transfer from low Pluto orbit to low Charon orbit, and inclination changes about charon. A nominal payload can be deliverd in as little as 15 years, 1000 kg in 17 years, and close to 2000 kg in 20 years. Scientific return is enormously aided by the availability of up to 10 kWe, due to greater data transfer rates and more/better instruments. The bi-modal system can provide power at Pluto/Charon for 10 or more years, enabling an extremely robust, scientifically rewarding, and cost-effective exploration mission.

Local-scaling density-functional method: Intraorbit and interorbit density optimizations

International Nuclear Information System (INIS)

Koga, T.; Yamamoto, Y.; Ludena, E.V.

1991-01-01

The recently proposed local-scaling density-functional theory provides us with a practical method for the direct variational determination of the electron density function ρ(r). The structure of ''orbits,'' which ensures the one-to-one correspondence between the electron density ρ(r) and the N-electron wave function Ψ({r k }), is studied in detail. For the realization of the local-scaling density-functional calculations, procedures for intraorbit and interorbit optimizations of the electron density function are proposed. These procedures are numerically illustrated for the helium atom in its ground state at the beyond-Hartree-Fock level

Bimodal Networks as Candidates for Electroactive Polymers

DEFF Research Database (Denmark)

Bahrt, Frederikke; Daugaard, Anders Egede; Bejenariu, Anca Gabriela

An alternative network formulation method was adopted in order to obtain a different type of silicone based elastomeric systems - the so-called bimodal networks - using two vinyl-terminated polydimethyl siloxanes (PDMS) of different molecular weight, a labelled crosslinker (3 or 4-functional), an...... themselves between the long chains and show how this leads to unexpectedly good properties for DEAP purposes due both to the low extensibility of the short chains that attach strongly the long chains and to the extensibility of the last ones that retards the rupture process....

Irreducible complexity of iterated symmetric bimodal maps

Directory of Open Access Journals (Sweden)

J. P. Lampreia

2005-01-01

Full Text Available We introduce a tree structure for the iterates of symmetric bimodal maps and identify a subset which we prove to be isomorphic to the family of unimodal maps. This subset is used as a second factor for a ∗-product that we define in the space of bimodal kneading sequences. Finally, we give some properties for this product and study the ∗-product induced on the associated Markov shifts.

The influence of phonotactic probability and neighborhood density on children's production of newly learned words.

Science.gov (United States)

Heisler, Lori; Goffman, Lisa

A word learning paradigm was used to teach children novel words that varied in phonotactic probability and neighborhood density. The effects of frequency and density on speech production were examined when phonetic forms were non-referential (i.e., when no referent was attached) and when phonetic forms were referential (i.e., when a referent was attached through fast mapping). Two methods of analysis were included: (1) kinematic variability of speech movement patterning; and (2) measures of segmental accuracy. Results showed that phonotactic frequency influenced the stability of movement patterning whereas neighborhood density influenced phoneme accuracy. Motor learning was observed in both non-referential and referential novel words. Forms with low phonotactic probability and low neighborhood density showed a word learning effect when a referent was assigned during fast mapping. These results elaborate on and specify the nature of interactivity observed across lexical, phonological, and articulatory domains.

Decision making generalized by a cumulative probability weighting function

Science.gov (United States)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

Phenol-formaldehyde carbon with ordered/disordered bimodal mesoporous structure as high-performance electrode materials for supercapacitors

Science.gov (United States)

Cai, Tingwei; Zhou, Min; Han, Guangshuai; Guan, Shiyou

2013-11-01

A novel phenol-formaldehyde carbon with ordered/disordered bimodal mesoporous structure is synthesized by the facile evaporation induced self-assembly strategy under a basic aqueous condition with SiO2 particles as template. The prepared bimodal mesoporous carbons (BMCs) are composed of ordered mesoporous and disordered mesoporous with diameter of about 3.5 nm and 7.0 nm, respectively. They can be employed as supercapacitor electrodes in H2SO4 aqueous electrolyte after the simple acid-treatment. BMC exhibits an exceptional specific capacitance of 344 F g-1 at the current density of 0.1 A g-1, although it has a relatively low surface area of 722 m2 g-1. And the BMC electrode displays an excellent cycling stability over 10,000 cycles.

Probability functions in the context of signed involutive meadows

NARCIS (Netherlands)

Bergstra, J.A.; Ponse, A.

2016-01-01

The Kolmogorov axioms for probability functions are placed in the context of signed meadows. A completeness theorem is stated and proven for the resulting equational theory of probability calculus. Elementary definitions of probability theory are restated in this framework.

A bimodal biometric identification system

Science.gov (United States)

Laghari, Mohammad S.; Khuwaja, Gulzar A.

2013-03-01

Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

Application of tests of goodness of fit in determining the probability density function for spacing of steel sets in tunnel support system

Directory of Open Access Journals (Sweden)

Farnoosh Basaligheh

2015-12-01

Full Text Available One of the conventional methods for temporary support of tunnels is to use steel sets with shotcrete. The nature of a temporary support system demands a quick installation of its structures. As a result, the spacing between steel sets is not a fixed amount and it can be considered as a random variable. Hence, in the reliability analysis of these types of structures, the selection of an appropriate probability distribution function of spacing of steel sets is essential. In the present paper, the distances between steel sets are collected from an under-construction tunnel and the collected data is used to suggest a proper Probability Distribution Function (PDF for the spacing of steel sets. The tunnel has two different excavation sections. In this regard, different distribution functions were investigated and three common tests of goodness of fit were used for evaluation of each function for each excavation section. Results from all three methods indicate that the Wakeby distribution function can be suggested as the proper PDF for spacing between the steel sets. It is also noted that, although the probability distribution function for two different tunnel sections is the same, the parameters of PDF for the individual sections are different from each other.

Wave-function functionals for the density

International Nuclear Information System (INIS)

Slamet, Marlina; Pan Xiaoyin; Sahni, Viraht

2011-01-01

We extend the idea of the constrained-search variational method for the construction of wave-function functionals ψ[χ] of functions χ. The search is constrained to those functions χ such that ψ[χ] reproduces the density ρ(r) while simultaneously leading to an upper bound to the energy. The functionals are thereby normalized and automatically satisfy the electron-nucleus coalescence condition. The functionals ψ[χ] are also constructed to satisfy the electron-electron coalescence condition. The method is applied to the ground state of the helium atom to construct functionals ψ[χ] that reproduce the density as given by the Kinoshita correlated wave function. The expectation of single-particle operators W=Σ i r i n , n=-2,-1,1,2, W=Σ i δ(r i ) are exact, as must be the case. The expectations of the kinetic energy operator W=-(1/2)Σ i ∇ i 2 , the two-particle operators W=Σ n u n , n=-2,-1,1,2, where u=|r i -r j |, and the energy are accurate. We note that the construction of such functionals ψ[χ] is an application of the Levy-Lieb constrained-search definition of density functional theory. It is thereby possible to rigorously determine which functional ψ[χ] is closer to the true wave function.

Density functional theory

International Nuclear Information System (INIS)

Das, M.P.

1984-07-01

The state of the art of the density functional formalism (DFT) is reviewed. The theory is quantum statistical in nature; its simplest version is the well-known Thomas-Fermi theory. The DFT is a powerful formalism in which one can treat the effect of interactions in inhomogeneous systems. After some introductory material, the DFT is outlined from the two basic theorems, and various generalizations of the theorems appropriate to several physical situations are pointed out. Next, various approximations to the density functionals are presented and some practical schemes, discussed; the approximations include an electron gas of almost constant density and an electron gas of slowly varying density. Then applications of DFT in various diverse areas of physics (atomic systems, plasmas, liquids, nuclear matter) are mentioned, and its strengths and weaknesses are pointed out. In conclusion, more recent developments of DFT are indicated

Bimodal gate-dielectric deposition for improved performance of AlGaN/GaN metal-oxide-semiconductor high-electron-mobility transistors

International Nuclear Information System (INIS)

Pang Liang; Kim, Kyekyoon

2012-01-01

A bimodal deposition scheme combining radiofrequency magnetron sputtering and plasma enhanced chemical vapour deposition (PECVD) is proposed as a means for improving the performance of GaN-based metal-oxide-semiconductor high-electron-mobility transistors (MOSHEMTs). High-density sputtered-SiO 2 is utilized to reduce the gate leakage current and enhance the breakdown voltage while low-density PECVD-SiO 2 is employed to buffer the sputtering damage and further increase the drain current by engineering the stress-induced-polarization. Thus-fabricated MOSHEMT exhibited a low leakage current of 4.21 × 10 -9 A mm -1 and high breakdown voltage of 634 V for a gate-drain distance of 6 µm, demonstrating the promise of bimodal-SiO 2 deposition scheme for the development of GaN-based MOSHEMTs for high-power application. (paper)

Level Densities and Radiative Strength Functions in ⁵⁶FE and ⁵⁷FE

Energy Technology Data Exchange (ETDEWEB)

Tavukcu, Emel [North Carolina State Univ., Raleigh, NC (United States)

2002-12-10

Understanding nuclear level densities and radiative strength functions is important for pure and applied nuclear physics. Recently, the Oslo Cyclotron Group has developed an experimental method to extract level densities and radiative strength functions simultaneously from the primary γ rays after a light-ion reaction. A primary γ-ray spectrum represents the γ-decay probability distribution. The Oslo method is based on the Axel-Brink hypothesis, according to which the primary γ-ray spectrum is proportional to the product of the level density at the final energy and the radiative strength function. The level density and the radiative strength function are fit to the experimental primary γ-ray spectra, and then normalized to known data. The method works well for heavy nuclei. The present measurements extend the Oslo method to the lighter mass nuclei ⁵⁶Fe and ⁵⁷Fe. The experimental level densities in ⁵⁶Fe and ⁵⁷Fe reveal step structure. This step structure is a signature for nucleon pair breaking. The predicted pairing gap parameter is in good agreement with the step corresponding to the first pair breaking. Thermodynamic quantities for ⁵⁶Fe and ⁵⁷Fe are derived within the microcanonical and canonical ensembles using the experimental level densities. Energy-temperature relations are considered using caloric curves and probability density functions. The differences between the thermodynamics of small and large systems are emphasized. The experimental heat capacities are compared with the recent theoretical calculations obtained in the Shell Model Monte Carlo method. Radiative strength functions in ⁵⁶Fe and ⁵⁷Fe have surprisingly high values at low γ-ray energies. This behavior has not been observed for heavy nuclei, but has been observed in other light- and medium-mass nuclei. The origin of this low γ-ray energy effect remains unknown.

Protein distance constraints predicted by neural networks and probability density functions

DEFF Research Database (Denmark)

Lund, Ole; Frimand, Kenneth; Gorodkin, Jan

1997-01-01

We predict interatomic C-α distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taki...... method based on the predicted distances is presented. A homepage with software, predictions and data related to this paper is available at http://www.cbs.dtu.dk/services/CPHmodels/...

High solids emulsions produced by ultrasound as a function of energy density.

Science.gov (United States)

Consoli, Larissa; de Figueiredo Furtado, Guilherme; da Cunha, Rosiane Lopes; Hubinger, Míriam Dupas

2017-09-01

The use of emulsifying methods is frequently required before spray drying food ingredients, where using high concentration of solids increases the drying process yield. In this work, we used ultrasound to obtain kinetically stable palm oil-in-water emulsions with 30g solids/100g of emulsion. Sodium caseinate, maltodextrin and dried glucose syrup were used as stabilizing agents. Sonication time of 3, 7 and 11min were evaluated at power of 72, 105 and 148W (which represents 50%, 75% and 100% of power amplitude in relation to the nominal power of the equipment). Energy density required for each assay was calculated. Emulsions were characterized for droplets mean diameter and size distribution, optical microscopy, confocal microscopy, ζ-potential, creaming index (CI) and rheological behavior. Emulsions presented bimodal size distribution, with D [3,2] ranging from 0.7 to 1.4μm and CI between 5% and 12%, being these parameters inversely proportional to sonication time and power, but with a visual kinetically stabilization after the treatment at 148W at 7min sonication. D [3,2] showed to depend of energy density as a power function. Sonication presented as an effective method to be integrated to spray drying when emulsification is needed before the drying process. Copyright © 2016 Elsevier B.V. All rights reserved.

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

Science.gov (United States)

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

Brain deactivation in the outperformance in bimodal tasks: an FMRI study.

Directory of Open Access Journals (Sweden)

Tzu-Ching Chiang

Full Text Available While it is known that some individuals can effectively perform two tasks simultaneously, other individuals cannot. How the brain deals with performing simultaneous tasks remains unclear. In the present study, we aimed to assess which brain areas corresponded to various phenomena in task performance. Nineteen subjects were requested to sequentially perform three blocks of tasks, including two unimodal tasks and one bimodal task. The unimodal tasks measured either visual feature binding or auditory pitch comparison, while the bimodal task required performance of the two tasks simultaneously. The functional magnetic resonance imaging (fMRI results are compatible with previous studies showing that distinct brain areas, such as the visual cortices, frontal eye field (FEF, lateral parietal lobe (BA7, and medial and inferior frontal lobe, are involved in processing of visual unimodal tasks. In addition, the temporal lobes and Brodmann area 43 (BA43 were involved in processing of auditory unimodal tasks. These results lend support to concepts of modality-specific attention. Compared to the unimodal tasks, bimodal tasks required activation of additional brain areas. Furthermore, while deactivated brain areas were related to good performance in the bimodal task, these areas were not deactivated where the subject performed well in only one of the two simultaneous tasks. These results indicate that efficient information processing does not require some brain areas to be overly active; rather, the specific brain areas need to be relatively deactivated to remain alert and perform well on two tasks simultaneously. Meanwhile, it can also offer a neural basis for biofeedback in training courses, such as courses in how to perform multiple tasks simultaneously.

A Novel Method of Extraction of Blend Component Structure from SANS Measurements of Homopolymer Bimodal Blends.

Science.gov (United States)

Smerdova, Olga; Graham, Richard S; Gasser, Urs; Hutchings, Lian R; De Focatiis, Davide S A

2014-05-01

A new method is presented for the extraction of single-chain form factors and interchain interference functions from a range of small-angle neutron scattering (SANS) experiments on bimodal homopolymer blends. The method requires a minimum of three blends, made up of hydrogenated and deuterated components with matched degree of polymerization at two different chain lengths, but with carefully varying deuteration levels. The method is validated through an experimental study on polystyrene homopolymer bimodal blends with [Formula: see text]. By fitting Debye functions to the structure factors, it is shown that there is good agreement between the molar mass of the components obtained from SANS and from chromatography. The extraction method also enables, for the first time, interchain scattering functions to be produced for scattering between chains of different lengths. [Formula: see text].

Authentically radiolabelled Mn(II) complexes as bimodal PET/MR tracers

Energy Technology Data Exchange (ETDEWEB)

Vanasschen, Christian; Brandt, Marie; Ermert, Johannes [Institute of Neuroscience and Medicine, INM-5 - Nuclear Chemistry, Forschungszentrum Jülich (Germany); Neumaier, Bernd [Institute for Radiochemistry and Experimental Molecular Imaging, Medical Clinics, University of Cologne (Germany); Coenen, Heinz H [Institute of Neuroscience and Medicine, INM-5 - Nuclear Chemistry, Forschungszentrum Jülich (Germany)

2015-05-18

The development of small molecule bimodal PET/MR tracers is mainly hampered by the lack of dedicated preparation methods. Authentic radiolabelling of MR contrast agents ensures easy access to such probes: a ligand, chelating a paramagnetic metal ion (e.g. Mn2+) and the corresponding PET isotope (e.g. 52gMn), leads to a “cocktail mixture” where both imaging reporters exhibit the same pharmacokinetics. Paramagnetic [55Mn(CDTA)]2- shows an excellent compromise between thermodynamic stability, kinetic inertness and MR contrast enhancement. Therefore, the aim of this study was to develop new PET/MR tracers by labelling CDTA ligands with paramagnetic manganese and the β+-emitter 52gMn. N.c.a. 52gMn (t1/2: 5.6 d; Eβ+: 575.8 keV (29.6%)) was produced by proton irradiation of a natCr target followed by cation-exchange chromatography. CDTA was radiolabelled with n.c.a. 52gMn2+ in NaOAc buffer (pH 6) at RT. The complex was purified by RP-HPLC and its stability tested in PBS and blood plasma at 37°C. The redox stability was assessed by monitoring the T1 relaxation (20 MHz) in HEPES buffer (pH 7.4). A functionalized CDTA ligand was synthesized in 5 steps. [52gMn(CDTA)]2- was quantitatively formed within 30 min at RT. The complex was stable for at least 6 days in PBS and blood plasma at 37°C and no oxidation occurred within 7 months storage at RT. Labelling CDTA with an isotopic 52g/55Mn2+ mixture led to the corresponding bimodal PET/MR tracer. Furthermore, a functionalized CDTA ligand was synthesized with an overall yield of 18-25%. [52g/55Mn(CDTA)]2-, the first manganese-based bimodal PET/MR tracer prepared, exhibits excellent stability towards decomplexation and oxidation. This makes the functionalized CDTA ligand highly suitable for designing PET/MR tracers with high relaxivity or targeting properties.

Authentically radiolabelled Mn(II) complexes as bimodal PET/MR tracers

International Nuclear Information System (INIS)

Vanasschen, Christian; Brandt, Marie; Ermert, Johannes; Neumaier, Bernd; Coenen, Heinz H

2015-01-01

The development of small molecule bimodal PET/MR tracers is mainly hampered by the lack of dedicated preparation methods. Authentic radiolabelling of MR contrast agents ensures easy access to such probes: a ligand, chelating a paramagnetic metal ion (e.g. Mn2+) and the corresponding PET isotope (e.g. 52gMn), leads to a “cocktail mixture” where both imaging reporters exhibit the same pharmacokinetics. Paramagnetic [55Mn(CDTA)]2- shows an excellent compromise between thermodynamic stability, kinetic inertness and MR contrast enhancement. Therefore, the aim of this study was to develop new PET/MR tracers by labelling CDTA ligands with paramagnetic manganese and the β+-emitter 52gMn. N.c.a. 52gMn (t1/2: 5.6 d; Eβ+: 575.8 keV (29.6%)) was produced by proton irradiation of a natCr target followed by cation-exchange chromatography. CDTA was radiolabelled with n.c.a. 52gMn2+ in NaOAc buffer (pH 6) at RT. The complex was purified by RP-HPLC and its stability tested in PBS and blood plasma at 37°C. The redox stability was assessed by monitoring the T1 relaxation (20 MHz) in HEPES buffer (pH 7.4). A functionalized CDTA ligand was synthesized in 5 steps. [52gMn(CDTA)]2- was quantitatively formed within 30 min at RT. The complex was stable for at least 6 days in PBS and blood plasma at 37°C and no oxidation occurred within 7 months storage at RT. Labelling CDTA with an isotopic 52g/55Mn2+ mixture led to the corresponding bimodal PET/MR tracer. Furthermore, a functionalized CDTA ligand was synthesized with an overall yield of 18-25%. [52g/55Mn(CDTA)]2-, the first manganese-based bimodal PET/MR tracer prepared, exhibits excellent stability towards decomplexation and oxidation. This makes the functionalized CDTA ligand highly suitable for designing PET/MR tracers with high relaxivity or targeting properties.

Probability distribution functions for intermittent scrape-off layer plasma fluctuations

Science.gov (United States)

Theodorsen, A.; Garcia, O. E.

2018-03-01

A stochastic model for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas has been constructed based on a super-position of uncorrelated pulses arriving according to a Poisson process. In the most common applications of the model, the pulse amplitudes are assumed exponentially distributed, supported by conditional averaging of large-amplitude fluctuations in experimental measurement data. This basic assumption has two potential limitations. First, statistical analysis of measurement data using conditional averaging only reveals the tail of the amplitude distribution to be exponentially distributed. Second, exponentially distributed amplitudes leads to a positive definite signal which cannot capture fluctuations in for example electric potential and radial velocity. Assuming pulse amplitudes which are not positive definite often make finding a closed form for the probability density function (PDF) difficult, even if the characteristic function remains relatively simple. Thus estimating model parameters requires an approach based on the characteristic function, not the PDF. In this contribution, the effect of changing the amplitude distribution on the moments, PDF and characteristic function of the process is investigated and a parameter estimation method using the empirical characteristic function is presented and tested on synthetically generated data. This proves valuable for describing intermittent fluctuations of all plasma parameters in the boundary region of magnetized plasmas.

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-03-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , S st , p st ) for stochastic uncertainty, a probability space (S su , S su , p su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , S st , p st ) and (S su , S su , p su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the U.S. Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-01-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , L st , P st ) for stochastic uncertainty, a probability space (S su , L su , P su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , L st , P st ) and (S su , L su , P su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the US Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems

Penetration in bimodal, polydisperse granular material

KAUST Repository

Kouraytem, Nadia; Thoroddsen, Sigurdur T; Marston, J. O.

2016-01-01

We investigate the impact penetration of spheres into granular media which are compositions of two discrete size ranges, thus creating a polydisperse bimodal material. We examine the penetration depth as a function of the composition (volume fractions of the respective sizes) and impact speed. Penetration depths were found to vary between delta = 0.5D(0) and delta = 7D(0), which, for mono-modal media only, could be correlated in terms of the total drop height, H = h + delta, as in previous studies, by incorporating correction factors for the packing fraction. Bimodal data can only be collapsed by deriving a critical packing fraction for each mass fraction. The data for the mixed grains exhibit a surprising lubricating effect, which was most significant when the finest grains [d(s) similar to O(30) mu m] were added to the larger particles [d(l) similar to O(200 - 500) mu m], with a size ratio, epsilon = d(l)/d(s), larger than 3 and mass fractions over 25%, despite the increased packing fraction. We postulate that the small grains get between the large grains and reduce their intergrain friction, only when their mass fraction is sufficiently large to prevent them from simply rattling in the voids between the large particles. This is supported by our experimental observations of the largest lubrication effect produced by adding small glass beads to a bed of large sand particles with rough surfaces.

Penetration in bimodal, polydisperse granular material

KAUST Repository

Kouraytem, N.

2016-11-07

We investigate the impact penetration of spheres into granular media which are compositions of two discrete size ranges, thus creating a polydisperse bimodal material. We examine the penetration depth as a function of the composition (volume fractions of the respective sizes) and impact speed. Penetration depths were found to vary between delta = 0.5D(0) and delta = 7D(0), which, for mono-modal media only, could be correlated in terms of the total drop height, H = h + delta, as in previous studies, by incorporating correction factors for the packing fraction. Bimodal data can only be collapsed by deriving a critical packing fraction for each mass fraction. The data for the mixed grains exhibit a surprising lubricating effect, which was most significant when the finest grains [d(s) similar to O(30) mu m] were added to the larger particles [d(l) similar to O(200 - 500) mu m], with a size ratio, epsilon = d(l)/d(s), larger than 3 and mass fractions over 25%, despite the increased packing fraction. We postulate that the small grains get between the large grains and reduce their intergrain friction, only when their mass fraction is sufficiently large to prevent them from simply rattling in the voids between the large particles. This is supported by our experimental observations of the largest lubrication effect produced by adding small glass beads to a bed of large sand particles with rough surfaces.

Bimodality and negative heat capacity in multifragmentation

International Nuclear Information System (INIS)

Tamain, B.; Bougault, R.; Lopez, O.; Pichon, M.

2003-01-01

This contribution addresses the question of the possible link between multifragmentation and the liquid-gas phase transition of nuclear matter. Bi-modality seems to be a robust signal of this link in the sense that theoretical calculations indicate that it is preserved even if a sizeable fraction of the available energy has not been shared among all the degrees of freedom. The corresponding measured properties are coherent with what is expected in a liquid-gas phase transition picture. Moreover, bi-modality and negative heat capacity are observed for the same set of events. (authors)

Asymmetric Bimodal Exponential Power Distribution on the Real Line

Directory of Open Access Journals (Sweden)

Mehmet Niyazi Çankaya

2018-01-01

Full Text Available The asymmetric bimodal exponential power (ABEP distribution is an extension of the generalized gamma distribution to the real line via adding two parameters that fit the shape of peakedness in bimodality on the real line. The special values of peakedness parameters of the distribution are a combination of half Laplace and half normal distributions on the real line. The distribution has two parameters fitting the height of bimodality, so capacity of bimodality is enhanced by using these parameters. Adding a skewness parameter is considered to model asymmetry in data. The location-scale form of this distribution is proposed. The Fisher information matrix of these parameters in ABEP is obtained explicitly. Properties of ABEP are examined. Real data examples are given to illustrate the modelling capacity of ABEP. The replicated artificial data from maximum likelihood estimates of parameters of ABEP and other distributions having an algorithm for artificial data generation procedure are provided to test the similarity with real data. A brief simulation study is presented.

Density functionals from deep learning

OpenAIRE

McMahon, Jeffrey M.

2016-01-01

Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep learning is developed to approximate this functional. Deep learning allows computational models that are capable of naturally discovering intricate structure in large and/or high-dimensional data sets, with multiple levels of abstraction. As no assumptions are ...

Visualisation and characterisation of heterogeneous bimodal PDMS networks

DEFF Research Database (Denmark)

Bahrt, Frederikke; Daugaard, Anders Egede; Fleury, Clemence

2014-01-01

The existence of short-chain domains in heterogeneous bimodal PDMS networks has been confirmed visually, for the first time, through confocal fluorescence microscopy. The networks were prepared using a controlled reaction scheme where short PDMS chains were reacted below the gelation point...... bimodal networks with short-chain domains within a long-chain network. The average sizes of the short-chain domains were found to vary from 2.1 to 5.7 mm depending on the short-chain content. The visualised network structure could be correlated thereafter to the elastic properties, which were determined...... by rheology. All heterogeneous bimodal networks displayed significantly lower moduli than mono-modal PDMS elastomers prepared from the long polymer chains. Low-loss moduli as well as low-sol fractions indicate that low-elastic moduli can be obtained without compromising the network's structure...

Use of density functional theory in drug metabolism studies

DEFF Research Database (Denmark)

Rydberg, Patrik; Jørgensen, Flemming Steen; Olsen, Lars

2014-01-01

INTRODUCTION: The cytochrome P450 enzymes (CYPs) metabolize many drug compounds. They catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be generated. Density functional theory (DFT) has, over the past decade, been shown to be a powerful tool...... isoforms. This is probably due to the fact that the binding of the substrates is not the major determinant. When binding of the substrate plays a significant role, the well-known issue of determining the free energy of binding is the challenge. How approaches taking the protein environment into account...

Probability Density Functions for the CALIPSO Lidar Version 4 Cloud-Aerosol Discrimination (CAD) Algorithm

Science.gov (United States)

Liu, Z.; Kar, J.; Zeng, S.; Tackett, J. L.; Vaughan, M.; Trepte, C. R.; Omar, A. H.; Hu, Y.; Winker, D. M.

2017-12-01

In the CALIPSO retrieval algorithm, detection layers in the lidar measurements is followed by their classification as a "cloud" or "aerosol" using 5-dimensional probability density functions (PDFs). The five dimensions are the mean attenuated backscatter at 532 nm, the layer integrated total attenuated color ratio, the mid-layer altitude, integrated volume depolarization ratio and latitude. The new version 4 (V4) level 2 (L2) data products, released in November 2016, are the first major revision to the L2 product suite since May 2010. Significant calibration changes in the V4 level 1 data necessitated substantial revisions to the V4 L2 CAD algorithm. Accordingly, a new set of PDFs was generated to derive the V4 L2 data products. The V4 CAD algorithm is now applied to layers detected in the stratosphere, where volcanic layers and occasional cloud and smoke layers are observed. Previously, these layers were designated as `stratospheric', and not further classified. The V4 CAD algorithm is also applied to all layers detected at single shot (333 m) resolution. In prior data releases, single shot detections were uniformly classified as clouds. The CAD PDFs used in the earlier releases were generated using a full year (2008) of CALIPSO measurements. Because the CAD algorithm was not applied to stratospheric features, the properties of these layers were not incorporated into the PDFs. When building the V4 PDFs, the 2008 data were augmented with additional data from June 2011, and all stratospheric features were included. The Nabro and Puyehue-Cordon volcanos erupted in June 2011, and volcanic aerosol layers were observed in the upper troposphere and lower stratosphere in both the northern and southern hemispheres. The June 2011 data thus provides the stratospheric aerosol properties needed for comprehensive PDF generation. In contrast to earlier versions of the PDFs, which were generated based solely on observed distributions, construction of the V4 PDFs considered the

Momentum Probabilities for a Single Quantum Particle in Three-Dimensional Regular "Infinite" Wells: One Way of Promoting Understanding of Probability Densities

Science.gov (United States)

Riggs, Peter J.

2013-01-01

Students often wrestle unsuccessfully with the task of correctly calculating momentum probability densities and have difficulty in understanding their interpretation. In the case of a particle in an "infinite" potential well, its momentum can take values that are not just those corresponding to the particle's quantised energies but…

Bimodal magmatism produced by progressively inhibited crustal assimilation 2 (PICA)

NARCIS (Netherlands)

Meade, F.C.; Troll, V.R.; Ellam, R.M.; Freda, C.; Font Morales, L.; Donaldson, C.H.; Klonowska, I.

2014-01-01

The origin of bimodal (mafic-felsic) rock suites is a fundamental question in volcanology. Here we use major and trace elements, high-resolution Sr, Nd and Pb isotope analyses, experimental petrology and thermodynamic modelling to investigate bimodal magmatism at the iconic Carlingford Igneous

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

Science.gov (United States)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been

On the self-organizing process of large scale shear flows

Energy Technology Data Exchange (ETDEWEB)

Newton, Andrew P. L. [Department of Applied Maths, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Kim, Eun-jin [School of Mathematics and Statistics, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Liu, Han-Li [High Altitude Observatory, National Centre for Atmospheric Research, P. O. BOX 3000, Boulder, Colorado 80303-3000 (United States)

2013-09-15

Self organization is invoked as a paradigm to explore the processes governing the evolution of shear flows. By examining the probability density function (PDF) of the local flow gradient (shear), we show that shear flows reach a quasi-equilibrium state as its growth of shear is balanced by shear relaxation. Specifically, the PDFs of the local shear are calculated numerically and analytically in reduced 1D and 0D models, where the PDFs are shown to converge to a bimodal distribution in the case of finite correlated temporal forcing. This bimodal PDF is then shown to be reproduced in nonlinear simulation of 2D hydrodynamic turbulence. Furthermore, the bimodal PDF is demonstrated to result from a self-organizing shear flow with linear profile. Similar bimodal structure and linear profile of the shear flow are observed in gulf stream, suggesting self-organization.

Microstructure, plastic deformation and strengthening mechanisms of an Al–Mg–Si alloy with a bimodal grain structure

International Nuclear Information System (INIS)

Shakoori Oskooie, M.; Asgharzadeh, H.; Kim, H.S.

2015-01-01

Highlights: • Al6063 with bimodal grain structures was fabricated by a powder metallurgy route. • The bimodal alloys showed a reasonable ductility together with a high strength. • Grain boundary strengthening was reduced at higher fraction of coarse grains. • The enhanced tensile ductility was attributed to crack blunting and delamination. - Abstract: Al6063 alloys with bimodal grain size distributions comprised of ultrafine-grained (UFG) and coarse-grained (CG) regions were produced via mechanical milling followed by hot extrusion. High-energy planetary ball milling for 22.5 h with a rotational speed of 350 rpm was employed for the synthesis of nanocrystalline Al6063 powders. The as-milled Al6063 powders were mixed with 15, 30, and 45 vol.% of the unmilled powders and then the powder mixtures were consolidated via extrusion at 450 °C with an extrusion ratio of 9:1. The microstructure of the bimodal extrudates was investigated using optical microscope, transmission electron microscope (TEM) and field emission scanning electron microscope equipped with an electron backscattered diffraction (EBSD) detector. The deformation behavior was investigated by means of uniaxial tensile tests. The bimodal Al6063 exhibited balanced mechanical properties, including high yield stress and ultimate tensile strength resulting from the UFG regions together with reasonable ductility attained from the CG areas. The fracture surfaces demonstrated a ductile fracture mode, in which the dimple size was correlated with the grain structure. The strengthening mechanisms are discussed based on the dislocation models and the functions of the CGs in the deformation behavior and ductility enhancement of bimodal Al6063 are explored

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

Energy Technology Data Exchange (ETDEWEB)

Helton, J.C. [Arizona State Univ., Tempe, AZ (United States)

1996-03-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S{sub st}, S{sub st}, p{sub st}) for stochastic uncertainty, a probability space (S{sub su}, S{sub su}, p{sub su}) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S{sub st}, S{sub st}, p{sub st}) and (S{sub su}, S{sub su}, p{sub su}). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the U.S. Environmental Protection Agency`s standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems.

The maximum entropy method of moments and Bayesian probability theory

Science.gov (United States)

Bretthorst, G. Larry

2013-08-01

The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.

Probability density of tunneled carrier states near heterojunctions calculated numerically by the scattering method.

Energy Technology Data Exchange (ETDEWEB)

Wampler, William R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Myers, Samuel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Modine, Normand A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

The energy-dependent probability density of tunneled carrier states for arbitrarily specified longitudinal potential-energy profiles in planar bipolar devices is numerically computed using the scattering method. Results agree accurately with a previous treatment based on solution of the localized eigenvalue problem, where computation times are much greater. These developments enable quantitative treatment of tunneling-assisted recombination in irradiated heterojunction bipolar transistors, where band offsets may enhance the tunneling effect by orders of magnitude. The calculations also reveal the density of non-tunneled carrier states in spatially varying potentials, and thereby test the common approximation of uniform- bulk values for such densities.

Multicomponent density functional theory embedding formulation

Energy Technology Data Exchange (ETDEWEB)

Culpitt, Tanner; Brorsen, Kurt R.; Pak, Michael V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu [Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Ave, Urbana, Illinois 61801 (United States)

2016-07-28

Multicomponent density functional theory (DFT) methods have been developed to treat two types of particles, such as electrons and nuclei, quantum mechanically at the same level. In the nuclear-electronic orbital (NEO) approach, all electrons and select nuclei, typically key protons, are treated quantum mechanically. For multicomponent DFT methods developed within the NEO framework, electron-proton correlation functionals based on explicitly correlated wavefunctions have been designed and used in conjunction with well-established electronic exchange-correlation functionals. Herein a general theory for multicomponent embedded DFT is developed to enable the accurate treatment of larger systems. In the general theory, the total electronic density is separated into two subsystem densities, denoted as regular and special, and different electron-proton correlation functionals are used for these two electronic densities. In the specific implementation, the special electron density is defined in terms of spatially localized Kohn-Sham electronic orbitals, and electron-proton correlation is included only for the special electron density. The electron-proton correlation functional depends on only the special electron density and the proton density, whereas the electronic exchange-correlation functional depends on the total electronic density. This scheme includes the essential electron-proton correlation, which is a relatively local effect, as well as the electronic exchange-correlation for the entire system. This multicomponent DFT-in-DFT embedding theory is applied to the HCN and FHF{sup −} molecules in conjunction with two different electron-proton correlation functionals and three different electronic exchange-correlation functionals. The results illustrate that this approach provides qualitatively accurate nuclear densities in a computationally tractable manner. The general theory is also easily extended to other types of partitioning schemes for multicomponent systems.

Event-related potentials to visual, auditory, and bimodal (combined auditory-visual) stimuli.

Science.gov (United States)

Isoğlu-Alkaç, Ummühan; Kedzior, Karina; Keskindemirci, Gonca; Ermutlu, Numan; Karamursel, Sacit

2007-02-01

The purpose of this study was to investigate the response properties of event related potentials to unimodal and bimodal stimulations. The amplitudes of N1 and P2 were larger during bimodal evoked potentials (BEPs) than auditory evoked potentials (AEPs) in the anterior sites and the amplitudes of P1 were larger during BEPs than VEPs especially at the parieto-occipital locations. Responses to bimodal stimulation had longer latencies than responses to unimodal stimulation. The N1 and P2 components were larger in amplitude and longer in latency during the bimodal paradigm and predominantly occurred at the anterior sites. Therefore, the current bimodal paradigm can be used to investigate the involvement and location of specific neural generators that contribute to higher processing of sensory information. Moreover, this paradigm may be a useful tool to investigate the level of sensory dysfunctions in clinical samples.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean

Energy Technology Data Exchange (ETDEWEB)

Razooky, Brandon S. [Rockefeller Univ., New York, NY (United States). Lab. of Virology and Infectious Disease; Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Cao, Youfang [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hansen, Maike M. K. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Perelson, Alan S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Simpson, Michael L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Weinberger, Leor S. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States). Dept. of Biochemistry and Biophysics; Univ. of California, San Francisco, CA (United States). QB3: California Inst. of Quantitative Biosciences; Univ. of California, San Francisco, CA (United States). Dept. of Pharmaceutical Chemistry

2017-10-18

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where two alternate expression states simultaneously exist. Here in this study, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV Tat protein manipulates the intrinsic toggling of HIV’s promoter, the LTR, to generate bimodal ON-OFF expression, and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit’s non-cooperative ‘non-latching’ feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that non-latching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean-expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.

A HYPOTHESIS FOR THE COLOR BIMODALITY OF JUPITER TROJANS

Energy Technology Data Exchange (ETDEWEB)

Wong, Ian; Brown, Michael E., E-mail: iwong@caltech.edu [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 (United States)

2016-10-01

One of the most enigmatic and hitherto unexplained properties of Jupiter Trojans is their bimodal color distribution. This bimodality is indicative of two sub-populations within the Trojans, which have distinct size distributions. In this paper, we present a simple, plausible hypothesis for the origin and evolution of the two Trojan color sub-populations. In the framework of dynamical instability models of early solar system evolution, which suggest a common primordial progenitor population for both Trojans and Kuiper Belt objects, we use observational constraints to assert that the color bimodalities evident in both minor body populations developed within the primordial population prior to the onset of instability. We show that, beginning with an initial composition of rock and ices, location-dependent volatile loss through sublimation in this primordial population could have led to sharp changes in the surface composition with heliocentric distance. We propose that the depletion or retention of H{sub 2}S ice on the surface of these objects was the key factor in creating an initial color bimodality. Objects that retained H{sub 2}S on their surfaces developed characteristically redder colors upon irradiation than those that did not. After the bodies from the primordial population were scattered and emplaced into their current positions, they preserved this primordial color bimodality to the present day. We explore predictions of the volatile loss model—in particular, the effect of collisions within the Trojan population on the size distributions of the two sub-populations—and propose further experimental and observational tests of our hypothesis.

A HYPOTHESIS FOR THE COLOR BIMODALITY OF JUPITER TROJANS

International Nuclear Information System (INIS)

Wong, Ian; Brown, Michael E.

2016-01-01

One of the most enigmatic and hitherto unexplained properties of Jupiter Trojans is their bimodal color distribution. This bimodality is indicative of two sub-populations within the Trojans, which have distinct size distributions. In this paper, we present a simple, plausible hypothesis for the origin and evolution of the two Trojan color sub-populations. In the framework of dynamical instability models of early solar system evolution, which suggest a common primordial progenitor population for both Trojans and Kuiper Belt objects, we use observational constraints to assert that the color bimodalities evident in both minor body populations developed within the primordial population prior to the onset of instability. We show that, beginning with an initial composition of rock and ices, location-dependent volatile loss through sublimation in this primordial population could have led to sharp changes in the surface composition with heliocentric distance. We propose that the depletion or retention of H 2 S ice on the surface of these objects was the key factor in creating an initial color bimodality. Objects that retained H 2 S on their surfaces developed characteristically redder colors upon irradiation than those that did not. After the bodies from the primordial population were scattered and emplaced into their current positions, they preserved this primordial color bimodality to the present day. We explore predictions of the volatile loss model—in particular, the effect of collisions within the Trojan population on the size distributions of the two sub-populations—and propose further experimental and observational tests of our hypothesis.

'Bimodal' NTR and LANTR propulsion for human missions to Mars/Phobos

International Nuclear Information System (INIS)

Borowski, Stanley K.; Dudzinski, Leonard A.; McGuire, Melissa L.

1999-01-01

The nuclear thermal rocket (NTR) is one of the leading propulsion options for future human missions to Mars due to its high specific impulse (Isp ∼850-1000 s) and attractive engine thrust-to-weight ratio (∼3-10). Because only a miniscule amount of enriched uranium-235 fuel is consumed in a NTR during the primary propulsion maneuvers of a typical Mars mission, engines configured for both propulsive thrust and modest power generation (referred to as 'bimodal' operation) provide the basis for a robust, 'power-rich' stage enabling propulsive Mars capture and reuse capability. A family of modular 'bimodal' NTR (BNTR) vehicles are described which utilize a common 'core' stage powered by three 66.7 kN (∼15 klbf) BNTRs that produce 50 kWe of total electrical power for crew life support, an active refrigeration/reliquification system for long term, 'zero-boiloff' liquid hydrogen (LH 2 ) storage, and high data rate communications. Compared to other propulsion options, a Mars mission architecture using BNTR transfer vehicles requires fewer transportation system elements which reduces mission mass, cost and risk because of simplified space operations. For difficult Mars options, such as a Phobos rendezvous and sample return mission, volume (not mass) constraints limit the performance of the 'all LH 2 ' BNTR stage. The use of ''LOX-augmented' NTR (LANTR) engines, operating at a modest oxygen-to-hydrogen (O/H) mixture ratio (MR) of 0.5, helps to increase 'bulk' propellant density and total thrust during the trans-Mars injection (TMI) burn. On all subsequent burns, the bimodal LANTR engines operate on LH 2 only (MR=0) to maximize vehicle performance while staying within the mass limits of two ∼80 t 'Magnum' heavy lift launch vehicles (HLLVs)

Nuclear level density and gamma strength function in 64Fe

Science.gov (United States)

Smith, M. K.; Spyrou, A.; Ahn, T.; Dombos, A. C.; Liddick, S. N.; Montes, F.; Naqvi, F.; Richman, D.; Schatz, H.; Brown, J.; Childers, K.; Crider, B. P.; Prokop, C. J.; Deleeuw, E.; Deyoung, P. A.; Langer, C.; Lewis, R.; Meisel, Z.; Pereira, J.; Quinn, S. J.; Schmidt, K.; Larsen, A. C.; Guttormsen, M.

2017-09-01

The Fe-Cd mass region exhibits enhanced collectivity and an unexpected increased in gamma-decay probability at low energies. These effects could be significant for r-process nucleosynthesis, where masses, beta-decay probabilities, and neutron capture cross sections are among the most important inputs. Neutron capture is notoriously difficult to measure; so the recent development of an indirect technique to constrain neutron-captures far from stability is especially valuable. This is the beta-Oslo method, which allows the extraction of the nuclear level density and gamma-ray strength function to compute neutron-capture cross sections. This work reports on 64Fe, populated via beta-decay of 64Mn at the National Superconducting Cyclotron Laboratory and measured with the 4pi Summing NaI (SuN) total gamma-ray spectrometer.

Wigner function and the probability representation of quantum states

Directory of Open Access Journals (Sweden)

Man’ko Margarita A.

2014-01-01

Full Text Available The relation of theWigner function with the fair probability distribution called tomographic distribution or quantum tomogram associated with the quantum state is reviewed. The connection of the tomographic picture of quantum mechanics with the integral Radon transform of the Wigner quasidistribution is discussed. The Wigner–Moyal equation for the Wigner function is presented in the form of kinetic equation for the tomographic probability distribution both in quantum mechanics and in the classical limit of the Liouville equation. The calculation of moments of physical observables in terms of integrals with the state tomographic probability distributions is constructed having a standard form of averaging in the probability theory. New uncertainty relations for the position and momentum are written in terms of optical tomograms suitable for directexperimental check. Some recent experiments on checking the uncertainty relations including the entropic uncertainty relations are discussed.

Time shift in slope failure prediction between unimodal and bimodal modeling approaches

Science.gov (United States)

Ciervo, Fabio; Casini, Francesca; Nicolina Papa, Maria; Medina, Vicente

2016-04-01

Together with the need to use more appropriate mathematical expressions for describing hydro-mechanical soil processes, a challenge issue relates to the need of considering the effects induced by terrain heterogeneities on the physical mechanisms, taking into account the implications of the heterogeneities in affecting time-dependent hydro-mechanical variables, would improve the prediction capacities of models, such as the ones used in early warning systems. The presence of the heterogeneities in partially-saturated slopes results in irregular propagation of the moisture and suction front. To mathematically represent the "dual-implication" generally induced by the heterogeneities in describing the hydraulic terrain behavior, several bimodal hydraulic models have been presented in literature and replaced the conventional sigmoidal/unimodal functions; this presupposes that the scale of the macrostructure is comparable with the local scale (Darcy scale), thus the Richards' model can be assumed adequate to mathematically reproduce the processes. The purpose of this work is to focus on the differences in simulating flow infiltration processes and slope stability conditions originated from preliminary choices of hydraulic models and contextually between different approaches to evaluate the factor of safety (FoS). In particular, the results of two approaches are compared. The first one includes the conventional expression of the FoS under saturated conditions and the widespread used hydraulic model of van Genuchten-Mualem. The second approach includes a generalized FoS equation for infinite-slope model under variably saturated soil conditions (Lu and Godt, 2008) and the bimodal Romano et al.'s (2011) functions to describe the hydraulic response. The extension of the above mentioned approach to the bimodal context is based on an analytical method to assess the effects of the hydraulic properties on soil shear developed integrating a bimodal lognormal hydraulic function

The H-Function and Probability Density Functions of Certain Algebraic Combinations of Independent Random Variables with H-Function Probability Distribution

Science.gov (United States)

1981-05-01

Education, 10 (2), A45-A49 (1976). 48. Rain&, R. K., and C. L. Kaul (Koul), "Some inequalities involving the Fox’s H- function," Proceedings of the Indian...1973). 51. Srivastava , A., and K. C. Gupta, "On certain recurrence rela- tions," Mathematische Nachrichten, 46, 13- 23 (1970), 49, 187- 197 (1971). 52...34 Vilnana Parishad Anusandhan Patrika, 10, 205- 217 (1967). 69. Gupta, K. C., and A. Srivastava , "On finite expansions for the H- function," Indian Journal

Structure of solvent-free grafted nanoparticles: Molecular dynamics and density-functional theory

KAUST Repository

Chremos, Alexandros

2011-01-01

The structure of solvent-free oligomer-grafted nanoparticles has been investigated using molecular dynamics simulations and density-functional theory. At low temperatures and moderate to high oligomer lengths, the qualitative features of the core particle pair probability, structure factor, and the oligomer brush configuration obtained from the simulations can be explained by a density-functional theory that incorporates the configurational entropy of the space-filling oligomers. In particular, the structure factor at small wave numbers attains a value much smaller than the corresponding hard-sphere suspension, the first peak of the pair distribution function is enhanced due to entropic attractions among the particles, and the oligomer brush expands with decreasing particle volume fraction to fill the interstitial space. At higher temperatures, the simulations reveal effects that differ from the theory and are likely caused by steric repulsions of the expanded corona chains. © 2011 American Institute of Physics.

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

Science.gov (United States)

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Magnetic fields and density functional theory

Energy Technology Data Exchange (ETDEWEB)

Salsbury Jr., Freddie [Univ. of California, Berkeley, CA (United States)

1999-02-01

A major focus of this dissertation is the development of functionals for the magnetic susceptibility and the chemical shielding within the context of magnetic field density functional theory (BDFT). These functionals depend on the electron density in the absence of the field, which is unlike any other treatment of these responses. There have been several advances made within this theory. The first of which is the development of local density functionals for chemical shieldings and magnetic susceptibilities. There are the first such functionals ever proposed. These parameters have been studied by constructing functionals for the current density and then using the Biot-Savart equations to obtain the responses. In order to examine the advantages and disadvantages of the local functionals, they were tested numerically on some small molecules.

Magnetic fields and density functional theory

International Nuclear Information System (INIS)

Salsbury, Freddie Jr.

1999-01-01

A major focus of this dissertation is the development of functionals for the magnetic susceptibility and the chemical shielding within the context of magnetic field density functional theory (BDFT). These functionals depend on the electron density in the absence of the field, which is unlike any other treatment of these responses. There have been several advances made within this theory. The first of which is the development of local density functionals for chemical shieldings and magnetic susceptibilities. There are the first such functionals ever proposed. These parameters have been studied by constructing functionals for the current density and then using the Biot-Savart equations to obtain the responses. In order to examine the advantages and disadvantages of the local functionals, they were tested numerically on some small molecules

BDVC (Bimodal Database of Violent Content): A database of violent audio and video

Science.gov (United States)

Rivera Martínez, Jose Luis; Mijes Cruz, Mario Humberto; Rodríguez Vázqu, Manuel Antonio; Rodríguez Espejo, Luis; Montoya Obeso, Abraham; García Vázquez, Mireya Saraí; Ramírez Acosta, Alejandro Álvaro

2017-09-01

Nowadays there is a trend towards the use of unimodal databases for multimedia content description, organization and retrieval applications of a single type of content like text, voice and images, instead bimodal databases allow to associate semantically two different types of content like audio-video, image-text, among others. The generation of a bimodal database of audio-video implies the creation of a connection between the multimedia content through the semantic relation that associates the actions of both types of information. This paper describes in detail the used characteristics and methodology for the creation of the bimodal database of violent content; the semantic relationship is stablished by the proposed concepts that describe the audiovisual information. The use of bimodal databases in applications related to the audiovisual content processing allows an increase in the semantic performance only and only if these applications process both type of content. This bimodal database counts with 580 audiovisual annotated segments, with a duration of 28 minutes, divided in 41 classes. Bimodal databases are a tool in the generation of applications for the semantic web.

Density dependence of the nuclear energy-density functional

Science.gov (United States)

Papakonstantinou, Panagiota; Park, Tae-Sun; Lim, Yeunhwan; Hyun, Chang Ho

2018-01-01

Background: The explicit density dependence in the coupling coefficients entering the nonrelativistic nuclear energy-density functional (EDF) is understood to encode effects of three-nucleon forces and dynamical correlations. The necessity for the density-dependent coupling coefficients to assume the form of a preferably small fractional power of the density ρ is empirical and the power is often chosen arbitrarily. Consequently, precision-oriented parametrizations risk overfitting in the regime of saturation and extrapolations in dilute or dense matter may lose predictive power. Purpose: Beginning with the observation that the Fermi momentum kF, i.e., the cubic root of the density, is a key variable in the description of Fermi systems, we first wish to examine if a power hierarchy in a kF expansion can be inferred from the properties of homogeneous matter in a domain of densities, which is relevant for nuclear structure and neutron stars. For subsequent applications we want to determine a functional that is of good quality but not overtrained. Method: For the EDF, we fit systematically polynomial and other functions of ρ1 /3 to existing microscopic, variational calculations of the energy of symmetric and pure neutron matter (pseudodata) and analyze the behavior of the fits. We select a form and a set of parameters, which we found robust, and examine the parameters' naturalness and the quality of resulting extrapolations. Results: A statistical analysis confirms that low-order terms such as ρ1 /3 and ρ2 /3 are the most relevant ones in the nuclear EDF beyond lowest order. It also hints at a different power hierarchy for symmetric vs. pure neutron matter, supporting the need for more than one density-dependent term in nonrelativistic EDFs. The functional we propose easily accommodates known or adopted properties of nuclear matter near saturation. More importantly, upon extrapolation to dilute or asymmetric matter, it reproduces a range of existing microscopic

Development of a Prototype Web GIS-Based Disaster Management System for Safe Operation of the Next Generation Bimodal Tram, South Korea—Focused Flooding and Snowfall

Directory of Open Access Journals (Sweden)

Won Seok Jang

2014-04-01

Full Text Available The Korea Railroad Research Institute (KRRI has developed a bimodal tram and advanced bus rapid transit (BRT system which is an optimized public transit system created by mixing the railway’s punctual operation and the bus’ easy and convenient access. The bimodal tram system provides mass-transportation service with an eco-friendly and human-centered approach. Natural disasters have been increasing worldwide in recent years, including floods, snow, and typhoons disasters. Flooding is the most frequent natural disaster in many countries and is increasingly a concern with climate change; it seriously affects people’s lives and productivity, causing considerable economic loss and significant damage. Enhanced conventional disaster management systems are needed to support comprehensive actions to secure safety and convenience. The objective of this study is to develop a prototype version of a Web GIS-based bimodal tram disaster management system (BTDMS using the Storm Water Management Model (SWMM 5.0 to enhance on-time operation and safety of the bimodal tram system. The BTDMS was tested at the bimodal tram test railroad by simulating probable maximum flood (PMF and snow melting for forecasting flooding and snow covered roads. This result could provide the basis for plans to protect against flooding disasters and snow covered roads in operating the bimodal tram system. The BTDMS will be used to assess and predict weather impacts on roadway conditions and operations and thus has the potential to influence economic growth. The methodology presented in this paper makes it possible to manage impacts of flooding and snowfall on urban transportation and enhance operation of the bimodal tram system. Such a methodology based on modeling could be created for most metropolitan areas in Korea and in many other countries.

Learning Grasp Affordance Densities

DEFF Research Database (Denmark)

Detry, Renaud; Kraft, Dirk; Kroemer, Oliver

2011-01-01

and relies on kernel density estimation to provide a continuous model. Grasp densities are learned and refined from exploration, by letting a robot “play” with an object in a sequence of graspand-drop actions: The robot uses visual cues to generate a set of grasp hypotheses; it then executes......We address the issue of learning and representing object grasp affordance models. We model grasp affordances with continuous probability density functions (grasp densities) which link object-relative grasp poses to their success probability. The underlying function representation is nonparametric...... these and records their outcomes. When a satisfactory number of grasp data is available, an importance-sampling algorithm turns these into a grasp density. We evaluate our method in a largely autonomous learning experiment run on three objects of distinct shapes. The experiment shows how learning increases success...

Speech Recognition and Cognitive Skills in Bimodal Cochlear Implant Users

Science.gov (United States)

Hua, Håkan; Johansson, Björn; Magnusson, Lennart; Lyxell, Björn; Ellis, Rachel J.

2017-01-01

Purpose: To examine the relation between speech recognition and cognitive skills in bimodal cochlear implant (CI) and hearing aid users. Method: Seventeen bimodal CI users (28-74 years) were recruited to the study. Speech recognition tests were carried out in quiet and in noise. The cognitive tests employed included the Reading Span Test and the…

Density-functional theory for internal magnetic fields

Science.gov (United States)

Tellgren, Erik I.

2018-01-01

A density-functional theory is developed based on the Maxwell-Schrödinger equation with an internal magnetic field in addition to the external electromagnetic potentials. The basic variables of this theory are the electron density and the total magnetic field, which can equivalently be represented as a physical current density. Hence, the theory can be regarded as a physical current density-functional theory and an alternative to the paramagnetic current density-functional theory due to Vignale and Rasolt. The energy functional has strong enough convexity properties to allow a formulation that generalizes Lieb's convex analysis formulation of standard density-functional theory. Several variational principles as well as a Hohenberg-Kohn-like mapping between potentials and ground-state densities follow from the underlying convex structure. Moreover, the energy functional can be regarded as the result of a standard approximation technique (Moreau-Yosida regularization) applied to the conventional Schrödinger ground-state energy, which imposes limits on the maximum curvature of the energy (with respect to the magnetic field) and enables construction of a (Fréchet) differentiable universal density functional.

Modeling the Hydrological Cycle in the Atmosphere of Mars: Influence of a Bimodal Size Distribution of Aerosol Nucleation Particles

Science.gov (United States)

Shaposhnikov, Dmitry S.; Rodin, Alexander V.; Medvedev, Alexander S.; Fedorova, Anna A.; Kuroda, Takeshi; Hartogh, Paul

2018-02-01

We present a new implementation of the hydrological cycle scheme into a general circulation model of the Martian atmosphere. The model includes a semi-Lagrangian transport scheme for water vapor and ice and accounts for microphysics of phase transitions between them. The hydrological scheme includes processes of saturation, nucleation, particle growth, sublimation, and sedimentation under the assumption of a variable size distribution. The scheme has been implemented into the Max Planck Institute Martian general circulation model and tested assuming monomodal and bimodal lognormal distributions of ice condensation nuclei. We present a comparison of the simulated annual variations, horizontal and vertical distributions of water vapor, and ice clouds with the available observations from instruments on board Mars orbiters. The accounting for bimodality of aerosol particle distribution improves the simulations of the annual hydrological cycle, including predicted ice clouds mass, opacity, number density, and particle radii. The increased number density and lower nucleation rates bring the simulated cloud opacities closer to observations. Simulations show a weak effect of the excess of small aerosol particles on the simulated water vapor distributions.

Elimination of Bimodal Size in InAs/GaAs Quantum Dots for Preparation of 1.3-μm Quantum Dot Lasers.

Science.gov (United States)

Su, Xiang-Bin; Ding, Ying; Ma, Ben; Zhang, Ke-Lu; Chen, Ze-Sheng; Li, Jing-Lun; Cui, Xiao-Ran; Xu, Ying-Qiang; Ni, Hai-Qiao; Niu, Zhi-Chuan

2018-02-21

The device characteristics of semiconductor quantum dot lasers have been improved with progress in active layer structures. Self-assembly formed InAs quantum dots grown on GaAs had been intensively promoted in order to achieve quantum dot lasers with superior device performances. In the process of growing high-density InAs/GaAs quantum dots, bimodal size occurs due to large mismatch and other factors. The bimodal size in the InAs/GaAs quantum dot system is eliminated by the method of high-temperature annealing and optimized the in situ annealing temperature. The annealing temperature is taken as the key optimization parameters, and the optimal annealing temperature of 680 °C was obtained. In this process, quantum dot growth temperature, InAs deposition, and arsenic (As) pressure are optimized to improve quantum dot quality and emission wavelength. A 1.3-μm high-performance F-P quantum dot laser with a threshold current density of 110 A/cm 2 was demonstrated.

Density-density functionals and effective potentials in many-body electronic structure calculations

International Nuclear Information System (INIS)

Reboredo, Fernando A.; Kent, Paul R.

2008-01-01

We demonstrate the existence of different density-density functionals designed to retain selected properties of the many-body ground state in a non-interacting solution starting from the standard density functional theory ground state. We focus on diffusion quantum Monte Carlo applications that require trial wave functions with optimal Fermion nodes. The theory is extensible and can be used to understand current practices in several electronic structure methods within a generalized density functional framework. The theory justifies and stimulates the search of optimal empirical density functionals and effective potentials for accurate calculations of the properties of real materials, but also cautions on the limits of their applicability. The concepts are tested and validated with a near-analytic model.

Jump probabilities in the non-Markovian quantum jump method

International Nuclear Information System (INIS)

Haerkoenen, Kari

2010-01-01

The dynamics of a non-Markovian open quantum system described by a general time-local master equation is studied. The propagation of the density operator is constructed in terms of two processes: (i) deterministic evolution and (ii) evolution of a probability density functional in the projective Hilbert space. The analysis provides a derivation for the jump probabilities used in the recently developed non-Markovian quantum jump (NMQJ) method (Piilo et al 2008 Phys. Rev. Lett. 100 180402).

Excited-state density functional theory

International Nuclear Information System (INIS)

Harbola, Manoj K; Hemanadhan, M; Shamim, Md; Samal, P

2012-01-01

Starting with a brief introduction to excited-state density functional theory, we present our method of constructing modified local density approximated (MLDA) energy functionals for the excited states. We show that these functionals give accurate results for kinetic energy and exchange energy compared to the ground state LDA functionals. Further, with the inclusion of GGA correction, highly accurate total energies for excited states are obtained. We conclude with a brief discussion on the further direction of research that include the construction of correlation energy functional and exchange potential for excited states.

Multiple regimes of operation in bimodal AFM: understanding the energy of cantilever eigenmodes

Directory of Open Access Journals (Sweden)

Daniel Kiracofe

2013-06-01

Full Text Available One of the key goals in atomic force microscopy (AFM imaging is to enhance material property contrast with high resolution. Bimodal AFM, where two eigenmodes are simultaneously excited, confers significant advantages over conventional single-frequency tapping mode AFM due to its ability to provide contrast between regions with different material properties under gentle imaging conditions. Bimodal AFM traditionally uses the first two eigenmodes of the AFM cantilever. In this work, the authors explore the use of higher eigenmodes in bimodal AFM (e.g., exciting the first and fourth eigenmodes. It is found that such operation leads to interesting contrast reversals compared to traditional bimodal AFM. A series of experiments and numerical simulations shows that the primary cause of the contrast reversals is not the choice of eigenmode itself (e.g., second versus fourth, but rather the relative kinetic energy between the higher eigenmode and the first eigenmode. This leads to the identification of three distinct imaging regimes in bimodal AFM. This result, which is applicable even to traditional bimodal AFM, should allow researchers to choose cantilever and operating parameters in a more rational manner in order to optimize resolution and contrast during nanoscale imaging of materials.

Collision Probability Analysis

DEFF Research Database (Denmark)

Hansen, Peter Friis; Pedersen, Preben Terndrup

1998-01-01

It is the purpose of this report to apply a rational model for prediction of ship-ship collision probabilities as function of the ship and the crew characteristics and the navigational environment for MS Dextra sailing on a route between Cadiz and the Canary Islands.The most important ship and crew...... characteristics are: ship speed, ship manoeuvrability, the layout of the navigational bridge, the radar system, the number and the training of navigators, the presence of a look out etc. The main parameters affecting the navigational environment are ship traffic density, probability distributions of wind speeds...... probability, i.e. a study of the navigator's role in resolving critical situations, a causation factor is derived as a second step.The report documents the first step in a probabilistic collision damage analysis. Future work will inlcude calculation of energy released for crushing of structures giving...

Spectral function from Reduced Density Matrix Functional Theory

Science.gov (United States)

Romaniello, Pina; di Sabatino, Stefano; Berger, Jan A.; Reining, Lucia

2015-03-01

In this work we focus on the calculation of the spectral function, which determines, for example, photoemission spectra, from reduced density matrix functional theory. Starting from its definition in terms of the one-body Green's function we derive an expression for the spectral function that depends on the natural occupation numbers and on an effective energy which accounts for all the charged excitations. This effective energy depends on the two-body as well as higher-order density matrices. Various approximations to this expression are explored by using the exactly solvable Hubbard chains.

Ground-state densities from the Rayleigh-Ritz variation principle and from density-functional theory.

Science.gov (United States)

Kvaal, Simen; Helgaker, Trygve

2015-11-14

The relationship between the densities of ground-state wave functions (i.e., the minimizers of the Rayleigh-Ritz variation principle) and the ground-state densities in density-functional theory (i.e., the minimizers of the Hohenberg-Kohn variation principle) is studied within the framework of convex conjugation, in a generic setting covering molecular systems, solid-state systems, and more. Having introduced admissible density functionals as functionals that produce the exact ground-state energy for a given external potential by minimizing over densities in the Hohenberg-Kohn variation principle, necessary and sufficient conditions on such functionals are established to ensure that the Rayleigh-Ritz ground-state densities and the Hohenberg-Kohn ground-state densities are identical. We apply the results to molecular systems in the Born-Oppenheimer approximation. For any given potential v ∈ L(3/2)(ℝ(3)) + L(∞)(ℝ(3)), we establish a one-to-one correspondence between the mixed ground-state densities of the Rayleigh-Ritz variation principle and the mixed ground-state densities of the Hohenberg-Kohn variation principle when the Lieb density-matrix constrained-search universal density functional is taken as the admissible functional. A similar one-to-one correspondence is established between the pure ground-state densities of the Rayleigh-Ritz variation principle and the pure ground-state densities obtained using the Hohenberg-Kohn variation principle with the Levy-Lieb pure-state constrained-search functional. In other words, all physical ground-state densities (pure or mixed) are recovered with these functionals and no false densities (i.e., minimizing densities that are not physical) exist. The importance of topology (i.e., choice of Banach space of densities and potentials) is emphasized and illustrated. The relevance of these results for current-density-functional theory is examined.

Bimodal distribution of glucose is not universally useful for diagnosing diabetes

DEFF Research Database (Denmark)

Vistisen, Dorte; Colagiuri, Stephen; Borch-Johnsen, Knut

2009-01-01

OBJECTIVE: Bimodality in the distribution of glucose has been used to define the cut point for the diagnosis of diabetes. Previous studies on bimodality have primarily been in populations with a high prevalence of type 2 diabetes, including one study in a white Caucasian population. All studies i...

Single-particle energies and density of states in density functional theory

Science.gov (United States)

van Aggelen, H.; Chan, G. K.-L.

2015-07-01

Time-dependent density functional theory (TD-DFT) is commonly used as the foundation to obtain neutral excited states and transition weights in DFT, but does not allow direct access to density of states and single-particle energies, i.e. ionisation energies and electron affinities. Here we show that by extending TD-DFT to a superfluid formulation, which involves operators that break particle-number symmetry, we can obtain the density of states and single-particle energies from the poles of an appropriate superfluid response function. The standard Kohn- Sham eigenvalues emerge as the adiabatic limit of the superfluid response under the assumption that the exchange- correlation functional has no dependence on the superfluid density. The Kohn- Sham eigenvalues can thus be interpreted as approximations to the ionisation energies and electron affinities. Beyond this approximation, the formalism provides an incentive for creating a new class of density functionals specifically targeted at accurate single-particle eigenvalues and bandgaps.

Density of states functions for photonic crystals

International Nuclear Information System (INIS)

McPhedran, R.C.; McOrist, J.; Sterke, C.M. de; Nicorovici, N.A.; Botten, L.C.; Asatryan, A.A.

2004-01-01

We discuss density of states functions for photonic crystals, in the context of the two-dimensional problem for arrays of cylinders of arbitrary cross section. We introduce the mutual density of states (MDOS), and show that this function can be used to calculate both the local density of states (LDOS), which gives position information for emission of radiation from photonic crystals, and the spectral density of states (SDOS), which gives angular information. We establish the connection between MDOS, LDOS, SDOS and the conventional density of states, which depends only on frequency. We relate all four functions to the band structure and propagating states within the crystal, and give numerical examples of the relation between band structure and density of states functions

Nonlocal kinetic-energy-density functionals

International Nuclear Information System (INIS)

Garcia-Gonzalez, P.; Alvarellos, J.E.; Chacon, E.

1996-01-01

In this paper we present nonlocal kinetic-energy functionals T[n] within the average density approximation (ADA) framework, which do not require any extra input when applied to any electron system and recover the exact kinetic energy and the linear response function of a homogeneous system. In contrast with previous ADA functionals, these present good behavior of the long-range tail of the exact weight function. The averaging procedure for the kinetic functional (averaging the Fermi momentum of the electron gas, instead of averaging the electron density) leads to a functional without numerical difficulties in the calculation of extended systems, and it gives excellent results when applied to atoms and jellium surfaces. copyright 1996 The American Physical Society

Response and reliability analysis of nonlinear uncertain dynamical structures by the probability density evolution method

DEFF Research Database (Denmark)

Nielsen, Søren R. K.; Peng, Yongbo; Sichani, Mahdi Teimouri

2016-01-01

The paper deals with the response and reliability analysis of hysteretic or geometric nonlinear uncertain dynamical systems of arbitrary dimensionality driven by stochastic processes. The approach is based on the probability density evolution method proposed by Li and Chen (Stochastic dynamics...... of structures, 1st edn. Wiley, London, 2009; Probab Eng Mech 20(1):33–44, 2005), which circumvents the dimensional curse of traditional methods for the determination of non-stationary probability densities based on Markov process assumptions and the numerical solution of the related Fokker–Planck and Kolmogorov......–Feller equations. The main obstacle of the method is that a multi-dimensional convolution integral needs to be carried out over the sample space of a set of basic random variables, for which reason the number of these need to be relatively low. In order to handle this problem an approach is suggested, which...

Exchange-correlation energies of atoms from efficient density functionals: influence of the electron density

Science.gov (United States)

Tao, Jianmin; Ye, Lin-Hui; Duan, Yuhua

2017-12-01

The primary goal of Kohn-Sham density functional theory is to evaluate the exchange-correlation contribution to electronic properties. However, the accuracy of a density functional can be affected by the electron density. Here we apply the nonempirical Tao-Mo (TM) semilocal functional to study the influence of the electron density on the exchange and correlation energies of atoms and ions, and compare the results with the commonly used nonempirical semilocal functionals local spin-density approximation (LSDA), Perdew-Burke-Ernzerhof (PBE), Tao-Perdew-Staroverov-Scuseria (TPSS), and hybrid functional PBE0. We find that the spin-restricted Hartree-Fock density yields the exchange and correlation energies in good agreement with the Optimized Effective Potential method, particularly for spherical atoms and ions. However, the errors of these semilocal and hybrid functionals become larger for self-consistent densities. We further find that the quality of the electron density have greater effect on the exchange-correlation energies of kinetic energy density-dependent meta-GGA functionals TPSS and TM than on those of the LSDA and GGA, and therefore, should have greater influence on the performance of meta-GGA functionals. Finally, we show that the influence of the density quality on PBE0 is slightly reduced, compared to that of PBE, due to the exact mixing.

A multiconfigurational hybrid density-functional theory

DEFF Research Database (Denmark)

Sharkas, Kamal; Savin, Andreas; Jensen, Hans Jørgen Aagaard

2012-01-01

We propose a multiconfigurational hybrid density-functional theory which rigorously combines a multiconfiguration self-consistent-field calculation with a density-functional approximation based on a linear decomposition of the electron-electron interaction. This gives a straightforward extension ...

Corredor Bimodal Cafetero

OpenAIRE

Duque Escobar, Gonzalo

2015-01-01

El Corredor Bimodal Cafetero es un proyecto de infraestructura estratégica que articula la Hidrovía del Magdalena con el Corredor Férreo del río Cauca, inscrito en el Plan Nacional de Desarrollo 2014/2018 y financiable con la salida de 30 mil toneladas diarias de carbón andino a la cuenca del Pacífico. Incluye el Túnel Cumanday para cruzar la Cordillera Central, el Ferrocarril Cafetero de 150 km y 3% de pendiente entre La Dorada y el Km 41, y la Transversal Cafetera de 108 km para una vía de...

Local density approximation for exchange in excited-state density functional theory

OpenAIRE

Harbola, Manoj K.; Samal, Prasanjit

2004-01-01

Local density approximation for the exchange energy is made for treatment of excited-states in density-functional theory. It is shown that taking care of the state-dependence of the LDA exchange energy functional leads to accurate excitation energies.

Optimizing an objective function under a bivariate probability model

NARCIS (Netherlands)

X. Brusset; N.M. Temme (Nico)

2007-01-01

htmlabstractThe motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probability distribution functions that may be dependent. This method is applicable when results need to be

Energy vs. density on paths toward more exact density functionals.

Science.gov (United States)

Kepp, Kasper P

2018-03-14

Recently, the progression toward more exact density functional theory has been questioned, implying a need for more formal ways to systematically measure progress, i.e. a "path". Here I use the Hohenberg-Kohn theorems and the definition of normality by Burke et al. to define a path toward exactness and "straying" from the "path" by separating errors in ρ and E[ρ]. A consistent path toward exactness involves minimizing both errors. Second, a suitably diverse test set of trial densities ρ' can be used to estimate the significance of errors in ρ without knowing the exact densities which are often inaccessible. To illustrate this, the systems previously studied by Medvedev et al., the first ionization energies of atoms with Z = 1 to 10, the ionization energy of water, and the bond dissociation energies of five diatomic molecules were investigated using CCSD(T)/aug-cc-pV5Z as benchmark at chemical accuracy. Four functionals of distinct designs was used: B3LYP, PBE, M06, and S-VWN. For atomic cations regardless of charge and compactness up to Z = 10, the energy effects of the different ρ are energy-wise insignificant. An interesting oscillating behavior in the density sensitivity is observed vs. Z, explained by orbital occupation effects. Finally, it is shown that even large "normal" problems such as the Co-C bond energy of cobalamins can use simpler (e.g. PBE) trial densities to drastically speed up computation by loss of a few kJ mol -1 in accuracy. The proposed method of using a test set of trial densities to estimate the sensitivity and significance of density errors of functionals may be useful for testing and designing new balanced functionals with more systematic improvement of densities and energies.

Bimodal pollination system of the bromeliad Aechmea nudicaulis involving hummingbirds and bees.

Science.gov (United States)

Schmid, S; Schmid, V S; Zillikens, A; Harter-Marques, B; Steiner, J

2011-01-01

In order to compare the effectiveness of birds and insects as pollinators, we studied the floral biology of the bromeliad Aechmea nudicaulis (L.) Grisebach in the biome of the Atlantic rain forest, southern Brazil. On Santa Catarina Island, flowering extends from mid-September to the end of December, with diurnal anthesis. The reproductive system is obligatory xenogamy, thus pollinator-dependent. Flowers secrete 31.84 μl of nectar per day, with a mean sugar concentration of 23.2%. Highest nectar volume and sugar concentration occur at the beginning of anthesis. Most floral traits are characteristic for ornithophily, and nectar production appears to be adapted to the energy demand of hummingbirds. Continued secretion of the sucrose-dominated nectar attracts and binds visitors to inflorescences, strengthening trapline foraging behaviour. Experiments assessing seed set after single flower visits were performed with the most frequent visitors, revealing the hummingbird Thalurania glaucopis as the most effective pollen vector. In addition, bees are also functional pollinators, as substantiated by their high visitation frequency. We conclude that this pollination system is bimodal. Thus, there is redundancy in the pollination service provided by birds and bees, granting a high probability of successful reproduction in Ae. nudicaulis. © 2010 German Botanical Society and The Royal Botanical Society of the Netherlands.

Structure functions are not parton probabilities

International Nuclear Information System (INIS)

Brodsky, Stanley J.; Hoyer, Paul; Sannino, Francesco; Marchal, Nils; Peigne, Stephane

2002-01-01

The common view that structure functions measured in deep inelastic lepton scattering are determined by the probability of finding quarks and gluons in the target is not correct in gauge theory. We show that gluon exchange between the fast, outgoing partons and target spectators, which is usually assumed to be an irrelevant gauge artifact, affects the leading twist structure functions in a profound way. This observation removes the apparent contradiction between the projectile (eikonal) and target (parton model) views of diffractive and small x B phenomena. The diffractive scattering of the fast outgoing quarks on spectators in the target causes shadowing in the DIS cross section. Thus the depletion of the nuclear structure functions is not intrinsic to the wave function of the nucleus, but is a coherent effect arising from the destructive interference of diffractive channels induced by final state interactions. This is consistent with the Glauber-Gribov interpretation of shadowing as a rescattering effect

Prospect evaluation as a function of numeracy and probability denominator.

Science.gov (United States)

Millroth, Philip; Juslin, Peter

2015-05-01

This study examines how numeracy and probability denominator (a direct-ratio probability, a relative frequency with denominator 100, a relative frequency with denominator 10,000) affect the evaluation of prospects in an expected-value based pricing task. We expected that numeracy would affect the results due to differences in the linearity of number perception and the susceptibility to denominator neglect with different probability formats. An analysis with functional measurement verified that participants integrated value and probability into an expected value. However, a significant interaction between numeracy and probability format and subsequent analyses of the parameters of cumulative prospect theory showed that the manipulation of probability denominator changed participants' psychophysical response to probability and value. Standard methods in decision research may thus confound people's genuine risk attitude with their numerical capacities and the probability format used. Copyright © 2015 Elsevier B.V. All rights reserved.

A course in bimodal provability logic

NARCIS (Netherlands)

Visser, A.

The aim of the present paper is twofold: first I am somewhat dissatisfied with current treatments of Bimodal Provability Logic: the models employed there are singled out by certain syntactical conditions, moreover they validate the logics under consideration only locally. In this paper I give a

Density distribution function of a self-gravitating isothermal compressible turbulent fluid in the context of molecular clouds ensembles

Science.gov (United States)

Donkov, Sava; Stefanov, Ivan Z.

2018-03-01

We have set ourselves the task of obtaining the probability distribution function of the mass density of a self-gravitating isothermal compressible turbulent fluid from its physics. We have done this in the context of a new notion: the molecular clouds ensemble. We have applied a new approach that takes into account the fractal nature of the fluid. Using the medium equations, under the assumption of steady state, we show that the total energy per unit mass is an invariant with respect to the fractal scales. As a next step we obtain a non-linear integral equation for the dimensionless scale Q which is the third root of the integral of the probability distribution function. It is solved approximately up to the leading-order term in the series expansion. We obtain two solutions. They are power-law distributions with different slopes: the first one is -1.5 at low densities, corresponding to an equilibrium between all energies at a given scale, and the second one is -2 at high densities, corresponding to a free fall at small scales.

Multiphase flow modeling of a crude-oil spill site with a bimodal permeability distribution

Science.gov (United States)

Dillard, Leslie A.; Essaid, Hedeff I.; Herkelrath, William N.

1997-01-01

Fluid saturation, particle-size distribution, and porosity measurements were obtained from 269 core samples collected from six boreholes along a 90-m transect at a subregion of a crude-oil spill site, the north pool, near Bemidji, Minnesota. The oil saturation data, collected 11 years after the spill, showed an irregularly shaped oil body that appeared to be affected by sediment spatial variability. The particle-size distribution data were used to estimate the permeability (k) and retention curves for each sample. An additional 344 k estimates were obtained from samples previously collected at the north pool. The 613 k estimates were distributed bimodal lognormally with the two population distributions corresponding to the two predominant lithologies: a coarse glacial outwash deposit and fine-grained interbedded lenses. A two-step geostatistical approach was used to generate a conditioned realization of k representing the bimodal heterogeneity. A cross-sectional multiphase flow model was used to simulate the flow of oil and water in the presence of air along the north pool transect for an 11-year period. The inclusion of a representation of the bimodal aquifer heterogeneity was crucial for reproduction of general features of the observed oil body. If the bimodal heterogeneity was characterized, hysteresis did not have to be incorporated into the model because a hysteretic effect was produced by the sediment spatial variability. By revising the relative permeability functional relation, an improved reproduction of the observed oil saturation distribution was achieved. The inclusion of water table fluctuations in the model did not significantly affect the simulated oil saturation distribution.

INVESTIGATION OF INFLUENCE OF ENCODING FUNCTION COMPLEXITY ON DISTRIBUTION OF ERROR MASKING PROBABILITY

Directory of Open Access Journals (Sweden)

A. B. Levina

2016-03-01

Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking

Relativistic density functional for nuclear structure

CERN Document Server

2016-01-01

This book aims to provide a detailed introduction to the state-of-the-art covariant density functional theory, which follows the Lorentz invariance from the very beginning and is able to describe nuclear many-body quantum systems microscopically and self-consistently. Covariant density functional theory was introduced in nuclear physics in the 1970s and has since been developed and used to describe the diversity of nuclear properties and phenomena with great success. In order to provide an advanced and updated textbook of covariant density functional theory for graduate students and nuclear physics researchers, this book summarizes the enormous amount of material that has accumulated in the field of covariant density functional theory over the last few decades as well as the latest developments in this area. Moreover, the book contains enough details for readers to follow the formalism and theoretical results, and provides exhaustive references to explore the research literature.

The probability of a tornado missile hitting a target

International Nuclear Information System (INIS)

Goodman, J.; Koch, J.E.

1983-01-01

It is shown that tornado missile transportation is a diffusion Markovian process. Therefore, the Green's function method is applied for the estimation of the probability of hitting a unit target area. This propability is expressed through a joint density of tornado intensity and path area, a probability of tornado missile injection and a tornado missile height distribution. (orig.)

Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils

Directory of Open Access Journals (Sweden)

J. A. P. Pollacco

2017-06-01

Full Text Available Descriptions of soil hydraulic properties, such as the soil moisture retention curve, θ(h, and saturated hydraulic conductivities, Ks, are a prerequisite for hydrological models. Since the measurement of Ks is expensive, it is frequently derived from statistical pedotransfer functions (PTFs. Because it is usually more difficult to describe Ks than θ(h from pedotransfer functions, Pollacco et al. (2013 developed a physical unimodal model to compute Ks solely from hydraulic parameters derived from the Kosugi θ(h. This unimodal Ks model, which is based on a unimodal Kosugi soil pore-size distribution, was developed by combining the approach of Hagen–Poiseuille with Darcy's law and by introducing three tortuosity parameters. We report here on (1 the suitability of the Pollacco unimodal Ks model to predict Ks for a range of New Zealand soils from the New Zealand soil database (S-map and (2 further adaptations to this model to adapt it to dual-porosity structured soils by computing the soil water flux through a continuous function of an improved bimodal pore-size distribution. The improved bimodal Ks model was tested with a New Zealand data set derived from historical measurements of Ks and θ(h for a range of soils derived from sandstone and siltstone. The Ks data were collected using a small core size of 10 cm diameter, causing large uncertainty in replicate measurements. Predictions of Ks were further improved by distinguishing topsoils from subsoil. Nevertheless, as expected, stratifying the data with soil texture only slightly improved the predictions of the physical Ks models because the Ks model is based on pore-size distribution and the calibrated parameters were obtained within the physically feasible range. The improvements made to the unimodal Ks model by using the new bimodal Ks model are modest when compared to the unimodal model, which is explained by the poor accuracy of measured total porosity. Nevertheless, the new bimodal

Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils

Science.gov (United States)

Pollacco, Joseph Alexander Paul; Webb, Trevor; McNeill, Stephen; Hu, Wei; Carrick, Sam; Hewitt, Allan; Lilburne, Linda

2017-06-01

Descriptions of soil hydraulic properties, such as the soil moisture retention curve, θ(h), and saturated hydraulic conductivities, Ks, are a prerequisite for hydrological models. Since the measurement of Ks is expensive, it is frequently derived from statistical pedotransfer functions (PTFs). Because it is usually more difficult to describe Ks than θ(h) from pedotransfer functions, Pollacco et al. (2013) developed a physical unimodal model to compute Ks solely from hydraulic parameters derived from the Kosugi θ(h). This unimodal Ks model, which is based on a unimodal Kosugi soil pore-size distribution, was developed by combining the approach of Hagen-Poiseuille with Darcy's law and by introducing three tortuosity parameters. We report here on (1) the suitability of the Pollacco unimodal Ks model to predict Ks for a range of New Zealand soils from the New Zealand soil database (S-map) and (2) further adaptations to this model to adapt it to dual-porosity structured soils by computing the soil water flux through a continuous function of an improved bimodal pore-size distribution. The improved bimodal Ks model was tested with a New Zealand data set derived from historical measurements of Ks and θ(h) for a range of soils derived from sandstone and siltstone. The Ks data were collected using a small core size of 10 cm diameter, causing large uncertainty in replicate measurements. Predictions of Ks were further improved by distinguishing topsoils from subsoil. Nevertheless, as expected, stratifying the data with soil texture only slightly improved the predictions of the physical Ks models because the Ks model is based on pore-size distribution and the calibrated parameters were obtained within the physically feasible range. The improvements made to the unimodal Ks model by using the new bimodal Ks model are modest when compared to the unimodal model, which is explained by the poor accuracy of measured total porosity. Nevertheless, the new bimodal model provides an

Uncertainty plus prior equals rational bias: an intuitive Bayesian probability weighting function.

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-10-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several nonexpected utility theories, including rank-dependent models and prospect theory; here, we propose a Bayesian approach to the probability weighting function and, with it, a psychological rationale. In the real world, uncertainty is ubiquitous and, accordingly, the optimal strategy is to combine probability statements with prior information using Bayes' rule. First, we show that any reasonable prior on probabilities leads to 2 of the observed effects; overweighting of low probabilities and underweighting of high probabilities. We then investigate 2 plausible kinds of priors: informative priors based on previous experience and uninformative priors of ignorance. Individually, these priors potentially lead to large problems of bias and inefficiency, respectively; however, when combined using Bayesian model comparison methods, both forms of prior can be applied adaptively, gaining the efficiency of empirical priors and the robustness of ignorance priors. We illustrate this for the simple case of generic good and bad options, using Internet blogs to estimate the relevant priors of inference. Given this combined ignorant/informative prior, the Bayesian probability weighting function is not only robust and efficient but also matches all of the major characteristics of the distortions found in empirical research. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Bimodal atomic force microscopy imaging of isolated antibodies in air and liquids

International Nuclear Information System (INIS)

MartInez, N F; Lozano, J R; Herruzo, E T; Garcia, F; Garcia, R; Richter, C; Sulzbach, T

2008-01-01

We have developed a dynamic atomic force microscopy (AFM) method based on the simultaneous excitation of the first two flexural modes of the cantilever. The instrument, called a bimodal atomic force microscope, allows us to resolve the structural components of antibodies in both monomer and pentameric forms. The instrument operates in both high and low quality factor environments, i.e., air and liquids. We show that under the same experimental conditions, bimodal AFM is more sensitive to compositional changes than amplitude modulation AFM. By using theoretical and numerical methods, we study the material contrast sensitivity as well as the forces applied on the sample during bimodal AFM operation

Gadolinium(III-DOTA Complex Functionalized with BODIPY as a Potential Bimodal Contrast Agent for MRI and Optical Imaging

Directory of Open Access Journals (Sweden)

Matthias Ceulemans

2015-11-01

Full Text Available The synthesis and characterization of a novel gadolinium(III DOTA complex functionalized with a boron-dipyrromethene derivative (BODIPY is described. The assembly of the complex relies on azide diazotransfer chemistry in a copper tube flow reactor. The azide thus formed is coupled directly with an alkyne via click chemistry, resulting into a paramagnetic and luminescent gadolinium(III complex. Luminescent data and relaxometric properties of the complex have been evaluated, suggesting the potential applicability of the complexes as a bimodal contrast agent for magnetic resonance and optical imaging. The complex displays a bright emission at 523 nm with an absorption maximum of 507 nm and high quantum yields of up to 83% in water. The proton relaxivity of the complex measured at 310 K and at frequencies of 20 and 60 MHz had the values of 3.9 and 3.6 s−1·mM−1, respectively.

Entanglement probabilities of polymers: a white noise functional approach

International Nuclear Information System (INIS)

Bernido, Christopher C; Carpio-Bernido, M Victoria

2003-01-01

The entanglement probabilities for a highly flexible polymer to wind n times around a straight polymer are evaluated using white noise analysis. To introduce the white noise functional approach, the one-dimensional random walk problem is taken as an example. The polymer entanglement scenario, viewed as a random walk on a plane, is then treated and the entanglement probabilities are obtained for a magnetic flux confined along the straight polymer, and a case where an entangled polymer is subjected to the potential V = f-dot(s)θ. In the absence of the magnetic flux and the potential V, the entanglement probabilities reduce to a result obtained by Wiegel

Locality of correlation in density functional theory

Energy Technology Data Exchange (ETDEWEB)

Burke, Kieron [Department of Chemistry, University of California, Irvine, California 92697 (United States); Cancio, Antonio [Department of Physics and Astronomy, Ball State University, Muncie, Indiana 47306 (United States); Gould, Tim [Qld Micro- and Nanotechnology Centre, Griffith University, Nathan, Qld 4111 (Australia); Pittalis, Stefano [CNR-Istituto di Nanoscienze, Via Campi 213A, I-41125 Modena (Italy)

2016-08-07

The Hohenberg-Kohn density functional was long ago shown to reduce to the Thomas-Fermi (TF) approximation in the non-relativistic semiclassical (or large-Z) limit for all matter, i.e., the kinetic energy becomes local. Exchange also becomes local in this limit. Numerical data on the correlation energy of atoms support the conjecture that this is also true for correlation, but much less relevant to atoms. We illustrate how expansions around a large particle number are equivalent to local density approximations and their strong relevance to density functional approximations. Analyzing highly accurate atomic correlation energies, we show that E{sub C} → −A{sub C} ZlnZ + B{sub C}Z as Z → ∞, where Z is the atomic number, A{sub C} is known, and we estimate B{sub C} to be about 37 mhartree. The local density approximation yields A{sub C} exactly, but a very incorrect value for B{sub C}, showing that the local approximation is less relevant for the correlation alone. This limit is a benchmark for the non-empirical construction of density functional approximations. We conjecture that, beyond atoms, the leading correction to the local density approximation in the large-Z limit generally takes this form, but with B{sub C} a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed.

Early Bimodal Stimulation Benefits Language Acquisition for Children With Cochlear Implants.

Science.gov (United States)

Moberly, Aaron C; Lowenstein, Joanna H; Nittrouer, Susan

2016-01-01

Adding a low-frequency acoustic signal to the cochlear implant (CI) signal (i.e., bimodal stimulation) for a period of time early in life improves language acquisition. Children must acquire sensitivity to the phonemic units of language to develop most language-related skills, including expressive vocabulary, working memory, and reading. Acquiring sensitivity to phonemic structure depends largely on having refined spectral (frequency) representations available in the signal, which does not happen with CIs alone. Combining the low-frequency acoustic signal available through hearing aids with the CI signal can enhance signal quality. A period with this bimodal stimulation has been shown to improve language skills in very young children. This study examined whether these benefits persist into childhood. Data were examined for 48 children with CIs implanted under age 3 years, participating in a longitudinal study. All children wore hearing aids before receiving a CI, but upon receiving a first CI, 24 children had at least 1 year of bimodal stimulation (Bimodal group), and 24 children had only electric stimulation subsequent to implantation (CI-only group). Measures of phonemic awareness were obtained at second and fourth grades, along with measures of expressive vocabulary, working memory, and reading. Children in the Bimodal group generally performed better on measures of phonemic awareness, and that advantage was reflected in other language measures. Having even a brief period of time early in life with combined electric-acoustic input provides benefits to language learning into childhood, likely because of the enhancement in spectral representations provided.

Functional derivative of noninteracting kinetic energy density functional

International Nuclear Information System (INIS)

Liu Shubin; Ayers, Paul W.

2004-01-01

Proofs from different theoretical frameworks, namely, the Hohenbergh-Kohn theorems, the Kohn-Sham scheme, and the first-order density matrix representation, have been presented in this paper to show that the functional derivative of the noninteracting kinetic energy density functional can uniquely be expressed as the negative of the Kohn-Sham effective potential, arbitrary only to an additive orbital-independent constant. Key points leading to the current result as well as confusion about the quantity in the literature are briefly discussed

Dynamical and statistical bimodality in nuclear fragmentation

Science.gov (United States)

Mallik, S.; Chaudhuri, G.; Gulminelli, F.

2018-02-01

The origin of bimodal behavior in the residue distribution experimentally measured in heavy ion reactions is reexamined using Boltzmann-Uehling-Uhlenbeck simulations. We suggest that, depending on the incident energy and impact parameter of the reaction, both entrance channel and exit channel effects can be at the origin of the observed behavior. Specifically, fluctuations in the reaction mechanism induced by fluctuations in the collision rate, as well as thermal bimodality directly linked to the nuclear liquid-gas phase transition, are observed in our simulations. Both phenomenologies were previously proposed in the literature but presented as incompatible and contradictory interpretations of the experimental measurements. These results indicate that heavy ion collisions at intermediate energies can be viewed as a powerful tool to study both bifurcations induced by out-of-equilibrium critical phenomena, as well as finite-size precursors of thermal phase transitions.

Deaf Children's Bimodal Bilingualism and Education

Science.gov (United States)

Swanwick, Ruth

2016-01-01

This paper provides an overview of the research into deaf children's bilingualism and bilingual education through a synthesis of studies published over the last 15 years. This review brings together the linguistic and pedagogical work on bimodal bilingualism to inform educational practice. The first section of the review provides a synthesis of…

Density functionals in the laboratory frame

International Nuclear Information System (INIS)

Giraud, B. G.

2008-01-01

We compare several definitions of the density of a self-bound system, such as a nucleus, in relation with its center-of-mass zero-point motion. A trivial deconvolution relates the internal density to the density defined in the laboratory frame. This result is useful for the practical definition of density functionals

The trade-off between heat tolerance and metabolic cost drives the bimodal life strategy at the air-water interface

KAUST Repository

Fusi, Marco; Cannicci, Stefano; Daffonchio, Daniele; Mostert, Bruce; Pö rtner, Hans-Otto; Giomi, Folco

2016-01-01

The principle of oxygen and capacity limitation of thermal tolerance in ectotherms suggests that the long-term upper limits of an organism's thermal niche are equivalent to the upper limits of the organism's functional capacity for oxygen provision to tissues. Air-breathing ectotherms show wider thermal tolerances, since they can take advantage of the higher availability of oxygen in air than in water. Bimodal species move from aquatic to aerial media and switch between habitats in response to environmental variations such as cyclical or anomalous temperature fluctuations. Here we tested the prediction that bimodal species cope better with thermal stress than truly aquatic species using the crab Pachygrapsus marmoratus as a model species. When in water, oxygen consumption rates of P. marmoratus acutely rise during warming. Beyond a temperature threshold of 23 °C the crab's aerobic metabolism in air remains lower than in water. In parallel, the haemolymph oxygen partial pressure of submerged animals progressive decreases during warming, while it remains low but constant during emersion. Our results demonstrate the ability of a bimodal breathing ectotherm to extend its thermal tolerance during air-breathing, suggesting that there are temperature-related physiological benefits during the evolution of the bimodal life style.

The trade-off between heat tolerance and metabolic cost drives the bimodal life strategy at the air-water interface

KAUST Repository

Fusi, Marco

2016-01-13

The principle of oxygen and capacity limitation of thermal tolerance in ectotherms suggests that the long-term upper limits of an organism\\'s thermal niche are equivalent to the upper limits of the organism\\'s functional capacity for oxygen provision to tissues. Air-breathing ectotherms show wider thermal tolerances, since they can take advantage of the higher availability of oxygen in air than in water. Bimodal species move from aquatic to aerial media and switch between habitats in response to environmental variations such as cyclical or anomalous temperature fluctuations. Here we tested the prediction that bimodal species cope better with thermal stress than truly aquatic species using the crab Pachygrapsus marmoratus as a model species. When in water, oxygen consumption rates of P. marmoratus acutely rise during warming. Beyond a temperature threshold of 23 °C the crab\\'s aerobic metabolism in air remains lower than in water. In parallel, the haemolymph oxygen partial pressure of submerged animals progressive decreases during warming, while it remains low but constant during emersion. Our results demonstrate the ability of a bimodal breathing ectotherm to extend its thermal tolerance during air-breathing, suggesting that there are temperature-related physiological benefits during the evolution of the bimodal life style.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Science.gov (United States)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

Science.gov (United States)

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Density-functional expansion methods: Grand challenges.

Science.gov (United States)

Giese, Timothy J; York, Darrin M

2012-03-01

We discuss the source of errors in semiempirical density functional expansion (VE) methods. In particular, we show that VE methods are capable of well-reproducing their standard Kohn-Sham density functional method counterparts, but suffer from large errors upon using one or more of these approximations: the limited size of the atomic orbital basis, the Slater monopole auxiliary basis description of the response density, and the one- and two-body treatment of the core-Hamiltonian matrix elements. In the process of discussing these approximations and highlighting their symptoms, we introduce a new model that supplements the second-order density-functional tight-binding model with a self-consistent charge-dependent chemical potential equalization correction; we review our recently reported method for generalizing the auxiliary basis description of the atomic orbital response density; and we decompose the first-order potential into a summation of additive atomic components and many-body corrections, and from this examination, we provide new insights and preliminary results that motivate and inspire new approximate treatments of the core-Hamiltonian.

Periodic subsystem density-functional theory

International Nuclear Information System (INIS)

Genova, Alessandro; Pavanello, Michele; Ceresoli, Davide

2014-01-01

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) has recently emerged as a powerful tool for reducing the computational scaling of Kohn–Sham DFT. To date, however, FDE has been employed to molecular systems only. Periodic systems, such as metals, semiconductors, and other crystalline solids have been outside the applicability of FDE, mostly because of the lack of a periodic FDE implementation. To fill this gap, in this work we aim at extending FDE to treat subsystems of molecular and periodic character. This goal is achieved by a dual approach. On one side, the development of a theoretical framework for periodic subsystem DFT. On the other, the realization of the method into a parallel computer code. We find that periodic FDE is capable of reproducing total electron densities and (to a lesser extent) also interaction energies of molecular systems weakly interacting with metallic surfaces. In the pilot calculations considered, we find that FDE fails in those cases where there is appreciable density overlap between the subsystems. Conversely, we find FDE to be in semiquantitative agreement with Kohn–Sham DFT when the inter-subsystem density overlap is low. We also conclude that to make FDE a suitable method for describing molecular adsorption at surfaces, kinetic energy density functionals that go beyond the GGA level must be employed

Periodic subsystem density-functional theory

Science.gov (United States)

Genova, Alessandro; Ceresoli, Davide; Pavanello, Michele

2014-11-01

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) has recently emerged as a powerful tool for reducing the computational scaling of Kohn-Sham DFT. To date, however, FDE has been employed to molecular systems only. Periodic systems, such as metals, semiconductors, and other crystalline solids have been outside the applicability of FDE, mostly because of the lack of a periodic FDE implementation. To fill this gap, in this work we aim at extending FDE to treat subsystems of molecular and periodic character. This goal is achieved by a dual approach. On one side, the development of a theoretical framework for periodic subsystem DFT. On the other, the realization of the method into a parallel computer code. We find that periodic FDE is capable of reproducing total electron densities and (to a lesser extent) also interaction energies of molecular systems weakly interacting with metallic surfaces. In the pilot calculations considered, we find that FDE fails in those cases where there is appreciable density overlap between the subsystems. Conversely, we find FDE to be in semiquantitative agreement with Kohn-Sham DFT when the inter-subsystem density overlap is low. We also conclude that to make FDE a suitable method for describing molecular adsorption at surfaces, kinetic energy density functionals that go beyond the GGA level must be employed.

The probability representation as a new formulation of quantum mechanics

International Nuclear Information System (INIS)

Man'ko, Margarita A; Man'ko, Vladimir I

2012-01-01

We present a new formulation of conventional quantum mechanics, in which the notion of a quantum state is identified via a fair probability distribution of the position measured in a reference frame of the phase space with rotated axes. In this formulation, the quantum evolution equation as well as the equation for finding energy levels are expressed as linear equations for the probability distributions that determine the quantum states. We also give the integral transforms relating the probability distribution (called the tomographic-probability distribution or the state tomogram) to the density matrix and the Wigner function and discuss their connection with the Radon transform. Qudit states are considered and the invertible map of the state density operators onto the probability vectors is discussed. The tomographic entropies and entropic uncertainty relations are reviewed. We demonstrate the uncertainty relations for the position and momentum and the entropic uncertainty relations in the tomographic-probability representation, which is suitable for an experimental check of the uncertainty relations.

Uncertainty plus Prior Equals Rational Bias: An Intuitive Bayesian Probability Weighting Function

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-01-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several…

Bimodal Formation Time Distribution for Infall Dark Matter Halos

Science.gov (United States)

Shi, Jingjing; Wang, Huiyuan; Mo, H. J.; Xie, Lizhi; Wang, Xiaoyu; Lapi, Andrea; Sheth, Ravi K.

2018-04-01

We use a 200 {h}-1 {Mpc} a-side N-body simulation to study the mass accretion history (MAH) of dark matter halos to be accreted by larger halos, which we call infall halos. We define a quantity {a}nf}\\equiv (1+{z}{{f}})/(1+{z}peak}) to characterize the MAH of infall halos, where {z}peak} and {z}{{f}} are the accretion and formation redshifts, respectively. We find that, at given {z}peak}, their MAH is bimodal. Infall halos are dominated by a young population at high redshift and by an old population at low redshift. For the young population, the {a}nf} distribution is narrow and peaks at about 1.2, independent of {z}peak}, while for the old population, the peak position and width of the {a}nf} distribution both increase with decreasing {z}peak} and are both larger than those of the young population. This bimodal distribution is found to be closely connected to the two phases in the MAHs of halos. While members of the young population are still in the fast accretion phase at z peak, those of the old population have already entered the slow accretion phase at {z}peak}. This bimodal distribution is not found for the whole halo population, nor is it seen in halo merger trees generated with the extended Press–Schechter formalism. The infall halo population at {z}peak} are, on average, younger than the whole halo population of similar masses identified at the same redshift. We discuss the implications of our findings in connection to the bimodal color distribution of observed galaxies and to the link between central and satellite galaxies.

How the bimodal format of presentation affects working memory: an overview.

Science.gov (United States)

Mastroberardino, Serena; Santangelo, Valerio; Botta, Fabiano; Marucci, Francesco S; Olivetti Belardinelli, Marta

2008-03-01

The best format in which information that has to be recalled is presented has been investigated in several studies, which focused on the impact of bimodal stimulation on working memory performance. An enhancement of participant's performance in terms of correct recall has been repeatedly found, when bimodal formats of presentation (i.e., audiovisual) were compared to unimodal formats (i.e, either visual or auditory), in providing implications for multimedial learning. Several theoretical frameworks have been suggested in order to account for the bimodal advantage, ranging from those emphasizing early stages of processing (such as automatic alerting effects or multisensory integration processes) to those centred on late stages of processing (as postulated by the dual coding theory). The aim of this paper is to review previous contributions to this topic, providing a comprehensive theoretical framework, which is updated by the latest empirical studies.

Quantal density functional theory

CERN Document Server

Sahni, Viraht

2016-01-01

This book deals with quantal density functional theory (QDFT) which is a time-dependent local effective potential theory of the electronic structure of matter. The treated time-independent QDFT constitutes a special case. In the 2nd edition, the theory is extended to include the presence of external magnetostatic fields. The theory is a description of matter based on the ‘quantal Newtonian’ first and second laws which is in terms of “classical” fields that pervade all space, and their quantal sources. The fields, which are explicitly defined, are separately representative of electron correlations due to the Pauli exclusion principle, Coulomb repulsion, correlation-kinetic, correlation-current-density, and correlation-magnetic effects. The book further describes Schrödinger theory from the new physical perspective of fields and quantal sources. It also describes traditional Hohenberg-Kohn-Sham DFT, and explains via QDFT the physics underlying the various energy functionals and functional derivatives o...

Wind power statistics and an evaluation of wind energy density

Energy Technology Data Exchange (ETDEWEB)

Jamil, M.; Parsa, S.; Majidi, M. [Materials and Energy Research Centre, Tehran (Iran, Islamic Republic of)

1995-11-01

In this paper the statistical data of fifty days` wind speed measurements at the MERC- solar site are used to find out the wind energy density and other wind characteristics with the help of the Weibull probability distribution function. It is emphasized that the Weibull and Rayleigh probability functions are useful tools for wind energy density estimation but are not quite appropriate for properly fitting the actual wind data of low mean speed, short-time records. One has to use either the actual wind data (histogram) or look for a better fit by other models of the probability function. (Author)

Reduced density matrix functional theory via a wave function based approach

Energy Technology Data Exchange (ETDEWEB)

Schade, Robert; Bloechl, Peter [Institute for Theoretical Physics, Clausthal University of Technology, Clausthal (Germany); Pruschke, Thomas [Institute for Theoretical Physics, University of Goettingen, Goettingen (Germany)

2016-07-01

We propose a new method for the calculation of the electronic and atomic structure of correlated electron systems based on reduced density matrix functional theory (rDMFT). The density-matrix functional is evaluated on the fly using Levy's constrained search formalism. The present implementation rests on a local approximation of the interaction reminiscent to that of dynamical mean field theory (DMFT). We focus here on additional approximations to the exact density-matrix functional in the local approximation and evaluate their performance.

A real-space stochastic density matrix approach for density functional electronic structure.

Science.gov (United States)

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

Evidence for a bimodal distribution in human communication.

Science.gov (United States)

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-11-02

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Decay of autoionizing states in time-dependent density functional and reduced density matrix functional theory

Energy Technology Data Exchange (ETDEWEB)

Kapoor, Varun; Brics, Martins; Bauer, Dieter [Institut fuer Physik, Universitaet Rostock, 18051 Rostock (Germany)

2013-07-01

Autoionizing states are inaccessible to time-dependent density functional theory (TDDFT) using known, adiabatic Kohn-Sham (KS) potentials. We determine the exact KS potential for a numerically exactly solvable model Helium atom interacting with a laser field that is populating an autoionizing state. The exact single-particle density of the population in the autoionizing state corresponds to that of the energetically lowest quasi-stationary state in the exact KS potential. We describe how this exact potential controls the decay by a barrier whose height and width allows for the density to tunnel out and decay with the same rate as in the ab initio time-dependent Schroedinger calculation. However, devising a useful exchange-correlation potential that is capable of governing such a scenario in general and in more complex systems is hopeless. As an improvement over TDDFT, time-dependent reduced density matrix functional theory has been proposed. We are able to obtain for the above described autoionization process the exact time-dependent natural orbitals (i.e., the eigenfunctions of the exact, time-dependent one-body reduced density matrix) and study the potentials that appear in the equations of motion for the natural orbitals and the structure of the two-body density matrix expanded in them.

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation/probability density function method

Science.gov (United States)

Kim, Jeonglae; Pope, Stephen B.

2014-05-01

A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational efficiency of combined dimension reduction and tabulation of chemistry. The computational condition matches the Volvo rig experiments. For the reactive simulation, the Lagrangian Large-Eddy Simulation/Probability Density Function (LES/PDF) formulation is used. A novel two-way coupling approach between LES and PDF is applied to obtain resolved density to reduce its statistical fluctuations. Composition mixing is evaluated by the modified Interaction-by-Exchange with the Mean (IEM) model. A baseline case uses In Situ Adaptive Tabulation (ISAT) to calculate chemical reactions efficiently. Its results demonstrate good agreement with the experimental measurements in turbulence statistics, temperature, and minor species mass fractions. For dimension reduction, 11 and 16 represented species are chosen and a variant of Rate Controlled Constrained Equilibrium (RCCE) is applied in conjunction with ISAT to each case. All the quantities in the comparison are indistinguishable from the baseline results using ISAT only. The combined use of RCCE/ISAT reduces the computational time for chemical reaction by more than 50%. However, for the current turbulent premixed flame, chemical reaction takes only a minor portion of the overall computational cost, in contrast to non-premixed flame simulations using LES/PDF, presumably due to the restricted manifold of purely premixed flame in the composition space. Instead, composition mixing is the major contributor to cost reduction since the mean-drift term, which is computationally expensive, is computed for the reduced representation. Overall, a reduction of more than 15% in the computational cost is obtained.

Self-Interaction Error in Density Functional Theory: An Appraisal.

Science.gov (United States)

Bao, Junwei Lucas; Gagliardi, Laura; Truhlar, Donald G

2018-05-03

Self-interaction error (SIE) is considered to be one of the major sources of error in most approximate exchange-correlation functionals for Kohn-Sham density-functional theory (KS-DFT), and it is large with all local exchange-correlation functionals and with some hybrid functionals. In this work, we consider systems conventionally considered to be dominated by SIE. For these systems, we demonstrate that by using multiconfiguration pair-density functional theory (MC-PDFT), the error of a translated local density-functional approximation is significantly reduced (by a factor of 3) when using an MCSCF density and on-top density, as compared to using KS-DFT with the parent functional; the error in MC-PDFT with local on-top functionals is even lower than the error in some popular KS-DFT hybrid functionals. Density-functional theory, either in MC-PDFT form with local on-top functionals or in KS-DFT form with some functionals having 50% or more nonlocal exchange, has smaller errors for SIE-prone systems than does CASSCF, which has no SIE.

Bimodal Reading: Benefits of a Talking Computer for Average and Less Skilled Readers.

Science.gov (United States)

Montali, Julie; Lewandowski, Lawrence

1996-01-01

Eighteen average readers and 18 less-skilled readers (grades 8 and 9) were presented with social studies and science passages via a computer either visually (on screen), auditorily (read by digitized voice), or bimodally (on screen, highlighted while being voiced). Less-skilled readers demonstrated comprehension in the bimodal condition equivalent…

Density functional theory and parallel processing

International Nuclear Information System (INIS)

Ward, R.C.; Geist, G.A.; Butler, W.H.

1987-01-01

The authors demonstrate a method for obtaining the ground state energies and charge densities of a system of atoms described within density functional theory using simulated annealing on a parallel computer

Quantifying Young's moduli of protein fibrils and particles with bimodal force spectroscopy.

Science.gov (United States)

Gilbert, Jay; Charnley, Mirren; Cheng, Christopher; Reynolds, Nicholas P; Jones, Owen G

2017-10-19

Force spectroscopy is a means of obtaining mechanical information of individual nanometer-scale structures in composite materials, such as protein assemblies for use in consumer films or gels. As a recently developed force spectroscopy technique, bimodal force spectroscopy relates frequency shifts in cantilevers simultaneously excited at multiple frequencies to the elastic properties of the contacted material, yet its utility for quantitative characterization of biopolymer assemblies has been limited. In this study, a linear correlation between experimental frequency shift and Young's modulus of polymer films was used to calibrate bimodal force spectroscopy and quantify Young's modulus of two protein nanostructures: β-lactoglobulin fibrils and zein nanoparticles. Cross-sectional Young's modulus of protein fibrils was determined to be 1.6 GPa while the modulus of zein nanoparticles was determined as 854 MPa. Parallel measurement of β-lactoglobulin fibril by a competing pulsed-force technique found a higher cross-sectional Young's modulus, highlighting the importance of comparative calibration against known standards in both pulsed and bimodal force spectroscopies. These findings demonstrate a successful procedure for measuring mechanical properties of individual protein assemblies with potential use in biological or packaging applications using bimodal force spectroscopy.

Rational Density Functional Selection Using Game Theory.

Science.gov (United States)

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

Histogram Estimators of Bivariate Densities

National Research Council Canada - National Science Library

Husemann, Joyce A

1986-01-01

One-dimensional fixed-interval histogram estimators of univariate probability density functions are less efficient than the analogous variable-interval estimators which are constructed from intervals...

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

Directory of Open Access Journals (Sweden)

Lorraine Perronnet

2017-04-01

Full Text Available Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D. Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

Numerical Loading of a Maxwellian Probability Distribution Function

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2003-01-01

A renormalization procedure for the numerical loading of a Maxwellian probability distribution function (PDF) is formulated. The procedure, which involves the solution of three coupled nonlinear equations, yields a numerically loaded PDF with improved properties for higher velocity moments. This method is particularly useful for low-noise particle-in-cell simulations with electron dynamics

ERF/ERFC, Calculation of Error Function, Complementary Error Function, Probability Integrals

International Nuclear Information System (INIS)

Vogel, J.E.

1983-01-01

1 - Description of problem or function: ERF and ERFC are used to compute values of the error function and complementary error function for any real number. They may be used to compute other related functions such as the normal probability integrals. 4. Method of solution: The error function and complementary error function are approximated by rational functions. Three such rational approximations are used depending on whether - x .GE.4.0. In the first region the error function is computed directly and the complementary error function is computed via the identity erfc(x)=1.0-erf(x). In the other two regions the complementary error function is computed directly and the error function is computed from the identity erf(x)=1.0-erfc(x). The error function and complementary error function are real-valued functions of any real argument. The range of the error function is (-1,1). The range of the complementary error function is (0,2). 5. Restrictions on the complexity of the problem: The user is cautioned against using ERF to compute the complementary error function by using the identity erfc(x)=1.0-erf(x). This subtraction may cause partial or total loss of significance for certain values of x

Analysis of Observation Data of Earth-Rockfill Dam Based on Cloud Probability Distribution Density Algorithm

Directory of Open Access Journals (Sweden)

Han Liwei

2014-07-01

Full Text Available Monitoring data on an earth-rockfill dam constitutes a form of spatial data. Such data include much uncertainty owing to the limitation of measurement information, material parameters, load, geometry size, initial conditions, boundary conditions and the calculation model. So the cloud probability density of the monitoring data must be addressed. In this paper, the cloud theory model was used to address the uncertainty transition between the qualitative concept and the quantitative description. Then an improved algorithm of cloud probability distribution density based on a backward cloud generator was proposed. This was used to effectively convert certain parcels of accurate data into concepts which can be described by proper qualitative linguistic values. Such qualitative description was addressed as cloud numerical characteristics-- {Ex, En, He}, which could represent the characteristics of all cloud drops. The algorithm was then applied to analyze the observation data of a piezometric tube in an earth-rockfill dam. And experiment results proved that the proposed algorithm was feasible, through which, we could reveal the changing regularity of piezometric tube’s water level. And the damage of the seepage in the body was able to be found out.

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

Directory of Open Access Journals (Sweden)

Rongda Chen

Full Text Available Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation

Science.gov (United States)

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558

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

Science.gov (United States)

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

2015-04-21

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

Bi-modal G\\"odel logic over [0,1]-valued Kripke frames

OpenAIRE

Caicedo, Xavier; Rodriguez, Ricardo Oscar

2011-01-01

We consider the G\\"odel bi-modal logic determined by fuzzy Kripke models where both the propositions and the accessibility relation are infinitely valued over the standard G\\"odel algebra [0,1] and prove strong completeness of Fischer Servi intuitionistic modal logic IK plus the prelinearity axiom with respect to this semantics. We axiomatize also the bi-modal analogues of $T,$ $S4,$ and $S5$ obtained by restricting to models over frames satisfying the [0,1]-valued versions of the structural ...

Bimodal SLD Ice Accretion on a NACA 0012 Airfoil Model

Science.gov (United States)

Potapczuk, Mark; Tsao, Jen-Ching; King-Steen, Laura

2016-01-01

This presentation describes the results of ice accretion measurements on a NACA 0012 airfoil model, from the NASA Icing Research Tunnel, using an icing cloud composed of a bimodal distribution of Supercooled Large Droplets. The data consists of photographs, laser scans of the ice surface, and measurements of the mass of ice for each icing condition. The results of ice shapes accumulated as a result of exposure to an icing cloud with a bimodal droplet distribution were compared to the ice shapes resulting from an equivalent cloud composed of a droplet distribution with a standard bell curve shape.

Convenient synthesis of (68)Ga-labeled gadolinium(III) complexes:towards bimodal responsive probes for functional imaging with PET/MRI

OpenAIRE

Notni, Johannes; Hermann, Petr; Dregely, Isabel; Wester, Hans-Jürgen

2013-01-01

A killer application? Recently, fully integrated full-body positron-emission tomography (PET) and magnetic-resonance imaging (MRI) scanners were brought to market, allowing simultaneous recording of complementary 3D data sets. By using bimodal PET/MRI probes (see figure), in vivo 3D mapping of various parameters with medical relevance could become feasible.

Microbubble embedded with upconversion nanoparticles as a bimodal contrast agent for fluorescence and ultrasound imaging

International Nuclear Information System (INIS)

Jin, Birui; Lin, Min; You, Minli; Xu, Feng; Lu, Tianjian; Zong, Yujin; Wan, Mingxi; Duan, Zhenfeng

2015-01-01

Bimodal imaging offers additional imaging signal thus finds wide spread application in clinical diagnostic imaging. Fluorescence/ultrasound bimodal imaging contrast agent using fluorescent dyes or quantum dots for fluorescence signal has emerged as a promising method, which however requires visible light or UV irradiation resulting in photobleaching, photoblinking, auto-fluorescence and limited tissue penetration depth. To surmount these problems, we developed a novel bimodal contrast agent using layer-by-layer assembly of upconversion nanoparticles onto the surface of microbubbles. The resulting microbubbles with average size of 2 μm provide enhanced ultrasound echo for ultrasound imaging and upconversion emission upon near infrared irradiation for fluorescence imaging. The developed bimodal contrast agent holds great potential to be applied in ultrasound target technique for targeted diseases diagnostics and therapy. (paper)

Uniform magnetic fields in density-functional theory

Science.gov (United States)

Tellgren, Erik I.; Laestadius, Andre; Helgaker, Trygve; Kvaal, Simen; Teale, Andrew M.

2018-01-01

We construct a density-functional formalism adapted to uniform external magnetic fields that is intermediate between conventional density functional theory and Current-Density Functional Theory (CDFT). In the intermediate theory, which we term linear vector potential-DFT (LDFT), the basic variables are the density, the canonical momentum, and the paramagnetic contribution to the magnetic moment. Both a constrained-search formulation and a convex formulation in terms of Legendre-Fenchel transformations are constructed. Many theoretical issues in CDFT find simplified analogs in LDFT. We prove results concerning N-representability, Hohenberg-Kohn-like mappings, existence of minimizers in the constrained-search expression, and a restricted analog to gauge invariance. The issue of additivity of the energy over non-interacting subsystems, which is qualitatively different in LDFT and CDFT, is also discussed.

density functional theory approach

Indian Academy of Sciences (India)

YOGESH ERANDE

2017-07-27

Jul 27, 2017 ... a key role in all optical switching devices, since their optical properties can be .... optimized in the gas phase using Density Functional Theory. (DFT).39 The ...... The Mediation of Electrostatic Effects by Sol- vents J. Am. Chem.

ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

Directory of Open Access Journals (Sweden)

Carmen Moret-Tatay

2018-05-01

Full Text Available The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area. The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density.

Science.gov (United States)

Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro

2018-01-01

The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

THE SLUGGS SURVEY: NGC 3115, A CRITICAL TEST CASE FOR METALLICITY BIMODALITY IN GLOBULAR CLUSTER SYSTEMS

International Nuclear Information System (INIS)

Brodie, Jean P.; Conroy, Charlie; Arnold, Jacob A.; Romanowsky, Aaron J.; Usher, Christopher; Forbes, Duncan A.; Strader, Jay

2012-01-01

Due to its proximity (9 Mpc) and the strongly bimodal color distribution of its spectroscopically well-sampled globular cluster (GC) system, the early-type galaxy NGC 3115 provides one of the best available tests of whether the color bimodality widely observed in GC systems generally reflects a true metallicity bimodality. Color bimodality has alternatively been attributed to a strongly nonlinear color-metallicity relation reflecting the influence of hot horizontal-branch stars. Here, we couple Subaru Suprime-Cam gi photometry with Keck/DEIMOS spectroscopy to accurately measure GC colors and a CaT index that measures the Ca II triplet. We find the NGC 3115 GC system to be unambiguously bimodal in both color and the CaT index. Using simple stellar population models, we show that the CaT index is essentially unaffected by variations in horizontal-branch morphology over the range of metallicities relevant to GC systems (and is thus a robust indicator of metallicity) and confirm bimodality in the metallicity distribution. We assess the existing evidence for and against multiple metallicity subpopulations in early- and late-type galaxies and conclude that metallicity bi/multimodality is common. We briefly discuss how this fundamental characteristic links directly to the star formation and assembly histories of galaxies.

THE SLUGGS SURVEY: NGC 3115, A CRITICAL TEST CASE FOR METALLICITY BIMODALITY IN GLOBULAR CLUSTER SYSTEMS

Energy Technology Data Exchange (ETDEWEB)

Brodie, Jean P.; Conroy, Charlie; Arnold, Jacob A.; Romanowsky, Aaron J. [University of California Observatories and Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States); Usher, Christopher; Forbes, Duncan A. [Centre for Astrophysics and Supercomputing, Swinburne University, Hawthorn, VIC 3122 (Australia); Strader, Jay, E-mail: brodie@ucolick.org [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)

2012-11-10

Due to its proximity (9 Mpc) and the strongly bimodal color distribution of its spectroscopically well-sampled globular cluster (GC) system, the early-type galaxy NGC 3115 provides one of the best available tests of whether the color bimodality widely observed in GC systems generally reflects a true metallicity bimodality. Color bimodality has alternatively been attributed to a strongly nonlinear color-metallicity relation reflecting the influence of hot horizontal-branch stars. Here, we couple Subaru Suprime-Cam gi photometry with Keck/DEIMOS spectroscopy to accurately measure GC colors and a CaT index that measures the Ca II triplet. We find the NGC 3115 GC system to be unambiguously bimodal in both color and the CaT index. Using simple stellar population models, we show that the CaT index is essentially unaffected by variations in horizontal-branch morphology over the range of metallicities relevant to GC systems (and is thus a robust indicator of metallicity) and confirm bimodality in the metallicity distribution. We assess the existing evidence for and against multiple metallicity subpopulations in early- and late-type galaxies and conclude that metallicity bi/multimodality is common. We briefly discuss how this fundamental characteristic links directly to the star formation and assembly histories of galaxies.

Strong Correlation in Kohn-Sham Density Functional Theory

NARCIS (Netherlands)

Malet, F.; Gori Giorgi, P.

2012-01-01

We use the exact strong-interaction limit of the Hohenberg-Kohn energy density functional to approximate the exchange-correlation energy of the restricted Kohn-Sham scheme. Our approximation corresponds to a highly nonlocal density functional whose functional derivative can be easily constructed,

Multiconfiguration Pair-Density Functional Theory Outperforms Kohn-Sham Density Functional Theory and Multireference Perturbation Theory for Ground-State and Excited-State Charge Transfer.

Science.gov (United States)

Ghosh, Soumen; Sonnenberger, Andrew L; Hoyer, Chad E; Truhlar, Donald G; Gagliardi, Laura

2015-08-11

The correct description of charge transfer in ground and excited states is very important for molecular interactions, photochemistry, electrochemistry, and charge transport, but it is very challenging for Kohn-Sham (KS) density functional theory (DFT). KS-DFT exchange-correlation functionals without nonlocal exchange fail to describe both ground- and excited-state charge transfer properly. We have recently proposed a theory called multiconfiguration pair-density functional theory (MC-PDFT), which is based on a combination of multiconfiguration wave function theory with a new type of density functional called an on-top density functional. Here we have used MC-PDFT to study challenging ground- and excited-state charge-transfer processes by using on-top density functionals obtained by translating KS exchange-correlation functionals. For ground-state charge transfer, MC-PDFT performs better than either the PBE exchange-correlation functional or CASPT2 wave function theory. For excited-state charge transfer, MC-PDFT (unlike KS-DFT) shows qualitatively correct behavior at long-range with great improvement in predicted excitation energies.

Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Seunggyu [Korea Aerospace Research Institue, Daejeon (Korea, Republic of); Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2017-05-15

The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

Functional renormalization group and Kohn-Sham scheme in density functional theory

Science.gov (United States)

Liang, Haozhao; Niu, Yifei; Hatsuda, Tetsuo

2018-04-01

Deriving accurate energy density functional is one of the central problems in condensed matter physics, nuclear physics, and quantum chemistry. We propose a novel method to deduce the energy density functional by combining the idea of the functional renormalization group and the Kohn-Sham scheme in density functional theory. The key idea is to solve the renormalization group flow for the effective action decomposed into the mean-field part and the correlation part. Also, we propose a simple practical method to quantify the uncertainty associated with the truncation of the correlation part. By taking the φ4 theory in zero dimension as a benchmark, we demonstrate that our method shows extremely fast convergence to the exact result even for the highly strong coupling regime.

Refining Bimodal Microstructure of Materials with MSTRUCT

Czech Academy of Sciences Publication Activity Database

Matěj, Z.; Kadlecová, A.; Janeček, M.; Matějová, Lenka; Dopita, M.; Kužel, R.

2014-01-01

Roč. 29, S2 (2014), S35-S41 ISSN 0885-7156 R&D Projects: GA ČR GA14-23274S Grant - others:UK(CZ) UNCE 204023/2012 Institutional support: RVO:67985858 Keywords : XRD * bimodal * crystallite size Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 0.636, year: 2014

Density functional theory: Foundations reviewed

Energy Technology Data Exchange (ETDEWEB)

Kryachko, Eugene S., E-mail: eugene.kryachko@ulg.ac.be [Bogolyubov Institute for Theoretical Physics, Kiev, 03680 (Ukraine); Ludeña, Eduardo V., E-mail: popluabe@yahoo.es [Centro de Química, Instituto Venezolano de Investigaciones Científicas, IVIC, Apartado 21827, Caracas 1020-A (Venezuela, Bolivarian Republic of); Prometheus Program, Senescyt (Ecuador); Grupo Ecuatoriano para el Estudio Experimental y Teórico de Nanosistemas, GETNano, USFQ, N104-E, Quito (Ecuador); Escuela Politécnica Superior del Litoral, ESPOL, Guayaquil (Ecuador)

2014-11-10

Guided by the above motto (quotation), we review a broad range of issues lying at the foundations of Density Functional Theory, DFT, a theory which is currently omnipresent in our everyday computational study of atoms and molecules, solids and nano-materials, and which lies at the heart of modern many-body computational technologies. The key goal is to demonstrate that there are definitely the ways to improve DFT. We start by considering DFT in the larger context provided by reduced density matrix theory (RDMT) and natural orbital functional theory (NOFT), and examine the implications that N-representability conditions on the second-order reduced density matrix (2-RDM) have not only on RDMT and NOFT but, also, by extension, on the functionals of DFT. This examination is timely in view of the fact that necessary and sufficient N-representability conditions on the 2-RDM have recently been attained. In the second place, we review some problems appearing in the original formulation of the first Hohenberg–Kohn theorem which is still a subject of some controversy. In this vein we recall Lieb’s comment on this proof and the extension to this proof given by Pino et al. (2009), and in this context examine the conditions that must be met in order that the one-to-one correspondence between ground-state densities and external potentials remains valid for finite subspaces (namely, the subspaces where all Kohn–Sham solutions are obtained in practical applications). We also consider the issue of whether the Kohn–Sham equations can be derived from basic principles or whether they are postulated. We examine this problem in relation to ab initio DFT. The possibility of postulating arbitrary Kohn–Sham-type equations, where the effective potential is by definition some arbitrary mixture of local and non-local terms, is discussed. We also deal with the issue of whether there exists a universal functional, or whether one should advocate instead the construction of problem

Estimation of functional failure probability of passive systems based on subset simulation method

International Nuclear Information System (INIS)

Wang Dongqing; Wang Baosheng; Zhang Jianmin; Jiang Jing

2012-01-01

In order to solve the problem of multi-dimensional epistemic uncertainties and small functional failure probability of passive systems, an innovative reliability analysis algorithm called subset simulation based on Markov chain Monte Carlo was presented. The method is found on the idea that a small failure probability can be expressed as a product of larger conditional failure probabilities by introducing a proper choice of intermediate failure events. Markov chain Monte Carlo simulation was implemented to efficiently generate conditional samples for estimating the conditional failure probabilities. Taking the AP1000 passive residual heat removal system, for example, the uncertainties related to the model of a passive system and the numerical values of its input parameters were considered in this paper. And then the probability of functional failure was estimated with subset simulation method. The numerical results demonstrate that subset simulation method has the high computing efficiency and excellent computing accuracy compared with traditional probability analysis methods. (authors)

Linear scaling of density functional algorithms

International Nuclear Information System (INIS)

Stechel, E.B.; Feibelman, P.J.; Williams, A.R.

1993-01-01

An efficient density functional algorithm (DFA) that scales linearly with system size will revolutionize electronic structure calculations. Density functional calculations are reliable and accurate in determining many condensed matter and molecular ground-state properties. However, because current DFA's, including methods related to that of Car and Parrinello, scale with the cube of the system size, density functional studies are not routinely applied to large systems. Linear scaling is achieved by constructing functions that are both localized and fully occupied, thereby eliminating the need to calculate global eigenfunctions. It is, however, widely believed that exponential localization requires the existence of an energy gap between the occupied and unoccupied states. Despite this, the authors demonstrate that linear scaling can still be achieved for metals. Using a linear scaling algorithm, they have explicitly constructed localized, almost fully occupied orbitals for the quintessential metallic system, jellium. The algorithm is readily generalizable to any system geometry and Hamiltonian. They will discuss the conceptual issues involved, convergence properties and scaling for their new algorithm

Density-Functional formalism

International Nuclear Information System (INIS)

Szasz, L.; Berrios-Pagan, I.; McGinn, G.

1975-01-01

A new Density-Functional formula is constructed for atoms. The kinetic energy of the electron is divided into two parts: the kinetic self-energy and the orthogonalization energy. Calculations were made for the total energies of neutral atoms, positive ions and for the He isoelectronic series. For neutral atoms the results match the Hartree-Fock energies within 1% for atoms with N 36 the results generally match the HF energies within 0.1%. For positive ions the results are fair; for the molecular applications a simplified model is developed in which the kinetic energy consists of the Weizsaecker term plus the Fermi energy reduced by a continuous function. (orig.) [de

Density-functional, density-functional tight-binding, and wave-function calculations on biomolecular systems

Czech Academy of Sciences Publication Activity Database

Kubař, Tomáš; Jurečka, Petr; Černý, Jiří; Řezáč, Jan; Otyepka, M.; Valdes, Haydee; Hobza, Pavel

2007-01-01

Roč. 111, č. 26 (2007), s. 5642-5647 ISSN 1089-5639 R&D Projects: GA MŠk LC512; GA AV ČR IAA400550510; GA ČR(CZ) GD203/05/H001; GA ČR GA203/05/0009 Institutional research plan: CEZ:AV0Z40550506 Keywords : density functional theory * empirical dispersion-energy term * non-covalent interactions Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.918, year: 2007

Children with dyslexia show a reduced processing benefit from bimodal speech information compared to their typically developing peers.

Science.gov (United States)

Schaadt, Gesa; van der Meer, Elke; Pannekamp, Ann; Oberecker, Regine; Männel, Claudia

2018-01-17

During information processing, individuals benefit from bimodally presented input, as has been demonstrated for speech perception (i.e., printed letters and speech sounds) or the perception of emotional expressions (i.e., facial expression and voice tuning). While typically developing individuals show this bimodal benefit, school children with dyslexia do not. Currently, it is unknown whether the bimodal processing deficit in dyslexia also occurs for visual-auditory speech processing that is independent of reading and spelling acquisition (i.e., no letter-sound knowledge is required). Here, we tested school children with and without spelling problems on their bimodal perception of video-recorded mouth movements pronouncing syllables. We analyzed the event-related potential Mismatch Response (MMR) to visual-auditory speech information and compared this response to the MMR to monomodal speech information (i.e., auditory-only, visual-only). We found a reduced MMR with later onset to visual-auditory speech information in children with spelling problems compared to children without spelling problems. Moreover, when comparing bimodal and monomodal speech perception, we found that children without spelling problems showed significantly larger responses in the visual-auditory experiment compared to the visual-only response, whereas children with spelling problems did not. Our results suggest that children with dyslexia exhibit general difficulties in bimodal speech perception independently of letter-speech sound knowledge, as apparent in altered bimodal speech perception and lacking benefit from bimodal information. This general deficit in children with dyslexia may underlie the previously reported reduced bimodal benefit for letter-speech sound combinations and similar findings in emotion perception. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2017-01-01

The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days

Versatile Density Functionals for Computational Surface Science

DEFF Research Database (Denmark)

Wellendorff, Jess

Density functional theory (DFT) emerged almost 50 years ago. Since then DFT has established itself as the central electronic structure methodology for simulating atomicscale systems from a few atoms to a few hundred atoms. This success of DFT is due to a very favorable accuracy-to-computational c......Density functional theory (DFT) emerged almost 50 years ago. Since then DFT has established itself as the central electronic structure methodology for simulating atomicscale systems from a few atoms to a few hundred atoms. This success of DFT is due to a very favorable accuracy...... resampling techniques, thereby systematically avoiding problems with overfitting. The first ever density functional presenting both reliable accuracy and convincing error estimation is generated. The methodology is general enough to be applied to more complex functional forms with higher-dimensional fitting...

Estimation of Bimodal Urban Link Travel Time Distribution and Its Applications in Traffic Analysis

Directory of Open Access Journals (Sweden)

Yuxiong Ji

2015-01-01

Full Text Available Vehicles travelling on urban streets are heavily influenced by traffic signal controls, pedestrian crossings, and conflicting traffic from cross streets, which would result in bimodal travel time distributions, with one mode corresponding to travels without delays and the other travels with delays. A hierarchical Bayesian bimodal travel time model is proposed to capture the interrupted nature of urban traffic flows. The travel time distributions obtained from the proposed model are then considered to analyze traffic operations and estimate travel time distribution in real time. The advantage of the proposed bimodal model is demonstrated using empirical data, and the results are encouraging.

Quadrupole collective dynamics from energy density functionals: Collective Hamiltonian and the interacting boson model

International Nuclear Information System (INIS)

Nomura, K.; Vretenar, D.; Niksic, T.; Otsuka, T.; Shimizu, N.

2011-01-01

Microscopic energy density functionals have become a standard tool for nuclear structure calculations, providing an accurate global description of nuclear ground states and collective excitations. For spectroscopic applications, this framework has to be extended to account for collective correlations related to restoration of symmetries broken by the static mean field, and for fluctuations of collective variables. In this paper, we compare two approaches to five-dimensional quadrupole dynamics: the collective Hamiltonian for quadrupole vibrations and rotations and the interacting boson model (IBM). The two models are compared in a study of the evolution of nonaxial shapes in Pt isotopes. Starting from the binding energy surfaces of 192,194,196 Pt, calculated with a microscopic energy density functional, we analyze the resulting low-energy collective spectra obtained from the collective Hamiltonian, and the corresponding IBM Hamiltonian. The calculated excitation spectra and transition probabilities for the ground-state bands and the γ-vibration bands are compared to the corresponding sequences of experimental states.

Research on bimodal particle extinction coefficient during Brownian coagulation and condensation for the entire particle size regime

International Nuclear Information System (INIS)

Tang Hong; Lin Jianzhong

2011-01-01

The extinction coefficient of atmospheric aerosol particles influences the earth’s radiation balance directly or indirectly, and it can be determined by the scattering and absorption characteristics of aerosol particles. The problem of estimating the change of extinction coefficient due to time evolution of bimodal particle size distribution is studied, and two improved methods for calculating the Brownian coagulation coefficient and the condensation growth rate are proposed, respectively. Through the improved method based on Otto kernel, the Brownian coagulation coefficient can be expressed simply in powers of particle volume for the entire particle size regime based on the fitted polynomials of the mean enhancement function. Meanwhile, the improved method based on Fuchs–Sutugin kernel is developed to obtain the condensation growth rate for the entire particle size regime. And then, the change of the overall extinction coefficient of bimodal distributions undergoing Brownian coagulation and condensation can be estimated comprehensively for the entire particle size regime. Simulation experiments indicate that the extinction coefficients obtained with the improved methods coincide fairly well with the true values, which provide a simple, reliable, and general method to estimate the change of extinction coefficient for the entire particle size regime during the bimodal particle dynamic processes.

Impact of proof test interval and coverage on probability of failure of safety instrumented function

International Nuclear Information System (INIS)

Jin, Jianghong; Pang, Lei; Hu, Bin; Wang, Xiaodong

2016-01-01

Highlights: • Introduction of proof test coverage makes the calculation of the probability of failure for SIF more accurate. • The probability of failure undetected by proof test is independently defined as P TIF and calculated. • P TIF is quantified using reliability block diagram and simple formula of PFD avg . • Improving proof test coverage and adopting reasonable test period can reduce the probability of failure for SIF. - Abstract: Imperfection of proof test can result in the safety function failure of safety instrumented system (SIS) at any time in its life period. IEC61508 and other references ignored or only elementarily analyzed the imperfection of proof test. In order to further study the impact of the imperfection of proof test on the probability of failure for safety instrumented function (SIF), the necessity of proof test and influence of its imperfection on system performance was first analyzed theoretically. The probability of failure for safety instrumented function resulted from the imperfection of proof test was defined as probability of test independent failures (P TIF ), and P TIF was separately calculated by introducing proof test coverage and adopting reliability block diagram, with reference to the simplified calculation formula of average probability of failure on demand (PFD avg ). Research results show that: the shorter proof test period and the higher proof test coverage indicate the smaller probability of failure for safety instrumented function. The probability of failure for safety instrumented function which is calculated by introducing proof test coverage will be more accurate.

Local and linear chemical reactivity response functions at finite temperature in density functional theory

International Nuclear Information System (INIS)

Franco-Pérez, Marco; Ayers, Paul W.; Gázquez, José L.; Vela, Alberto

2015-01-01

We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model

DCMDN: Deep Convolutional Mixture Density Network

Science.gov (United States)

D'Isanto, Antonio; Polsterer, Kai Lars

2017-09-01

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

Evolution of twinning in extruded AZ31 alloy with bimodal grain structure

Energy Technology Data Exchange (ETDEWEB)

Garcés, G., E-mail: ggarces@cenim.csic.es [Department of Physical Metallurgy, National Centre for Metallurgical Research CENIM-CSIC, Av. De Gregorio del Amo 8, 28040 Madrid (Spain); Oñorbe, E. [CIEMAT, Division of Structural Materials, Avenida Complutense, 40, 28040 Madrid (Spain); Gan, W. [German Engineering Materials Science Centre at MLZ, Helmholtz-Zentrum Geesthacht, Lichtebergstr. 1, D-85747 Garching (Germany); Máthis, K. [Department of Physics of Materials, Faculty of Mathematics and Physics, Charles University, KeKarlovu 5, 121 16 Praha 2 (Czech Republic); Tolnai, D. [Institute of Materials Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht (Germany); Horváth, K. [Department of Physics of Materials, Faculty of Mathematics and Physics, Charles University, KeKarlovu 5, 121 16 Praha 2 (Czech Republic); Pérez, P.; Adeva, P. [Department of Physical Metallurgy, National Centre for Metallurgical Research CENIM-CSIC, Av. De Gregorio del Amo 8, 28040 Madrid (Spain)

2017-04-15

Twinning in extruded AZ31 alloy with a bimodal grain structure is studied under compression along the extrusion direction. This study has combined in-situ measurements during the compression tests by Synchrotron Radiation Diffraction and Acoustic Emission techniques and the evaluation of the microstructure and texture in post-mortem compression samples deformed at different strains. The microstructure of the alloy is characterized by the coexistence of large areas of fine dynamic recrystallized grains and coarse non-recrystallized grains elongated along extrusion direction. Twinning occurs initially in large elongated grains before the macroscopic yield stress which is controlled by the twinning in equiaxed dynamically recrystallized grains. - Highlights: • The AZ31 extruded at low temperature exhibits a bimodal grains structure. • Twinning takes place before macroscopic yielding in coarse non-DRXed grains. • DRXed grains controls the beginning of plasticity in magnesium alloys with bimodal grain structure.

Transfer learning for bimodal biometrics recognition

Science.gov (United States)

Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

2013-10-01

Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

概率密度函数法研究重构吸引子的结构%Probability Density Function Method for Observing Reconstructed Attractor Structure

Institute of Scientific and Technical Information of China (English)

陆宏伟; 陈亚珠; 卫青

2004-01-01

Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men.PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor.To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure.Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6-6.5 dimensional complex dynamical systems.It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough.A cluster effect mechanism is presented to explain this phenomenon.By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated.Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.

THE NUMBER DENSITY AND MASS DENSITY OF STAR-FORMING AND QUIESCENT GALAXIES AT 0.4 ≤ z ≤ 2.2

International Nuclear Information System (INIS)

Brammer, Gabriel B.; Whitaker, K. E.; Van Dokkum, P. G.; Lee, K.-S.; Muzzin, A.; Marchesini, D.; Franx, M.; Kriek, M.; Labbe, I.; Quadri, R. F.; Williams, R.; Rudnick, G.

2011-01-01

We study the buildup of the bimodal galaxy population using the NEWFIRM Medium-Band Survey, which provides excellent redshifts and well-sampled spectral energy distributions of ∼27, 000 galaxies with K 3 x 10 10 M sun increases by a factor of ∼10 from z ∼ 2 to the present day, whereas the mass density in star-forming galaxies is flat or decreases over the same time period. Modest mass growth by a factor of ∼2 of individual quiescent galaxies can explain roughly half of the strong density evolution at masses >10 11 M sun , due to the steepness of the exponential tail of the mass function. The rest of the density evolution of massive, quiescent galaxies is likely due to transformation (e.g., quenching) of the massive star-forming population, a conclusion which is consistent with the density evolution we observe for the star-forming galaxies themselves, which is flat or decreasing with cosmic time. Modest mass growth does not explain the evolution of less massive quiescent galaxies (∼10 10.5 M sun ), which show a similarly steep increase in their number densities. The less massive quiescent galaxies are therefore continuously formed by transforming galaxies from the star-forming population.

Diagnostic probability function for acute coronary heart disease garnered from experts' tacit knowledge.

Science.gov (United States)

Steurer, Johann; Held, Ulrike; Miettinen, Olli S

2013-11-01

Knowing about a diagnostic probability requires general knowledge about the way in which the probability depends on the diagnostic indicators involved in the specification of the case at issue. Diagnostic probability functions (DPFs) are generally unavailable at present. Our objective was to illustrate how diagnostic experts' case-specific tacit knowledge about diagnostic probabilities could be garnered in the form of DPFs. Focusing on diagnosis of acute coronary heart disease (ACHD), we presented doctors with extensive experience in hospitals' emergency departments a set of hypothetical cases specified in terms of an inclusive set of diagnostic indicators. We translated the medians of these experts' case-specific probabilities into a logistic DPF for ACHD. The principal result was the experts' typical diagnostic probability for ACHD as a joint function of the set of diagnostic indicators. A related result of note was the finding that the experts' probabilities in any given case had a surprising degree of variability. Garnering diagnostic experts' case-specific tacit knowledge about diagnostic probabilities in the form of DPFs is feasible to accomplish. Thus, once the methodology of this type of work has been "perfected," practice-guiding diagnostic expert systems can be developed. Copyright © 2013 Elsevier Inc. All rights reserved.

A Safari Through Density Functional Theory

Science.gov (United States)

Dreizler, Reiner M.; Lüdde, Cora S.

Density functional theory is widely used to treat quantum many body problems in many areas of physics and related fields. A brief survey of this method covering foundations, functionals and applications is presented here.

Probability in quantum mechanics

Directory of Open Access Journals (Sweden)

J. G. Gilson

1982-01-01

Full Text Available By using a fluid theory which is an alternative to quantum theory but from which the latter can be deduced exactly, the long-standing problem of how quantum mechanics is related to stochastic processes is studied. It can be seen how the Schrödinger probability density has a relationship to time spent on small sections of an orbit, just as the probability density has in some classical contexts.

Time-averaged probability density functions of soot nanoparticles along the centerline of a piloted turbulent diffusion flame using a scanning mobility particle sizer

KAUST Repository

Chowdhury, Snehaunshu

2017-01-23

In this study, we demonstrate the use of a scanning mobility particle sizer (SMPS) as an effective tool to measure the probability density functions (PDFs) of soot nanoparticles in turbulent flames. Time-averaged soot PDFs necessary for validating existing soot models are reported at intervals of ∆x/D∆x/D = 5 along the centerline of turbulent, non-premixed, C2H4/N2 flames. The jet exit Reynolds numbers of the flames investigated were 10,000 and 20,000. A simplified burner geometry based on a published design was chosen to aid modelers. Soot was sampled directly from the flame using a sampling probe with a 0.5-mm diameter orifice and diluted with N2 by a two-stage dilution process. The overall dilution ratio was not evaluated. An SMPS system was used to analyze soot particle concentrations in the diluted samples. Sampling conditions were optimized over a wide range of dilution ratios to eliminate the effect of agglomeration in the sampling probe. Two differential mobility analyzers (DMAs) with different size ranges were used separately in the SMPS measurements to characterize the entire size range of particles. In both flames, the PDFs were found to be mono-modal in nature near the jet exit. Further downstream, the profiles were flatter with a fall-off at larger particle diameters. The geometric mean of the soot size distributions was less than 10 nm for all cases and increased monotonically with axial distance in both flames.

Comparison of exact-exchange calculations for solids in current-spin-density- and spin-density-functional theory

DEFF Research Database (Denmark)

Sharma, S.; Pittalis, S.; Kurth, S.

2007-01-01

The relative merits of current-spin-density- and spin-density-functional theory are investigated for solids treated within the exact-exchange-only approximation. Spin-orbit splittings and orbital magnetic moments are determined at zero external magnetic field. We find that for magnetic (Fe, Co......, and Ni) and nonmagnetic (Si and Ge) solids, the exact-exchange current-spin-density functional approach does not significantly improve the accuracy of the corresponding spin-density functional results....

Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States.

Science.gov (United States)

Vargas-Melendez, Leandro; Boada, Beatriz L; Boada, Maria Jesus L; Gauchia, Antonio; Diaz, Vicente

2017-04-29

Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33 % of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm.

Dynamical density functional theory for dense atomic liquids

International Nuclear Information System (INIS)

Archer, A J

2006-01-01

Starting from Newton's equations of motion, we derive a dynamical density functional theory (DDFT) applicable to atomic liquids. The theory has the feature that it requires as input the Helmholtz free energy functional from equilibrium density functional theory. This means that, given a reliable equilibrium free energy functional, the correct equilibrium fluid density profile is guaranteed. We show that when the isothermal compressibility is small, the DDFT generates the correct value for the speed of sound in a dense liquid. We also interpret the theory as a dynamical equation for a coarse grained fluid density and show that the theory can be used (making further approximations) to derive the standard mode coupling theory that is used to describe the glass transition. The present theory should provide a useful starting point for describing the dynamics of inhomogeneous atomic fluids

Constructive definition of functional derivatives in density-functional theory

International Nuclear Information System (INIS)

Luo Ji

2006-01-01

It is shown that the functional derivatives in density-functional theory (DFT) can be explicitly defined within the domain of electron densities restricted by the electron number, and a constructive definition of such restricted derivatives is suggested. With this definition, Kohn-Sham (KS) equations can be established for an N-electron system without extending the functional domain and introducing a Lagrange multiplier. This may clarify some of the fundamental questions raised by Nesbet (1998 Phys. Rev. A 58 R12). The definition naturally leads to the fact that the KS effective potential is determined only to within an additive constant, thus the KS levels can shift freely and the relation between the highest occupied molecular orbital (HOMO) energy and the ionization potential of the system depends on the choice of the constant. On the other hand, if the domain of functionals is indeed extended beyond the electron number restriction, conclusions depend on whether the extended functionals have unrestricted derivatives or not. It is shown that the ensemble extension of DFT to open systems of mixed states (Perdew et al 1982 Phys. Rev. Lett. 49 1691) leads to an energy functional which has no unrestricted derivative at integer electron numbers. Hence after this extension, the relation between the HOMO energy and the ionization potential for an N-electron system is still uncertain. Besides, there are different extensions of the energy functional to a domain of densities unrestricted by the integer electron number, resulting in different unrestricted derivatives and electron systems with different chemical potentials. Even for the exact exchange-correlation potential, there is still an undetermined constant, whether it is a restricted or unrestricted derivative

Density functional theory in quantum chemistry

CERN Document Server

Tsuneda, Takao

2014-01-01

This book examines density functional theory based on the foundation of quantum chemistry. Unconventional in approach, it reviews basic concepts, then describes the physical meanings of state-of-the-art exchange-correlation functionals and their corrections.

Conserving relativistic many-body approach: Equation of state, spectral function, and occupation probabilities of nuclear matter

International Nuclear Information System (INIS)

de Jong, F.; Malfliet, R.

1991-01-01

Starting from a relativistic Lagrangian we derive a ''conserving'' approximation for the description of nuclear matter. We show this to be a nontrivial extension over the relativistic Dirac-Brueckner scheme. The saturation point of the equation of state calculated agrees very well with the empirical saturation point. The conserving character of the approach is tested by means of the Hugenholtz--van Hove theorem. We find the theorem fulfilled very well around saturation. A new value for compression modulus is derived, K=310 MeV. Also we calculate the occupation probabilities at normal nuclear matter densities by means of the spectral function. The average depletion κ of the Fermi sea is found to be κ∼0.11

Comment on 'Kinetic energy as a density functional'

International Nuclear Information System (INIS)

Holas, A.; March, N.H.

2002-01-01

In a recent paper, Nesbet [Phys. Rev. A 65, 010502(R) (2001)] has proposed dropping ''the widespread but unjustified assumption that the existence of a ground-state density functional for the kinetic energy, T s [ρ], of an N-electron system implies the existence of a density-functional derivative, δT s [ρ]/δρ(r), equivalent to a local potential function,'' because, according to his arguments, this derivative 'has the mathematical character of a linear operator that acts on orbital wave functions'. Our Comment demonstrates that the statement called by Nesbet an 'unjustified assumption' happens, in fact, to be a rigorously proven theorem. Therefore, his previous conclusions stemming from his different view of this derivative, which undermined the foundations of density-functional theory, can be discounted

SYNTHESIS, CHARACTERIZATION AND DENSITY FUNCTIONAL ...

African Journals Online (AJOL)

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We synthesized a number of aniline derivatives containing acyl groups to compare their barriers of rotation around ... KEY WORDS: Monoacyl aniline, Synthesis, Density functional theory, Rotation barrier. INTRODUCTION. Developments in ...

The intensity detection of single-photon detectors based on photon counting probability density statistics

International Nuclear Information System (INIS)

Zhang Zijing; Song Jie; Zhao Yuan; Wu Long

2017-01-01

Single-photon detectors possess the ultra-high sensitivity, but they cannot directly respond to signal intensity. Conventional methods adopt sampling gates with fixed width and count the triggered number of sampling gates, which is capable of obtaining photon counting probability to estimate the echo signal intensity. In this paper, we not only count the number of triggered sampling gates, but also record the triggered time position of photon counting pulses. The photon counting probability density distribution is obtained through the statistics of a series of the triggered time positions. Then Minimum Variance Unbiased Estimation (MVUE) method is used to estimate the echo signal intensity. Compared with conventional methods, this method can improve the estimation accuracy of echo signal intensity due to the acquisition of more detected information. Finally, a proof-of-principle laboratory system is established. The estimation accuracy of echo signal intensity is discussed and a high accuracy intensity image is acquired under low-light level environments. (paper)

Density functional approach to the many-body problem : Key concepts and exact functionals

NARCIS (Netherlands)

van Leeuwen, Robert

2003-01-01

We give an overview of the fundamental concepts of density functional theory. We give a careful discussion of the several density functionals and their differentiability properties. We show that for nondegenerate ground states we can calculate the necessary functional derivatives by means of linear

Does bimodal stimulus presentation increase ERP components usable in BCIs?

Science.gov (United States)

Thurlings, Marieke E.; Brouwer, Anne-Marie; Van Erp, Jan B. F.; Blankertz, Benjamin; Werkhoven, Peter J.

2012-08-01

Event-related potential (ERP)-based brain-computer interfaces (BCIs) employ differences in brain responses to attended and ignored stimuli. Typically, visual stimuli are used. Tactile stimuli have recently been suggested as a gaze-independent alternative. Bimodal stimuli could evoke additional brain activity due to multisensory integration which may be of use in BCIs. We investigated the effect of visual-tactile stimulus presentation on the chain of ERP components, BCI performance (classification accuracies and bitrates) and participants’ task performance (counting of targets). Ten participants were instructed to navigate a visual display by attending (spatially) to targets in sequences of either visual, tactile or visual-tactile stimuli. We observe that attending to visual-tactile (compared to either visual or tactile) stimuli results in an enhanced early ERP component (N1). This bimodal N1 may enhance BCI performance, as suggested by a nonsignificant positive trend in offline classification accuracies. A late ERP component (P300) is reduced when attending to visual-tactile compared to visual stimuli, which is consistent with the nonsignificant negative trend of participants’ task performance. We discuss these findings in the light of affected spatial attention at high-level compared to low-level stimulus processing. Furthermore, we evaluate bimodal BCIs from a practical perspective and for future applications.

RSMASS-D nuclear thermal propulsion and bimodal system mass models

Science.gov (United States)

King, Donald B.; Marshall, Albert C.

1997-01-01

Two relatively simple models have been developed to estimate reactor, radiation shield, and balance of system masses for a particle bed reactor (PBR) nuclear thermal propulsion concept and a cermet-core power and propulsion (bimodal) concept. The approach was based on the methodology developed for the RSMASS-D models. The RSMASS-D approach for the reactor and shield sub-systems uses a combination of simple equations derived from reactor physics and other fundamental considerations along with tabulations of data from more detailed neutron and gamma transport theory computations. Relatively simple models are used to estimate the masses of other subsystem components of the nuclear propulsion and bimodal systems. Other subsystem components include instrumentation and control (I&C), boom, safety systems, radiator, thermoelectrics, heat pipes, and nozzle. The user of these models can vary basic design parameters within an allowed range to achieve a parameter choice which yields a minimum mass for the operational conditions of interest. Estimated system masses are presented for a range of reactor power levels for propulsion for the PBR propulsion concept and for both electrical power and propulsion for the cermet-core bimodal concept. The estimated reactor system masses agree with mass predictions from detailed calculations with xx percent for both models.

Extended screened exchange functional derived from transcorrelated density functional theory.

Science.gov (United States)

Umezawa, Naoto

2017-09-14

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

Probability laws related to the Jacobi theta and Riemann zeta function and Brownian excursions

OpenAIRE

Biane, P.; Pitman, J.; Yor, M.

1999-01-01

This paper reviews known results which connect Riemann's integral representations of his zeta function, involving Jacobi's theta function and its derivatives, to some particular probability laws governing sums of independent exponential variables. These laws are related to one-dimensional Brownian motion and to higher dimensional Bessel processes. We present some characterizations of these probability laws, and some approximations of Riemann's zeta function which are related to these laws.

Observability of the probability current density using spin rotator as a quantum clock

International Nuclear Information System (INIS)

Home, D.; Alok Kumar Pan; Md Manirul Ali

2005-01-01

Full text: An experimentally realizable scheme is formulated which can test any quantum mechanical approach for calculating the arrival time distribution. This is specifically illustrated by using the modulus of the probability current density for calculating the arrival time distribution of spin-1/2 neutral particles at the exit point of a spin rotator (SR) which contains a constant magnetic field. Such a calculated time distribution is then used for evaluating the distribution of spin orientations along different directions for these particles emerging from the SR. Based on this, the result of spin measurement along any arbitrary direction for such an ensemble is predicted. (author)

Quantum Crystallography: Density Matrix-Density Functional Theory and the X-Ray Diffraction Experiment

Science.gov (United States)

Soirat, Arnaud J. A.

Density Matrix Theory is a Quantum Mechanical formalism in which the wavefunction is eliminated and its role taken over by reduced density matrices. The interest of this is that, it allows one, in principle, to calculate any electronic property of a physical system, without having to solve the Schrodinger equation, using only two entities much simpler than an N-body wavefunction: first and second -order reduced density matrices. In practice, though, this very promising possibility faces the tremendous theoretical problem of N-representability, which has been solved for the former, but, until now, voids any hope of theoretically determining the latter. However, it has been shown that single determinant reduced density matrices of any order may be recovered from coherent X-ray diffraction data, if one provides a proper Quantum Mechanical description of the Crystallography experiment. A deeper investigation of this method is the purpose of this work, where we, first, further study the calculation of X-ray reduced density matrices N-representable by a single Slater determinant. In this context, we independently derive necessary and sufficient conditions for the uniqueness of the method. We then show how to account for electron correlation in this model. For the first time, indeed, we derive highly accurate, yet practical, density matrices approximately N-representable by correlated-determinant wavefunctions. The interest of such a result lies in the Quantum Mechanical validity of these density matrices, their property of being entirely obtainable from X-ray coherent diffraction data, their very high accuracy conferred by this known property of the N-representing wavefunction, as well as their definition as explicit functionals of the density. All of these properties are finally used in both a theoretical and a numerical application: in the former, we show that these density matrices may be used in the context of Density Functional Theory to highly accurately determine

Density functional theory of nuclei

International Nuclear Information System (INIS)

Terasaki, Jun

2008-01-01

The density functional theory of nuclei has come to draw attention of scientists in the field of nuclear structure because the theory is expected to provide reliable numerical data in wide range on the nuclear chart. This article is organized to present an overview of the theory to the people engaged in the theory of other fields as well as those people in the nuclear physics experiments. At first, the outline of the density functional theory widely used in the electronic systems (condensed matter, atoms, and molecules) was described starting from the Kohn-Sham equation derived on the variational principle. Then the theory used in the field of nuclear physics was presented. Hartree-Fock and Hartree-Fock-Bogolyubov approximation by using Skyrme interaction was explained. Comparison of the results of calculations and experiments of binding energies and ground state mean square charge radii of some magic number nuclei were shown. The similarity and dissimilarity between the two streams were summarized. Finally the activities of the international project of Universal Nuclear Energy Density Functional (UNEDF) which was started recently lead by US scientist was reported. This project is programmed for five years. One of the applications of the project is the calculation of the neutron capture cross section of nuclei on the r-process, which is absolutely necessary for the nucleosynthesis research. (S. Funahashi)

Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used

Directory of Open Access Journals (Sweden)

Cinicioglu Esma Nur

2014-01-01

Full Text Available Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of a decision theory of belief functions gives rise to the need to use the probability transformation methods for decision making. For representation of statistical evidence, the class of consonant belief functions is used which is not closed under Dempster’s rule of combination but is closed under Walley’s rule of combination. In this research, it is shown that the outcomes obtained using both Dempster’s and Walley’s rules do result in different probability distributions when pignistic transformation is used. However, when plausibility transformation is used, they do result in the same probability distribution. This result shows that the choice of the combination rule and probability transformation method may have a significant effect on decision making since it may change the choice of the decision alternative selected. This result is illustrated via an example of missile type identification.

Use of probability tables for propagating uncertainties in neutronics

International Nuclear Information System (INIS)

Coste-Delclaux, M.; Diop, C.M.; Lahaye, S.

2017-01-01

Highlights: • Moment-based probability table formalism is described. • Representation by probability tables of any uncertainty distribution is established. • Multiband equations for two kinds of uncertainty propagation problems are solved. • Numerical examples are provided and validated against Monte Carlo simulations. - Abstract: Probability tables are a generic tool that allows representing any random variable whose probability density function is known. In the field of nuclear reactor physics, this tool is currently used to represent the variation of cross-sections versus energy (neutron transport codes TRIPOLI4®, MCNP, APOLLO2, APOLLO3®, ECCO/ERANOS…). In the present article we show how we can propagate uncertainties, thanks to a probability table representation, through two simple physical problems: an eigenvalue problem (neutron multiplication factor) and a depletion problem.

Optimal Bandwidth Selection for Kernel Density Functionals Estimation

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Su Chen

2015-01-01

Full Text Available The choice of bandwidth is crucial to the kernel density estimation (KDE and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade. It has been known that scale and location parameters are proportional to density functionals ∫γ(xf2(xdx with appropriate choice of γ(x and furthermore equality of scale and location tests can be transformed to comparisons of the density functionals among populations. ∫γ(xf2(xdx can be estimated nonparametrically via kernel density functionals estimation (KDFE. However, the optimal bandwidth selection for KDFE of ∫γ(xf2(xdx has not been examined. We propose a method to select the optimal bandwidth for the KDFE. The idea underlying this method is to search for the optimal bandwidth by minimizing the mean square error (MSE of the KDFE. Two main practical bandwidth selection techniques for the KDFE of ∫γ(xf2(xdx are provided: Normal scale bandwidth selection (namely, “Rule of Thumb” and direct plug-in bandwidth selection. Simulation studies display that our proposed bandwidth selection methods are superior to existing density estimation bandwidth selection methods in estimating density functionals.

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

Science.gov (United States)

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Diverse Kir expression contributes to distinct bimodal distribution of resting potentials and vasotone responses of arterioles.

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Yuqin Yang

Full Text Available The resting membrane potential (RP of vascular smooth muscle cells (VSMCs is a major determinant of cytosolic calcium concentration and vascular tone. The heterogeneity of RPs and its underlying mechanism among different vascular beds remain poorly understood. We compared the RPs and vasomotion properties between the guinea pig spiral modiolar artery (SMA, brain arterioles (BA and mesenteric arteries (MA. We found: 1 RPs showed a robust bimodal distribution peaked at -76 and -40 mV evenly in the SMA, unevenly at -77 and -51 mV in the BA and ~-71 and -52 mV in the MA. Ba(2+ 0.1 mM eliminated their high RP peaks ~-75 mV. 2 Cells with low RP (~-45 mV hyperpolarized in response to 10 mM extracellular K(+, while cells with a high RP depolarized, and cells with intermediate RP (~-58 mV displayed an initial hyperpolarization followed by prolonged depolarization. Moderate high K(+ typically induced dilation, constriction and a dilation followed by constriction in the SMA, MA and BA, respectively. 3 Boltzmann-fit analysis of the Ba(2+-sensitive inward rectifier K(+ (Kir whole-cell current showed that the maximum Kir conductance density significantly differed among the vessels, and the half-activation voltage was significantly more negative in the MA. 4 Corresponding to the whole-cell data, computational modeling simulated the three RP distribution patterns and the dynamics of RP changes obtained experimentally, including the regenerative swift shifts between the two RP levels after reaching a threshold. 5 Molecular works revealed strong Kir2.1 and Kir2.2 transcripts and Kir2.1 immunolabeling in all 3 vessels, while Kir2.3 and Kir2.4 transcript levels varied. We conclude that a dense expression of functional Kir2.X channels underlies the more negative RPs in endothelial cells and a subset of VSMC in these arterioles, and the heterogeneous Kir function is primarily responsible for the distinct bimodal RPs among these arterioles. The fast Kir

Are star formation rates of galaxies bimodal?

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Feldmann, Robert

2017-09-01

Star formation rate (SFR) distributions of galaxies are often assumed to be bimodal with modes corresponding to star-forming and quiescent galaxies, respectively. Both classes of galaxies are typically studied separately, and SFR distributions of star-forming galaxies are commonly modelled as lognormals. Using both observational data and results from numerical simulations, I argue that this division into star-forming and quiescent galaxies is unnecessary from a theoretical point of view and that the SFR distributions of the whole population can be well fitted by zero-inflated negative binomial distributions. This family of distributions has three parameters that determine the average SFR of the galaxies in the sample, the scatter relative to the star-forming sequence and the fraction of galaxies with zero SFRs, respectively. The proposed distributions naturally account for (I) the discrete nature of star formation, (II) the presence of 'dead' galaxies with zero SFRs and (III) asymmetric scatter. Excluding 'dead' galaxies, the distribution of log SFR is unimodal with a peak at the star-forming sequence and an extended tail towards low SFRs. However, uncertainties and biases in the SFR measurements can create the appearance of a bimodal distribution.

Role of block copolymer adsorption versus bimodal grafting on nanoparticle self-assembly in polymer nanocomposites.

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Zhao, Dan; Di Nicola, Matteo; Khani, Mohammad M; Jestin, Jacques; Benicewicz, Brian C; Kumar, Sanat K

2016-09-14

We compare the self-assembly of silica nanoparticles (NPs) with physically adsorbed polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP) copolymers (BCP) against NPs with grafted bimodal (BM) brushes comprised of long, sparsely grafted PS chains and a short dense carpet of P2VP chains. As with grafted NPs, the dispersion state of the BCP NPs can be facilely tuned in PS matrices by varying the PS coverage on the NP surface or by changes in the ratio of the PS graft to matrix chain lengths. Surprisingly, the BCP NPs are remarkably better dispersed than the NPs tethered with bimodal brushes at comparable PS grafting densities. We postulate that this difference arises because of two factors inherent in the synthesis of the NPs: In the case of the BCP NPs the adsorption process is analogous to the chains being "grafted to" the NP surface, while the BM case corresponds to "grafting from" the surface. We have shown that the "grafted from" protocol yields patchy NPs even if the graft points are uniformly placed on each particle. This phenomenon, which is caused by chain conformation fluctuations, is exacerbated by the distribution function associated with the (small) number of grafts per particle. In contrast, in the case of BCP adsorption, each NP is more uniformly coated by a P2VP monolayer driven by the strongly favorable P2VP-silica interactions. Since each P2VP block is connected to a PS chain we conjecture that these adsorbed systems are closer to the limit of spatially uniform sparse brush coverage than the chemically grafted case. We finally show that the better NP dispersion resulting from BCP adsorption leads to larger mechanical reinforcement than those achieved with BM particles. These results emphasize that physical adsorption of BCPs is a simple, effective and practically promising strategy to direct NP dispersion in a chemically unfavorable polymer matrix.

Reduced density-matrix functional theory: Correlation and spectroscopy.

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Di Sabatino, S; Berger, J A; Reining, L; Romaniello, P

2015-07-14

In this work, we explore the performance of approximations to electron correlation in reduced density-matrix functional theory (RDMFT) and of approximations to the observables calculated within this theory. Our analysis focuses on the calculation of total energies, occupation numbers, removal/addition energies, and spectral functions. We use the exactly solvable Hubbard dimer at 1/4 and 1/2 fillings as test systems. This allows us to analyze the underlying physics and to elucidate the origin of the observed trends. For comparison, we also report the results of the GW approximation, where the self-energy functional is approximated, but no further hypothesis is made concerning the approximations of the observables. In particular, we focus on the atomic limit, where the two sites of the dimer are pulled apart and electrons localize on either site with equal probability, unless a small perturbation is present: this is the regime of strong electron correlation. In this limit, using the Hubbard dimer at 1/2 filling with or without a spin-symmetry-broken ground state allows us to explore how degeneracies and spin-symmetry breaking are treated in RDMFT. We find that, within the used approximations, neither in RDMFT nor in GW, the signature of strong correlation is present, when looking at the removal/addition energies and spectral function from the spin-singlet ground state, whereas both give the exact result for the spin-symmetry broken case. Moreover, we show how the spectroscopic properties change from one spin structure to the other.

Non-Gaussian theory of rubberlike elasticity based on rotational isomeric state simulations of network chain configurations. II. Bimodal poly(dimethylsiloxane) networks

International Nuclear Information System (INIS)

Curro, J.G.; Mark, J.E.

1984-01-01

Bimodal, poly(dimethylsiloxane) (PDMS) networks containing a large mole fraction of very short chains have been shown to be unusually tough elastomers. The purpose of this investigation is to understand the rubber elasticity behavior of these bimodal networks. As a first approach, we have assumed that the average chain deformation is affine. This deformation, however, is partitioned nonaffinely between the long and short chains so that the free energy is minimized. Gaussian statistics are used for the long chains. The distribution function for the short chains is found from Monte Carlo calculations. This model predicts an upturn in the stress-strain curve, the steepness depending on the network composition, as is observed experimentally

Current Density Functional Theory Using Meta-Generalized Gradient Exchange-Correlation Functionals.

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Furness, James W; Verbeke, Joachim; Tellgren, Erik I; Stopkowicz, Stella; Ekström, Ulf; Helgaker, Trygve; Teale, Andrew M

2015-09-08

We present the self-consistent implementation of current-dependent (hybrid) meta-generalized gradient approximation (mGGA) density functionals using London atomic orbitals. A previously proposed generalized kinetic energy density is utilized to implement mGGAs in the framework of Kohn-Sham current density functional theory (KS-CDFT). A unique feature of the nonperturbative implementation of these functionals is the ability to seamlessly explore a wide range of magnetic fields up to 1 au (∼235 kT) in strength. CDFT functionals based on the TPSS and B98 forms are investigated, and their performance is assessed by comparison with accurate coupled-cluster singles, doubles, and perturbative triples (CCSD(T)) data. In the weak field regime, magnetic properties such as magnetizabilities and nuclear magnetic resonance shielding constants show modest but systematic improvements over generalized gradient approximations (GGA). However, in the strong field regime, the mGGA-based forms lead to a significantly improved description of the recently proposed perpendicular paramagnetic bonding mechanism, comparing well with CCSD(T) data. In contrast to functionals based on the vorticity, these forms are found to be numerically stable, and their accuracy at high field suggests that the extension of mGGAs to CDFT via the generalized kinetic energy density should provide a useful starting point for further development of CDFT approximations.

Auditory-somatosensory bimodal stimulation desynchronizes brain circuitry to reduce tinnitus in guinea pigs and humans.

Science.gov (United States)

Marks, Kendra L; Martel, David T; Wu, Calvin; Basura, Gregory J; Roberts, Larry E; Schvartz-Leyzac, Kara C; Shore, Susan E

2018-01-03

The dorsal cochlear nucleus is the first site of multisensory convergence in mammalian auditory pathways. Principal output neurons, the fusiform cells, integrate auditory nerve inputs from the cochlea with somatosensory inputs from the head and neck. In previous work, we developed a guinea pig model of tinnitus induced by noise exposure and showed that the fusiform cells in these animals exhibited increased spontaneous activity and cross-unit synchrony, which are physiological correlates of tinnitus. We delivered repeated bimodal auditory-somatosensory stimulation to the dorsal cochlear nucleus of guinea pigs with tinnitus, choosing a stimulus interval known to induce long-term depression (LTD). Twenty minutes per day of LTD-inducing bimodal (but not unimodal) stimulation reduced physiological and behavioral evidence of tinnitus in the guinea pigs after 25 days. Next, we applied the same bimodal treatment to 20 human subjects with tinnitus using a double-blinded, sham-controlled, crossover study. Twenty-eight days of LTD-inducing bimodal stimulation reduced tinnitus loudness and intrusiveness. Unimodal auditory stimulation did not deliver either benefit. Bimodal auditory-somatosensory stimulation that induces LTD in the dorsal cochlear nucleus may hold promise for suppressing chronic tinnitus, which reduces quality of life for millions of tinnitus sufferers worldwide. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

How bilingualism protects the brain from aging: Insights from bimodal bilinguals.

Science.gov (United States)

Li, Le; Abutalebi, Jubin; Emmorey, Karen; Gong, Gaolang; Yan, Xin; Feng, Xiaoxia; Zou, Lijuan; Ding, Guosheng

2017-08-01

Bilingual experience can delay cognitive decline during aging. A general hypothesis is that the executive control system of bilinguals faces an increased load due to controlling two languages, and this increased load results in a more "tuned brain" that eventually creates a neural reserve. Here we explored whether such a neuroprotective effect is independent of language modality, i.e., not limited to bilinguals who speak two languages but also occurs for bilinguals who use a spoken and a signed language. We addressed this issue by comparing bimodal bilinguals to monolinguals in order to detect age-induced structural brain changes and to determine whether we can detect the same beneficial effects on brain structure, in terms of preservation of gray matter volume (GMV), for bimodal bilinguals as has been reported for unimodal bilinguals. Our GMV analyses revealed a significant interaction effect of age × group in the bilateral anterior temporal lobes, left hippocampus/amygdala, and left insula where bimodal bilinguals showed slight GMV increases while monolinguals showed significant age-induced GMV decreases. We further found through cortical surface-based measurements that this effect was present for surface area and not for cortical thickness. Moreover, to further explore the hypothesis that overall bilingualism provides neuroprotection, we carried out a direct comparison of GMV, extracted from the brain regions reported above, between bimodal bilinguals, unimodal bilinguals, and monolinguals. Bilinguals, regardless of language modality, exhibited higher GMV compared to monolinguals. This finding highlights the general beneficial effects provided by experience handling two language systems, whether signed or spoken. Hum Brain Mapp 38:4109-4124, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates.

Science.gov (United States)

Pardo-Igúzquiza, Eulogio; Chica-Olmo, Mario; Luque-Espinar, Juan A; Rodríguez-Galiano, Víctor

2015-11-01

Contamination by nitrates is an important cause of groundwater pollution and represents a potential risk to human health. Management decisions must be made using probability maps that assess the nitrate concentration potential of exceeding regulatory thresholds. However these maps are obtained with only a small number of sparse monitoring locations where the nitrate concentrations have been measured. It is therefore of great interest to have an efficient methodology for obtaining those probability maps. In this paper, we make use of the fact that the discrete probability density function is a compositional variable. The spatial discrete probability density function is estimated by compositional cokriging. There are several advantages in using this approach: (i) problems of classical indicator cokriging, like estimates outside the interval (0,1) and order relations, are avoided; (ii) secondary variables (e.g. aquifer parameters) can be included in the estimation of the probability maps; (iii) uncertainty maps of the probability maps can be obtained; (iv) finally there are modelling advantages because the variograms and cross-variograms of real variables that do not have the restrictions of indicator variograms and indicator cross-variograms. The methodology was applied to the Vega de Granada aquifer in Southern Spain and the advantages of the compositional cokriging approach were demonstrated. Copyright © 2015 Elsevier B.V. All rights reserved.

Comments on the locality in density-functional theory

International Nuclear Information System (INIS)

Lindgren, Ingvar; Salomonson, Sten

2003-01-01

The 'locality hypothesis' in density-functional theory (DFT), implying that the functional derivative is equivalent to a multiplicative local function, forms the basis of models of Kohn-Sham type. This has been generally accepted by the community since the advent of the model, and has later been formally proved for a large class of functionals. The hypothesis has recently been questioned by Nesbet [Phys. Rev. A 58, R12 (1998) and Phys. Rev. A 65, 010502 (2001)], who claims that it fails for the kinetic-energy functional for a system with more than two noninteracting electrons with a nondegenerate ground state. This conclusion has been questioned by Gal [Phys. Rev. A 62, 044501 (2000)] and by Holas and March [Phys. Rev. A 64, 016501 (2001)]. We claim that the arguments of Nesbet are incorrect, since the orbital functional used for the kinetic energy is not a unique functional of the total density in the domain of unnormalized orbitals. We have demonstrated that with a proper definition of the kinetic energy, which is a unique density functional also in the unnormalized region, the derivative can be represented by a single local multiplicative function for all v-representable densities. Therefore, we consider the controversy connected with the issue raised by Nesbet as resolved. We believe that the proof of the differentiability given here can be extended to larger groups of DFT functionals, and works along these lines are in progress

The Efficiency of the Bimodal System Transportation

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Nada Štrumberger

2012-10-01

Full Text Available The development of fast railway results in an increased applicationof Trailer Train bimodal system transportation. Thetraffic costs are multiply reduced, particularly the variablecosts. On the other hand the environmental pollution from exhaustgases is also reduced. Therefore, by the year 2010 cargotransport should be preponderant~v used which would be characterisedby fast electric trains producing less noise, at lowercosts and with clean environment.

The distribution function of a probability measure on a space with a fractal structure

Energy Technology Data Exchange (ETDEWEB)

Sanchez-Granero, M.A.; Galvez-Rodriguez, J.F.

2017-07-01

In this work we show how to define a probability measure with the help of a fractal structure. One of the keys of this approach is to use the completion of the fractal structure. Then we use the theory of a cumulative distribution function on a Polish ultrametric space and describe it in this context. Finally, with the help of fractal structures, we prove that a function satisfying the properties of a cumulative distribution function on a Polish ultrametric space is a cumulative distribution function with respect to some probability measure on the space. (Author)

Probability density function of the number of embryos collected from superovulated Nelore breed donors Função de densidade de probabilidade do número de embriões produzidos por doadoras da raça Nelore

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Renato Travassos Beltrame

2009-08-01

Full Text Available Several models have been developed to evaluate reproductive status of cows through concentration of progesterone in milk, the effect of sex selection in the commercial production of herds and bioeconomic performance of the multiple ovulation and embryo transfer system in select herds. However, models describing the production of embryos in superovulated females have yet to be developed. A probability density function of the number of embryos collected by donors of the Nelore breed was determined. Records of 61,928 embryo collections from 26,767 donors from 1991 to 2005 were analyzed. Data were provided by the Brazilian Association of Creators of Zebu and Controlmax Consultoria e Sistemas Ltda. The probability density function of the number of viable embryos was modeled using exponential and gamma distributions. Parameter fitting was carried out for maximum likelihood using a non-linear gradient method. Both distributions presented similar level of precision: root mean square error (RMSE = 0.0072 and 0.0071 for the exponential and gamma distributions, respectively; both distributions are thus deemed suitable for representing the probability density function of embryo production by Nelore females.Diversos modelos têm sido desenvolvidos para avaliar o estado reprodutivo de vacas por meio da concentração de progesterona no leite, o efeito da seleção do sexo na produção comercial de rebanhos e o desempenho bioeconômico da ovulação múltipla e transferência de embriões em rebanhos selecionados. No entanto, modelos que descrevem a produção de embriões em fêmeas superovulados ainda têm de ser desenvolvidos. Uma função de densidade probabilidade para o número de embriões viáveis recuperados de doadoras da raça Nelore foi determinada. Dados de 61.928 coletas de 26.767 doadoras entre 1991 e 2005 foram analisados. Os resultados foram fornecidos pela Associação Brasileira de Criadores de Zebu (ABCZ e pela empresa Controlmax

Trivial constraints on orbital-free kinetic energy density functionals

Science.gov (United States)

Luo, Kai; Trickey, S. B.

2018-03-01

Approximate kinetic energy density functionals (KEDFs) are central to orbital-free density functional theory. Limitations on the spatial derivative dependencies of KEDFs have been claimed from differential virial theorems. We identify a central defect in the argument: the relationships are not true for an arbitrary density but hold only for the minimizing density and corresponding chemical potential. Contrary to the claims therefore, the relationships are not constraints and provide no independent information about the spatial derivative dependencies of approximate KEDFs. A simple argument also shows that validity for arbitrary v-representable densities is not restored by appeal to the density-potential bijection.

Computing exact bundle compliance control charts via probability generating functions.

Science.gov (United States)

Chen, Binchao; Matis, Timothy; Benneyan, James

2016-06-01

Compliance to evidenced-base practices, individually and in 'bundles', remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

Self-consistent embedding of density-matrix renormalization group wavefunctions in a density functional environment.

Science.gov (United States)

Dresselhaus, Thomas; Neugebauer, Johannes; Knecht, Stefan; Keller, Sebastian; Ma, Yingjin; Reiher, Markus

2015-01-28

We present the first implementation of a density matrix renormalization group algorithm embedded in an environment described by density functional theory. The frozen density embedding scheme is used with a freeze-and-thaw strategy for a self-consistent polarization of the orbital-optimized wavefunction and the environmental densities with respect to each other.

Geometric modeling in probability and statistics

CERN Document Server

Calin, Ovidiu

2014-01-01

This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader...

Rydberg energies using excited state density functional theory

International Nuclear Information System (INIS)

Cheng, C.-L.; Wu Qin; Van Voorhis, Troy

2008-01-01

We utilize excited state density functional theory (eDFT) to study Rydberg states in atoms. We show both analytically and numerically that semilocal functionals can give quite reasonable Rydberg energies from eDFT, even in cases where time dependent density functional theory (TDDFT) fails catastrophically. We trace these findings to the fact that in eDFT the Kohn-Sham potential for each state is computed using the appropriate excited state density. Unlike the ground state potential, which typically falls off exponentially, the sequence of excited state potentials has a component that falls off polynomially with distance, leading to a Rydberg-type series. We also address the rigorous basis of eDFT for these systems. Perdew and Levy have shown using the constrained search formalism that every stationary density corresponds, in principle, to an exact stationary state of the full many-body Hamiltonian. In the present context, this means that the excited state DFT solutions are rigorous as long as they deliver the minimum noninteracting kinetic energy for the given density. We use optimized effective potential techniques to show that, in some cases, the eDFT Rydberg solutions appear to deliver the minimum kinetic energy because the associated density is not pure state v-representable. We thus find that eDFT plays a complementary role to constrained DFT: The former works only if the excited state density is not the ground state of some potential while the latter applies only when the density is a ground state density.

Application of a bi-modal PBR nuclear propulsion and power system to military missions

Science.gov (United States)

Venetoklis, Peter S.

1995-01-01

The rapid proliferation of arms technology and space access combined with current economic realities in the United States are creating ever greater demands for more capable space-based military assets. The paper illustrates that bi-modal nuclear propulsion and power based on the Particle Bed Reactor (PBR) is a high-leverage tehcnology that can maximize utility while minimizing cost. Mission benefits offered by the bi-modal PBR, including enhanced maneuverability, lifetime, survivability, payload power, and operational flexibility, are discussed. The ability to deliver desired payloads on smaller boosters is also illustrated. System descriptions and parameters for 10 kWe and 100 kWe power output levels are summarized. It is demonstrated via design exercise that bi-modal PBR dramtically enhances performance of a military satellite in geosynchronous orbit, increasing payload mass, payload power, and maneuverability.

Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

International Nuclear Information System (INIS)

Werner, F.; Hofmann, M.; Them, K.; Knopp, T.; Jung, C.; Salamon, J.; Kaul, M. G.; Mummert, T.; Adam, G.; Ittrich, H.; Werner, R.; Säring, D.; Weber, O. M.

2016-01-01

Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors’ study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP–MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and used in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MR–MP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.

Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

Energy Technology Data Exchange (ETDEWEB)

Werner, F., E-mail: f.werner@uke.de; Hofmann, M.; Them, K.; Knopp, T. [Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany and Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg 21073 (Germany); Jung, C.; Salamon, J.; Kaul, M. G.; Mummert, T.; Adam, G.; Ittrich, H. [Department of Diagnostic and Interventional Radiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246 (Germany); Werner, R.; Säring, D. [Institute for Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg 20246 (Germany); Weber, O. M. [Philips Medical Systems DMC GmbH, Hamburg 22335 (Germany)

2016-06-15

Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors’ study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP–MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and used in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MR–MP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.

Ignition Probability

Data.gov (United States)

Earth Data Analysis Center, University of New Mexico — USFS, State Forestry, BLM, and DOI fire occurrence point locations from 1987 to 2008 were combined and converted into a fire occurrence probability or density grid...

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.

2012-03-11

The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).

Covariant Density Functionals: time-odd channel investigated

International Nuclear Information System (INIS)

Afanasjev, A. V.; Abusara, H.

2009-01-01

The description of exotic nuclear systems and phenomena requires a detailed understanding of all channels of density functional theories. The role of time-odd mean fields, their evidence in experiment, and an accurate description of these fields are subject of current interest. Recent studies advanced the understanding of these fields in energy density functional theories based on the Skyrme force [1,2]. Time-odd mean fields are related to nuclear magnetism in covariant density functional (CDF) theories [3]. They arise from space-like components of vector mesons and Lorentz invariance requires that their coupling strengths are identical to that of time-like components. There were only few limited efforts to understand the role of time-odd mean fields in covariant density functional theory [4,5]. For example, the microscopic role of nuclear magnetism and its impact on rotational properties of nuclei has been studied in Ref. [5]. It is known that time-odd mean fields modify the angular momentum content of the single-particle orbitals and thus the moments of inertia, effective alignments, alignment gains at the band crossings and other physical observables. We aim on more detailed and systematic understanding of the role of time-odd mean fields in covariant density functional theory. This investigation covers both rotating and non-rotating systems. It is shown that contrary to the Skyrme energy density functionals time-odd mean fields of CDF theory always provide additional binding in the systems with broken time-reversal symmetry (rotating nuclei, odd mass nuclei). This additional binding increases with spin and has its maximum exactly at the terminating state [6], where it can reach several MeV. The impact of time-odd mean fields on the properties of rotating systems has been studied in a systematic way (as a function of particle number and deformation) across the nuclear chart [7]. In addition, this contribution extends these studies to non-rotating systems such as

Density functional theory of the electrical double layer: the RFD functional

International Nuclear Information System (INIS)

Gillespie, Dirk; Valisko, Monika; Boda, Dezso

2005-01-01

Density functional theory (DFT) of electrolytes is applied to the electrical double layer under a wide range of conditions. The ions are charged, hard spheres of different size and valence, and the wall creating the double layer is uncharged, weakly charged, and strongly charged. Under all conditions, the density and electrostatic potential profiles calculated using the recently proposed RFD electrostatic functional (Gillespie et al 2002 J. Phys.: Condens. Matter 14 12129; 2003 Phys. Rev. E 68 031503) compare well to Monte Carlo simulations. When the wall is strongly charged, the RFD functional results agree with the results of a simpler perturbative electrostatic DFT, but the two functionals' results qualitatively disagree when the wall is uncharged or weakly charged. The RFD functional reproduces these phenomena of weakly charged double layers. It also reproduces bulk thermodynamic quantities calculated from pair correlation functions

Exact capture probability analysis of GSC receivers over i.n.d. Rayleigh fading channels

KAUST Repository

Nam, Sungsik; Yang, Hongchuan; Alouini, Mohamed-Slim; Kim, Dongin

2013-01-01

variates. With this motivation in mind, we first provide in this paper some new order statistics results in terms of both moment generating function (MGF) and probability density function (PDF) expressions under an i.n.d. assumption and then derive a new

Orthogonal bases of radial functions for charge density refinements

International Nuclear Information System (INIS)

Restori, R.

1990-01-01

Charge density determination from X-ray measurements necessitates the evaluation of the Fourier-Bessel transforms of the radial functions used to expand the charge density. Analytical expressions are given here for four sets of orthogonal functions which can substitute for the 'traditional exponential functions' set in least-squares refinements. (orig.)

Sharp Bounds by Probability-Generating Functions and Variable Drift

DEFF Research Database (Denmark)

Doerr, Benjamin; Fouz, Mahmoud; Witt, Carsten

2011-01-01

We introduce to the runtime analysis of evolutionary algorithms two powerful techniques: probability-generating functions and variable drift analysis. They are shown to provide a clean framework for proving sharp upper and lower bounds. As an application, we improve the results by Doerr et al....... (GECCO 2010) in several respects. First, the upper bound on the expected running time of the most successful quasirandom evolutionary algorithm for the OneMax function is improved from 1.28nln n to 0.982nlnn, which breaks the barrier of nln n posed by coupon-collector processes. Compared to the classical...

Time-dependent density-functional tight-binding method with the third-order expansion of electron density.

Science.gov (United States)

Nishimoto, Yoshio

2015-09-07

We develop a formalism for the calculation of excitation energies and excited state gradients for the self-consistent-charge density-functional tight-binding method with the third-order contributions of a Taylor series of the density functional theory energy with respect to the fluctuation of electron density (time-dependent density-functional tight-binding (TD-DFTB3)). The formulation of the excitation energy is based on the existing time-dependent density functional theory and the older TD-DFTB2 formulae. The analytical gradient is computed by solving Z-vector equations, and it requires one to calculate the third-order derivative of the total energy with respect to density matrix elements due to the inclusion of the third-order contributions. The comparison of adiabatic excitation energies for selected small and medium-size molecules using the TD-DFTB2 and TD-DFTB3 methods shows that the inclusion of the third-order contributions does not affect excitation energies significantly. A different set of parameters, which are optimized for DFTB3, slightly improves the prediction of adiabatic excitation energies statistically. The application of TD-DFTB for the prediction of absorption and fluorescence energies of cresyl violet demonstrates that TD-DFTB3 reproduced the experimental fluorescence energy quite well.

Bimodality and the formation of Saturn's ring particles

International Nuclear Information System (INIS)

Gehrels, T.

1980-01-01

The F ring appears to have an outer and an inner rim, with only the latter observed by the imaging photopolarimeter (IPP) on the Pioneer Saturn spacecraft. The inside of the G ring, near 2.49 R/sub S/, may also be seen in the optical data. 1979S1 is red as well as dark. The light scattered through the B ring is noticeably red. The A ring has a dense outer rim. The Cassini Division and the French Division (Dollfus Division) have a dark gap near their centers. The C ring becomes weaker toward the center such that outer, middle, and inner C rings can be recognized. The Pioneer and earth-based observations are explained with a model for the B and A rings to some extent of a bimodal size distributions of particles; the larger ones may be original accretions, while small debris diffuses inward through the Cassini Division and the C ring. During the formation of the ring system, differential gravitation allowed only silicaceous grains of higher density (rho> or approx. =3 g cm -3 ) to coagulate. These serve as interstitial cores for snowy carbonaceous grains, between the times of accretion from interplanetary cometary grains and liberation by collision followed by diffusion inward to Saturn and final evaporation

Near-Infrared Squaraine Dye Encapsulated Micelles for in Vivo Fluorescence and Photoacoustic Bimodal Imaging.

Science.gov (United States)

Sreejith, Sivaramapanicker; Joseph, James; Lin, Manjing; Menon, Nishanth Venugopal; Borah, Parijat; Ng, Hao Jun; Loong, Yun Xian; Kang, Yuejun; Yu, Sidney Wing-Kwong; Zhao, Yanli

2015-06-23

Combined near-infrared (NIR) fluorescence and photoacoustic imaging techniques present promising capabilities for noninvasive visualization of biological structures. Development of bimodal noninvasive optical imaging approaches by combining NIR fluorescence and photoacoustic tomography demands suitable NIR-active exogenous contrast agents. If the aggregation and photobleaching are prevented, squaraine dyes are ideal candidates for fluorescence and photoacoustic imaging. Herein, we report rational selection, preparation, and micelle encapsulation of an NIR-absorbing squaraine dye (D1) for in vivo fluorescence and photoacoustic bimodal imaging. D1 was encapsulated inside micelles constructed from a biocompatible nonionic surfactant (Pluoronic F-127) to obtain D1-encapsulated micelles (D1(micelle)) in aqueous conditions. The micelle encapsulation retains both the photophysical features and chemical stability of D1. D1(micelle) exhibits high photostability and low cytotoxicity in biological conditions. Unique properties of D1(micelle) in the NIR window of 800-900 nm enable the development of a squaraine-based exogenous contrast agent for fluorescence and photoacoustic bimodal imaging above 820 nm. In vivo imaging using D1(micelle), as demonstrated by fluorescence and photoacoustic tomography experiments in live mice, shows contrast-enhanced deep tissue imaging capability. The usage of D1(micelle) proven by preclinical experiments in rodents reveals its excellent applicability for NIR fluorescence and photoacoustic bimodal imaging.

Energy vs. density on paths toward exact density functionals

DEFF Research Database (Denmark)

Kepp, Kasper Planeta

2018-01-01

Recently, the progression toward more exact density functional theory has been questioned, implying a need for more formal ways to systematically measure progress, i.e. a “path”. Here I use the Hohenberg-Kohn theorems and the definition of normality by Burke et al. to define a path toward exactness...

Variable kernel density estimation in high-dimensional feature spaces

CSIR Research Space (South Africa)

Van der Walt, Christiaan M

2017-02-01

Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...

Elements of a function analytic approach to probability.

Energy Technology Data Exchange (ETDEWEB)

Ghanem, Roger Georges (University of Southern California, Los Angeles, CA); Red-Horse, John Robert

2008-02-01

We first provide a detailed motivation for using probability theory as a mathematical context in which to analyze engineering and scientific systems that possess uncertainties. We then present introductory notes on the function analytic approach to probabilistic analysis, emphasizing the connections to various classical deterministic mathematical analysis elements. Lastly, we describe how to use the approach as a means to augment deterministic analysis methods in a particular Hilbert space context, and thus enable a rigorous framework for commingling deterministic and probabilistic analysis tools in an application setting.

Multicomponent density-functional theory for time-dependent systems

NARCIS (Netherlands)

Butriy, O.; Ebadi, H.; de Boeij, P. L.; van Leeuwen, R.; Gross, E. K. U.

2007-01-01

We derive the basic formalism of density functional theory for time-dependent electron-nuclear systems. The basic variables of this theory are the electron density in body-fixed frame coordinates and the diagonal of the nuclear N-body density matrix. The body-fixed frame transformation is carried

The Development of Bimodal Bilingualism: Implications for Linguistic Theory.

Science.gov (United States)

Lillo-Martin, Diane; de Quadros, Ronice Müller; Pichler, Deborah Chen

2016-01-01

A wide range of linguistic phenomena contribute to our understanding of the architecture of the human linguistic system. In this paper we present a proposal dubbed Language Synthesis to capture bilingual phenomena including code-switching and 'transfer' as automatic consequences of the addition of a second language, using basic concepts of Minimalism and Distributed Morphology. Bimodal bilinguals, who use a sign language and a spoken language, provide a new type of evidence regarding possible bilingual phenomena, namely code-blending, the simultaneous production of (aspects of) a message in both speech and sign. We argue that code-blending also follows naturally once a second articulatory interface is added to the model. Several different types of code-blending are discussed in connection to the predictions of the Synthesis model. Our primary data come from children developing as bimodal bilinguals, but our proposal is intended to capture a wide range of bilingual effects across any language pair.

Improved Density Functional Tight Binding Potentials for Metalloid Aluminum Clusters

Science.gov (United States)

2016-06-01

unlimited IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS by Joon H. Kim June 2016 Thesis Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS 5. FUNDING...repulsive potentials for use in density-functional tight binding (DFTB) simulations of low-valence aluminum metalloid clusters . These systems are under

Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

Directory of Open Access Journals (Sweden)

Osmar Abílio de Carvalho Júnior

2014-04-01

Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

A density functional approach to ferrogels

Science.gov (United States)

Cremer, P.; Heinen, M.; Menzel, A. M.; Löwen, H.

2017-07-01

Ferrogels consist of magnetic colloidal particles embedded in an elastic polymer matrix. As a consequence, their structural and rheological properties are governed by a competition between magnetic particle-particle interactions and mechanical matrix elasticity. Typically, the particles are permanently fixed within the matrix, which makes them distinguishable by their positions. Over time, particle neighbors do not change due to the fixation by the matrix. Here we present a classical density functional approach for such ferrogels. We map the elastic matrix-induced interactions between neighboring colloidal particles distinguishable by their positions onto effective pairwise interactions between indistinguishable particles similar to a ‘pairwise pseudopotential’. Using Monte-Carlo computer simulations, we demonstrate for one-dimensional dipole-spring models of ferrogels that this mapping is justified. We then use the pseudopotential as an input into classical density functional theory of inhomogeneous fluids and predict the bulk elastic modulus of the ferrogel under various conditions. In addition, we propose the use of an ‘external pseudopotential’ when one switches from the viewpoint of a one-dimensional dipole-spring object to a one-dimensional chain embedded in an infinitely extended bulk matrix. Our mapping approach paves the way to describe various inhomogeneous situations of ferrogels using classical density functional concepts of inhomogeneous fluids.

Recent developments in LIBXC - A comprehensive library of functionals for density functional theory

Science.gov (United States)

Lehtola, Susi; Steigemann, Conrad; Oliveira, Micael J. T.; Marques, Miguel A. L.

2018-01-01

LIBXC is a library of exchange-correlation functionals for density-functional theory. We are concerned with semi-local functionals (or the semi-local part of hybrid functionals), namely local-density approximations, generalized-gradient approximations, and meta-generalized-gradient approximations. Currently we include around 400 functionals for the exchange, correlation, and the kinetic energy, spanning more than 50 years of research. Moreover, LIBXC is by now used by more than 20 codes, not only from the atomic, molecular, and solid-state physics, but also from the quantum chemistry communities.

Functional development in density functional theory for superconductors

Energy Technology Data Exchange (ETDEWEB)

Sanna, Antonio; Gross, E.K.U.; Essenberger, Frank [Max Planck Institute of Microstructure Physics, Halle (Saale) (Germany)

2015-07-01

Density functional theory for superconductors (SCDFT) is a fully parameter-free approach to superconductivity that allows for accurate predictions of critical temperature and properties of superconductors. We report on the most recent extensions of the method, in particular the development of new functionals to: (1) incorporate in a correct fashion Migdal's theorem; (2) compute the excitation spectrum; (3) include spin-fluctuation mediated pairing Applications and predictions are shown for a set of materials, including conventional and unconventional superconductors.

Equation satisfied by electron-electron mutual Coulomb repulsion energy density functional

OpenAIRE

Joubert, Daniel P.

2011-01-01

The electron-electron mutual Coulomb repulsion energy density functional satisfies an equation that links functionals and functional derivatives at N-electron and (N-1)-electron densities for densities determined from the same adiabatic scaled external potential for the N-electron system.

Density-functional theory in one dimension for contact-interacting fermions

International Nuclear Information System (INIS)

Magyar, R.J.; Burke, K.

2004-01-01

A density-functional theory is developed for fermions in one dimension, interacting via a δ function. Such systems provide a natural testing ground for questions of principle, as the local-density approximation should be highly accurate since for this interaction type the exchange contribution to the local-density approximation is intrinsically self-interaction-free. The exact-exchange contribution to the total energy is a local functional of the density. A local-density approximation for correlation is obtained using perturbation theory and Bethe ansatz results for the one-dimensional contact-interacting uniform Fermi gas. The ground-state energies are calculated for two finite systems, the analogs of helium and of Hooke's atom. The local-density approximation is shown to be excellent as expected

Self-contained filtered density function

Science.gov (United States)

Nouri, A. G.; Nik, M. B.; Givi, P.; Livescu, D.; Pope, S. B.

2017-09-01

The filtered density function (FDF) closure is extended to a "self-contained" format to include the subgrid-scale (SGS) statistics of all of the hydro-thermo-chemical variables in turbulent flows. These are the thermodynamic pressure, the specific internal energy, the velocity vector, and the composition field. In this format, the model is comprehensive and facilitates large-eddy simulation (LES) of flows at both low and high compressibility levels. A transport equation is developed for the joint pressure-energy-velocity-composition filtered mass density function (PEVC-FMDF). In this equation, the effect of convection appears in closed form. The coupling of the hydrodynamics and thermochemistry is modeled via a set of stochastic differential equation for each of the transport variables. This yields a self-contained SGS closure. For demonstration, LES is conducted of a turbulent shear flow with transport of a passive scalar. The consistency of the PEVC-FMDF formulation is established, and its overall predictive capability is appraised via comparison with direct numerical simulation (DNS) data.

THE BIMODAL STRUCTURE OF THE SOLAR CYCLE

Energy Technology Data Exchange (ETDEWEB)

Du, Z. L., E-mail: zldu@nao.cas.cn [Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China)

2015-05-01

Some properties of the 11 yr solar cycle can be explained by the current solar dynamo models. However, some other features remain not well understood such as the asymmetry of the cycle, the double-peaked structure, and the “Waldmeier effect” that a stronger cycle tends to have less rise time and a shorter cycle length. We speculate that the solar cycle is governed by a bi-dynamo model forming two stochastic processes depicted by a bimodal Gaussian function with a time gap of about 2 yr, from which the above features can be reasonably explained. The first one describes the main properties of the cycle dominated by the current solar dynamo models, and the second one occurs either in the rising phase as a short weak explosive perturbation or in the declining phase as a long stochastic perturbation. The above function is the best one selected from several in terms of the Akaike information criterion. Through analyzing different distributions, one might speculate about the dominant physical process inside the convection zone. The secondary (main) process is found to be closely associated with complicated (simple) active ranges. In effect, the bi-dynamo model is a reduced form of a multi-dynamo model, which could occur from the base of the convection zone through its envelope and from low to high heliographic latitude, reflecting the active belts in the convection zone. These results are insensitive to the hemispheric asymmetry, smoothing filters, and distribution functions selected and are expected to be helpful in understanding the formation of solar and stellar cycles.

Microscopically based energy density functionals for nuclei using the density matrix expansion. II. Full optimization and validation

Science.gov (United States)

Navarro Pérez, R.; Schunck, N.; Dyhdalo, A.; Furnstahl, R. J.; Bogner, S. K.

2018-05-01

Background: Energy density functional methods provide a generic framework to compute properties of atomic nuclei starting from models of nuclear potentials and the rules of quantum mechanics. Until now, the overwhelming majority of functionals have been constructed either from empirical nuclear potentials such as the Skyrme or Gogny forces, or from systematic gradient-like expansions in the spirit of the density functional theory for atoms. Purpose: We seek to obtain a usable form of the nuclear energy density functional that is rooted in the modern theory of nuclear forces. We thus consider a functional obtained from the density matrix expansion of local nuclear potentials from chiral effective field theory. We propose a parametrization of this functional carefully calibrated and validated on selected ground-state properties that is suitable for large-scale calculations of nuclear properties. Methods: Our energy functional comprises two main components. The first component is a non-local functional of the density and corresponds to the direct part (Hartree term) of the expectation value of local chiral potentials on a Slater determinant. Contributions to the mean field and the energy of this term are computed by expanding the spatial, finite-range components of the chiral potential onto Gaussian functions. The second component is a local functional of the density and is obtained by applying the density matrix expansion to the exchange part (Fock term) of the expectation value of the local chiral potential. We apply the UNEDF2 optimization protocol to determine the coupling constants of this energy functional. Results: We obtain a set of microscopically constrained functionals for local chiral potentials from leading order up to next-to-next-to-leading order with and without three-body forces and contributions from Δ excitations. These functionals are validated on the calculation of nuclear and neutron matter, nuclear mass tables, single-particle shell structure

Exact probability distribution function for the volatility of cumulative production

Science.gov (United States)

Zadourian, Rubina; Klümper, Andreas

2018-04-01

In this paper we study the volatility and its probability distribution function for the cumulative production based on the experience curve hypothesis. This work presents a generalization of the study of volatility in Lafond et al. (2017), which addressed the effects of normally distributed noise in the production process. Due to its wide applicability in industrial and technological activities we present here the mathematical foundation for an arbitrary distribution function of the process, which we expect will pave the future research on forecasting of the production process.

Probabilities for gravitational lensing by point masses in a locally inhomogeneous universe

International Nuclear Information System (INIS)

Isaacson, J.A.; Canizares, C.R.

1989-01-01

Probability functions for gravitational lensing by point masses that incorporate Poisson statistics and flux conservation are formulated in the Dyer-Roeder construction. Optical depths to lensing for distant sources are calculated using both the method of Press and Gunn (1973) which counts lenses in an otherwise empty cone, and the method of Ehlers and Schneider (1986) which projects lensing cross sections onto the source sphere. These are then used as parameters of the probability density for lensing in the case of a critical (q0 = 1/2) Friedmann universe. A comparison of the probability functions indicates that the effects of angle-averaging can be well approximated by adjusting the average magnification along a random line of sight so as to conserve flux. 17 references

Compact baby universe model in ten dimension and probability function of quantum gravity

International Nuclear Information System (INIS)

Yan Jun; Hu Shike

1991-01-01

The quantum probability functions are calculated for ten-dimensional compact baby universe model. The authors find that the probability for the Yang-Mills baby universe to undergo a spontaneous compactification down to a four-dimensional spacetime is greater than that to remain in the original homogeneous multidimensional state. Some questions about large-wormhole catastrophe are also discussed

Does bimodal stimulus presentation increase ERP components usable in BCIs?

NARCIS (Netherlands)

Thurlings, M.E.; Brouwer, A.M.; Erp, J.B.F. van; Blankertz, B.; Werkhoven, P.J.

2012-01-01

Event-related potential (ERP)-based brain–computer interfaces (BCIs) employ differences in brain responses to attended and ignored stimuli. Typically, visual stimuli are used. Tactile stimuli have recently been suggested as a gaze-independent alternative. Bimodal stimuli could evoke additional brain

Design and simulation of stratified probability digital receiver with application to the multipath communication

Science.gov (United States)

Deal, J. H.

1975-01-01

One approach to the problem of simplifying complex nonlinear filtering algorithms is through using stratified probability approximations where the continuous probability density functions of certain random variables are represented by discrete mass approximations. This technique is developed in this paper and used to simplify the filtering algorithms developed for the optimum receiver for signals corrupted by both additive and multiplicative noise.

Graphene on metals: A van der Waals density functional study

DEFF Research Database (Denmark)

Vanin, Marco; Mortensen, Jens Jørgen; Kelkkanen, Kari André

2010-01-01

We use density functional theory (DFT) with a recently developed van der Waals density functional (vdW-DF) to study the adsorption of graphene on Co, Ni, Pd, Ag, Au, Cu, Pt, and Al(111) surfaces. In contrast to the local-density approximation (LDA) which predicts relatively strong binding for Ni...

Stellar Rotation with Kepler and Gaia: Evidence for a Bimodal Star Formation History

Science.gov (United States)

Davenport, James

2018-01-01

Kepler stars with rotation periods measured via starspot modulations in their light curves have been matched against the astrometric data from Gaia Data Release 1. A total of 1,299 bright rotating stars were recovered, most with temperatures hotter than 5000 K. From these, 894 were selected as being near the main sequence. These main sequence stars show a bimodality in their rotation period distribution, centered around a ~600 Myr rotation-isochrone. This feature matches the bimodal period distribution found in cooler stars with Kepler, but was previously undetected for solar-type stars due to sample contamination by subgiant and binary stars. A tenuous connection between the rotation period and total proper motion is found, suggesting the period bimodality is due to the age distribution of stars within 300pc of the Sun, rather than a phase of rapid angular momentum loss. I will discuss how the combination of Kepler/K2/TESS with Gaia will enable us to map the star formation history of our galactic neighborhood.

Bayesian error estimation in density-functional theory

DEFF Research Database (Denmark)

Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund

2005-01-01

We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...

Nuclear energy density functional from chiral pion-nucleon dynamics revisited

Science.gov (United States)

Kaiser, N.; Weise, W.

2010-05-01

We use a recently improved density-matrix expansion to calculate the nuclear energy density functional in the framework of in-medium chiral perturbation theory. Our calculation treats systematically the effects from 1 π-exchange, iterated 1 π-exchange, and irreducible 2 π-exchange with intermediate Δ-isobar excitations, including Pauli-blocking corrections up to three-loop order. We find that the effective nucleon mass M(ρ) entering the energy density functional is identical to the one of Fermi-liquid theory when employing the improved density-matrix expansion. The strength F(ρ) of the ( surface-term as provided by the pion-exchange dynamics is in good agreement with that of phenomenological Skyrme forces in the density region ρ/2short-range spin-orbit interaction. The strength function F(ρ) multiplying the square of the spin-orbit density comes out much larger than in phenomenological Skyrme forces and it has a pronounced density dependence.

The role of continuous low-frequency harmonicity cues for interrupted speech perception in bimodal hearing.

Science.gov (United States)

Oh, Soo Hee; Donaldson, Gail S; Kong, Ying-Yee

2016-04-01

Low-frequency acoustic cues have been shown to enhance speech perception by cochlear-implant users, particularly when target speech occurs in a competing background. The present study examined the extent to which a continuous representation of low-frequency harmonicity cues contributes to bimodal benefit in simulated bimodal listeners. Experiment 1 examined the benefit of restoring a continuous temporal envelope to the low-frequency ear while the vocoder ear received a temporally interrupted stimulus. Experiment 2 examined the effect of providing continuous harmonicity cues in the low-frequency ear as compared to restoring a continuous temporal envelope in the vocoder ear. Findings indicate that bimodal benefit for temporally interrupted speech increases when continuity is restored to either or both ears. The primary benefit appears to stem from the continuous temporal envelope in the low-frequency region providing additional phonetic cues related to manner and F1 frequency; a secondary contribution is provided by low-frequency harmonicity cues when a continuous representation of the temporal envelope is present in the low-frequency, or both ears. The continuous temporal envelope and harmonicity cues of low-frequency speech are thought to support bimodal benefit by facilitating identification of word and syllable boundaries, and by restoring partial phonetic cues that occur during gaps in the temporally interrupted stimulus.

The heat current density correlation function: sum rules and thermal conductivity

International Nuclear Information System (INIS)

Singh, Shaminder; Tankeshwar, K; Pathak, K N; Ranganathan, S

2006-01-01

Expressions for the second and fourth sum rules of the heat current density correlation function have been derived in an appropriate ensemble. The thermal conductivity of Lennard-Jones fluids has been calculated using these sum rules for the heat current density correlation function and the Gaussian form of the memory function. It is found that the results obtained for the thermal conductivity are in good agreement with the molecular dynamics simulation results over a wide range of densities and temperatures. Earlier results obtained using the energy current density correlation function are also discussed

The heat current density correlation function: sum rules and thermal conductivity

Energy Technology Data Exchange (ETDEWEB)

Singh, Shaminder [Department of Physics, Panjab University, Chandigarh-160 014 (India); Tankeshwar, K [Department of Physics, Panjab University, Chandigarh-160 014 (India); Pathak, K N [Department of Physics, Panjab University, Chandigarh-160 014 (India); Ranganathan, S [Department of Physics, Royal Military College, Kingston, ON, K7K 7B4 (Canada)

2006-02-01

Expressions for the second and fourth sum rules of the heat current density correlation function have been derived in an appropriate ensemble. The thermal conductivity of Lennard-Jones fluids has been calculated using these sum rules for the heat current density correlation function and the Gaussian form of the memory function. It is found that the results obtained for the thermal conductivity are in good agreement with the molecular dynamics simulation results over a wide range of densities and temperatures. Earlier results obtained using the energy current density correlation function are also discussed.

A bimodal power and propulsion system based on cermet fuel and heat pipe energy transport

International Nuclear Information System (INIS)

Polansky, G.F.; Gunther, N.A.; Rochow, R.F.; Bixler, C.H.

1995-01-01

Bimodal space reactor systems provide both thermal propulsion for the spacecraft orbital transfer and electrical power to the spacecraft bus once it is on station. These systems have the potential to increase both the available payload in high energy orbits and the available power to that payload. These increased mass and power capabilities can be used to either reduce mission cost by permitting the use of smaller launch vehicles or to provide increased mission performance from the current launch vehicle. A major barrier to the deployment of these bimodal systems has been the cost associated with their development. This paper describes a bimodal reactor system with performance potential to permit more than 70% of the instrumented payload of the Titan IV/Centaur to be launched from the Atlas IIAS. The development cost is minimized by basing the design on existing component technologies

A classical density functional theory of ionic liquids.

Science.gov (United States)

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

2011-04-28

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

Propensity, Probability, and Quantum Theory

Science.gov (United States)

Ballentine, Leslie E.

2016-08-01

Quantum mechanics and probability theory share one peculiarity. Both have well established mathematical formalisms, yet both are subject to controversy about the meaning and interpretation of their basic concepts. Since probability plays a fundamental role in QM, the conceptual problems of one theory can affect the other. We first classify the interpretations of probability into three major classes: (a) inferential probability, (b) ensemble probability, and (c) propensity. Class (a) is the basis of inductive logic; (b) deals with the frequencies of events in repeatable experiments; (c) describes a form of causality that is weaker than determinism. An important, but neglected, paper by P. Humphreys demonstrated that propensity must differ mathematically, as well as conceptually, from probability, but he did not develop a theory of propensity. Such a theory is developed in this paper. Propensity theory shares many, but not all, of the axioms of probability theory. As a consequence, propensity supports the Law of Large Numbers from probability theory, but does not support Bayes theorem. Although there are particular problems within QM to which any of the classes of probability may be applied, it is argued that the intrinsic quantum probabilities (calculated from a state vector or density matrix) are most naturally interpreted as quantum propensities. This does not alter the familiar statistical interpretation of QM. But the interpretation of quantum states as representing knowledge is untenable. Examples show that a density matrix fails to represent knowledge.

Emotional Intensity Modulates the Integration of Bimodal Angry Expressions: ERP Evidence

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Zhihui Pan

2017-06-01

Full Text Available Integration of information from face and voice plays a central role in social interactions. The present study investigated the modulation of emotional intensity on the integration of facial-vocal emotional cues by recording EEG for participants while they were performing emotion identification task on facial, vocal, and bimodal angry expressions varying in emotional intensity. Behavioral results showed the rates of anger and reaction speed increased as emotional intensity across modalities. Critically, the P2 amplitudes were larger for bimodal expressions than for the sum of facial and vocal expressions for low emotional intensity stimuli, but not for middle and high emotional intensity stimuli. These findings suggested that emotional intensity modulates the integration of facial-vocal angry expressions, following the principle of Inverse Effectiveness (IE in multimodal sensory integration.

Self-contained filtered density function

International Nuclear Information System (INIS)

Nouri, Arash G.; Pope, Stephen B.

2017-01-01

The filtered density function (FDF) closure is extended to a “self-contained” format to include the subgrid-scale (SGS) statistics of all of the hydro-thermo-chemical variables in turbulent flows. These are the thermodynamic pressure, the specific internal energy, the velocity vector, and the composition field. In this format, the model is comprehensive and facilitates large-eddy simulation (LES) of flows at both low and high compressibility levels. A transport equation is developed for the joint pressure-energy-velocity-composition filtered mass density function (PEVC-FMDF). In this equation, the effect of convection appears in closed form. The coupling of the hydrodynamics and thermochemistry is modeled via a set of stochastic differential equation for each of the transport variables. This yields a self-contained SGS closure. We demonstrated how LES is conducted of a turbulent shear flow with transport of a passive scalar. Finally, the consistency of the PEVC-FMDF formulation is established, and its overall predictive capability is appraised via comparison with direct numerical simulation (DNS) data.

Matching Automatic Gain Control Across Devices in Bimodal Cochlear Implant Users.

Science.gov (United States)

Veugen, Lidwien C E; Chalupper, Josef; Snik, Ad F M; Opstal, A John van; Mens, Lucas H M

2016-01-01

The purpose of this study was to improve bimodal benefit in listeners using a cochlear implant (CI) and a hearing aid (HA) in contralateral ears, by matching the time constants and the number of compression channels of the automatic gain control (AGC) of the HA to the CI. Equivalent AGC was hypothesized to support a balanced loudness for dynamically changing signals like speech and improve bimodal benefit for speech understanding in quiet and with noise presented from the side(s) at 90 degree. Fifteen subjects participated in the study, all using the same Advanced Bionics Harmony CI processor and HA (Phonak Naida S IX UP). In a 3-visit crossover design with 4 weeks between sessions, performance was measured using a HA with a standard AGC (syllabic multichannel compression with 1 ms attack time and 50 ms release time) or an AGC that was adjusted to match that of the CI processor (dual AGC broadband compression, 3 and 240 msec attack time, 80 and 1500 msec release time). In all devices, the AGC was activated above the threshold of 63 dB SPL. The authors balanced loudness across the devices for soft and loud input sounds in 3 frequency bands (0 to 548, 548 to 1000, and >1000 Hz). Speech understanding was tested in free field in quiet and in noise for three spatial speaker configurations, with target speech always presented from the front. Single-talker noise was either presented from the CI side or the HA side, or uncorrelated stationary speech-weighted noise or single-talker noise was presented from both sides. Questionnaires were administered to assess differences in perception between the two bimodal fittings. Significant bimodal benefit over the CI alone was only found for the AGC-matched HA for the speech tests with single-talker noise. Compared with the standard HA, matched AGC characteristics significantly improved speech understanding in single-talker noise by 1.9 dB when noise was presented from the HA side. AGC matching increased bimodal benefit

Multiconfiguration Pair-Density Functional Theory Is Free From Delocalization Error.

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Bao, Junwei Lucas; Wang, Ying; He, Xiao; Gagliardi, Laura; Truhlar, Donald G

2017-11-16

Delocalization error has been singled out by Yang and co-workers as the dominant error in Kohn-Sham density functional theory (KS-DFT) with conventional approximate functionals. In this Letter, by computing the vertical first ionization energy for well separated He clusters, we show that multiconfiguration pair-density functional theory (MC-PDFT) is free from delocalization error. To put MC-PDFT in perspective, we also compare it with some Kohn-Sham density functionals, including both traditional and modern functionals. Whereas large delocalization errors are almost universal in KS-DFT (the only exception being the very recent corrected functionals of Yang and co-workers), delocalization error is removed by MC-PDFT, which bodes well for its future as a step forward from KS-DFT.

Probability an introduction

CERN Document Server

Goldberg, Samuel

1960-01-01

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.

Benchmark density functional theory calculations for nanoscale conductance

DEFF Research Database (Denmark)

Strange, Mikkel; Bækgaard, Iben Sig Buur; Thygesen, Kristian Sommer

2008-01-01

We present a set of benchmark calculations for the Kohn-Sham elastic transmission function of five representative single-molecule junctions. The transmission functions are calculated using two different density functional theory methods, namely an ultrasoft pseudopotential plane-wave code...

SURFACE SYMMETRY ENERGY OF NUCLEAR ENERGY DENSITY FUNCTIONALS

Energy Technology Data Exchange (ETDEWEB)

Nikolov, N; Schunck, N; Nazarewicz, W; Bender, M; Pei, J

2010-12-20

We study the bulk deformation properties of the Skyrme nuclear energy density functionals. Following simple arguments based on the leptodermous expansion and liquid drop model, we apply the nuclear density functional theory to assess the role of the surface symmetry energy in nuclei. To this end, we validate the commonly used functional parametrizations against the data on excitation energies of superdeformed band-heads in Hg and Pb isotopes, and fission isomers in actinide nuclei. After subtracting shell effects, the results of our self-consistent calculations are consistent with macroscopic arguments and indicate that experimental data on strongly deformed configurations in neutron-rich nuclei are essential for optimizing future nuclear energy density functionals. The resulting survey provides a useful benchmark for further theoretical improvements. Unlike in nuclei close to the stability valley, whose macroscopic deformability hangs on the balance of surface and Coulomb terms, the deformability of neutron-rich nuclei strongly depends on the surface-symmetry energy; hence, its proper determination is crucial for the stability of deformed phases of the neutron-rich matter and description of fission rates for r-process nucleosynthesis.

Theoretical derivation of wind power probability distribution function and applications

International Nuclear Information System (INIS)

Altunkaynak, Abdüsselam; Erdik, Tarkan; Dabanlı, İsmail; Şen, Zekai

2012-01-01

Highlights: ► Derivation of wind power stochastic characteristics are standard deviation and the dimensionless skewness. ► The perturbation is expressions for the wind power statistics from Weibull probability distribution function (PDF). ► Comparisons with the corresponding characteristics of wind speed PDF abides by the Weibull PDF. ► The wind power abides with the Weibull-PDF. -- Abstract: The instantaneous wind power contained in the air current is directly proportional with the cube of the wind speed. In practice, there is a record of wind speeds in the form of a time series. It is, therefore, necessary to develop a formulation that takes into consideration the statistical parameters of such a time series. The purpose of this paper is to derive the general wind power formulation in terms of the statistical parameters by using the perturbation theory, which leads to a general formulation of the wind power expectation and other statistical parameter expressions such as the standard deviation and the coefficient of variation. The formulation is very general and can be applied specifically for any wind speed probability distribution function. Its application to two-parameter Weibull probability distribution of wind speeds is presented in full detail. It is concluded that provided wind speed is distributed according to a Weibull distribution, the wind power could be derived based on wind speed data. It is possible to determine wind power at any desired risk level, however, in practical studies most often 5% or 10% risk levels are preferred and the necessary simple procedure is presented for this purpose in this paper.

Kinetic-energy density functional: Atoms and shell structure

International Nuclear Information System (INIS)

Garcia-Gonzalez, P.; Alvarellos, J.E.; Chacon, E.

1996-01-01

We present a nonlocal kinetic-energy functional which includes an anisotropic average of the density through a symmetrization procedure. This functional allows a better description of the nonlocal effects of the electron system. The main consequence of the symmetrization is the appearance of a clear shell structure in the atomic density profiles, obtained after the minimization of the total energy. Although previous results with some of the nonlocal kinetic functionals have given incipient structures for heavy atoms, only our functional shows a clear shell structure for most of the atoms. The atomic total energies have a good agreement with the exact calculations. Discussion of the chemical potential and the first ionization potential in atoms is included. The functional is also extended to spin-polarized systems. copyright 1996 The American Physical Society

Design and characterization of a cough simulator.

Science.gov (United States)

Zhang, Bo; Zhu, Chao; Ji, Zhiming; Lin, Chao-Hsin